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Characterization of Sorption and Degradation of Pesticides in Carbonatic and Associated Soils from South Florida and Pue...

Permanent Link: http://ufdc.ufl.edu/UFE0021753/00001

Material Information

Title: Characterization of Sorption and Degradation of Pesticides in Carbonatic and Associated Soils from South Florida and Puerto Rico, and Oxisols from Uganda
Physical Description: 1 online resource (156 p.)
Language: english
Creator: Kasozi, Gabriel N
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: ametryn, atrazine, calcareous, carbonatic, degradation, diuron, everglades, florida, histosols, puerto, rico, sorption, south, uganda
Soil and Water Science -- Dissertations, Academic -- UF
Genre: Soil and Water Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Sorption and degradation are major processes that influence the fate of pesticides in the environment. This study was designed to characterize these processes in carbonatic, associated non-carbonatic soils from South Florida and Puerto Rico and Oxisols from Uganda. Spodosols from Alachua County were collected for comparison. Carbonatic soils are characterized by a high water table, and underlain by porous limestone bedrock. These soils support 85% of Florida's vegetables and tropical fruits. The sub-tropical to tropical climates in South Florida, Puerto Rico and Uganda encourage proliferation of pests that require pesticides control. Several pesticides applied to crops grown on carbonatic soils have been reported in both surface and ground water of South Florida and Puerto Rico. Although a lot of research has been done on characterizing the sorption of organic pesticides in non-carbonatic soils, a literature search indicates lack of these data for carbonatic soils. The conversion factors from organic matter (OM) to organic carbon (OC) of 1.74, 1.48 and 1.44 obtained for carbonatic soils, Histosols and Spodosols, respectively indicate that OC content in OM differs between soils from different vegetative and hydrologic regimes. Data on atrazine, ametryn, and duiron sorption indicate that these pesticides adsorb less on carbonatic soils. The sorption coefficients for the non-carbonatic soils were about 3 times higher than of carbonatic soils. Marl carbonatic soils showed even lower sorption potential and the order was Marl < rockplowed carbonatic soils < Histosols < Oxisols < Spodosols. The data indicated a linear relationship between sorption and OC content although comparison across soils showed that organic matter quality is important in sorption. Degradation of diuron and ametryn was not different between carbonatic and non-carbonatic soils and was not influenced by sorption. In order to understand the fundamental differences in OM that may account for the anomalous behavior of carbonatic soils, 13C CP-MAS NMR technique was used. Carbonatic soils differed from the other soils in terms of aromatic carbon chemical shifts by showing low aromaticity. A strong relationship was found between aromatic C/alkyl C and Koc. This implies that the aromatic carbon controls the sorption of neutral hydrophobic organic chemicals.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Gabriel N Kasozi.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Nkedi-Kizza, Peter.
Local: Co-adviser: Li, Yuncong.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021753:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021753/00001

Material Information

Title: Characterization of Sorption and Degradation of Pesticides in Carbonatic and Associated Soils from South Florida and Puerto Rico, and Oxisols from Uganda
Physical Description: 1 online resource (156 p.)
Language: english
Creator: Kasozi, Gabriel N
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: ametryn, atrazine, calcareous, carbonatic, degradation, diuron, everglades, florida, histosols, puerto, rico, sorption, south, uganda
Soil and Water Science -- Dissertations, Academic -- UF
Genre: Soil and Water Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Sorption and degradation are major processes that influence the fate of pesticides in the environment. This study was designed to characterize these processes in carbonatic, associated non-carbonatic soils from South Florida and Puerto Rico and Oxisols from Uganda. Spodosols from Alachua County were collected for comparison. Carbonatic soils are characterized by a high water table, and underlain by porous limestone bedrock. These soils support 85% of Florida's vegetables and tropical fruits. The sub-tropical to tropical climates in South Florida, Puerto Rico and Uganda encourage proliferation of pests that require pesticides control. Several pesticides applied to crops grown on carbonatic soils have been reported in both surface and ground water of South Florida and Puerto Rico. Although a lot of research has been done on characterizing the sorption of organic pesticides in non-carbonatic soils, a literature search indicates lack of these data for carbonatic soils. The conversion factors from organic matter (OM) to organic carbon (OC) of 1.74, 1.48 and 1.44 obtained for carbonatic soils, Histosols and Spodosols, respectively indicate that OC content in OM differs between soils from different vegetative and hydrologic regimes. Data on atrazine, ametryn, and duiron sorption indicate that these pesticides adsorb less on carbonatic soils. The sorption coefficients for the non-carbonatic soils were about 3 times higher than of carbonatic soils. Marl carbonatic soils showed even lower sorption potential and the order was Marl < rockplowed carbonatic soils < Histosols < Oxisols < Spodosols. The data indicated a linear relationship between sorption and OC content although comparison across soils showed that organic matter quality is important in sorption. Degradation of diuron and ametryn was not different between carbonatic and non-carbonatic soils and was not influenced by sorption. In order to understand the fundamental differences in OM that may account for the anomalous behavior of carbonatic soils, 13C CP-MAS NMR technique was used. Carbonatic soils differed from the other soils in terms of aromatic carbon chemical shifts by showing low aromaticity. A strong relationship was found between aromatic C/alkyl C and Koc. This implies that the aromatic carbon controls the sorption of neutral hydrophobic organic chemicals.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Gabriel N Kasozi.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Nkedi-Kizza, Peter.
Local: Co-adviser: Li, Yuncong.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021753:00001


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CHARACTERIZATION OF SORPTION AND DEGRADATION OF PESTICIDES IN
CARBONATIC AND ASSOCIATED SOILS FROM SOUTH FLORIDA AND PUERTO
RICO, AND OXISOLS FROM UGANDA

























By

GABRIEL NUFFIELD KASOZI


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2007

































2007 Gabriel Nuffield Kasozi




































To my Dad, the late Lawrence Lubega ofMasajja Kyadondo, Uganda. His love, words of
wisdom and integrity will always remain a light to my path. May God rest his soul in eternal
peace.









ACKNOWLEDGMENTS

I am extremely indebted to my major advisor, Dr. Peter Nkedi-Kizza, for his unwavering

and parental support. His guidance and the expertise that he has shared with me during the

pursuit of this study are greatly appreciated. I feel so lucky to have been able to work under his

guidance. He has cultivated in me a new strength by allowing me to exercise creative thinking in

both academics and in daily life. I am also thankful to the rest of my committee (Drs. Yucong Li,

D. Powell and D. Hodell) for their significant contribution toward this research. Their ideas and

suggestion have gone a great length in enhancing my academic and research experience at the

University of Florida.

I am especially thankful to Dr. Harris for accepting to be part of my advisory committee.

He has never at one time turned me away despite his busy schedule. He has been such a

tremendous mentor and he has shared with me his experience and his contribution to this study is

greatly appreciated. He has given me "all he is got" and selflessly shared with me his enormous

experience and his thought provoking and innovative ideas have propelled me very far into

getting an insight in the world of soil science. I am grateful to Dr. Dean Rhue for his continued

assistance and to the entire faculty of the Soil and Water Science department whose support and

ideas have been essential during the course of my study. I am especially thankful to Bill Porthier

for his assistance with the stable isotope analysis. A number of professors at the University of

Florida have helped sharpen my scientific skills and I am grateful for their efforts. It has been a

great learning experience and it has positively impacted my life. I am highly indebted to Dr.

Bernard Kiremire at the Department of Chemistry Makerere University Kampala, for giving me

chance to pursue graduate school. May the Almighty God reward him abundantly. I am also

thankful to Dr. Patrick G. Hatcher at Old Dominion Univeristy for accepting to run the NMR

analysis in his laboratory.









I am thankful to my friends, Dr. D Herrera, Dr. M. Josan, Dr. E Bagu, Mr. M. Ssematengo,

Mr. T. Kayondo, Mr. S. Muyingo, Mr. A. Simbwa, Mr. K. Mukalazi, Mr. B. Kamugisha, Mr. M.

Khalid, Mr. M. Geiger, and many others; the list is long, thank you for the love and support.

Special thanks go to my family. I love you all.

I am especially thankful to my wife Allen for being a wonderful companion and being

there for me at all times in all situations. Thank you for giving me a beautiful little angel

Danielle.

Finally I thank the Almighty for seeing me through all.









TABLE OF CONTENTS

page

A CK N O W LED G M EN T S ................................................................. ........... ............. .....

L IST O F T A B L E S ..................................................................................................... . 9

LIST OF FIGURES ................................. .. .... ..... ................. 10

L IST O F A B B R E V IA T IO N ............................ .................................................. ......................13

L IS T O F T E R M S ......... ....................... ...................................................................14

ABSTRAC T ................................................... ............... 16

CHAPTER

1 INTRODUCTION ............... ..................................................... ..... 18

2 L ITE R A TU R E R E V IE W ........................................................................ .. .......................23

C arbonatic Soils F orm action .......................................................................... ....................23
Soil O organic M matter (SO M ) ...................................................................... ... .....................27
Review of the M methods ..................................... ................ ............... .. .... .... 30
Soil O rganic C arbon D eterm nation ........................................................... ..................31
Elemental Analysis (Total Organic Carbon, Total Carbon, Total Nitrogen) ..................33
U V -vis and Fluorescence Spectroscopy ................................... .................................... 33
F T -IR ................... .................................................... 3 3
Stable Isotopes Characterization (613Carbon, Carbon-Nitrogen Ratio) ........................34
Cross Polarization Magnetic Angle Spinning Nuclear Magnetic Resonance (CP-
M A S 13C -N M R ) ................ ...... ....... ...... .. .............. .................. .. ...... .. 35
Tetramethylammonium Hydroxide (TMAH) Thermochemolysis Coupled with Gas
Chromatography/ Pyrolysis GC-MS.................... .. ................. ............... 37
Fiber Optics and Spectroscopic Analysis................................... ......................... 37
K ey F in d in g s ........................................................................... .. 3 8
What is yet to be known about the Characteristics of Organic Matter..........................38
Chem icals Studied and Rationale ...................... .... ............................................... 39
A tra z in e ........................................................................3 9
D iu ro n ........................ ................... .. ......................................................................... 4 0
Ametryn ....................... ..... .... ........ ........ ...............40
Sorption and Solute Transport in a Porous Medium .................................... ....41
Interaction with Organic Carbon ............................................................ 42
S option M o d els.......................................................................4 3
T he L near Sorption M odel ....................................................................................... 43
F reundlich Isotherm M odel ....................................................................................... 44
L agm u ir S option M odel ........................................................................................... 44
Pesticide Degradation ...................................................................... ........ 45


6









Environm mental Fate of Pesticides ................................... ......... ... ....................... 46
H ypotheses.......... ..........................................................46
S tu d y O b je c tiv e s ............................................................................................................... 4 7

3 M A TER IA L S A N D M ETH O D S ........................................ .............................................50

D description of Sam pling Sites ........................................................................ .................. 50
P pesticides Studied ............................... ..................................................................52
D term nation of Soil Properties .................................................. .............................. 52
S oil pH ......................................52
Organic Carbon and Organic Matter Determination ..................................................52
Sam ple hom ogenization .............. ...................... .................... ............... 53
W alkley and Black m ethod (W B) ........................................ ........................ 53
T herm ogravim etry (T G )..................................................... ................... 54
W eight loss on ignition (W LO I) ........................................ ......................... 54
M uffle furnace ..................................................................... ......... 54
Carbon Stable Isotope Determination ......................... ............. ... .............. 55
Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance
spectroscopy ............... ............... .. ........................................ 55
Soil treatment for Cross Polarized Magic Angle Spinning 13Carbon Nuclear
M agnetic Resonance spectroscopy analysis......................................................55
Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance
spectroscopic determ nation ........................................ ........................... 56
Sorption of Pesticides on Soils ................................ ............. ...................................... 57
Pesticide D degradation ............. ...... .............. .. .......... ..... ......... .... 59

4 ORGANIC MATTER CHARACTERIZATION IN CARBONATIC AND
ASSOCIATED SOILS FROM SOUTH FLORIDA AND PUERTO RICO USING
THERM AL AND OXIDATION M ETHODS............................................. .....................68

Introduction ................... .......................................................... ................. 68
M materials and M methods ..................................... ... .. .......... ....... ...... 70
Sam ple H om ogenization ............................................ .................................. 70
Organic Carbon, Organic Matter and Carbonate Determination.........................70
Results and Discussion ...................................... .. ......... ....... ..... 71
C onclu sions.......... ..........................................................76

5 SORPTION AND DEGRADATION OF SELECTED PESTICIDES IN
CARBONATIC AND ASSOCIATED SOILS................................... ....................... 88

Introduction ................. ......................................... ............................88
M materials and M methods ..................................... .... .. ........... ....... ...... 90
A trazine A naly sis ................................................................90
A m etry n A n aly sis ...................................................................... ........ .... .... .. ..... 9 1
D iuron A analysis ................................................. 91
M odel Fitting ................................. .......................... ..... ..... ......... 91
P pesticide D degradation ........ ........................................................... ........ .... .... .... .. 92









Quality Control/Quality A assurance ....................................................... .... ........... 92
Results and Discussion ...................................... .. ......... ....... ..... 92
A traz in e S o rp tio n ....................................................................................................... 9 2
A m etry n S o rp tio n .................................................................... .......... .... .................... 9 5
A m etryn D degradation ........................ ...................... .. .... .... ......... .. .... .. 96
D iuron Sorption ......... .. ....... .............................................................................. 96
D iuron D degradation ................................................ .. .... ........ .... .... ............ 97
Vulnerability of Groundwater to HOCs Contamination ...........................................98
C onclu sions.......... ..........................................................99

6 CROSS POLARIZED MAGIC ANGLE SPINNING CARBON NUCLEAR
MAGNETIC RESONANCE AND STABLE ISOTOPE CHARACTERIZATION OF
ORGANIC MATTER IN CARBONATIC AND NON-CARBONATIC SOILS OF
SOUTH FLORIDA, PUERTO RICO AND OXISOLS FROM UGANDA ........................118

In tro d u ctio n ................... ...................1.............................8
M materials and M methods ..................................... ........... .......... .. ........ .... 119
R results and D discussion ..................................... ............ .......... .. ........ .... 119
Stable Isotope D eterm nation ................................................................. ................ ... 119
13Carbon Cross Polarized Magic Angle Spinning Nuclear Magnetic Resonance
A naly sis.................................................... 120
C onclusions.....................................................................122

7 CONCLUSIONS AND RECOMMENDATIONS.........................................................133

C o n c lu sio n s ........................................................................................................................... 1 3 3
Recommendations.................. ..... .. .. .... ..... .... ........... 134

APPENDIX

A SELECTED PESTICIDE SORPTION ISOTHERMS ................ ................................... 135

B SELECTED SOIL ORGANIC MATTER 13CARBON CROSS POLARIZED MAGIC
ANGLE SPINNING NUCLEAR MAGNETIC RESONANCE SPECTRA ........................141

L IST O F R E F E R E N C E S ..................................................................................... ..................145

B IO G R A PH IC A L SK E T C H ......................................................................... ... ..................... 156













8









LIST OF TABLES


Table page

2-1 Chemical properties of atrazine, diuron and ametryn................................................. 48

3-1 Description of the sampling sites in Florida U.S.A. and Puerto Rico .............................62

3-2 Description of the sampling sites in Uganda East Africa ................................................63

3-2 Carbon-13 cross polarized magic angle spinning nuclear magnetic resonance
chem ical shifts for soil organic m atter........................................ ........................... 64

4-1 Organic carbon (OC) and organic matter (OM) determination in carbonatic soils
using WB, TG, and WLOI methods, and carbonates. Soils sampled 0-15 cm ................77

4-2 Organic carbon (OC) and organic matter (OM) determination in Histosols from
Florida (FL) and Puerto Rico (PR) using WB, TG, and WLOI methods .........................78

4-3 Organic carbon (OC) and organic matter (OM) determination in Spodosols using
W B, TG and W LOI methods. ..... ........................... .........................................78

5-1 Soil organic carbon content, and atrazine distribution coefficients (Kd) and organic
carbon sorption coefficients (Ko) for carbonatic soils from Florida and Puerto Rico....101

5-2 Soil organic carbon content, atrazine, diuron and ametryn distribution coefficients
(Kd) and sorption coefficients (Ko) for Oxisols from Uganda and Puerto Rico ...........102

5-3 Ametryn and diuron degradation and sorption coefficients for carbonatic soils from
F lorida and Puerto R ico. ........................................................................ ....................103

5-4 Soil organic matter content, and atrazine distribution coefficients and organic carbon
sorption coefficients for H istosols from Florida ............................................................104

5-5 Soil organic matter content, and atrazine distribution coefficients and organic carbon
sorption coefficients for Spodosols from Florida. ................................... ..................... 105

5-6 Diuron half-life and GUS scores in soils from Florida, Puerto Rico and Uganda........... 106

5-7 Ametryn half life and GUS scores in soils from Florida, and Puerto Rico. ....................107

6-1 Physicochemical properties of the soils that were used for stable isotope
determ nation. Duplicate sam ples w ere analyzed..........................................................124









LIST OF FIGURES


Figure page

2-1 Classification of 13Carbon nuclear magenitic resonance spectra (Kogel-Knabner,
2002, modified from Bortiyatinski et al., 1996). .................................... .................49

3-1 Typical rock-plowed carbonatic soil from Homestead, Miami Dade County South
Florida. G ravely, w ell drained soils ...................................................... ............... 65

3-2 Algal derived secondary calcite flakes precipitation leading to formation of marl
carb o n atic so ils ....................................................................... 6 6

3-3 Set up of the degradation of pesticides in polycarbonate tubes with loose covers to
prevent excessive m oisture loss. ............................................... .............................. 67

4-1 Verification of the TG calibration using standard calcium carbonate. Line 1 is weight
loss, while line 2 is 1st temperature derivative. ................... ................... .............. 79

4-2 Confirmation for the onset decomposition temperature for calcium carbonate
preheated to 550 C for 2 h, decomposition starts at 600 C. Line 1 Figure B is
temperature profile and Line 2 is the derivative for weight loss onset............................80

4-3 TG thermograms A) For carbonatic soils, pre-heated at 110 C for 24 hour. B) For
Histosols, pre-heated at 110 C for 24 hour ........................................................... 81

4-4 TG analysis of a Histosol heated to 180 oC, cooled then heated to 1000 C. Line 1 is
the temperature profile and line 2 is the weight loss ............................... ............... .82

4-5 TG analysis of organic soil material (from a Histosol), using isothermal steps to
investigate energy dependency for weight loss versus time. Line 1 is oven
temperature and line 2 is soil sample percent weight loss ..............................................83

4-6 Correlation between TG %OM and WB %OC. A) For carbonatic soils. B) For
H istosols. C ) For Spodosols ......... ................. ......................................... ............... 84

4-7 Correlation between WLOI %OM and WB %OC for Histosols .............................. 85

4-8 Correlation between WLOI %OM and TG %OM in carbonatic soils ....................... 85

4-9 X-ray diffraction curves for Bicayne series (carbonatic soil) .........................................86

4-10 X-ray diffraction curves for a Ugandan Oxisol from Kakira Jinja.................................87

5-1 Diuron sorption isotherm of Lauderhill series (Histosol) from South Florida ..............108

5-2 Correlation of atrazine distribution coefficients (Kd) with the fraction of organic
carbon for different soil series. ........................................ .......................................... 109









5-3 Correlation of atrazine Kd with fraction of organic carbon for A) For carbonatic soils,
B) For Histosols, C) For Oxiosols and D) For Spodosols. Slopes represent average
K oc ............ ...................... ..................................................................................................1 1 0

5-4 Correlation of ametryn Kd with fraction of organic carbon. A) For carbonatic soils.
B) For Histosols. C) For Oxiosols. D) For Spodosols. .............................. .................111

5-5 Correlation of diuron Kd with fraction of organic carbon. A) For carbonatic soils. B)
For Histosols. C) For Oxiosols. D) For Spodosols .................................................. 112

5-6 Graphical representation of average Koc values for the different soil types analyzed.
Error bars indicate 95 % confidence interval..........................................................113

5-7 Degradation of diuron in Lignumvitae series from Florida Keys, South Florida ..........14

5-8 Selected degradation curves for diuron in carbonatic soils from South Florida..............115

5-9 Groundwater ubiquity score classification for diuron in different soil types ................116

5-10 Groundwater ubiquity score classification for ametryn in carbonatic soils and
S p o d o so ls. ........................................................................................................................1 1 7

6-1 Relationship between the Koc values of ametryn and corresponding 613C values for
carbonatic and non-carbonatic soils .................................................................... ....... 125

6-2 Distribution of 613C in different soil classifications. .....................................................126

6-3. 13Carbon Cross Polarized Magic Angle Spinning Nuclear Magenetic Resonance spectra
for Algae grown in our laboratory. .............................................................................127

6-4 13Carbon Cross Polarized Magic Angle Spinning Nuclear Magenetic Resonance
spectra for Biscayne a typical Marl soil from Dade County, South Florida....................127

6-5 Correlation between aromatic C/alkyl C with diuron Koc......................................128

6-6 Correlation between aromatic C/alkyl C with ametryn Koc.............. ............. .........129

6-7 Correlation between aromatic C with ametryn and diuron Koc ......................................130

6-8 Correlation between aromatic C with atrazine Koc. ..................................... ...........131

6-8 Correlation between aromatic C/alky C with atrazine Koc ...........................................132

A-i Sorption isotherm for ametryn in Biscayne from Miami Dade Florida (marl-
c arb o n atic) .......................................................... ................ 13 5

A-2 Sorption isotherm for ametryn in Lauderhill from Miami Dade, South Florida
(H isto so l) ...................................... .................................................... 13 5









A-3 Sorption isotherm for ametryn in Pomona from Aston Cary, Alachua County Florida
(S p o d o so l) ............................................................................................. 13 6

A-4 Sorption isotherm for atrazine in a Kakira soil from Jinja, Uganda (Oxisol)..................136

A-5 Sorption isotherm for ametryn in Biscayne (marl-carbonatic). .......................................137

A-6 Sorption isotherm for ametryn in Lauderhill from Miami Dade, South Florida
(H isto so l) ...................................... .................................................... 13 7

A-7 Sorption isotherm for ametryn in Pomona from Aston Cary, Alachua County Florida
(S p o d o so l) ............................................................................................. 13 8

A-8 Sorption isotherm for ametryn in a Kakira soil from Jinja, Uganda (Oxisol). ..............138

A-9 Sorption isotherm for diuron in Biscayne (marl-carbonatic)................. .....................139

A-10 Sorption isotherm for diuron in Lauderhill from Miami Dade, South Florida
(H isto so l) ...................................... .................................................... 13 9

A-11 Sorption isotherm for diuron in Pomona from Aston Cary, Alachua County Florida
(S p o d o so l) ............................................................................................. 14 0

A-12 Sorption isotherm for diuron in a Kakira soil from Jinja, Uganda (Oxisol)..................140

B-l Nuclear magnetic resonance spectra for Laboratory grown Algae and carbonatic soil
(Florida Keys) ...................................... .................................. .......... 141

B-2 Nuclear magnetic resonance spectra for carbonatic soils from Dade County, South
F lo rid a ........ ........ ..........................................................................14 2

B-3 Nuclear magnetic resonance spectra for carbonatic soils from Puerto Rico .................142

B-4 Nuclear magnetic resonance spectra for Spodosols from Alachua County Florida. .......143

B-5 Nuclear magnetic resonance spectra for Histosols from Miami Dade, Florida (L) and
M onroe County, Key W est, Florida (R). .............................................. ............... 143

B-6 Nuclear magnetic resonance spectra for Oxisols from Uganda..................................... 144









LIST OF ABBREVIATION


CEC:

CP-MAS NMR:

DOM:

FL:

FDEP:

GUS:

HOC:

NAWQA:

OC:

OM:

PR:

SOM:

SSSA:

TG:

TOC:

UG:

USDA-NRCS:


USEPA:

USGS:

UV:

WLOI:


Cation exchange capacity

Cross polarized magic angle spinning nuclear magnetic resonance

Dissolve organic matter

Florida

Florida Department of Environmental Protection

Groundwater ubiquity score

Hydrophobic organic chemical

National Water Quality Assessment

Organic carbon

Organic matter

Puerto Rico

Soil organic matter

Soil Scince Society of America

Thermogravimetry

Total organic carbon

Uganda

United States Department of Agriculture, National Resources
Conservation Service

United States Environment Protection Agency

United States Geological Services

Ultraviolet

Weight loss on ignition









LIST OF TERMS


Adsorption:


Absorption:


Bh Horizon:




Bryozoa:

Carbonatic soil:


Chemisorption:


Degradation:


The process through which a net accumulation of a substance occurs at the
common boundary of two contiguous phases (Lal and Shukla, 2004).

The process through which a net accumulation of a substance occurs
inside the solid phase.

Horizon below the A, E or O horizon formed due to obliteration of the
original rock solubilizing Fe, Al, Si and organic matter complexes and
translocating the illuvial aluminum silicate organic complexes in the
region where the seasonal water table fluctuations occur.

Tiny marine animals that build colonies with their calcareous shells.

Soil composed of more than 40 % carbonates (Calcite and/or dolomite) in
their mineralogy.

Retention of a substance on a surface through formation of chemical
bonds.

Degradation in this manuscript is operationally defined as "the extractable
disappearance of a pesticide (amount remaining) in a soil sample at time
t". This may involve biotic (biological) and abiotic (chemical)
transformation.


Distribution


Coefficient (Kd):


Flat:


Half-life:


Marl:


Organic matter:


Oxisols:


Coefficient obtained from the ratio of the equilibrium concentration of a
substance sorbed on a solid phase to the concentration of the solution.

Area characterized by a continuous surface or stretch of land that is
smooth, even, or horizontal, or nearly so, and that lacks any significant
curvature, slope, elevations, or depressions. (Jackson, 1997).

Time required for dissipation or degradation of a chemical to half its initial
concentration (Hornsby et al., 1996).

Deposit in marine or fresh water of very fine secondary calcium carbonate
as a result of chemical action of algal mats and organic detritus
(periphyton) photosynthesis.

Plant and animal residue in the soil at various stages of decomposition.

Mineral soils with an oxic horizon within 2 cm of the surface or plinthite
as a continuous phas within 30 cm of the surface and do not have a spodic
or argillic horizon above the oxic horizon.









Pesticide:



Sapric soil matrix:

Sorption:

Spodosols:


Substances or mixture there of intended for preventing, destroying,
repelling, or mitigating any pest. Also, any substance or mixture intended
for use as a plant regulator, defoliant, or desiccant (EPA, 2007).

Most highly decomposed of all organic soil material.

Sorption is a combination of the adsorption and absorption processes.

Mineral soils that have a spodic horizon or a placic horizon that over-lies
afragipan.

Sources: SSSA, 1997; Laird and Sawhney, 2002; FDEP, 1994.









Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

CHARACTERIZATION OF SORPTION AND DEGRADATION OF PESTICIDES IN
CARBONATIC AND ASSOCIATED SOILS FROM SOUTH FLORIDA AND PUERTO
RICO, AND OXISOLS FROM UGANDA

By

Gabriel Nuffield Kasozi

December 2007

Chair: Peter Nkedi-Kizza
Cochair: Yuncong Li
Major: Soil and Water Science

Sorption and degradation are major processes that influence the fate of pesticides in the

environment. This study was designed to characterize these processes in carbonatic, associated

non-carbonatic soils from South Florida and Puerto Rico and Oxisols from Uganda. Spodosols

from Alachua County were collected for comparison. Carbonatic soils are characterized by a

high water table, and underlain by porous limestone bedrock. These soils support 85 % of

Florida's vegetables and tropical fruits. The sub-tropical to tropical climates in South Florida,

Puerto Rico and Uganda encourage proliferation of pests that require pesticides control. Several

pesticides applied to crops grown on carbonatic soils have been reported in both surface and

ground water of South Florida and Puerto Rico. Although a lot of research has been done on

characterizing the sorption of organic pesticides in non-carbonatic soils, a literature search

indicates lack of these data for carbonatic soils.

The conversion factors from organic matter (OM) to organic carbon (OC) of 1.74, 1.48 and

1.44 obtained for carbonatic soils, Histosols and Spodosols, respectively indicate that OC content

in OM differs between soils from different vegetative and hydrologic regimes. Data on atrazine,

ametryn, and duiron sorption indicate that these pesticides adsorb less on carbonatic soils. The









sorption coefficients for the non-carbonatic soils were about 3 times higher than of carbonatic

soils. Marl carbonatic soils showed even lower sorption potential and the order was Marl < rock-

plowed carbonatic soils< Histosols < Oxisols < Spodosols. The data indicated a linear

relationship between sorption and OC content although comparison across soils showed that

organic matter quality is important in sorption. Degradation of diuron and ametryn was not

different between carbonatic and non-carbonatic soils and was not influenced by sorption.

In order to understand the fundamental differences in OM that may account for the

anomalous behavior of carbonatic soils, 13C CP-MAS NMR technique was used. Carbonatic soils

differed from the other soils in terms of aromatic carbon chemical shifts by showing low

aromaticity. A strong relationship was found between aromatic C/alkyl C and Koc. This implies

that the aromatic carbon controls the sorption of neutral hydrophobic organic chemicals.









CHAPTER 1
INTRODUCTION

The increasing world population and decreasing arable land due to urbanization has led to

increased strategies aimed at sustainable food production. In addition to using improved crop

varieties, irrigation techniques and mechanization, fertilizer and pesticide usage has increased

over the years. Pesticide consumption in the world is estimated to be 2.5 billion kg (Pimental,

1995) of which about 20 % is consumed by United States alone. The U.S. annual pesticide usage

increased by 42 million kg from 1992 to 1997 (Gianessi and Silver, 2000). In 1991, an annual

consumption of 600 pesticide active ingredients amounting to 0.5 billion kg was reported,

compared to 86 million kg reported in 1964 and 50 million kg in 1945 (Aspelin, 1994; Pimentel,

1995). As a result, several pesticides among those with highest use have been detected in water

monitoring programs from across the regions of the United States (Banks et al., 2005; USGS,

1999; Larson et al., 1997; Miles and Pfueffer, 1997; USEPA, 1992; Ritter et al., 1987). The

results of the U.S. National Water Quality Assessment (NAWQA) monitoring program showed

widespread detection of pesticides in both streams and ground water samples (Gilliom, 2007;

USGS, 1999). Recent studies (Zhou et al., 2003; Scott et al., 2002) reported the potential of

endosulfan, (given its high sorption coefficient (Ko)) to contaminate South Florida's surface

water via runoff. Levels of Endosulfan above the surface water quality criteria of the Florida

Department of Environment Protection (FDEP) have been reported in South Florida water canals

(Miles and Pfueffer, 1997). Atrazine has also been reported in both surface and ground water

within Miami Dade County (Miles and Pfueffer, 1997). Across the U.S., atrazine and its

metabolite deethylatrazine are the most frequently detected pesticides in the water resources

(Gillion, 2007). Between 1996 and 1997, atrazine, chlorpyrifos, chlorothanil and endosulfan

comprised the most frequently detected pesticides (at levels below EPA water criteria for fresh









water) in South Florida surface waters with occurrence of 92%, 81%, 85% and 100% of the

analyzed samples, respectively (Scott et al, 2002). Given the shallow Biscayne aquifer, the

numerous water canals and the porous nature of the calcium carbonate bedrock in South Florida,

the presence of pesticides in surface waters, poses risk to groundwater contamination since these

two water resources are interconnected. About half of the U.S. urban population relies on

groundwater supplies as source for drinking water and the proportion increases in rural areas

(National Research Council, 1986). Maintaining sustainable agricultural production, conserving

of soils, and protecting natural ecosystems, the water resources and the environment, require an

understanding of the processes that control the fate of organic pollutants in the soil and water

resources. This necessitates designing research strategies and implementation of effective

management practices aimed at controlling environmental pollution. Regulation and registration

of pesticides used, implementation of integrated pesticide management (IPM), and observance of

application rates and timing may go a long way in reducing pesticide contamination. In Texas for

instance, a reduction in detection rates was observed following a federal ban of diazinon (Banks

et al., 2005). Soils are recipients of the applied agrochemicals and as such there is a potential

danger for these pesticides to reach surface and ground water resources via non-point sources.

Sorption and degradation are major processes that determine the fate of pesticides in the

environment (Karapanagioti et al., 2001). The slow water movement and interaction of pesticides

with the soil matrix and microbial communities, allows for sorption and degradation of pesticides

(USGS, 1999) which may reduce contamination of groundwater resources. Carbonatic soils from

South Florida have been found to adsorb pesticides much less compared to the non-carbonatic

soils from within the same area (Nkedi-Kizza et al., 2006). Given the low pesticide sorption

characteristics of carbonatic soils, and the high water tables within this area, an understanding of









the interactions of pesticides in these soils is critical. Their low pesticide sorption potential

presents concerns to the shallow Biscayne aquifer and the Everglades ecosystem.

There are 510 official soil series description with carbonatic mineralogy in the United

States. Among the states with the highest occurrence of carbonatic soils is Nevada with 123,

followed by Utah (99), Texas (95), and Idaho (61) (USDA-NRCS, 1996). This study

characterized pesticide sorption of carbonatic soils from South Florida and Puerto Rico, along

with associated Histosols from South Florida, and Oxisols from Uganda for comparative

purposes. In Florida there are 12 series with carbonatic mineralogy, namely Biscayne, Chekika,

Cudjoe, Keyvaka, Keywest, Krome, Lignumvitae, Pennekamp, Pennsuco, Perrine, Saddlebunch,

and Sumter. Five of these soils series namely Biscayne, Chekika, Krome, Pennsuco, and Perrine

are found in Miami Dade County, and the other six are found in Florida Keys (Hurt et al., 1995;

Noble et al., 1996). The Florida Keys are underlain by Coral limestone bedrock in the northern

and eastern side and with oolitic limestone on the southern and western part of the small islands

(Hurt et al., 1995). Most areas in the Florida Keys are used as habitat for wildlife, residential,

urban and for recreation. However the depth to the bedrock, high seasonal water table and severe

flooding limits use of many areas in the Florida Keys for building, and development of recreation

and sanitary facilities (Hurt et al., 1995). Thirteen soil series were classified with carbonatic

mineralogy in Puerto Rico (Aguilita, Altamira, Atoradello, Bahia Salinas, Catano, Colinas,

Costa, La Covana, Naranjo, Parguera, San Sebastian, Tuque, and Yauco).

The area in Florida where carbonatic soils are found is characterized by long, warm rainy

summers and mild dry winters (Noble et al., 1996). Although in many other states carbonatic

soils are mainly used as rangelands, wildlife habitat and livestock grazing, urban and recreational

development, pasture land and to some extent croplands, these soils are important in Dade









County for agricultural produce. They are used for growing vegetables, tomatoes, beans, corn,

malanga, limes and ornamental nurseries (Noble et al., 1996). Over 85% of Florida's tropical

fruits and vegetables are grown on carbonatic soils in the southern part of Florida (Li, 2001).

Numerous researchers (Maheswari and Ramesh, 2007; Cox et al., 1998; Nkedi-Kizza et al.,

1983; Karickhoff et al., 1979; Chiou et al., 1979) have established a positive correlation between

soil organic carbon (SOC) content and hydrophobic organic chemical (HOCs) retention. It can

therefore be concluded that SOC provides the best single predictor for adsorption isotherm

parameters for HOCs. Since humic materials of different origin constitute a heterogeneous group

of macromolecules with different complexity and sorption capacities towards organic pollutants

(Thomsen et al., 2002), understanding how OM was formed may be an important predictor for

the fate of pollutants.

The degree of adsorption of a pesticide is an important parameter in determining the fate of

a pesticide. Low sorption potential and relatively long half-life pesticides are associated with

high leaching potential through the soil subsurface thereby contaminating groundwater

(Wauchope et al., 2002; Triegel and Guo, 1994). Adsorption mainly takes place in the topsoil yet

it is still in topsoil where pesticide degradation and dissipation mainly takes place. Strongly

adsorbed and/or highly degradable pesticides are less likely to reach groundwater. Some studies

(Nkedi-Kizza and Brown, 1998; Steinberg et al., 1987; Ogram et al., 1985; Moyer et al, 1972)

have reported that the adsorbed phase is amenable to microbial degradation. Adsorption may

therefore influence the rate of pesticide degradation and dissipation and if this contaminated

topsoil is eroded, then there is risk to surface water contamination. The major components in

soils controlling adsorption are OM, clays and oxides and hydroxides of Al and Fe (Morrill et al.,









1982). OM mainly controls the adsorption of hydrophobic organic chemicals while clays play an

important in controlling the adsorption of cationic organic chemicals like diquat, and paraquat.

Recently, numerous field and laboratory controlled studies (Maheswari and Ramesh, 2007;

Oliver et al., 2005; Kulikova and Perminova, 2002; Cox et al., 1998; Nkedi-Kizza et al., 1998;

Ma et al., 1996, Nkedi-Kizza et al., 1983) have been conducted aimed at understanding and

characterizing the sorption and degradation of organic pesticides applied on non-carbonatic soils

but a search in literature indicates lack of these data in carbonatic soils. To predict movement of

pesticides in a soil profile, model simulators need physicochemical parameters of soils including

sorption coefficients, and degradation rates.

The overall objective of this study was to characterize the sorption and degradation of

pesticides and to understand why carbonatic soils of South Florida and Puerto Rico do not adsorb

organic pesticides as effectively as the non-carbonatic soils. Of concern are pesticides with high

leaching potential and relatively high persistence and particularly those that have been detected

in surface and groundwater of South Florida and Puerto Rico. This study aims at characterizing

carbonatic soils in order to provide these important properties which will be useful in

understanding the fate of HOCs in these soils.









CHAPTER 2
LITERATURE REVIEW

Carbonatic Soils Formation

The geologic history of Florida is believed to start from the time of continental drift where

North America was split from Western Africa (FDEP, 1994). The fragment of West Africa

which remained attached to North America formed basis for carbonate build-up, resulting in

present day Florida and the Bahamas Platform. The limestone in South Florida consists of oolitic

facies and the bryozoan facies, the latter being made up of mollusks, bryozoans and corals. The

bryozoan facies cover most of the Eveglades and extend as far as Fort Lauderdale while the

Miami oolite covers a large extent of the Atlantic coastal ridge (Hoffmeister, 1974). The South

Florida's subtropical environmental conditions are believed to have created suitable conditions

for warm waters, increased evaporation and subsequent enhanced super-saturation, resulting in

oolite deposition. The oolites formed from originally loose unconsolidated sand grains cemented

with calcium carbonate (Hoffmeister, 1974).

It is believed that during the Pleistocene, the water level fluctuations provided suitable

conditions for development of new calcite colonies which may explain the high prevalence of

calcite deposition within South Florida. It is also believed that (six million years ago), a shallow

sea covered Florida. The rock beneath the Big Cypress swamp (Tamiami formation) which is

also the oldest rock in South Florida (Hoffmeister, 1974) was a shallow marine bank where

calcareous sediments and bryozoan reefs accumulated. Although the Tamiami formation is the

oldest rock at about six million years of age, other South Florida rocks (Miami Limestone, Fort

Thompson formation and Key Largo limestone) are among the youngest in the country, differ in

composition, and were deposited under different environmental conditions (Hoffmeister, 1974).

As the water levels dropped, the rock outcrops were exposed to form the present Florida. The









Tamiami formation happens to be the most permeable ever investigated by U.S. Goeological

survey (Mowry and Bennett, 1948). The Miami oolite which formed later (100,000 years ago)

overlies the Tamiami formation and is also highly permeable (Noble et al., 1996, Hoffmeister,

1974). The formation covers most the Eastern Everglades National park and Florida Bay and

forms the land surface for the Florida Keys, Big Pine Key and Key West (Mowry and Bennett,

1948). During the Pleistocene, the unique geographical position of South Florida produced a

terrain different from the rest of the Florida peninsula creating prevalence of carbonate sediments

as opposed to the sandy ridges of central Florida. Most of the continental quartz was funneled

offshore and lost down the continental slope. It is also believed that during the glacial period, as

sea level rose the southern most tip of present Florida was floated but calcium carbonate was the

major source of sediment.

The accumulation of dead coral reefs, deposition under low energy wave conditions, and

recession of the water level is believed to be the basis for the present day calcite formation in

Miami Dade and all the way to the Florida Keys. The carbonate bedrock forms the parent

material for cabonatic soils in South Florida. Carbonatic soils are soils containing more than 40%

of carbonates in their mineralogy. The major forms of carbonates in the calcareous soils are

calcite (CaCO3) and dolomite [CaMg(CO3)2]. The sources of dolomite are mainly inheritance

from parent material. The well drained rock/gravelly soils such as those adjacent to the Miami

ridge in South Florida (Chekika and Krome) were formed from rock-plowing or scarification of

the carbonate bedrock. The carbonate bedrock in the most parts of Florida (Ocala limestone) is

believed to have formed during the upper Eocene.

In the low lying, poorly drained and often flooded soils in South Florida, the prevalence of

periphyton mats has induced secondary precipitation of predominantly silt-sized calcium









carbonate that comprises the parent material leading to formation of marl soils. Marl soils

formed in coastal and freshwater marshes and sloughs. In the areas that are flooded for most of

the year, organic matter (OM) accretion occurs leading to formation of organic soils. In South

Florida, the marl and organic soils formed on nearly level ground with slopes from 0 to 2 %. The

natural vegetation of marl soils consists of sawgrass, whitetop sedge, yellowtop, goldenrod,

gulfdune paspalum, broom sedge, glades lobelia, dogfennel, gulf muhly, bluejoint panicum,

bushy beard bluestem, and South Florida bluestem. Carbonatic soils are underlain by the highly

porous Miami Oolitic limestone bedrock that formed from small spherules of calcium carbonate

(Noble et al., 1996). The water table in these soils is within 25 cm from the surface for at least 4

to 6 months of most years. The soils are flooded for several months during the summer followed

by dry months in winter. The hydro-period in marl soils is shorter than in organic soils. During

the dry months OM is oxidized leading to lower OM content in these soils.

The major underlying difference between marl soils like Biscayne and non-marl carbonatic

(rock/ gravelly) soils like Krome is the way they were formed. Krome and Chekika are well

drained soils that were formed from rock-plowing or scarification for purposes of agricultural

production. In the marl soils, the microalgae (periphyton mat) that grow on the surface of the

water-inundated-soils use carbon dioxide during their photosynthesis and these reactions are

responsible for the formation of secondary carbonate. In poorly drained soils, algal uptake of

CO2 at the wet soil surface reduces the carbon dioxide partial pressure (pCO2). The upward water

flux due to evapotranspiration limits gas diffusion in the subsoil (pCO2 in poorly drained soils

increases with depth). The loss of CO2 to the atmosphere dn to algal photosynthesis lowers

pCO2, and the slow re-dissolution of CO2 into water and/or loss of water due to

evapotranspiration near the soil surface, drives the reaction in Equation 2-1 to the right.









The principal reaction leading to formation of secondary CaCO3 and marl soil formation is

shown in Equation 2-1:

Ca2+ + 2HC03 CaCO3 + H20 + C02 [2-1]

When plant roots decay, they release organic acids that dissolve the rocks, therefore

increasing the concentration of Ca2+ in the soil solution. The carbon dioxide involved in calcite

formation is either atmospheric or from calcite dissolution. These factors favor precipitation of

secondary CaCO3 at or above the soil surface, from water saturated with CaCO3 when soil

undergoes desiccation. As Ca2+ and HC03- move with the upward water flux, precipitation takes

place near the soil surface where pCO2 is lower and the soil solution is concentrated due to

evaporation.

The above mechanism of formation of secondary CaCO3 is strong evidence that the water

table in South Florida is at or above the soil surface because secondary calcite putativelyy marls)

is prevalent in South Florida. The carbonate formed due to secondary formation is fine giving the

soils a loamy texture. Krome soil (Loamy-skeletal, carbonatic, hypothermic Lithic Udorthents) is

a typical rock-plowed soil while Biscayne (Loamy, carbonatic, hyperthermic, shallow Typic

Fluvaquents) is a typical marl. The rocky soils formed at higher elevation adjacent to the Miami

ridge while the marl soils formed in low lying southeastern coastal areas and the Everglades in

South Florida.

The Histosols in South Florida were formed in areas that inundated with water. In 1948,

Histosols covered 40 % of the soil survey area (Mowry and Bennett, 1948). These soils play an

important role in carbon sequestration as they accumulate OM resulting from wetness throughout

the year. The Histosol that were sampled are associated with the carbonatic soils but may have

different vegetation (such as saw grass) compared to algae in marl carbonatic soils. Oxisols from









Uganda constitute the most highly weathered soils. These are tropical soils that were formed in

hot and moist climate. Since these soils come from a completely different geographical region

(Eastern Africa), whose vegetation differs from that of the sub-tropical regions of Florida and

Puerto Rico, it is expected that the OM present in these soils differs. The expected differences in

OM and sorption properties formed the basis for their inclusion in this study.

Soil Organic Matter (SOM)

Plant litter and micro-biomass are the major contributors to OM in the soil. These

decompose forming complex macromolecules with a range of polarities and complexities, posing

challenge to conventional analytical techniques. Plant residues constitute the majority of SOM

substrate while the rest is contributed by decayed biomass. The decomposition of plant residue

by microorganisms results in breakdown of the residues into carbon which is either evolved as

carbon dioxide or incorporated in the biomass when microorganism use SOM as a source of

energy. As such, low OM decomposition mostly due to soil anaerobic conditions lead to SOM

accretion. Although SOM usually constitutes a small percentage of soil mass, it greatly

influences soil chemical and physical properties. The pH dependent charge on SOM contributes

up to 80 % of soil cation exchange capacity (CEC) with CEC contribution of 150-300 cmol kg1,

a range considerably higher than for clay minerals. In terms of CEC contribution by clays, the

expanding type with the 2:1 conformation (montmorillonite and vermiculite), have higher CEC

compared to the non-expanding type such as Illite and Chlorite (Smith and Walker, 1977). The

influence of SOM on soil structure and aggregation, soil bulk density, soil color, water holding

capacity and organic pollutant sequestration is well known. OM plays an important role in

controlling the chemical, biological and physical properties of soils and sediments. It is

responsible for nutrient retention/ release, soil color, cation exchange capacity (CEC), improved

soil aggregation, water holding capacity, porosity and serves as an energy source for









microorganisms (Stevenson, 1994). Soil aggregation improves infiltration rates, and gas

exchange between the atmosphere and the soil root zone. The carbon content of humus in soils is

generally given as 58 % (1:1.724) of SOM (Westman et al., 2006; Hanna, 1964; van Bemmelen,

1891). Understanding SOM chemical functionalities and its dynamics in soils is important in soil

nutrient management, soil remediation, sustainable agricultural production and global carbon

cycling. The improvement in designing predictive capabilities and strategic models aimed at

reducing environmental bioavailability, and leaching of toxic xenobiotics to surface and

groundwater Investigating the adsorptive capacity of organic compounds by SOM is useful in

understanding the adsorption mechanism and thereby.

Variations in SOM reaction capacities have been noted and these have been attributed to

variation of SOM composition and cation saturation capacities (Smith, 1974). In order to

characterize the structure and functionality of SOM, CPMAS 13C NMR, liquid state NMR, and

IR have been used. Some studies (Cox et al., 1998; Nkedi-Kizza et al., 1983; Maheswari and

Ramesh, 2007) have indicated the role of organic carbon as a major contributor in the adsorption

process of hydrophobic organic compounds (HOCs) and as such may determine the effectiveness

and activity due to its influence on the partition between the soil solution and the soil solid phase.

To maintain pesticide application effectiveness, it is a common practice to increase the amount

of a pesticide applied with increase in SOM content. Piccolo et al. (2001) related increase of

hydrophobicity of OM as a good indicator of interaction potential for non-polar compounds.

