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Performance, Microbial Ecology, and Life Cycle Assessment of an Activated Carbon Biofilter Used for Methanol Removal

Permanent Link: http://ufdc.ufl.edu/UFE0021573/00001

Material Information

Title: Performance, Microbial Ecology, and Life Cycle Assessment of an Activated Carbon Biofilter Used for Methanol Removal
Physical Description: 1 online resource (123 p.)
Language: english
Creator: Babbitt, Callie Whitfield
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: bacterial, biofilter, dgge, diversity, ecology, enrichment, hap, hvlc, lca, lci, methanol, methylotroph, microbial, paper, pcr, pulp
Environmental Engineering Sciences -- Dissertations, Academic -- UF
Genre: Environmental Engineering Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The forest products industry is responsible for producing valuable industrial chemicals, wood products, and consumer goods. However, processes involved in creating these materials at pulp, paper, and paperboard mills also generate hazardous air pollutants (HAPs), such as methanol, that are released during wood pulp production. With increasingly stringent regulations on methanol emissions, mills are continually seeking effective and cost efficient ways to control its release. Motivated by the need to study economical and environmentally friendly methanol control technologies, a bench-scale activated carbon biofiltration system was developed and evaluated for its ability to remove methanol from an artificially contaminated air stream. The biofilter contained a novel packing mixture of activated carbon, perlite, slow release nutrient pellets, and water retaining crystals, and showed excellent biofilm growth and close to 100% biological methanol removal, both with and without addition of an inoculum containing enriched methanol-degrading bacteria. Design of the biofilter using an inoculum enriched for methanol-degrading bacteria also facilitated characterization of biofilm samples from a pulp and paper mill on the basis of selecting a biofilter inoculum and optimizing growth and activity in mixed culture. Studies of enriched cultures from the biofilm samples showed higher bacterial community diversity and methanol removal when using nitrate as the nitrogen source for enrichment, rather than ammonium. Design and operation of this bench-scale system also enabled further investigation with microbial ecology and molecular techniques to characterize diversity of bacterial communities colonizing the biofilter over different points in time and under varied operational conditions. Amplification and separation of DNA from biofilter samples, using polymerase chain reaction (PCR) and denaturing gel gradient electrophoresis (DGGE), indicated that although bacterial diversity and abundance varied over the length of the biofilter, the populations rapidly formed a stable community that was maintained over the entire 138 days of operation and in variable operating conditions. Phylogenetic reconstruction of bands excised from DGGE gels indicated that the biofilter supported a diverse community of methanol-degrading bacteria. Finally, the design and operation of the bench-scale biofilter provided parameters for use in a life cycle assessment (LCA) that compared raw materials and energy required and emissions and environmental impacts produced by construction and operation of a proposed photocatalytic oxidation (PCO)-biofilter system, to those associated with treatment using a more traditional regenerative thermal oxidizer (RTO). LCA results indicated that environmental impacts associated with construction of a RTO far outweighed infrastructure requirements of the PCO-biofilter system. However, the operating impacts to global warming and human toxicity for the PCO-biofilter system were higher than for the RTO, because of the replacement requirements of packing for the PCO reactor and biofilter, as well as the electricity requirement to operate the PCO reactor.
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 Callie Whitfield Babbitt.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Lindner, Angela S.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021573:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021573/00001

Material Information

Title: Performance, Microbial Ecology, and Life Cycle Assessment of an Activated Carbon Biofilter Used for Methanol Removal
Physical Description: 1 online resource (123 p.)
Language: english
Creator: Babbitt, Callie Whitfield
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: bacterial, biofilter, dgge, diversity, ecology, enrichment, hap, hvlc, lca, lci, methanol, methylotroph, microbial, paper, pcr, pulp
Environmental Engineering Sciences -- Dissertations, Academic -- UF
Genre: Environmental Engineering Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The forest products industry is responsible for producing valuable industrial chemicals, wood products, and consumer goods. However, processes involved in creating these materials at pulp, paper, and paperboard mills also generate hazardous air pollutants (HAPs), such as methanol, that are released during wood pulp production. With increasingly stringent regulations on methanol emissions, mills are continually seeking effective and cost efficient ways to control its release. Motivated by the need to study economical and environmentally friendly methanol control technologies, a bench-scale activated carbon biofiltration system was developed and evaluated for its ability to remove methanol from an artificially contaminated air stream. The biofilter contained a novel packing mixture of activated carbon, perlite, slow release nutrient pellets, and water retaining crystals, and showed excellent biofilm growth and close to 100% biological methanol removal, both with and without addition of an inoculum containing enriched methanol-degrading bacteria. Design of the biofilter using an inoculum enriched for methanol-degrading bacteria also facilitated characterization of biofilm samples from a pulp and paper mill on the basis of selecting a biofilter inoculum and optimizing growth and activity in mixed culture. Studies of enriched cultures from the biofilm samples showed higher bacterial community diversity and methanol removal when using nitrate as the nitrogen source for enrichment, rather than ammonium. Design and operation of this bench-scale system also enabled further investigation with microbial ecology and molecular techniques to characterize diversity of bacterial communities colonizing the biofilter over different points in time and under varied operational conditions. Amplification and separation of DNA from biofilter samples, using polymerase chain reaction (PCR) and denaturing gel gradient electrophoresis (DGGE), indicated that although bacterial diversity and abundance varied over the length of the biofilter, the populations rapidly formed a stable community that was maintained over the entire 138 days of operation and in variable operating conditions. Phylogenetic reconstruction of bands excised from DGGE gels indicated that the biofilter supported a diverse community of methanol-degrading bacteria. Finally, the design and operation of the bench-scale biofilter provided parameters for use in a life cycle assessment (LCA) that compared raw materials and energy required and emissions and environmental impacts produced by construction and operation of a proposed photocatalytic oxidation (PCO)-biofilter system, to those associated with treatment using a more traditional regenerative thermal oxidizer (RTO). LCA results indicated that environmental impacts associated with construction of a RTO far outweighed infrastructure requirements of the PCO-biofilter system. However, the operating impacts to global warming and human toxicity for the PCO-biofilter system were higher than for the RTO, because of the replacement requirements of packing for the PCO reactor and biofilter, as well as the electricity requirement to operate the PCO reactor.
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 Callie Whitfield Babbitt.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Lindner, Angela S.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021573:00001


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PERFORMANCE, MICROBIAL ECOLOGY, AND LIFE CYCLE ASSESSMENT OF AN
ACTIVATED CARBON BIOFILTER FOR METHANOL REMOVAL

















By

CALLIE WHITFIELD BABBITT


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




























O 2007 Callie Whitfield Babbitt




























To my grandmother, Mary Lou Whitfield, who inspires my love of learning and appreciation
of the past; and to my daughter Nora Caroline Babbitt, who inspires me to do my part to create
a more sustainable world for future generations.









ACKNOWLEDGMENTS

I acknowledge and thank Dr. Angela S. Lindner, my supervisory committee chairperson,

for her time, hard work, leadership, and guidance. Her passion for teaching and lifelong learning

has been an inspiration to me, and her commitment to her students has made it possible for me to

attain the goal of completing my Ph.D. I thank my current and past committee members (Dr.

Ben Koopman, Dr. David Mazyck, Dr. Madeline Rasche, Dr. Spyros Svoronos, and Dr. Chang-

Yu Wu) for their direction, time, and support. I am also very grateful to Adriana Pacheco for

feedback, instruction, and support throughout this proj ect.

I acknowledge and gratefully thank Rebecca McLarty, Shweta Patole, Michael

Friedlander, Mauricio Arias, and Jennifer Stokke for assistance in laboratory data collection and

sample analysis; the Environmental Engineering Sciences department faculty and staff members

for assistance and guidance; Ashok Jain, Jim Stainfield, and Karen Mentz (NCASI) for technical

advisement and data analysis; and Timothy McKelvey, Chet Thompson, Cecile Hance, and Myra

Carpenter (industry representatives) for tours, technical information, and collection of biofilm

and other process samples.

This proj ect was supported by the Department of Energy, Award Number: DE-FC36-

03ID14437, the Sally and William Glick Foundation 2005 Graduate Research Award, and a

2005 Air & Waste Management Association Graduate Student Scholarship.

Finally, and most importantly, I acknowledge and thank Greg Babbitt for his continued

support and love; and Nora Babbitt, Sarah Whitfield, my parents Diane and Richard Whitfield,

and all my family for their moral support, interest in my work, and belief in my abilities.












TABLE OF CONTENTS


Page
ACKNOWLEDGMENTS .............. ...............4.....


LIST OF TABLES ................ ...............8............ ....


LIST OF FIGURES .............. ...............9.....


AB S TRAC T ............._. .......... ..............._ 1 1..


CHAPTER


1 INTRODUCTION ................. ...............13.................


Background and Significance ................. ...............13........... ....
Research Context................ ...............16
Research Goals and Obj ectives ................ ...............19........... ...


2 INITIAL PHENOTYPIC CHARACTERIZATION OF METHYLOTROPHIC MIXED
CULTURES FROM PULP AND PAPER MILL BIOFILMS................ ...............2


Introducti on... ... ......... ...............21._._._.......
M ethods................... ..............2
Sample Collection... ........... ...............21......
Mixed Culture Enrichment ........._.___..... .__. ...............22....
Colony Observations ................ ............. ... .. ..... ....... ........2
Growth of Mixed Cultures in Liquid Medium with Methanol as the Carbon Source23
Results and Discussion............... ...............2
Colony Observations ................ ............. ... .. ..... ....... ........2
Growth of Mixed Cultures in Liquid Medium with Methanol as the Carbon Source25
Conclusions.... ...............2


3 EFFECT OF ENRICHMENT NITROGEN SOURCE ON THE GENETIC DIVERSITY
AND METHANOL OXIDATION POTENTIAL OF TWO METHYLOTROPHIC
MIXED CULTURES FROM PULP AND PAPER MILL BIOFILMS ............... ...............30


Introducti on .... ....._.___......_. ...............3 0....
M ethods................... ..............3

Sample Collection... ............... .... .. ...............33
Enrichment for Methylotrophic Bacteria .............. ... ...__ ... ..._._..............3
Comparison of Growth and Methanol Degradation Using Two Types of Nitrogen
Source .................... .. ... ..... .........................3
Diversity of Microbial Populations in Cultures Enriched with Different Nitrogen
S ourc e s.........._.... ........._._._ ...............36...
DNA Separation using DGGE ............ ......__ ...............38..
DGGE Image Analysis .............. ...............38....
Diversity M easurements .............. ...............3 8....












DNA Sequencing and Phylogenetic Analysis .............. ...............39....
Results and Discussion................ ......... ... ... .. ............4

Comparison of Growth and Methanol Degradation Using Two Types of Nitrogen
Source .................... .. ... ..... .........................4
Diversity of Microbial Populations in Cultures Enriched with Different Nitrogen
S ourc e s................ ....... .... ... .. ...............41...

Phylogenetic Analysis of Dominant Species ................. .............. ......... .....42
Conclusions.... ...............4


4 METHANOL REMOVAL EFFICIENCY AND BACTERIAL DIVERSITY OF AN
ACTIVATED CARBON BIOFILTER .....__.....___ ..........._ ............5


Introducti on ............ ..... ._ ...............50...
Materials and Methods .............. ....._ ...............52...
Selection of Biological Inoculum ............_......__ .... ............5
Selection of Packing Material ............ ......__ ...............54..
BioHilter Design...... ........... ......... .. .............5
BioHilter Operation and Performance Measurements .................... .................5
Abundance and Diversity of Microbial Populations in the Biofilter ........................57
DNA Extraction and Amplifieation............... .............5
DNA Separation and Analysis............... ...............60
DGGE Image Analysis ................. ...... ...............6
DNA Sequencing and Phylogenetic Analysis .............. ...............61....
Results and Discussion............... ...............6
BioHilter Design...... ...... ...............62........
BioHilter Performance ................. ..................... ........6
Bacterial Counts over the Length of the BioHilters ........................... ...............64
Bacterial Diversity Comparisons ............................... ...............65......
Phylogenetic Analysis of Methylotrophic Bacteria ....._.__._ ........___ ........._....68
Conclusions.... ...............7


5 LIFE CYCLE ASSESSMENT OF TWO OPTIONS FOR CONTROLLING
HAZARDOUS AIR POLLUTANTS AT PULP AND PAPER MILLS: A
COMPARISON OF THERMAL OXIDATION WITH A NOVEL
PHOTOCATALYTIC OXIDATION AND BIOFILTRATION SYSTEM............._.._. ......78


Introducti on .... .......... .. ...............78......... ......
M ethods............. .. ........ .... ........7
Goal and Scope Definition............... ...............8
Inventory .............. ...............83.................
Impact Assessment... ........... ... .... ...............84
Interpretation and Sensitivity Analysis............... ...............85
Re sults ... .... ..... .. ...............86.......... ......
Inventory .............. ...............86.................
Impact Assessment... .......... ...............87......
Sensitivity Analy si s.. ............ ...............87.....
Discussion ....... ........ ...............87.......... ......