Using CPMAS 13C NMR data, he defined the hydrophobicity index (HI/HB) as the ratio of the

quantity of the hydrophilic C to hydrophobic C (Equation 2-2):

[(45-60) + (60-110) + (160-190)/ (0-45) + (110-160)] [2-2]









SOM is made up of a mixture of plants, microbial biomass and insect residues, dissolved

organic matter (DOC) and humic substances (Chefetz et al., 2000). There are two bio-chemical

classifications of plants, from which OM is derived, namely non-vascular (with no woody and

cellulosic tissue like algae) and those that are vascular (with tissue like shrubs, grasses and trees).

The Calvin-Benson photosynthetic pathway used by C3 plants to incorporate carbon,

preferentially incorporates 12C producing a shift of 20%o while the C4 pathway produces a shift

of -8%o to -12%o (Meyers and Ishiwatari, 1993). Complex structural polysaccharides and

phenolic polymers (lingo-Cellulose) comprise the most abundant biopolymer in OM (Kogel-

Knabner, 2002; Kirk, 1984). Cellulose makes up the major component of the cell wall for both

woody plants (45-90%) and herbaceous plants (15-30%). The hydroxyl groups in its structure are

responsible for its hydrogen bonding and its fibrous nature hence its supramolecular structure

(Kogel-Knabner, 2002).

SOM is divided in to two classes: Humic and non-Humic substances. The humic

substances consist of components of plants, animals and micro-organisms that have been

transformed by microbial or chemical processes. Non-humic substances on the other hand

consist of unaltered materials of plants, animals and microorganisms mainly consisting of

cellulose, starch, proteins, chitins and fats (Morrill et al., 1982). In terms of adsorption capacity,

non-humic substances contribute negligible effect compared to the humic substances which

provide large surface area and charge density per unit area (Dunigan, 1971). The humification

process results in the formation of humic substances described as supramolecular associations of

low-molecular-mass organic molecules (Kulikova and Perminova, 2002), operationally divided

on the basis of their solubility (Moreda-Pifieiro et al., 2004; Morrill et al., 1982) into fulvic acids,

humic acids, and humin. Humic acids dissolve in bases but not acids, while fulvic acids dissolve









in both acids and bases and humins are insoluble in both acids and bases. Humic acids possess a

high degree of polymerization compared to fulvic acids while fulvic acids are known to contain

higher proportions of acidic functional groups. The source of DOC in oceans is thought to be due

to primary production and the disappearance pathways are thought to be photodecomposition and

microbial reworking (Koch et al., 2005). In terms of composition, marine DOM contains less

aromatic and phenolic hydroxyl groups compared to freshwater DOM (Koch et al., 2005).

Separation and identification of complex organic structures and functional groups still remains a

mystery, despite recent improvement in analytical capabilities.

Earlier methods of OM quantification involved use of hazardous oxidizing agents

(Walkley and Black, 1934). Recent methods have utilized more environmentally safe procedures

like thermograviemtry, and near or mid-infrared (IR) reflectance spectroscopy. Spectroscopic

measurements are coupled with multivariate calibrations to enable data interpretation. Recent

advances in OM analysis involve use of spectroscopic techniques, high resolution nuclear

magnetic resonance spectral analysis, high resolution mass spectrometer and ionizing techniques

like nano-electrospray that enable analysis of molecule > 500 daltons (Kogel-Knabner, 2002).

Review of the Methods

Thermogravimetric methods, stable carbon isotope determination, and spectroscopic

methods such as UV-vis and fluorescence have been used in quantification and characterizing

SOM. However, for detailed structural characterization, methods like Fourier transform infrared

(FT-IR), Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), 13C-NMR

and 1H-NMR spectroscopy have been applied to investigate molecular changes in SOM and to

elucidate composition of SOM complexes. Recent developments in analytical equipment

technology have improved capabilities for analysis of macromolecules which were not possible

in the past. These include pyrolysis GC-MS and nano-electrospray ionization mass spectrometry.









These improvements have made steps aimed at overcoming the low mass cut-off of mass

spectrometers.

Soil Organic Carbon Determination

Soil organic carbon is commonly determined by use of oxidation processes that were

originally developed by Schollenberger (1927) and Degtjareff (1930), modified by

Schollenberger (1931) and later by Walkley and Black (1934). Though the Walkley and Black's

procedure was suggested for quick and approximate determination of organic carbon (Walkley,

1947), this oxidation method is to-date still the most universal and most widely used method for

rapid determination of soil organic carbon. However, there is no such a universal method for

determination of SOM/ OC for all soils due to the presence of compounds in numerous soils that

may interfere with OM determination. The major demerits of the Walkley and Black method are

its generation of large amounts of toxic dichromate waste and possible interference from soils

constituents such as chlorides and oxides of iron and Manganese (Walkley, 1947). In addition, an

incomplete conversion of organic carbon to carbon dioxide (76% average) is achieved by the

method thus warranting the use of a (1.32) correction factor (Schollenberger, 1945; Walkley and

Black, 1934). Alternative methods have since been developed that include thermal methods and

elemental analysis that involves determination of total carbon. The use of thermal methods for

determination of OM dates as far back as the late 1940s (Mitchell and Birnie, 1970). Some

studies (Critter and Airoldi, 2006; Mitchell and Birnie, 1970; Schnitzer and Hoffman, 1965) have

used thermal methods to characterize the physical and chemical nature of OM. The applicability

of thermal methods to OM analysis relies on the premise that the soils do not contain compounds

like gibbsite, smectite and kaolinite clays that decompose within the same temperature range

(200-5500C) as OM (Karathanasis and Harris, 1994; Mackenzie, 1970). The presence of these

components curtails use of thermal methods for analysis of Oxisols and other soils that contains









large amounts of clays. Following decarbonation of inorganic carbon with hydrochloric acid,

total organic carbon (TOC) can be determined by elemental analysis. However the treatment step

may affect purgeable OM (Motter and Jones, 2006). Total carbon on the other hand may be used

but this requires knowledge of carbonate amounts in carbonatic soils in order to determine

organic carbon by difference.

The presence of OM in soils can influence factors like soil fertility, water and nutrient

retention capacity, bulk density, soil aggregation and xenobiotic retention. An accurate

determination of SOC is necessary in order to predict the sorption coefficient (Ko) of

hydrophobic organic chemicals (HOCs) whose retention in soils is predominantly associated

with soil organic carbon (Nkedi-Kizza et al., 2006; Wauchope et al., 2002; Nkedi-Kizza et al.,

1983). Since the sorption of HOCs in soils is normalized with the fraction of organic carbon (fo)

present in soils (Ko = Kd/foc), if SOC is inaccurately determined, the sorption coefficient Ko

determined may be in error. SOC and SOM are often determined indirectly depending on the

method used. A conversion factor is then used to convert from one parameter to another. A factor

that is commonly used in literature is 1.724 (Westman et al., 2006; Hana, 1964; van Bemmelen,

1891; Ranney, 1969). A single factor for all soils seems inappropriate. Already, some studies

(Ranney, 1969; Broadnet, 1953) have indicated conversion factors up to 2.5. Probably this

explains to a large extent the variability of Ko values found in the literature for a given neutral

organic chemical.

This study examined the use of thermogravimetry (TG) and weight-loss-on-ignition

(WLOI) thermal methods for determination of SOM in carbonatic and associated soils, Oxisols,

and Spodosols. Thermogravimetry utilizes untreated whole soil samples and provides a highly

sensitive and accurate determination of OM in carbonatic soils and the amount of carbonates in









the soils in one run. Unlike WLOI which is carried out "blindly" in the muffle furnace, TG

provides an online weight loss and insight on the onset temperature points during decomposition

thus giving a more accurate determination of soil components. Addition of first order derivative

can provide valuable information regarding the reactions taking place during thermal

decomposition.

Elemental Analysis (Total Organic Carbon, Total Carbon, Total Nitrogen)

The methods to determine total organic carbon content and total organic nitrogen involve

use of elemental analyzers. Analysis of the C/N ratio by depth can be useful in understanding the

paleo-environmental changes (Punning and Thugu, 2000) since the OM decomposition results in

biomarkers that are characteristic of the microbial populations driving the degradation process,

sources of OM and its diagenesis.

UV-vis and Fluorescence Spectroscopy

Humic and Fulvic acids form complexes with trace metals making them able to attenuate

light. The fluorescence properties of OM have been attributed to the quinone-like fluorophores

which result from phenol oxidation (Cory and McKnight, 2005; Leenheer, 2003). Fluorescence

in dissolved organic matter (DOM) has been suggested to be a measure of redox potential of

DOM (Cory and McKnight, 2005). The recent advances in spectroscopic and mass spectrometer

techniques (Kogel-Knabner, 2002, ), coupled with novel ionization procedures like nano-

electrospray ionization and matrix-assisted laser desorption ionization (MALDI) have improved

capabilities of analyzing macromolecules thus providing a better understanding of the molecular

structure and functional groups in OM and its decomposition pathways.

FT-IR

Fourier Transform infrared (FT-IR) spectroscopy has been described in measurement of

OM in soil. Coupled with multivariate calibration and use of principle component analysis, FT-









IR provides a rapid, nondestructive and environmentally safe method for OM quantification.

Fourier transformation ion cyclotron resonance mass spectrometry (FT-ICR MS) is a technique

with high resolving power and mass accuracy (Marshall 2000; Marshall et al., 1998). Stenson et

al., (2002a) and Marshall et al. (1998) provide detailed description of ultra-high-resolution FT-

ICR MS. The methods are used to determine singly charged ions at mass resolving power

between 60,000 and 120,000 and therefore eliminating low molecular weight bias resulting from

multiple charged ions. Electrospray ionization has been described as the method of choice for

analysis of humic substances (Stenson et al., 2002b). By use of electrospray and MALDI

ionizations techniques, coupled with FT-ICR MS, for the first time identification of up to 5000

molecular formulas for large and individual fulvic acids have been reported (Stenson et al.,

2003). This research indicates a breakthrough in OM analysis as this may shed more light in

understanding the chemistry of humic substances.

Stable Isotopes Characterization (S13Carbon, Carbon-Nitrogen Ratio)

Lake studies utilize C/N ratios to try and reconstruct changes in primary production and

trophic state of the lake (Punning and T6ugu, 2000) in order to assess terrestrial impacts on the

lake system. Sources of OM pools may cause difference in carbon fractionation, carbon stable

isotope ratios 613C, and organic C/N ratios. Isotope ratios are reported in per mil against Peedee

Belemnite (PDB) standard (Doi et al., 2003). The isotopic composition from the long-chain n-

alkanes reflects the differences in carbon dioxide fixation mechanism between C4 and C3 plants

as well as the temporal variations in environmental changes that affect primary producers

(Fuhrmann et al., 2003). OM with low C/N ratios (4-10) indicates microalgal sources while

higher C/N ratios (>20) indicates terrestrial origin of OM (Doi et al., 2003). Paleo-environmental

and paleo-climatic studies have utilized stable carbon isotopes as biomarkers to specify the

primary producers and reconstruction of the vegetation history. The determination of stable









isotopes involves coupling Gas Chromatography or an elemental analyzer with an isotope ratio

mass spectrometer (Kelly et al., 2005). Organic nitrogen contributes significantly to the total

nitrogen pool. Understanding the contribution of organic nitrogen to the biogeochemical cycles

requires appropriate methods to characterize and identify its sources. Until recently, isotope

studies have concentrated on characterizing organic carbon but more recent studies have

included nitrogen isotopic measurement in characterizing the sources and cycling of inorganic

and organic nitrogen (Kelly et al., 2005).

However, the determination of contributors to stable isotope signatures becomes fuzzy

when mixed C3 and C4 plant species are contributing towards the carbon fractionation.

Additionally the change in energy levels due to nuclei spins and resonance frequencies are

characteristic of the strength of the magnetic field. This makes it hard to compare spectral results

obtained from another NMR unless a standard is used to correct for the chemical shifts (Kogel-

Knabner, 2002).

Cross Polarization Magnetic Angle Spinning Nuclear Magnetic Resonance (CP-MAS 13C-
NMR)

NMR spectroscopy is a technique based on magnetic properties of the observed nucleus,

(which is influenced by electron density) and its interaction with its physical environment.

Organic compounds contain protons in specific environments, making them sensitive to 1H

NMR. 13C NMR on the other hand is valuable in showing changes in the backbone of organic

molecules. The accuracy of NMR spectroscopy and sensitivity enables it to detect small

chemical differences in local environments (1-300 Hz), which accounts for its wide use in

biochemistry, medicine and compound elucidation (Jayasundera et al., 2000). Nuclear magnetic

resonance (NMR) is the most commonly used method for SOM characterization. Several

researchers have reported successful use of Solid state 13C NMR (Mathers and Xu, 2003; Laws et









al., 2002) in characterizing OM. Liquid state NMR is more commonly used than solid state NMR

but recently solid NMR is emerging as a powerful tool in the studies of solid materials (Laws et

al., 2002). Unlike liquid state NMR which involves organic extraction using a base, alteration in

the nature of OM in the sample is unlikely in solid state NMR since it requires little (removal of

paramagnetic impurities) or no sample pre-treatment. NMR can be used to elucidate structure at

atomic and molecular level by subjecting the sample to a magnetic field that forces the nuclei

spins to distribute themselves in different energy levels. The chemical shifts (Figure 2-1) can be

used to identify the functional groups present. Recent advances to improve NMR analysis

include cross polarization, magic-angle-spinning, decoupling and recoupling techniques,

dynamic angle spinning, two dimensional homonuclear total correlation spectroscopy (TOCSY),

heteronuclear multiple quantum coherence (HMQC), and dipolar diphasing (Laws et al., 2002;

Kingery et al., 2000). These advances have improved functional group assignment, chemical

shift anisotropy measurement, and dipolar coupling and have provided a better understanding of

OM chemistry.

The nature of binding that exists between a pollutant and OM determines its environmental

dynamics and availability. Using NMR, specific changes in parameters such as line broadening,

chemical shifts in specific nuclei, relaxation times, and coupling constants can be useful in

elucidation of the types of interactions covalentt, or non-covalent) that take place between the

pollutants and the natural environmental samples (Jayasundera et al., 2000). The binding of

pollutants to mineral and humic surfaces induces NMR chemical shifts and spin lattice and these

changes are used in determining the binding sites and strengths.

CP-MAS NMR technique is said to be less but sufficiently sensitive to heterocyclic N than

to N amides, as sensitivity is thought to depend on transfer of magnetic energy from 1H to 15N









nuclei yet heterocyclic are not usually directly protonated (Kulikova and Perminova, 2002).

Other than obtaining a gross chemical composition of plant residue, NMR does not provide

specific compound identification (Kogel-Knabner, 2002).

Tetramethylammonium Hydroxide (TMAH) Thermochemolysis Coupled with Gas
Chromatography/ Pyrolysis GC-MS

Recent advances using thermochemolysis and tetramethyl ammoniun hydroxide (TMAH)

have been instrumental in shedding more light in studies that involve macromolecules (Chefetz

et al., 2000; Chefetz et al., 2002). TMAH fragments OM into lignin derived compounds,

nonlignin-derived aromatic compounds, fatty acid methyl esters (FAMEs), heterocyclic N, and

dicarboxylic acid dimethyl esters (DAMEs). TMAH works by hydrolysis and methylation of

esters and ether linkages (Filley et al., 1999). The fragmented compounds are then subjected to

gas chromatography (GC) or gas chromatography coupled with mass spectrometry (GCMS).

Pyrolysis of humic substances produces fragments of pyrazoles, pyridines, substituted

pyrimidines, pyrazines, indoles, quinolines, N-derivatives of benzene, alkyl amines, alkyl and

aromatic nitriles (Stuczynski et al., 1997; Schulten et al., 2002). Fuhrmann et al., 2003 described

a detailed method in which they used Fison GC 8000 coupled with Fison quadrupole MD 800

mass spectrometer. Full mass spectrum was recorded within the 10-420 amu with 2.5 scans/s

(Fuhrmann et al., 2003).

Fiber Optics and Spectroscopic Analysis

A new emerging method for OM analysis involves use of near infrared spectroscopy. The

equipment is composed of a sensor system with four optical fiber probes, a spectrometer and a

control unit. Two of the fiber probes provide the illumination of the sample while the other two

are for collecting soil reflectance from the visible to the near infrared (NIR) wavebands. Real-

time soil reflectance has been described in the field at a depth of 30 cm (Li, 2005). The amount









of OM and differences in OM types ((Ben-Dor et al., 1997; Palmborg and Nordgren, 1993) can

be determined using NIR spectroscopy. Compared to other methods, the integrative function of

the NIR calibrations may explain the low analytical errors in NIR spectroscopy. In addition, it is

a rapid, low price analytical technique and no hazardous chemicals are used (Borjesson et al.,

1999).

Key Findings

For the first time, Stenson et al. (2003) reported identification of up to 5000 molecular

formulas for large and individual fulvic acids. Using FT-ICR MS, Koch et al., 2005 were also

able to identify 1580 different molecular formulas. 13C labeling in conjunction with 13C NMR,

have also been used to provide evidence for 13C-2, 4-dichlorophenol (DCP) binding properties

with macromolecular structures of humic substances (Hatcher et al., 1993). An understanding of

the binding properties can be a powerful tool in designing environmental remediation strategies.

Research findings that indicate the fluorescence properties of OM that result from quinone-like

fluorophores have been useful in advancing methods that use fluorescence in characterizing OM.

Quinones are also thought to be responsible for the electron shuttling ability of OM.

What is yet to be known about the Characteristics of Organic Matter

Current research finding are able to provide class-level as opposed to specific compound

level therefore a deeper understanding of the complex nature of OM will require techniques that

will go to the specific compound level. FT-ICR MS coupled with nano-electrospray seems

promising in this regard (Stenson, et al., 2003; Koch et al., 2005). Synthesis of specific

compounds will also pose research challenge given the complexity of OM.

Advances in analytical capabilities in fields such as spectrometry, mass spectrometry,

nano-ionization, and stable isotopes have shed light and increased our understanding of the OM

functionality. These techniques have been widely used in biological studies especially in the









medical field and less in classical chemistry. Understanding the binding properties of drugs to

proteins has helped greatly in drug discovery. The molecular information may help answer

questions like nature of OM, chemical structure, and surface site reactivity. The reports by

Stenson et al. (2003) indicate successful steps in OM characterization. Coupling Electrospray

ionization with ultra-high-resolution FT-ICR mass spectrometry results in 10-100 times higher

mass resolution and mass accuracy compared to other mass analysis technique though the very

high costs and maintenance for the analytical equipment (Marshall, 2000), may be a hindrance in

commercializing the equipment.

Chemicals Studied and Rationale

Atrazine

Atrazine (2-chloro-4-ethylamino-6-isopropylamino-1, 3, 5-triazine) belongs to s-Triazines,

a class of herbicides which have been the most widely used for control of broadleaf weeds.

Triazines use is slowly being phased out and replaced with pesticides that are more effective at

low application rates. Atrazine (Table 2-1) is one of the most widely used herbicide in United

States (USEPA, 2006) and the most commonly detected pesticides in precipitation (Majewski et

al., 2000; Goolsby et al., 1997) and in agricultural and urban streams across U.S.A (Gilliom,

2007) and is also one of the most widely studied herbicides. Its interactions with soil minerals

surfaces is probably the most understood. Atrazine is used as a pre- and post-emergent herbicide

for control of broad leaf weeds, applied at 7 kg/ha on sod for muck and 3.5 kg/ha on sandy soils.

It is one of the most commonly used s-triazine in U.S.A. Protonation of atrazine may be possible

at pH < 4 but such conditions are not environmentally relevant. The pH of most soil solutions (4-

8) ranges well above the pKa of atrazine (1.7) meaning that atrazine mainly sorbs as neutral

species. The likely mechanism of interaction between atrazine and soil surfaces is believed to be

via weak Van der Waals forces and H-bonding though it is assumed that entropy changes









contributes most of the interaction energy (Laird and Sawhney, 2002). The hydrophobic

interactions are likely between the alkyl groups and the uncharged siloxane surfaces of

philosilicates. In South Florida, atrazine was detected in 59 % of the samples analyzed while its

metabolite deethyl-atrazine was detected in about 5% of the samples analyzed.

It is generally agreed that soil OM controls sorption of hydrophobic organic chemicals

especially for soils with more than 1 % organic carbon but this may not be true for soils with low

organic carbon content and high clay content (Laird and Sawhney, 2002; Karickoff, 1981). Polar

chemicals are believed to be strongly adsorbed to soil mineral surfaces via cation exchange.

Some studies (Talbert and Fletchall, 1965) have reported no adsorption of atrazine and simazine

on kaolinite. The adsorption coefficients (Ko) reported in literature averaged 100 and 80 % of

the selected studies had Ko values that exceeded 100 (Hornsby et al., 1996).

Diuron

Diuron (3-[3, 4-dichlorophenyl]-1,1-dimethylurea) is herbicide belonging to the

phenylurea class (Table 2-1). The substituted urea acts by inhibiting photosynthesis by

preventing oxygen production. The rate of hydrolysis at neutral pH is negligible but increases at

high acidic and alkaline pH and degrades to 3, 4-dichloroanaline (Giacomazzi and Cochet,

2004). The literature Ko for diuron is 480 and a half-life of 90 days (Giacomazzi and Cochet,

2004; Hornsby et al., 1996; Wauchope et al., 1992). It remains a priority pollutant since its

degradation has not been properly characterized (Giacomazzi and Cochet, 2004) yet its detection

in water resources across the United States is widespread (Gilliom, 2007).

Ametryn

Ametryn (2-ethylamino-4-isoprpylamino-6-methylthio-s-triazine) is a pre- and post-

emergence herbicide belonging to the s-Triazine class (Table 2-1). Ametryn is stable under

neutral condition but it hydrolyses under acidic and alkaline pH. Ametryn has a log Kow of 2.63









and water solubility of 200 mg/L at 20 C. In the field, ametryn is applied at a rate of 1kg/Ha.

The literature Ko for ametryn is 300 and degradation half-life of 60 days (Hornsby et al., 1996).

The selected values in Homsby et al., 1996 for Ko ranged 170-389.

Sorption and Solute Transport in a Porous Medium

The sorption parameter can be useful in predicting the relative potential for pesticides

mobility and persistence. The high soil spatial variability of soil properties however, may prevent

large scale accurate predictions. The heterogeneous nature of OM in soils does not support the

equilibrium partition model to be sufficient in explaining sorption of HOCs as other non-

equilibrium processes during transport may be involved in controlling sorption (Pignatello and

Xing, 1996). The estimation of the organic carbon sorption coefficients (Ko) requires accurate

determination of soil organic carbon (SOC) content since the distribution constant (Kd) is

normalized against OC to calculate the Ko values. The movement of HOCs in a soil profile

essentially depends on the interactive forces that control the solute distribution between the soil

solution and soil surfaces, and its degradation rates. A solute with low soil retention and longer

soil persistence will likely pollute ground water while a strongly retained solute will remain in

the top soil profile thereby prone to lateral movement via soil erosion. The movement of solutes

is assumed to be controlled by convection, diffusion and dispersion processes. Once the solute is

introduced in a soil matrix it undergoes diffusion and dispersion processes thus interacting with

the soil solid and the mobile phase of the soil matrix (Malone et al., 2004; Triegel and Guo,

1994; Nielsen et al., 1986).

The movement of solutes from high to low concentration gradient is known as diffusion.

Alongside diffusion is a passive process known as mechanical dispersion. Though diffusion is

considered an active process, both diffusion and mechanical dispersion are considered additive

during solute transport within a soil profile. As a result of soil pore size and structural









differences, mechanical dispersion, a velocity gradient is registered between solute velocities for

solutes at the soil surface and those in the center of the soil pores with respect to the average pore

water velocity. As the solute moves through the soil profile, sorption and exclusion of the solute

take place where sorption determines the solute retention in the solid phase (soil) while exclusion

refers to the phase in the soil solution. This distribution of the solute between the two phases and

the tortuous nature of the flow path within a soil matrix creates a velocity gradient between the

water and the solute hence resulting in solute retardation due to soil interactions. Some studies

(Swanson et al., 1954) have found a correlation between HOC adsorption with soil clay content.

Upchurch and Mason (1962) reported a positive correlation between soil OM and the quantity of

herbicide required to produce 50 % growth reduction, an indication that OM adsorbs and

sequesters a portion of herbicide applied.

Interaction with Organic Carbon

Although some studies (Oliver et al., 2005; Spark and Swift, 2002) did not find a

relationship between organic carbon content and sorption of HOCs, several studies (Maheswari

and Ramesh, 2007; Cox et al., 1998; Nkedi-Kizza et al., 1983) have established a linear relation

between organic carbon content and sorption of HOCs. The interaction mechanism has been

described mainly to be due to partitioning.

For soils with low organic carbon content, clay minerals may contribute greatly to the

sorption of polar and non-polar pesticides. The Ko theory may therefore break down. The nature

and properties of mineral surface may be affected by pH. The pH at which the net positive

charge and negative are equal is called the zero point of net charge (ZPC). Organic acids tend to

have stronger interactions at pKa < ZPC and at pKa > ZPC for organic bases.









Sorption Models

Equilibrium isotherms are often described by mass action, Linear, Freundlich, or Langmuir

sorption models (Nielsen et al., 1986). The linear model was relevant to our study since we

worked within the linear range of the isotherms. Sorption models are classified as those that were

derived for the adsorption of gases by solids, the empirical models and those that are kinetic or

rate models. Adsorption of HOCs can assume three phases, which may be represented by the

Equation 2-3:

S = Se + Sk +Sir [2-3]

where Se is the rapidly established equilibrium between solutes concentration and the solid

sorbed phase, Sk is the time dependent kinetic type sorption and Sir, the irreversible adsorption.

The Linear Sorption Model

The linear model is derived from the linear equation

Se = mCe + b [2-4]

where Se = equilibrium sorbed phase (mg of solute/kg of soil), Ce = equilibrium solute

concentration (mg/L) and m and b are empirical constants. It is assumed in Equation 2-4 that at

at initial concentration (Co) = zero there is no adsorption so the "b" in the equation is assumed to

be zero, thus transforming the equation to common sorption linear equation (Equation 2-5). This

approach assumes instant adsorption and a linear relationship between the adsorbed phase and

the soil solution phase thus forcing the intercept through zero. Linearity of the isotherms is

primarily dependent on the pesticide concentration, mostly linear when the solution

concentration is less than half of the compound's water solubility (Karickoff, 1981).









Non-linearity tends to increase as solution concentration increases and as such Equations 2-4

hold if the experiment is performed within the linear range of the isotherm.

Se = KdCe [2-5]

where Kd (L/kg) is the empirical distribution (partition) coefficient. Normalization of the

distribution coefficient for HOCs against the fraction of soil organic carbon content (foc) yields

a new sorption coefficient known as Ko (Equation 2-6), which enable comparison of sorption

across a wide range of soils with varied OM content.

K
Koc [2-6]
foc

Freundlich Isotherm Model

This model is empirically derived and has a mathematical equation written as:

Se = KfCN [2-7]

where Se is the equilibrium adsorbed concentration; Kf [(mg/kg)*(L/mg)N] is the Freundlich

constant related to the amount adsorbed, Ce is the solution equilibrium concentration and N

(usually ranging between 0.7
isotherm. As the N value approaches 1, Kf approximates to Kd.

Lagmuir Sorption Model

The Langmiur isotherm model (Equation 2-5) has sound conceptual basis and was derived

to describe adsorption of gases on to solid surfaces. This model assumes that:

1. The adsorption energy is constant and independent of the surface coverage.

2. Adsorption occurs on localized sites and there is no interaction between adsorbed

molecules.

3. The maximum adsorption possible is that of a complete monolayer.









The mathematical equation is written as:


Se = Qax aCe [2-5]
( (1+ aCe)

where Se is the concentration of the adsorbed phase, Ce is the equilibrium concentration, Qmax is

the maximum amount of available sorption sites and "a" is a constant related to the bonding

energy.

Pesticide Degradation

The primary factor that determines pesticide dissipation is microbial degradation

(Edwards, 1973). The degradation of pesticides is often carried out at ambient temperature.

Pesticide concentration has been described to be the limiting factor and not the microflora which

is excess in the soils (Zimdal et. al., 1977). Accelerated pesticide degradation has been described

resulting from repeated application and subsequent soil enrichment of specific pesticide

degrading microbial species. Pesticide degradation is said to be affected by chemical and

environmental factors which include chemical structure and position and type of functional

groups, SOM content, soil pH, added concentration and previous applications, application

methods and rates, temperature, presence of other chemicals, soil moisture content, and the types

and population of the degrading microbes (Morrill et al., 1982; Nkedi-Kizza and Brown, 1998,

Hamaker, 1972). In some cases, SOM has been found to inhibit degradation by protecting

pesticides from microbial attack via adsorption for compounds like atrazine, and chrolopyrifos

(Hornsby et al., 1996; Rao et al., 1993). A positive relation has also been reported between

increase of OM and degradation rates for DDT, diazinon, diuron, and parathion (Morrill et al.,

1982). This increase is due to use of SOM acting as a co-metabolite and its ability to supply

nutrients for microbes and as a source of energy (Morrill, 1982).









In the early days pesticide resistance was a desirable attribute to enable extended pesticide

effectiveness. The first pesticides contained Arsenic which was persistent. Due to environmental

and health concerns these chemicals have been phased out and replaced with less persistent

alternative such as organophosphates and carbamates which have short half-lives of about 1-120

and 1-60 days respectively (Hornsby et al., 1996; Weber, 1994). Some pesticides have been

known to decompose to more persistent and more toxic metabolites than the parent compounds

and to cause health and reproductive effects to non-target species (Edwards, 1973).

Environmental Fate of Pesticides

Understanding the fate of a chemical in the soil environment requires knowledge of its

sorption capacity and degradation rates. Several researchers have reported low potential of

leaching for pesticides that are strongly adsorbed such as DDT (Edwards et al., 1971;

Lichtenstein, 1958) but more in runoff water (Zhou et al., 2003; Scott et al., 2002; Dur et al.,

1998; Edwards et al, 1971). In a study conducted by Dur et al. (1998), eroded particles did not

contribute to pesticide transfer but they attributed the runoff to adsorption-desorption (dilution)

phenomena to contribute to the runoff The study reported that strongly adsorbed chemical

required small fraction pesticide desorption to reach equilibrium during transport and that

reaching equilibrium was fast. Generally, it can be stated that pesticides with low sorption

coefficients have a high leaching potential provided they persist long enough during the

downward movement.

Hypotheses

* Hypothesis 1: Soil organic matter is the major contributor to pesticide adsorption in
carbonatic soils.

* Hypothesis 2: Soil organic matter in carbonatic soils is different from that in non-
carbonatic soils.

* Hypothesis 3: Carbonatic soils adsorb pesticides less compared to non-carbonatic soils.









" Hypothesis 4: Degradation of pesticides will be faster in carbonatic soils compared to non-
carbonatic soils due to less sorption in carbonatic soils.

" Hypothesis 5: Organic pesticides applied to carbonatic soils are likely to pose greater risk
to groundwater pollution than those applied on non-carbonatic soils due to decreased
sorption capacity in carbonatic soils.

Study Objectives

This study was aimed at understanding soil factors that determine interactions of organic

pesticides in carbonatic soils. In order to assess and predict the movement of pesticides in the

subsurface environment, this study aimed to understanding of the factors and processes that

influence interactions of pesticides with soil surfaces. The data obtained can be usable as input

model parameters (Malone et al., 2004; Ma et al., 1996) for simulating fate and transport of

pesticides.

* Objective 1: Characterize the chemical, physical and mineralogical properties of selected
carbonatic soils and associated non-carbonatic soil series from South Florida, and Puerto
Rico and Oxisols from Uganda.

* Objective 2: Characterize sorption and degradation of selected pesticides used on
important crops grown on carbonatic soils and associated non-carbonatic soils and Oxisols
from Uganda.

* Objective 3: Characterize organic matter from the selected soils, in terms of its formation,
composition, and functionality.

* Objective 4: Identify which type of organic carbon is predominant in marl soils compared
to associated peat soils from South Florida and Puerto Rico and Oxisols from Uganda.

* Objective 5: Identify the most dominant component of soil organic matter that influences
sorption of HOCs.

* Objective 6: Provide a database for sorption coefficients and degradation rate coefficients
for the major pesticides used on the carbonatic soils in South Florida, Puerto Rico and
Oxisols from Uganda.










Table 2-1. Chemical properties of atrazine, diuron and ametryn.
Solubility Half-life


Name


Class


(mg/L)


(days)


Atrazine s-triazine


Ametryn s-triazine


380


Chemical Structure



Cl- N NNHCHCH3

N N

NHCH(CH3)2

CHSy N* NHCH2CH3


NHCH(CH)
NHCH(CH3)2


Substituted


Diuron


330


urea


C480 l NHCON(CH3)2

C


Source: Wauchope et al., 2002; Wauchope et al., 1992; Hamaker and Thompson, 1972.











aromatic aromatic
i henalbct R
OH OR alcoholic
RC-OH
RC-OR
S*neehowr Mlpkyl.-C
\ / CHa
R-C ca yl paraffinic






R-C (aIdehye)
R-C"H l

R-C (R kol 200 100 0

Chemical shift (ppm)


Figure 2-1. Classification of 13Carbon nuclear magenitic resonance spectra (Kogel-Knabner,
2002, modified from Bortiyatinski et al., 1996).









CHAPTER 3
MATERIALS AND METHODS

Description of Sampling Sites

The carbonatic soils from South Florida's Miami Dade and Monroe Counties were

classified as Entisol, except Keyvaca which was classified as a Mollisol (Noble et al., 1996; Hurt

et al., 1995). Those collected from Puerto Rico (Aguilita, Colinas, San Sebatian, and Yauco)

were classified as Mollisols with the exception of Catano and Tuque which were classified as

Entisols and Aridisols, respectively (Mount and Lynn, 2004). Seven of the Histosols that were

sampled from South Florida and Puerto Ricot (Tamiami, Lauderhill, Islamorada, Dania,

Pahokee, Torryn, and Tiburonest) were classified as saprists and Matecumbe was classified as a

folist (Mount and Lynn, 2004; Noble et al., 1996). The Histosols which are widespread in the

Everglades and they generally form under Cladium spp. (sawgrass) vegetation and flatwoods,

with anaerobic marsh conditions minimize organic matter (OM) oxidation rates, leading to the

accretion of OM. The Spodosols were collected from flatwoods in Alachua County and were

classified as Aquods. Spodosols are sandy-soils with a characteristic spodic horizon where OM

has accumulated in the subsurface in association with Al and Fe. The Spodosols constitute the

predominant soil series in the state of Florida (USDA-NRCS, 2007 Online), thus Myakka

(600,000 ha).is designated the state soil.

Carbonatic soils are defined as soils containing at least 40% carbonates (calcite and/or

dolomite). In South Florida, there are two types of carbonatic soils, namely: Marl derived

carbonatic soils made up of limnic materials and the marine derived oolitic limestone rock-

plowed-carbonatic soils. Both the marl and rock-plowed carbonatic soils were included in this

study. Marl soils are very poorly drained and located within the low elevation areas of coastal

flats southern Everglades and the Florida Keys. The marl soils classified in the 1958 survey









(Gallatin et al., 1958) were Perrine marl, Ochopee fine sandy marl, the Hialeah mucky marl and

the Flamingo marl. The 1987 soil survey updated the marl soils classification in Dade County to

include Biscayne, Perrine and Pennsuco (Noble et al., 1996) while those classified as marl soils

from Monroe County were Key West, Cudjoe, Saddlebunch and Lignumvitae (Hurt et al., 1995).

These soils are formed by algal photosynthesis which leads to secondary precipitation of calcite

on top of the calcite bedrock (Figure 3-2). With the exception of Keyvaca which is a Mollisol,

the rest of the carbonatic soils from South Florida were classified as Entisols. The soils are

poorly to very poorly drained, moderately to rapidly permeable. Associated soils namely

Lauderhill, Matecumbe, Tamiami and Islamorada classified as Histosols were included. The

carbonatic soils sampled from Puerto Rico were classified as Aguilita, Catan6, Colinas, San

Sebastian, Yauco, and Tuque. With the exception of Catano and Tuque which are classified as

Entisols and Aridisols, respectively, the rest of the carbonatic soils were classified as Mollisols.

San Anton (Mollisol), and Bayamon (Oxisol) were non-carbonatic. The Ugandan Oxisols were

classified as Ferrisols and Ferrarisols (Selvaradjou et al., 2005). Surface samples (0-15 cm) were

collected for four soil types, encompassing a wide range of vegetation, climate and OM

composition. The rock plowed soils result from scarification of the marine derived oolitic

limestone bedrock on the Miami ridge to create sites for crop production. They are generally well

drained and gravelly. Table 3-1 shows the soils from Miami Dade County, Monroe County and

Puerto Rico classified as carbonatic that were collected for this study.

The carbonates in these soils are mainly composed of calcite and dolomite, with calcite

being more prevalent in Miami Dade (Noble et al., 1996). Carbonatic soils are associated with

organic soils that accrete OM as a result of their hydrology. Marl development is driven by algal

and periphyton mats that lead to formation of secondary carbonate. These soils are inundated









with water for four to eight months of the year while those that are flooded for at least twelve

months accrete OM resulting in accumulation of an organic layer. In Puerto Rico, a total of 13

soil series out of 175 established series are taxonomic classified as carbonatic (USDA-NRCS.,

1996). Agulita (11,274 hectares), Colinas (14,107 ha), Naranjo (1,958 ha), San Sebastian (12,246

ha), Tuque (3,139 ha) and Yauco (1,337 ha) are classified as Mollisols while Cataho (3,617 ha)

and Juacas (56 ha) are classified as Entisols (Mount and Lynn, 2004; USDA-NRCS, 1996). The

major agricultural soils from Uganda are mainly Oxisols, mainly classified as Ferrarisols and

Ferrisols. Carbonatic soils in Uganda are of small extent and they are mainly used for production

of Cement and Lime. They can be found in Western Uganda in Kasese (Hima and Muhookya

areas), Rukungiri (Rubaabo area) and in Tororo (Eastern Uganda).

Pesticides Studied

Based on major use and pollution potential, atrazine, ametryn, and diuron were chosen for

this study.

Determination of Soil Properties

Soil pH

Soil pH was determined at soil solution ratio of 1:2. Determination of pH was carried out

using distilled and dionized water, using 0.01 M calcium chloride solution as well as 1 M

potassium chloride. An Accumet pH meter model 925 was used. Before pH measurement the

meter was calibrated using buffers of pH 4, 7 and 10. For basic soils, buffers with pH 7 and pH

10 were used. For acidic soils buffers of pH 4 and pH 7 were used for the meter calibration. The

sample was allowed to equilibrate for 5 minutes before the reading was taken.

Organic Carbon and Organic Matter Determination

Organic carbon (OC) was determined using Walkley and Black (WB), while OM content

was determined using thermogravimetric analysis (TG) and weight loss on ignition (WLOI).









Sample homogenization

Before WB and TG analysis, whole soil sample homogenization was achieved in a Spex

CertiPrep mixer/ball-mill model 8000M by placing the samples in a Lucite grinding vial

containing two plastic balls and ball milling for 10 minutes.

Walkley and Black method (WB)

OC was determined using WB method (Walkley and Black, 1934) and OM by TG method

(Schnitzer and Hoffman, 1965; Karathanasis and Harris, 1994). WB %OC was determined by

weighing an amount of soil corresponding to the color of the soil. For the dark soils, 0.5g

samples were weighed into a 250 mL volumetric flask and 2.5 g for the light soils. To the soil

was added 10 mL of IN potassium dichromate (49.04 g of potassium dichromate were dissolved

per liter of solution) followed by 20 mL of concentrated sulfuric acid. The mixture was allowed

to digest for 1 hour. The digestion was stopped by adding distilled and de-ionized water to make

a total volume of about 200 mL. The mixture was allowed to cool for about 30 minutes and then

titrated against 0.5N ferrous sulfate using a Brinkmann Metrohm auto-titrator model 665

Dosimat. The ferrous sulfate solution was prepared by adding 138.30 g per liter of distilled water

and carefully adding 40 mL of concentrated sulfuric acid to the solution and then making it to

volume with distilled water. 5 drops of Ferrous sulfate complex indicator were added before the

titration. The end point of the titration was when the mixture turned from orange to green and

finally reddish-brown.

The OC content was calculated using the following equation:

% OC = {(mL of Blank)-(mL of sample)}* {Norm of FeSO4*0.3/0.77)/G of sample}

Where mL of Blank is the average titer value for the amount of FeSO4 required to reach

end point for a blank of acidified potassium dichromate. Norm is normality of FeSO4 and G of

sample is the weight of the sample taken based on the color of the soil.









Thermogravimetry (TG)

Thermogravimetric analysis (TG) was performed using a computer-controlled thermal

analysis system null microbalance Omnitherm Corporation TG Analyzer Unit model 25TG950

where the static position of the beam during weight loss is maintained by a restoring force. TGA

acquire software version 3.00.208, Instrument Specialists Inc 1996 was used to acquire data.

Whole grinded soil samples were analyzed using TG with weights that ranged from 9-15 mg.

The temperature program was set at 21-150 oC at a rate of 25 OC/min held for 0 min and raised

from 150-600 C at a rate of 5 OC/min, held for 0 min and finally raised from 600- 1000 C at a

rate of 25 OC/min. Thermo Analysis Software version 3.2, Instrument Specialists 1999 was used

to analyze the Thermograms. Calibration of the TG was achieved using a standard weight and

onset checked by using standard barium chloride (BaCl2.2H20) and standard calcite.

Weight loss on ignition (WLOI)

Five gram duplicate sieved samples (2 mm mesh) were weighed in a 50 mL beaker using a

Mettler balance (Model AE 100). The samples were placed in a hot air oven at 110 C for 24

hours. The samples were allowed to cool in a desiccator. The oven dry weight (Wod) was

recorded.

Muffle furnace

Weight loss on ignition was performed on the pre-heated samples at 450 C and 550 C for

12 hours. The samples were removed from the furnace, allowed to cool and their weight (Wf)

taken. Weight loss was calculated as:

WC -W
WLOI % = d x 100
W od









Carbon Stable Isotope Determination

The abundance of carbon isotopes (13C/12C) in the atmosphere and how plants incorporate

carbon can be used to characterize origin of OM. Inorganic carbon carbonatess) was removed

from carbonatic soils using 2M hydrochloric acid. 10 g were weighed in a 1 L beaker.

Hydrochloric acid was added slowly until there was no effervescence. Excess acid was added

and the soils were left to stand overnight to ensure complete removal of the carbonates. The soils

were centrifuged using a Beckman centrifuge Model J2-21 at 7000 rpm for 15 minutes. The

residue was washed twice with distilled water then transferred in a 50 mL beaker. The samples

were then allowed to dry in a hot air oven set at 40 oC, allowed to cool and then ground in a

mortar.

Sub-samples were measured in a tin capsule using a Sartorius M500P weighing balance.

The samples were analyzed using a Carlo Erba EA-1108 CE Elantech, Lakewood NJ, interfaced

with a Delta Plus (ThermoFinnigan) isotope ratio mass spectrometer. Carbon isotopes were

measured against a Vienna PeeDee Belemnite (VPDB) limestone standard. The results were

expressed using the delta notation (613C) in per mil (%o) deviation from the VPDB standard. The

Nitrogen isotope was measured against UF-N2 REF standard. Nitrogen values were expressed in

per mil (%o) deviation from air.

Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance
spectroscopy

The use of solid state 13C cross polarization magic angel spinning nuclear magnetic

resonance (CP-MAS NMR) can be useful in characterizing carbon in OM.

Soil treatment for Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic
Resonance spectroscopy analysis

20 g soil samples were weighed in a 1 L plastic beaker. The samples were treated with a

total of 200 mL of 2M hydrochloric acid. To avoid spill over, the acid was carefully added for









soils with high inorganic carbonate content. The samples were left to stand for 24 hrs and then

centrifuged at 12000 rpm. The supernatant was carefully decanted. The residue was washed three

times with DDI water followed by subsequent centrifuging at 12000 rpm. The residue was then

treated with 70 mL of 10% hydrofluoric acid (HF acid was used cautiously). The treatment was

repeated 5 times by shaking the mixture for 1 hr and centrifuging at 12000 rpm for 20 minutes

followed by a treatment for 16hrs and a last treatment of 64 hrs. The samples were then washed

four times with DDI water to remove HF and then dried in a hot air oven set at 40 oC. The

residue was homogenized using Spex CertiPrep mixer/ball-mill model 8000M in a Lucite

grinding vial with plastic balls. The treated soil samples were then analyzed using CP-MAS 13C-

NMR.

Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance
spectroscopic determination

The pre-treated samples were packed in cylindrical zirconia rotors (80 uL, 4 mm outer

diameter) and sealed using KelF end caps. Solid state CP-MAS 13C NMR analysis was

performed using a Bruker 400 MHz Avance II spectrometer and a CP-MAS probe set at magic

angle (54.70). In order to reduce spectral errors, samples were run with variable contact time

pulse sequence (Conte et al., 1997; Piccolo et al, 2005) to establish optimum contact times.

Spectra were obtained with spinning rates of 13 KHz, TPPM decoupling, 1.5 ms contact time

(found to be optimum for all C functionalities in the soils analyzed), 1.5 s recycle delay, spectral

width of 50 kHz and 2000 scans or more. The spectra were processed using 100 Hz line

broadening and baseline correction.

Bloch decay (DPMAS) experiments were performed (on selected samples) at 900 pulse of

5 [is and were detected in the presence of TPPM decoupling. In order to achieve 13C relaxation, a

recycle delay of 10-60 s was used. Due to excessive baseline noise, cross polarization was









performed on all samples since it yielded better spectral results. In order to minimize errors in

peak area evaluations, we performed variable contact time pulse sequence tests to optimize the

13C signal. A contact time of 1.5 ms was found to be optimum for the analyses. The areas in the

chemical shifts regions were integrated as a percentage of total area (relative intensity).

The chemical shifts (Table 3-2) adopted for this study were: Alkyl-C (0-50 ppm);

Methoxyl (50-60 ppm); O-Alkyl (Carbohydrate) (60-95 ppm); Di-O-Alkyl (95-110 ppm);

Aromatic (110-145 ppm); Phenolic (145-160 ppm); and Carbonyl-C (Amide) (160-200 ppm).

These spectral regions have been further segmented as unsubstituted alkyl-C alkaness and fatty

acids) (0-35 ppm); N-alkyl-C, Quaternary C (35-50 ppm); Methoxyl C (amino acids, peptides,

protein C) (50-60 ppm); aliphatic C-O (carbohydrates) (60-108); aromatic (unsaturated and

saturated C) (108-145); phenolics (145-160); carboxyl-C carboxylatee, esthers, ketones,

aldehydes) (160-220) (Stevenson, 1994).

Sorption of Pesticides on Soils

The batch slurry method (Wauchope et al., 2002; Weber, 1986) was used to measure the

sorption isotherms and to determine the sorption coefficients of hydrophobic organic (HOCs).

The equilibrium concentrations (Ce) were determined using HPLC and the adsorbed

concentration (Se) was determined by difference from original concentration. Sorption data for

HOCs have often been described using the Freundlich model (Equation 3-1) (Albanis et al 1989;

Clay and Koskinen 1990).

S,= KrC~e [3-1]

where Kf is Freundlich sorption constant (L/kg), N is the Freundlich coefficient dimensionlesss).

Given S, = KrfC,


Kd = e NK, C [3-2]
dCe









As N approaches 1 Kd approximates to Kf. At Ce = 1 Kd = NKf.

Hence within the linear range of the isotherm (low concentration), as the value of the Freundlich

coefficient approximates 1.0, the Freundlich equation reduces to the linear isotherm equation:

Se = Kd Ce [3-3]

where Kd is the distribution coefficient (L/kg).