Inventory ..... ............... ...............87.......
Impact Assessment... .......... ...............90......
Interpretati on ..........._._ ...............91._._._......
Conclusions..... ..............9


6 SUMMARY, CONCLUSIONS, RECOMMENDATIONS AND BROADER IMPACTS107


Summary ....... ....__ ...............107__ .......
Conclusions.... .......... .. ........10
Recommendations and Broader Impacts .....__.....___ ..........._ .............0


APPENDIX: ADDITIONAL FIGURES ............. .....__ .... ..............11


LIST OF REFERENCES ............. ...... ._ ...............114..


BIOGRAPHICAL SKETCH ............. ...... __ ...............123...










LIST OF TABLES


Table page

2-1 Observations of mixed methylotrophic culture isolates grown on nitrate mineral salts
agar plates............... ...............26.

2-2 Growth characteristics of mixed methylotrophic cultures ................. .......... .............27

3-1 Bacterial species, diversity, and evenness for SA and SB cultures in both AMS and
NM S m edia .............. ...............45....

4-1 Summary of biofilter operating conditions ................ ......... ....___ ...........7

4-2 Comparison of activated carbons and inoculation methods ................. ......__ ............72

5-1 List of data sources used for maj or processes in compiling the life cycle inventory of
two alternative technologies for methanol control .............. ...............95....

5-2 Average fuel mix for electricity production in the United States and at an average pulp
and paper m ill ................. ...............96................

5-3 Material and energy inputs from the "technosphere" directly to and solid waste outputs
from construction and operation of two alternative technologies for methanol control ......97

5-4 Raw material inputs, in kg per functional unit, from nature into the total life cycle of
construction and operation of two alternative technologies for methanol control ...............98

5-5 Emissions to air in kg per functional unit, for construction and operation of two
alternative technologies for methanol control ....__ ......_____ .......___ ...........9

5-6 VOC emissions, in kg per functional unit, from HVLC sources in the brownstock pulp
washing process before treatment and estimated VOC emissions resulting from the two
alternative technologies for methanol control .....__.....___ .......... .. ...........0










LIST OF FIGURES


Figure page

2-1 Sampling sites in the pulp and paper mill wastewater treatment system ................... ..........28

2-2 Growth in liquid culture over time for five biofilm enrichment cultures (SA-SE) with
initial methanol concentrations of 0.2% by volume ................. ............... ......... ...29

3-1 Comparison of methanol removal by SA and SB cultures in both AMS and NMS
medium with an initial methanol concentration of 1,000 mg/L. .............. ....................4

3-2 Comparison of batch growth rates in SA and SB cultures in both AMS and NMS
medium with an initial methanol concentration of 1,000 mg/L. .............. ....................4

3-3 Bacterial diversity measured using PCR-DGGE analysis............... ...............47

3-4 Phylogenetic reconstruction of known methylotrophic bacteria and unknown culture
strains using mxaF gene sequences. ............. ...............48.....

3-5 Phylogenetic reconstruction of known bacteria and unknown culture strains using 16s
rRNA gene sequences .............. ...............49....

4-1 Biofilter operation schematic .............. ...............72....

4-2 Methanol removal efficiency in the biologically inoculated and non-inoculated biofilters
as a function of time and methanol loading rate. .......... ...............73......

4-3 Abundance of cultivable bacteria in three spatial regions of the biofilters using three
types of culture media.. ............ ...............74.....

4-4 Bacterial diversity of the biofilters over time, measured using PCR-DGGE......................75

4-5 Bacterial diversity of the biofilters in different spatial regions.............___ .........__ ......76

4-6 Phylogenetic reconstruction of known methylotrophic bacteria and unknown biofilter
and inoculum strains using Neighbor Joining method. The inferred phylogeny was
bootstrapped with 1,000 replicates, and bootstrap values greater than 75% are shown
on corresponding branches ................. ...............77..___. ......

5-1 System boundaries for the life cycle of the construction and operation of a regenerative
thermal oxidizer (RTO) and caustic scrubber for the treatment of methanol .................. .. 101

5-2 System boundaries for the life cycle of the construction and operation of a
photocatalytic oxidation (PCO) reactor and biofilter for the treatment of methanol .........102

5-3 Total comparative life cycle impacts, per functional unit, of the construction and
operation of two alternative technologies for methanol control ................. ........_.._.....103










5-4 Sensitivity analysis of wood or coal used as precursor material for granular activated
carbon production, based on relative impact of the PCO-biofilter system as compared
to the RTO-scrubber system ................. ...............104....._.._....

5-5 Sensitivity analysis of the lifetime of biofilter packing media and STC pellets, based on
relative impact of the PCO-biofilter system as compared to the RTO-scrubber system ...105

5-6 Sensitivity analysis of the lifetime energy requirement of UV bulbs in the PCO reactor,
based on relative impact of the PCO-biofilter system as compared to the RTO-scrubber
sy stem ................. ...............106_._._.......

A-1 Methanol removal efficiency as a function of time and methanol loading rate, in a
preliminary trial of a biologically inoculated biofilters using SB as inoculum.
Excessive biomass formation and clogging was observed by day 20, which correlated
with loss of methanol removal performance. .........._.__.......... ....._.. ...........1

A-2 Photograph of preliminary biofilter, clogged by excess biomass when using SB as
inoculum. ........._.._.._ ....__. ...............112...

A-3 Freundlich isotherm plot of batch isotherm results for the activated carbon biofilter
packing material. ........._.._.._ ...............112....._......

A-4 DGGE analysis of mxaF and 16s rRNA gene sequences from a long-term batch culture
created using the same biofilter inoculum derived from SA as used to inoculate the
activate carbon biofilter "BB." ............... ...............113........... ...









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

PERFORMANCE, MICROBIAL ECOLOGY, AND LIFE CYCLE ASSESSMENT OF AN
ACTIVATED CARBON BIOFILTER FOR METHANOL REMOVAL

By

Callie Whitfield Babbitt

December 2007

Chair: Angela S. Lindner
Major: Environmental Engineering Sciences

The forest products industry is responsible for producing valuable industrial chemicals,

wood products, and consumer goods. However, processes involved in creating these materials at

pulp, paper, and paperboard mills also generate hazardous air pollutants (HAPs), such as

methanol, that are released during wood pulp production. With increasingly stringent regulations

on methanol emissions, mills are continually seeking effective and cost efficient ways to control

its release. Motivated by the need to study economical and environmentally friendly methanol

control technologies, a bench-scale activated carbon biofiltration system was developed and

evaluated for its ability to remove methanol from an artificially contaminated air stream. The

biofilter contained a novel packing mixture of activated carbon, perlite, slow release nutrient

pellets, and water retaining crystals, and showed excellent biofilm growth and close to 100%

biological methanol removal, both with and without addition of an inoculum containing enriched

methanol-degrading bacteria.

Design of the biofilter using an inoculum enriched for methanol-degrading bacteria also

facilitated characterization of biofilm samples from a pulp and paper mill on the basis of

selecting a biofilter inoculum and optimizing growth and activity in mixed culture. Studies of









enriched cultures from the biofilm samples showed higher bacterial community diversity and

methanol removal when using nitrate as the nitrogen source for enrichment, rather than

ammomium .

Design and operation of this bench-scale system also enabled further investigation with

microbial ecology and molecular techniques to characterize diversity of bacterial communities

colonizing the biofilter over different points in time and under varied operational conditions.

Amplification and separation of DNA from biofilter samples, using polymerase chain reaction

(PCR) and denaturing gel gradient electrophoresis (DGGE), indicated that although bacterial

diversity and abundance varied over the length of the biofilter, the populations rapidly formed a

stable community that was maintained over the entire 138 days of operation and in variable

operating conditions. Phylogenetic reconstruction of bands excised from DGGE gels indicated

that the biofilter supported a diverse community of methanol-degrading bacteria.

Finally, the design and operation of the bench-scale biofilter provided parameters for use

in a life cycle assessment (LCA) that compared raw materials and energy required and emissions

and environmental impacts produced by construction and operation of a proposed photocatalytic

oxidation (PCO)-biofilter system, to those associated with treatment using a more traditional

regenerative thermal oxidizer (RTO). LCA results indicated that environmental impacts

associated with construction of a RTO far outweighed infrastructure requirements of the PCO-

biofilter system. However, the operating impacts to global warming and human toxicity for the

PCO-biofilter system were higher than for the RTO, because of the replacement requirements of

packing for the PCO reactor and biofilter, as well as the electricity requirement to operate the

PCO reactor.









CHAPTER 1
INTTRODUCTION

Background and Significance

The forest products industry, specifically pulp and paper mills, produces a variety of

industrial and consumer products from wood cellulose, including paper, paperboard, infant,

female, and adult hygiene products, high porosity filters, food casings, rayon filament, and

chemicals such as ethers and acetate. Pulp required for these products is produced by physical

processes that convert whole trees to wood chips and chemical processes that digest the chips to

produce either a brownstock or bleached final pulp. Throughout many of these processes,

organic compounds that are naturally present in wood or produced during the degradation of

cellulose are released to the environment.

In 1998, the U. S. Environmental Protection Agency (U.S. EPA) passed a regulation

known as the "Cluster Rule," which regulates the release of these compounds to both the air and

the water (U.S. EPA 1998). Air emissions included in the Cluster Rule that present established

or potential impacts to human or environmental health are known as hazardous air pollutants

(HAPs). The HAP of greatest concern is methanol, which represents over 70% of the total

release of HAPs from this industry, amounting to over 44,000 tons each year. (U. S. EPA 2004).

Released in this quantity, methanol can contribute to human health impacts, such as

cancer, respiratory irritation, and damage to the nervous system (U.S. EPA, 1998). Other

emissions include acetaldehyde, formaldehyde, methyl ethyl ketone (MEK), methyl isobutyl

ketone (MIBK), ot- and P-pinene, and reduced sulfur species including dimethyl sulfide,

dimethyl disulfide, and methyl mercaptan, which are collectively termed total reduced sulfur

(TRS). To prevent potential environmental and health impacts from these emissions, the Cluster









Rule includes a section specifying the maximum available control technology (MACT) required

to limit the amount of HAPs emitted.

MACT regulations require that pulp and paper mills collect and treat non-condensable

gas from high volume low concentration sources (HVLC). HVLC gases are those with large

volumes (typically 10,000-30,000 acfm for an entire mill) and relatively dilute compound

concentrations (below the lower explosion limit of the gas mixture) and are emitted from pulp

washing systems, oxygen delignification systems, deckers, knotters, and black liquor storage

tanks, etc. (Varma 2003). MACT regulations give pulp and paper mills flexibility of complying

with emission limits with any technology proven to perform to at least the minimum

requirements of the emission standards (98% methanol removal) (U.S. EPA 1998). Most mills

plan to comply with MACT by collecting the gases in vent hoods, using fans or blowers to

transport the gases, and eliminating the HAPs by combustion in either an existing power boiler

or lime kiln or in new stand-alone thermal oxidizers (Varma 2003). Albeit effective, thermal

oxidation has the drawbacks of requiring a constant input of natural gas or other fuel supply to

support incineration and increasing the emissions of carbon dioxide (CO2), Sulfur dioxide (SO2),

and nitrogen oxides (NOx). This technology also has very high capital costs, because of the need

to install ductwork and other infrastructure for gas collection and transport. Therefore, a more

environmental and economical solution is desired for HAPs control for pulp and paper industry.

One technology proposed as an alternative to thermal oxidation is a photocatalytic

oxidation (PCO) reactor containing a packed bed of a composite material of silica and the

photocatalyst titanium dioxide (TiO2) (Stokke et al. 2006), in which the silica provides a catalyst

support and adsorbs HAPs from the air stream while the photocatalyst promotes destruction of

these compounds when exposed to UV light. However, when the reactor is not functioning with









maximum efficiency or if it is designed to remove less than 100% of incoming contaminant, the

HAPs will not be completely eliminated from the gas stream, necessitating a secondary or

"polishing" treatment step. This secondary system would consist of a Eixed bed granular

activated carbon (GAC) biofilter, although such a biofilter may also serve as a primary treatment

sy stem.