Since we worked within the linear range of the isotherm, the data in this study was fitted

using the linear model in order to determine the sorption coefficients. The adsorption coefficients

(Kd) were normalized with OC.

The maximum amount of soil (m) that will give equilibrium solution concentration (Ce) to

be in the linear range of the isotherm was calculated based on the linear equation (Eq. 3-3) and

the mass balance Eq. 3-4.

CoVo= mSe + CeVo [3-4]

where Co = Initial solution concentration; Vo = Total volume of solution; m = mass of soil added

to solution. Substituting Equation 3-3 in Eq. 3-4, yields Equation 3-5.

CoVo= m Kd Ce + CeVo [3-5]

Rearranging eqn 3-4

Co mK,
S mKd+1 [3-6]
Ce Vo

assuming maximum initial concentration (Co) = 10 [tg/mL, Volume of pesticide added (Vo) = 10

mL with an adsorption coefficient (Ko) =100 and % soil OC = 2 %. From the literature

adsorption coefficient (Ko) we can estimate the compound's distribution coefficient (Kd):

Kd = Koc*foc [3-7]

Kd = 100 0.02 = 2









If we set the maximum solution coefficient after equilibration (Ce) at 5 atg/ml, then the

mass of soil (m) weighed =

10 m*2
-=-+1 m<5g
5 10

However this is just an estimation basing on the assumption that sorption increases with

increase SOM content.

Atrazine and ametryn were determined at the same parameters with the wavelength set at

230 nm and flow rate of 1.5 mL/min for ametryn while the wavelength for atrazine was set at

220 nm. 10 uL were injected and the mobile phase used was methanol (60 %), water (30 %)

acetonitrile (10 %) v/v.

Diuron was determined at the same parameters except the wavelength was set at 250 nm

and a flow rate of 2.0 mL/min.

Pesticide Degradation

5 g soil samples were weighed in to triplicate 50 mL polycarbonate centrifuge tubes

(Figure 3-3). The samples were fortified by an aqueous solution of a pesticide with concentration

ranging between 20 mg/L to 100 mg/L. The amount of standard added was based on a

predetermined soil moisture content equivalent to 60 % of the soil water holding capacity. The

mixture was allowed to stand for about 30 minutes and then stirred with a spatula to allow

homogenous distribution of the pesticide. Extraction frequency was based on the literature

pesticide degradation with the more persistent pesticides sampled less frequently compare to

those with faster degradation rates.

Extraction was achieved by shaking the soil sample with 20 mL of methanol for three

hours, centrifuging the mixture for 10 minutes and filtering the supernatant through a Fisher

Brand Q2 filter paper into a 25 mL volumetric flask. The residue was extracted with an









additional 10 mL methanol for 2 hours and centrifuged for 10 minutes. The extracts were

combined and made to volume with methanol. The extracted sampled were transferred in to a

screw capped sample vial and stored at -20 C until analysis. The extracted samples were then

analyzed by HPLC.

In this study, degradation is operationally defined as the disappearance of the parent

compound. The disappearance of pesticide which is known as first order reaction is proportional

to amount left in the soil and this has been found to describe a wide range of pesticide

degradation rates (Zimdahl and Gwynn, 1977; Morrill et al., 1982). The first order kinetics rate

equation can be written as:

Rate = kMo [3-8]

Where Mo is the initial concentration and k the rate constant.

dM
Equation 3-8 is mathematically transformed to- = kM which upon integration and
dt

transformation reduces to:

M
log = -kt [3-9]
M0

Equation 3-9 is rearranged to:

M, = Mo e Kt [3-10]

where Mo = VCo and is the initial soil concentration in mg/kg; V (mL) is the added volume and

Co (mg/L) is the solution concentration; Mt (mg/kg) = Concentration at time t (days); k (1/day) is

the decay constant. Equation 3-10 which is conventionally used was modified to equation 3-11

because the initial concentration and the recovered amount differed for the soils analyzed. The

calculated k was therefore not based on (Mo/Mt).









t M e-Kt [3-11]
f *
where Mo is the added pesticide concentration in mg/kg of soil;"f is the method extraction

efficiency. Log transformation of Equation 3-11 yeilds Equation 3-12:

Ln(M,) = Ln(Mof *)- kt [3-12]

The decay equation was modified so that the decay constant was not dependent on the

initial concentration. The decay constant k, was the slope obtained by plotting Ln(M,) against

time t. The intercept [Ln(Mof*) ] is a function of the initial concentration corrected for

laboratory recovery. The pesticide half-life (tl/ 2) is calculated from:

k = 0.693/t1/2 [3-13]










Table 3-1. Description of the sampling sites in Florida U.S.A. and Puerto Rico


GPS location


Classification
Florida soil


Biscayne

Chekika

Cudjoe

Keyvaca

KeyWest

Krome

Lignumvitae

Pennsuco

Perrine

Perrine-Tamiamit

Saddlebunch
Monteocha
Pomona
Islamorada
Lauderhill
Matecumbe
Tamiami


NA

NA

240 57 231 N 0800 35 013 W

240 41 923 N 0810 22 515 W

240 41 445 N 0810 06 274 W

NA

240 57 068 N 0800 35 473 W

250 28 340 N 0800 23 221 W

NA

250 45 202 N 0800 28 940 W

240 39 136 N 0810 30 945 W
290 44 784 N 0820 15 841 W
290 41 484 N 0820 13 002 W
250 09 550 N 0800 23 204 W
250 58 731 N 0800 25 885 W
NA
250 45 203 N 0800 28 982 W


Loamy, carbonatic, hyperthermic, shallow Typic
Fluvaquents
Loamy-skeletal, carbonatic, hypothermic Lithic
Udorthents
Loamy, carbonatic, isohyperthermic, shallow
typic Fluvaquents
Loamy-skeletal, carbonatic. Isohyperthermic
Lithic Haprendolls
Coarse-silty, carbonatic isohyperthermic Thapto-
histic Fluvaquents
Loamy-skeletal, carbonatic, hypothermic Lithic
Udorthents
Coarse-silty, carbonatic isohyperthermic Typic
Fluvaquents
coarse-silty, carbonatic, hyperthermic Typic
Fluvaquents
coarse-silty, carbonatic, hyperthermic Typic
Fluvaquents
coarse-silty, carbonatic, hyperthermic Typic
Fluvaquents
Loamy, carbonatic isohyperthermic, shallow
Typic Fluvaquents
Sandy, siliceous, hyperthermic Ultic Alaquods
Sandy, siliceous, hyperthermic Ultic Alaquods
Euic, isohyperthermic Lithic Haplosaprists
Euic, hyperthermic Lithic Medisaprists
Euic, isohyperthermic Lithic Tropofolists
Euic, hyperthermic Lithic Medisaprists


Puerto Rico Soils


Aguilita
Catan6
Colinas

San Sebastian

Tuque

Yauco

Banyamon

San Anton


18 00 101 N 0660 48 712 W
180 30 765 N 0670 03 302 W
18 22 507 N 0670 01 278 W

180 22 798 N 0670 01 315 W

170 58 502 N 0660 41 035 W

180 01 817 N 0660 31 397 W

180 25 807 N 0660 26 192 W

180 01 613 N 0660 31 580 W


NA Not Available. Source: Soil Survey Staff, USDA-NRCS Official
Tamiami map unit.


Coarse-loamy, carbonatic, isohyperthermic Aridic
Calciustolls
Carbonatic, isohyperthermic Typic Udipsamments
Coarse-loamy, carbonatic, isohyperthermic Typic
Haprendolls
Clayey-skeletal, carbonatic, isohyperthermic
Calcic Argiudolls
Clayey, carbonatic, isohyperthermic Calcic Lithic
Petrocalcids
Fine-silty, carbonatic, isohyperthermic Typic
Calciustolls
Very-fine, kaolinitic, isohyperthermic Typic
Hapludox
Fine-loamy, mixed, superactive, isohyperthermic
Cumulic Haplustolls
Soils Descriptions. Perrine-Tamiami t is an inclusion in the


Soil series










Table 3-2. Description of the sampling sites in Uganda East Africa


Classification
Uganda soils (Oxisols)


Fiduga 1 000 15 847 N 0320 24 655 E
Fiduga 2 000 16 061 N 0320 24 505 E
Fiduga 3 00 15 911 N 0320 24 595 E
Fiduga Pooled 000 15 911 N 0320 24 595 E
Hima 1 NA
Hima 2 NA
Hima 3 NA
Hima Lime NA
Hima Pooled NA
Kakira 1 NA
Kakira 2 NA
Kakira 3 NA
Kakira Pooled NA
Kasaku 1 000 20 436 N 0320 53 907 E
Kasaku 2 000 20 505 N 0320 54 050 E
Kasaku 3 000 20 459 N 0320 54 077 E
Kasaku 4 000 20 870 N 0320 53 889 E
MK Flora 1 NA
MK Flora 2 000 15 982 N 0320 23 985 E
MK Flora 3 00 15 928 N 0320 23 982 E
MK Flora 4 000 15 978 N 0320 23 927 E
MK Flora Pooled NA
Muhookya 1 NA
Muhookya 2 000 06 194 N 0320 03 224 E
Muhookya 3 NA
Muhookya Pooled NA
Rubaabo Sediment NA
ScoulLugazi1 NA
Scoul Lugazi 2 000 23 642 N 0320 56 503 E
Scoul Lugazi 3 00 23 957 N 0320 56 525 E
ScoulLugazi 4 NA
Scoul Lugazi Pooled NA
Wagagai 1 000 03 651 N 0320 30 829 E
Wagagai 2 000 03 654 N 0320 30 858 E
Wagagai 3 000 03 619 N 0320 30 853 E
Wagagai Pooled 000 03 654 N 0320 30 858 E
NA=Not Available. Soil classification: Selvaradjou


Agricultural Organisation/European Union classification in parenthsis.


Buganda Catena (Ferrallitic soils)
Buganda Catena (Ferrallitic soils)
Buganda Catena (Ferrallitic soils)
Buganda Catena (Ferrallitic soils)
Kasese series (Lithosols)
Kasese series (Lithosols)
Kasese series (Lithosols)
Kasese series (Lithosols)
Kasese series (Lithosols)
Kabira Catena (Ferrisols)
Kabira Catena (Ferrisols)
Kabira Catena (Ferrisols)
Kabira Catena (Ferrisols)
Mabira Catena (Ferrisols)
Mabira Catena (Ferrisols)
Mabira Catena (Ferrisols)
Mabira Catena (Ferrisols)
Buganda Catena (Ferrallitic soils)
Buganda Catena (Ferrallitic soils)
Buganda Catena (Ferrallitic soils)
Buganda Catena (Ferrallitic soils)
Buganda Catena (Ferrallitic soils)
Kasese series (Lithosols)
Kasese series (Lithosols)
Kasese series (Lithosols)
Kasese series (Lithosols)
Bugangari series (Lithosols)
Mabila Catena (Ferrisols)
Mabila Catena (Ferrisols)
Mabila Catena (Ferrisols)
Mabila Catena (Ferrisols)
Mabila Catena (Ferrisols)
Katera series (Ferrallitic soils)
Katera series (Ferrallitic soils)
Katera series (Ferrallitic soils)
Katera series (Ferrallitic soils)
et al., 2005. Local classification and Food


Soil series


GPS location









Table 3-2. Carbon-13 cross polarized magic angle spinning nuclear magnetic resonance chemical
shifts for soil organic matter
Functional group Shift Functional group further segmentation Shift
(ppm) (ppm)


Alkyl-C
Methoxyl
O-Alkyl /Carbohydrate
Di-O-Alkyl
Aromatic
Phenolic
Carbonyl-C (Amide)

Source: Stevenson, 1994.


0-45
45-60
60-95
95-110
110-145
145-160
160-200


Alkyl-C alkaness and fatty acids)
N-alkyl-C, Quaternary C
Methoxyl (amino acids, peptides, protein C)
Aliphatic C-O (carbohydrates
Aromatic (unsaturated and saturated C)
Phenolics
Carboxyl-C carboxylatee, esthers, ketones,
aldehydes)


0-35
35-50
50-60
60-108
108-145
145-160
160-120


































Figure 3-1. Typical rock-plowed carbonatic soil from Homestead, Miami Dade County South
Florida. Gravely, well drained soils.



































Figure 3-2. Algal derived secondary calcite flakes precipitation leading to formation of marl
carbonatic soils.




























AMETRYN DEGRADATION
01-20-2006


Figure 3-3. Set up of the degradation of pesticides in polycarbonate tubes with loose covers to
prevent excessive moisture loss.









CHAPTER 4
ORGANIC MATTER CHARACTERIZATION IN CARBONATIC AND ASSOCIATED
SOILS FROM SOUTH FLORIDA AND PUERTO RICO USING THERMAL AND
OXIDATION METHODS

Introduction

Soil organic carbon (OC) is commonly determined by use of oxidation processes that were

originally developed by Schollenberger (1927) and Degtjareff (1930), modified by

Schollenberger (1931) and later by Walkley and Black (1934). Though the Walkley-Black (WB)

procedure was suggested for quick and approximate determination of OC (Walkley, 1947), this

oxidation method is still widely used for rapid determination of soil OC. However, there is no

universal method for determining the OC content of organic matter (OM) for all soils due to the

presence of compounds in numerous soils that may interfere with OM determination. A

disadvantage of the WB method is its generation of large amounts of toxic dichromate waste and

possible interference from soils constituents such as oxides of iron and manganese (Walkley,

1947). In addition, the method requires the use of a correction factor (1.32) to cater for the

incomplete conversion averaging 76 % achieved, from organic carbon to carbon dioxide

(Walkley and Black, 1934; Schollenberger, 1945). Alternative methods have since been

developed that include thermal methods and elemental analysis. Elemental analysis involves

determination of total carbon while thermal method determinations follow weight loss due to

decomposition of OM. The use of thermal methods for determination of OM dates as far back as

the late 1940s (Mitchell and Bimie, 1970). Some studies (Schnitzer and Hoffman, 1965; Mitchell

and Birnie, 1970; Critter and Airoldi, 2006) have used thermal methods to characterize the

physical and chemical nature of OM. The applicability of thermal methods to OM analysis relies

on the premise that the soils do not contain compounds like gibbsite, smectite and kaolinite clays

that decompose within the same temperature range (200-550 C) as OM (Mackenzie, 1970;









Karathanasis and Harris, 1994). Thermal methods are not appropriate for analysis of Oxisols and

other soils that contains large amounts of clay-sized minerals that undergo dehydroxylation or

other mass losses in the temperature range of OM combustion. Following decarbonation of

inorganic C with hydrochloric acid, total organic carbon (TOC) can be determined by elemental

analysis. However, the treatment step may affect purgeable OM (Motter and Jones, 2006). Total

C on the other hand may be used but this requires knowledge of carbonate amounts in carbonatic

soils in order to determine organic carbon by difference.

The presence of OM in soils can influence factors like soil fertility, soil carbon cycling and

sequestration, water and nutrient retention capacity, bulk density, soil aggregation and xenobiotic

retention. An accurate determination of OC is necessary in order to calculate the sorption

coefficient (Ko) of hydrophobic organic chemicals (HOCs) whose retention in soils is

predominantly associated with soil OC (Nkedi-Kizza et al., 2006; Wauchope et al., 2002; Nkedi-

Kizza et al., 1983). The sorption coefficient (Kd) of HOCs in soils is normalized with the fraction

of organic carbon (foc) present in soils (Koc = Kd/foc), and if OC is inaccurately determined, the

Koc calculated may be in error. Soil OC and OM are often determined indirectly depending on

the method used. A conversion factor is then used to convert from one parameter to another. The

applicability of the commonly used factor of 1.724 also known as the van Bemmelen factor

(Westman et al., 2006; Hana, 1964; van Bemmelen, 1891), to all soils has been contested by

researchers dating as far back as 1953 (Lowther et al., 1990; Howard and Howard, 1989;

Ranney, 1969; Broadnet, 1953). This is due to variability in nature and composition of OM, and

thus using the factor to convert WLOI data to OC can lead to serious errors. The fundamental

differences in SOM composition, may explain to a large extent the variability of Ko values

found in the literature for a given neutral organic chemical (Wauchope et al., 2002).









The objective of this study was to use thermogravimetry (TG), weight loss on ignition

(WLOI), and the WB methods to explore the relationship between OM content and OC content

for three categories of soils: Carbonatic soils, associated Histosols, and Spodosols. TG provides a

highly sensitive and accurate simultaneous determination of OM and carbonates in a soil sample.

Unlike WLOI which is carried out "blindly" in the muffle furnace, using a microbalance in the

TG method provides a continuous weight loss recording and insight on the onset temperatures

for decomposition reactions, thus giving a more accurate determination of soil components.

Materials and Methods

Surface soil samples (0-15 cm) were collected for three soil types encompassing a wide

range of vegetation and OM. Carbonatic soils from South Florida and Puerto Rico, classified as

Entisols and Mollisols, associated Histosols from South Florida, and Spodosols from Alachua

County were collected for this study. The detailed sites descriptions are available in Chapter 3.

Sample Homogenization

Before WB and TG analysis, whole soil sample homogenization was achieved in a Spex

CertiPrep mixer/ball-mill model 8000M by placing the samples in a Lucite grinding vial

containing two plastic balls and ball milling for 10 minutes.

Organic Carbon, Organic Matter and Carbonate Determination

Prior to analysis, sample homogenization was performed as described in Chapter 3.

Organic carbon was determined using WB method (Walkley and Black, 1934) and OM by TG

method (Schnitzer and Hoffman, 1965; Karathanasis and Harris, 1994). Detailed %OC

determination by WB is described in Chapter 3.

Florida soil characterization data (Noble et al., 1996; Hurt et al., 1995) for series of

carbonatic soils and Spodosols used in this study indicate that their surface horizons do not

contain significant proportions of minerals that would undergo weight loss reactions in the









temperature range of OM combustion. Hence thermal methods are considered appropriate for

determining OM content of these soils. Mineralogical analyses were not determined for Histosols

due to their high OM content.

TG analysis was performed using a computer-controlled thermal analysis system null

microbalance where the static position of the beam during weight loss is maintained by a

restoring force. The temperature program was set as described in Chapter 3. Calibration of the

TG was achieved using a standard weight and onset checked by using standard barium chloride

(BaCl2.2H20) and standard calcite (CaCO3). Weight loss on ignition was carried out as described

in Chapter 3.

Results and Discussion

Standard CaCO3 loses 44 g of carbon dioxide per 100 g of the carbonate and in the check,

a loss of 44 % between 600-800 C was observed (Figure 4-1) while BaCl2.2H20 (not shown)

lost 14.5 % between 75-160 C corresponding to water of crystallization (theoretical weight loss

= 14.75 %). Some workers (Westman et al., 2006; Smith, 2003) have indicted that inorganic

carbon in calcareous soils may decompose if these soils are heated at 550 C. The result of this

study (Figure 4-2) show that calcium carbonate decomposition is energy dependent rather than

time dependent and requires temperatures as high as 600 C to decompose. Using TG, standard

carbonate was heated from room temperature to 550 C and the T was held at 550 C for two

hours and thereafter increased to 1000 C. It can be seen that the loss in weight was negligible

between room temperatures and 597 C even during the isothermal temperatures of 550 C

(Figure 4-2 A and B). Similar onset temperatures (600 C) for carbonate decomposition in

carbonatic soils were observed (Figure 4-3A) suggesting that even in the presence of other soil

components, the temperatures for carbonate decomposition is unchanged. Based on the results of

this study, presuming that the oven temperatures is accurate and is maintained at constant









temperatures, it is unlikely that a temperatures of 550 C, if used in WLOI would cause loss of

inorganic carbon carbonatess).

The data in Figure 4-3(A) show the inflection temperatures for OM and carbonates from a

carbonatic soil. The inflection between 200 and 550 C was attributed to OM decomposition

while that between 600 and 800 C was ascribed to CaCO3. It was observed (Figure 4-3B) that

even after oven treatment of Histosols at 105 oC, the Histosols continue to lose considerable

weight between 105 to 200 C which was not the case for the mineral soils analyzed. Similar

weight losses between 25-150 C were observed by Critter and Airoldi (2006) in TG

thermograms of humic acids. The onset temperature for OM decomposition is about 200 C

(Karathanasis and Harris, 1994; Barros et al, 2007) hence the weight loss between 105 and 200

C (Figure 4-3B) cannot be attributed to OM decomposition. A temperature program was

performed that involved heating of the soil sample to 180 oC, allowing it to cool down to ambient

T in the TG oven and reheating to 1000 C (Figures 4-4 and 4-5). Histosol samples regained the

lost weight in one hour which indicates that the reaction is reversible and fast. This implies that

some component of the Histosols, possibly OM itself, has a strong tendency to retain or re-

adsorb water even at temperatures > 100 C. However, we did not find a correlation between the

quantity of OM and the 105-200 C weight loss, suggesting that water loss from an unknown

inorganic component could also be responsible for the weight loss. The weight loss between 105

and 200 C could not be attributed to loss of labile organic components because their loss should

be irreversible. Unlike Histosols (Figure 4-3B), there was no significant weight loss between 105

and 200 C for mineral soils. Implications are that WLOI is not a reliable measure of OM even

for predominantly organic soils unless the procedure is modified to account for weight loss at

temperature < 200 C that are not attributable to OM combustion. Some Histosols showed two









distinct inflection points between the 200-550 C, with peak maxima at 280 and 480 C probably

indicating that Histosols contain the heat labile and heat stable fractions of organic matter with

the later requiring higher temperature (400-500 C) for decomposition. No mass loss over time

was observed when the sample temperature was held at 105 C for one hour. Weight loss was

observed when the sample was heated to 180 C, indicating the reversible mass loss (presumably

water desorption) is energy rather time dependent (Fig. 4-5). Possibly it relates to the dominant

influence of the sawgrass detritus.

The results obtained from correlation between TG %OM and WB %OC indicate that the

slopes for Carbonatic soils differ from those of Histosols and Spodosols (Figures 4-6A, 4-6B,

and 4-6C). This may be due to differences in the nature of OM, as influenced by sources of C

pools in these soil categories. The conversion factor 1.74 0.12 ( 0.12 is the 95% CI), for

Carbonatic soils, unlike those of the Histosol (1.48) and Spodosol (1.44), closely corresponds to

the literature conversion factor of 1.724. However, this factor is not universally applicable due to

the inherent heterogeneity and complexity of OM composition and functionality, as documented

in this study.

It is possible that the OC content of OM in Carbonatic soils differs from that of other soils

due to its hydrologic and biological setting. Marl formation is driven by algal and periphyton

photosynthesis and algal mats constitute the majority of the OM pool present in these soils as

compared to Histosols, whose major OM source is sawgrass, and Spodosols, which are strongly

influenced by forest litter. Possibly the composition of OM in carbonatic soils has lower affinity

for water compared to the OM derived from higher plants like sawgrass and forest litter. The

carbon content in humic acids is assumed to range from 53.8 to 58.7 percent (Stevenson, 1994).

Using this relationship yields a conventional equation: %OC = 0.58 %OM. Data in Figure 4-









6B on the other hand, show a mean factor of 1.48 0.08 for Histosols. This conversion factor

suggests that Histosols may have a higher percent OC per gram of OM of about 64-72 %

compared to common mineral soils whose colloidal SOM is assumed to contain 58% OC. Hence

using a conversion factor targeted to mineral soils may result in underestimating organic carbon

content in Histosols. Statistical analysis showed a difference in TG and WLOI methods (a=0.05)

for Histosols. The source of the difference between the two methods was attributed to the ability

oft Histosols to retain sufficient amounts of water even after heating it in an oven at 105 C for

24 h. The common practice involves heating soils at 105 C to remove moisture and then the

subsequent loss in the muffle oven is ascribed to OM. Organic matter accretion in Histosols of

South Florida is due to inundation of poorly drained soils with water for most part of the year

causing anaerobic conditions that slow down OM oxidation. Carbonatic soils form under

relatively similar conditions but the difference in the hydrologic regimes and OM pools (algal

derived) may explain the difference observed in carbonatic soils in terms of water retention.

The conversion factor obtained by correlation of TG %OM with WB %OC for Spodosols

(Figure 4-6C) was 1.44 0.10. Spodosols were included in this study due their prevalence in

Florida and the state soil "Myakka" is classified as Spodosols. The conditions required for

Spodosols development include acid litter from forests and high precipitation and seasonal water

table for most part of the year. This accordingly results in translocation and accumulation of

organo-metallic complexes of aluminum, iron, silica and OM from upper horizons to the Spodic

horizon. The wet conditions probably slow down the oxidation process resulting in OM with a

higher OC content hence the observed conversion factor of less that 1.74 used in the literature for

mineral soils.









The effect of temperature on WLOI results was investigated by determining OM at 450 C

and 550 C. An increase in weight loss was observed after heating the sample at 550 C though

statistical analysis showed no difference between the two temperature set points. Weight loss on

ignition (Figure 4-7) yielded a conversion factor of 1.76 + 0.09 for Histosols. The high

correlation (R2 = 0.95) obtained between WLOI % OM and WB %OC (Figure 4-7) suggests that

the water of hydration is associated with OM. No difference ( a = 0.05) was observed between

soil carbonate content determined by TG and carbon dioxide coulometric measurements.

Data obtained from all three methods for OC, OM and carbonates are summarized in

Tables 4-1 to 4-3 for the soils studied. OC in carbonatic soils ranged between 1.17-11.37 %

while carbonates ranged 47-94 %. The OC content for Histosols and Spodosols ranged 9.47-

53.37, and 0.85-5.32 %, respectively. It is evident that TG and WLOI methods predict OM well

in carbonatic soils (Figure 4-8) with a conversion factor of essentially one between the two

methods. A statistical analysis of the two methods showed no significant difference. However, in

addition to simultaneous determination of carbonates, the TG method provides more insight on

the onset points thus providing a better estimate of reaction taking place during soil combustion.

XRD analysis of carbonatic soils indicated the presence of calcite at D spacing = 3.84 and

3.03 (Figure 4-9) as the major mineral in these soils. The absence of minerals that can interfere

with OM analysis and the fact that the amount of OM present may not be sufficient to abstract

water makes thermal methods suitable for estimation of OM in carbonatic soils. Basing on the

XRD for carbonatic soils and the fact that these soils are associated in South Florida, but

differing in formation in terms vegetation and hydrologic regimes, it is unlikely that the observed

loss of water (between 105-180 C) is associated minerals in Histosols other than OM.









The regression analysis of TG %OM with WB %OC obtained for Oxisols from Uganda

resulted in a conversion factor of 3.91 (data not shown) which confirms that thermal methods are

inappropriate for analysis of OM in Oxisols. XRD (Figure 4-10) confirmed presence of kaolinite

(7.19 and 3.57) and hematite (2.69 and 2.51) minerals in these highly weathered soils. The

presence of these minerals in the Oxisols may hinder use of thermal methods in the analysis of

OM in Oxisols. A relatively well defined peak with maxima between 450-520 C was observed

in the Oxisols. The peak between 450 and 520 C could be due to decomposition of kaolite along

side the more thermally stable moieties of OM such as aromatic groups.

Conclusions

The OC content of OM was similar for the Histosols and Spodosols studied, but was

significantly higher than what would be calculated from the common conversion factor of 1.724.

However, this factor was reasonably close to that determined for the Carbonatic soils (1.74). The

Carbonatic soils, Histosols, and Spodosols studied differ in primary producers, i.e., algae,

sawgrass and forest litter respectively. A single conversion factor is not realistic for all soils,

given the spatial and compositional variability of OM. Since the predominant mineral in

carbonatic soils is calcite, their OM and calcite content can be determined simultaneously with

TG. The conversion factors of 1.48, and 1.44 for Histosols and Spodosols, respectively, obtained

in this study indicate that these soils may contain more OC per gram of OM. The use of 0.58 to

convert OM to OC may result in underestimation of OC in Histosols and Spodosols. The fact

that Oxisols contain minerals like kaolinite that interfere with OM analysis renders thermal

methods inappropriate for determination of soil OM in Oxisols.

Results of this study document that 1) OC content of OM differs significantly between

soils of different hydrologic and vegetative settings, and 2) WLOI is not a reliable measure of

OM, even for organic soils, unless weight loss below 200 C is taken into account.










Table 4-1. Organic carbon (OC) and organic matter (OM) determination in carbonatic soils
using WB, TG, and WLOI methods, and carbonates. Soils sampled 0-15 cm.
Soil WLOI WLOI Carbonates %
Carbonatic soil origin WB % TG % %OM %OM
name OC OM a C atCO2
at 450 oC at 550 oC TG
Coulometry


Aguilita
Biscayne 1
Biscayne 2
Biscayne 3
Cudjoe
Chekika
Chekika 2
Colinas
Key Vaca
KeyWest 1
KeyWest 2
Krome 1
Krome 2
Legumnivitae 1
Legumnivitae 2
Pennsuco
Perrine 1
Perrine 2
Saddle Bunch 1
Saddle Bunch 2
San Sebastian
Tuque
Yauco


4.79
5.69
2.91
4.15
10.15
2.05
4.10
2.39
11.38
1.22
1.17
1.49
2.28
6.12
4.71
2.74
2.92
2.89
1.71
8.06
2.25
2.35
7.56


10.32
9.42
5.93
6.78
17.85
4.01
8.77
5.01
19.03
3.30
2.80
3.77
6.47
9.04
7.43
5.73
5.16
4.16
1.80
11.80
5.88
5.22
5.36


10.18
10.30
6.09
7.16
18.89
4.45
8.97
5.33
19.06
3.14
3.21
4.47
6.65
9.92
9.20
6.34
5.58
4.98
3.61
14.82
6.12
4.93
7.29


13.32
11.73
8.27
7.61
22.72
6.58
12.63
8.99
21.33
7.50
6.40
7.44
9.45
11.63
10.92
7.40
6.24
5.39
4.43
15.51
7.36
6.11
9.39


56
75










Table 4-2. Organic carbon (OC) and organic matter (OM) determination in Histosols from
Florida (FL) and Puerto Rico (PR) using WB, TG, and WLOI methods.
Soil Soil WLOI WLOI Carbonates
Histosols WB % TG %
Histools origin Depth WB TG %OM %OM %
soil name OC OMC at 550 C by TG
(cm) at 450 oC at 550 oC by TG


Dania 1
Dania 2
Islamorada
Lauderhill 1
Lauderhill 2
Lauderhill 3
Matecumbe 1
Matecumbe 2
Pahokee 1
Pahokee 2
Tamiami 1
Tamiami 2
Tamiami 3
Tiburones
Torry 1
Torry 2


0-15
15-30
0-15
0-15
0-15
0-15
0-15
0-15
0-15
15-30
0-15
0-15
0-15
0-15
0-15
15-30


42.91
53.37
38.79
28.74
20.98
22.73
32.47
19.76
42.30
47.11
40.05
19.78
39.72
9.47
12.78
9.63


71.64
70.77
53.63
44.21
32.35
35.00
47.08
42.61
62.84
66.71
58.10
26.36
59.78
16.13
20.79
18.92


84.97
85.73
67.36
49.64
32.88
41.04
54.06
47.73
78.52
82.67
66.03
28.43
68.96
15.57
20.11
17.74


85.25
85.93
68.03
50.38
33.43
41.77
54.43
48.83
78.91
82.95
66.66
28.84
69.63
16.79
22.69
19.68


7
8
10
10
18
0
11
0
10
9
0
54
5
5
0
34


Table 4-3. Organic carbon (OC) and organic matter (OM) determination in Spodosols using WB,


TG and WLOI methods.
Soil
Spodosol name Soil Soi
or horizon origin depth
(cm)
Monteocha 1 FL 0-15
Monteocha 2 FL 0-15
Pomona 1 FL 0-15
Pomona 2 FL 0-15
Pomona 3 FL 0-15
Pomona 4 FL 0-15
Pomona E FL 15-30
Pomona Bh-1 FL 80-95
Pomona Bh-2 FL 80-95
Pomona Bh-3 FL 80-95


WB
%
OC
5.32
1.12
0.85
2.32
1.12
2.04
0.21
0.89
1.83
0.62


TG
%
OM
7.53
1.73

3.13
1.75
3.37
0.48
1.84
3.00
1.03


WLOI %OM
at 450 C
8.55
2.71
1.60
3.66
2.23
4.07
0.28
2.32
4.07
2.44


WLOI %OM
at 550 C

8.58
2.73
1.62
3.68
2.25
4.09
0.28
2.43
4.13
2.48

















10





.m 73

70
: 2

2




0 100 2an 11 Sa00 a EDO Tom Uo sO 100]
Tei pe ti r ( C)


Figure 4-1. Verification of the TG calibration using standard calcium carbonate. Line 1 is weight
loss, while line 2 is 1st temperature derivative.



































0 10 2M 30m 4m sm 6B T7 3S 9s0 1i
Tem p rat re ('C)


28 min


0 2 10 e6 EU
Ttn e (i 1k)


148 min


ut Loss:
3-9T %







160.1 ml


I


100 120 140 160


Confirmation for the onset decomposition temperature for calcium carbonate
preheated to 550 C for 2 h, decomposition starts at 600 C. Line 1 Figure B is
temperature profile and Line 2 is the derivative for weight loss onset.


65

60

55






1m0. I


Figure 4-2.


_ ___ ___


S .1 s I


/ Temp. Held at 550 C for 2 h;
Wt Loss < 600 C = 0.02 %;
/Wt Loss > 600 C= 43.98 %


"






























Lo ss:2 35 45%


S12.I C


IlOlt Lo :: 0.695 %


Loss: 10517 %


0 1DD00 2D 40D S0D 60D 7T [0 ME] 90S 1Dooo
Tem pe rat re CC)





1 I it Loss: 7.931 %
195.2 C
-lBC







.Ot Loss: 623T t %






556.1 C Lrit LOSS: t.3ts %

.. . I .


0 100 23 :300 400 !50D 600 TO0
Tem pe ratl re CC)


M:O S3 1000


Figure 4-3. TG thermograms A) For carbonatic soils, pre-heated at 110 C for 24 hour. B) For

Histosols, pre-heated at 110 C for 24 hour.


en



















A


-20 0 40 I~ 0 M 100
Tim e (m Ih


120 140


160 180 a03


Figure 4-4. TG analysis of a Histosol heated to 180 C, cooled then heated to 1000 C. Line 1 is
the temperature profile and line 2 is the weight loss












































82
















1000


WOc
ED

70

so







4oo
40









0 2 40 en 100 120 140 160 l30
Tin e (n 11)


Figure 4-5. TG analysis of organic soil material (from a Histosol), using isothermal steps to
investigate energy dependency for weight loss versus time. Line 1 is oven

temperature and line 2 is soil sample percent weight loss.














A
20 Carbonatic
OM = 1.74xOC
15 R2 = 0.90


10


5


0


2.000 4.000 6.000 8.000 10.000
WB %/OC


12.000


B
Histosols
OM = 1.48xOC
R2 = 0.93 (n=16)


20 30
WB %OC


C
Spodosols
OM = 1.44x OC
R2 = 0.99


2 3
WB %/OC


Figure 4-6.


Correlation between TG %OM and WB %OC. A) For carbonatic soils. B) For
Histosols. C) For Spodosols.


0.000












Histosols
OM = 1.76xOC
95% CI= (1.67-1.86)
R2 = 0.95 (n=16)


Walkley-Black %OC


Figure 4-7. Correlation between WLOI %OM and WB %OC for Histosols.




25


Carbonatic soils
WLOI %OM = 1.0 x TG %OM + 0.4
R2 = 0.97


5 10 15


TG /oOM

Figure 4-8. Correlation between WLOI %OM and TG %OM in carbonatic soils.








































Theta(deq)

Figure 4-9. X-ray diffraction curves for Bicayne series (carbonatic soil).



















Kakira-Oxisol Soil Sample


d=7.1929


Kak Clay Mg/Gly Saturated


d=4 4095


d=3.5769 d=3 1388
I


5 10 15 20 25 30
Theta(deg)



Figure 4-10. X-ray diffraction curves for a Ugandan Oxisol from Kakira Jinja.


d=26954 d=25040









CHAPTER 5
SORPTION AND DEGRADATION OF SELECTED PESTICIDES IN CARBONATIC AND
ASSOCIATED SOILS

Introduction

Sorption and transformation are believed to be the major processes that determine the fate

of an organic pesticide once applied in the soil environment (Karapanagioti et al., 2001; Nkedi-

Kizza, 1983; Karickhoff et al., 1979). Sorption is also believed to protect the sorbed phase of

pesticides from microbial degradation hence half-lives of pesticides are likely to differ in

different soils depending upon the sorption capacity of the soil. The soil/solution distribution

coefficients (Kd values), have been found to correlate with organic carbon (OC) therefore

invoking the linear model to describe the partition of HOCs in soils. Using this relationship, it is

assumed that OC controls sorption ofHOCs (Thurston, 1953; Goring and Hamaker, 1972).

Normalizing the Kd values with OC results in a unique partition coefficient (Ko) which can aid

decision support models to predict the potential of chemical movement in a soil profile. Higher

Koc values indicate high sorption capacity of the chemicals that may pose risk to surface water

pollution via erosion. On the other hand, depending on the half-life (ti/2) of the compound,

chemicals with low Ko have potential to leach to ground water, thus posing risk to pollution of

groundwater resources.

The groundwater ubiquity score (GUS) developed by Gustafson (1989), has been used to

assess potential for groundwater pollution. By use of the Ko and ti/2 a GUS score can be

calculated from Equation 5-1:

GUS= [4 -logKo ]*logtl2 [5-1]









A GUS score of<1.8 indicates low leaching potential; 1.8
and GUS > 2.8 indicates potential for leaching (Bernard et al., 2005; Geisler et al., 2004; Laabs

et al., 2002; Gustafason, 1989).

The tropical environment in Uganda encourages proliferation of agricultural pests resulting

in destruction of agricultural produce. The use of pesticides is mostly uncontrolled though the

scale is smaller compared to the United States. The low pesticide consumption is due to the fact

that agriculture in Uganda is mostly at subsistence levels.

Isotherm non-linearity, differences in the nature and functionality of OM and errors

resulting in determination of soil OC may explain the variability. A single Ko for a particular

pesticide may not be realistic since previous studies have showed isotherm non-linearity and

variations in sorption capacities of a single compound in various soils. Although pesticides are

applied to control target pests, they usually end up polluting the environment due to leaching and

surface transport due to erosion. They may also degrade forming metabolites that are more toxic

and persistent than the parent compound (Edwards, 1973) posing environmental hazards. Among

the most frequently detected pesticides in surface and ground water resources of South Florida

are ametryn, atrazine, atrazine desethyl, chlorpyrifos, chlorpyrifos ethyl, 2,4-D, endosulfan

alpha, beta and endosulfan sulfate, hexazinone and metolachlor (Miles and Pfeuffer, 1997).

Atrazine (6-chloro-N-ethyl-N'-(1-methylethyl)-l,3,5-triazine-2,4-diamine) classified as an s-

triazine is one of the most widely applied herbicides in the United States. It is used as a pre- and

post-emergence herbicide and acts by stopping photosynthesis, thus killing the plant. Ametryn

(N-ethyl-N'-(1-methylethyl)-6-(methylthio)-l,3,5-triazine-2,4-diamine) classified as

methylthiotriazine is also widely used in USA. Its inclusion in this study was based on its

detection in surface waters of South Florida.









Materials and Methods

Carbonatic soils and associated non-carbonatic soils were collected from South Florida and

Puerto Rico. Oxisols from Uganda and Spodosols from Alachua County Florida were included

for comparison. Surface horizons (0-15 cm) were collected for analysis except Torry, Pahokee

and Dania for Histosols and Spodosols from Alachua where both surface and lower horizons

were collected. Detailed soils descriptions are in chapter 3. The soils were air dried and passed

through a 2 mm sieve before analysis.

Atrazine Analysis

Atrazine standard was obtained from Accustandard with purity of 98%. Standard solutions

were prepared by parallel dilution. Standard atrazine was dissolved in 2 mL methanol and made

to volume (1 L) with 0.01 M calcium chloride solution.

Sorption isotherms were determined using Batch and Slurry equilibrium method

(Wauchope et al., 2002; Nkedi-Kizza et al., 1985; Weber, 1986). Different concentrations of

atrazine were added to the soils at concentrations of 10, 7.5, 5, and 2.5 [g/mL in 0.01 M calcium

chloride. 10 mL of each concentration level were added to the soil in triplicate. The mixture was

then shaken on an action shaker at ambient temperature for 24 hours. Blanks were included to

check for adsorption on the walls of the tubes and/ or degradation of analyte during the

equilibration process. After equilibration, the mixture was centrifuged using a Beckman model

J2 21 centrifuge at 10,000 rpm for 15 minutes. The supernatant was then filtered through a # 42

Whattman filter paper before transfer to a borosilicate glass vial. Analysis was done using

Waters 2690 Separation Module Reversed Phase HPLC (Waters Chromatography Division,

Millipore) equipped with a Waters 2487 Dual Absorbance UV detector and Nova-Pak C18

reversed phase column (150 x 3.9 mm). The detector was set at 230 nm and 1 Aufs. A methanol









and water mixture (60: 40 v/v) was used as mobile phase, at a flow rate was 1.5 mL/min. Data

was handled using Millenium32, Version 3.05.01 1998 Waters Corporation software.

Ametryn Analysis

Ametryn standard was obtained from Accustandard with purity of 98%. Standard solutions

were prepared by parallel dilution. Standard ametryn was dissolved in 2 mL methanol and made

to volume (1 L) with 0.01 M calcium chloride solution.

The batch experiment was set up as described for atrazine. The HPLC UV-VIS detector

was set at 250 nm wavelength and 0.5 AUFS absorbance. The sorption isotherms for ametryn

were treated as described for atrazine.

Diuron Analysis

Diuron standard was obtained from Accustandard with purity of 98%. Standard solutions

were prepared by parallel dilution. Standard diuron was dissolved in 2 mL methanol and made to

volume (1 L) with 0.01 M calcium chloride solution.

The batch experiment was set up as described for atrazine. The HPLC UV-VIS detector

was set at 250 nm wavelength and 0.5 AUFS absorbance. The sorption isotherms for diuron were

treated as described for atrazine.

Model Fitting

Sorption data were fitted using the linear sorption isotherm model

Se = KdCe [5-2]

where Se is the sorbed concentration (mg/kg of solid surface) at equilibrium, Kd is distribution

coefficient (L/kg) and Ce is the solution concentration (mg/L) at equilibrium. From the plot of Se

against Ce, the slope obtained from the linear graph (Kd) was normalized with fraction of OC (foo)

to calculate the sorption coefficient Koc.

Koc = Kd/ (oc) [5-3]









Pesticide Degradation

Degradation was defined as the extractable concentration of the pesticide at time t (days)

of.incubation. The extraction and analytical procedure are outline in Chapter 3.

Quality Control/Quality Assurance

Triplicate samples were analyzed for each fortification concentration level. Blanks were

included in the analysis to assess potential for sorption on container walls. 10 mL of the

standards at varying concentrations were transferred into centrifuge tubes without soil. The tubes

were treated similarly as those with soil. A sub sample of the solution was analyzed and

percentage recoveries based on original concentration in the tube.

Results and Discussion

Atrazine Sorption

The recoveries in the blanks (without soil) exceeded 95 % which indicated no sorption of

atrazine on the walls of the centrifuge tubes or degradation within 24 hours of the equilibration

process. In addition, recovery of atrazine through filtration using Whatman # 42 filter paper

exceeded 95 %.

The Kd values reported in Table 5-1 for carbonatic soils range from 0.565 to 6.937 thus the

Kd values varied within a factor of 12. Key West soil series had the lowest Kd values and

Keyvaca the highest. Marl-carbonatic soils showed lowest sorption capacities for atrazine with

an average Ko of 45 compared to 65, 108, 183 and 790 for non-marl carbonatic, Histosols,

Oxisols and Spodosols, respectively. The range of Ko values for carbonatic soils was 45-105.

The variation was within a factor of 2. The literature Ko value for non-carbonatic soils is 172

(Hamaker and Thompson, 1972). Among the carbonatic soils sampled, the Perrine-Tamiami

association showed the highest sorption capacity (Ko = 105). Although this soil had 4.1 %OC

content compared to Keyvaca and Cudjoe which had 11.4 % and 10.2 % OC content,









respectively, it displayed higher sorption (Ko = 106). Islamorada which is an organic soil (39

%OC) from South Florida showed rather low Ko, comparable with Krome (1.5 % OC). The Ko

values for Islamorada were 74, 157, and 273 for atrazine, ametryn and diuron, respectively.

These observations confirm that the nature of OM present in the soils played an important role in

the sorption properties. The Perrine-Tamiami association sample was collected from within the

Tamiami series map unit. The vegetation in Histosols is predominantly Cladium spp. (sawgrass)

compared to marl soils whose organic primary producer is the algae, which drive the marl soil

formation. Some studies have found correlation between organic carbon and distribution

coefficient (Hamaker and Thompson, 1972) suggesting OC is the predominant soil component

that controls sorption of HOCs. However, the difference in the nature of OM present in different

soils may result in different affinities for sorption of HOCs and as a result for a particular

pesticide, Ko values may vary from one soil to another and from region to region depending on

the nature and origin of the OM present in the different soils. The OM in the rock-outcrop-

carbonatic soils such as Chekika and Krome forms from different sources compared to that in

marl-carbonatic soils (algal detritus). It is possible that this difference accounts for the higher Ko

values in the rock-plowed-carbonatic soils. Generally, carbonatic soils showed lower sorption

capacity irrespective of origin compared to the other soils types. The tendency of non-linear

sorption isotherms for organic soils has been observed in a few cases in this study especially as

the initial solution increased. Other studies attribute the non-linearity tendency of sorption of

organic compounds to particulate kerogen and black carbon (Cornelissen et al., 2005). In this

study initial pesticide concentrations were in ranges slightly higher that the recommended

application rates to enable detection by HPLC. The results may remain relevant in cases where

application rates may be exceeded or in cases of environmental spills. Even at these slightly









higher levels, the isotherms were linear (Figures 5-1, A-1 to A-12). A correlation of Kd values

with the fraction of organic carbon (Figures 5-3 A, 5-4 A and 5-5 A) is an indication that

partitioning HOCs to soil organic carbon could be the major process controlling the sorption in

carbonatic soils. When the Kd values were normalized with organic carbon the Ko values ranged

from 36 to 105 with Perrine soil series having the lowest Ko and Perrine-Tamaimi association

series having the highest Ko values. The marl carbonatic soils had lower Ko values compared to

the non marl carbonatic soils.

Data in Figure 5-1 show an isotherm for Lauderhill series from South Florida. The figure

shows that the data could be described using the linear model (R2 > 0.95). The slopes of the

graphs for different soil types (Figure 5-2) varied indicating that these soils may be adsorbing

pesticides differently. The atrazine slopes (Ko values) were 57, 117, 174, and 510 for carbonatic

soils, Histosols, Oxisols and Spodosols, respectively. The results show that the order of sorption

is Spodosols > Oxisols > Organic soils > Carbonatic soils. The data analyzed separately for each

soils series show that the sorption capacity for atrazine was in the order: Spodosols (Figure 5-3

D) > Oxisols (Figure 5-3 C) > Histosols (Figure 5-3 B) > Carbonatic soils (Figure 5-3 A). The

sorption capacity for marl-carbonatic soils was lower (a = 0.05) than what was observed for rock

plowed carbonatic soils. This may be due to difference in OM composition since these soils

formed under different vegetative conditions. It is likely that the OM primary producers are

playing an important role in the sorption capacities of these two soil types with carbonatic

mineralogy. The OM content in Spodosols was very low ranging between 0.62 % and 5.32 %.