GAC is a highly porous adsorbent material that removes contaminants by nature of van

der Waals interactions between the contaminants and the carbon surface when they are in

intimate contact (Dabrowski 2000). Activated carbon is produced from a carbonaceous material

(typically wood, coal, or biomass residue) that is carbonized in the absence of oxygen and

activated by either a chemical or physical process that increases the porosity and changes the

surface chemistry to enable high levels of adsorption of target contaminants (Menendes-Diaz and

Martin-Gull6n 2006). Adsorption is a finite process, however, with a physical limit to the extent

activated carbon can be used before its capacity is exhausted. One means of extending the GAC

service life and the economic advantage of this technology is the incorporation of biological

activity to create a synergistic process by which the GAC adsorbs VOCs from the air stream,

creating a favorable environment for the formation and maintenance of a stable microbial bioailm

that subsequently degrades adsorbed and incoming organic (Aizpuru et al. 2003; Chang and

Rittman 1987; Herzberg et al. 2003; Hodge and Devinny 1994; Weber and Hartmans 1995;

Zhang et al. 1991). Considering the nature of the pulp and paper mill system, specifically warm

temperatures, high humidity, and predominance of one-carbon compounds, biofilm formation,

growth, and activity are expected to be inherent to the system.

Based on the design obj ective to treat low or fluctuating concentrations of VOCs in large

volumes of gas (Kennes and Veiga 2001) and the expected availability of biological inoculum









inherent to the pulp mill environment, an activated carbon biofilter would be an ideal solution for

the polishing step of the methanol removal train. A biofilter has traditionally been characterized

as having a fixed-bed containing inert organic packing that serves as a carrier for biomass and a

nutrient source, where contaminants in polluted air are degraded by the active biomass and

where no mobile liquid phase is present (Devinny et al. 1999; Kennes and Thalasso 1998;

Kennes and Veiga 2001). This definition has been expanded in recent research to include

surface-active packing that provides adsorption capacity (e.g., for buffering peak loads or

process instabilities) as well as inorganic packing with discontinuous aqueous nutrient addition

(Aizpuru et al. 2003; Prado et al. 2002; Teran-Perez et al. 2002; Yang et al. 2002). Use of

activated carbon as the primary biofilter packing material (not just as inorganic support for

compost or other organic packing) falls into both of the latter categories.

Research Context

A great deal of literature exists that addresses the design, operation, and performance of

biofilters for removal of contaminants from gaseous effluent streams (e.g., Devinny et al. 1999;

Kennes and Thalasso 1998; Kennes and Veiga 2001). In many of such studies, a drop in a

biofilter' s performance has been usually hypothesized to be due to factors such as excess or

limited moisture, nutrients, or substrate, pH excursions, or biomass buildup or clogging (e.g.,

Gribbins and Loehr 1998; Jin-Ying et al. 2005; Teran-Perez et al. 2002; Yang et al. 2002).

However, a disconnect exists in the literature between hypotheses about bacterial causes of

reduced performance and actual observations of the bacterial systems or measurements of

bacterial abundance or diversity. In addition, when inorganic material such as activated carbon

is used for biofilter packing, it is common to inoculate the system with biological material able to

grow and degrade contaminants under the conditions expected in the treatment train, including









particular pH, temperature, and substrate concentration values (Devinny et al. 1999) Often,

these criteria aren't explicitly investigated, but, rather, inoculum is derived from enrichment of

available activated sludge or other waste materials (Aizpuru et al. 2003; Moe and Qi 2005),

obtained from prior lab studies (Herzberg et al. 2003; Thalasso et al. 2000), or added as pure

cultures (Speitel and McLay 1993). There is little known about how the microbial populations

used as inoculum actually influence the bioHilter performance or the ultimate structure of the

bioailm colonizing the packing media.

Fortunately, more recent work has begun to focus on the relationships between bioailter

performance and biofilm properties, including distribution, activity, and kinetics of the attached

bioailm (Song and Kinney 2000; Veiga et al. 1999). These studies and others focusing on the

bacterial abundance and activity in bioHilters (Acuna et al. 1999; Aizpuru et al. 2003) used

traditional culture-dependent techniques to enumerate bacteria present in the biofilm and

correlate those results with phases of operation and performance. The maj or limitation to such

culture-dependent techniques is their potential bias to those organisms which grow fastest under

lab conditions and their inability to adequately represent all microorganisms present (Hugenholz

2002).

Therefore, molecular techniques have been increasingly used due to more readily

available 16s rRNA sequences for comparison purposes (Clarridge 2004) and ever-improving

methods for extracting, amplifying, and sequencing DNA directly from an environmental sample

with no culturing required (Torsvik and Ovreas 2002). Examples of these methods include

phospholipids fatty acid (PLFA) analysis, denaturing (or temperature) gradient gel

electrophoresis (DGGE/TGGE), terminal restriction length polymorphism (TRFLP), or

ribosomal intergenic spacer analysis (RISA) (Torsvik and Ovreas 2002).









DGGE in particular is a molecular method that is becoming very popular for

investigating bacterial diversity and community structure in environmental and applied

biological systems. DGGE is an approach used to determine the genetic diversity of mixed

microbial populations by electrophoresis of PCR-amplified DNA in a polyacrylamide gel with a

linear gradient of denaturant (Muyzer et al. 1993). This approach has been popularized recently

due to the reported ability to separate DNA fragments of the same length but slightly different

sequences (e.g., single base changes, Myers et al. 1987), as based on the relative electrophoretic

mobility associated with the melting point of a given DNA sequence (Muyzer and Smalla 1998).

The resulting banding pattern, when the gel is visualized using UV light, provides an illustrative

comparison of frequency and presence or absence of banding patterns for different conditions

investigated. DNA fragments associated with a banding pattern of interest can be excised from

this gel, re-amplified, and sequenced to assess mutations or presence of specific bacterial strains,

or the banding patterns can be mathematically assessed to determine relative changes in the

diversity or phylogeneticc richness" (Ogram and Sharma 2002) to increase understanding of the

microbial ecology of a system. For example, Li and Moe (2004) used DGGE to evaluate the

spatial structure throughout the length of two types of biofilters treating methyl ethyl ketone to

explain the superior performance of one configuration over another. Others apply this method to

determine the acclimation or stability of cultures in biological treatment systems over time

(Labbe et al. 2003; Rombaut et al. 2001). Another approach has been to compare banding

patterns generated from amplified sequences from functional genes to determine the relative

abundance or dominance of specific types of bacteria, such as different types of methanotrophs

(Fjellbirkeland et al. 2001; Henckel et al. 1999) or denitrifiers (Goregues et al. 2005). Takaku et

al. (2006) were able to relate significant shifts in bacterial community structure, as assessed by









DGGE, to distinct temperature changes in their system, while Sercu et al. (2005) compared

attached biofilm diversity in a biotrickling fi1ter to bacterial communities in the planktonic state.

Even with these successes, there are also several limitations to the use of DGGE as a

microbial ecology tool, namely the limitation to DNA fragments of about 500 bp or less, the

production of anomalous PCR products from incorporating a GC clamp into primers, and

potential difficulty interpreting or comparing results (Gilbride et al. 2006; Bruns et al. 1991;

Muyzer and Smalla 1998). In addition, the most common approach is to use 16S rRNA gene

sequences for amplification, giving an idea of diversity of all bacteria present. Other than a

small amount of work done to target specific bacterial groups, as discussed above, the use of

functional genes has been much more limited for a combined PCR-DGGE approach.

Nevertheless, use of molecular methods such as DGGE can potentially offer a more detailed

insight into the microbial ecology of biological systems, such as biofilters, than possible with

performance measurements or culture-dependent studies alone.

Research Goals and Objectives

This research was motivated by the need to investigate a more economical and

environmentally friendly methanol control technology for the pulp and paper industry, such as an

activated carbon biofiltration system. With this goal in mind, the research reported herein

focused on developing and testing a bench-scale activated carbon biofiltration system capable of

removing methanol from an artificially contaminated air stream in concentrations representative

of industrial processes. Operation of this bench-scale system enabled further investigation with

four specific obj ectives:

1. Collect and characterize biological samples from the pulp and paper industry on the basis
of selecting a biofilter inoculum and optimizing their growth and biodegradation in mixed
culture using different nitrogen sources and concentrations (Chapters 2 and 3);









2. Measure the methanol removal efficiency of the bench-scale bioailter containing a novel
heterogeneous packing material comprised of granular activated carbon, perlite, slow-
release nutrient pellets, and water-retaining crystals (Chapter 4);

3. Use selected culture-dependent and independent microbial ecology and molecular
techniques, such as DGGE, to characterize the diversity of bacterial communities
colonizing the biofilter over different points in time, under varied operational conditions,
and at different spatial points in the biofilter (Chapter 4); and

4. Perform a life cycle assessment (LCA) to compare raw material and energy requirements
and emissions and environmental impacts of the proposed photocatalytic oxidation
reactor and biofiltration system to those associated with traditional treatment systems,
specifically regenerative thermal oxidation and wet scrubbing (Chapter 5).

A more thorough understanding of the biofilter technology as part of a novel methanol

treatment train promises to yield significant environmental and economic savings for the pulp

and paper industry, as well as other industry sectors that are challenged with controlling HAPs

and other volatile organic compounds (VOCs) in their process streams.









CHAPTER 2
INITIAL PHENOTYPIC CHARACTERIZATION OF METHYLOTROPHIC MIXED
CULTURES FROM PULP AND PAPER MILL BIOFILMS

Introduction

Use of a biological system, such as a biofilter, for treating air pollutants requires the

presence of active microbial consortia that are capable of degrading contaminants of interest.

When inorganic material such as activated carbon is used, inoculation with enrichments targeted

for degradation of known concentrations of contaminants under specific temperatures and pH,

may be necessary (Devinny et al. 1999). Often, these criteria are not explicitly investigated, but,

rather, inoculum is derived from enrichment of available activated sludge or other waste

materials (Aizpuru et al. 2003; Moe and Qi 2005), obtained from prior lab studies (Herzberg et

al. 2003; Thalasso et al. 2000), or added as pure cultures (Speitel et al. 1993).

Pulp and paper mills possess environments expected to be favorable for microbial

growth, due to warm, moist conditions and the presence of readily degradable organic substrates.

In fact, overabundance of biofilms or slimess" at these mills often creates operational problems

(Lahtinen et al. 2006), yet such biofilms could make ideal inocula for a biological treatment

system. This chapter reports an initial characterization of biofilm samples collected from various

locations at a southeast pulp, paper, and paperboard mill that uses a biological wastewater

treatment system. Traditional culture-dependent characterization methods were used to evaluate

and select potential inocula for subsequent biofiltration treatment for methanol removal from air.

Methods

Sample Collection

Seven grab samples of biofilm samples collected from this mill were collected during

June 2004, from locations believed by mill staff to be representative of methanol-degrading









consortia or having a high number of bacteria present and stored on ice in sterilized Teflon

collection vessels until they could be processed in the lab or stored over a longer term at 4 deg.

C. The locations of these samples, identified as Sample A-G (SA-SG) are as follows:

Sample A (SA): Vent tubes of an oxygen activated sludge "UNOX" reactor
Sample B (SB): Return activated sludge (exiting secondary clarifiers)
Sample C (SC): Wet material from cooling tower baffles
Sample D (SD): Partially dry material from cooling tower baffles
Sample E (SE): Wood wall outside of the cooling tower
Sample F (SF): Secondary clarifier weirs
Sample G (SG): Mixed liquor exiting the UNOX reactor

The wastewater treatment system and selected sites are shown in Figure 2-1.

Mixed Culture Enrichment

The samples collected were enriched in the laboratory in batch culture in a modified

nitrate mineral salts medium (NMS) containing 0.2% methanol (vol/vol) as recommended by

Hanson (1998). The basal medium contained, on a g/L basis: MgSO4*7H20, 1.0; KNO3, 1.0;

CaCl2, 0.2; KH2PO4, 0.026; Na2HPO4, 0.033. Trace elements were added, on a mg/L basis:

FeSO4*7H20, 0.5; ZnSO4*H20, 0.4; EDTA disodium salt, 0.25; CoCl2*6H20, 0.05;

MnCl2*4H20, 0.02; H3BO3, 0.015; NiCl2*6H20, 0.01; Na2MoO4*4H20, 0.005; and FeEDTA,

0.0038. Vitamins added, on a mg/L basis, were the following: biotin, 0.02; folic acid, 0.02;

thiamin*HC1, 0.05; calcium pantothenate, 0.05; riboflavin, 0.05; nicotinamide, 0.05; and Bl2,

0.001. All chemicals used were obtained from Fisher Scientific (Pittsburgh, PA, USA) or Sigma

Aldrich (St. Louis, MO, USA).

Cultures were maintained in a 1:10 ratio of inoculum:medium to a total volume of 55 mL

in 250 mL Erlenmeyer flasks at 30 oC on a rotary shaker at 250 rpm. Initial enrichment cultures

were incubated for one month, while subsequent transfers to fresh media were prepared on a

bimonthly basis. Two cultures, derived from the samples taken from the secondary clarifier (SF)









and the mixed liquor exiting the UNOX reactor (SG), were not easily maintained in batch

culture, due to continual creation of pellicles in liquid solution and lack of turbidity formation.

For that reason, these two cultures were not compared with the others for many of the

characterization tests.

Colony Observations

Serially diluted samples from the five remaining cultures were spread-plated on NMS

agar plates, two months after initial enrichment, and incubated at 30 oC with methanol present in

the vapor phase. Colonies appearing to be morphologically unique from each other by

inspection under light microscope were transferred by streaking onto new NMS plates in an

attempt to obtain relatively pure isolates. These transfers were conducted so that morphological

distinctions between isolates could be observed, with the goal of determining how many

potentially different strains might be present in the cultures. Observations included color, shape,

transparency, and edge of the colony, as well as Gram stain, and motility. Colonies were also

streaked onto tryptic soy and nutrient agar plates and incubated at 30 oC with no methanol

present, to determine the ability of the isolates to grow on multiple carbon sources.

Growth of Mixed Cultures in Liquid Medium with Methanol as the Carbon Source

In addition to morphological distinctions among the cultures, Samples A-E cultures were

also observed on their ability to grow in liquid media with methanol as the sole carbon and

energy source. Enriched mixed cultures were grown to%3/ log phase, harvested by centrifugation

in a J2-HS Beckman floor model centrifuge (Beckman Coulter, Inc., Fullerton, CA, USA), then

twice washed with phosphate buffer and recentrifuged to remove residual methanol. Cells were

resuspended in the NMS medium to obtain an optical density of 0. 1 at 600 nm, and aliquotted in

triplicate into side-arm flasks to a final ratio of 1:10 cells to medium. Liquid methanol was









added to the mixture to a final concentration of 0.2% by volume, and the cultures were incubated

for nine days on a rotary shaker at 250 rpm and 30 oC. Growth, assayed by optical density, was

measured using a spectrophotometer at 600nm, directly from the sample in the glass vial.

Results and Discussion

Colony Observations

Isolated strains from the five mixed methylotrophic cultures (SA-SE) were grown on

solid agar plates with methanol in the vapor phase and observed based on their morphology,

motility, and Gram stain (on NMS plates), as well as their growth on multi-carbon tryptic soy

agar (TSA) and nutrient agar plates, with results shown in Table 2-1. Cultures from samples SA

and SB appear to have the most distinct isolates as cultured under these lab conditions, which

possibly may represent higher diversity in their natural environment, an ideal characteristic of

bacterial consortia used for biological treatment systems. All but one of the isolates was Gram

negative, and the isolate (number 1 from SB) that tested Gram positive showed inconclusive

results on repeated testing. Only one of the isolates, number 6 from SB, showed clear signs of

motility. Lack of motility may be related to the enrichment of samples collected from a biofilm

environment, which, in the mill environment, may cause selection for bacteria that can attach to

surfaces, rather than for those with appendages required for motility in a suspended state (Dunne

2002). Colonies obtained from all five samples showed a variety of morphological differences,

with colors ranging from clear to beige and opacity from transparent to semi-opaque. The

various colonies were both irregular and circular in shape and were observed to have edge

margins including lobate (irregular lobes), erose (serrated), undulate (wavy), curled, filamentous,

and entire (smooth). Colony elevations ranged from completely flat to convex, to pulvinate

(completely rounded). All colonies except three (number 4 in SA and numbers 2 and 3 in SB)









were observed to show at least some growth on TSA and nutrient plates. The ability for growth

on multi-carbon source plates indicates that the bacterial cultures enriched from the biofilms

likely contain facultative or restricted facultative methylotrophs, those bacteria capable of using

methanol or other compounds with carbon-carbon bonds as a carbon source (Lidstrom 2001).

Growth of Mixed Cultures in Liquid Medium with Methanol as the Carbon Source

Growth rates for the five mixed methylotrophic cultures are shown in Figure 2-2, with

error bars representing the standard error for optical density measurements in triplicate. In many

cases, the error is relatively high because of interference from the suspended and attached

pellicles formed by the bacteria in the growth flask. Additional parameters extracted from this

growth curve are given in Table 2-2, including the lag time, growth rate, and generation (or

doubling) time. Based on these results, cultures from SB and SC exhibited the fastest

acclimation and highest biomass production within the batch culture. Cultures from SA and SB

showed the shortest lag time from inoculation until growth commenced, while cultures from SA,

SB, and SC exhibited the fastest growth rate

Conclusions

Phenotypic observations from this initial characterization indicated that the mill biofilms

may be host to highly diverse populations of bacteria, which would make for straightforward

provision of an inoculum culture if a biofilter or other biological treatment system were to be

implemented in the mill environment. Based on potential high diversity (as observed by the

number of distinct colony isolates), ability for isolates to grow on multiple carbon sources, and

minimal lag time and rapid growth rate in liquid culture, SA and SB were selected as the best

potential biofilter inocula, and were further characterized on the basis of their methanol

degradation potential using different nitrogen sources, as reported in Chapter 3.
















































For growth measurements, no sign indicates no growth; + indicates minimal growth; ++ indicates growth over at least 50% of the
plate; +++ indicates excellent growth over at least 75% of the plate. For motility and gram stain, (+) indicates a positive result, (-)
indicates a negative result.


Table 2-1. Obse rations of mixed methylotrophic culture isolates grown on nitrate mineral salts agar plates
Growth on Growth on
Growth on Gram
Sample Isolate Color Transparency Form Elevation Margin MehnlTryptic Soy Nutrient SanMotility
Agar Agar
1 Clear Transparent Irregular Flat Lobate ++ +++ +++ (- ()
2 Pale Yellow Transparent Circular Pulvinate Lobate ++ +++ +++ (-) (-)
3 Pale Yellow Transparent Irregular Pulvinate Lobate ++ +++ +++ (- ()
A 4 Yellow Semi-Opaque Circular Umbonate Erose ++ + (-) (-)
5 Pale Yellow Transparent Irregular Pulvinate Undulate + +++ ++(- ()
6 Clear Transparent Irregular Flat Undulate +++ +++ ++ (-) (-)
7 Clear Transparent Irregular Flat Undulate ++ ++ +++ (-) (-)
1 Beige Transparent Irregular Umbonate Curled +++ + + (-) (+/-)
2 Clear Transparent Circular Convex Entire +(- ()
3 Clear Transparent Circular Convex Entire ++ (-) (-)
B 4 Beige Semi-Opaque Filamentous Convex Filametous ++ ++ ++(- ()
5 Yellow Semi-Opaque Circular Convex Undulate + ++ ++ (-) (-)
6 Yellow Semi-Opaque Circular Convex Entire +++ ++ ++ (+) (-
7 Beige Transparent Circular Umbonate Curled +++ ++ ++(- ()
C 1 Clear Transparent Circular Convex Entire ++ + +(- ()


_


r


D 2
3
1
2
E 3
4
5


Pale Yellow
Clear
Pale Yellow
Clear
Yellow
Clear
Clear
Clear


Semi-Opaque
Transparent
Semi-Opaque
Transparent
Semi-Opaque
Transparent
Transparent
Transparent


Circular
Circular
Circular
Irregular
Circular
Irregular
Circular
Irregular


Umbonate
Flat
Convex
Flat
Umbonate
Umbonate
Umbonate
Flat


Entire
Erose
Undulate
Lobate
Erose
Lobate
Undulate
Curled


++

++
+++
+++
+++
++
+++









Table 2-2. Growth characteristics of mixed methylotrophic cultures
Source of Lag Phase Growth Rate Generation Time
Culture
Inoculum (hr) (hr-1) (hr)
A Enclosed Aeration Basin Vent Tube 21.0 0.111 6.26

B Return activated sludge 17.5 0.132 5.24
C WWT cooling tower baffle (wet) 31.0 0.172 4.04
D WWT cooling tower baffle (dry) 25.7 0.093 7.49
E WWT cooling tower wall 25.7 0.062 11.2
Biofilm samples collected from the secondary clarifier weirs (F) and from mixed liquors (G)
were not able to be enriched in the lab. All samples were obtained from the wastewater
treatment (WWT) system of a southeast paper and paperboard mill. Growth parameters are
based on liquid culture containing initial methanol concentrations of 0.2% by volume.






















































Figure 2-1. Schematic of sampling sites in the pulp and paper mill wastewater treatment system: A: Vent tubes of an oxygen activated

sludge "UNOX" reactor; B: Return activated sludge (exiting secondary clarifiers); C: Wet material from cooling tower baffles;
D: Partially dry material from cooling tower baffles; E: Wood wall outside of the cooling tower; F: Secondary clarifier weirs;

G: Mixed liquor exiting the UNOX reactor.


.*,
,----
-
i=L~
r*
'I

~;r~s

::


;;
-~
~fi~"~;"

~C~-s~:r



ia":it'~
I
-I
':?rsi? r::u"
er;s


IB;d~EiEn3F:al;li- ULI:: ~clC"~I
'IZC*


G .


C,D,E -


I ~L

i--*r~~Ef "' "":'


I


"ic:Z

















0.6 SB


~0.5- S
8 -r- SE
S0.4




S0.2




0. 1


0.0I
0 20 40 60 80 100 120 140 160 180 200 220

Time (hr)


Figure 2-2. Growth in liquid culture over time for five biofilm enrichment cultures (SA-SE) with
initial methanol concentrations of 0.2% by volume.









CHAPTER 3
EFFECT OF ENRICHMENT NITROGEN SOURCE ON THE GENETIC DIVERSITY AND
METHANOL OXIDATION POTENTIAL OF TWO METHYLOTROPHIC MIXED
CULTURES FROM PULP AND PAPER MILL BIOFILMS


Introduction

Methylotrophic bacteria are ubiquitous in many aquatic and terrestrial environments and

play an important role in the carbon cycle because of their ability to oxidize methane, methanol,

and other reduced carbon substrates. Many previous studies on methylotrophs have focused on

methanotrophs, a functional group of methylotrophs able to utilize methane as their sole carbon

source. Within this body of work (e.g., Conrad 1996; Hanson and Hanson 1996; King 1992),

interest has been directed towards the role of methanotrophs. in oxidizing methane, a greenhouse

gas, andingand cometabolizing toxic hydrocarbons. However, less attention has been given to

the potential use of methylotrophs in removing methanol, a common pollutant in aqueous or

gaseous industrial effluents.

The paper and allied products industry is a maj or contributor of methanol emissions,

where it is produced during wood pulping and released to the air and discharged in the mill

wastewater (Someshwar and Pinkerton 1992). For example, in 2002, the top three facilities

reporting the largest methanol emissions through the Toxic Release Inventory (approximately

10.8 million pounds) were paper and allied products companies (Scorecard 2007). While most

pulp mills comply with regulations to control these methanol emissions by incinerating the

methanol in thermal oxidation systems (Varma 2003), environmental and economic advantages

potentially are achieved by using a biological treatment system that takes advantage of the

natural methanol degradation ability of the diverse bacteria classified as methylotrophs.









One biological system of interest is a granular activated carbon (GAC) biofilter, in which

the activated carbon provides an adsorptive fixed bed where degrading microorganisms are

immobilized. Organic contaminants present in the air flowing through the bed ideally are

removed by a synergistic mechanism of adsorption by the GAC and biodegradation by the

microorganisms. As such, this biological system requires the presence of active microbial

consortia that are capable of degrading contaminants of interest under the conditions expected to

be present in the treatment train, including specific pH, temperature, and substrate concentration

values (Devinny et al. 1999) When considering treatment of gaseous methanol from a pulp and

paper mill, using as an inoculum mixed methylotrophic bacterial cultures enriched from samples

obtained from the mill has been demonstrated to influence the ultimate community structure of

bacteria colonizing GAC biofilter, while the specific role of the biological community in the

biofilter in removing methanol and the effects of conditions in the biofilter on the populations

have not been entirely identified (Babbitt et al. 2007).

An important criterion that has not been fully investigated is the importance of the form

and concentration of the nitrogen source used in enriching for methylotrophs or supporting their

growth and activity in liquid culture or in applications such as a biofilter. The intermittent

addition of nitrogen in a mineral salts mixture has been demonstrated to improve the capacity of

biofilters in removing ethanol (Teran Perez et al. 2002) and toluene (Prado et al. 2002). Addition

of greater concentration of nutrients appears to be most important when the biofilter is subj ected

to high mass loading rates (Gribbins and Loehr 1998). When comparing nitrogen added as either

nitrate or ammonium, Yang et al. (2002) demonstrated that ammonium resulted in higher

elimination capacities in a methanol biofilter but that, at high nitrogen-to-carbon ratios, the

ammonium could also inhibit methanol removal. The added nitrate did not show this inhibitory









effect (Yang et al. 2002). Despite the benefit of these studies, it is still unclear how the type and

concentration of nitrogen used directly affects the methanol degradation potential of mixed

methylotrophic cultures a bioHilter application.