However these soils displayed higher Ko values for atrazine (Table 5-5) ranging from 374 to

1060 and 115 to 443 for surface and Bh horizons respectively. Given the low OM content and

high Ko values, it is possible that other soil components other than OM may be contributing to









the sorption of HOCs in Spodosols. Furthermore, the OM present in Spodosols is of different

origin as it is mostly contributed by forest litter compared to Histosols whose OM source is

sawgrass and algae for marl-carbonatic soils. The Ko values for Histosols were lower than that

of Spodosols and Oxisols though Histosols contained organic carbon up to 10 times higher than

for Oxisols and Spodosols. The Ko for Histosols ranged from 69 (Pahokee series) to 171 (Dania

series).

It is generally believed that sorption capacity increases with increase in organic carbon.

However in this study, this model broke down when we compared soils that may contain

different sources and forms of OM. The composition of OM in terms of humic acids, humic,

kerogen and their affinity for HOCs may be different. This study shows that the quality as well

as the quantity of OM contributes greatly to the sorption capacity of soils. Xing (1997) found

similar Ko variation which he attributed to the nature of SOM.

Ametryn Sorption

Ametryn sorption on container wall was checked and the recoveries exceeded 95 %. The

sorption coefficients for ametryn were higher (Table 5-2) than for atrazine (Table 5-1) but were

lower than those for diuron except for Spodosols which had Ko values higher than obtained for

diuron. Saddlebunch (Key West area, South Florida) showed the lowest Ko for marl soils with a

Koc of 60 while Pomona series showed the highest Ko value of 6960. The OC content for

Spodosols ranged 0.8 and 5.3 for surface soils and 0.6 to 1.8 in Bh horizons. The values for OC

content were generally higher than 1 % cutoff where mineral materials' contribution to sorption

becomes important. The low correlation in Spodosols, (Figure 5-4 D) indicates that OC content

alone may not account for sorption. Although the pH values for Spodosols were in the acidic

range (3.86-4.24 in surface soils and 4.36-4.71 in Bh horizons), the chemicals studied are

expected to be in neutral phase hence partitioning is expected to be the major adsorption









mechanism. Marl-carbonatic soils showed the lowest sorption capacities for ametryn sorption.

The Ko values for ametryn in marl-carbonatic soils averaged 107 and were 2, 2, 6, and 21 times

lower than those of non-marl-carbonatic soils, Histosols, Oxisols and Spodosols, respectively.

Ametryn Degradation

Ametryn degradation was best described by exponential decay fitting first order reaction

kinetics. The t1/2 value for carbonatic soils ranged between 15 and 248 days with Key West soil

series showing the longest half life. No relationship was observed between ametryn degradation

rates and sorption.

Diuron Sorption

Diuron sorption was higher than that of atrazine and ametryn. The Average Ko for

carbonatic soils was 257 compared to 59 and 134 for atrazine and ametryn, respectively. The

literature log Kow values have been used to describe compound hydrophobicity (Inoue et al.,

2004). The Kow of 2.85 for diuron, compared to 2.50 for atrazine, shows that diuron is more

hydrophobic than atrazine. This high hydrophobicity may explain diuron's higher ability to

partition to organic matrix hence the higher Ko values compared to atrazine. The results showed

a positive relationship between the distribution coefficients (Kd) and the fraction of OC (fo,),

which indicates that OC may be playing an important role in the sorption process of diuron in the

soils studied. The low R2 (0.2) for Oxisols (Figure 5-4 C) suggests that OC alone may not

account for the whole pesticide sorption for Oxisols. Despite their low OC content, Spodosols

displayed the highest sorption capacities. It is possible that the OM reactions in Spodosols and

Oxisols result in accumulation of components contributing the most to the sorption of HOCs.

Alternatively, other components other than OM may be contributing to the sorption of HOCs in

Oxisols and Spodosols.









Carbonatic soils showed the lowest sorption capacities for sorption. The Ko values for

diuron in marl-carbonatic soils averaged 197 and were 2, 3, 5, and 8 times lower than for non-

marl-carbonatic soils, Histosols, Oxisols and Spodosols, respectively. The literature Koc for

diuron in non-carbonatics is 480 (Wauchope et al., 1992).

Diuron Degradation

Diuron degradation was described by first order (Figure 5-7A). The decay constant was

obtained from the slope of the log transformed of concentration against time (Figure 5-7B). The

tl/2 of diuron in carbonatic soils ranged between 45 (Keyvaca FL) and 315 days (Saddlebunch -

FL). Bayamon is classified as an Oxisol showed the fastest degradation rate for diuron with a ti/2

of 35 days while Saddlebunch, classified as a Mollisol with carbonatic mineralogy showed the

slowest degradation rate for diuron with a of 315 days. The tl/2 values were calculated from log

transformed data (Figure 5-8) from the decay constants obtained from the degradation curves. In

this study no relation was observed with sorption or OM. Brown (1994) similarly observed no

relationship between sorption and degradation. It is possible that hydrolysis plays an important

role in the chemical disappearance hence the poor correlation between sorption and degradation.

If hydrolysis contributes greatly to the pesticide disappearance, the concept of pesticide

protection may not hold. The low initial concentration recovery may be evidence that hydrolysis

occurs rapidly at the beginning leading to poor recoveries. The results were inconsistent with

other studies (Smith et al., 1992; Ogram et al., 1985; McCormick and Hiltbold, 1966) that

reported an increase in degradation rate as OM increases. This was thought to be due to

utilization of OM by microbes as a source of energy. Some studies (Johnson and Sims, 1993;

Ogram et al., 1985; Helling et al., 1971; Harris, 1967) have reported a decrease in degradation

with increase in sorption capacity citing protection of the chemical from microbial attack due to

sorption.









The relatively slow degradation rate and low sorption for diuron in carbonatic soils may

provide reason for its frequent detection in South Florida and Puerto Rico surface waters. Since

application rates are based on soil OC content which affects the net activity (solution

concentration) of the compound applied, it is possible that diuron remains effective in carbonatic

soils even when applied at lower rates since the chemical is poorly adsorbed. Protecting the

environment in these vulnerable soils may therefore require lowering the application rates for

HOCs. There was no difference in diuron tl/2 values obtained for carbonatic and non-carbonatic

soils.

Vulnerability of Groundwater to HOCs Contamination

The GUS scores (Figure 5-9) for diuron ranged between 3.32-4.55, 2.62-4.11, 2.61-3.67,

1.85-3.29, and 0.80-1.74 for marl carbonatic, non-marl carbonatic, Histosols, Oxisols and

Spodosols, respectively. Table 5-6 shows the diuron degradation data for the soils that were

analyzed. Saddlebunch showed the highest potential to leach diuron from South Florida while

Tuques showed the highest potential for soils from Puerto Rico. Key West (marl carbonatic)

showed the highest potential to leach ametryn (Table 5-7). Marl soils showed highest potential to

leach diuron while the Spodosols GUS values indicated very low leaching potential for diuron.

This trend was similarly reflected in the Koc values that were obtained for the different soil

classes. The scores in carbonatic soils were lower (a=0.05) for ametryn compared to those

obtained for diuron. This may indicate lower leaching potential for ametryn in carbonatic soils

(Figure 5-10). A chemical is considered a leacher if it's GUS score is greater than 2.8 (Bernard et

al., 2005; Geisler et al., 2004; Laabs et al., 2002; Gustafson, 1989). Figure 5-9 shows that in

accordance with the GUS score Spodosols have low potential for leaching diuron, the Oxisols

were in the transitional state while Histosols and carbonatic soils were found to be vulnerable to

leaching of diuron. The leaching potential may however, vary according to climatic conditions









like temperature and precipitation, intrinsic soil properties such as permeability and drainage

class, depth to the water table, and farming practices. The GUS scores for ametryn were

significantly lower (a = 0.05) than those for diuron suggesting that diuron has higher leaching

potential than ametryn. The results showed that leaching potential varies across chemicals

resulting from their degradation rates and sorption potential.

Conclusions

The average pesticide sorption coefficient for marl-carbonatic soils was found to be less

than 1/3 of the Ko values calculated for non-carbonatic soils. Marl carbonatic soils were found

to sorb less compared to the rock-plowed carbonatic soils. This is likely due to differences in

OM primary producers in the two soil types. Given the physical and chemical properties of the

soils and their differing genesis, it can be seen that the two soil types (Marl and non-marl-

carbonatic) present different challenges to sorption of pesticides. The algae which drive the marl

formation, may be the major primary producer thus influencing their OM physical-chemical

behavior, hence the low sorption capacity for HOCs. The linear relationship obtained from

regressing Kd with OC content indicated that OC controls the sorption process of the HOCs in

carbonatic soils, and Histosols. By comparing the quantities of OC in carbonatic soils, Histosols,

Oxisols and Spodosols (Tables 5-1 to 5-5), the results show that the quality as well as the

quantity of OM contributes greatly to the sorption capacity of soils. The poor correlation

between Ko and SOC content, obtained for atrazine, ametryn and diuron in Oxisols and

Spodosols indicates that SOC content alone is insufficient to account for the sorption of HOCs in

these soils.

The rock-plowed soils of South Florida are gravelly and well drained and have a shallow

water table. Despite the fact that these soils show higher sorption capacities in the laboratory

studies, possibly due to the nature of OM, the pesticides may not have sufficient time to interact









with the soil OM, thus preventing leaching/ contaminating groundwater under field conditions.

The GUS score classification (Figure 5-9) indicates that rock-outcrop carbonatic soils have a

high potential to leach diuron. Marl soils on the other hand tend to exhibit lower sorption

capacity due the nature of OM in these soils. The OM in marl soils which is from diatoms may

not be as complex as that from higher plants that are prevalent in well drained rock-plowed soils.

The difference in the nature of OM present in the two soil types may lead to higher pollution

potential in marls soils since these appear to sorb pesticides less compared to the rock-plowed

soils. Besides, the water table in marl soils is very shallow.










Table 5-1. Soil organic carbon content, and atrazine distribution coefficients (Kd) and organic
carbon sorption coefficients (Ko) for carbonatic soils from Florida and Puerto Rico.


Soil Sample


Aguilita
Biscayne
Biscayne 2
Cadjoe
Chekika
Chekika 2
Colinas
Key Vaca
KeyWest 1
KeyWest 2
Krome 1
Krome 2
Legumnivitae 1
Legumnivitae 2
Pennsuco
Perrine 1
Perrine 2
Perrine-Tamiami Assoc
Saddle Bunch 1
Saddle Bunch 2
S-Sebastian
Tuque
Yauco
Type: C = Carbonatic, M
foc= fraction of OC; Kd =


pH
Type H20 0.01M Origin
CaCl2
7.44 6.94
C 7.23 6.99 PR
MC 7.43 7.18 FL
MC 7.30 7.19 FL
MC 7.35 7.18 FL
C 6.86 7.00 FL
C 7.13 7.15 FL
C 7.44 7.26 PR
MC 8.34 8.16 FL
MC 8.12 7.69 FL
MC 7.73 7.48 FL
C 7.35 7.36 FL
C 7.33 7.16 FL
MC 7.42 7.28 FL
MC 7.52 7.36 FL
MC 7.40 7.30 FL
MC 7.29 7.25 FL
MC 7.47 7.33 FL
C 7.70 7.45 FL
MC 7.57 7.42 FL
MC 7.42 7.18 FL
C 7.52 7.27 PR
C 7.54 7.25 PR
C 7.44 6.94 PR
C = Marl carbonatic; Origin: FL


Atrazine


foc


0.048
0.057
0.029
0.102
0.020
0.041
0.024
0.114
0.012
0.012
0.015
0.023
0.061
0.047
0.027
0.029
0.029
0.041
0.017
0.081
0.022
0.023
0.031


Kd
L kg-1
2.878
2.717
1.418
5.749
1.244
3.389
2.004
6.937
0.565
0.573
1.190
1.852
3.628
2.159
1.256
1.088
1.030
4.339
0.727
3.371
1.364
1.171
1.593


Florida, PR


Puerto Rico;


sorption coefficient normalized with OC.


Distribution coefficient; K,,,










Table 5-2. Soil organic carbon content, atrazine, diuron and ametryn distribution coefficients
(Kd) and sorption coefficients (Ko,) for Oxisols from Uganda and Puerto Rico.
pH Atrazine Ametryn Diuron
Soil Sample Origin foc
ISoil Sample Orn M KCI Kd Koc Kd Koc Kd Koc
g kg L kg-1 L kg1


Bayamon
Bayamon 2
Fiduga 1
Fiduga 2
Fiduga 3
Fiduga Pooled
Hima 1
Hima 2
Hima 3
Hima Lime
Hima Pooled
Kakira 1
Kakira 2
Kakira 3
Kakira Pooled
Kasaku 1
Kasaku 2
Kasaku 3
Kasaku 4
MK Flora 1
MK Flora 2
MK Flora 3
MK Flora 4
MK Flora Pooled
Muhookya 1
Muhookya 2
Muhookya 3
Muhookya Pooled
Rubaabo Sediment
ScoulLugazi1
ScoulLugazi 2
Scoul Lugazi 3
ScoulLugazi 4
Scoul Pooled
Wagagai 1
Wagagai 2
Wagagai 3
Wagagai Pooled


PR
PR
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG
UG


0.015
0.018
0.018
0.014
0.016
0.012
0.038
0.061
0.043
0.007
0.026
0.024
0.029
0.025
0.028
0.027
0.030
0.027
0.026
0.026
0.021
0.027
0.023
0.024
0.007
0.027
0.003
0.008
0.015
0.025
0.024
0.030
0.034
0.025
0.010
0.010
0.018
0.009


5.80
7.31
7.06

6.98
6.98
6.99
7.57

5.21
4.48
5.84






4.58
4.20
4.53
4.95

6.93
7.00
6.99









4.12
3.97
4.02


1.15 76 2.11
1.76 100 4.00
3.22 181 8.56
1.97 139 4.47
2.09 133 3.83
2.45 213 3.84
3.78 100 6.37
8.08 132 12.26
5.13 121 7.87
2.55 388 6.39
2.92 114 4.64
4.58 194 11.12
6.37 219 22.38
3.42 136 15.51
4.87 174 11.47
3.11 115 13.32
4.68 158 15.22
4.26 157 11.14
3.79 146 14.80
6.60 250 18.64
3.40 165 11.48
11.49 424 29.76
6.40 281 20.54
7.57 317 22.59
0.64 94 1.90
3.04 113 5.07
0.46 157 1.76
2.81 367 2.22
2.39 164 4.71
5.66 222 23.65
4.59 190 22.95
6.84 231 21.53
8.60 250 31.60
6.36 254 14.87
0.66 67 4.63
0.60 61 5.43
1.50 85 8.38
1.13 128 2.55


139 4.97 328
228 5.83 333
481 22.30 1253
316 10.88 770
245 14.20 908
333 14.79 1282
168 29.16 768
200 59.32 969
185 35.57 837
973 7.83 1192
182 17.66 691
471 32.95 1396
771 48.45 1669
618 20.23 806
409 29.65 1058
491 19.43 717
516 35.02 1186
410 15.40 567
568 19.32 742
706 39.79 1508
556 16.43 796
1097 56.30 2076
903 36.88 1621
945 33.37 1397
278 2.38 348
189 15.67 585
599 1.59 541
290 5.63 736
323 16.99 1165
930 38.90 1529
947 32.73 1351
726 55.90 1885
918 49.45 1437
593 28.94 1154
468 2.44 247
548 2.51 253
476 6.01 342
289 4.87 552


Type: Oxisols; Origin: PR = Puerto Rico, UG = Uganda. ** The names for Oxisols from Uganda
are not series names. They indicate site name where they were collected.










Table 5-3. Ametryn and diuron degradation and sorption coefficients for carbonatic soils from
Florida and Puerto Rico.


Soil Sample


Aguilita
Biscayne
Biscayne 2
Cudjoe
Chekika
Chekika 2
Colinas
Keyvaca
KeyWest 1
KeyWest 2
Krome 1
Krome 2
Lignumvitae 1
Lignumvitae 2
Pennsuco
Perrine 1
Perrine 2
Perrine-Tamiami assoc
Saddlebunch 1
Saddlebunch 2
San Sebastian
Tuque
Yauco


Type Origin


C
MC
MC
MC
C
C
C
MC
MC
MC
C
C
MC
MC
MC
MC
MC
C
MC
MC
C
C
C


Ametryn
Kd Koco
g kg
6.23 130
6.59 116
3.00 103
10.71 106
3.60 175
6.94 169
3.54 148
13.78 121
1.38 113
1.84 157
3.18 213
4.12 181
8.03 131
4.83 103
2.96 108
2.54 87
2.75 95
10.22 247
1.62 95
4.84 60
3.21 143
2.49 106
3.01 97


Type: C = Carbonatic, MC = Marl carbonatic; Or
fraction of OM; Kd = Distribution coefficient; Koc =
carbon; tl/2 = Half life.


Diuron


Kd
L kg-1
12.53
12.50
5.92
25.89
5.99
18.39
9.61
29.83
1.86
1.90
6.50
10.58
15.37
7.90
5.92
4.89
4.64
20.57
2.59
15.22
5.08
3.64
6.42
Florida, PR


261
220
204
255
292
448
403
262
152
162
436
463
251
168
216
167
161
496
152
189
226
155
207
Puerto Rico; foe


sorption coefficient normalized with organic











Table 5-4. Soil organic matter content, and atrazine distribution coefficients and organic carbon
sorption coefficients for Histosols from Florida.
pH Atrazine Ametryn Diuron
Soil Sample f H20 0.01M
H CaC2 Kd Koc Kd Koc Kd Koc
CaCl2
Lkg-1 Lkg1 L kg-1
Dania 0-6" 0.43 6.08 5.94 73.22 171 184.44 430 421.32 982
Dania 6-12" 0.53 5.89 5.72 80.24 150 251.84 472 486.15 911
Islamorada 0.39 6.57 6.65 27.88 72 60.71 157 105.85 273
Lauderhill 1 0.29 7.05 7.06 30.10 105 65.07 226 156.50 545
Lauderhill 2 0.21 7.30 7.22 17.13 82 36.36 173 82.02 391
Lauderhill 3 0.23 7.18 7.18 24.35 107 48.84 215 123.38 543
Matecumbe 1 0.32 7.10 7.00 37.88 117 79.18 244 218.83 674
Matecumbe 2 0.20 7.07 6.97 15.84 80 40.75 206 111.51 564
Pahokee 0-6" 0.42 7.25 7.20 29.05 69 56.93 135 196.31 464
Pahokee 6-12" 0.47 6.30 6.27 58.00 123 122.57 260 360.54 765
Tamiami 1 0.40 6.39 6.30 38.66 97 87.10 217 194.43 485
Tamiami 2 0.2 6.63 6.65 14.57 74 31.05 157 56.46 285
Tamiami 3 0.40 7.10 7.20 57.39 144 110.02 277 262.07 660
Torry 1 (0-6") 0.13 6.57 6.65 15.91 125 30.78 241 65.03 509
Torry 2 (6-12") 0.10 6.96 6.86 13.37 139 24.73 257 53.49 556
Type: Histosols, Origin: Florida; foc = fraction of organic carbon; Kd = Distribution coefficient;
Koc = sorption coefficient normalized with organic carbon.










Table 5-5. Soil organic matter content, and atrazine distribution coefficients
sorption coefficients for Spodosols from Florida.


and organic carbon


pH Atrazine Ametryn Diuron
Soil Sample fo H 0.01M Kd
H CaCl2 Kd Koo Kd Koo Koo
CaC12
Lkg-1 Lkg-1 L kg1
Bh-1 0.009 4.35 3.93 1.03 115 5.19 584 5.25 590
Bh-2 0.018 4.36 3.87 4.20 229 13.09 714 11.57 631
Bh-3 0.006 4.39 3.89 2.75 443 8.57 1383 7.12 1149
E 0.002 4.71 3.79 0.38 184 2.23 1068 1.16 555
Monteocha 1 0.053 4.12 3.57 19.88 374 124.48 2341 84.32 1586
Monteocha 2 0.011 4.11 3.32 10.20 913 56.79 5084 43.68 3910
Pomona 1 0.009 4.24 3.55 4.56 534 22.77 2666 14.33 1678
Pomona 2 0.023 3.86 3.16 19.08 823 90.19 3889 62.04 2675
Pomona 3 0.011 4.00 3.23 11.57 1035 60.62 5427 43.39 3885
Pomona 4 0.020 4.01 3.30 21.64 1060 142.06 6960 86.60 4243
Type: Spodosols, Origin: Alachua County Florida. Bh horizon depth 80-100 cm,










Table 5-6. Diuron half-life and GUS scores in soils from Florida, Puerto Rico and Uganda.


Soil Name


Aguilita
Biscayne
Biscayne 2
Chekika 1
Colinas
Key Vaca
KeyWest 2
Krome 1
Lignumvitae 1
Lignumvitae 2
Pennsuco
Perrine 1
Saddlebunch 1
Saddlebunch 2
San Sebastian
Tuque
Yauco


Islamorada
Lauderhill 1
Matecumbe 1
Tamiami 1
Tiburones

Monteocha 1
Monteocha 2
Pomona 1
Pomona 2
Pomona 3
Pomona 4

Bayamon 1
Bayamon 2
Fiduga Pooled
Hima Pooled
Kakira Pooled
MK Flora Pooled
Muhookya Pooled
Scoul Pooled
Wagagai Pooled

San Antont
GUS = groundwater
Mollisol; = "Carbor


Soil
Origin


% Moisture Diuron Decay
Content Constant (K)
(Adjusted) 1/day
Carbonatic soils*
37 0.0069
54 0.0026
42 0.0043
21 0.009
32 0.0045
68 0.0153
26 0.0029
21 0.0058
39 0.0058
39 0.0029
38 0.003
38 0.0067
20 0.0022
45 0.0026
31 0.0024
25 0.0037
33 0.0059
Non carbonatic soils
Histosols
111 0.0004
77 0.0037
102 0.0041
106 0.0042
35 0.0024
Spodosols
21 0.0046
20 0.005
20 0.0047
20 0.0033
16 0.0033
22 0.0048
Oxisols
22 0.0031
22 0.0198
22 0.0047
31 0.0036
29 0.0041
23 0.0047
36 0.0031
23 0.0042
21 0.0042
Other
24 0.0021


Diuron
Half-life (tl/2)
days


100
267
161
77
154
45
239
119
119
239
231
103
315
267
289
187
117


1733
187
169
165
289

151
139
147
210
210
144

224
35
147
193
169
147
224
165
165

330


ubiquity score; FL = Florida; PR = Puerto Rico; UG
latic" refers to soil mineralogy not taxonomic classification.


Diuron GUS


3.17
4.02
3.73
2.89
3.05
2.62
4.26
2.83
3.32
4.22
3.94
3.58
4.55
4.18
4.05
4.11
3.49


5.07
2.87
2.61
2.91
3.67

1.74
0.87
1.68
1.33
0.95
0.80

3.49
2.28
1.93
2.65
2.17
1.85
2.66
2.08
2.79

3.29
Uganda; t











Table 5-7. Ametryn half l


Soil Name



Aguilita
Biscayne
Biscayne 2
Colinas
Cudjoe
Chekika 1
Key Vaca
KeyWest 1
KeyWest 2
Krome 1
Lignumvitae 1
Lignumvitae 2
Pennsuco
Perrine 1
Perrine-Tamiami assoc
Saddlebunch 1
Saddlebunch 2
San Sebastian
Tuque
Yauco

Monteocha 1
Monteocha 2
Pomona 1
Pomona 2
Pomona 3
Pomona 4
tGUS = groundwater ubic
taxonomic classification.


ife and GUS scores in soils from Florida, and Puerto Rico.
Ametrytn
%Moisture Ametrytn Ametryn
Soil % iuDecay A
Content Half-life (t/z)
Origin (Ajted) Constant (k (da
(Adjusted) /day) (days)
Carbonatic soils*
PR 37 0.0173 40
FL 54 0.0173 40
FL 42 0.0462 15
PR 32 0.0222 31
FL 0.0374 19
FL 21 0.0465 15
FL 68 0.0286 24
FL 27 0.0027 248
FL 26 0.0083 83
FL 21 0.0241 29
FL 39 0.0221 31
FL 39 0.0126 55
FL 38 0.0246 28
FL 38 0.0363 19
FL 0.0077 90
FL 20 0.014 47
FL 45 0.0157 44
PR 31 0.0159 44
PR 25 0.0117 29
PR 33 0.0237 29
Spodosols
FL 21 0.0038 182
FL 20 0.0118 59
FL 20 0.0121 58
FL 20 0.0047 151
FL 16 0.008 87
FL 22 0.0121 56
luitv score; FL = Florida; = "Carbonatic" refers to soil miner


metryn
GiUS


3.02
3.10
2.34
2.73
2.53
2.06
2.65
4.67
3.46
2.44
2.81
3.46
2.85
2.64
3.14
3.38
3.65
3.03
2.89
2.95


1.43
0.52
1.01
0.89
0.51
0.28
alogy not












200
180
E 160
E 140 y 156.5x
R2 =0.9963
O 120
o 100
2 80
ca
w 60-
0
o 40
20

0-
0 0.2 0.4 0.6 0.8 1 1.2
SOLUTION CONC., (mg/L)

Figure 5-1. Diuron sorption isotherm of Lauderhill series (Histosol) from South Florida.
















y = 164x
2 = 0.3523


y= 117x
R2 = 0.735


R2 = 0.8574


0.100 0.200


0.300 0.400
Walkley-Black Foc


* Carbonatic


* Histosols


Oxisols


* Spodosols


Figure 5-2. Correlation of atrazine distribution coefficients (Kd) with the fraction of organic
carbon for different soil series.


=510x
= 0.4617


0.000


0.500


0.600


















A
Carbonatic
Koc = 57xFoc
R2 = 0.8574



+ *



.^-^^


0.040


0.060


0.080


0.100


Histosols
Koc = 117xFoc
R2= 0.735


0.100


0.200


0.300


0.400


0.500


0.600


Oxisols
Koc= 174xFoc
R2= 0.464


* ***


80

70 -

60

50

40

30

20

10 -

0 -
0.000


14

12

10

8

6

4

2

0
0.000


D
25 Spodosols
Koc = 510xFoc
20 R2 = 0.4617


0 --4
0.000


0.010


0.020 0.030 0.040 0.050
Walkley-Black Foc


0.060


Figure 5-3. Correlation of atrazine Kd with fraction of organic carbon for A) For carbonatic soils,

B) For Histosols, C) For Oxiosols and D) For Spodosols. Slopes represent average

Koc.







110


3-

2

1 -

0 -
0 .000


0.020


0.120


..

0.010 0.020 0.030 0.040 0.050 0.060 0.070


















A
Carbonatic
Koc = 116xfoc
R2 = 0.7339


16

14

12

10

8-

6

4

2

0
0.000


0.100


0.200


0.300
Walkley-Black Foc


0.400


0.500


0.600


C
Oxisols
Koc= 483 x foc
R2 = 0.2122


0.010 0.020 0.030 0.040
Walkley-Black Foc


0.050 0.060 0.070


250


200


150


100


50


0
0.000



35

30

25

20

15

10

5

0
0.000



180 -

160

140

120

100
80

60

40

20
0 "
0.000
tO-

O.OO


Figure 5-4. Correlation of ametryn Kd with fraction of organic carbon. A) For carbonatic soils.

B) For Histosols. C) For Oxiosols. D) For Spodosols.











111


0.010


0.020 0.030 0.040 0.050
Walkley-Black Foc


0.060


0.020 0.040 0.060 0.080 0.100 0.120
Walkley-Black Foc






B
Histosols
Koc = 278x foc
R2=0.615


-


300


D
Spodosols
Koc = 2950 x foc
R2 = 0.505


















30

25

20

15

10

5

0
0.000


B
Histosols
Koc= 650xFoc
R2= 0.6969 *










0.100 0.200 0.300 0.400 0.500


0.600


C
Oxisols .
Koc = 1075xFoc
R2 = 0.6088


" 4


0.010 0.020 0.030 0.040 0.050 0.060 0.070


0.060


100 D
Spodosols
80 Koc= 1992xFoc
R2 = 0.5324

60

40 -

20


0 0--
0.000
ONoo


0.010 0.020 0.030 0.040 0.050
Walkley-Black Foc


Figure 5-5. Correlation of diuron Kd with fraction of organic carbon. A) For carbonatic soils. B)

For Histosols. C) For Oxiosols. D) For Spodosols.








112


A
Carbonatic
Koc = 255xFoc
R2 = 0.7887


0.020 0.040 0.060 0 080 0 100


600


0 120


500


400


300


200


100


0 --
0.000


70

60

50

40

30

20

10

0 4
0.000


120











800


700 I Marl
0 Non marl carbonatic
600 Histosols
SOxisols
0500
o 0 iSpodosols

m400


c300


200 T


100


Arain
F Atrazine


00


30


Ih


Ametryn


Figure 5-6. Graphical representation of average Ko values for the different soil types analyzed.
Error bars indicate 95 % confidence interval.


I Diuron
















Mt = 4.2089e- 0059xt
R2 = 0.9812


S30
E
25

20


14

12


10


08


06


0 20 40 60 80 100 120 140 160
Time (Days)


B
Ln(Mt) = -0.0059xt + 1.4372
S0.9812
R = 0.9812


20 40 60 80 100 120 140 160
Time (Days)


Figure 5-7. Degradation of diuron in Lignumvitae series from Florida Keys, South Florida.
































0 20 40 60 80
Time (Days)


120 140


Saddlebunch-1


*Saddlebunch-2


* Lignumvitae


Figure 5-8. Selected degradation curves for diuron in carbonatic soils from South Florida.


3.00

2.50


2.00

1.50


1.00


0.50

0.00


m Biscayne-1
















low leaching 1.8 Medium 2.8 High Leaching Potentail
Potential Leaching
Potential
Spodosols *** **



Oxisols ** o


Histosols A & A

Puerto Rico soils
Carbonatic ** =


Marl ** 4 *



0-
0.0 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2 3.6 4.0 4.4 4.8
GUS


Figure 5-9. Groundwater ubiquity score classification for diuron in different soil types.












low leaching
Potential







Spodosols

A A AA A



Carbonatic



Marl


1.8 medium 2.8 High Leaching Potentail
Leaching
Potential













U U U ,l, E


0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
GUS


Figure 5-10. Groundwater ubiquity score
Spodosols.


classification for ametryn in carbonatic soils and









CHAPTER 6
CROSS POLARIZED MAGIC ANGLE SPINNING CARBON NUCLEAR MAGNETIC
RESONANCE AND STABLE ISOTOPE CHARACTERIZATION OF ORGANIC MATTER
IN CARBONATIC AND NON-CARBONATIC SOILS OF SOUTH FLORIDA, PUERTO
RICO AND OXISOLS FROM UGANDA

Introduction

Organic matter (OM) is usually present in small amounts in mineral soils, but contributes a

great deal to soil properties. Its influence to soil color, water retention capacity, soil aggregation,

sorption of hydrophobic organic chemicals (HOCs) and a source of energy for microbial

processes is well known. However, due to its complexity, OM poses challenges to even the most

recent advanced analytical techniques. Thermo analysis using Thermogravimetric analysis (TG)

provides an accurate determination of OM in soils that do not constitute minerals that decompose

with the same temperature (T) range (150-550 C). Kucerik et al., 2006 described three onset

steps for the thermo-oxidation of OM during thermo analysis. The lower T range constituting the

aliphatic, polar groups and simple aromatic groups and another step 200-300 C resulting from

decomposition of polyaromatic moieties. The third onset (>400 C) is ascribed to

polyheterocyclic molecules. The use of CP-MAS 13C NMR to whole soil samples can provide

more insight on the functionality of the OM present in the soils. Previous studies (Dai et al.,

2001) have reported success in using 13C CP-MAS to elucidate functional moieties of OM in

soils.

The aim of this study was to characterize OM and to assess the accuracy of the methods

used for OM and/or OC characterization. Previous studies (Maheswari and Ramesh, 2007; Cox

et al., 1998; Nkedi-Kizza et al., 1983) have reported a positive correlation between sorption

distribution coefficients with organic carbon. Based on the relationship, the organic carbon

parameter is used in normalizing sorption distribution coefficients (Kd) to provide a unique

sorption coefficient (Ko). Some studies (Oliver et al., 2005; Spark and Swift, 2002) however, did









not find a relationship between sorption of atrazine, imidaclopid, thiacloprid, and diuron with

organic carbon, suggesting that organic carbon may not adequately account for sorption of HOCs

in all soils. Walkley-Black has been used for many years for analysis of soil organic carbon

however its generation of large amounts of toxic wastes calls for development of more

environmentally safe methods for OC determination. In this study we report use of TG methods

for determination of OM in carbonatic soils.

Materials and Methods

Soils were collected from South Florida Dade county and Monroe county and Puerto Rico.

The Oxisols were collected from Uganda, East Africa. OM present in these soils was

characterized using CP-MAS 13C NMR and stable isotope analysis.

The detailed methods description for stable isotope and CP-MAS 13C NMR analysis are

provided in Chapter 3 of this manuscript.

Results and Discussion

Stable Isotope Determination

Stable isotope determination indicates the fractionation of carbon during photosynthesis

for plants. The pathway for carbon dioxide intake leaves a 613C signature that can be investigated

using stable isotope analysis. Plants that follow C3 fractionation have 613C ranging from -22 %o

to -32 %o (average -27 %o). Most plants, algae and forest ecosystems are C3 plants. C4 plants are

mainly found in hot arid environment so C4 plants are adapted to more efficient water use. These

constitute plants such as sugar cane, corn, sorghum, and millet (Ehleringer and Pearcy, 1983).

Plants that follow C4 type photosynthesis pathways have 613C ranging from -12 %o to -17 %o

(average -13 %o). Stable isotopes can be useful in "fingerprinting" the nature of plant of plants

and how they fractionate carbon. The approach is better applicable to terrestrial versus marine

plants since these tend to have different sources of carbon. However, in a garden environment









this may be fuzzy determination since both C3 and C4 plants may co-exist in the same

environment. In this study, the 136 signatures were consistent with what we expected but the data

did not provide trends that can allow prediction of sorption capacities of hydrophobic organic

compounds based on 613C values and Kd values. The data in Figure 6-1 show no correlation

between sorption and 613C values. The 613C values ranged between -15.3 %o and -23.3 %o. It is

evident that the 613C signatures are intermediary (Figure 6-2) indicating that both C3 and C4

plants may be influencing the OM present in carbonatic soils. Smith and Epstein (1970) observed

similar 613C signatures for marine and fresh water algae ranging from -12.3 %o to -22.7 %o. In

their study they observed that higher plants and lower vascular plants had values lower than -23

%o. Matecumbe (-25.95 %o) and Lauderhill (-25.72 %o) showed 613C signature that indicated that

C3 plants are predominant in these soils thus influencing the nature of OM in Histosols.

13Carbon Cross Polarized Magic Angle Spinning Nuclear Magnetic Resonance Analysis

The solid state NMR spectra in Appendix B show the functional similarities and

differences between soils of different origins. Carbonatic soils from South Florida had low

aromaticity compared to Organic soils from South Florida and Oxisols from Uganda. This can be

seen in the spectral region of 105-160 ppm. The quantitative errors in the NMR analysis were

minimized by performing variable contact time analysis (Hatcher et al., 1993). Even then, NMR

results are semi-quantitative. This is due to the difficulty in cross polarization of carbons remote

to protons hence causing errors in quantification. The spectra obtained in this study (Figure 6-4)

are similar to those obtained for algae grown in the laboratory (Figure 6-3), which confirms that

the major primary producer for OM in the marl soils of South Florida is algae. It is likely that the

humification of algae produces less complex moieties of OM with low HOCs sorptive capacities.

In this study, a correlation was observed between sorption capacity (Ko) of HOCs and aromatic

C content (110-160 ppm) of OM (Figure 6-7 and 6-8). Other studies (Xing, 1997; Gauthier et al.,









1987) found a similar relationship. A negative relation was observed between Ko and alkyl C

content (0-45 ppm). The aromatic C/alkyl C ratio (110-160 ppm/ 0-45 ppm) provided a stronger

relationship with Ko (Figures 6-5, 6-6 and 6-8). The aromatic C/ alkyl C ratio will be referred to

as the "aromatic C index". This index was not related with Ko in Spodosols. The sorption of

HOCs in Spodosols is probably controlled by other components other than aromatic C. The poor

correlation obtained by regressing Ko with the aromatic C indices for atrazine, ametryn and

diuron seems to confirm that OC content alone is insufficient to explain the sorption of HOCs as

earlier observed by correlating Ko withffc. The OC content cut-off of 1 % for mineral

components controlling sorption may become important for Spodosols, however the magnitude

of mineral material to influence sorption of HOCs in Spodosols would accordingly be

magnitudes higher than SOC influence since the sorption capacities were about ten times or

higher than for carbonatic soils. The negative correlation between sorption capacities of HOC

with alky-C probably suggests that partitioning to the alkyl C plays a minor role in adsorption of

HOC's in these soils studied. The high sorption capacity of HOCs exhibited by Oxisols and

Histosols compared to carbonatic soils confirms that sorption is strongly influenced by aromatic

C content of OM. Haumaier and Zech (1995) suggested that the signal observed at 130 ppm is

likely derived from black carbon and not from humification of native plant material. Since we do

not know the history of burning in the soils that were sampled (except for some Oxisols from

Uganda), we cannot conclude that it is black carbon influencing the sorption properties of the

soils. Already some researchers (Pignatello et al., 2006; Cornelissen, 2005) have suggested

greater sorption capacity of HOCs by black carbon. The high surface area of black could be the

major factor in the observed enhanced sorption capacities. Some of the Oxisols that were

analyzed in this study were obtained from sugar cane fields in Uganda and burning is used for









harvesting of sugar canes. Nevertheless other Oxisols that were obtained from other areas in

Uganda where no burning was used as a method of harvest indicated high sorption capacity

suggesting that it is rather OM from higher plants that contributes to greater sorption capacity.

By comparing the spectra in Appendix B for different soils, aromatic C content for Lauderhill

and Islamorada (Figure B-5) was lower than that for Spodosols (Figure B-4) and Oxisols (Figure

B-6). Despite high OM content, Islamorada which is a Histosol, showed low sorption potential

suggesting that the type of OM in this soil series does not possess high affinity for HOCs which

seems to confirm that aromatic C influences sorption of HOCs.

An overlay of the Bloch Decay and 13C CP-MAS (not shown) indicated a discrimination of

the aromatic signal by CP-MAS. Bloch Decay on the other seemed to discriminate Oxy-Alkyl,

Methoxyl, and the alkyl-C region. Although CP-MAS generally provided better signal to noise

spectra compared to Bloch Decay, direct polarization at a pulse of 60 s gave better signal

compared to direct polarization at 10 s. Due to excessive signal to noise level in the Bloch Decay

analysis, all the other samples were analyzed using 13C CP-MAS.

Conclusions

Stable isotope studies results were consistent with the expected carbon sources but no

relationship was found with sorption. The NMR studies showed differences in functionality of

OM present in carbonatic soils compared to the non-carbonatic soils. Fundemental differences

were observed in the aromatic carbon chemical shifts. This suggests that SOM aromaticity plays

a major role in HOCs sorption. A strong relationship was observed between arom C/alkyl C ratio

(aromatic C index) and Ko. However, aromatic C indices for atrazine, ametryn and diuron were

not related with Ko in Spodosols suggesting that other components other than OC may be

controlling sorption of HOCs in Spodosols.









The 13C CP-MAS NMR spectra indicate fundamental differences in the aromatic carbon

chemical shifts for carbonatic and non-carbonatic soils. Carbonatic soils exhibited low aromatic

C content compared to Oxisols and Histosols. The results indicate the usefulness of CP-MAS

NMR in elucidating the nature and functionalities of OM in soils.










Table 6-1. Physicochemical properties of the soils that were used for


determination. Duplicate samples were analyzed.


Soil name
Hima 3
Tuque
S.Sebastian
S. Anton
Colinas
Bayamon 1
Biscayne 1
Perrine 1
Chekika 1
Aguilita
Saddle Bunch 1
Krome 1
Pennsuco
Yauco
Perine 2
Krome 2
Cadjoe
Catano
Lauderhill 1
Matecumbe 1


Type
Gelisol
carbonatic
carbonatic
carbonatic
carbonatic
Oxisol
carbonatic
carbonatic
carbonatic
carbonatic
carbonatic
carbonatic
carbonatic
carbonatic
carbonatic
carbonatic
carbonatic

Histosol
Histosol


Ametr Koo 61DC
185 -12.08
106 -15.14
143 -15.73
199 -16.90
148 -18.29
173 -18.84
118 -18.85
91 -20.53
175 -21.17
130 -20.99
95 -20.81
213 -21.69
108 -22.11
97 -22.15
95 -22.35
181 -22.56
106 -24.20
164 -23.74
226 -25.77
272 -25.97


6 13C
-12.40
-15.47
-16.14
-17.06
-18.17
-19.28
-19.61
-20.60
-21.02
-21.24
-22.39
-21.67
-21.98
-22.08
-22.41
-23.09
-22.54
-23.73
-25.67
-25.93


Av 5 3C
-12.24
-15.31
-15.93
-16.98
-18.23
-19.06
-19.23
-20.57
-21.10
-21.11
-21.60
-21.68
-22.05
-22.11
-22.38
-22.83
-23.37
-23.74
-25.72
-25.95


SD
0.23
0.23
0.29
0.11
0.08
0.31
0.54
0.05
0.11
0.17
1.12
0.01
0.09
0.05
0.04
0.37
1.17
0.01
0.07
0.03


stable isotope
















y = -2.6989x + 95.763
R2 = 0.0335


**
*


-8.00


-10.00 -12.00 -14.00 -16.00 -18.00 -20.00 -22.00 -24.00 -26.00 -28.00


613C signatures

Figure 6-1. Relationship between the Ko values of ametryn and corresponding 613C values for
carbonatic and non-carbonatic soils.



















C4 plants


Intermediate


U mE


-10.00 -12.00 -14.00 -16.00 -18.00 -20.00 -22.00
13C/12C


Carbonatic PR 0 Carbonatic FL Histosols FL


Figure 6-2. Distribution of 613C in different soil classifications.


C3 plants


m m U


24.00 -26.00 -28.00



o Non-Carbonatic PR


-7




























I . I . II .. .
200 1 s 1 o so o Chemical shift (ppm)

Figure 6-3. 13Carbon Cross Polarized Magic Angle Spinning Nuclear Magenetic Resonance
spectra for Algae grown in our laboratory.


ERis c.ynci I\/I arl


200 150 100 50


o Chemical shift (ppm)


Figure 6-4. 13Carbon Cross Polarized Magic Angle Spinning Nuclear Magenetic Resonance
spectra for Biscayne a typical Marl soil from Dade County, South Florida.
















2000

y = 646.91x + 19.135
R2 = 0.8335
1500



1000




500 M



0
0.00 0.50 1.00 1.50 2.00 2.50
Arom C/Alkyl C


Figure 6-5. Correlation between aromatic C/alkyl C with diuron Koc.










1200



1000


y = 327.52x 5.6968
800R2 = 0.7872



o 600


400 -*



200 -t


0
0.00 0.50 1.00 1.50 2.00
Arom C/Alkyl C


Figure 6-6. Correlation between aromatic C/alkyl C with ametryn Koc.


2.50











1400 *

1200

1000 Diuron
y = 19.73x + 89.483
0 800 R2 = 0.3608

600 -

400 -- ...........Ametryn
Sy = 15.3321 46.145
200 */ R2 = 0.4799

0
0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00
Arom C content

Diuron m Ametryn


Figure 6-7. Correlation between aromatic C with ametryn and diuron Koc.

















Atrazine
y = 8.4729x 45.933
R2 = 0.6996


Figure 6-8. Correlation between aromatic C with atrazine Koc.


450

400

350

300

250

200

150

100

50

0
0.00


5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00
Arom C










450

400
Atrazine
350 y = 143.98x + 3.7593
R2 = 0.7928
300 -

o 250
N
200

150 -

100 -4

50 -

0
0.00 0.50 1.00 1.50 2.00 2.50 3.00
Arom C/ Alkyl C


Figure 6-8. Correlation between aromatic C/alky C with atrazine Koc.









CHAPTER 7
CONCLUSIONS AND RECOMMENDATIONS

Conclusions

The results of this study indicate that OC content of OM differs significantly between soils

of different hydrologic and vegetative settings, and that WLOI is not a reliable measure of OM,

even for organic soils, unless weight loss below 200 C is taken into account.

Carbonatic soils were found to adsorb pesticides less compared to non-carbonatic soils.

Marl soils adsorbed pesticides even less compared to the outcrop carbonatic soils. The NMR data

indicate that Algae is the primary producer in the marl soils, implying that its contribution to OC

aromaticity which appeared to control the sorption is limited. The lack of aromatic C in

carbonatic soils OM probably leads to the low sorption capacities exhibited by marl and rock

outcrop carbonatic soils from South Florida and Puerto Rico. The linear relationship obtained by

normalizing the sorption coefficients (Kd) with fraction of OC (fo,) indicates that OC controls the

adoption of HOCs in carbonatic soils. However, the data vairiability across different soil types

suggest that quality of OM is equally important criteria for sorption. The degradation studies

indicted that diuron is relatively persistent. Using the modified degradation equation rids the

analysis of uncertainties created by initial concentration (Mo), given that the recoveries in soils

were lower than would be expected in solution chemistry. The GUS score also showed higher

potential for the chemical to leach to groundwater. Non-marl carbonatic soils generally showed

medium potential to leach and the GUS scores for marl soils also shifted to lower leaching

potential values. This may indicate lower leaching potential for ametryn compared to diuron.

The results of this study may be useful in designing management strategies and farming

practices, aimed at protecting the aquifers that underlie the carbonatic soils. These strategies may

include revision of application rates for pesticides applied to crops grown on carbonatic soils,









adding soil amendments and long term change of the nature of OM by altering the organic

carbon primary producers.

Recommendations

To avoid contamination of the water resource in Puerto Rico and the shallow Biscayne

aquifer in South Florida where carbonatic soils are widely used for agriculture, it is

recommended that application rates be adjusted to cater for the low sorption capacity of the

carbonatic soils. Amendment of the carbonatic soils with material with high sorptive properties

may provide long term remedies to the leaching potential of HOCs hence protecting the shallow

South Florida aquifers of South Florida.

Since chemical decompose leaving behind metabolite which may have longer half lives

than the parent compounds and sometime even more toxic, characterizing the behavior of the

metabolite in these agriculturally important soils is essential.










APPENDIX A
SELECTED PESTICIDE SORPTION ISOTHERMS


16

E 14
12
z
O 10
S8
S6
0
wC 4
Q2


y= 2.7636x
R2= 0.9943


0 1 2 3 4 5 6
SOLUTION CONC., (mg/L)

Figure A-i. Sorption isotherm for ametryn in Biscayne from Miami Dade Florida (marl-
carbonatic).




180

160 -

140 Kd = 30
E
120 R2 0.9937



a 80 -
w
60
0 40


0 1 2 3 4 5
SOLUTION CONC., (mg/L)


Figure A-2. Sorption isotherm for ametryn in Lauderhill from Miami Dade, South Florida
(Histosol).















S20
E

0 15
z
O

w 10

0
S5


Kd = 4.6
R2 = 0.9365


0 1 2 3 4 5
SOLUTION CONC., (mg/L)

Figure A-3. Sorption isotherm for ametryn in Pomona from Aston Cary, Alachua County Florida
(Spodosol).



25 n


20
E

S15
z
0

w 10

uO
05
a 5
<


Kd = 4.6
R2 = 0.9694


0 1 2 3 4 5
SOLUTION CONC., (mg/L)

Figure A-4. Sorption isotherm for atrazine in a Kakira soil from Jinja, Uganda (Oxisol).

















Kd = 6.59
R2 = 0.9746


0 1 2 3 4 5
SOLUTION CONC., (m g/L)

Figure A-5. Sorption isotherm for ametryn in Biscayne (marl-carbonatic).