When considering batch cultures, extensive work has been conducted to select and

optimize nutrients, growth factors, trace elements, and substrate concentrations for

methanotrophs. (Bowman and Sayler 1994; Park et al. 1992; Park et al. 1991). Less specific

attention has been focused on enrichment of the more general group of methylotrophs. For

example, use of specific nutrient sources, particularly nitrate or ammonium as a nitrogen source,

is not consistently reported in studies involving methylotrophs. In part, this inconsistency

appears to be due to early work showing better growth of methanotrophic bacteria when using

nitrate (Whittenbury et al. 1970), which has been more recently been associated with the

possibility that ammonium inhibits methane oxidation in these bacteria (Boiesen et al. 1993; De

Visscher and Van Cleemput 2003; Higgins et al. 1991). Therefore, some recommendations for

growth of restricted or facultative methylotrophic bacteria follow those for methanotrophs. (e.g.,

use of nitrate as nitrogen source) (Hanson 1998), whereas other studies report use of ammonium

as the nitrogen source, in varied concentrations (Patt et al. 1974, El-Nawawy et al. 1990). The

effect of form and concentration of nitrogen on methanol degradation potential of methylotrophs

is also not clearly understood, nor are the effects on population diversity and stability. Selection

and enrichment of an appropriate inoculum for biological treatment systems, such as GAC

biofilters, may be greatly improved with additional knowledge of optimum nutrient requirements

and concentrations. As an initial step towards this goal, this paper reports the effect of the form

and concentration of nitrogen in batch enrichment cultures on the growth and methanol removal









potentials and the genetic diversity of methylotrophic cultures enriched from biofilm samples

taken from a Kraft pulp mill.

Methods

Sample Collection

To study the effect of nitrogen source and concentration on methylotrophic cultures that

could be used as biofilter inoculum, sampling and analysis was focused on biofilms and other

biological cultures obtained directly from a pulp mill environment. These biological samples

were obtained from a pulp and paperboard company located in the Southeast and with a

biological waste water treatment system. Seven grab samples of biofilm were collected during

June 2004 from locations believed by mill staff to be representative of methanol-degrading

consortia or having a high number of bacteria present, and stored on ice in sterilized Teflon

collection vessels until they could be processed in the lab or stored over a longer term at 4 oC.

Initial culture-dependent growth and isolation techniques demonstrated that two of the seven

samples could be good candidates for inocula in a methanol treatment system, based on their

superior growth and methanol degradation rates and morphologically diverse, culturable

community (determined by identification of visibly distinct colonies on agar plates) (as discussed

in Chapter 2). These samples, A and B, were named "SA" and "SB" and described as follows.

The SA biofilm was obtained directly from the vent tubes of a pure oxygen activated sludge

"UNOX" (Union Carbide Oxidation) reactor, where the conditions would be expected to include

temperatures between 32-36 oC, methanol concentrations between 1,000-5,000 mg/L, and

nitrogen as ammonium in concentrations between 20-140 mg/L (ammonium is added to the

reactor to improve performance). SB biofilm was collected from the return activated sludge









system, with conditions expected to include ambient outdoor temperatures (26-30 oC), and low

methanol (<10-100 mg/L) concentrations.

Enrichment for Methylotrophic Bacteria

Subsamples (10 mL each) from SA and SB were first homogenized in 90 mL of sterile

phosphate-buffered solution for one hour on a rotary shaker at 30 oC at 250 rpm, then this

mixture was used to inoculate batch cultures in both modified nitrate mineral salts (NMS) and

ammonium mineral salts (AMS) media, containing 0.2% methanol (vol/vol) as recommended by

Hanson (1998). The basal medium contained, on a g/L basis: MgSO4*7H20, 1.0; CaCl2, 0.2;

KH2PO4, 0.026; Na2HPO4, 0.033. Trace elements were added, on a mg/L basis: FeSO4*7H20,

0.5; ZnSO4*H20, 0.4; EDTA disodium salt, 0.25; CoCl2*6H20, 0.05; MnCl2*4H20, 0.02;

H3BO3, 0.015; NiCl2*6H20, 0.01; Na2MoO4*4H20, 0.005; and FeEDTA, 0.0038. Vitamins were

added, on a mg/L basis: biotin, 0.02; folic acid, 0.02; thiamin*HC1, 0.05; calcium pantothenate,

0.05; riboflavin, 0.05; nicotinamide, 0.05; and Bl2, 0.001. The nitrogen source was added to the

medium as nitrate (1.0 g/L KNO3) Or ammonium (0.5 g/L NH4C1). All chemicals used were

obtained from Fisher Scientific (Pittsburgh, PA, USA) or Sigma Aldrich (St. Louis, MO, USA)

and were of the highest purity available. The cultures were maintained in a 1:10 ratio of

inoculum to medium to a total volume of 55 mL in 250 mL Erlenmeyer flasks at 30 oC on a

rotary shaker at 250 rpm. Initial enrichment cultures were incubated for one month, while

subsequent transfers to fresh medium were made twice, with a two-week period between

transfers.

Comparison of Growth and Methanol Degradation Using Two Types of Nitrogen Source

To compare methanol degradation by batch mixed methylotrophic cultures with two

potential nitrogen sources, a factorial (32) design was used. This design included either nitrate









added as KNO3 at levels of 0, 1.0, and 2.0 g/L or ammonium added as NH4Cl at levels of 0, 0.5,

and 1.0 g/L (these represent 0, 0.13, and 0.26 g N/L), and methanol added at 10, 100, and 1000

mg/L in the liquid phase. These nitrogen levels reflect common ranges used in both batch and in

biofilter applications (Yang et al. 2002; Gribbins and Loehr 1998). Concentrations of0O g N/L

were also included to assess whether the cultures could degrade methanol with only soluble cell

nitrogen or atmospheric N2 preSent, as such a condition might be expected if nutrients become

exhausted in a biofilter or even in a batch culture.

The last transfer of the enrichment cultures was made to a 2400 mL flask, in which 500

mL of the culture was grown to%3/ log phase, harvested by centrifugation in a J2-HS Beckman

floor model centrifuge (Beckman Coulter, Inc., Fullerton, CA, USA), then twice washed with

phosphate buffer and recentrifuged to remove residual nitrogen and methanol. Cells were

resuspended in the appropriate mineral salts medium with no added nitrogen to obtain an optical

density of 0. 1 at 600nm. For each combination of nitrogen and carbon concentrations, a master

mixture of cells and medium in a 1:10 ratio was prepared. Liquid methanol was added to the

mixture to the desired concentration, and 4 mL from each master mixture was aliquotted into 20

mL glass vials and sealed with crimp top Teflon-lined septa. Three identical cultures were

prepared for each of the nine nitrogen and methanol combinations. Control vials were prepared

with killed cells and with no cells, to account for any methanol that might be removed by

physical adsorption to the cells or volatilized during the handling and analysis process. The

cultures were incubated for 48 hours on a rotary shaker at 250 rpm and 30 oC. Every 4-6 hours

during this incubation, growth, assayed by optical density, was measured using a

spectrophotometer at 600 nm, directly from the sample in the glass vial. At 48 hours, the cells

were pelleted using the floor centrifuge, and 2 mL of the liquid supernatant were collected and









analyzed for final methanol concentration. Aqueous methanol concentrations were analyzed by

GC/FID using a Clarus 500 (PerkinElmer, Wellesley, MA, USA), with helium at 31.3 psig as the

carrier gas, and hydrogen and air at 45 mL/min and 450 mL/min, respectively, as combustion

gases. Cyclohexanol was used as the internal standard.

Diversity of Microbial Populations in Cultures Enriched with Different Nitrogen Sources

To determine the genetic diversity of the bacterial populations enriched from both

samples with both nitrogen sources, denaturing gradient gel electrophoresis (DGGE) was

performed using the polymerase chain reaction (PCR)-amplified DNA extracted from the

enriched cultures and from the original biofilm samples. Genomic DNA was extracted from the

same SA and SB cultures in both AMS and NMS that were used to initiate the methanol

oxidation study, using UltraClean Microbial DNA kits (MO BIO Laboratories, Carlsbad, CA,

USA) and the accompanying protocol for DNA extraction and purification from microbial

samples. In addition, DNA was extracted from the original SA and SB biofilm samples using

UltraClean Soil DNA kits (MO BIO Laboratories, Carlsbad, CA, USA) and the accompanying

protocol for DNA extraction.

The polymerase chain reaction (PCR) was used to amplify specific DNA sequences

found in expected methylotrophic (methanol-oxidizing) populations in the biofilm. In all known

gram-negative methylotrophic bacteria, methanol oxidation is catalyzed by the enzyme methanol

dehydrogenase (MDH), the large subunit of which is encoded by the highly conserved functional

gene mxa~F (Barta and Hanson, 1993; McDonald and Murrell, 1997). Therefore, mxaF-specific

primers fl003 (5'-3' GCC CGC CGC GCC CCG CGC CCG TCC CGC CGC CCC CGC CCG

GCG GCA CCA ACT GGG GCT GGT), which includes a 39-bp GC-clamp at the 5' end, and

rl561 (5'-3' GGG CAG CAT GAA GGG CTC CC) were used to detect methylotrophs as









described by McDonald and Murrell (1997) and McDonald et al. (1995). The 16S rRNA

sequences were amplified using primers f27 (5'-3' CGC CCG CCG CGC GCG GGC GGG GCG

GGG GCA CGG GGG GAG AGT TTG ATC MTG GCT CAG), which includes a 40-bp GC

clamp at the 5' end, and r534 (5'-3' ATT ACC GCG GCT GCT GC).

Initial PCR and DGGE conditions were based on Henckel et al. (1999), Fj ellbirkeland et

al. (2001), McDonald et al. (1995), and McDonald and Murrell (1997), but optimized for this

specific system and primer set. The PCR reaction mixture was prepared in 0.2 mL thin-walled

PCR tubes and contained lX MgCl2-free PCR buffer, 1.5 mM MgCl2, 100 uM of each dNTP,1U

Taq polymerase (all from Invitrogen, Carlsbad, CA, USA), 0.5 CM of each primer (Integrated

DNA Technologies, Inc, Coralville, IA, USA.), 1-2 CIL of template DNA (50-100 ng), and sterile

water to a final volume of 50 CIL. Amplifications with mxa~F primers were carried out using a

Mastercycler Personal 5332 thermocycler (Eppendorf North America, Westbury, NY, USA) with

the block preheated to 92 oC, using a reaction program of initial denaturation at 92 oC for 3

minutes, a total of 30 cycles of denaturation (30 seconds at 92 oC), annealing using a touchdown

program (30 seconds per cycle from 60 to 50 oC at -0.5 degrees/cycle for the first 20 cycles and

50 oC for the last 10 cycles), and extension (45 seconds at 72 oC), and a final extension at 72 oC

for four minutes. The same reaction setup was used for the 16s rRNA primers, but with an

annealing touchdown temperature profile of the first 10 cycles from 55 to 50 oC at -0.5 degree/

cycle and the last 20 cycles at 50 oC. The touchdown program was used because it increased

yield and number of bands observed on subsequent DGGE gels, over a set annealing

temperature. PCR products were verified on a 1.2% agarose gel, photographed, and their yield

estimated using ImageJ software (Rasband, 2006) calibrated with a low DNA marker (50-2,000

bp, BioNexus, Inc, Oakland, CA, USA.).









DNA Separation using DGGE

DNA fragments were separated using denaturing gel gradient electrophoresis (DGGE)

with a 16xl6 cm, 1 mm thick gel containing 6% acrylamide, lX TAE, and a linear gradient of

35-65% denaturant (100% denaturant is equivalent to 7 M urea and 40% formamide), cast for 90

minutes. Approximately 500 ng of PCR product was mixed with 10-20 CIL of 2X gel loading

dye (70% glycerol, 0.05% Bromophenol Blue, 2mM EDTA), loaded on the gel, and

electrophoresed at 60 oC for 5 hours at 150V in lX TAE, using a DCode Universal Mutation

Detection System Model 475 Gradient Delivery System (Bio-Rad Laboratories, Hercules, CA,

USA). Gels were stained with 50 Clg/mL ethidium bromide in lX TAE for 15 minutes and

destined in lX TAE for 10 minutes. Bands were visualized and photographed using a Fisher

Biotech Model 88A variable UV intensity Transilluminator and DCode DocIt software system

(Bio-Rad Laboratories, Hercules, CA, USA).

DGGE Image Analysis

The digitized gel images were analyzed using ImageJ (Rasband 2006). The background

was subtracted using a rolling ball radius of 50. Bands in each lane were automatically detected

and plotted. Peak area and relative intensity of each band was measured, and bands contributing

less than 1% to the total intensity within one lane were omitted from subsequent analysis.