300


250

E
200
z
0 150


S100
0

< 50


Kd = 65
R2 = 0.9585


0 0.5 1 1.5 2 2.5 3 3.5
SOLUTION CONC., (mg/L)

Figure A-6. Sorption isotherm for ametryn in Lauderhill from Miami Dade, South Florida
(Histosol).















50 -
Kd = 23
40 R2 = 0.9466


o 30
a
O
0 20
o
S10


0
0 0.5 1 1.5 2 2.5
SOLUTION CONC., (mg/L)

Figure A-7. Sorption isotherm for ametryn in Pomona from Aston Cary, Alachua County Florida
(Spodosol).




60


a 50 -
a Kd =11
E. R2 =0.9608
40 -

30
30

m 20
0O
0 -


0-
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
SOLUTION CONC., (mg/L)

Figure A-8. Sorption isotherm for ametryn in a Kakira soil from Jinja, Uganda (Oxisol).

















Kd = 12
R2 = 0.9667


0 0.5 1 1.5 2 2.5 3
SOLUTION CONC., (mg/L)

Figure A-9. Sorption isotherm for diuron in Biscayne (marl-carbonatic).




200
180
160
6 Kd =156
140 R2 0.9963
S120
o 100
S80
a 60
0
o 40
20 -
0-
0 0.2 0.4 0.6 0.8 1 1.2
SOLUTION CONC., (mg/L)

Figure A-10. Sorption isotherm for diuron in Lauderhill from Miami Dade, South Florida
(Histosol).















Kd = 14
R2 = 0.9579


0 0.5 1 1.5 2 2.5
SOLUTION CONC., (mg/L)

Figure A-11. Sorption isotherm for diuron in Pomona from Aston Cary, Alachua County Florida
(Spodosol).



60


Kd = 33
R2 = 0.9592


0 0.2 0.4 0.6 0.8 1 1.2 1.4
SOLUTION CONC., (mg/L)

Figure A-12. Sorption isotherm for diuron in a Kakira soil from Jinja, Uganda (Oxisol).









APPENDIX B
SELECTED SOIL ORGANIC MATTER CARBON CROSS POLARIZED MAGIC ANGLE
SPINNING NUCLEAR MAGNETIC RESONANCE SPECTRA

The selected spectra in the figures below for 13C cross-polarization magic angle spinning

nuclear magnetic resonance (CP-MAS NMR) show the fundamental differences and similarities

in the chemical shifts of the functionalities of OM from soil of different geographical origins,

series and vegetation cover. Two sample spectra for each soil group were selected except for

algae which was grown in our laboratory for purposes of confirming our previous observations

for carbonatic soils NMR chemical shift patterns. The spectra were done at a spin of 13 KHz, 1.5

ms contact time, 1 s recycle time and spectra were processed with a 100 Hz line broadening and

baseline correction. The scale for the chemical shift on the x-axis of the NMR spectra is in ppm.




Algae Key Vaca- FL










- V---- r-- /--- uw Vyr- -- -- f ^ v
250 200 150 100 50 0 -ppm 250 200 150 100 50 0 -0ppm
Figure B-1. (L-R) Nuclear magnetic resonance spectra for Laboratory grown Algae and
carbonatic soil (Florida Keys)











Biscayne Marl.


Perrine Marl I FL


....... ^.............. ....... ... ..... ...... ......... ............... ... ............... ----..... I I----I--I---I
200 1SO 100 50 0 200 150 100 50 0
ppm ppm
Figure B-2. Nuclear magnetic resonance spectra for carbonatic soils from Dade County, South
Florida.


Colinas- PR


250 200 150 100 s5 0 -50ppm 00 150 100 5
Figure B-3. Nuclear magnetic resonance spectra for carbonatic soils from Puerto Rico.












Pomona FL


Pomona -FL
Bh2 Horizon


200 150 100 5o o pp 250 200 150 100 50 0 -pp
Figure B-4. Nuclear magnetic resonance spectra for Spodosols from Alachua County Florida.


Lauderhill FL


Islamorada FL


v "I II ,I 'I I I '
2 I .. . I I i 200 150 100 50 0
200 150 100 50 0 ppm I ,
ppm ppm
Figure B-5. Nuclear magnetic resonance spectra for Histosols from Miami Dade, Florida (L) and
Monroe County, Key West, Florida (R).











Oxisol 2 Ug
Kakira Jinja


Oxisol 4 Ug
Hima


* 1 T I I I. 1 I - I -
250 200 150 100 so 0 -s ppm 250 200 150 1a0
Figure B-6. Nuclear magnetic resonance spectra for Oxisols from Uganda.


50 0 -50 ppm









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BIOGRAPHICAL SKETCH

Gabriel Nuffield Kasozi was born in 1969 at Rubaga (Kampala, Uganda). He was born to

Mrs. Noelina and Mr. Lawrence Lubega of Masajja Kyadondo. He received his Bachelor of

Science with Education, majoring in chemistry from Makerere University Kampala in 1992. He

received his Master of Science, majoring in Chemistry from Makerere University Kampala in

2002. He was awarded a PhD in December 2007.





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1 CHARACTERIZATION OF SORPTION AND DEGRADATION OF PESTICIDES IN CARBONATIC AND ASSOCIATED SOILS FROM SOUTH FLORIDA AND PUERTO RICO, AND OXISOLS FROM UGANDA By GABRIEL NUFFIELD KASOZI A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007

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2 2007 Gabriel Nuffield Kasozi

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3 To my Dad, the late Lawrence Lubega of Masajja Kyadondo, Uganda. His love, words of wisdom and integrity will always remain a light to my path. Ma y God rest his soul in eternal peace.

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4 ACKNOWLEDGMENTS I am extremely indebted to my major adviso r, Dr. Peter Nkedi-Kizza, for his unwavering and parental support. His guidance and the exper tise that he has shared with me during the pursuit of this study are greatly a ppreciated. I feel so lucky to ha ve been able to work under his guidance. He has cultivated in me a new strength by allowing me to exercise creative thinking in both academics and in daily life. I am also thankf ul to the rest of my committee (Drs. Yucong Li, D. Powell and D. Hodell) for their significant cont ribution toward this re search. Their ideas and suggestion have gone a great length in enhancing my academic and research experience at the University of Florida. I am especially thankful to Dr. Harris for accep ting to be part of my advisory committee. He has never at one time turned me away de spite his busy schedule. He has been such a tremendous mentor and he has shared with me his experience and his contri bution to this study is greatly appreciated. He has given me all he is go t and selflessly shared with me his enormous experience and his thought provoking and innova tive ideas have propelled me very far into getting an insight in the world of soil science. I am grateful to Dr. Dean Rhue for his continued assistance and to the entire f aculty of the Soil and Water Scie nce department whose support and ideas have been essential during th e course of my study. I am especia lly thankful to Bill Porthier for his assistance with the stable isotope analysis A number of professors at the University of Florida have helped sharpen my sc ientific skills and I am grateful for their efforts. It has been a great learning experience and it has positively im pacted my life. I am highly indebted to Dr. Bernard Kiremire at the Department of Chemistr y Makerere University Kampala, for giving me chance to pursue graduate school. May the Al mighty God reward him abundantly. I am also thankful to Dr. Patrick G. Ha tcher at Old Dominion Univeristy for accepting to run the NMR analysis in his laboratory.

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5 I am thankful to my friends, Dr. D Herrera Dr. M. Josan, Dr. E Bagu, Mr. M. Ssematengo, Mr. T. Kayondo, Mr. S. Muyingo, Mr. A. Simbwa, Mr K. Mukalazi, Mr. B. Kamugisha, Mr. M. Khalid, Mr. M. Geiger, and many others; the li st is long, thank you for the love and support. Special thanks go to my family. I love you all. I am especially thankful to my wife Allen for being a wonderful companion and being there for me at all times in all situations. Thank you for giving me a beautiful little angel Danielle. Finally I thank the Almighty for seeing me through all.

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6 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........9 LIST OF FIGURES.......................................................................................................................10 LIST OF ABBREVIATION.......................................................................................................... 13 LIST OF TERMS...........................................................................................................................14 ABSTRACT...................................................................................................................................16 CHAP TER 1 INTRODUCTION..................................................................................................................18 2 LITERATURE REVIEW.......................................................................................................23 Carbonatic Soils Formation.................................................................................................... 23 Soil Organic Matter (SOM)....................................................................................................27 Review of the Methods...........................................................................................................30 Soil Organic Carbon Determination................................................................................ 31 Elemental Analysis (Total Organic Carbon, Total Carbon, Total Nitrogen) ..................33 UV-vis and Fluorescence Spectroscopy..........................................................................33 FT-IR...............................................................................................................................33 Stable Isotopes Characterization (13Carbon, Carbon-Nitrogen Ratio).......................... 34 Cross Polarization Magnetic Angle Sp inning Nuclear Magnetic Resonance (CPMAS 13C-NMR)...........................................................................................................35 Tetramethylammonium Hydroxide (TMAH) Therm ochemolysis Coupled with Gas Chromatography/ Pyrolysis GC-MS............................................................................ 37 Fiber Optics and Spectroscopic Analysis........................................................................ 37 Key Findings...................................................................................................................38 What is yet to be known about the Characteristics of Organic Matter ............................ 38 Chemicals Studied and Rationale........................................................................................... 39 Atrazine...........................................................................................................................39 Diuron..............................................................................................................................40 Ametryn........................................................................................................................ ...40 Sorption and Solute Transport in a Porous Medium..............................................................41 Interaction with Organic Carbon..................................................................................... 42 Sorption Models......................................................................................................................43 The Linear Sorption Model............................................................................................. 43 Freundlich Isotherm Model............................................................................................. 44 Lagmuir Sorption Model................................................................................................. 44 Pesticide Degradation.............................................................................................................45

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7 Environmental Fate of Pesticides........................................................................................... 46 Hypotheses..............................................................................................................................46 Study Objectives.....................................................................................................................47 3 MATERIALS AND METHODS........................................................................................... 50 Description of Sampling Sites................................................................................................ 50 Pesticides Studied...................................................................................................................52 Determination of Soil Properties............................................................................................ 52 Soil pH.............................................................................................................................52 Organic Carbon and Organic Matter Determination....................................................... 52 Sample homogenization...........................................................................................53 Walkley and Black method (WB)............................................................................53 Thermogravimetry (TG)........................................................................................... 54 Weight loss on ignition (WLOI).............................................................................. 54 Muffle furnace.......................................................................................................... 54 Carbon Stable Isotope Determination............................................................................. 55 Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance spectroscopy.................................................................................................................55 Soil treatment for Cross Pola rized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance spectroscopy analysis......................................................... 55 Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance spectroscopic determination................................................................................. 56 Sorption of Pesticides on Soils............................................................................................... 57 Pesticide Degradation.............................................................................................................59 4 ORGANIC MATTER CHAR ACTERIZATION IN CARBONATIC AND ASSOCIAT ED SOILS FROM SOUTH FL ORIDA AND PUERTO RICO USING THERMAL AND OXIDATION METHODS........................................................................ 68 Introduction................................................................................................................... ..........68 Materials and Methods...........................................................................................................70 Sample Homogenization.................................................................................................70 Organic Carbon, Organic Matter and Carbonate Determ ination..................................... 70 Results and Discussion......................................................................................................... ..71 Conclusions.............................................................................................................................76 5 SORPTION AND DEGRADATION OF SELECTED PESTICIDES IN CARBONATIC AND ASSOCIAT ED SOILS....................................................................... 88 Introduction................................................................................................................... ..........88 Materials and Methods...........................................................................................................90 Atrazine Analysis............................................................................................................ 90 Ametryn Analysis............................................................................................................ 91 Diuron Analysis...............................................................................................................91 Model Fitting...................................................................................................................91 Pesticide Degradation......................................................................................................92

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8 Quality Control/Quality Assurance................................................................................. 92 Results and Discussion......................................................................................................... ..92 Atrazine Sorption.............................................................................................................92 Ametryn Sorption............................................................................................................95 Ametryn Degradation...................................................................................................... 96 Diuron Sorption...............................................................................................................96 Diuron Degradation.........................................................................................................97 Vulnerability of Groundwater to HOCs Contamination................................................. 98 Conclusions.............................................................................................................................99 6 CROSS POLARIZED MAGIC ANGLE SPINNING 13CARBON NUCLEAR MAGNETIC RESONANCE AND STABLE ISOTOPE CHARACTERIZATION OF ORGANIC MATTER IN CARBONATIC AND NON-CARBONATIC SOILS OF SOUTH FLORIDA, PUERTO RICO AND OXISOLS FROM UGANDA........................ 118 Introduction................................................................................................................... ........118 Materials and Methods.........................................................................................................119 Results and Discussion......................................................................................................... 119 Stable Isotope Determination........................................................................................ 119 13Carbon Cross Polarized Magic Angle Sp inning Nuclear Magnetic Resonance Analysis......................................................................................................................120 Conclusions...........................................................................................................................122 7 CONCLUSIONS AND RECOMME NDATIONS............................................................... 133 Conclusions...........................................................................................................................133 Recommendations................................................................................................................ .134 APPENDIX A SELECTED PESTICIDE SORPTION ISOTHERMS.........................................................135 B SELECTED SOIL ORGANIC MATTER 13CARBON CROSS POLARIZED MAGIC ANGLE SPINNING NUCLEAR MAGNETI C RESONANCE SPECTRA........................ 141 LIST OF REFERENCES.............................................................................................................145 BIOGRAPHICAL SKETCH.......................................................................................................156

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9 LIST OF TABLES Table page 2-1 Chemical properties of at razine, diuron and am etryn........................................................ 48 3-1 Description of the sampling sites in Florida U.S.A. and Puerto Rico ............................... 62 3-2 Description of the sampling sites in Uganda East Africa .................................................. 63 3-2 Carbon-13 cross polarized m agic angle spinning nuclear magnetic resonance chemical shifts for soil organic matter............................................................................... 64 4-1 Organic carbon (OC) and organic matter (OM) determ ination in carbonatic soils using WB, TG, and WLOI methods, and carbonates. Soils sampled 0-15 cm.................. 77 4-2 Organic carbon (OC) and organic matter (OM) determ ination in Histosols from Florida (FL) and Puerto Rico (PR) using WB, TG, and WLOI methods.......................... 78 4-3 Organic carbon (OC) and organic matter (OM) determ ination in Spodosols using WB, TG and WLOI methods............................................................................................. 78 5-1 Soil organic carbon content, and at razine distribution coefficients (Kd) and organic carbon sorption coefficients (Koc) for carbonatic soils from Florida and Puerto Rico.... 101 5-2 Soil organic carbon content, atrazine, di uron and am etryn distribution coefficients (Kd) and sorption coefficients (Koc) for Oxisols from Uganda and Puerto Rico............. 102 5-3 Ametryn and diuron degradation and sorpti on co efficients for carbonatic soils from Florida and Puerto Rico................................................................................................... 103 5-4 Soil organic matter content, and atrazine distribution coefficien ts and organic carbon sorption coefficients for Histosols from Florida.............................................................. 104 5-5 Soil organic matter content, and atrazine distribution coefficien ts and organic carbon sorption coefficients for Spodosols from Florida............................................................ 105 5-6 Diuron half-life and GUS scores in soils from Florida, Puerto Rico and Uganda........... 106 5-7 Ametryn half life and GUS scores in soils from Florida, and Puerto Rico..................... 107 6-1 Physicochemical propertie s of the soils that were used for stable isotope determination. Duplicate samples were analyzed............................................................ 124

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10 LIST OF FIGURES Figure page 2-1 Classification of 13Carbon nuclear magenitic resona nce spectra (Kgel-Knabner, 2002, modified from Bortiy atinski et al., 1996)................................................................ 49 3-1 Typical rock-plowed carbonatic soil fr om Homestead, Miami Dade County South Florida. Gravely, well drained soils................................................................................... 65 3-2 Algal derived secondary cal cite flakes precipitation lead ing to for mation of marl carbonatic soils...................................................................................................................66 3-3 Set up of the degradation of pesticides in polycarbonate tubes with loose covers to prevent excessive m oisture loss......................................................................................... 67 4-1 Verification of the TG calibration using st andard calcium carbonate. Line 1 is weight loss, while line 2 is 1st temperature derivative.................................................................. 79 4-2 Confirmation for the onset decomposition temperature for calcium carbonate preheated to 550 oC for 2 h, decomposition starts at 600 oC. Line 1 Figure B is temperature profile and Line 2 is th e derivative for weight loss onset.............................. 80 4-3 TG thermograms A) For carbonatic soils, pre-heated at 110 oC for 24 hour. B) For Histosols, pre-heated at 110 oC for 24 hour.......................................................................81 4-4 TG analysis of a Hi stosol heated to 180 oC, cooled then heated to 1000 oC. Line 1 is the temperature profile and line 2 is the weight loss......................................................... 82 4-5 TG analysis of organic soil material (from a Histosol), using isothermal steps to investigate energy dependency for wei ght loss versus time. Line 1 is oven temperature and line 2 is soil sample percent weight loss................................................. 83 4-6 Correlation between TG %OM and WB %O C. A) For carb onatic soils. B) For Histosols. C) For Spodosols............................................................................................... 84 4-7 Correlation between WLOI %O M and W B %OC for Histosols....................................... 85 4-8 Correlation between WLOI %OM a nd TG %OM in carbonatic soils. .............................. 85 4-9 X-ray diffraction curves for Bi cayne series (carbonatic soil). ........................................... 86 4-10 X-ray diffraction curves for a Ug andan Oxisol from Kakira Jinja.................................... 87 5-1 Diuron sorption isotherm of Lauderhill series (Histosol) from South Florida................ 108 5-2 Correlation of atrazine distribution coefficients (Kd) with the fraction of organic carbon for different soil series......................................................................................... 109

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11 5-3 Correlation of atrazine Kd with fraction of organic carbon for A) For carbonatic soils, B) For Histosols, C) For Oxiosols and D) For Spodosols. Slopes represent average Koc....................................................................................................................................110 5-4 Correlation of ametryn Kd with fraction of organic ca rbon. A) For carbonatic soils. B) For Histosols. C) For Oxiosols. D) For Spodosols..................................................... 111 5-5 Correlation of diuron Kd with fraction of organic car bon. A) For carbonatic soils. B) For Histosols. C) For Oxiosols. D) For Spodosols.......................................................... 112 5-6 Graphical represen tation of average Koc values for the different soil types analyzed. Error bars indicate 95 % confidence interval................................................................... 113 5-7 Degradation of diuron in Lignumvitae series from Florida Keys, South Florida. ........... 114 5-8 Selected degradation curves for diuron in carbonatic soils from South Florida. ............. 115 5-9 Groundwater ubiquity score classificati on for diuron in different soil types. .................116 5-10 Groundwater ubiquity score classificati on for am etryn in carbonatic soils and Spodosols.........................................................................................................................117 6-1 Relationship between the Koc values of ametryn and corresponding 13C values for carbonatic and non-carbonatic soils................................................................................. 125 6-2 Distribution of 13C in different soil classifications........................................................126 6-3. 13Carbon Cross Polarized Magic Angle Spi nning Nuclear Magenetic Resonance spectra for Algae grown in our laboratory...................................................................................127 6-4 13Carbon Cross Polarized Magic Angle Spinning Nuclear Magenetic Resonance spectra for Biscayne a t ypical Marl soil from Dade County, South Florida.................... 127 6-5 Correlation between aroma tic C/alkyl C with diuron Koc................................................128 6-6 Correlation between aromatic C/alkyl C with am etryn Koc.............................................129 6-7 Correlation between aromatic C with ametryn and diuron Koc.......................................130 6-8 Correlation between aromatic C with atrazine Koc..........................................................131 6-8 Correlation between aromatic C/alky C with atrazine Koc..............................................132 A-1 Sorption isotherm for ametryn in Biscayne from Miam i Dade Florida (marlcarbonatic)........................................................................................................................135 A-2 Sorption isotherm for ametryn in La uderhill from Miam i Dade, South Florida (Histosol)..........................................................................................................................135

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12 A-3 Sorption isotherm for ametryn in Pomona from Aston Cary, Alachua County Florida (Spodosol). .................................................................................................................... ...136 A-4 Sorption isotherm for atrazine in a Ka kira soil from Jinja, Uganda (Oxisol). .................136 A-5 Sorption isotherm for ametryn in Biscayne (m arl-carbonatic)........................................ 137 A-6 Sorption isotherm for ametryn in La uderhill from Miam i Dade, South Florida (Histosol)..........................................................................................................................137 A-7 Sorption isotherm for ametryn in Pomona from Aston Cary, Alachua County Florida (Spodosol). .................................................................................................................... ...138 A-8 Sorption isotherm for ametryn in a Kaki ra soil from Jinja, Uganda (Oxisol)................. 138 A-9 Sorption isotherm for diuron in Biscayne (m arl-carbonatic)........................................... 139 A-10 Sorption isotherm for diuron in Laud erhill from Miami Dade, South Florida (Histosol)..........................................................................................................................139 A-11 Sorption isotherm for diuron in Pomona from Aston Cary, Alachua County Florida (Spodosol)..................................................................................................................... ...140 A-12 Sorption isotherm for diuron in a Kaki ra soil from Jinja, Uganda (Oxisol). ................... 140 B-1 Nuclear magnetic resonance spectra for Laboratory grown Algae and carbonatic soil (Florida Keys) ..................................................................................................................141 B-2 Nuclear magnetic resonance spectra fo r carbonatic soils from Dade County, South Florida. ....................................................................................................................... ......142 B-3 Nuclear magnetic resonance spectra fo r carbonatic soils from Puerto Rico. .................. 142 B-4 Nuclear magnetic resonance spectra fo r Spodosols from Alachua County Florida........ 143 B-5 Nuclear magnetic resonance spectra for Hi stosols from Miami Dade, Florida (L) and Monroe County, Key West, Florida (R).......................................................................... 143 B-6 Nuclear magnetic resonance spec tra for Oxisols from Uganda....................................... 144

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13 LIST OF ABBREVIATION CEC: Cation exchange capacity CP-MAS NMR: Cross polarized magic angl e spinning nuclear magnetic resonance DOM: Dissolve organic matter FL: Florida FDEP: Florida Department of Environmental Protection GUS: Groundwater ubiquity score HOC: Hydrophobic organic chemical NAWQA: National Water Quality Assessment OC: Organic carbon OM: Organic matter PR: Puerto Rico SOM: Soil organic matter SSSA: Soil Scince Society of America TG: Thermogravimetry TOC: Total organic carbon UG: Uganda USDA-NRCS: United States Department of Agriculture, National Resources Conservation Service USEPA: United States Environment Protection Agency USGS: United States Geological Services UV: Ultraviolet WLOI: Weight loss on ignition

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14 LIST OF TERMS Adsorption: The process through which a net accumulation of a substance occurs at the common boundary of two contiguous phases (Lal and Shukla, 2004). Absorption: The process through which a ne t accumulation of a substance occurs inside the solid phase. Bh Horizon: Horizon below the A, E or O horizon formed due to obliteration of the original rock solubilizing Fe, Al, Si and organic matter complexes and translocating the illuvial aluminum silicate organic complexes in the region where the seasonal water table fluctuations occur. Bryozoa: Tiny marine animals that build col onies with their calcareous shells. Carbonatic soil: Soil composed of more than 40 % carbonates (Calcite and/or dolomite) in their mineralogy. Chemisorption: Retention of a substance on a surface through formation of chemical bonds. Degradation: Degradation in this manuscript is operationally defined as the extractable disappearance of a pesticide (amount rema ining) in a soil sample at time t. This may involve biotic (bio logical) and abiotic (chemical) transformation. Distribution Coefficient (Kd): Coefficient obtained from the ratio of the equilibrium concentration of a substance sorbed on a solid phase to the concentration of the solution. Flat: Area characterized by a continuous surface or stretch of land that is smooth, even, or horizontal, or nearly so, and that lacks any significant curvature, slope, elevations, or depressions. (Jackson, 1997). Half-life: Time required for dissipation or degr adation of a chemical to half its initial concentration (Hor nsby et al., 1996). Marl: Deposit in marine or fresh water of very fine secondary calcium carbonate as a result of chemical action of algal mats and organic detritus (periphyton) photosynthesis. Organic matter: Plant and animal residue in the soil at various stages of decomposition. Oxisols: Mineral soils with an oxic horiz on within 2 cm of the surface or plinthite as a continuous phas within 30 cm of the surface and do not have a spodic or argillic horizon above the oxic horizon.

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15 Pesticide: Substances or mixture ther e of intended for preventing, destroying, repelling, or mitigating any pest. Also, any substance or mixture intended for use as a plant regulator, de foliant, or desiccant (EPA, 2007). Sapric soil matrix: Most highly decom posed of all organic soil material. Sorption: Sorption is a combination of th e adsorption and absorption processes. Spodosols: Mineral soils that have a spodic horizon or a placic horizon that over-lies afragipan. Sources: SSSA, 1997; Laird and Sawhney, 2002; FDEP, 1994.

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16 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy CHARACTERIZATION OF SORPTION AND DEGRADATION OF PESTICIDES IN CARBONATIC AND ASSOCIATED SOILS FROM SOUTH FLORIDA AND PUERTO RICO, AND OXISOLS FROM UGANDA By Gabriel Nuffield Kasozi December 2007 Chair: Peter Nkedi-Kizza Cochair: Yuncong Li Major: Soil and Water Science Sorption and degradation are major processes that influence the fate of pesticides in the environment. This study was designed to character ize these processes in carbonatic, associated non-carbonatic soils from South Florida and Puer to Rico and Oxisols from Uganda. Spodosols from Alachua County were collected for comp arison. Carbonatic soils are characterized by a high water table, and underlain by porous lim estone bedrock. These soils support 85 % of Floridas vegetables and tropical fruits. The subtropical to tropical climates in South Florida, Puerto Rico and Uganda encourage proliferation of pests that requi re pesticides control. Several pesticides applied to crops grown on carbonatic soils have been reported in both surface and ground water of South Florida and Puerto Rico. Although a lot of research has been done on characterizing the sorption of or ganic pesticides in non-carbona tic soils, a literature search indicates lack of these da ta for carbonatic soils. The conversion factors from organic matter (O M) to organic carbon (OC) of 1.74, 1.48 and 1.44 obtained for carbonatic soils, Histosols and Spodosols, respectiv ely indicate that OC content in OM differs between soils from different vegetative and hydrologic regi mes. Data on atrazine, ametryn, and duiron sorption indicate that these pesticides adsorb less on carbonatic soils. The

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17 sorption coefficients for the noncarbonatic soils were about 3 tim es higher than of carbonatic soils. Marl carbonatic soils showed even lower so rption potential and the order was Marl < rockplowed carbonatic soils< Hist osols < Oxisols < Spodosols. The data indicated a linear relationship between sorption and OC content although comparison across soils showed that organic matter quality is important in sorption. Degradation of diuron and ametryn was not different between carbonatic and non-carbonatic soils and wa s not influenced by sorption. In order to understand the fundamental di fferences in OM that may account for the anomalous behavior of carbonatic soils, 13C CP-MAS NMR technique wa s used. Carbonatic soils differed from the other soils in terms of aromatic carbon ch emical shifts by showing low aromaticity. A strong relationship was found between aromatic C/alkyl C and Koc. This implies that the aromatic carbon cont rols the sorption of neutral hydrophobic organic chemicals.

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18 CHAPTER 1 INTRODUCTION The increasing world population and decreasing ar able land due to urbanization has led to increased s trategies aimed at sustainable f ood production. In addition to using improved crop varieties, irrigation techniques a nd mechanization, fertilizer a nd pesticide usage has increased over the years. Pesticide consumption in the worl d is estimated to be 2.5 billion kg (Pimental, 1995) of which about 20 % is consumed by United States alone. The U.S. annual pesticide usage increased by 42 million kg from 1992 to 1997 (G ianessi and Silver, 2000). In 1991, an annual consumption of 600 pesticide active ingredients amounting to 0.5 billion kg was reported, compared to 86 million kg reported in 1964 and 50 million kg in 1945 (Aspelin, 1994; Pimentel, 1995). As a result, several pesticides among those w ith highest use have been detected in water monitoring programs from across the regions of the United States (Banks et al., 2005; USGS, 1999; Larson et al., 1997; Miles and Pfueffer 1997; USEPA, 1992; Ritter et al., 1987). The results of the U.S. National Water Quality A ssessment (NAWQA) mon itoring program showed widespread detection of pestic ides in both streams and groun d water samples (Gilliom, 2007; USGS, 1999). Recent studies (Zhou et al., 2003; Scott et al., 2002) reported the potential of endosulfan, (given its high sorption coefficient (Ko)) to contaminate South Floridas surface water via runoff. Levels of Endosulfan above th e surface water quality criteria of the Florida Department of Environment Protect ion (FDEP) have been reported in South Florida water canals (Miles and Pfueffer, 1997). Atrazine has also been reported in both surface and ground water within Miami Dade County (Miles and Pfueff er, 1997). Across the U.S., atrazine and its metabolite deethylatrazine are the most frequently detected pesticides in the water resources (Gillion, 2007). Between 1996 and 1997, atrazine, chlorpyrifos, ch lorothanil and endosulfan comprised the most frequently detected pesticides (at levels below EPA water criteria for fresh

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19 water) in South Florida surface waters with occurrence of 92%, 81%, 85% and 100% of the analyzed samples, respectively (Scott et al, 2002). Given the shallow Biscayne aquifer, the numerous water canals and the porou s nature of the calcium carbonate bedrock in South Florida, the presence of pesticides in surface waters, poses risk to gro undwater contamination since these two water resources are interc onnected. About half of the U. S. urban population relies on groundwater supplies as source fo r drinking water and the proportion increases in rural areas (National Research Council, 1986 ). Maintaining sustainable ag ricultural production, conserving of soils, and protecting natural eco systems, the water resources a nd the environment, require an understanding of the processes that control the fate of organic pollutants in th e soil and water resources. This necessitates designing research strategies and implementation of effective management practices aimed at controlling envi ronmental pollution. Regulation and registration of pesticides used, implementation of integrated pesticide management (IPM), and observance of application rates and timing may go a long way in reducing pesticide contamination. In Texas for instance, a reduction in detection rates was obser ved following a federal ban of diazinon (Banks et al., 2005). Soils are recipients of the applied agrochemical s and as such there is a potential danger for these pesticides to reach surface and ground water resources via non-point sources. Sorption and degradation are majo r processes that determine the fate of pesticides in the environment (Karapanagioti et al., 2001). The slow water movement and interaction of pesticides with the soil matrix and microbi al communities, allows for sorption and degradation of pesticides (USGS, 1999) which may reduce contamination of groundwater resources. Carbonatic soils from South Florida have been found to adsorb pest icides much less compared to the non-carbonatic soils from within the same area (Nkedi-Kizza et al., 2006). Gi ven the low pesticide sorption characteristics of carbonatic soil s, and the high water tables with in this area, an understanding of

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20 the interactions of pesticides in these soils is critical. Their low pesticide sorption potential presents concerns to the shallow Bisca yne aquifer and the Everglades ecosystem. There are 510 official soil series descri ption with carbonatic mineralogy in the United States. Among the states with the highest occu rrence of carbonatic soil s is Nevada with 123, followed by Utah (99), Texas (95), and Idaho (61) (USDA-NRCS, 1996). This study characterized pesticide sorption of carbonatic so ils from South Florida and Puerto Rico, along with associated Histosols from South Florid a, and Oxisols from Uganda for comparative purposes. In Florida there are 12 series with carbonatic mineralogy, namely Biscayne, Chekika, Cudjoe, Keyvaka, Keywest, Krome, Lignumvit ae, Pennekamp, Pennsuco, Perrine, Saddlebunch, and Sumter. Five of these soils series namely Biscayne, Chekika, Krome, Pennsuco, and Perrine are found in Miami Dade County, and the other si x are found in Florida Ke ys (Hurt et al., 1995; Noble et al., 1996). The Florida Keys are underl ain by Coral limestone be drock in the northern and eastern side and with oolitic limestone on the southern and we stern part of the small islands (Hurt et al., 1995). Most areas in the Florida Keys are used as ha bitat for wildlife, residential, urban and for recreation. However the depth to th e bedrock, high seasonal water table and severe flooding limits use of many areas in the Florida Ke ys for building, and development of recreation and sanitary facilities (Hurt et al., 1995). Thirteen soil series we re classified with carbonatic mineralogy in Puerto Rico (Aguilita, Altamira Atoradello, Bahia Sali nas, Catano, Colinas, Costa, La Covana, Naranjo, Parguera San Sebastian, Tuque, and Yauco). The area in Florida where car bonatic soils are found is char acterized by long, warm rainy summers and mild dry winters (Noble et al., 1996). Although in many other states carbonatic soils are mainly used as rangelands, wildlife habi tat and livestock grazing, urban and recreational development, pasture land and to some extent croplands, these soils ar e important in Dade

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21 County for agricultural produce. They are used fo r growing vegetables, tomatoes, beans, corn, malanga, limes and ornamental nurseries (Noble et al., 1996). Over 85% of Florida's tropical fruits and vegetables are grown on carbonatic soils in the southern part of Florida (Li, 2001). Numerous researchers (Maheswari and Ramesh 2007; Cox et al., 1998; Nkedi-Kizza et al., 1983; Karickhoff et al., 1979; Chiou et al., 1979) ha ve established a positive correlation between soil organic carbon (SOC) content and hydrophobic or ganic chemical (HOCs) retention. It can therefore be concluded that SO C provides the best single predictor for adsorption isotherm parameters for HOCs. Since humic materials of di fferent origin constitute a heterogeneous group of macromolecules with different complexity an d sorption capacities towards organic pollutants (Thomsen et al., 2002), understand ing how OM was formed may be an important predictor for the fate of pollutants. The degree of adsorption of a pes ticide is an important parameter in determining the fate of a pesticide. Low sorption potential and relatively long half-life pesticides are associated with high leaching potential through the soil s ubsurface thereby contaminating groundwater (Wauchope et al., 2002; Triegel a nd Guo, 1994). Adsorption mainly takes place in the topsoil yet it is still in topsoil wh ere pesticide degradation and dissipa tion mainly takes place. Strongly adsorbed and/or highly degradab le pesticides are less likely to reach groundwater. Some studies (Nkedi-Kizza and Brown, 1998; St einberg et al., 1987; Ogram et al., 1985; Moyer et al, 1972) have reported that the adsorbed phase is am enable to microbial degradation. Adsorption may therefore influence the rate of pesticide degradation and dissipa tion and if this contaminated topsoil is eroded, then there is risk to surf ace water contamination. The major components in soils controlling adsorption are OM, clays and oxides and hydroxides of Al and Fe (Morrill et al.,

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22 1982). OM mainly controls the adsorption of hydr ophobic organic chemicals while clays play an important in controlling the adso rption of cationic orga nic chemicals like di quat, and paraquat. Recently, numerous field and laboratory contro lled studies (Maheswari and Ramesh, 2007; Oliver et al., 2005; Kulikova and Perminova, 200 2; Cox et al., 1998; Nkedi-Kizza et al., 1998; Ma et al., 1996, Nkedi-Kizza et al., 1983) have been conducted aimed at understanding and characterizing the sorption and degradation of organic pesticides applied on non-carbonatic soils but a search in literature indicates lack of these data in carbonatic soils. To predict movement of pesticides in a soil profile, model simulators ne ed physicochemical paramete rs of soils including sorption coefficients, an d degradation rates. The overall objective of this study was to ch aracterize the sorption and degradation of pesticides and to understand why carbonatic soils of South Florida and Puerto Rico do not adsorb organic pesticides as effectivel y as the non-carbonatic soils. Of concern are pesticides with high leaching potential and relatively hi gh persistence and particularly those that have been detected in surface and groundwater of Sout h Florida and Puerto Rico. This study aims at characterizing carbonatic soils in order to provide these im portant properties which will be useful in understanding the fate of HOCs in these soils.

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23 CHAPTER 2 LITERATURE REVIEW Carbonatic Soils Formation The geologic history of Florida is be lieved to start from the time of continental drift where North America was split from Western Africa (FDEP, 1994). The fragment of West Africa which remained attached to North America fo rmed basis for carbonate build-up, resulting in present day Florida and the Bahama s Platform. The limestone in South Florida consists of oolitic facies and the bryozoan facies, the latter being made up of mollusks, bryozoans and corals. The bryozoan facies cover most of the Eveglades a nd extend as far as Fort Lauderdale while the Miami oolite covers a large exte nt of the Atlantic coastal ri dge (Hoffmeister, 1974). The South Floridas subtropical environmenta l conditions are believed to ha ve created suitable conditions for warm waters, increased evaporation and subs equent enhanced super-saturation, resulting in oolite deposition. The oolites formed from origina lly loose unconsolidated sand grains cemented with calcium carbonate (Hoffmeister, 1974). It is believed that during the Pleistocene, the water level fluctuations provided suitable conditions for development of new calcite colonies which may explain the high prevalence of calcite deposition within South Florida. It is also believed that (s ix million years ago), a shallow sea covered Florida. The rock beneath the Big Cypress swamp (Tamiami formation) which is also the oldest rock in Sout h Florida (Hoffmeister, 1974) was a shallow marine bank where calcareous sediments and bryozoan reefs accumulated. Although the Tamiami formation is the oldest rock at about six million years of age, other South Florida rocks (Miami Limestone, Fort Thompson formation and Key Largo limestone) ar e among the youngest in the country, differ in composition, and were deposited under different environmental conditions (Hoffmeister, 1974). As the water levels dropped, the rock outcrops were exposed to form the present Florida. The

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24 Tamiami formation happens to be the most perm eable ever investigated by U.S. Goeological survey (Mowry and Bennett, 1948). The Miami oolite which formed later (100,000 years ago) overlies the Tamiami formation and is also hi ghly permeable (Noble et al., 1996, Hoffmeister, 1974). The formation covers most the Eastern Ev erglades National park and Florida Bay and forms the land surface for the Florida Keys, Big Pine Key and Key West (Mowry and Bennett, 1948). During the Pleistocene, the unique geogr aphical position of South Florida produced a terrain different from the rest of the Florida pe ninsula creating prevalence of carbonate sediments as opposed to the sandy ridges of central Florida. Most of the continental quartz was funneled offshore and lost down the continental slope. It is also believed that duri ng the glacial period, as sea level rose the southern most tip of presen t Florida was floated but calcium carbonate was the major source of sediment. The accumulation of dead coral reefs, depos ition under low energy wave conditions, and recession of the water level is believed to be th e basis for the present day calcite formation in Miami Dade and all the way to the Florida Keys. The carbonate bedrock forms the parent material for cabonatic soils in So uth Florida. Carbonatic soils are soils containing more than 40% of carbonates in their mineralogy. The major fo rms of carbonates in the calcareous soils are calcite (CaCO3) and dolomite [CaMg(CO3)2]. The sources of dolomite are mainly inheritance from parent material. The well drained rock/grave lly soils such as those adjacent to the Miami ridge in South Florida (Chekika and Krome) were formed from ro ck-plowing or scarification of the carbonate bedrock. The carbonate bedrock in th e most parts of Florida (Ocala limestone) is believed to have formed during the upper Eocene. In the low lying, poorly drained and often flooded soils in Sout h Florida, the prevalence of periphyton mats has induced secondary precipit ation of predominatly silt-sized calcium

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25 carbonate that comprises the parent material leading to formati on of marl soils. Marl soils formed in coastal and freshwater marshes and sl oughs. In the areas that are flooded for most of the year, organic matter (OM) accretion occurs le ading to formation of organic soils. In South Florida, the marl and organic soils formed on nearly level ground with slopes from 0 to 2 %. The natural vegetation of marl so ils consists of sawgrass, whitetop sedge, yellowtop, goldenrod, gulfdune paspalum, broom sedge, glades lobelia dogfennel, gulf muhly, bluejoint panicum, bushy beard bluestem, and South Florida bluestem Carbonatic soils are underlain by the highly porous Miami Oolitic limestone bedrock that form ed from small spherules of calcium carbonate (Noble et al., 1996). The water table in these soils is within 25 cm from the surface for at least 4 to 6 months of most years. The soils are floode d for several months during the summer followed by dry months in winter. The hydro-period in marl soils is shorter than in organic soils. During the dry months OM is oxidized leading to lower OM content in these soils. The major underlying difference between marl so ils like Biscayne and non-marl carbonatic (rock/ gravelly) soils like Krome is the way th ey were formed. Krome and Chekika are well drained soils that were formed from rock-plowi ng or scarification for purposes of agricultural production. In the marl soils, the microalgae (p eriphyton mat) that grow on the surface of the water-inundated-soils use carbon dioxide during their photosynthesis a nd these reactions are responsible for the formation of secondary carbonate. In poorly drained soils, algal uptake of CO2 at the wet soil surface reduces the carbon dioxide partial pressure (pCO2). The upward water flux due to evapotranspiration limits gas diffusion in the subsoil (pCO2 in poorly drained soils increases with depth). The loss of CO2 to the atmospherea dn to algal photosynthesis lowers pCO2, and the slow re-dissolution of CO2 into water and/or loss of water due to evapotranspiration near the soil surface, drives the reaction in Equation 2-1 to the right.

PAGE 26

26 The principal reaction leading to formation of secondary CaCO3 and marl soil formation is shown in Equation 2-1: Ca2+ + 2HCO3 CaCO3 + H2O + CO2 [2-1] When plant roots decay, they release organi c acids that dissolve the rocks, therefore increasing the concentration of Ca2+ in the soil solution. The carbon dioxide involved in calcite formation is either atmospheric or from calcite dissolution. Thes e factors favor precipitation of secondary CaCO3 at or above the soil surface, from water saturated with CaCO3 when soil undergoes desiccation. As Ca2+ and HCO3 move with the upward water flux, precipitation takes place near the soil surface where pCO2 is lower and the soil solution is concentrated due to evaporation. The above mechanism of formation of secondary CaCO3 is strong evidence that the water table in South Florida is at or above the soil su rface because secondary calcite (putatively marls) is prevalent in South Florida. The carbonate form ed due to secondary formation is fine giving the soils a loamy texture. Krome soil (Loamy-skeleta l, carbonatic, hypothermic Lithic Udorthents) is a typical rock-plowed soil while Biscayne (L oamy, carbonatic, hyperthermic, shallow Typic Fluvaquents) is a typical marl. Th e rocky soils formed at higher elevation adjacent to the Miami ridge while the marl soils formed in low lying so utheastern coastal areas and the Everglades in South Florida. The Histosols in South Florida were formed in areas that inundated with water. In 1948, Histosols covered 40 % of the so il survey area (Mowry and Bennett, 1948). These soils play an important role in carbon sequestration as they accumulate OM resulting from wetness throughout the year. The Histosol that were sampled are associated with the carbona tic soils but may have different vegetation (such as saw grass) compared to algae in marl carbonatic soils. Oxisols from

PAGE 27

27 Uganda constitute the most highly weathered soils. These are tropical soils that were formed in hot and moist climate. Since these soils come from a completely different geographical region (Eastern Africa), whose vegetation differs from that of the sub-tr opical regions of Florida and Puerto Rico, it is expected that the OM present in these soils differs. The expected differences in OM and sorption properties formed the ba sis for their inclusion in this study. Soil Organic Matter (SOM) Plant litter and m icro-biomass are the majo r contributors to OM in the soil. These decompose forming complex macromolecules with a range of polarities and complexities, posing challenge to conventional analytic al techniques. Plant residues c onstitute the majority of SOM substrate while the rest is contributed by decay ed biomass. The decomposition of plant residue by microorganisms results in breakdown of the re sidues into carbon which is either evolved as carbon dioxide or incorporated in the biomass when microorganism use SOM as a source of energy. As such, low OM decomposition mostly due to soil anaerobic conditions lead to SOM accretion. Although SOM usually c onstitutes a small percentage of soil mass, it greatly influences soil chemical and physical properties. The pH dependent charge on SOM contributes up to 80 % of soil cation exchange capacity (CEC) with CEC contribution of 150-300 cmol kg-1, a range considerably higher than for clay minerals. In terms of CEC contribution by clays, the expanding type with the 2:1 conformation (montmorillonite and vermiculite), have higher CEC compared to the non-expanding type such as Ill ite and Chlorite (Smith and Walker, 1977). The influence of SOM on soil structure and aggreg ation, soil bulk density, so il color, water holding capacity and organic pollutant sequestration is well known. OM plays an important role in controlling the chemical, biologi cal and physical properties of soils and sediments. It is responsible for nutrient retention/ release, soil color, cation ex change capacity (CEC), improved soil aggregation, water holding capacity, poros ity and serves as an energy source for

PAGE 28

28 microorganisms (Stevenson, 1994). Soil aggrega tion improves infiltration rates, and gas exchange between the atmosphere and the soil root zone. The carbon content of humus in soils is generally given as 58 % (1:1.724) of SOM (Westman et al., 2006; Hanna, 1964; van Bemmelen, 1891). Understanding SOM chemical functionalities and its dynamics in soils is important in soil nutrient management, soil remediation, sustai nable agricultural produc tion and global carbon cycling. The improvement in designing predictive capabilities and strategic models aimed at reducing environmental bioavailability, and le aching of toxic xenobiot ics to surface and groundwater Investigating the ad sorptive capacity of organic compounds by SOM is useful in understanding the adsorption mechanism and thereby. Variations in SOM reaction capacities have been noted and these have been attributed to variation of SOM composition and cation saturation capacities (Smith, 1974). In order to characterize the structure and functionality of SOM, CPMAS 13C NMR, liquid state NMR, and IR have been used. Some studies (Cox et al., 1998; Nkedi-Kizza et al., 1983; Maheswari and Ramesh, 2007) have indicated the role of organi c carbon as a major contri butor in the adsorption process of hydrophobic organic co mpounds (HOCs) and as such may determine the effectiveness and activity due to its influence on the partition between the soil solution and the soil solid phase. To maintain pesticide applicati on effectiveness, it is a common practice to increase the amount of a pesticide applied with incr ease in SOM content. Piccolo et al. (2001) related increase of hydrophobicity of OM as a good indicator of interaction potential for non-polar compounds. Using CPMAS 13C NMR data, he defined the hydr ophobicity index (HI/HB) as the ratio of the quantity of the hydrophilic C to hydrophobic C (Equation 2-2): [(45-60) + (60-110) + (160-190)/ (045) + (110-160)] [2-2]

PAGE 29

29 SOM is made up of a mixture of plants, micr obial biomass and insect residues, dissolved organic matter (DOC) and humic substances (Che fetz et al., 2000). Ther e are two bio-chemical classifications of plants, from which OM is derived, namely non-vascular (with no woody and cellulosic tissue like algae) and those that are vasc ular (with tissue like sh rubs, grasses and trees). The Calvin-Benson photosynthetic pathway us ed by C3 plants to incorporate carbon, preferentially incorporates 12C producing a shift of 20 while th e C4 pathway produces a shift of -8 to -12 (Meyers and Ishiwatari, 1993) Complex structural polysaccharides and phenolic polymers (lingo-Cellu lose) comprise the most abunda nt biopolymer in OM (KgelKnabner, 2002; Kirk, 1984). Cellulose makes up the major component of the cell wall for both woody plants (45-90%) and herbaceous plants (1 5-30%). The hydroxyl groups in its structure are responsible for its hydrogen bonding and its fibrous nature hence its supramolecular structure (Kgel-Knabner, 2002). SOM is divided in to two classes: Hu mic and non-Humic substances. The humic substances consist of components of plants, animals and micro-organisms that have been transformed by microbial or chemical processe s. Non-humic substances on the other hand consist of unaltered materials of plants, an imals and microorganisms mainly consisting of cellulose, starch, proteins, chitins and fats (Morri ll et al., 1982). In terms of adsorption capacity, non-humic substances contribute negligible eff ect compared to the humic substances which provide large surface area and charge density per unit area (Dunigan, 1971). The humification process results in the formation of humic substan ces described as supramolecular associations of low-molecular-mass organic molecules (Kuli kova and Perminova, 2002), operationally divided on the basis of their solu bility (Moreda-Pieiro et al., 2004; Mo rrill et al., 1982) into fulvic acids, humic acids, and humin. Humic acids dissolve in bases but not acids while fulvic acids dissolve

PAGE 30

30 in both acids and bases and humins are insolubl e in both acids and base s. Humic acids possess a high degree of polymerization comp ared to fulvic acids while fulvic acids are known to contain higher proportions of acidic functional groups. Th e source of DOC in oceans is thought to be due to primary production and the disappearance path ways are thought to be photodecomposition and microbial reworking (Koch et al., 2005). In te rms of composition, marine DOM contains less aromatic and phenolic hydroxyl groups compar ed to freshwater DOM (Koch et al., 2005). Separation and identification of complex organic structures and functiona l groups still remains a mystery, despite recent improvement in analytical capabilities. Earlier methods of OM quantification invol ved use of hazardous oxidizing agents (Walkley and Black, 1934). Recent methods have utilized more environmentally safe procedures like thermograviemtry, and near or mid-infrar ed (IR) reflectance spectroscopy. Spectroscopic measurements are coupled with multivariate calib rations to enable data interpretation. Recent advances in OM analysis i nvolve use of spectroscopic tec hniques, high resolution nuclear magnetic resonance spectral analysis, high reso lution mass spectrometer and ionizing techniques like nano-electrospray that enab le analysis of molecule > 50 0 daltons (Kgel-Knabner, 2002). Review of the Methods Therm ogravimetric methods, stable carbon isotope determination, and spectroscopic methods such as UV-vis and fluorescence have b een used in quantifica tion and characterizing SOM. However, for detailed structural character ization, methods like Fourier transform infrared (FT-IR), Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), 13C-NMR and 1H-NMR spectroscopy have been applied to inve stigate molecular changes in SOM and to elucidate composition of SOM complexes. Recen t developments in analytical equipment technology have improved capabilities for analysis of macromolecules which were not possible in the past. These include pyrolysis GC-MS and nano-electrospray ionization mass spectrometry.

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31 These improvements have made steps aimed at overcoming the low mass cut-off of mass spectrometers. Soil Organic Carbon Determination Soil organic carbon is commonly determ ined by use of oxidation processes that were originally developed by Schollenberger (1927) and Degtjareff (1930), modified by Schollenberger (1931) and later by Walkley and Black (1934). Though the Walkley and Blacks procedure was suggested for quick and approxima te determination of organic carbon (Walkley, 1947), this oxidation method is to-d ate still the most universal a nd most widely used method for rapid determination of soil organic carbon. Howeve r, there is no such a universal method for determination of SOM/ OC for a ll soils due to the presence of co mpounds in numerous soils that may interfere with OM determination. The major demerits of the Walkley and Black method are its generation of large amounts of toxic dichromate waste and po ssible interferences from soils constituents such as chlorides and oxides of iron and Manganese (Walkley, 1947). In addition, an incomplete conversion of organic carbon to car bon dioxide (76% average) is achieved by the method thus warranting the use of a (1.32) correct ion factor (Schollenber ger, 1945; Walkley and Black, 1934). Alternative methods have since been developed that include thermal methods and elemental analysis that involves determination of total carbon. The use of thermal methods for determination of OM dates as far back as the late 1940s (Mitchell and Birnie, 1970). Some studies (Critter and Airoldi, 2006; Mitchell and Birnie, 1970; Sc hnitzer and Hoffman, 1965) have used thermal methods to characterize the physical and chemical nature of OM. The applicability of thermal methods to OM analysis relies on th e premise that the soils do not contain compounds like gibbsite, smectite and kaolinite clays that decompose within the same temperature range (200-550OC) as OM (Karathanasis and Harris, 1994; Mackenzie, 1970). The presence of these components curtails use of thermal methods for anal ysis of Oxisols and other soils that contains

PAGE 32

32 large amounts of clays. Following decarbonati on of inorganic carbon w ith hydrochloric acid, total organic carbon (TOC) can be determined by el emental analysis. However the treatment step may affect purgeable OM (Motter and Jones, 20 06). Total carbon on the ot her hand may be used but this requires knowledge of carbonate amounts in carbonatic soils in order to determine organic carbon by difference. The presence of OM in soils can influence factors like soil fertility, water and nutrient retention capacity, bulk density, soil aggregation and xenobiotic retention. An accurate determination of SOC is necessary in order to predict the sorption coefficient (Koc) of hydrophobic organic chemicals (HOCs) whose retent ion in soils is predominantly associated with soil organic carbon (Nkedi-K izza et al., 2006; Wauchope et al., 2002; Nkedi-Kizza et al., 1983). Since the sorption of HOCs in soils is nor malized with the fraction of organic carbon ( foc) present in soils (Koc = Kd/ foc), if SOC is inaccurately determined, the sorption coefficient Koc determined may be in error. SOC and SOM are often determined indirectly depending on the method used. A conversion factor is then used to convert from one parameter to another. A factor that is commonly used in literature is 1.724 (W estman et al., 2006; Hana, 1964; van Bemmelen, 1891; Ranney, 1969). A single factor for all soils seems inappropriate. Already, some studies (Ranney, 1969; Broadnet, 1953) have indicated conversion factors up to 2.5. Probably this explains to a large extent the variability of Koc values found in the litera ture for a given neutral organic chemical. This study examined the use of thermograv imetry (TG) and weight-loss-on-ignition (WLOI) thermal methods for determination of SOM in carbonatic and associated soils, Oxisols, and Spodosols. Thermogravimetry utilizes untr eated whole soil samples and provides a highly sensitive and accurate determination of OM in carbonatic soils and the amount of carbonates in

PAGE 33

33 the soils in one run. Unlike WLOI which is car ried out blindly in the muffle furnace, TG provides an online weight loss and insight on the onset temper ature points during decomposition thus giving a more accurate determination of so il components. Addition of first order derivative can provide valuable information regardi ng the reactions taking place during thermal decomposition. Elemental Analysis (Total Organic Ca rbon, Total Carbon, Total Nitrogen) The m ethods to determine total organic carbon content and total organic nitrogen involve use of elemental analyzers. Analysis of the C/ N ratio by depth can be useful in understanding the paleo-environmental changes (Punning and Tugu, 2000) since the OM decomposition results in biomarkers that are characteristic of the micr obial populations driving th e degradation process, sources of OM and its diagenesis. UV-vis and Fluorescence Spectroscopy Hum ic and Fulvic acids form complexes with trace metals making them able to attenuate light. The fluorescence properties of OM have been attributed to the quinone-like fluorophores which result from phenol oxidation (Cory and Mc Knight, 2005; Leenheer, 2003). Fluorescence in dissolved organic matter (DOM) has been s uggested to be a measur e of redox potential of DOM (Cory and McKnight, 2005). The recent adva nces in spectroscopic and mass spectrometer techniques (Kgel-Knabner, 2002, ), coupled with novel ionization procedures like nanoelectrospray ionization and matrix-assisted laser desorption ionization (MALDI) have improved capabilities of analyzing macromolecules thus providing a better understa nding of the molecular structure and functional groups in OM and its decomposition pathways. FT-IR Fourier Transfor m infrared (FT-IR) spectroscopy has been described in measurement of OM in soil. Coupled with multivar iate calibration and use of principle component analysis, FT-

PAGE 34

34 IR provides a rapid, nondestruc tive and environmentally safe method for OM quantification. Fourier transformation ion cyclotron resonance mass spectrometr y (FT-ICR MS) is a technique with high resolving power and mass accuracy (Marshall 2000; Marshall et al., 1998). Stenson et al., (2002a) and Marshall et al. (1998) provide detailed descripti on of ultra-high-resolution FTICR MS. The methods are used to determine singly charged ions at mass resolving power between 60,000 and 120,000 and therefore eliminating low molecular weight bias resulting from multiple charged ions. Electrospray ionization ha s been described as the method of choice for analysis of humic substances (Stenson et al., 2002b). By use of electrospray and MALDI ionizations techniques, coupled with FT-ICR MS, for the first time identification of up to 5000 molecular formulas for large and individual fulv ic acids have been reported (Stenson et al., 2003). This research indicates a breakthrough in OM analysis as this may shed more light in understanding the chemistry of humic substances. Stable Isotopes Characterization ( 13Carbon, Carbon-Nitrogen Ratio) Lake studies utilize C/N rati os to try and reconstruct ch anges in primary production and trophic state of the lake (Punning and Tugu, 2000) in order to assess terrestrial impacts on the lake system. Sources of OM pools may cause difference in carbon fractionation, carbon stable isotope ratios 13C, and organic C/N ratios. Isotope ratios are reported in per mil against Peedee Belemnite (PDB) standard (Doi et al., 2003) The isotopic composition from the long-chain nalkanes reflects the differences in carbon dioxide fixation mechan ism between C4 and C3 plants as well as the temporal varia tions in environmental changes that affect primary producers (Fuhrmann et al., 2003). OM with low C/N ratios (4-10) indica tes microalgal sources while higher C/N ratios (>20) indicates te rrestrial origin of OM (Doi et al., 2003). Paleo-environmental and paleo-climatic studies have utilized stable carbon isotopes as biomarkers to specify the primary producers and reconstruction of the ve getation history. The determination of stable

PAGE 35

35 isotopes involves coupling Gas Chromatography or an elemental analyzer with an isotope ratio mass spectrometer (Kelly et al., 2005). Organic n itrogen contributes significantly to the total nitrogen pool. Understanding the contribution of organic nitrogen to the biogeochemical cycles requires appropriate methods to characterize and identify its sources. Until recently, isotope studies have concentrated on characterizing organic carbon but more recent studies have included nitrogen isotopic measurement in charac terizing the sources and cycling of inorganic and organic nitrogen (K elly et al., 2005). However, the determination of contributors to stable isotope signatures becomes fuzzy when mixed C3 and C4 plant species are contributing towards the carbon fractionation. Additionally the change in energy levels due to nuclei spins and res onance frequencies are characteristic of the strength of the magnetic fiel d. This makes it hard to compare spectral results obtained from another NMR unless a standard is used to correct for the chemical shifts (KgelKnabner, 2002). Cross Polarization Magnetic Angle Spinni ng Nuclear Mag netic Resonance (CP-MAS 13CNMR) NMR spectroscopy is a technique based on magn etic properties of the observed nucleus, (which is influenced by electron density) and it s interaction with its physical environment. Organic compounds contain protons in specif ic environments, making them sensitive to 1H NMR. 13C NMR on the other hand is valuable in s howing changes in the backbone of organic molecules. The accuracy of NMR spectroscopy and sensitivity enables it to detect small chemical differences in local environments (1 -300 Hz), which accounts for its wide use in biochemistry, medicine and com pound elucidation (Jayasundera et al., 2000). Nuclear magnetic resonance (NMR) is the most commonly used method for SOM characterization. Several researchers have reported su ccessful use of Solid state 13C NMR (Mathers and Xu, 2003; Laws et

PAGE 36

36 al., 2002) in characterizing OM. Li quid state NMR is more commonly used than solid state NMR but recently solid NMR is emerging as a powerful t ool in the studies of so lid materials (Laws et al., 2002). Unlike liquid state NMR which involves or ganic extraction using a base, alteration in the nature of OM in the sample is unlikely in solid state NMR since it requires little (removal of paramagnetic impurities) or no sample pre-treatment. NMR can be used to elucidate structure at atomic and molecular level by subjecting the samp le to a magnetic field that forces the nuclei spins to distribute themselves in different energy levels. The chemical shifts (Figure 2-1) can be used to identify the functional groups presen t. Recent advances to improve NMR analysis include cross polarization, ma gic-angle-spinning, decouplin g and recoupling techniques, dynamic angle spinning, two dimensional homonucle ar total correlation sp ectroscopy (TOCSY), heteronuclear multiple quantum coherence (HMQ C), and dipolar diphasing (Laws et al., 2002; Kingery et al., 2000). These advances have im proved functional group assignment, chemical shift anisotropy measurement, and dipolar coup ling and have provided a better understanding of OM chemistry. The nature of binding that exists between a pol lutant and OM determines its environmental dynamics and availability. Using NMR, specific ch anges in parameters su ch as line broadening, chemical shifts in specific nuclei, relaxation times, and coupling constants can be useful in elucidation of the types of interactions (covale nt, or non-covalent) that take place between the pollutants and the natural envi ronmental samples (Jayasundera et al., 2000). The binding of pollutants to mineral and humic su rfaces induces NMR chemical shif ts and spin lattice and these changes are used in determining the binding sites and strengths. CP-MAS NMR technique is said to be less but sufficiently sensitive to heterocyclic N than to N amides, as sensitivity is thought to depend on transfer of magnetic energy from 1H to 15N

PAGE 37

37 nuclei yet heterocyclic are not usually directly protonated (Kulikova and Perminova, 2002). Other than obtaining a gross chemical composition of plant residue, NMR does not provide specific compound identification (Kgel-Knabner, 2002). Tetramethylammonium Hydroxide (TMAH) Thermochemolysis Coupled w ith Gas Chromatography/ Pyrolysis GC-MS Recent advances using thermochemolysis a nd tetramethyl ammoni un hydroxide (TMAH) have been instrumental in shedding more light in studies that involve macromolecules (Chefetz et al., 2000; Chefetz et al., 2002). TMAH frag ments OM into lignin derived compounds, nonlignin-derived aromatic compounds, fatty acid methyl esters (FAMEs), heterocyclic N, and dicarboxylic acid dimethyl esters (DAMEs). TM AH works by hydrolysis and methylation of esters and ether linkages (Filley et al., 1999). The fragmented compounds are then subjected to gas chromatography (GC) or gas chromatography coupled with mass spectrometry (GCMS). Pyrolysis of humic substances produces frag ments of pyrazoles, pyridines, substituted pyrimidines, pyrazines, indoles, quinolines, N-deri vatives of benzene, alkyl amines, alkyl and aromatic nitriles (Stuczynski et al., 1997; Schulten et al., 2002). Fuhrmann et al., 2003 described a detailed method in which they used Fis on GC 8000 coupled with Fison quadrupole MD 800 mass spectrometer. Full mass spectrum was reco rded within the 10-420 amu with 2.5 scans/s (Fuhrmann et al., 2003). Fiber Optics and Spectroscopic Analysis A new e merging method for OM analysis involve s use of near infrared spectroscopy. The equipment is composed of a sensor system with four optical fiber probes, a spectrometer and a control unit. Two of the fiber probes provide the illumination of the sample while the other two are for collecting soil reflectance from the visibl e to the near infrared (NIR) wavebands. Realtime soil reflectance has been described in the field at a depth of 30 cm (Li, 2005). The amount

PAGE 38

38 of OM and differences in OM types ((Ben-Dor et al., 1997; Palmborg and Nordgren, 1993) can be determined using NIR spectroscopy. Compared to other methods, the integrative function of the NIR calibrations may explain the low analytical errors in NIR spectroscopy. In addition, it is a rapid, low price analytical t echnique and no hazardous chemicals are used (Brjesson et al., 1999). Key Findings For the first tim e, Stenson et al. (2003) reported identification of up to 5000 molecular formulas for large and individua l fulvic acids. Using FT-ICR MS, Koch et al., 2005 were also able to identify 1580 different molecular formulas. 13C labeling in conjunction with 13C NMR, have also been used to provide evidence for 13C-2, 4-dichlorophenol (D CP) binding properties with macromolecular structures of humic substances (Hatcher et al., 1993). An understanding of the binding properties can be a powerful tool in designing envir onmental remediation strategies. Research findings that indicate the fluorescence properties of OM that result from quinone-like fluorophores have been useful in advancing met hods that use fluorescence in characterizing OM. Quinones are also thought to be responsible for the electr on shuttling ability of OM. What is yet to be known about the Characteris tics of Organic Matter Current research finding are able to provide class-level as opposed to specific compound level therefore a deeper understand ing of the complex nature of OM will require techniques that will go to the specific compound level. FT-ICR MS coupled with nano-electrospray seems promising in this regard (Stenson, et al., 2003; Koch et al., 2005). Synthesis of specific compounds will also pose research cha llenge given the complexity of OM. Advances in analytical capabilities in fi elds such as spectrometry, mass spectrometry, nano-ionization, and stable isotopes have shed li ght and increased our understanding of the OM functionality. These techniques have been widely used in biologi cal studies especially in the

PAGE 39

39 medical field and less in classical chemistry. U nderstanding the binding properties of drugs to proteins has helped greatly in drug discover y. The molecular information may help answer questions like nature of OM, chemical struct ure, and surface site r eactivity. The reports by Stenson et al. (2003) indicate successful steps in OM characterization. Coupling Electrospray ionization with ultra-high-reso lution FT-ICR mass spectrometry results in 10-100 times higher mass resolution and mass accuracy compared to ot her mass analysis technique though the very high costs and maintenance for the analytical equipment (Marshall, 2000), may be a hindrance in commercializing the equipment. Chemicals Studied and Rationale Atrazine Atrazine (2-chloro-4-ethylam ino-6-isopropylamino-1, 3, 5-triazine ) belongs to s-Triazines, a class of herbicides which have been the most widely used for control of broadleaf weeds. Triazines use is slowly being phased out and replaced with pesticides that are more effective at low application rates. Atrazine (Table 2-1) is one of the most widely used herbicide in United States (USEPA, 2006) and the most commonly detect ed pesticides in prec ipitation (Majewski et al., 2000; Goolsby et al., 1997) and in agricu ltural and urban streams across U.S.A (Gilliom, 2007) and is also one of the most widely studied herbicides. Its interactio ns with soil minerals surfaces is probably the most understood. Atrazine is used as a preand post-emergent herbicide for control of broad leaf weeds, applied at 7 kg/ha on sod for muck and 3.5 kg/ha on sandy soils. It is one of the most commonly used s-triazine in U.S.A. Protonation of atrazine may be possible at pH 4 but such conditions are no t environmentally relevant. The pH of most soil solutions (48) ranges well above the pKa of atrazine (1.7) meaning that atrazine mainly sorbs as neutral species. The likely mechanism of interaction between atrazine and soil surfaces is believed to be via weak Van der Waals forces and H-bonding though it is assumed that entropy changes

PAGE 40

40 contributes most of the in teraction energy (Laird a nd Sawhney, 2002). The hydrophobic interactions are likely between the alkyl gr oups and the uncharged siloxane surfaces of philosilicates. In South Florida, atrazine was detected in 59 % of the samples analyzed while its metabolite deethyl-atrazine was detected in about 5% of the samples analyzed. It is generally agreed that soil OM cont rols sorption of hydrophobic organic chemicals especially for soils with more th an 1 % organic carbon but this may not be true for soils with low organic carbon content and high clay content (Laird and Saw hney, 2002; Karickoff 1981). Polar chemicals are believed to be strongly adsorb ed to soil mineral surf aces via cation exchange. Some studies (Talbert and Fletch all, 1965) have reported no adsorp tion of atrazine and simazine on kaolinite. The adsorption coefficients (Koc) reported in literature averaged 100 and 80 % of the selected studies had Koc values that exceeded 100 (Hornsby et al., 1996). Diuron Diuron (3-[3, 4-dichlorophenyl]-1,1-dim ethyl urea) is herbicide belonging to the phenylurea class (Table 2-1). The substitute d urea acts by inhibiting photosynthesis by preventing oxygen production. The rate of hydrolysis at neutral pH is negligible but increases at high acidic and alkaline pH and degrades to 3, 4-dichloroanaline (Giacomazzi and Cochet, 2004). The literature Koc for diuron is 480 and a half-life of 90 days (Giacomazzi and Cochet, 2004; Hornsby et al., 1996; Wauchope et al., 1992) It remains a priority pollutant since its degradation has not been properly characterized (Giacomazzi and Cochet, 2004) yet its detection in water resources across the United States is widespread (Gilliom, 2007). Ametryn Am etryn (2-ethylamino-4-isoprpylamino-6-me thylthio-s-triazine) is a preand postemergence herbicide belonging to the s-Triazine class (Table 2-1). Am etryn is stable under neutral condition but it hydrol yses under acidic and alkaline pH. Ametryn has a log Kow of 2.63

PAGE 41

41 and water solubility of 200 mg/L at 20 oC. In the field, ametryn is applied at a rate of 1kg/Ha. The literature Koc for ametryn is 300 and degradation half -life of 60 days (Hornsby et al., 1996). The selected values in Hornsby et al., 1996 for Koc ranged 170-389. Sorption and Solute Transport in a Porous Medium The sorption param eter can be useful in pred icting the relative pot ential for pesticides mobility and persistence. The high soil spatial vari ability of soil properties however, may prevent large scale accurate predictions. The heterogeneou s nature of OM in so ils does not support the equilibrium partition model to be sufficient in explaining sorption of HOCs as other nonequilibrium processes during transport may be involved in controlling so rption (Pignatello and Xing, 1996). The estimation of the organi c carbon sorption coefficients (Koc) requires accurate determination of soil organi c carbon (SOC) content since the distribution constant (Kd) is normalized against OC to calculate the Koc values. The movement of HOCs in a soil profile essentially depends on the interactive forces that control the solute distribution between the soil solution and soil surfaces, and its degradation rates. A solute with low soil retention and longer soil persistence will likely pollute ground water while a strongly reta ined solute will remain in the top soil profile there by prone to lateral movement via soil erosion. The movement of solutes is assumed to be controlled by convection, diffusion and dispersion processes. Once the solute is introduced in a soil matrix it und ergoes diffusion and dispersion pr ocesses thus interacting with the soil solid and the mobile phase of the so il matrix (Malone et al., 2004; Triegel and Guo, 1994; Nielsen et al., 1986). The movement of solutes from high to low c oncentration gradient is known as diffusion. Alongside diffusion is a passive process known as mechanical dispersion. Though diffusion is considered an active process, both diffusion and mechanical dispersion are considered additive during solute transport within a soil profile. As a result of soil pore size and structural

PAGE 42

42 differences, mechanical dispersion, a velocity gradient is registered between solute velocities for solutes at the soil surface and thos e in the center of the soil pores w ith respect to the average pore water velocity. As the solute moves through the so il profile, sorption and exclusion of the solute take place where sorption determines the solute rete ntion in the solid phase (soil) while exclusion refers to the phase in the soil solution. This dist ribution of the solute between the two phases and the tortuous nature of the flow path within a soil matrix creates a veloc ity gradient between the water and the solute hence resulting in solute re tardation due to soil interactions. Some studies (Swanson et al., 1954) have found a correlation between HOC adsorption with soil clay content. Upchurch and Mason (1962) reporte d a positive correlation between soil OM and the quantity of herbicide required to produce 50 % growth reduction, an indi cation that OM adsorbs and sequesters a portion of herbicide applied. Interaction with Organic Carbon Although som e studies (Oliver et al., 2005; Spark and Swift, 2002) did not find a relationship between organic car bon content and sorption of HOCs, several studies (Maheswari and Ramesh, 2007; Cox et al., 1998; Nkedi-Kizza et al., 1983) have established a linear relation between organic carbon content and sorption of HOCs. The interaction mechanism has been described mainly to be due to partitioning. For soils with low organic carbon content, clay minerals may contribute greatly to the sorption of polar and non-polar pesticides. The Koc theory may therefore break down. The nature and properties of mineral surface may be affect ed by pH. The pH at which the net positive charge and negative are equal is called the zero point of net char ge (ZPC). Organic acids tend to have stronger interactions at pKa < ZP C and at pKa > ZPC for organic bases.

PAGE 43

43 Sorption Models Equilib rium isotherms are often described by mass action, Linear, Freundlich, or Langmuir sorption models (Nielsen et al., 1986). The lin ear model was relevant to our study since we worked within the linear range of the isotherms. Sorption models are classified as those that were derived for the adsorption of gases by solids, the empirical models and those that are kinetic or rate models. Adsorption of HOCs can assume three phases, which may be represented by the Equation 2-3: S = Se + Sk +Sir [2-3] where Se is the rapidly established equilibrium between solutes concentration and the solid sorbed phase, Sk is the time dependent ki netic type sorption and Sir, the irreversible adsorption. The Linear Sorption Model The linea r model is derived from the linear equation Se = mCe + b [2-4] where Se = equilibrium sorbed phase (mg of solute/kg of soil), Ce = equilibrium solute concentration (mg/L) and m and b are empirical constants. It is assumed in Equation 2-4 that at at initial concentration (Co) = zer o there is no adsorption so the b in the equation is assumed to be zero, thus transforming the equation to comm on sorption linear equation (Equation 2-5). This approach assumes instant adsorption and a linear relationship between the adsorbed phase and the soil solution phase thus fo rcing the intercept through zero. Linearity of the isotherms is primarily dependent on the pesticide concen tration, mostly linear when the solution concentration is less than half of the compounds water solubility (Karickoff, 1981).

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44 Non-linearity tends to increase as solution concentration increas es and as such Equations 2-4 hold if the experiment is performed within the linear range of the isotherm. Se = KdCe [2-5] where Kd (L/kg) is the empirical di stribution (partition) coeffici ent. Normalization of the distribution coefficient for HOCs against the fraction of soil orga nic carbon content (ocf ) yields a new sorption coefficient known as Koc (Equation 2-6), which enable comparison of sorption across a wide range of soils with varied OM content. Koc = oc df K [2-6] Freundlich Isotherm Model This m odel is empirically derived and has a mathematical equation written as: Se = KfN eC [2-7] where Se is the equilibrium adsorbed concentration; Kf [(mg/kg)*(L/mg)N] is the Freundlich constant related to the amount adsorbed, Ce is the solution equilibrium concentration and N (usually ranging between 0.7 N<1 is a constant related to the t ype and degree of curvature of the isotherm. As the N value approaches 1, Kf approximates to Kd. Lagmuir Sorption Model The Langm iur isotherm model (Equation 2-5) has sound conceptual basis and was derived to describe adsorption of gases on to so lid surfaces. This model assumes that: 1. The adsorption energy is constant and independent of the surface coverage. 2. Adsorption occurs on localized sites and there is no in teraction between adsorbed molecules. 3. The maximum adsorption possible is that of a complete monolayer.

PAGE 45

45 The mathematicl equation is written as: Se = Qmax )1(e eaC aC [2-5] where Se is the concentration of the adsorbed phase, Ce is the equilibrium concentration, Qmax is the maximum amount of available sorption sites and a is a constant related to the bonding energy. Pesticide Degradation The prim ary factor that determines pes ticide dissipation is microbial degradation (Edwards, 1973). The degradation of pesticides is often carried out at ambient temperature. Pesticide concentration has been described to be the limiting fact or and not the microflora which is excess in the soils (Zimdal et al., 1977). Accelerated pesticide degradation has been described resulting from repeated application and subs equent soil enrichment of specific pesticide degrading microbial species. Pe sticide degradation is said to be affected by chemical and environmental factors which include chemical structure and position and type of functional groups, SOM content, soil pH, added concentration and previous applications, application methods and rates, temperature, presence of other chemicals, soil moisture content, and the types and population of the degrading microbes (Mor rill et al., 1982; Nkedi-Kizza and Brown, 1998, Hamaker, 1972). In some cases, SOM has been found to inhibit degradation by protecting pesticides from microbial attack via adsorpti on for compounds like atrazi ne, and chrolopyrifos (Hornsby et al., 1996; Rao et al., 1993). A positiv e relation has also been reported between increase of OM and degradation rates for DDT diazinon, diuron, and parathion (Morrill et al., 1982). This increase is due to use of SOM acti ng as a co-metabolite a nd its ability to supply nutrients for microbes and as a s ource of energy (Morrill, 1982).

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46 In the early days pesticide resistance was a de sirable attribute to enable extended pesticide effectiveness. The first pesticides contained Ar senic which was persistent. Due to environmental and health concerns these chemicals have been phased out and replaced with less persistent alternative such as organophosphates and carbamate s which have short half-lives of about 1-120 and 1-60 days respectively (Hornsby et al., 199 6; Weber, 1994). Some pesticides have been known to decompose to more persistent and more toxic metabolites than the parent compounds and to cause health and repr oductive effects to non-targ et species (Edwards, 1973). Environmental Fate of Pesticides Understanding the fate of a chem ical in th e soil environment requi res knowledge of its sorption capacity and degradation rates. Several researchers ha ve reported low potential of leaching for pesticides that are strongly ad sorbed such as DDT (Edwards et al., 1971; Lichtenstein, 1958) but more in runoff water (Z hou et al., 2003; Scott et al., 2002; Dur et al., 1998; Edwards et al, 1971). In a study conducted by Dur et al. (1998), er oded particles did not contribute to pesticide transfer but they attributed the runoff to adsorption-desorption (dilution) phenomena to contribute to the runoff. The study reported that strongly adsorbed chemical required small fraction pesticide desorption to reach equilibrium duri ng transport and that reaching equilibrium was fast. Generally, it can be stated that pesticides with low sorption coefficients have a high leaching potential pr ovided they persist long enough during the downward movement. Hypotheses Hypothesis 1 : Soil or ganic matter is the major contributor to pesticide adsorption in carbonatic soils. Hypothesis 2 : Soil organic matter in carbonatic soils is different from that in noncarbonatic soils. Hypothesis 3 : Carbonatic soils adsorb pesticides less compared to non-carbonatic soils.

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47 Hypothesis 4 : Degradation of pesticides will be fast er in carbonatic soils compared to noncarbonatic soils due to less so rption in carbonatic soils. Hypothesis 5 : Organic pesticides applied to carbonatic soils are likely to pose greater risk to groundwater pollution than those applied on non-carbonat ic soils due to decreased sorption capacity in carbonatic soils. Study Objectives This study was aim ed at understanding soil factors that determine interactions of organic pesticides in carbonatic soils. In order to assess and predict the movement of pesticides in the subsurface environment, this study aimed to unde rstanding of the factors and processes that influence interactions of pesticides with soil surfaces. The data obtained can be usable as input model parameters (Malone et al., 2004; Ma et al., 1996) for simulating fa te and transport of pesticides. Objective 1 : Characterize the chemical physical and mineralogical properties of selected carbonatic soils and associated non-carbonatic so il series from South Florida, and Puerto Rico and Oxisols from Uganda. Objective 2: Characterize sorption and degradation of selected pesticides used on important crops grown on carbonatic soils and as sociated non-carbonatic soils and Oxisols from Uganda. Objective 3: Characterize organic matter from the sel ected soils, in terms of its formation, composition, and functionality. Objective 4: Identify which type of organic carbon is predominant in marl soils compared to associated peat soils from South Florida and Puerto Rico and Oxisols from Uganda. Objective 5: Identify the most dominant component of soil organic matter that influences sorption of HOCs. Objective 6: Provide a database for sorption coefficien ts and degradation rate coefficients for the major pesticides used on the carbonatic soils in Sout h Florida, Puerto Rico and Oxisols from Uganda.

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48 Table 2-1. Chemical properties of atrazine, diuron and ametryn. Name Class Solubility (mg/L) Half-life (days) Koc Chemical Structure Atrazine s-triazine 33 60 172 NN N NHCH(CH3)2NHCH2CH3Cl Ametryn s-triazine 185 60 380 NN N CH3S NHCH(CH3)2NHCH2CH3 Diuron Substituted urea 42 330 480 Cl Cl NHCON(CH3)2 Source: Wauchope et al., 2002; Wauchope et al., 1992; Hamaker and Thompson, 1972.

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49 Figure 2-1. Classification of 13Carbon nuclear magenitic resona nce spectra (Kgel-Knabner, 2002, modified from Bor tiyatinski et al., 1996).

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50 CHAPTER 3 MATERIALS AND METHODS Description of Sampling Sites The carbonatic soils from South Floridas Miam i Dade and Monroe Counties were classified as Entisol, except Keyv aca which was classified as a Mo llisol (Noble et al., 1996; Hurt et al., 1995). Those collected from Puerto Rico (Aguilita, Colinas, San Sebatian, and Yauco) were classified as Mollisols w ith the exception of Catano and T uque which were classified as Entisols and Aridisols, respectively (Mount and Lynn, 2004). Seven of the Histosols that were sampled from South Florida and Puerto Rico (Tamiami, Lauderhill, Islamorada, Dania, Pahokee, Torry, and Tiburones) were classified as saprists and Matecumbe was classified as a folist (Mount and Lynn, 2004; Noble et al., 1996). The Histosols which are widespread in the Everglades and they generally form under Cladium spp. (sawgrass) vegetation and flatwoods, with anaerobic marsh conditions minimize organi c matter (OM) oxidation rates, leading to the accretion of OM. The Spodosols were collected from flatwoods in Alachua County and were classified as Aquods. Spodosols are sandy soils with a characteristic spodic horizon where OM has accumulated in the subsurface in association with Al and Fe The Spodosols constitute the predominant soil series in the state of Florida (USDA-NRCS, 2007 Online), thus Myakka (600,000 ha).is designated the state soil. Carbonatic soils are defined as soils contai ning at least 40% carbona tes (calcite and/or dolomite). In South Florida, there are two t ypes of carbonatic soils, namely: Marl derived carbonatic soils made up of limnic materials and the marine derived oolitic limestone rockplowed-carbonatic soils. Both th e marl and rock-plowed carbonatic soils were included in this study. Marl soils are very poorly drained and located within the low elevation areas of coastal flats southern Everglades and the Florida Keys The marl soils classified in the 1958 survey

PAGE 51

51 (Gallatin et al., 1958) were Perr ine marl, Ochopee fine sandy marl, the Hialeah mucky marl and the Flamingo marl. The 1987 soil survey updated the marl soils classification in Dade County to include Biscayne, Perrine and Pe nnsuco (Noble et al., 1996) while t hose classified as marl soils from Monroe County were Key West, Cudjoe, Saddlebunch and Lignumvit ae (Hurt et al., 1995). These soils are formed by algal photosynthesis wh ich leads to secondary precipitation of calcite on top of the calcite bedrock (Figure 3-2). With the exception of Keyvaca which is a Mollisol, the rest of the carbonatic soils fr om South Florida were classifi ed as Entisols. The soils are poorly to very poorly drained, moderately to rapidly permeable. Associated soils namely Lauderhill, Matecumbe, Tamiami and Islamorada classified as Histosols were included. The carbonatic soils sampled from Puerto Rico were classified as Aguilita, Catan, Colinas, San Sebastian, Yauco, and Tuque. With the exception of Catano and Tuque which are classified as Entisols and Aridisols, respectively, the rest of the carbonatic soils were cl assified as Mollisols. San Anton (Mollisol), and Bayamon (Oxisol) we re non-carbonatic. The Ugandan Oxisols were classified as Ferrisols and Ferrarisols (Selvara djou et al., 2005). Surface samples (0-15 cm) were collected for four soil types, encompassing a wide range of vegetation, climate and OM composition. The rock plowed soils result from scarification of the ma rine derived oolitic limestone bedrock on the Miami ridge to create sites for crop production. They are generally well drained and gravelly. Table 3-1 shows the soil s from Miami Dade County, Monroe County and Puerto Rico classified as carbonatic that were collected for this study. The carbonates in these soils are mainly com posed of calcite and dolomite, with calcite being more prevalent in Miami Dade (Noble et al., 1996). Carbonatic soils are associated with organic soils that accrete OM as a result of their hydrology. Marl development is driven by algal and periphyton mats that lead to formation of secondary carbonate. These soils are inundated

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52 with water for four to eight months of the year while those that are fl ooded for at least twelve months accrete OM resulting in accumulation of an organic layer. In Puerto Rico, a total of 13 soil series out of 175 established series are ta xonomic classified as carbonatic (USDA-NRCS., 1996). Agulita (11,274 hectares), Colinas (14,107 ha), Naranjo (1,958 ha), San Sebastian (12,246 ha), Tuque (3,139 ha) and Yauco (1,337 ha) ar e classified as Mollisols while Cata o (3,617 ha) and Juacas (56 ha) are classified as Entisol s (Mount and Lynn, 2004; USDA-NRCS, 1996). The major agricultural soils from Uganda are mainly Oxisols, mainly classified as Ferrarisols and Ferrisols. Carbonatic soils in Uganda are of sma ll extent and they are mainly used for production of Cement and Lime. They can be found in Western Uganda in Kasese (Hima and Muhookya areas), Rukungiri (Rubaabo area) and in Tororo (Eastern Uganda). Pesticides Studied Based on major use and pollution potential, at razine, am etryn, and diuron were chosen for this study. Determination of Soil Properties Soil pH Soil pH was determ ined at soil solution ratio of 1:2. Determination of pH was carried out using distilled and dionized water, using 0.01 M calcium chloride solution as well as 1 M potassium chloride. An Accumet pH meter m odel 925 was used. Before pH measurement the meter was calibrated using buffers of pH 4, 7 and 10. For basic soils, buffers with pH 7 and pH 10 were used. For acidic soils buffers of pH 4 an d pH 7 were used for the meter calibration. The sample was allowed to equilibrate for 5 minutes before the reading was taken. Organic Carbon and Organic Matter Determination Organic carbon (OC) was determ ined using Walkley and Black (WB), while OM content was determined using thermogravimetric analys is (TG) and weight loss on ignition (WLOI).

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53 Sample homogenization Before W B and TG analysis, whole soil samp le homogenization was achieved in a Spex CertiPrep mixer/ball-mill model 8000M by placi ng the samples in a Lucite grinding vial containing two plastic balls a nd ball milling for 10 minutes. Walkley and Black method (WB) OC was determ ined using WB method (Wal kley and Black, 1934) and OM by TG method (Schnitzer and Hoffman, 1965; Karathanasis a nd Harris, 1994). WB %OC was determined by weighing an amount of soil corresp onding to the color of the soil. For th e dark soils, 0.5g samples were weighed into a 250 mL volumetric fl ask and 2.5 g for the light soils. To the soil was added 10 mL of 1N potassium dichromate (49.04 g of potassium dichromate were dissolved per liter of solution) followed by 20 mL of conc entrated sulfuric acid. The mixture was allowed to digest for 1 hour. The digestion was stopped by adding distilled and de-ionized water to make a total volume of about 200 mL. The mixture was al lowed to cool for about 30 minutes and then titrated against 0.5N ferrous sulfate using a Brinkmann Metrohm auto-titrator model 665 Dosimat. The ferrous sulfate solution was prep ared by adding 138.30 g per liter of distilled water and carefully adding 40 mL of concentrated sulfur ic acid to the solution and then making it to volume with distilled water. 5 drops of Ferrous sulfate complex indicator were added before the titration. The end point of the tit ration was when the mixture turned from orange to green and finally reddish-brown. The OC content was calculated using the following equation: % OC = {(mL of Blank)(mL of sample)}*{Norm of FeSO4*0.3/0.77)/G of sample} Where mL of Blank is the average titer value for the amount of FeSO4 required to reach end point for a blank of acidified potassi um dichromate. Norm is normality of FeSO4 and G of sample is the weight of the sample taken based on the color of the soil.

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54 Thermogravimetry (TG) Therm ogravimetric analysis (TG) was perf ormed using a computer-controlled thermal analysis system null microbalance Omnitherm Corporation TG Analyzer Unit model 25TG950 where the static position of th e beam during weight loss is main tained by a restoring force. TGA acquire software version 3.00.208, Instrument Speci alists Inc 1996 was used to acquire data. Whole grinded soil samples were analyzed using TG with weights that ranged from 9-15 mg. The temperature program was set at 21 OC at a rate of 25 OC/min held for 0 min and raised from 150 OC at a rate of 5 OC/min, held for 0 min and fi nally raised from 600 1000 OC at a rate of 25 OC/min. Thermo Analysis Software version 3.2, Instrument Specialists 1999 was used to analyze the Thermograms. Calibration of the TG was achieved using a standard weight and onset checked by using standa rd barium chloride (BaCl2.2H2O) and standard calcite. Weight loss on ignition (WLOI) Five gram duplicate sieved samples (2 mm me sh) were weighed in a 50 mL beaker using a Mettler balance (Model AE 100). The sample s were placed in a hot air oven at 110 oC for 24 hours. The samples were allowed to cool in a desiccator. The oven dry weight (Wod) was recorded. Muffle furnace Weight loss on ignition wa s performed on the pre-heated samples at 450 oC and 550 oC for 12 hours. The samples were removed from the furnace, allowed to cool and their weight (Wf) taken. Weight loss was calculated as: WLOI % = 100 od fodW WW

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55 Carbon Stable Isotope Determination The abundance of carbon isotopes (13C/12C) in the atmosphere a nd how plants incorporate carbon can be used to characterize origin of OM. Inorganic carbon (car bonates) was removed from carbonatic soils using 2M hydrochloric acid. 10 g were weighed in a 1 L beaker. Hydrochloric acid was added slowly until ther e was no effervescence. Excess acid was added and the soils were left to stand overnight to ensure complete rem oval of the carbonates. The soils were centrifuged using a Beckman centrifuge Model J2-21 at 7000 rpm for 15 minutes. The residue was washed twice with distilled water th en transferred in a 50 mL beaker. The samples were then allowed to dry in a hot air oven set at 40 oC, allowed to cool and then ground in a mortar. Sub-samples were measured in a tin capsul e using a Sartorius M500P weighing balance. The samples were analyzed using a Carlo Erba EA-1108 CE Elantech, Lakewood NJ, interfaced with a Delta Plus (ThermoFinnigan) isotope ratio mass spectrometer. Carbon isotopes were measured against a Vienna PeeDee Belemnite (V PDB) limestone standard. The results were expressed using the delta notation (13C) in per mil () deviation from the VPDB standard. The Nitrogen isotope was measured against UF-N2 REF standard. Nitrogen values were expressed in per mil () deviation from air. Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance spectroscopy The use of solid state 13C cross polarization magic a ngel spinning nuc lear magnetic resonance (CP-MAS NMR) can be usef ul in characterizing carbon in OM. Soil treatment for Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance spectroscopy analysis 20 g soil samples were weighed in a 1 L plasti c beaker. The samples were treated with a total of 200 mL of 2M hydrochloric acid. To avoi d spill over, the acid was carefully added for

PAGE 56

56 soils with high inorganic carbonate content. The sa mples were left to stand for 24 hrs and then centrifuged at 12000 rpm. The supe rnatant was carefully decanted. The residue was washed three times with DDI water followed by subsequent centrifuging at 12000 rpm. The residue was then treated with 70 mL of 10% hydrofluoric acid (H F acid was used cautiously). The treatment was repeated 5 times by shaking the mixture for 1 hr and centrifuging at 12000 rpm for 20 minutes followed by a treatment for 16hrs and a last treatme nt of 64 hrs. The samples were then washed four times with DDI water to remove HF and then dried in a hot air oven set at 40 oC. The residue was homogenized using Spex CertiP rep mixer/ball-mill model 8000M in a Lucite grinding vial with plastic balls. The treated soil samples were then analyzed using CP-MAS 13CNMR. Cross Polarized Magic Angle Spinning 13Carbon Nuclear Magnetic Resonance spectroscopic determination The pre-treated samples were packed in cylindrical zirconia rotors (80 uL, 4 mm outer diameter) and sealed using KelF end caps. Solid state CP-MAS 13C NMR analysis was performed using a Bruker 400 MHz Avance II spect rometer and a CP-MAS probe set at magic angle (54.7o). In order to reduce spectral errors, samp les were run with variable contact time pulse sequence (Conte et al., 1997; Piccolo et al 2005) to establish optimum contact times. Spectra were obtained with spinning rates of 13 KHz, TPPM decoupling, 1.5 ms contact time (found to be optimum for all C func tionalities in the soils analyzed), 1.5 s recycle delay, spectral width of 50 kHz and 2000 scans or more. The spectra were proce ssed using 100 Hz line broadening and baseline correction. Bloch decay (DPMAS) experiments were performed (on selected samples) at 90o pulse of 5 s and were detected in the presence of TPPM decoupling. In order to achieve 13C relaxation, a recycle delay of 10-60 s was used. Due to exce ssive baseline noise, cross polarization was

PAGE 57

57 performed on all samples since it yielded better spectral results. In order to minimize errors in peak area evaluations, we performed variable contact time pulse sequence tests to optimize the 13C signal. A contact time of 1.5 ms was found to be optimum for the analyses. The areas in the chemical shifts regions were integrated as a percentage of total area (relative intensity). The chemical shifts (Table 3-2) adopte d for this study were: Alkyl-C (0-50 ppm); Methoxyl (50-60 ppm); O-Alkyl (Carbohydrate) (60-95 ppm); Di-O-Alkyl (95-110 ppm); Aromatic (110-145 ppm); Phenolic (145-160 ppm ); and Carbonyl-C (Amide) (160-200 ppm). These spectral regions have been further segmented as unsubstituted alkyl-C (alkanes and fatty acids) (0-35 ppm); N-alkyl-C, Quaternary C (35-50 ppm); Me thoxyl C (amino acids, peptides, protein C) (50-60 ppm); aliphatic C-O (carbohydra tes) (60-108); aromatic (unsaturated and saturated C) (108-145); phenolics (145-160); carboxyl-C (carboxylate, esthers, ketones, aldehydes) (160-220) (Stevenson, 1994). Sorption of Pesticides on Soils The batch slurry m ethod (Wauchope et al., 2002; Weber, 1986) was used to measure the sorption isotherms and to determine the sorp tion coefficients of hydrophobic organic (HOCs). The equilibrium concentrations (Ce) were determined using HPLC and the adsorbed concentration (Se) was determined by difference from orig inal concentration. Sorption data for HOCs have often been described using the Freund lich model (Equation 3-1) (Albanis et al 1989; Clay and Koskinen 1990). Se = KfCe N [3-1] where Kf is Freundlich sorption consta nt (L/kg), N is the Freundlic h coefficient (dimensionless). Given Se = KfCe N Kd = dCe dSe = NKf1 N eC [3-2]

PAGE 58

58 As N approaches 1 Kd approximates to Kf. At Ce = 1 Kd = NKf. Hence within the linear range of the isotherm (low concentration), as the value of the Freundlich coefficient approximates 1.0, the Freundlich equati on reduces to the linear isotherm equation: Se = Kd Ce [3-3] where Kd is the distribution coefficient (L/kg). Since we worked within the linear range of th e isotherm, the data in this study was fitted using the linear model in order to determine the sorption coefficients. The adsorption coefficients (Kd) were normalized with OC. The maximum amount of soil (m) that will give equilibrium solu tion concentration (Ce) to be in the linear range of the isotherm was calcu lated based on the linear equation (Eq. 3-3) and the mass balance Eq. 3-4. CoVo = mSe + CeVo [3-4] where Co = Initial solution concentration; Vo = Total volume of solution; m = mass of soil added to solution. Substituting Equation 3-3 in Eq. 3-4, yields Equation 3-5. CoVo = m Kd Ce + CeVo [3-5] Rearranging eqn 3-4 eCoC = 1 o dV mK [3-6] assuming maximum initial concentration (Co) = 10 g/mL, Volume of pesticide added (Vo) = 10 mL with an adsorption coefficient (Koc) =100 and % soil OC = 2 %. From the literature adsorption coefficient (Koc) we can estimate the compound s distribution coefficient (Kd): Kd = Koc* foc [3-7] Kd = 100 0.02 = 2

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59 If we set the maximum solution coeffi cient after equilibr ation (Ce) at 5 g/ml, then the mass of soil (m) weighed = 1 10 2* 5 10 m m 5 g However this is just an estimation basing on the assumption that sorption increases with increase SOM content. Atrazine and ametryn were determined at the same parameters with the wavelength set at 230 nm and flow rate of 1.5 mL/min for ametr yn while the wavelength fo r atrazine was set at 220 nm. 10 uL were injected and the mobile phase used was me thanol (60 %), water (30 %) acetonitrile (10 %) v/v. Diuron was determined at the same paramete rs except the wavelength was set at 250 nm and a flow rate of 2.0 mL/min. Pesticide Degradation 5 g soil samples were weighed in to trip licate 50 mL polycarbona te centrifuge tubes (Figure 3-3). The samples were fortified by an aq ueous solution of a pestic ide with concentration ranging between 20 mg/L to 100 mg/L. The am ount of standard added was based on a predetermined soil moisture content equivalent to 60 % of the soil wa ter holding capacity. The mixture was allowed to stand for about 30 minutes and then stirred with a spatula to allow homogenous distribution of the pesticide. Extraction frequenc y was based on the literature pesticide degradation with the more persistent pesticides sampled less frequently compare to those with faster degradation rates. Extraction was achieved by shaking the soil sa mple with 20 mL of methanol for three hours, centrifuging the mixture for 10 minutes an d filtering the supernatant through a Fisher Brand Q2 filter paper into a 25 mL volumetric flask. The residue was extracted with an

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60 additional 10 mL methanol for 2 hours and centrifuged for 10 minutes. The extracts were combined and made to volume with methanol. Th e extracted sampled were transferred in to a screw capped sample vial and stored at -20 oC until analysis. The extracted samples were then analyzed by HPLC. In this study, degradation is operationally defined as the disappearance of the parent compound. The disappearance of pe sticide which is known as firs t order reaction is proportional to amount left in the soil and this has been found to describe a wide range of pesticide degradation rates (Zimdahl and Gwynn, 1977; Morri ll et al., 1982). The firs t order kinetics rate equation can be written as: Rate = kMo [3-8] Where Mo is the initial concentration and k the rate constant. Equation 3-8 is mathematically transformed to kM dt dM which upon integration and transformation reduces to: kt M Mo log [3-9] Equation 3-9 is rearranged to: tM = OMKte [3-10] where OM= VCo and is the initial soil concentration in mg/kg; V (mL) is the added volume and Co (mg/L) is the solution concentration; Mt (mg/kg) = Concentration at time t (days); k (1/day) is the decay constant. Equation 3-10 which is conve ntionally used was modified to equation 3-11 because the initial concentrati on and the recovered amount differ ed for the soils analyzed. The calculated k was therefore not based on (Mo/Mt).