Diversity Measurements

Diversity in each sample was estimated using measurements of species richness (S),

diversity (H), and evenness (E). S was determined by simply counting the bands in each lane,

with the assumption that a single species would migrate to each unique location. Shannon's H

(Hayek and Buzas 1997) was used as a diversity index (Equation 3-1).


H = -p, In(p,) (3-1)









where pi is the relative intensity of the ith band compared to the total intensity of all bands in that

lane. E was calculated from Pielou's evenness (Equation 3-2) (Hayek and Buzas 1997).


E =- (3-2)
In(S)

DNA Sequencing and Phylogenetic Analysis

To further characterize the bacteria under both nitrogen use profiles, selected bands from

the mxaF and 16s rRNA DGGE gels were excised for sequencing. Bands were chosen from

DNA that showed the highest intensity when visualized on the UV transilluminator and were

excised using a sterile pipet tip and scalpel. The gel fragments were eluted overnight at 30 oC at

250 rpm in 30 CIL of an elution buffer containing 10mM Tris-Cl (pH 7.5), 50 mM NaC1, and

ImM EDTA (pH 8.0) (Chory and Pollard 1999). Gel fragments were removed, and DNA was

precipitated from the liquid by adding 50 CIL of 95% cold ethanol, chilling 30 minutes at -40 oC,

and pelleting the DNA by centrifuging 10 minutes at 10,000xg. After pouring off the ethanol

supernatant, the pellet was dried at 40 oC for 4-5 hours and resuspended in 30 CIL of TE buffer

(Chory and Pollard 1999). This template was reamplified using the same methods as described

previously and checked on a DGGE gel for purity and for migration to the same gradient position

as in the original sample. Sequencing was performed at the University of Florida

Interdisciplinary Center for Biotechnology Research (ICBR) using the fluorescent dideoxy

terminator method of cycle sequencing on either a Perkin Elmer Applied Biosystems Division

(PE/ABD) 373A or 377 automated DNA sequencer, following ABD protocols, with consensus

sequences generated using the Sequencher Software from Gene Codes. Sequences of partial

mxaF and 16s rRNA gene fragments have been deposited in the GenBank database. Fragments

Ml, M3, and M6 were identical to bands sequenced from biofilter samples (Babbitt et al. 2007),

which have previously been submitted under accession numbers EU099402, EU099404, and









EU099407, respectively. For this study, mxaF fragments M2, M4, and M5 were submitted under

accession numbers EUl38867, EUl38868, and EU 138869, respectively; and 16s rRNA

fragments Ul-U7 were submitted under accession numbers EUl38870-EUl38876, respectively.

Published sequences with high similarity to sample sequences were obtained by

performing a nucleotide-nucleotide BLAST (NCBI) search. The 10 most similar sequences of

known species with E scores lower than 1E-20 were chosen for each sample, with duplicates

removed. Sequences were aligned using ClustalW, with default gap penalties, and manual

inspection and refinement of alignments. A phylogenetic tree was constructed using the

Neighbor Joining method and bootstrapped with 1,000 replicates. Because all known y-

proteobacteria clustered into a distinct branch, this group was selected as the out-group. All

phylogenetic and molecular evolution analyses were conducted using MEGA version 3.1 (Kumar

et al. 2004).

Results and Discussion

Comparison of Growth and Methanol Degradation Using Two Types of Nitrogen Source

The two pulp mill biofilm samples (SA and SB), enriched using different nitrogen

sources, were compared on the basis of methanol degradation under different methanol and

nitrogen concentrations. Both samples, regardless of nitrogen source or concentration, showed

100% methanol removal for initial methanol concentrations of 10 and 100 mg/L. Differences

among the cultures became apparent when methanol was introduced at concentrations of 1,000

mg/L. The percent of methanol removed, based on an initial 1,000 mg/L concentration, is shown

in Figure 3-1. For all of the cultures, the percent of methanol removed from the liquid phase

increased with increasing nitrogen concentration. In addition, for all of the cultures assessed in

medium with added nitrogen, a higher methanol removal was achieved when nitrate served as









the nitrogen source. In fact, the SB culture enriched in NMS medium with the highest

concentration of nitrate (0.26 g N/L) showed 100% removal. On the other hand, after transfer to

medium with no added nitrogen, both SA cultures showed significantly higher methanol removal

than SB, regardless of the original enrichment N-source.

A slightly different trend was observed when comparing growth rate with an initial 1,000

mg/L methanol concentration and varied nitrogen sources and concentrations (Figure 3-2).

These results showed that the mixed cultures grew almost equally as fast with either ammonium

or nitrate present at the high (0.26 g N/L) or medium (0.13 g N/L) concentrations tested. Growth

rate slightly increased when NMS was used, but the trends were not as dramatic as when

comparing methanol removal. For example, for nitrogen levels of 0.26 g N/L, SA exhibited

growth at 0.061 hr- in AMS and 0.068 hr- in NMS; and SB grew at a rate of 0.062 hr- in AMS

and 0.074 hr- in NMS. However, the growth rate was significantly lower when the cultures

were cultured in the presence of no added nitrogen in either form (Figure 3-2).

Diversity of Microbial Populations in Cultures Enriched with Different Nitrogen Sources

To expand growth and activity comparisons to the community level of the enriched

samples, DGGE was used to separate DNA fragments amplified for methylotrophs and all

bacteria from the original biofilm samples and their enrichments, as shown in Figure 3-3.

Quantitative estimates of diversity, based on banding patterns in the DGGE gels, are provided in

Table 3-1. Results obtained for methylotrophs and universal bacteria were not compared

directly, because different primer sets can amplify entirely different populations; however, both

sets of results were used for determining trends in the population changes for the nitrogen

sources used. The results in Table 3-1 showed consistent trends among the different enrichment

and molecular methods, except for the methylotrophs enriched from SA, where regardless of









which nitrogen source was used, the diversity of this type of bacteria dropped to zero, with

potentially only one dominant methylotrophic species present. When comparing methylotrophs

in SB and all bacteria in SA, species richness, diversity, and evenness generally showed a

smaller decrease from the quantities observed in the original biofilm culture to the levels shown

in the enriched culture. It was interesting to note that in all the cases, the diversity metrics were

greater for the mixed cultures enriched using nitrate, as compared to ammonium, as the nitrogen

source. This result could potentially correspond to the observation that cultures enriched in

nitrate also showed higher methanol removal and growth rate.

Phylogenetic Analysis of Dominant Species

The genetic comparisons among the cultures were expanded by selecting dominant

species within each culture and determining their mxa-F or 16s rRNA sequence and phylogenetic

relationship to other closely related known bacteria. All excised and sequenced bands are

denoted in Figures 3-3A and 3-3B, as indicated by circles placed adj acent to sequenced bands.

The phylogenic relationships among the species dominating the cultures in these experiments

and known bacteria are shown in Figures 3-4 and 3-5.

Figure 3-4 shows the distribution of selected and recovered dominant bands that were

produced by amplifying the functional gene for methanol dehydrogenase. Bands from the six

samples show similarity to sequences found in the alpha-, beta-, and gamma-proteobacteria.

Dominant bands from the original SA biofilm species are labeled as Ml, which appears closely

related to beta-proteobacteria M~ethylophihts methylotrophus, a ribulose monophosphate (RuMP)

cycle restricted facultative methylotroph; and M6, which shows the greatest genetic similarity to

a dominant species from the SB biofilm (MS), and both are grouped with other alpha-

proteobacteria in the order Rhizobiales. Interestingly, enriching SA in AMS or NMS produced









similar nzxa~F profies that appear to be dominated by a single methylotroph, band M3, which is

not visible in the original culture, possibly because its DNA was present in too small a

concentration to be amplified sufficiently for visualization in the DGGE gel. Band M3 showed

high sequence similarity to one cluster within the genus Hyphomicrobium, bacteria also

classified as non-N2 Eixing, restrictive facultative methylotrophs, but which use the serine

pathway and are members of the alpha-Proteobacteria (Lidstrom 2006; Rainey et al. 1998). The

community shift observed when enriching SB in AMS or NMS was not as consistent as with SA.

M2, a strong band from enrichments of SB in AMS, appeared to be closely related to a species

within the genera of2~ethylovorus, an RuMP pathway, restrictive facultative methylotrophs

classified as beta-Proteobacteria (Doronina et al. 2005). However, M3 was also present for SB

enriched in NMS, as is band M4, which has a highly similar nzxa~F sequence.

As shown in Figure 3-5, dominant bands obtained from 16s rRNA of the samples also

showed wide distribution among the alpha-, beta-, and gamma-proteobacteria and no consistent

community structure under either enrichment profie. The original SA bioHilm sample had three

sequenced dominant bands: U3, U4, and U7. Band U3 was most similar to three Pseudonzona~s

speci es (gamma-Proteob acteri a); b and U4 was grouped with a Buradyrhizobium speci es (alpha-

Proteobacteria); and band U7 was highly similar to several Jhiobacillus species (sulfur oxidizing

chemolithoautotrophic b eta-Proteobacteria) On enrichment in AMS, one dominant band was

shown, US, which was grouped with one cluster of the Hyphomicrobium, a similar result to what

was observed when using nzxa~F primers. Although U5 also appeared to be present in the SA

NMS enrichment, that was not confirmed by sequencing. However, the dominant SA NMS

bands were U2 and U6, which were most similar in 16s rRNA sequence to methylotrophs found

in the beta-Proteobacteria, including serine cycle methylotrophs in the family Rhodocyclaceae









and RuMP cycle methylotrophs in the family M\~ethylophilaceae, respectively. The original SB

biofilm sample was dominated by one band, U7, which was also found in SA and described

above. SB enriched in AMS produced an intense band, Ul, with a 16s rRNA sequence similar to

several M~ethylobacillus species. SB enriched in NMS produced multiple strong bands, although

only one was able to be recovered and sequenced, U2, which was also found in SA-NMS and

shown to be similar to methylotrophic beta-Proteobacteria.

Conclusions

Results from this study illustrated that the type and concentration of nitrogen source used

when enriching mixed methylotrophic cultures from samples removed from a pulp mill does

influence the growth and methanol degradation ability of these bacteria. Generally, the cultures

enriched with nitrate showed faster growth and higher methanol removal than those enriched

with ammonium. Higher concentrations of nitrogen in either form also resulted in greater

methanol removal in all cases. The form of nitrogen used also affected the diversity and

community structure of the methylotrophic populations present in each of the final cultures.

Although the enrichment process did decrease the overall diversity from the original samples, the

cultures grown with nitrate as nitrogen source preserved a higher level of species number,

diversity, and evenness than those grown with ammonium. Based on the results reported herein,

nitrate is recommended to be used as the nitrogen source when enriching or working with

methylotrophic cultures from pulp and paper mills, and should be investigated further as a

nutrient addition to biofilters.











Table 3-1. Bacterial species, diversity, and evenness for SA and SB cultures in both AMS and
NMS media
Methylotrophs Universal
(mxaF) (16s rRNA)
Sample S H E S H E
SA 4 1.04 0.75 9 2.02 0.92

SA-AMS 1 0 0 3 1.06 0.96

SA-NMS 1 0 0 7 1.74 0.89


SB 5 1.56 0.97 10 2.09

SB -AM S 2 0.34 0.49 8 1 .48

SB-NMS 6 1.39 0.78 9 1.90

Species richness is indicated by "S," diversity is indicated by "H,"
"E."


0.91

0.71

0.87
and evenness is indicated by


100

90

80

F70
0
a 60

c 50

40

a,30

20

10

0


0 g N/L 0.13 g N/L 0.26 g N/L
Nitrogen concentration in growth media


Figure 3-1. Comparison of methanol removal by SA and SB cultures in both AMS and NMS
medium with an initial methanol concentration of 1,000 mg/L.
















0 08


0 07 L" ''' f

O5 06 -l



0 0 05- -


C 0 04--



r*r 0 03 -

e 0 02-


O 01 -



O g N/L 0 13 g N/L 0 26 g N/L
Nitrogen concentration in growth media


Figure 3-2. Comparison of batch growth rates in SA and SB cultures in both AMS and NMS
medium with an initial methanol concentration of 1,000 mg/L.