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61 *f Mt = OMKte [3-11] where Mo is the added pesticide concentration in mg/kg of soil; f* is the method extraction efficiency. Log transformation of Equation 3-11 yeilds Equation 3-12: ktfMLnMLno t ) ( [3-12] The decay equation was modified so that th e decay constant was not dependent on the initial concentration. The decay constant k, was the slope obtained by plotting ) (tMLnagainst time t. The intercept [*) (fMLno] is a function of the initial concentration corrected for laboratory recovery. The pesticide half-life ( 21t) is calculated from: 21693.0 tk [3-13]

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62 Table 3-1. Description of the sampling s ites in Florida U.S.A. and Puerto Rico Soil series GPS location Classification Florida soil Biscayne NA Loamy, carbonatic hyperthermic, shallow Typic Fluvaquents Chekika NA Loamy-skeletal, carbonatic hypothermic Lithic Udorthents Cudjoe 240 57 231 N 0800 35 013 W Loamy, carbonatic isohyperthermic, shallow typic Fluvaquents Keyvaca 240 41 923 N 0810 22 515 W Loamy-skeletal, carbonatic Isohyperthermic Lithic Haprendolls KeyWest 240 41 445 N 0810 06 274 W Coarse-silty, carbonatic isohyperthermic Thaptohistic Fluvaquents Krome NA Loamy-skeletal, carbonatic hypothermic Lithic Udorthents Lignumvitae 240 57 068 N 0800 35 473 W Coarse-silty, carbonatic isohyperthermic Typic Fluvaquents Pennsuco 250 28 340 N 0800 23 221 W coarse-silty, carbonatic hyperthermic Typic Fluvaquents Perrine NA coarse-silty, carbonatic hyperthermic Typic Fluvaquents Perrine-Tamiami 250 45 202 N 0800 28 940 W coarse-silty, carbonatic hyperthermic Typic Fluvaquents Saddlebunch 240 39 136 N 0810 30 945 W Loamy, carbonatic isohyperthermic, shallow Typic Fluvaquents Monteocha 290 44 784 N 0820 15 841 W Sandy, siliceous, hyperthermic Ultic Alaquods Pomona 290 41 484 N 0820 13 002 W Sandy, siliceous, hyperthermic Ultic Alaquods Islamorada 250 09 550 N 0800 23 204 W Euic, isohyperthermic Lithic Haplosaprists Lauderhill 250 58 731 N 0800 25 885 W Euic, hyperthermic Lithic Medisaprists Matecumbe NA Euic, isohyperthermic Lithic Tropofolists Tamiami 250 45 203 N 0800 28 982 W Euic, hyperthermic Lithic Medisaprists Puerto Rico Soils Aguilita 180 00 101 N 0660 48 712 W Coarse-loamy, carbonatic isohyperthermic Aridic Calciustolls Catan 180 30 765 N 0670 03 302 W Carbonatic isohyperthermic Typic Udipsamments Colinas 180 22 507 N 0670 01 278 W Coarse-loamy, carbonatic isohyperthermic Typic Haprendolls San Sebastian 180 22 798 N 0670 01 315 W Clayey-skeletal, carbonatic isohyperthermic Calcic Argiudolls Tuque 170 58 502 N 0660 41 035 W Clayey, carbonatic isohyperthermic Calcic Lithic Petrocalcids Yauco 180 01 817 N 0660 31 397 W Fine-silty, carbonatic isohyperthermic Typic Calciustolls Banyam n 180 25 807 N 0660 26 192 W Very-fine, kaolinitic, isohyperthermic Typic Hapludox San Anton 180 01 613 N 0660 31 580 W Fine-loamy, mixed, superactive, isohyperthermic Cumulic Haplustolls NA=Not Available. Source: Soil Survey Staff, USDA-NRCS Official Soils Descriptions. Perrine-Tamiami is an inclusion in the Tamiami map unit.

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63 Table 3-2. Description of the samp ling sites in Uganda East Africa Soil series GPS location Classification Uganda soils (Oxisols) Fiduga 1 000 15 847 N 0320 24 655 E Buganda Catena (Ferrallitic soils) Fiduga 2 000 16 061 N 0320 24 505 E Buganda Catena (Ferrallitic soils) Fiduga 3 000 15 911 N 0320 24 595 E Buganda Catena (Ferrallitic soils) Fiduga Pooled 000 15 911 N 0320 24 595 E Buganda Catena (Ferrallitic soils) Hima 1 NA Kasese series (Lithosols) Hima 2 NA Kasese series (Lithosols) Hima 3 NA Kasese series (Lithosols) Hima Lime NA Kasese series (Lithosols) Hima Pooled NA Kasese series (Lithosols) Kakira 1 NA Kabira Catena (Ferrisols) Kakira 2 NA Kabira Catena (Ferrisols) Kakira 3 NA Kabira Catena (Ferrisols) Kakira Pooled NA Kabira Catena (Ferrisols) Kasaku 1 000 20 436 N 0320 53 907 E Mabira Catena (Ferrisols) Kasaku 2 000 20 505 N 0320 54 050 E Mabira Catena (Ferrisols) Kasaku 3 000 20 459 N 0320 54 077 E Mabira Catena (Ferrisols) Kasaku 4 000 20 870 N 0320 53 889 E Mabira Catena (Ferrisols) MK Flora 1 NA Buganda Catena (Ferrallitic soils) MK Flora 2 000 15 982 N 0320 23 985 E Buganda Catena (Ferrallitic soils) MK Flora 3 000 15 928 N 0320 23 982 E Buganda Catena (Ferrallitic soils) MK Flora 4 000 15 978 N 0320 23 927 E Buganda Catena (Ferrallitic soils) MK Flora Pooled NA Buganda Catena (Ferrallitic soils) Muhookya 1 NA Kasese series (Lithosols) Muhookya 2 000 06 194 N 0320 03 224 E Kasese series (Lithosols) Muhookya 3 NA Kasese series (Lithosols) Muhookya Pooled NA Kasese series (Lithosols) Rubaabo Sediment NA Bugangari series (Lithosols) Scoul Lugazi 1 NA Mabila Catena (Ferrisols) Scoul Lugazi 2 000 23 642 N 0320 56 503 E Mabila Catena (Ferrisols) Scoul Lugazi 3 000 23 957 N 0320 56 525 E Mabila Catena (Ferrisols) Scoul Lugazi 4 NA Mabila Catena (Ferrisols) Scoul Lugazi Pooled NA Mabila Catena (Ferrisols) Wagagai 1 000 03 651 N 0320 30 829 E Katera series (Ferrallitic soils) Wagagai 2 000 03 654 N 0320 30 858 E Katera series (Ferrallitic soils) Wagagai 3 000 03 619 N 0320 30 853 E Katera series (Ferrallitic soils) Wagagai Pooled 000 03 654 N 0320 30 858 E Katera series (Ferrallitic soils) NA=Not Available. Soil classification: Selvarad jou et al., 2005. Local classification and Food Agricultural Organisation/European Union classification in parenthsis.

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64 Table 3-2. Carbon-13 cross polariz ed magic angle spinning nuclear magnetic resonance chemical shifts for soil organic matter Functional group Shift (ppm) Functional group further segmentation Shift (ppm) Alkyl-C 0-45 Alkyl-C (alkanes and fatty acids) 0-35 Methoxyl 45-60 N-alkyl-C Quaternary C 35-50 O-Alkyl /Carbohydrate 60-95 Methoxyl (amino acids, pep tides, protein C) 50-60 Di-O-Alkyl 95-110 Aliphati c C-O (carbohydrates 60-108 Aromatic 110-145 Aromatic (unsat urated and saturated C) 108-145 Phenolic 145-160 Phenolics 145-160 Carbonyl-C (Amide) 160-200 Carboxyl-C (carboxylate, esthers, ketones, aldehydes) 160-120 Source: Stevenson, 1994.

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65 Kasozi UF-IFAS 2005 Figure 3-1. Typical rock-plowe d carbonatic soil from Homestead, Miami Dade County South Florida. Gravely, well drained soils.

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66 Figure 3-2. Algal derived seconda ry calcite flakes precipitation leading to formation of marl carbonatic soils.

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67 Figure 3-3. Set up of the degradation of pesticides in polycarbonate tubes with loose covers to prevent excessive moisture loss.

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68 CHAPTER 4 ORGANIC MATTER CHARACTE RIZATION IN CARBONAT IC AND ASSOCI ATED SOILS FROM SOUTH FLORIDA AND PU ERTO RICO USING THERMAL AND OXIDATION METHODS Introduction Soil organic carbon (OC) is commonly determined by use of oxidation processes that were originally developed by Schollenberger (1927) and Degtjareff (1930), modified by Schollenberger (1931) and later by Walkley and Black (1934). Though the Walkley-Black (WB) procedure was suggested for quick and approximate determination of OC (Walkley, 1947), this oxidation method is still widely used for rapid determinati on of soil OC. However, there is no universal method for determining th e OC content of organic matter (OM) for all soils due to the presence of compounds in numerous soils that may interfere with OM determination. A disadvantage of the WB method is its generation of large amounts of toxic dichromate waste and possible interferences from soils constituents such as oxides of iron and manganese (Walkley, 1947). In addition, the method requires the use of a correction factor (1.32) to cater for the incomplete conversion averaging 76 % achie ved, from organic carbon to carbon dioxide (Walkley and Black, 1934; Schollenberger, 1945 ). Alternative methods have since been developed that include thermal methods and elemental analysis. Elemental analysis involves determination of total carbon wh ile thermal method determinations follow weight loss due to decomposition of OM. The use of thermal methods fo r determination of OM dates as far back as the late 1940s (Mitchell and Birnie, 1970). Some studies (Schn itzer and Hoffman, 1965; Mitchell and Birnie, 1970; Critter and Ai roldi, 2006) have used thermal methods to characterize the physical and chemical nature of OM. The applicabili ty of thermal methods to OM analysis relies on the premise that the soils do not contain compounds like gibbsite, smectite and kaolinite clays that decompose within the same temperature range (200-550 oC) as OM (Mackenzie, 1970;

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69 Karathanasis and Harris, 1994). Thermal methods ar e not appropriate for an alysis of Oxisols and other soils that contains larg e amounts of clay-sized minera ls that undergo dehydroxylation or other mass losses in the temperature range of OM combustion. Following decarbonation of inorganic C with hydrochloric aci d, total organic carbon (TOC) can be determined by elemental analysis. However, the treatment step may affect purgeable OM (Motter and Jones, 2006). Total C on the other hand may be used but this re quires knowledge of carbonate amounts in carbonatic soils in order to determine organic carbon by difference. The presence of OM in soils can influence fact ors like soil fertility, soil carbon cycling and sequestration, water and nutrient retention capaci ty, bulk density, soil aggregation and xenobiotic retention. An accurate determination of OC is necessary in order to calculate the sorption coefficient (Koc) of hydrophobic organic chemicals (HOC s) whose retention in soils is predominantly associated with soil OC (Nke di-Kizza et al., 2006; Wauc hope et al., 2002; NkediKizza et al., 1983). The so rption coefficient (Kd) of HOCs in soils is normalized with the fraction of organic carbon ( foc) present in soils (Koc = Kd/ foc), and if OC is inaccurately determined, the Koc calculated may be in error. Soil OC and OM are often determined indirectly depending on the method used. A conversion factor is then used to convert from one parameter to another. The applicability of the commonly used factor of 1.724 also known as the van Bemmelen factor (Westman et al., 2006; Hana, 1964; van Bemmelen, 1891), to all soils has been contested by researchers dating as far back as 1953 (Low ther et al., 1990; Howard and Howard, 1989; Ranney, 1969; Broadnet, 1953). This is due to vari ability in nature and composition of OM, and thus using the factor to convert WLOI data to OC can lead to serious errors. The fundamental differences in SOM composition, may explain to a large extent the variability of Koc values found in the literature for a given neutral or ganic chemical (Wauchope et al., 2002).

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70 The objective of this study was to use therm ogravimetry (TG), wei ght loss on ignition (WLOI), and the WB methods to explore the relationship between OM content and OC content for three categories of soils: Car bonatic soils, associated Histosols, and Spodosols. TG provides a highly sensitive and accurate si multaneous determination of OM and carbonates in a soil sample. Unlike WLOI which is carried out blindly in the muffle furn ace, using a microbalance in the TG method provides a continuous we ight loss recording and insight on the onset temperatures for decomposition reactions, thus giving a more accurate determination of soil components. Materials and Methods Surface soil samples (0-15 cm) were collected for three soil types encompassing a wide range of vegetation and OM. Carbona tic soils from South Florida a nd Puerto Rico, classified as Entisols and Mollisols, associated Histosols from South Florida, and Spodosols from Alachua County were collected for this study. The detailed sites descriptions are available in Chapter 3. Sample Homogenization Before WB and TG analysis, whole soil sample homogeniza tion was achieved in a Spex CertiPrep mixer/ball-mill model 8000M by placing the samples in a Lucite grinding vial containing two plastic balls a nd ball milling for 10 minutes. Organic Carbon, Organic Matter and Carbonate Determination Prior to analysis, sample homogenization wa s performed as described in Chapter 3. Organic carbon was determined using WB me thod (Walkley and Black, 1934) and OM by TG method (Schnitzer and Hoffman, 1965; Karathanasis and Harris, 1994). Detailed %OC determination by WB is described in Chapter 3. Florida soil characterization da ta (Noble et al., 1996; Hurt et al., 1995) for series of carbonatic soils and Spodosols used in this study indicate that their surface horizons do not contain significant proportions of minerals that would undergo weight loss reactions in the

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71 temperature range of OM combustion. Hence th ermal methods are consid ered appropriate for determining OM content of these soils. Mineralogi cal analyses were not determined for Histosols due to their high OM content. TG analysis was performed us ing a computer-controlled th ermal analysis system null microbalance where the static position of the beam during weight loss is maintained by a restoring force. The temperature program was set as described in Chapter 3. Calibration of the TG was achieved using a standard weight and onset checked by using standard barium chloride (BaCl2.2H2O) and standard calcite (CaCO3). Weight loss on ignition wa s carried out as described in Chapter 3. Results and Discussion Standard CaCO3 loses 44 g of carbon dioxide per 100 g of the carbonate and in the check, a loss of 44 % between 600-800 oC was observed (Figure 4-1) while BaCl2.2H2O (not shown) lost 14.5 % between 75-160 oC corresponding to water of crystal lization (theoretical weight loss = 14.75 %). Some workers (Westman et al., 2006 ; Smith, 2003) have indicted that inorganic carbon in calcareous soils may decompos e if these soils are heated at 550 oC. The result of this study (Figure 4-2) show that calcium carbonate decomposition is energy dependent rather than time dependent and requires te mperatures as high as 600 oC to decompose. Using TG, standard carbonate was heated from room temperature to 550 oC and the T was held at 550 oC for two hours and thereafter increased to 1000 oC. It can be seen that the loss in weight was negligible between room temperatures and 597 oC even during the isothermal temperatures of 550 oC (Figure 4-2 A and B). Simila r onset temperatures (600 oC) for carbonate decomposition in carbonatic soils were observed (Figure 4-3A) sugges ting that even in the presence of other soil components, the temperatures for carbonate deco mposition is unchanged. Based on the results of this study, presuming that the oven temperatures is accurate and is maintained at constant

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72 temperatures, it is unlikely that a temperatures of 550 oC, if used in WLOI would cause loss of inorganic carbon (carbonates). The data in Figure 4-3(A) show the inflecti on temperatures for OM and carbonates from a carbonatic soil. The inflection between 200 and 550 oC was attributed to OM decomposition while that between 600 and 800 oC was ascribed to CaCO3. It was observed (Figure 4-3B) that even after oven treatment of Histosols at 105 oC, the Histosols continue to lose considerable weight between 105 to 200 oC which was not the case for the mineral soils analyzed. Similar weight losses between 25-150 oC were observed by Critter and Airoldi (2006) in TG thermograms of humic acids. The onset temp erature for OM decomposition is about 200 oC (Karathanasis and Harris, 1994; Barros et al, 2007) hence the weight loss between 105 and 200 oC (Figure 4-3B) cannot be attributed to OM decomposition. A temperature program was performed that involved hea ting of the soil sample to 180 oC, allowing it to cool down to ambient T in the TG oven and reheating to 1000 oC (Figures 4-4 and 4-5). Hist osol samples regained the lost weight in one hour which indi cates that the reaction is reversib le and fast. This implies that some component of the Histosols, possibly OM itself, has a st rong tendency to retain or readsorb water even at temperatures > 100 C. However, we did not find a correlation between the quantity of OM and the 105-200 oC weight loss, suggesting that water loss from an unknown inorganic component could also be responsible for the weight loss. The weight loss between 105 and 200 oC could not be attributed to loss of labile organic components be cause their loss should be irreversible. Unlike Histosols (Figure 4-3B), there was no significant weight loss between 105 and 200 oC for mineral soils. Implications are that WLOI is not a reliable measure of OM even for predominantly organic soils unless the proce dure is modified to account for weight loss at temperature < 200 oC that are not attributable to OM combustion. Some Histosols showed two

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73 distinct inflection po ints between the 200-550 oC, with peak maxima at 280 and 480 oC probably indicating that Histosols contain the heat labile and heat stab le fractions of organic matter with the later requiring higher temperature (400-500 oC) for decomposition. No mass loss over time was observed when the sample temperature was held at 105 oC for one hour. Weight loss was observed when the sample was heated to 180 oC, indicating the reversib le mass loss (presumably water desorption) is energy rath er time dependent (Fig. 4-5). Possibly it relates to the dominant influence of the sawgrass detritus. The results obtained from co rrelation between TG %OM and WB %OC indicate that the slopes for Carbonatic soils differ from those of Histosols and Spodosols (Figures 4-6A, 4-6B, and 4-6C). This may be due to differences in th e nature of OM, as influenced by sources of C pools in these soil categories. Th e conversion factor 1.74 0.12 ( 0.12 is the 95% CI), for Carbonatic soils, unlike those of the Histosol (1.48) and Spodosol (1.44), closely corresponds to the literature convers ion factor of 1.724. However, this factor is not universally applicable due to the inherent heterogeneity and complexity of OM composition and functionality, as documented in this study. It is possible that the OC content of OM in Carbonatic soils differs from that of other soils due to its hydrologic and biologi cal setting. Marl formation is driven by algal and periphyton photosynthesis and algal mats constitute the majority of the OM pool present in these soils as compared to Histosols, whose major OM source is sawgrass, and Spodosols, which are strongly influenced by forest litter. Possibly the compos ition of OM in carbonatic so ils has lower affinity for water compared to the OM derived from highe r plants like sawgrass and forest litter. The carbon content in humic acids is assumed to ra nge from 53.8 to 58.7 percent (Stevenson, 1994). Using this relationship yields a conventional equation: %OC = 0.58 %OM. Data in Figure 4-

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74 6B on the other hand, show a mean factor of 1.48 0.08 for Hist osols. This conversion factor suggests that Histosols may have a higher percent OC per gr am of OM of about 64-72 % compared to common mineral soils whose colloi dal SOM is assumed to contain 58% OC. Hence using a conversion factor targeted to mineral soils may result in underestimating organic carbon content in Histosols. Statisti cal analysis showed a differen ce in TG and WLOI methods ( =0.05) for Histosols. The source of the difference between the two methods was attributed to the ability oft Histosols to retain sufficient amounts of water even after heati ng it in an oven at 105 oC for 24 h. The common practice i nvolves heating soils at 105 oC to remove moisture and then the subsequent loss in the muffle oven is ascribed to OM. Organic matter acc retion in Histosols of South Florida is due to inundation of poorly drained soils with water for most part of the year causing anaerobic conditions th at slow down OM oxidation. Carbonatic soils form under relatively similar conditions but the difference in the hydrologic regimes and OM pools (algal derived) may explain the differe nce observed in carbonatic soils in terms of water retention. The conversion factor obtain ed by correlation of TG %OM with WB %OC for Spodosols (Figure 4-6C) was 1.44 0.10. Spodosols were included in this study due their prevalence in Florida and the state soil Mya kka is classified as Spodosols. The conditions required for Spodosols development include acid litter from fo rests and high precipita tion and seasonal water table for most part of the year. This accordin gly results in translocation and accumulation of organo-metallic complexes of aluminum, iron, si lica and OM from upper horizons to the Spodic horizon. The wet conditions probably slow down the oxidation process resulting in OM with a higher OC content hence the observed conversion factor of less that 1.74 used in the lite rature for mineral soils.

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75 The effect of temperature on WLOI results was investigated by determining OM at 450 oC and 550 oC. An increase in weight loss was obs erved after heating the sample at 550 oC though statistical analysis showed no difference between the two temper ature set points. Weight loss on ignition (Figure 4-7) yielded a conversion factor of 1.76 0.09 for Histosols. The high correlation (R2 = 0.95) obtained between WLOI % OM and WB %OC (Figure 4-7) suggests that the water of hydration is associ ated with OM. No difference ( = 0.05) was observed between soil carbonate content determined by TG a nd carbon dioxide coulom etric measurements. Data obtained from all three methods for OC, OM and carbonates are summarized in Tables 4-1 to 4-3 for the soils studied. OC in carbonatic soils ranged between 1.17-11.37 % while carbonates ranged 47-94 %. The OC cont ent for Histosols and Spodosols ranged 9.4753.37, and 0.85-5.32 %, respectively. It is evid ent that TG and WLOI methods predict OM well in carbonatic soils (Figure 4-8) with a conversion factor of essentially one between the two methods. A statistical analysis of the two methods showed no significant difference. However, in addition to simultaneous determination of carbona tes, the TG method provides more insight on the onset points thus providing a better estimate of reaction taking place du ring soil combustion. XRD analysis of carbonatic soils indicated th e presence of calcite at D spacing = 3.84 and 3.03 (Figure 4-9) as the major mi neral in these soils. The absence of minerals that can interfere with OM analysis and the fact that the amount of OM present ma y not be sufficient to abstract water makes thermal methods suitable for estima tion of OM in carbonatic soils. Basing on the XRD for carbonatic soils and the f act that these soils are associ ated in South Florida, but differing in formation in terms vegetation and hydro logic regimes, it is unl ikely that the observed loss of water (between 105-180 oC) is associated minerals in Histosols other than OM.

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76 The regression analysis of TG %OM with WB %OC obtaine d for Oxisols from Uganda resulted in a conversion factor of 3.91 (data not shown) which c onfirms that thermal methods are inappropriate for analysis of OM in Oxisols. XRD (Figure 4-10) confirme d presence of kaolinite (7.19 and 3.57) and hematite (2.69 and 2.51) mi nerals in these highly weathered soils. The presence of these minerals in the Oxisols may hi nder use of thermal methods in the analysis of OM in Oxisols. A relatively well defi ned peak with maxima between 450-520 oC was observed in the Oxisols. The peak between 450 and 520 oC could be due to decomposition of kaolite along side the more thermally stable moieties of OM such as aromatic groups. Conclusions The OC content of OM was similar for the Histosols and Spodosol s studied, but was significantly higher than what w ould be calculated from the comm on conversion factor of 1.724. However, this factor was reasonabl y close to that determined for the Carbonatic soils (1.74). The Carbonatic soils, Histosols, and Spodosols studied differ in pr imary producers, i.e., algae, sawgrass and forest litter respectively. A single conversion factor is not realistic for all soils, given the spatial and compositional variability of OM. Since the predominant mineral in carbonatic soils is calcite, their OM and calcite content can be determined simultaneously with TG. The conversion factors of 1.48, and 1.44 for Histosols and Spodosols, respectively, obtained in this study indicate that these soils may cont ain more OC per gram of OM. The use of 0.58 to convert OM to OC may result in underestimation of OC in Hist osols and Spodosols. The fact that Oxisols contain minerals like kaolinite that interfere with OM analysis renders thermal methods inappropriate for determin ation of soil OM in Oxisols. Results of this study document that 1) OC content of OM differs significantly between soils of different hydrologic and vegetative settin gs, and 2) WLOI is not a reliable measure of OM, even for organic soils, unless weight loss below 200 oC is taken into account.

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77 Table 4-1. Organic carbon (OC) and organic matter (OM) determination in carbonatic soils using WB, TG, and WLOI methods, a nd carbonates. Soils sampled 0-15 cm. Carbonates % Carbonatic soil name Soil origin WB % OC TG % OM WLOI %OM at 450 oC WLOI %OM at 550 oC TG CO2 Coulometry Aguilita PR 4.79 10.32 10.18 13.32 53 56 Biscayne 1 FL 5.69 9.42 10.30 11.73 84 75 Biscayne 2 FL 2.91 5.93 6.09 8.27 82 Biscayne 3 FL 4.15 6.78 7.16 7.61 90 Cudjoe FL 10.15 17.85 18.89 22.72 68 Chekika FL 2.05 4.01 4.45 6.58 89 84 Chekika 2 FL 4.10 8.77 8.97 12.63 58 Colinas PR 2.39 5.01 5.33 8.99 80 Key Vaca FL 11.38 19.03 19.06 21.33 64 KeyWest 1 FL 1.22 3.30 3.14 7.50 89 KeyWest 2 FL 1.17 2.80 3.21 6.40 94 Krome 1 FL 1.49 3.77 4.47 7.44 64 64 Krome 2 FL 2.28 6.47 6.65 9.45 50 51 Legumnivitae 1 FL 6.12 9.04 9.92 11.63 84 Legumnivitae 2 FL 4.71 7.43 9.20 10.92 85 Pennsuco FL 2.74 5.73 6.34 7.40 84 80 Perrine 1 FL 2.92 5.16 5.58 6.24 88 76 Perrine 2 FL 2.89 4.16 4.98 5.39 91 79 Saddle Bunch 1 FL 1.71 1.80 3.61 4.43 47 Saddle Bunch 2 FL 8.06 11.80 14.82 15.51 79 San Sebastian PR 2.25 5.88 6.12 7.36 53 Tuque PR 2.35 5.22 4.93 6.11 86 84 Yauco PR 7.56 5.36 7.29 9.39 62 65

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78 Table 4-2. Organic carbon (OC) and organic matter (OM) determination in Histosols from Florida (FL) and Puerto Rico (PR) using WB, TG, and WLOI methods. Histosols soil name Soil origin Soil Depth (cm) WB % OC TG % OM WLOI %OM at 450 oC WLOI %OM at 550 oC Carbonates % by TG Dania 1 FL 0-15 42.91 71.64 84.97 85.25 7 Dania 2 FL 15-30 53.37 70.77 85.73 85.93 8 Islamorada FL 0-15 38.79 53.63 67.36 68.03 10 Lauderhill 1 FL 0-15 28.74 44.21 49.64 50.38 10 Lauderhill 2 FL 0-15 20.98 32.35 32.88 33.43 18 Lauderhill 3 FL 0-15 22.73 35.00 41.04 41.77 0 Matecumbe 1 FL 0-15 32.47 47.08 54.06 54.43 11 Matecumbe 2 FL 0-15 19.76 42.61 47.73 48.83 0 Pahokee 1 FL 0-15 42.30 62.84 78.52 78.91 10 Pahokee 2 FL 15-30 47.11 66.71 82.67 82.95 9 Tamiami 1 FL 0-15 40.05 58.10 66.03 66.66 0 Tamiami 2 FL 0-15 19.78 26.36 28.43 28.84 54 Tamiami 3 FL 0-15 39.72 59.78 68.96 69.63 5 Tiburones PR 0-15 9.47 16.13 15.57 16.79 5 Torry 1 FL 0-15 12.78 20.79 20.11 22.69 0 Torry 2 FL 15-30 9.63 18.92 17.74 19.68 34 Table 4-3. Organic carbon (OC) and organic matter (OM) determ ination in Spodosols using WB, TG and WLOI methods. Spodosol name or horizon Soil origin Soil depth (cm) WB % OC TG % OM WLOI %OM at 450 oC WLOI %OM at 550 oC Monteocha 1 FL 0-15 5.32 7.53 8.55 8.58 Monteocha 2 FL 0-15 1.12 1.73 2.71 2.73 Pomona 1 FL 0-15 0.85 1.60 1.62 Pomona 2 FL 0-15 2.32 3.13 3.66 3.68 Pomona 3 FL 0-15 1.12 1.75 2.23 2.25 Pomona 4 FL 0-15 2.04 3.37 4.07 4.09 Pomona E FL 15-30 0.21 0.48 0.28 0.28 Pomona Bh-1 FL 80-95 0.89 1.84 2.32 2.43 Pomona Bh-2 FL 80-95 1.83 3.00 4.07 4.13 Pomona Bh-3 FL 80-95 0.62 1.03 2.44 2.48

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79 Figure 4-1. Verification of the TG calibration using standard calcium carbonate. Line 1 is weight loss, while line 2 is 1st temperature derivative.

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80 Figure 4-2. Confirmation for the onset deco mposition temperature for calcium carbonate preheated to 550 oC for 2 h, decomposition starts at 600 oC. Line 1 Figure B is temperature profile and Line 2 is the derivative for weight loss onset.

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81 Figure 4-3. TG thermograms A) Fo r carbonatic soils, pre-heated at 110 oC for 24 hour. B) For Histosols, pre-heated at 110 oC for 24 hour.

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82 Figure 4-4. TG analysis of a Histosol heated to 180 oC, cooled then heated to 1000 oC. Line 1 is the temperature profile and line 2 is the weight loss

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83 Figure 4-5. TG analysis of organic soil material (from a Histosol), using isothermal steps to investigate energy dependency for wei ght loss versus time. Line 1 is oven temperature and line 2 is soil sa mple percent weight loss.

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84 A Carbonatic OM = 1.74xOC R2 = 0.90 0 5 10 15 20 25 0.0002.0004.0006.0008.00010.00012.000 WB %OCTG %O M B Histosols OM = 1.48xOC R2 = 0.93 (n=16)0 10 20 30 40 50 60 70 80 90 0102030405060 WB %OCTG %O M C Spodosols OM = 1.44x OC R2 = 0.990 1 2 3 4 5 6 7 8 90123456 WB %OCTG %O M Figure 4-6. Correlation between TG %OM and WB %OC. A) Fo r carbonatic soils. B) For Histosols. C) For Spodosols.

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85 Histosols OM = 1.76xOC 95% CI= (1.67-1.86) R2 = 0.95 (n=16) 0 10 20 30 40 50 60 70 80 90 100 01 02 03 04 05 06 0 Walkley-Black %OCWLOI %OM Figure 4-7. Correlation between WLOI %OM and WB %OC for Histosols. Carbonatic soils WLOI %OM = 1.0 x TG %OM + 0.4 R2 = 0.97 0 5 10 15 20 25 0 5 10 15 20 TG %OMWLOI %OM Figure 4-8. Correlation between WLOI %O M and TG %OM in carbonatic soils.

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86 Figure 4-9. X-ray diffracti on curves for Bicayne seri es (carbonatic soil).

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87 Figure 4-10. X-ray diffraction curves for a Ugandan Oxis ol from Kakira Jinja.

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88 CHAPTER 5 SORPTION AND DEGRADATION OF SELECTED PESTICIDES IN CARBONATIC AND ASSOCIAT ED SOILS Introduction Sorption and transformation are believed to be the major processes that determine the fate of an organic pesticide once applied in the soil environment (Karapanagioti et al., 2001; NkediKizza, 1983; Karickhoff et al., 1979). Sorption is also believed to protect the sorbed phase of pesticides from microbial degrad ation hence half-lives of pesticides are likely to differ in different soils depending upon the sorption capacity of the soil. The soil/solution distribution coefficients (Kd values), have been found to correlate with organic carbon (OC) therefore invoking the linear model to describe the partition of HOCs in soils. Using this relationship, it is assumed that OC controls sorption of HOC s (Thurston, 1953; Gori ng and Hamaker, 1972). Normalizing the Kd values with OC results in a unique partition coefficient (Koc) which can aid decision support models to predic t the potential of chemical move ment in a soil profile. Higher Koc values indicate high sorption capacity of the chemicals that may pose risk to surface water pollution via erosion. On the othe r hand, depending on the half-life (t1/2) of the compound, chemicals with low Koc have potential to leach to ground water, thus pos ing risk to pollution of groundwater resources. The groundwater ubiquity score (GUS) developed by Gustafson (1989), has been used to assess potential for groundwater pollution. By use of the Koc and t1/2 a GUS score can be calculated from Equation 5-1: GUS = 2/1log*log4 tKoc [5-1]

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89 A GUS score of <1.8 indicates low leachi ng potential; 1.8 2.8 indicates potential for leaching (Bernard et al., 2005; Geisler et al., 2004; Laabs et al., 2002; Gustafason, 1989). The tropical environment in Uganda encourages proliferation of agricu ltural pests resulting in destruction of agricultural pr oduce. The use of pesticides is mostly uncontrolled though the scale is smaller compared to the United States. Th e low pesticide consumption is due to the fact that agriculture in Uganda is mostly at subsistence levels. Isotherm non-linearity, differen ces in the nature and functio nality of OM and errors resulting in determination of soil OC may explain the variability. A single Koc for a particular pesticide may not be realistic since previous studies have sh owed isotherm non-linearity and variations in sorption capaciti es of a single compound in various soils. Although pesticides are applied to control target pests, they usually end up polluting the environment due to leaching and surface transport due to erosion. They may also degrade forming metabolites that are more toxic and persistent than the parent compound (Edwards, 1973) posing environmental hazards. Among the most frequently detected pe sticides in surface and ground wa ter resources of South Florida are ametryn, atrazine, atrazine desethyl, chlorpyrifos, chlor pyrifos ethyl, 2,4-D, endosulfan alpha, beta and endosulfan sulfate, hexazinone and metolachlor (Mil es and Pfeuffer, 1997). Atrazine (6-chloroN -ethylN -(1-methylethyl)-1,3,5-triazine-2, 4-diamine) classified as an striazine is one of the most widely applied herbicides in the United States. It is used as a preand post-emergence herbicide and acts by stopping photosynthesis, thus killing the plant. Ametryn ( N -ethyl-N -(1-methylethyl)-6-(methylthio)-1,3,5-tri azine-2,4-diamine) classified as methylthiotriazine is also widely used in US A. Its inclusion in this study was based on its detection in surface waters of South Florida.

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90 Materials and Methods Carbonatic soils and associated non-carbonatic soils were coll ected from South Florida and Puerto Rico. Oxisols from Uganda and Spodosols from Alachua County Florida were included for comparison. Surface horizons (0-15 cm) were collected for analysis except Torry, Pahokee and Dania for Histosols and S podosols from Alachua where both surface and lower horizons were collected. Detailed soils descriptions are in chapter 3. The soils we re air dried and passed through a 2 mm sieve before analysis. Atrazine Analysis Atrazine standard was obtained from Accusta ndard with purity of 98%. Standard solutions were prepared by parallel diluti on. Standard atrazine was dissolv ed in 2 mL methanol and made to volume (1 L) with 0.01 M calcium chloride solution. Sorption isotherms were determined using Batch and Slurry equilibrium method (Wauchope et al., 2002; Nkedi-Kizza et al., 1985 ; Weber, 1986). Different concentrations of atrazine were added to the soils at concentrations of 10, 7.5, 5, and 2.5 g/mL in 0.01 M calcium chloride. 10 mL of each concentrat ion level were added to the soil in triplicate. The mixture was then shaken on an action shaker at ambient temp erature for 24 hours. Blanks were included to check for adsorption on the walls of the tubes and/ or degradation of analyte during the equilibration process. After equilibration, the mixture was centrifuged using a Beckman model J2 21 centrifuge at 10,000 rpm for 15 minutes. The supernatant wa s then filtered through a # 42 Whattman filter paper before tr ansfer to a borosilicate glass vial. Analysis was done using Waters 2690 Separation Module Reversed Phas e HPLC (Waters Chro matography Division, Millipore) equipped with a Wa ters 2487 Dual Absorbance UV detector and Nova-Pak C18 reversed phase column (150 x 3.9 mm). The det ector was set at 230 nm and 1 Aufs. A methanol

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91 and water mixture (60: 40 v/v) was used as mobile phase, at a flow rate was 1.5 mL/min. Data was handled using Millenium32, Version 3.05.01 1998 Waters Corporation software. Ametryn Analysis Ametryn standard was obtained from Accustanda rd with purity of 98% Standard solutions were prepared by parallel dilution. Standard am etryn was dissolved in 2 mL methanol and made to volume (1 L) with 0.01 M calcium chloride solution. The batch experiment was set up as describe d for atrazine. The HPLC UV-VIS detector was set at 250 nm wavelength and 0.5 AUFS ab sorbance. The sorption isotherms for ametryn were treated as described for atrazine. Diuron Analysis Diuron standard was obtained fr om Accustandard with purity of 98%. Standard solutions were prepared by parallel dilution. Standard diuron was dissolved in 2 mL methanol and made to volume (1 L) with 0.01 M calcium chloride solution. The batch experiment was set up as describe d for atrazine. The HPLC UV-VIS detector was set at 250 nm wavelength and 0.5 AUFS abso rbance. The sorption isotherms for diuron were treated as described for atrazine. Model Fitting Sorption data were fitted using th e linear sorption isotherm model Se = KdCe [5-2] where Se is the sorbed concentration (mg/kg of solid surface) at equilibrium, Kd is distribution coefficient (L/kg) and Ce is the solution concentration (mg/L) at equilibrium. From the plot of Se against Ce, the slope obtained from the linear graph (Kd) was normalized with fraction of OC ( foc) to calculate the sorption coefficient Koc. Koc = Kd/ ( foc) [5-3]

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92 Pesticide Degradation Degradation was defined as the extractable conc entration of the pesticide at time t (days) of.incubation. The extraction and analytical procedure are outline in Chapter 3. Quality Control/Quality Assurance Triplicate samples were analyzed for each for tification concentration level. Blanks were included in the analysis to assess potential for sorption on container walls. 10 mL of the standards at varying con centrations were transfe rred into centrifuge tubes without soil. The tubes were treated similarly as those with soil. A sub sample of the solution was analyzed and percentage recoveries based on orig inal concentration in the tube. Results and Discussion Atrazine Sorption The recoveries in the blanks (without soil) exceeded 95 % wh ich indicated no sorption of atrazine on the walls of the centrifuge tubes or degradation within 24 hours of the equilibration process. In addition, recovery of atrazine through filtration using Whatman # 42 filter paper exceeded 95 %. The Kd values reported in Table 5-1 for carbonatic soils range from 0.565 to 6.937 thus the Kd values varied within a factor of 12. Key West soil series had the lowest Kd values and Keyvaca the highest. Marl-carbonatic soils showed lowest sorption capacities for atrazine with an average Koc of 45 compared to 65, 108, 183 and 790 for non-marl carbonatic, Histosols, Oxisols and Spodosols, resp ectively. The range of Koc values for carbonatic soils was 45-105. The variation was within a f actor of 2. The literature Koc value for non-carbonatic soils is 172 (Hamaker and Thompson, 1972). Among the carbonatic soils sampled, the Perrine-Tamiami association showed the hi ghest sorption capacity (Koc = 105). Although this soil had 4.1 %OC content compared to Keyvaca and Cudjoe which had 11.4 % and 10.2 % OC content,

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93 respectively, it displa yed higher sorption (Koc = 106). Islamorada which is an organic soil (39 %OC) from South Florid a showed rather low Koc, comparable with Krome (1.5 % OC). The Koc values for Islamorada were 74, 157, and 273 fo r atrazine, ametryn and diuron, respectively. These observations confirm that the nature of OM present in the soils played an important role in the sorption properties. The Perrine-Tamiami association sample was collected from within the Tamiami series map unit. The vegetation in Histosols is predominantly Cladium spp. (sawgrass) compared to marl soils whose organic primary pr oducer is the algae, which drive the marl soil formation. Some studies have found correlation between organic ca rbon and distribution coefficient (Hamaker and Thompson, 1972) sugges ting OC is the predominant soil component that controls sorption of HOCs. Ho wever, the difference in the natu re of OM present in different soils may result in different affinities for sorp tion of HOCs and as a result for a particular pesticide, Koc values may vary from one soil to an other and from region to region depending on the nature and origin of the OM present in th e different soils. The OM in the rock-outcrop carbonatic soils such as Chekika and Krome forms from different sources compared to that in marl-carbonatic soils (algal detr itus). It is possible that this difference accounts for the higher Koc values in the rock-plowed-carbonatic soils. Gene rally, carbonatic soils showed lower sorption capacity irrespective of origin compared to the other soils ty pes. The tendency of non-linear sorption isotherms for organic soils has been obser ved in a few cases in this study especially as the initial solution increased. Other studies attribute the non-linearity tendency of sorption of organic compounds to particulat e kerogen and black carbon (Corne lissen et al., 2005). In this study initial pesticide concentra tions were in ranges slightly higher that the recommended application rates to enable detection by HPLC. The results may remain relevant in cases where application rates may be exceeded or in cases of environmental spills. Even at these slightly

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94 higher levels, the isotherms were linear (Figur es 5-1, A-1 to A-12). A correlation of Kd values with the fraction of organic ca rbon (Figures 5-3 A, 5-4 A and 5-5 A) is an indication that partitioning HOCs to soil organic carbon could be the major process contro lling the sorption in carbonatic soils. When the Kd values were normalized with organic carbon the Koc values ranged from 36 to 105 with Perrine soil series having the lowest Koc and Perrine-Tamaimi association series having the highest Koc values. The marl carbonatic soils had lower Koc values compared to the non marl carbonatic soils. Data in Figure 5-1 show an isotherm for Laude rhill series from South Florida. The figure shows that the data could be de scribed using the linear model (R2 > 0.95). The slopes of the graphs for different soil types (F igure 5-2) varied i ndicating that these soils may be adsorbing pesticides differently. The atrazine slopes (Koc values) were 57, 117, 174, and 510 for carbonatic soils, Histosols, Oxisols and Spodos ols, respectively. The results s how that the order of sorption is Spodosols > Oxisols > Organic soils > Carbonatic soils. The data analyzed separately for each soils series show that the sorp tion capacity for atrazine was in the order: Spodosols (Figure 5-3 D) > Oxisols (Figure 5-3 C) > Histosols (Figure 5-3 B) > Carbonatic soils (Figure 5-3 A). The sorption capacity for marl-c arbonatic soils was lower ( = 0.05) than what was observed for rock plowed carbonatic soils. This may be due to difference in OM composition since these soils formed under different vegetative conditions. It is likely that the OM primary producers are playing an important role in the sorption capacities of these two soil types with carbonatic mineralogy. The OM content in Spodosols was very low ranging between 0.62 % and 5.32 %. However these soils displayed higher Koc values for atrazine (Table 5-5) ranging from 374 to 1060 and 115 to 443 for surface and Bh horizons re spectively. Given the low OM content and high Koc values, it is possible that other soil com ponents other than OM may be contributing to

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95 the sorption of HOCs in Spodosols. Furthermore, the OM present in Spodosols is of different origin as it is mostly contributed by forest litter compared to Histos ols whose OM source is sawgrass and algae for marl-carbonatic soils. The Koc values for Histosols were lower than that of Spodosols and Oxisols though Hi stosols contained organic car bon up to 10 times higher than for Oxisols and Spodosols. The Koc for Histosols ranged from 69 (Pahokee series) to 171 (Dania series). It is generally believed that sorption capacity increases with increase in organic carbon. However in this study, this model broke down when we compared soils that may contain different sources and forms of OM. The compos ition of OM in terms of humic acids, humic, kerogen and their affinity for HOC s may be different. This study s hows that the quality as well as the quantity of OM contribu tes greatly to the sorption capac ity of soils. Xing (1997) found similar Koc variation which he attributed to the nature of SOM. Ametryn Sorption Ametryn sorption on container wall was checked and the recoveries exceeded 95 %. The sorption coefficients for ametryn we re higher (Table 5-2) than for atrazine (Table 5-1) but were lower than those for diuron except for Spodosols which had Koc values higher than obtained for diuron. Saddlebunch (Key West area, S outh Florida) showed the lowest Koc for marl soils with a Koc of 60 while Pomona series showed the highest Koc value of 6960. The OC content for Spodosols ranged 0.8 and 5.3 for surface soils and 0.6 to 1.8 in Bh horizons. The values for OC content were generally higher than 1 % cutoff where mineral materi als contribution to sorption becomes important. The low correlation in Spodosols (Figure 5-4 D) indicat es that OC content alone may not account for sorpti on. Although the pH values for Spodosols were in the acidic range (3.86-4.24 in surface soils and 4.36-4.71 in Bh horizons), the chemicals studied are expected to be in neutral phase hence partitioni ng is expected to be the major adsorption

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96 mechanism. Marl-carbonatic soils showed the lo west sorption capacities for ametryn sorption. The Koc values for ametryn in marl-carbonatic soils averaged 107 and were 2, 2, 6, and 21 times lower than those of non-marl-carbon atic soils, Histosols, Oxisols and Spodosols, respectively. Ametryn Degradation Ametryn degradation was best described by exponential decay fitting first order reaction kinetics. The t1/2 value for carbonatic soils ranged between 15 and 248 days with Key West soil series showing the longest half life. No rela tionship was observed betw een ametryn degradation rates and sorption. Diuron Sorption Diuron sorption was higher th an that of atrazine a nd ametryn. The Average Koc for carbonatic soils was 257 compared to 59 and 134 fo r atrazine and ametryn, respectively. The literature log Kow values have been used to descri be compound hydrophobicity (Inoue et al., 2004). The Kow of 2.85 for diuron, compared to 2.50 fo r atrazine, shows that diuron is more hydrophobic than atrazine. This high hydrophobicity may explain diurons higher ability to partition to organic matrix hence the higher Koc values compared to atrazine. The results showed a positive relationship between th e distribution coefficients (Kd) and the fraction of OC ( foc), which indicates that OC may be playing an important role in the sorption process of diuron in the soils studied. The low R2 (0.2) for Oxisols (Figure 5-4 C) suggests that OC alone may not account for the whole pesticide so rption for Oxisols. Despite their low OC content, Spodosols displayed the highest sorption capacities. It is possible that the OM r eactions in Spodosols and Oxisols result in accumulation of components cont ributing the most to the sorption of HOCs. Alternatively, other components ot her than OM may be contributi ng to the sorption of HOCs in Oxisols and Spodosols.

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97 Carbonatic soils showed the lowest so rption capacities for sorption. The Koc values for diuron in marl-carbonatic soils av eraged 197 and were 2, 3, 5, and 8 times lower than for nonmarl-carbonatic soils, Histosols, Oxisols and Spodosols, respec tively. The literature Koc for diuron in non-carbonatics is 480 (Wauchope et al., 1992). Diuron Degradation Diuron degradation was described by first or der (Figure 5-7A). The decay constant was obtained from the slope of the l og transformed of concentration against time (Figure 5-7B). The t1/2 of diuron in carbonatic soils ranged between 45 (Keyvaca FL) and 315 days (Saddlebunch FL). Bayamon is classified as an Oxisol showed the fastest degradation rate for diuron with a t1/2 of 35 days while Saddlebunch, classified as a Mollisol with carbonatic mineralogy showed the slowest degradation rate for di uron with a of 315 days. The t1/2 values were calculated from log transformed data (Figure 5-8) from the decay cons tants obtained from the degradation curves. In this study no relation was observed with sorp tion or OM. Brown (1994) similarly observed no relationship between sorption and degradation. It is possible that hydrolysis plays an important role in the chemical disappearance hence the poo r correlation between sorption and degradation. If hydrolysis contributes greatly to the pesticide disappearan ce, the concept of pesticide protection may not hold. The low initial concentr ation recovery may be evidence that hydrolysis occurs rapidly at the beginning l eading to poor recoveries. The results were inconsistent with other studies (Smith et al., 1992; Ogram et al., 1985; McCormick and Hiltbold, 1966) that reported an increase in degradation rate as OM increases. This was t hought to be due to utilization of OM by microbes as a source of energy. Some studies (Johnson and Sims, 1993; Ogram et al., 1985; Helling et al., 1971; Harris, 1967) have reported a decrease in degradation with increase in sorption capacity citing protection of the chemical from microbial attack due to sorption.

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98 The relatively slow degradati on rate and low sorption for di uron in carbonatic soils may provide reason for its frequent detection in Sout h Florida and Puerto Ri co surface waters. Since application rates are based on soil OC conten t which affects the net activity (solution concentration) of the compound a pplied, it is possible that diur on remains effective in carbonatic soils even when applied at lowe r rates since the chemical is poorly adsorbed. Protecting the environment in these vulnerable soils may theref ore require lowering the application rates for HOCs. There was no difference in diuron t1/2 values obtained for car bonatic and non-carbonatic soils. Vulnerability of Groundwater to HOCs Contamination The GUS scores (Figure 5-9) for diuron range d between 3.32-4.55, 2.62-4.11, 2.61-3.67, 1.85-3.29, and 0.80-1.74 for marl carbonatic, non -marl carbonatic, Histosols, Oxisols and Spodosols, respectively. Table 56 shows the diuron degradation da ta for the soils that were analyzed. Saddlebunch showed the highest poten tial to leach diuron from South Florida while Tuques showed the highest potential for soils from Puerto Rico. Key West (marl carbonatic) showed the highest poten tial to leach ametryn (Tab le 5-7). Marl soils show ed highest potential to leach diuron while the Spodosols GUS values indi cated very low leaching potential for diuron. This trend was similarly reflected in the Koc values that were obtained for the different soil classes. The scores in ca rbonatic soils were lower ( =0.05) for ametryn compared to those obtained for diuron. This may indicate lower leac hing potential for ametr yn in carbonatic soils (Figure 5-10). A chemical is considered a leacher if its GUS score is greater than 2.8 (Bernard et al., 2005; Geisler et al., 2004; L aabs et al., 2002; Gustafson, 1989) Figure 5-9 shows that in accordance with the GUS score Spodosols have lo w potential for leaching diuron, the Oxisols were in the transitional state while Histosols a nd carbonatic soils were found to be vulnerable to leaching of diuron. The leaching potential may ho wever, vary according to climatic conditions

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99 like temperature and precipitation, intrinsic so il properties such as permeability and drainage class, depth to the water table, and farmi ng practices. The GUS scores for ametryn were significantly lower ( = 0.05) than those for diuron sugge sting that diuron has higher leaching potential than ametryn. The results showed th at leaching potential varies across chemicals resulting from their degradation rates and sorption potential. Conclusions The average pesticide sorption coefficient fo r marl-carbonatic soils was found to be less than 1/3 of the Koc values calculated for non-carbonatic soil s. Marl carbonatic soils were found to sorb less compared to the ro ck-plowed carbonatic soils. This is likely due to differences in OM primary producers in the two soil types. Give n the physical and chemical properties of the soils and their differing genesis, it can be seen that the tw o soil types (Marl and non-marlcarbonatic) present different challeng es to sorption of pesticides. The algae which drive the marl formation, may be the major primary producer thus influencing their OM physical-chemical behavior, hence the low sorpti on capacity for HOCs. The linea r relationship obtained from regressing Kd with OC content indicated that OC controls the sorption process of the HOCs in carbonatic soils, and Histosols. By comparing the quantitie s of OC in carbonatic soils, Histosols, Oxisols and Spodosols (Tables 5-1 to 5-5), the results show that the quality as well as the quantity of OM contributes greatly to the sorption capacity of soils. The poor correlation between Koc and SOC content, obtained for atrazi ne, ametryn and diuron in Oxisols and Spodosols indicates that SOC conten t alone is insufficient to acc ount for the sorption of HOCs in these soils. The rock-plowed soils of South Florida are gr avelly and well draine d and have a shallow water table. Despite the fact that these soils show higher sorption capacit ies in the laboratory studies, possibly due to the nature of OM, the pesticides may not have sufficient time to interact

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100 with the soil OM, thus preventing leaching/ contaminating groundwater under field conditions. The GUS score classification (Fi gure 5-9) indicates that rock -outcrop carbonatic soils have a high potential to leach diuron. Marl soils on the other hand tend to exhibit lower sorption capacity due the nature of OM in these soils. Th e OM in marl soils which is from diatoms may not be as complex as that from higher plants that are prevalent in well drained rock-plowed soils. The difference in the nature of OM present in the two soil types may lead to higher pollution potential in marls soils since th ese appear to sorb pesticides less compared to the rock-plowed soils. Besides, the water table in marl soils is very shallow.

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101 Table 5-1. Soil organic carbon content, a nd atrazine distribut ion coefficients (Kd) and organic carbon sorption coefficients (Koc) for carbonatic soils from Florida and Puerto Rico. pH Atrazine Soil Sample Type H20 0.01M CaCl2 Origin foc Kd Koc 7.44 6.94 L kg-1 Aguilita C 7.23 6.99 PR 0.048 2.878 60 Biscayne MC 7.43 7.18 FL 0.057 2.717 48 Biscayne 2 MC 7.30 7.19 FL 0.029 1.418 49 Cadjoe MC 7.35 7.18 FL 0.102 5.749 57 Chekika C 6.86 7.00 FL 0.020 1.244 61 Chekika 2 C 7.13 7.15 FL 0.041 3.389 83 Colinas C 7.44 7.26 PR 0.024 2.004 84 Key Vaca MC 8.34 8.16 FL 0.114 6.937 61 KeyWest 1 MC 8.12 7.69 FL 0.012 0.565 46 KeyWest 2 MC 7.73 7.48 FL 0.012 0.573 49 Krome 1 C 7.35 7.36 FL 0.015 1.190 80 Krome 2 C 7.33 7.16 FL 0.023 1.852 81 Legumnivitae 1 MC 7.42 7.28 FL 0.061 3.628 59 Legumnivitae 2 MC 7.52 7.36 FL 0.047 2.159 46 Pennsuco MC 7.40 7.30 FL 0.027 1.256 46 Perrine 1 MC 7.29 7.25 FL 0.029 1.088 37 Perrine 2 MC 7.47 7.33 FL 0.029 1.030 36 Perrine-Tamiami Assoc C 7.70 7.45 FL 0.041 4.339 105 Saddle Bunch 1 MC 7.57 7.42 FL 0.017 0.727 43 Saddle Bunch 2 MC 7.42 7.18 FL 0.081 3.371 42 S-Sebastian C 7.52 7.27 PR 0.022 1.364 61 Tuque C 7.54 7.25 PR 0.023 1.171 50 Yauco C 7.44 6.94 PR 0.031 1.593 51 Type: C = Carbonatic, MC = Ma rl carbonatic; Origin: FL = Fl orida, PR = Puerto Rico; foc= fraction of OC; Kd = Distribution coefficient; Koc = sorption coefficient normalized with OC.

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102 Table 5-2. Soil organic carbon c ontent, atrazine, diuron and amet ryn distribution coefficients (Kd) and sorption coefficients (Koc) for Oxisols from Uganda and Puerto Rico. pH Atrazine Ametryn Diuron Soil Sample Origin foc 1M KCl Kd Koc Kd Koc Kd Koc g kg-1 L kg-1 L kg-1 Bayamon PR 0.015 1.15 76 2.11 139 4.97 328 Bayamon 2 PR 0.018 1.76 100 4.00 228 5.83 333 Fiduga 1 UG 0.018 5.80 3.22 181 8.56 481 22.30 1253 Fiduga 2 UG 0.014 7.31 1.97 139 4.47 316 10.88 770 Fiduga 3 UG 0.016 7.06 2.09 133 3.83 245 14.20 908 Fiduga Pooled UG 0.012 2.45 213 3.84 333 14.79 1282 Hima 1 UG 0.038 6.98 3.78 100 6.37 168 29.16 768 Hima 2 UG 0.061 6.98 8.08 132 12.26 200 59.32 969 Hima 3 UG 0.043 6.99 5.13 121 7.87 185 35.57 837 Hima Lime UG 0.007 7.57 2.55 388 6.39 973 7.83 1192 Hima Pooled UG 0.026 2.92 114 4.64 182 17.66 691 Kakira 1 UG 0.024 5.21 4.58 194 11.12 471 32.95 1396 Kakira 2 UG 0.029 4.48 6.37 219 22.38 771 48.45 1669 Kakira 3 UG 0.025 5.84 3.42 136 15.51 618 20.23 806 Kakira Pooled UG 0.028 4.87 174 11.47 409 29.65 1058 Kasaku 1 UG 0.027 3.11 115 13.32 491 19.43 717 Kasaku 2 UG 0.030 4.68 158 15.22 516 35.02 1186 Kasaku 3 UG 0.027 4.26 157 11.14 410 15.40 567 Kasaku 4 UG 0.026 3.79 146 14.80 568 19.32 742 MK Flora 1 UG 0.026 4.58 6.60 250 18.64 706 39.79 1508 MK Flora 2 UG 0.021 4.20 3.40 165 11.48 556 16.43 796 MK Flora 3 UG 0.027 4.53 11.49 424 29.76 1097 56.30 2076 MK Flora 4 UG 0.023 4.95 6.40 281 20.54 903 36.88 1621 MK Flora Pooled UG 0.024 7.57 317 22.59 945 33.37 1397 Muhookya 1 UG 0.007 6.93 0.64 94 1.90 278 2.38 348 Muhookya 2 UG 0.027 7.00 3.04 113 5.07 189 15.67 585 Muhookya 3 UG 0.003 6.99 0.46 157 1.76 599 1.59 541 Muhookya Pooled UG 0.008 2.81 367 2.22 290 5.63 736 Rubaabo Sediment UG 0.015 2.39 164 4.71 323 16.99 1165 Scoul Lugazi 1 UG 0.025 5.66 222 23.65 930 38.90 1529 Scoul Lugazi 2 UG 0.024 4.59 190 22.95 947 32.73 1351 Scoul Lugazi 3 UG 0.030 6.84 231 21.53 726 55.90 1885 Scoul Lugazi 4 UG 0.034 8.60 250 31.60 918 49.45 1437 Scoul Pooled UG 0.025 6.36 254 14.87 593 28.94 1154 Wagagai 1 UG 0.010 4.12 0.66 67 4.63 468 2.44 247 Wagagai 2 UG 0.010 3.97 0.60 61 5.43 548 2.51 253 Wagagai 3 UG 0.018 4.02 1.50 85 8.38 476 6.01 342 Wagagai Pooled UG 0.009 1.13 128 2.55 289 4.87 552 Type: Oxisols; Origin: PR = Puerto Rico, UG = Uganda. ** The names for Oxisols from Uganda are not series names. They indicate site name where they were collected.

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103 Table 5-3. Ametryn and diuron de gradation and sorption coefficien ts for carbonatic soils from Florida and Puerto Rico. Ametryn Diuron Soil Sample Type OriginKd Kocc Kd Koc g kg-1 L kg-1 Aguilita C PR 6.23 130 12.53 261 Biscayne MC FL 6.59 116 12.50 220 Biscayne 2 MC FL 3.00 103 5.92 204 Cudjoe MC FL 10.71 106 25.89 255 Chekika C FL 3.60 175 5.99 292 Chekika 2 C FL 6.94 169 18.39 448 Colinas C PR 3.54 148 9.61 403 Keyvaca MC FL 13.78 121 29.83 262 KeyWest 1 MC FL 1.38 113 1.86 152 KeyWest 2 MC FL 1.84 157 1.90 162 Krome 1 C FL 3.18 213 6.50 436 Krome 2 C FL 4.12 181 10.58 463 Lignumvitae 1 MC FL 8.03 131 15.37 251 Lignumvitae 2 MC FL 4.83 103 7.90 168 Pennsuco MC FL 2.96 108 5.92 216 Perrine 1 MC FL 2.54 87 4.89 167 Perrine 2 MC FL 2.75 95 4.64 161 Perrine-Tamiami assoc C FL 10.22 247 20.57 496 Saddlebunch 1 MC FL 1.62 95 2.59 152 Saddlebunch 2 MC FL 4.84 60 15.22 189 San Sebastian C PR 3.21 143 5.08 226 Tuque C PR 2.49 106 3.64 155 Yauco C PR 3.01 97 6.42 207 Type: C = Carbonatic, MC = Marl carbonatic; Origin: FL = Florida, PR = Puerto Rico; foc = fraction of OM; Kd = Distribution coefficient; Koc = sorption coefficient normalized with organic carbon; t1/2 = Half life.

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104 Table 5-4. Soil organic matter content, and atrazi ne distribution coeffici ents and organic carbon sorption coefficients for Histosols from Florida. pH Atrazine Ametryn Diuron Soil Sample foc H20 0.01M CaCl2 Kd Koc Kd Koc Kd Koc L kg-1 L kg-1 L kg-1 Dania 0-6" 0.43 6.08 5.94 73.22 171 184.44 430 421.32 982 Dania 6-12" 0.53 5.89 5.72 80.24 150 251.84 472 486.15 911 Islamorada 0.39 6.57 6.65 27.88 72 60.71 157 105.85 273 Lauderhill 1 0.29 7.05 7.06 30.10 105 65.07 226 156.50 545 Lauderhill 2 0.21 7.30 7.22 17.13 82 36.36 173 82.02 391 Lauderhill 3 0.23 7.18 7.18 24.35 107 48.84 215 123.38 543 Matecumbe 1 0.32 7.10 7.00 37.88 117 79.18 244 218.83 674 Matecumbe 2 0.20 7.07 6.97 15.84 80 40.75 206 111.51 564 Pahokee 0-6" 0.42 7.25 7.20 29.05 69 56.93 135 196.31 464 Pahokee 6-12" 0.47 6.30 6.27 58.00 123 122.57 260 360.54 765 Tamiami 1 0.40 6.39 6.30 38.66 97 87.10 217 194.43 485 Tamiami 2 0.2 6.63 6.65 14.57 74 31.05 157 56.46 285 Tamiami 3 0.40 7.10 7.20 57.39 144 110.02 277 262.07 660 Torry 1 (0-6") 0.13 6.57 6.65 15.91 125 30.78 241 65.03 509 Torry 2 (6-12") 0.10 6.96 6.86 13.37 139 24.73 257 53.49 556 Type: Histosols, Origin: Florida; foc = fraction of organic carbon; Kd = Distribution coefficient; Koc = sorption coefficient normalized with organic carbon.

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105 Table 5-5. Soil organic matter content, and atrazi ne distribution coeffici ents and organic carbon sorption coefficients for Spodosols from Florida. pH Atrazine Ametryn Diuron Soil Sample foc H20 0.01M CaCl2 Kd Koc Kd Koc Kd Koc L kg-1 L kg-1 L kg-1 Bh-1 0.009 4.35 3.93 1.03 115 5.19 584 5.25 590 Bh-2 0.018 4.36 3.87 4.20 229 13.09 714 11.57 631 Bh-3 0.006 4.39 3.89 2.75 443 8.57 1383 7.12 1149 E 0.002 4.71 3.79 0.38 184 2.23 1068 1.16 555 Monteocha 1 0.053 4.12 3.57 19.88 374 124.48 2341 84.32 1586 Monteocha 2 0.011 4.11 3.32 10.20 913 56.79 5084 43.68 3910 Pomona 1 0.009 4.24 3.55 4.56 534 22.77 2666 14.33 1678 Pomona 2 0.023 3.86 3.16 19.08 823 90.19 3889 62.04 2675 Pomona 3 0.011 4.00 3.23 11.57 1035 60.62 5427 43.39 3885 Pomona 4 0.020 4.01 3.30 21.64 1060 142.06 6960 86.60 4243 Type: Spodosols, Origin: Alachua County Florida. Bh horizon depth 80-100 cm,

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106 Table 5-6. Diuron half-life and GUS scores in soils from Flor ida, Puerto Rico and Uganda. Soil Name Soil Origin % Moisture Content (Adjusted) Diuron Decay Constant (K) 1/day Diuron Half-life (t1/2) days Diuron GUS Carbonatic soils* Aguilita PR 37 0.0069 100 3.17 Biscayne FL 54 0.0026 267 4.02 Biscayne 2 FL 42 0.0043 161 3.73 Chekika 1 FL 21 0.009 77 2.89 Colinas PR 32 0.0045 154 3.05 Key Vaca FL 68 0.0153 45 2.62 KeyWest 2 FL 26 0.0029 239 4.26 Krome 1 FL 21 0.0058 119 2.83 Lignumvitae 1 FL 39 0.0058 119 3.32 Lignumvitae 2 FL 39 0.0029 239 4.22 Pennsuco FL 38 0.003 231 3.94 Perrine 1 FL 38 0.0067 103 3.58 Saddlebunch 1 FL 20 0.0022 315 4.55 Saddlebunch 2 FL 45 0.0026 267 4.18 San Sebastian PR 31 0.0024 289 4.05 Tuque PR 25 0.0037 187 4.11 Yauco PR 33 0.0059 117 3.49 Non carbonatic soils Histosols Islamorada FL 111 0.0004 1733 5.07 Lauderhill 1 FL 77 0.0037 187 2.87 Matecumbe 1 FL 102 0.0041 169 2.61 Tamiami 1 FL 106 0.0042 165 2.91 Tiburones PR 35 0.0024 289 3.67 Spodosols Monteocha 1 FL 21 0.0046 151 1.74 Monteocha 2 FL 20 0.005 139 0.87 Pomona 1 FL 20 0.0047 147 1.68 Pomona 2 FL 20 0.0033 210 1.33 Pomona 3 FL 16 0.0033 210 0.95 Pomona 4 FL 22 0.0048 144 0.80 Oxisols Bayamon 1 FL 22 0.0031 224 3.49 Bayamon 2 PR 22 0.0198 35 2.28 Fiduga Pooled UG 22 0.0047 147 1.93 Hima Pooled UG 31 0.0036 193 2.65 Kakira Pooled UG 29 0.0041 169 2.17 MK Flora Pooled UG 23 0.0047 147 1.85 Muhookya Pooled UG 36 0.0031 224 2.66 Scoul Pooled UG 23 0.0042 165 2.08 Wagagai Pooled UG 21 0.0042 165 2.79 Other San Anton PR 24 0.0021 330 3.29 GUS = groundwater ubiquity score; FL = Florida; PR = Puerto Rico; UG = Uganda; = Mollisol; = Carbonatic refers to soil mi neralogy not taxonomic classification.

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107 Table 5-7. Ametryn half life and GUS scores in soils from Florida, and Puerto Rico. Soil Name Soil Origin %Moisture Content (Adjusted) Ametrytn Decay Constant (k 1/day) Ametryn Half-life (t1/2) (days) Ametryn GUS Carbonatic soils* Aguilita PR 37 0.0173 40 3.02 Biscayne FL 54 0.0173 40 3.10 Biscayne 2 FL 42 0.0462 15 2.34 Colinas PR 32 0.0222 31 2.73 Cudjoe FL 0.0374 19 2.53 Chekika 1 FL 21 0.0465 15 2.06 Key Vaca FL 68 0.0286 24 2.65 KeyWest 1 FL 27 0.0027 248 4.67 KeyWest 2 FL 26 0.0083 83 3.46 Krome 1 FL 21 0.0241 29 2.44 Lignumvitae 1 FL 39 0.0221 31 2.81 Lignumvitae 2 FL 39 0.0126 55 3.46 Pennsuco FL 38 0.0246 28 2.85 Perrine 1 FL 38 0.0363 19 2.64 Perrine-Tamiami assoc FL 0.0077 90 3.14 Saddlebunch 1 FL 20 0.014 47 3.38 Saddlebunch 2 FL 45 0.0157 44 3.65 San Sebastian PR 31 0.0159 44 3.03 Tuque PR 25 0.0117 29 2.89 Yauco PR 33 0.0237 29 2.95 Spodosols Monteocha 1 FL 21 0.0038 182 1.43 Monteocha 2 FL 20 0.0118 59 0.52 Pomona 1 FL 20 0.0121 58 1.01 Pomona 2 FL 20 0.0047 151 0.89 Pomona 3 FL 16 0.008 87 0.51 Pomona 4 FL 22 0.0121 56 0.28 GUS = groundwater ubiquity score; FL = Florida; = Carbonatic refers to soil mineralogy not taxonomic classification.

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108 y = 156.5x R2 = 0.9963 0 20 40 60 80 100 120 140 160 180 200 00 20 40 60 811 2 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure 5-1. Diuron sorpti on isotherm of Lauderhill series (Histosol) from South Florida.

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109 y = 57x R2 = 0.8574 y = 510x R2 = 0.4617 y = 117x R2 = 0.735 y = 164x R2 = 0.3523 0 10 20 30 40 50 60 70 80 90 0.0000.1000.2000.3000.4000.5000.600 Walkley-Black FocAtrazine Kd Carbonatic Histosols Oxisols Spodosols Figure 5-2. Correlation of atrazi ne distribution coefficients (Kd) with the fraction of organic carbon for different soil series.

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110 A Carbonatic Koc = 57xFoc R2 = 0.8574 0 1 2 3 4 5 6 7 8 0.0000.0200.0400.0600.0800.1000.120K d D Spodosols Koc = 510xFoc R2 = 0.4617 0 5 10 15 20 25 30 0.0000.0100.0200.0300.0400.0500.060 Walkley-Black FocK d C Oxisols Koc = 174xFoc R2 = 0.464 0 2 4 6 8 10 12 14 0.0000.0100.0200.0300.0400.0500.0600.070K d B Histosols Koc = 117xFoc R2 = 0.735 0 10 20 30 40 50 60 70 80 90 0.0000.1000.2000.3000.4000.5000.600K d Figure 5-3. Correlati on of atrazine Kd with fraction of organic car bon for A) For carbonatic soils, B) For Histosols, C) For Oxiosols and D) For Spodosols. Slopes represent average Koc.

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111 A Carbonatic Koc = 116x foc R2 = 0.7339 0 2 4 6 8 10 12 14 16 0.0000.0200.0400.0600.0800.1000.120 Walkley-Black FocKd B Histosols Koc = 278x foc R2 = 0.615 0 50 100 150 200 250 300 0.0000.1000.2000.3000.4000.5000.600 Walkley-Black FocKd D Spodosols Koc = 2950 x foc R2 = 0.505 0 20 40 60 80 100 120 140 160 180 0.0000.0100.0200.0300.0400.0500.060 Walkley-Black FocKd C Oxisols Koc= 483 x foc R2 = 0.2122 0 5 10 15 20 25 30 35 0.0000.0100.0200.0300.0400.0500.0600.070 Walkley-Black FocKd Figure 5-4. Correla tion of ametryn Kd with fraction of organic car bon. A) For carbonatic soils. B) For Histosols. C) For Ox iosols. D) For Spodosols.

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112 A Carbonatic Koc = 255xFoc R2 = 0.7887 0 5 10 15 20 25 30 35 0.0000.0200.0400.0600.0800.1000.120K d D Spodosols Koc = 1992xFoc R2 = 0.5324 0 20 40 60 80 100 120 0.0000.0100.0200.0300.0400.0500.060 Walkley-Black FocK d C Oxisols Koc = 1075xFoc R2 = 0.6088 0 10 20 30 40 50 60 70 0.0000.0100.0200.0300.0400.0500.0600.070K d B Histosols Koc = 650xFoc R2 = 0.6969 0 100 200 300 400 500 600 0.0000.1000.2000.3000.4000.5000.600K d Figure 5-5. Correla tion of diuron Kd with fraction of organic carbon. A) For carbonatic soils. B) For Histosols. C) For Oxiosols. D) For Spodosols.

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113 0 500 1000 1500 2000 2500 3000 3500 4000 4500 Ametryn 0 500 1000 1500 2000 2500 3000 3500 Diuron 0 100 200 300 400 500 600 700 800Avera g e Koc Marl Non marl carbonatic Histosols Oxisols Spodosols Atrazine Figure 5-6. Graphical repr esentation of average Koc values for the different soil types analyzed. Error bars indicate 95 % confidence interval.

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114 B Ln(Mt) = -0.0059xt + 1.4372 R2 = 0.98120.4 0.6 0.8 1.0 1.2 1.4 1.6 020406080100120140160 Time (Days)Ln(Mt) A Mt = 4.2089e-0.0059xtR2 = 0.98121.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 020406080100120140160 Time (Days)Mt (mg/kg)Aa Figure 5-7. Degradation of diur on in Lignumvitae series from Florida Keys, South Florida.

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115 0.00 0.50 1.00 1.50 2.00 2.50 3.00 020406080100120140160Time (Days)Ln (Mt) Biscayne-1 Saddlebunch-1 Saddlebunch-2 Lignumvitae Figure 5-8. Selected degradation curves for di uron in carbonatic soils from South Florida.

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116 0 0.00.40.81.21.62.02.42.83.23.64.04.44.8 GUS Medium Leaching Potential High Leaching Potentail Oxisols Histosols Carbonatic Marl Spodosols 2.8 1.8 low leaching Potentia l Puerto Rico soils Figure 5-9. Groundwater ubiquity score classification for diuron in different soil types.

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117 0 0.00.51.01.52.02.53.03.54.04.55.0 GUS Medium Leaching Potential High Leaching Potentail Carbonatic Marl Spodosols 2.8 1.8 low leaching Potentia l Figure 5-10. Groundwater ubiquity score classification for am etryn in carbonatic soils and Spodosols.

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118 CHAPTER 6 CROSS POLARIZED MAGIC ANGLE SPINNING 13CARBON NUCLEAR MAGNETIC RESONANCE AND STABLE IS OTOPE CHARACTERIZATI ON OF ORGANIC MATTER IN CARBONATIC AND NON-CARBONATIC SOILS OF SOUTH FLORIDA, PUERTO RICO AND OXISOLS FROM UGANDA Introduction Organic matter (OM) is usually present in sma ll amounts in mineral soils, but contributes a great deal to soil properties. Its influence to soil color, water re tention capacity, soil aggregation, sorption of hydrophobic organic chemicals (HOCs) and a sour ce of energy for microbial processes is well known. However, due to its comp lexity, OM poses challe nges to even the most recent advanced analytical techniques. Thermo an alysis using Thermogravimetric analysis (TG) provides an accurate determination of OM in soils that do not constitute minerals that decompose with the same temperature (T) range (150-550 oC). Ku erik et al., 2006 desc ribed three onset steps for the thermo-oxidation of OM during thermo analysis. The lower T range constituting the aliphatic, polar groups and simple aromatic groups and another step 200-300 oC resulting from decomposition of polyaromatic mo ieties. The third onset (>400 oC) is ascribed to polyheterocyclic molecules. The use of CP-MAS 13C NMR to whole soil samples can provide more insight on the functionality of the OM pres ent in the soils. Previous studies (Dai et al., 2001) have reported success in using 13C CP-MAS to elucidate functional moieties of OM in soils. The aim of this study was to characterize OM and to assess the accuracy of the methods used for OM and/or OC characterization. Prev ious studies (Maheswari and Ramesh, 2007; Cox et al., 1998; Nkedi-Kizza et al ., 1983) have reported a positiv e correlation between sorption distribution coefficients with organic carbon. Based on the re lationship, the organic carbon parameter is used in normalizing so rption distribution coefficients (Kd) to provide a unique sorption coefficient (Koc). Some studies (Oliver et al., 2005; Spark and Swift, 2002) however, did

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119 not find a relationship between so rption of atrazine, imidaclopid, thiacloprid, and diuron with organic carbon, suggesting that organic carbon may not adequate ly account for sorption of HOCs in all soils. Walkley-Black has been used fo r many years for analysis of soil organic carbon however its generation of large amounts of toxic wastes ca lls for development of more environmentally safe methods for OC determinati on. In this study we report use of TG methods for determination of OM in carbonatic soils. Materials and Methods Soils were collected from South Florida Dade county and Monroe c ounty and Puerto Rico. The Oxisols were collected from Uganda, Ea st Africa. OM present in these soils was characterized using CP-MAS 13C NMR and stable isotope analysis. The detailed methods description for stable isotope and CP-MAS 13C NMR analysis are provided in Chapter 3 of this manuscript. Results and Discussion Stable Isotope Determination Stable isotope determinati on indicates the fractionation of carbon during photosynthesis for plants. The pathway for car bon dioxide intake leaves a 13C signature that can be investigated using stable isotope analysis. Plants that follow C3 fractionation have 13C ranging from -22 to -32 (average -27 ) Most plants, algae and forest ecosys tems are C3 plants. C4 plants are mainly found in hot arid environm ent so C4 plants are adapted to more efficient water use. These constitute plants such as sugar cane, corn, sorghum, and millet (Ehleringer and Pearcy, 1983). Plants that follow C4 type photosynthesis pathways have 13C ranging from -12 to -17 (average -13 ). Stable isotopes can be useful in fingerprinting the nature of plant of plants and how they fractionate carbon. The approach is better applicable to terr estrial versus marine plants since these tend to have different sources of carbon. Howe ver, in a garden environment

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120 this may be fuzzy determination since both C3 and C4 plants may co -exist in the same environment. In this study, the 13 signatures were consistent with what we expected but the data did not provide trends that can allow prediction of sorption ca pacities of hydrophobic organic compounds based on 13C values and Kd values. The data in Figur e 6-1 show no correlation between sorption and 13C values. The 13C values ranged between -15. 3 and -23.3 It is evident that the 13C signatures are intermediary (Figure 6-2) indicating that both C3 and C4 plants may be influencing the OM present in car bonatic soils. Smith a nd Epstein (1970) observed similar 13C signatures for marine and fresh water alga e ranging from -12.3 to -22.7 In their study they observed that highe r plants and lower vascular plants had values lower than -23 Matecumbe (-25.95 ) and Lauderhill (-25.72 ) showed 13C signature that indicated that C3 plants are predominant in these soils thus influencing the nature of OM in Histosols. 13Carbon Cross Polarized Magic Angle Spinning Nuclear Magnetic Resonance Analysis The solid state NMR spectra in Appendix B show the functional similarities and differences between soils of di fferent origins. Carbonatic soils from South Florida had low aromaticity compared to Organic soils from Sout h Florida and Oxisols from Uganda. This can be seen in the spectral region of 105-160 ppm. The quantitative errors in the NMR analysis were minimized by performing variable contact time analysis (Hatcher et al., 1993). Even then, NMR results are semi-quantitative. This is due to the difficulty in cross polarization of carbons remote to protons hence causing errors in quantification. The spectra obtained in this study (Figure 6-4) are similar to those obtained for algae grown in the laboratory (Figure 6-3), which confirms that the major primary producer for OM in the marl soils of South Florida is algae. It is likely that the humification of algae produces less complex moieties of OM with low HOCs sorptive capacities. In this study, a correl ation was observed between sorption capacity (Koc) of HOCs and aromatic C content (110-160 ppm) of OM (Figure 6-7 and 6-8) Other studies (Xing, 1997; Gauthier et al.,

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121 1987) found a similar relationship. A nega tive relation was observed between Koc and alkyl C content (0-45 ppm). The aromatic C/alkyl C ratio (110-160 ppm/ 0-45 ppm) provided a stronger relationship with Koc (Figures 6-5, 6-6 and 6-8). The aroma tic C/ alkyl C ratio will be referred to as the aromatic C index. This index was not related with Koc in Spodosols. The sorption of HOCs in Spodosols is probably controlled by other components other than aromatic C. The poor correlation obtained by regressing Koc with the aromatic C indices for atrazine, ametryn and diuron seems to confirm that OC content alone is insufficient to explain the sorption of HOCs as earlier observed by correlating Koc with foc. The OC content cut-off of 1 % for mineral components controlling sorption may become impo rtant for Spodosols, however the magnitude of mineral material to influence sorption of HOCs in Spodosols would accordingly be magnitudes higher than SOC infl uence since the sorption capaciti es were about ten times or higher than for carbonatic soils The negative correl ation between sorpti on capacities of HOC with alky-C probably suggests that partitioning to the alkyl C plays a minor role in adsorption of HOCs in these soils studied. The high sorp tion capacity of HOCs exhibited by Oxisols and Histosols compared to carbonatic so ils confirms that sorption is strongly influenced by aromatic C content of OM. Haumaier and Zech (1995) suggested that the signal observed at 130 ppm is likely derived from black carbon a nd not from humification of nativ e plant material. Since we do not know the history of burning in the soils that were sampled (except for some Oxisols from Uganda), we cannot conclude that it is black carbon influencing the sorption properties of the soils. Already some researchers (Pignatello et al., 2006; Cornelissen, 2005) have suggested greater sorption capacity of HOCs by black carbon. The high surf ace area of black could be the major factor in the observed enhanced sorption capacities. Some of the Oxisols that were analyzed in this study were obtai ned from sugar cane fields in Uganda and burning is used for

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122 harvesting of sugar canes. Nevertheless other Oxis ols that were obtained from other areas in Uganda where no burning was used as a met hod of harvest indicated high sorption capacity suggesting that it is rather OM from higher plants th at contributes to gr eater sorption capacity. By comparing the spectra in Appendix B for diff erent soils, aromatic C content for Lauderhill and Islamorada (Figure B-5) was lower than that for Spodosols (F igure B-4) and Oxisols (Figure B-6). Despite high OM content, Islamorada whic h is a Histosol, showed low sorption potential suggesting that the type of OM in this soil se ries does not possess high affinity for HOCs which seems to confirm that aromatic C influences sorption of HOCs. An overlay of the Bloch Decay and 13C CP-MAS (not shown) indi cated a discrimination of the aromatic signal by CP-MAS. Bloch Decay on the other seemed to discriminate Oxy-Alkyl, Methoxyl, and the alkyl-C region. Although CP-MAS generally prov ided better signal to noise spectra compared to Bloch Decay, direct polarization at a pulse of 60 s gave better signal compared to direct polarization at 10 s. Due to excessive signal to noise level in the Bloch Decay analysis, all the other samp les were analyzed using 13C CP-MAS. Conclusions Stable isotope studies results were consistent with the expected carbon sources but no relationship was found with sorpti on. The NMR studies showed diffe rences in functionality of OM present in carbonatic soils compared to th e non-carbonatic soils. Fundemental differences were observed in the aromatic carbon chemical sh ifts. This suggests that SOM aromaticity plays a major role in HOCs sorption. A strong relations hip was observed between arom C/alkyl C ratio (aromatic C index) and Koc. However, aromatic C indices for atrazine, ametryn and diuron were not related with Koc in Spodosols suggesting that other components ot her than OC may be controlling sorption of HOCs in Spodosols.

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123 The 13C CP-MAS NMR spectra indicate fundament al differences in the aromatic carbon chemical shifts for carbonatic and non-carbonatic soils. Carbonatic soils exhibited low aromatic C content compared to Oxisols and Histosols. The results indicate the usefulness of CP-MAS NMR in elucidating the nature and functionalities of OM in soils.

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124 Table 6-1. Physicochemical properties of th e soils that were used for stable isotope determination. Duplicate samples were analyzed. Soil name Type Ametr Koc 13C 13C Av 13C SD Hima 3 Gelisol 185 -12.08 -12.40 -12.24 0.23 Tuque carbonatic 106 -15.14 -15.47 -15.31 0.23 S.Sebastian carbonatic 143 -15.73 -16.14 -15.93 0.29 S. Anton carbonatic 199 -16.90 -17.06 -16.98 0.11 Colinas carbonatic 148 -18.29 -18.17 -18.23 0.08 Bayamon 1 Oxisol 173 -18.84 -19.28 -19.06 0.31 Biscayne 1 carbonatic 118 -18.85 -19.61 -19.23 0.54 Perrine 1 carbonatic 91 -20.53 -20.60 -20.57 0.05 Chekika 1 carbonatic 175 -21.17 -21.02 -21.10 0.11 Aguilita carbonatic 130 -20.99 -21.24 -21.11 0.17 Saddle Bunch 1 carbonatic 95 -20.81 -22.39 -21.60 1.12 Krome 1 carbonatic 213 -21.69 -21.67 -21.68 0.01 Pennsuco carbonatic 108 -22.11 -21.98 -22.05 0.09 Yauco carbonatic 97 22.15 -22.08 -22.11 0.05 Perine 2 carbonatic 95 -22.35 -22.41 -22.38 0.04 Krome 2 carbonatic 181 -22.56 -23.09 -22.83 0.37 Cadjoe carbonatic 106 -24.20 -22.54 -23.37 1.17 Catano 164 -23.74 -23.73 -23.74 0.01 Lauderhill 1 Histosol 226 -25.77 -25.67 -25.72 0.07 Matecumbe 1 Histosol 272 -25.97 -25.93 -25.95 0.03

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125 y = -2.6989x + 95.763 R2 = 0.0335 0 50 100 150 200 250 300 -28.00 -26.00 -24.00 -22.00 -20.00 -18.00 -16.00 -14.00 -12.00 -10.00 -8.00 13C signaturesAmetryn Koc Figure 6-1. Relations hip between the Koc values of ametryn and corresponding 13C values for carbonatic and non-carbonatic soils.

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126 -28.00 -26.00 -24.00 -22.00 -20.00 -18.00 -16.00 -14.00 -12.00 -10.00 13C/12CSoil classification Carbonatic PR Carbonatic FL Histosols FL Non-Carbonatic PR C4 plants IntermediateC3 plants Figure 6-2. Di stribution of 13C in different soil classifications.

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127 Chemical shift (ppm) Figure 6-3. 13Carbon Cross Polarized Magic Angle Sp inning Nuclear Magenetic Resonance spectra for Algae grown in our laboratory. Biscayne MarlChemical shift (ppm) Figure 6-4. 13Carbon Cross Polarized Magic Angle Sp inning Nuclear Magenetic Resonance spectra for Biscayne a typi cal Marl soil from Dade County, South Florida.

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128 y = 646.91x + 19.135 R2 = 0.8335 0 500 1000 1500 2000 0.000.501.001.502.002.50 Arom C/Alkyl CKoc Figure 6-5. Correlation between ar omatic C/alkyl C with diuron Koc.

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129 y = 327.52x 5.6968 R2 = 0.7872 0 200 400 600 800 1000 1200 0.00 0.50 1.00 1.50 2.00 2.50 Arom C/Alkyl CKoc Figure 6-6. Correlation between arom atic C/alkyl C with ametryn Koc.

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130 Diuron y = 19.73x + 89.483 R2 = 0.3608 Ametryn y = 15.332x 46.145 R2 = 0.4799 0 200 400 600 800 1000 1200 1400 0.005.0010.0015.0020.0025.0030.0035.0040.0045.00 Arom C contentKoc Diuron Ametryn Figure 6-7. Correlation between arom atic C with ametryn and diuron Koc.

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131 Atrazine y = 8.4729x 45.933 R2 = 0.6996 0 50 100 150 200 250 300 350 400 450 0.005.0010.0015.0020.0025.0030.0035.0040.0045.00 Arom CAtraz Koc Figure 6-8. Correlation between aromatic C with atrazine Koc.

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132 Atrazine y = 143.98x + 3.7593 R2 = 0.7928 0 50 100 150 200 250 300 350 400 450 0.000.501.001.502.002.503.00 Arom C/ Alkyl CAtraz Koc Figure 6-8. Correlation between arom atic C/alky C with atrazine Koc.

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133 CHAPTER 7 CONCLUSIONS AND RECOMMENDATIONS Conclusions The results of this study indicate that OC c ontent of OM differs sign ificantly between soils of different hydrologic and vegeta tive settings, and that WLOI is not a reliable measure of OM, even for organic soils, unless weight loss below 200 oC is taken into account. Carbonatic soils were found to adsorb pest icides less compared to non-carbonatic soils. Marl soils adsorbed pesticides even less compared to the outcrop carbonatic soils. The NMR data indicate that Algae is the primary producer in th e marl soils, implying that its contribution to OC aromaticity which appeared to control the sorp tion is limited. The lack of aromatic C in carbonatic soils OM probably leads to the low sorption capacities exhibited by marl and rock outcrop carbonatic soils from Sout h Florida and Puerto Rico. The linear relationship obtained by normalizing the sorption coefficients (Kd) with fraction of OC ( foc) indicates that OC controls the adosption of HOCs in carbonatic soils. However, th e data vairiability accross different soil types suggest that quality of OM is equally important criteria for so rption. The degradation studies indicted that diuron is relativel y persistent. Using the modified degradation equation rids the analysis of uncertainties crea ted by initial concentration (Mo), given that the recoveries in soils were lower than would be expected in solutio n chemistry. The GUS score also showed higher potential for the chemical to leach to groundwat er. Non-marl carbonatic soils generally showed medium potential to leach and the GUS scores fo r marl soils also shifted to lower leaching potential values. This may indicate lower leach ing potential for ametryn compared to diuron. The results of this study may be useful in designing management strategies and farming practices, aimed at protecting the aquifers that underlie the car bonatic soils. These strategies may include revision of application rates for pesticides applied to crops grown on carbonatic soils,

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134 adding soil amendments and long term change of the nature of OM by altering the organic carbon primary producers. Recommendations To avoid contamination of the water resource in Puerto Rico and the shallow Biscayne aquifer in South Florida wher e carbonatic soils are widely used for agriculture, it is recommended that application rates be adjusted to cater for the low sorption capacity of the carbonatic soils. Amendment of th e carbonatic soils with material with high sorptive properties may provide long term remedies to the leaching potential of HOCs hence protecting the shallow South Florida aquifers of South Florida. Since chemical decompose leaving behind me tabolite which may have longer half lives than the parent compounds and sometime even mo re toxic, characterizing the behavior of the metabolite in these agriculturally important soils is essential.

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135 APPENDIX A SELECTED PESTICIDE SORPTION ISOTHERMS y = 2.7636x R2 = 0.9943 0 2 4 6 8 10 12 14 16 18 0123456 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/k g Figure A-1. Sorption isotherm for ametryn in Biscayne from Miami Dade Florida (marlcarbonatic). Kd = 30 R2 = 0.9937 0 20 40 60 80 100 120 140 160 180 012345 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-2. Sorption isotherm for ametryn in Lauderhill from Miami Dade, South Florida (Histosol).

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136 Kd = 4.6 R2 = 0.9365 0 5 10 15 20 25 012345 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-3. Sorption isotherm fo r ametryn in Pomona from Ast on Cary, Alachua County Florida (Spodosol). Kd = 4.6 R2 = 0.9694 0 5 10 15 20 25 012345 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-4. Sorption isotherm fo r atrazine in a Kakira soil fr om Jinja, Uganda (Oxisol).

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137 Kd = 6.59 R2 = 0.9746 0 5 10 15 20 25 30 35 012345 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-5. Sorption isotherm for amet ryn in Biscayne (marl-carbonatic). Kd = 65 R2 = 0.9585 0 50 100 150 200 250 300 00.511.522.533.5 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-6. Sorption isotherm for ametryn in Lauderhill from Miami Dade, South Florida (Histosol).

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138 Kd = 23 R2 = 0.9466 0 10 20 30 40 50 60 00 511 522 5 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-7. Sorption isotherm fo r ametryn in Pomona from Ast on Cary, Alachua County Florida (Spodosol). Kd = 11 R2 = 0.9608 0 10 20 30 40 50 60 00.511.522.533.544.55 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-8. Sorption isotherm fo r ametryn in a Kakira soil from Jinja, Uganda (Oxisol).

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139 Kd = 12 R2 = 0.9667 0 5 10 15 20 25 30 35 40 00.511.522.53 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-9. Sorption isotherm for diuron in Biscayne (marl-carbonatic). Kd = 156 R2 = 0.9963 0 20 40 60 80 100 120 140 160 180 200 0 0.2 0.4 0.6 0.8 1 1.2 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-10. Sorption isotherm for diuron in Lauderhill from Miami Dade, South Florida (Histosol).

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140 Kd = 14 R2 = 0.9579 0 5 10 15 20 25 30 35 40 45 0 0.5 1 1.5 2 2.5 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-11. Sorption isotherm for diuron in Po mona from Aston Cary, Alachua County Florida (Spodosol). Kd = 33 R2 = 0.9592 0 10 20 30 40 50 60 0 0.2 0.4 0.6 0.8 1 1.2 1.4 SOLUTION CONC., (mg/L)ADSORBED CONC., (mg/kg Figure A-12. Sorption isotherm for diuron in a Kakira soil fr om Jinja, Uganda (Oxisol).

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141 APPENDIX B SELECTED SOIL ORGANIC MATTER 13CARBON CROSS POLARIZED MAGIC ANGLE SPINNING NUCLEAR MAGNETIC RESONANCE SPECTRA The selected spectra in the figures below for 13C cross-polarization magic angle spinning nuclear magnetic resonance (CP-MAS NMR) show the fundamental differences and similarities in the chemical shifts of the functionalities of OM from soil of different geographical origins, series and vegetation cover. Two sample spectra for each soil group were selected except for algae which was grown in our laboratory for pur poses of confirming our previous observations for carbonatic soils NMR chemical shift patterns. The spectra were done at a spin of 13 KHz, 1.5 ms contact time, 1 s recycle time and spectra were processed with a 100 Hz line broadening and baseline correction. The scale fo r the chemical shift on the x-axis of the NMR spectra is in ppm. ppm ppm Figure B-1. (L-R) Nuclear magnetic resonanc e spectra for Laboratory grown Algae and carbonatic soil (Florida Keys)

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142 ppm Perrine Marl FLppm Figure B-2. Nuclear magnetic re sonance spectra for carbonatic so ils from Dade County, South Florida. ppm Yauco PRppm Figure B-3. Nuclear magnetic resonance spec tra for carbonatic soils from Puerto Rico.

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143 Pomona FL ppm ppm Figure B-4. Nuclear magnetic resonance spectr a for Spodosols from Al achua County Florida. Lauderhill FLppm ppm Figure B-5. Nuclear magnetic reso nance spectra for Histosols from Miami Dade, Florida (L) and Monroe County, Key West, Florida (R).

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144 ppm ppm Figure B-6. Nuclear magnetic resonan ce spectra for Oxisols from Uganda.

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156 BIOGRAPHICAL SKETCH Gabriel Nuffield Kasozi was bor n in 1969 at Rubaga (Kam pala, Uganda). He was born to Mrs. Noelina and Mr. Lawrence Lubega of Masa jja Kyadondo. He received his Bachelor of Science with Education, majori ng in chemistry from Makerere University Kampala in 1992. He received his Master of Science, majoring in Ch emistry from Makerere University Kampala in 2002. He was awarded a PhD in December 2007.