A: PCR-DGGE with mxaF-specific primers


B: PCR-DGGE with universal 16s rRNA primers


M1- e -


Ul-


M2-



M3-
M4-



M5-


U5-
U6-


e.... O.. ,
e-rli c ~ u

e-


e m
e-


U7-e -


All-***


SA SA SA SB SB SB
Biofilm AMS NMS Biofilm AMS NMS


SA SA SA SB SB SB
Biofilm AMS NMS Biofilm AMS NMS


Figure 3-3. Bacterial diversity measured using PCR-DGGE analysis. A) Using mxaF primers. B)
Using 16s rRNA primers. Bands marked with a circle were excised and sequenced, and
all marked bands on a vertical gradient labeled by M (methylotrophs) or U (universal)
were confirmed as identical in sequence.


































































I


1~111


87 Methylobacterium extorquens
97 Methylobacterium rhodinum

Methylobacterium dichloromethanicum
-Methylobacterium podarium
90
-Methylobacterium zatmanii

S r( ~ Afpia felis
100
S Methylobacterium organophilum
Methylobacterium jeotgali
94 Methylocystis aldrichii
Methylocystis heyeril
911 Methylocystis panrus
Methylosinus trichosporium
100~ Methylosinus sporium
Methylorhabdus multivorans
Methylocella silvestris
Beijerinckia mobilis
M5
M6

Angulomicrobium tetraedale
811 Paracoccus denitrificans

99 Methylopila capsulata
78 Albibacter methyloverans
Methylosulfonomonas methylovera
Hyphomicrobium zavarzinii
99~ Hyphomicrobium vulgare
Hyphomicrobium aestuaril
94 Hyphomicrobium facile
100 M3
90 IM

751 Hyphomicrobium denitrificans
Hyphomicrobium methylovnrum
100 M
Methylovnrus sp SS1


Methylotrophs (mxa- F)

Dominant In

SA-biofilm sample

SB-AMS

SA-AMS; SA-NMS; SB-NM

SA-AMS; SA-NMS; SB-NM

SB-biofilm sample

SA-biofilm sample


Band
M1

M2

M3

M4

M5

M6


98


100
Methylophilus methylotrophus
Methylobacillus Ragellatus KT
98 Methylobacillus glycogenes
Methylomonas methanica
Methylococcus capsulatus
99~ Methylocaldum sp E10a


Figure 3-4. Phylogenetic reconstruction of known methylotrophic bacteria and unknown culture
strains using mxaF gene sequences (Bootstrap values represent 1,000 replicates, and
values greater than 75% are shown).












98 Methylobacterium extorquens
80 Methylobacterium dichloromethanicum
1001 Methylobacterium podarium
94 Methylobacterium organophilum
Chelatococcus asaccharoverans
U4

as 94 Bradyrhizobium sp.
92 Methylocystis parvu~s
Methylocystis aldrichii
911 Methylosinus sporium
99 Methylosinus trichosporium
Hyphomicrobium vulgare

10 Hyphomicrobium hollandicum
Hyphomicrobium aestuarii
98 Hyphomicrobium zavarzinii
Hyphomicrobium methyloverum

100 U
86r Hyphomicrobium facile
Hyphomicrobium denitrificans
Thiobacillus sajanensis
98 Thiobacillus sayanicus
93 U7
Thiobacillus denitrificans
U6
92
100 I Methylo\Rrsatilis universalis

Cupriavidus sp. cmp2
77 Leptothrix sp. L18

100 Methylouorus glucosetrophus
Methylouorus mays
97 Methylophilus sp. ECd~s
99 Methylotenera mobila
U2

Methylobacillus pratensis
96 U1
89 Methylobacillus Ragellatus


Universal (16s rRNA)


Band Dominant In
U1 SB-AMS

U2 SA-NMS and SB-NMS

U3 SA-biofilm sample

U4 SA-biofilm sample

U5 SA-AMS

U6 SA-NMS
SA-biofilm sample and
U7
SB-biofilm sample













91


U3

10 Pseudomonas multiresinivorans
g g Pseudomonas alcaligenes
96 Pseudomonas stutzeri



Figure 3-5. Phylogenetic reconstruction of known bacteria and unknown culture strains using 16s
rRNA gene sequences (Bootstrap values represent 1,000 replicates, and values greater
than 75% are shown).









CHAPTER 4
METHANOL REMOVAL EFFICIENCY AND BACTERIAL DIVERSITY OF AN
ACTIVATED CARBON BIOFILTER

Introduction

The forest products industry produces valuable industrial and consumer products from

wood cellulose, including paper, paperboard, hygiene products, high porosity filters, food

casings, rayon filament, and chemicals such as ethers and acetate. During the chemical

processes that convert wood chips to cellulose pulp, organic compounds naturally present in

wood or produced during pulping are released to air and water (Someshwar and Pinkerton 1992).

In 1998, the U.S. Environmental Protection Agency (U. S. EPA) passed the "Cluster Rule" to

regulate the release of these compounds, including hazardous air pollutants (HAPs), chemicals

that pose great risk to human or environmental health (U.S. EPA 1998). Methanol is the primary

focus of these regulations, as it is released in quantities of over 44,000 tons per year, over 70% of

the total HAPs emitted by this industry (U. S. EPA 2004), and can contribute to human health

impacts such as cancer, respiratory irritation, and damage to the nervous system (U. S. EPA

1998).

To prevent potential environmental and health impacts from methanol emissions, the

Cluster Rule requires implementation of maximum available control technology (MACT) to

collect and treat non-condensable gas from high-volume (10,000-30,000 acfm), low-

concentration (below the lower explosion limit of the gas mixture) (HVLC) sources, including

pulp washing and screening, oxygen delignification, and weak black liquor storage tanks (Varma

2003). Most mills comply with MACT regulations by collection of HAPs in vent hoods and

subsequent oxidation in power boilers, stand-alone thermal oxidizers, or recovery furnaces

(Varma 2003).









Despite the effectiveness of oxidation in destroying HAPs such as methanol, the

drawbacks of requiring natural gas to support incineration, increased production of CO2, SO2,

and NO, emissions, and high capital costs for installation and infrastructure have motivated a

desire for more environmentally and economically beneficial technologies (Mycock et al. 1995;

Schnelle and Brown 2002). One potential alternative to thermal oxidation is the use of a

granular activated carbon (GAC) biofilter as a polishing step in combination with a primary

treatment system using photocatalytic oxidation (Stokke et al. 2006; Tao et al. 2006). Although

biofilters traditionally have contained a fixed bed of inert organic packing that serves as biomass

support and nutrient support (Devinny et al. 1999; Kennes and Thalasso 1998; Kennes and Veiga

2001), more recent work has shown the potential advantages of using surface active packing

such as GAC (Aizpuru et al. 2003; Prado et al. 2002; Teran-Perez et al. 2002; Yang et al. 2002).

The activated carbon adsorbs VOCs from the process stream, creating a favorable environment

for a stable microbial biofilm that subsequently degrades the contaminants (Aizpuru et al. 2003;

Chang and Rittman 1987; Herzberg et al. 2003; Hodge and Devinny 1994; Weber and Hartmans

1995; Zhang et al. 1991).

While recent studies (e.g., Aizpuru et al. 2003; Chung 2007; Liang et al. 2007) have

demonstrated excellent performance of activated carbon biofilters for contaminant removal, a

potential challenge to their use is the lack of inherent nutrients, moisture, and microorganisms

that would typically be found in an organic packing such as compost (Devinny et al. 1999).

Furthermore, little is known about the structure and dynamics of bacterial communities that

colonize GAC biofilters. Therefore, the overall goal of this work was to develop and

characterize a bench-scale activated carbon biofilter in removing methanol at concentrations

typically observed in pulp mill air effluents and to observe the bacterial diversity during the









bioHilter operation. This bench-scale bioHilter used a novel heterogeneous packing blend

containing granular activated carbon as the primary filter medium, mixed with perlite, slow-

release ammonium nitrate pellets, and water-retaining crystals, which were added to minimize

pressure drop, provide continuous nutrient input, and minimize bioHilter drying, respectively.

Studies on this biofilter system were carried out to meet three primary obj ectives: 1) to

demonstrate the methanol removal efficiency of the bench-scale activated carbon biofilter, 2) to

use denaturing gel gradient electrophoresis (DGGE) methods, in addition to culture-dependent

methods, to characterize the abundance, diversity, and spatial distribution of bacteria colonizing

the novel packing media; and 3) to use DGGE methods to assess similarities and differences in

stable bioailm communities in bioHilters with and without an inoculum specifically cultured for

methanol-degrading bacteria. The results of this work are reported herein and show promise for

the development of activated carbon bioailtration systems as an effective option for methanol

control for the pulp and paper industry.

Materials and Methods

Selection of Biological Inoculum

Potential bioHilter inocula were obtained from a pulp and paperboard company located in

the Southeast that uses a biological waste water treatment system. Seven grab samples of

bioHilm were collected during June 2004 from locations at this mill suspected to foster conditions

for enrichment of bacteria, including methanol-degrading consortia, and stored on ice in

sterilized Teflon collection vessels until they could be processed in the lab or stored over a

longer term at 4 oC. The collection locations of these samples were cooling tower baffles, an

oxygen activated sludge reactor (UNOX reactor, or Union Carbide pure oxygen reactor), a

secondary clarifier, mixed liquor, and return activated sludge from the clarifier.









From each sample, 10 mL or 10 g was homogenized with a phosphate buffer on a rotary

shaker at 30 oC and 250 rpm for one hour. A 5 mL sample of the homogenized mixture was used

to start a batch enrichment culture in a modified nitrate mineral salts medium (NMS) containing

0.2% methanol (vol/vol) as recommended by Hanson (1998). The basal medium contained (on a

g/L basis MgSO4*7H20, 1.0; KNO3, 1.0; CaCl2, 0.2; KH2PO4, 0.026; Na2HPO4, 0.033. Trace

elements were added, on a mg/L basis: FeSO4*7H20, 0.5; ZnSO4*H20, 0.4; EDTA disodium

salt, 0.25; CoCl2*6H20, 0.05; MnCl2*4H20, 0.02; H3BO3, 0.015; NiCl2*6H20, 0.01;

Na2MoO4*4H20, 0.005; and FeEDTA, 0.0038. Vitamins were added, on a mg/L basis: biotin,

0.02; folic acid, 0.02; thiamin*HC1, 0.05; calcium pantothenate, 0.05; riboflavin, 0.05;

nicotinamide, 0.05; and Bl2, 0.001. All chemicals used were obtained from Fisher Scientific

(Pittsburgh, PA, USA) or Sigma Aldrich (St. Louis, MO, USA) and were of analytical grade or

higher.

Cultures were maintained in a 1:10 ratio of inoculum:medium in a total volume of 55 mL

in 250 mL Erlenmeyer flasks at 30 oC on a rotary shaker at 250 rpm. Initial cultures were

incubated for one month, and subsequent transfers to fresh medium were made bimonthly. In

order to determine the most suitable biofilter inoculum, a series of culture-dependent growth,

methanol depletion, and characterization studies were performed on these cultures (Chapters 2

and 3). Based on superior growth and methanol degradation rates and morphologically diverse,

culturable community (determined by identification of visibly distinct colonies on agar plates),

the cultures derived from biofilm in the aerated activated sludge UNOX reactor (SA) and from

the return activated sludge (SB) were selected as potential biofilter inoculums. Despite the higher

methanol removal rate of SB demonstrated in Chapter 3, initial trials using this sample as an

inoculum resulted in excessive biomass formation, plugging, and high pressure drop in a









preliminary biofilter trial (data not shown). Therefore, SA was selected as the inoculum for the

final biofilter experiment reported in this chapter.

Selection of Packing Material

Two types of GAC packing, MeadWestvaco Bionuchar 120 (MeadWestvaco, Richmond,

VA, USA) and Calgon F400 (Calgon Carbon Corporation, Pittsburgh, PA, USA), were

compared to determine which would better foster the growth of biofilter bacteria. These two

types of GAC were selected because they are commonly available and are recommended by their

manufacturers for the removal of organic pollutants (MeadWestvaco 2002; Calgon 1996).

Bionuchar, a wood-based, chemically activated GAC with 1.1-1.3 mm particle size, is

specifically marketed as having physical characteristics that allow for maximum fixation of

beneficial biomass (MeadWestvaco 2002). F400 is a bituminous coal-based, physically

activated carbon with a 0.55-0.75 mm particle size (Calgon 1996).

The GACs were compared on the basis of immobilization and growth of the biofilter

inoculum on the carbon surface, measured first by enumerating bacteria in the liquid culture

inoculum and then by enumerating bacteria recovered from the GAC surface after inoculation.

Two inoculation methods were tested. One method involved suspending the biofilter inoculum

in the mineral medium and continuously circulating the inoculum through the packed bed for

seven days. The other method involved flooding the column with the suspended inoculums

incubating the column at 30 oC for four days, followed by draining the column and circulating

fresh medium with methanol for three days. In both cases, a sterile glass column, measuring 10

mm in diameter and 100 mm in length, was used. The inoculum and/or the mineral medium was

delivered to the column from sterile flasks using a peristaltic pump and Teflon tubing.









After both inoculation methods were complete, 5 g of GAC was removed from each

column and rinsed gently with sterile distilled water to remove particles and non-attached

bacteria. The sample was mixed with 5 mL of sterile phosphate-buffered saline (PBS) and

vortexed in 10-second pulses at 2500 rpm for two minutes to transfer biomass from the packing

surface to a liquid suspension. To measure cultivable bacteria, 1 mL aliquots from both the

bioailter inoculum and from the liquid suspension of biomass from the packing were serially

diluted (ten-fold) and spread plated in triplicate on NMS plates containing 0.2% methanol.

Plates were incubated at 30oC for seven days, at which time the total colony forming units

(CFUs) were quantified. The carbon was dried at 45oC for 14 days and then weighed to obtain

an air-dry weight.

Biofilter Design

The bioHilter housing consisted of a clear PVC column with 2-inch diameter, 24-inch

length, and 1,235 mL empty bed volume. The packing was added to a Einal volume of 1,100 mL

dry packing material, composed of a 4:2: 1:1 mixture of GAC, bulking agent (Perlite, Miracle-

Gro, Marysville, OH, USA), slow-release ammonium-nitrate fertilizer (Osmocote, Scotts-Sierra

Horticultural Products, Marysville, OH, USA), and water-retaining crystals (Agrosoke

International, Arlington, TX, USA). This mixture had a bulk density of 412 mg/mL. To

determine the ability of this material to adsorb methanol with no bacteria present, batch

isotherms were performed on small (1-2 g) samples of the packing, added to a 26 mL vial along

with a smaller vial containing 10, 50, or 100 CIL of methanol. The change in weight of the

activated carbon was measured at 24, 48, and 72 hours and at seven days. No change between

48 hours and seven days was observed, and the system was assumed to be at equilibrium. The

adsorption capacity was determined by plotting the ratio of adsorbed methanol mass to the GAC









mass as a function of equilibrium concentration, according to the Freundlich isotherm. Results

of this analysis (data not shown) indicated that the adsorptive capacity of the packing material

would be exhausted in approximately 20 hours and that methanol removal after that time would

likely be attributed to the bacterial activity in the biofilter.

Biofilter Operation and Performance Measurements

The GAC biofilter was inoculated with the selected biofilm culture enriched in a mixed

medium of ammonia and nitrate (composition of NMS described previously, but amended with

0.5 g/L NH4C1), with methanol added to a concentration of 0.2% by volume. A second column,

identical to the GAC biofilter but without the inoculum, was used in parallel to the biofilter to

demonstrate effects, if any, of using a specifically enriched inoculum. The inoculated packed

column will be referred to as "BB" (biologically-inoculated biofilter), and the non-inoculated

packed column will be referred to as "NB" (non-inoculated biofilter) throughout the text. Sterile

technique was used in working with the inoculum cultures and in preparing the columns, and all

tubing, glassware, and the GAC were sterilized by autoclave before use; however, the biofilters

were operated in a non-sterile environment and were periodically exposed to the ambient lab air

for sampling or maintenance purposes.

The biofilters were operated in up-flow mode with an air stream artificially contaminated

with varied methanol concentrations and 90-95% relative humidity (Figure 4-1). The air stream

was generated by splitting a stream from a compressed zero-grade air cylinder, with a small

fraction of air diverted through a methanol bubbler (about 1-5% by volume, depending on the

desired concentration) and the remaining fraction passing through a water bubbler to add

humidity. Upflow mode was selected based on the possible need to add liquid nutrients without









creating a leachate stream and to limit potential acidic byproduct buildup from using an

ammonium based nutrient to the lower fraction of the bed (Devinny et al. 1999).

Biofilter operation was characterized by three consecutive sets of operating conditions,

described here and summarized in Table 4-1. First, the column was operated at a high methanol

loading concentration (10,000 ppmy) and high gas retention time (5 minutes) for 46 days to

allow for bacterial colonization of the activated carbon and acclimatization to high

concentrations. Subsequently, for days 47-108, the operating conditions included methanol

concentrations below 100 ppmy and a retention time of one minute. Finally, for the last 30 days,

the concentration was increased to 1,000 ppmy while maintaining a retention time of one minute.

The stepwise changes in concentration between each set of operating conditions were used to

replicate a wide variability of conditions that could be expected in an industrial setting.

Column inlet and outlet gas concentrations were determined by the NCASI chilled

impinger method (NCASI, 1998), with two midget impingers (ARS, Gainesville, FL, USA) in

series, each containing 20 mL of nanopure water in an ice bath. Methanol concentrations were

analyzed by GC/FID using a Clarus 500 (PerkinElmer, Wellesley, MA, USA), with helium at

31.3 psig as the carrier gas, and hydrogen and air at 45 mL/min and 450 mL/min, respectively, as

combustion gases. Cyclohexanol was used as the internal standard.

Abundance and Diversity of Microbial Populations in the Biofilter

Samples were collected from both biofilters by removing about 5 g (wet weight) of

packing material from the middle of the column using sterile instruments on days 22, 46, 77,

102, 125, and 138, which provided two samples during each of the three operating conditions

described previously. The non-inoculated column was not sampled on day 22 because visible

growth of biofilm on the carbon surface had not yet formed. At the conclusion of the









experiment, packing material was also sampled from the inlet and outlet of the column. Each

packing sample was first rinsed gently with sterile distilled water to remove particles and non-

attached bacteria. Then the sample was mixed with 5 mL of sterile phosphate-buffered saline

(PB S) and vortexed in 10-second pulses at 2500 rpm for a total of two minutes to transfer

biomass from the packing surface to liquid suspension.

To determine bacterial abundance as a function of length along the column, the liquid

suspension from samples at the top, middle, and bottom of the biofilters from day 13 8 were

serially diluted eight-fold, and 100 CIL aliquots were spread on agar plates. Three types of agar

plates were used, nitrate mineral salts and ammonium mineral salts with methanol added in the

vapor phase and nutrient agar with mixed N- and C-sources and no methanol added. Plates were

incubated at 30 oC for seven days. Results were compared using one-way ANOVA and post-hoc

comparisons among all groups, using SPSS 8.0 (Chicago, IL, USA).

DNA Extraction and Amplification

DNA was extracted from the liquid suspension from column samples using UltraClean

Microbial DNA kits (MO BIO Laboratories, Carlsbad, CA, USA) and the accompanying

protocol. It has been reported that results obtained from this type of indirect approach are

comparable to those obtained from direct lysis from cells attached to the packing (Li and Moe

2004). The polymerase chain reaction (PCR) was used to amplify specific DNA sequences

found in expected methylotrophic (methanol-oxidizing) populations in the biofilm. In all known

gram-negative methylotrophic bacteria, methanol oxidation is catalyzed by the enzyme methanol

dehydrogenase (MDH), the large subunit of which is encoded by the highly conserved functional

gene mxa~F (Barta and Hanson 1993; McDonald and Murrell 1997). Therefore, mxaF-specific

primers fl003 (5'-3' GCC CGC CGC GCC CCG CGC CCG TCC CGC CGC CCC CGC CCG









GCG GCA CCA ACT GGG GCT GGT), which includes a 39-bp GC-clamp at the 5' end, and

rl561 (5'-3' GGG CAG CAT GAA GGG CTC CC) were used to detect methylotrophs as

described by McDonald and Murrell (1997) and McDonald et al. (1995). The 16S rRNA

sequences were amplified using primers f27 (5'-3' CGC CCG CCG CGC GCG GGC GGG GCG

GGG GCA CGG GGG GAG AGT TTG ATC MTG GCT CAG), which includes a 40-bp GC

clamp at the 5' end, and r518 (5'-3' ATT ACC GCG GCT GCT GC).

Initial PCR and DGGE conditions were based on Henckel et al. (1999), Fj ellbirkeland et

al. (2001), McDonald et al. (1995), McDonald and Murrell (1997), but optimized for this specific

system and primer set. The PCR reaction mixture was prepared in 0.2 mL thin-walled PCR

tubes and contained lX MgCl2-free PCR buffer, 1.5 mM MgCl2, 100 uM of each dNTP,1U Taxq

polymerase (all from Invitrogen, Carlsbad, CA, USA), 0.5 CM of each primer (Integrated DNA

Technologies, Inc, Coralville, IA, USA), 1-2 CIL of template DNA (50-100 ng), and sterile water

to a final volume of 50 CIL. Amplifications with mxa~F primers were carried out using a

Mastercycler Personal 5332 thermocycler (Eppendorf North America, Westbury, NY, USA) with

the block preheated to 92 oC, using a reaction program of initial denaturation at 92 oC for 3

minutes, a total of 30 cycles of denaturation (30 seconds at 92 oC), annealing using a touchdown

program (30 seconds per cycle from 60 to 50 oC at -0.5 degree/cycle for the first 20 cycles and

50 oC for the last 10 cycles), and extension (45 seconds at 72 oC), and a final extension at 72 oC

for four minutes. The same reaction setup was used for the 16s rRNA primers, but with an

annealing touchdown temperature profile of the first 10 cycles from 55 to 50 oC at -0.5 deg/cycle

and the last 20 cycles at 50 oC. The touchdown program was used because it increased yield and

number of bands observed on subsequent DGGE gels, over a set annealing temperature. PCR

products were verified on a 1.2% agarose gel, photographed, and their yield estimated using









ImageJ software (Rasband, 2006) calibrated with a low DNA marker (50-2,000 bp, BioNexus,

Inc, Oakland, CA, USA.).

DNA Separation and Analysis

DNA fragments were separated using denaturing gel gradient electrophoresis (DGGE)

with a 16xl6 cm, 1 mm thick gel containing 6% acrylamide, lX TAE, and a linear gradient of

35-65% denaturant (100% denaturant is equivalent to 7 M urea and 40% formamide), cast for 90

minutes. Approximately 500 ng of PCR product was mixed with 10-20 CIL of 2X gel loading

dye (70% glycerol, 0.05% Bromophenol Blue, 2mM EDTA), loaded on the gel, and

electrophoresed at 60 oC for 5 hours at 150V in lX TAE, using a DCode Universal Mutation

Detection System Model 475 Gradient Delivery System (Bio-Rad Laboratories, Hercules, CA,

USA). Gels were stained with 50 Clg/mL ethidium bromide in lX TAE for 15 minutes and

destined in lX TAE for 10 minutes. Bands were visualized and photographed using a Fisher

Biotech Model 88A variable UV intensity Transilluminator and DCode DocIt software system

(Bio-Rad Laboratories, Hercules, CA, USA).

DGGE Image Analysis

The digitized gel images were analyzed using ImageJ (Rasband 2006). The background

was subtracted using a rolling ball radius of 50. Bands in each lane were automatically detected

and plotted. Peak area and relative intensity of each band was measured, and bands contributing

less than 1% to the total intensity within one lane were omitted from subsequent analysis. No

comparisons were made between different gels, because no internal standard was used. No

comparisons were made between gels from the two primer sets, although the two were compared

based on trends in banding patterns among the samples. A distance matrix for pairwise

comparisons between lanes was generated by the unweighted Gower's distance (Equation 4-1),










D =1 1 -2, (4-1)
P R,

where P is the total number of bands being compared, yl and y2 are the band intensities for the

two lanes being compared, and R is the largest difference found across all bands in the gel

(Legendre and Legendre 1998). This matrix, generated with Mathcad 13 (Mathsoft, Parametric

Technologies Corporation, Needham, MA, USA), was used for hierarchical clustering with the

unweighted pair group method with arithmetic mean (UPGMA), constructed using MEGA

version 3.1 (Kumar et al. 2004).

DNA Sequencing and Phylogenetic Analysis

To further characterize the community of methanol-degrading bacteria present during

biofilter operation and in the original inoculum, selected bands from mxaF-specific DGGE gels

were excised for sequencing. Bands were chosen from mxaF-amplified DNA that showed the

highest intensity when visualized on the UV transilluminator and were excised using a sterile

pipet tip and scalpel. The gel fragments were eluted overnight at 30 oC at 250 rpm in 30 CIL of

an elution buffer containing 10mM Tris-Cl (pH 7.5), 50 mM NaC1, and ImM EDTA (pH 8.0)

(Chory and Pollard 1999). Gel fragments were removed, and DNA was precipitated from the

liquid by adding 50 CIL of 95% cold ethanol, chilling 30 minutes at -40 oC, and pelleting the

DNA by centrifuging 10 minutes at 10,000xg. After pouring off the ethanol supernatant, the

pellet was dried at 40 oC for 4-5 hours and resuspended in 30 CIL of TE buffer (Chory and

Pollard 1999). This template was reamplified using the same methods as described previously

and checked on a DGGE gel for purity and for migration to the same gradient position as in the

original sample. Sequencing was performed at the University of Florida Interdisciplinary Center

for Biotechnology Research (ICBR) using the fluorescent dideoxy terminator method of cycle

sequencing on either a Perkin Elmer Applied Biosystems Division (PE/ABD) 373A or 377









automated DNA sequencer, following ABD protocols, with consensus sequences generated using

the Sequencher Software from Gene Codes. Sequences of partial mxaF gene fragments have

been deposited in the GenBank database under accession numbers EU099402 through

EU099407.

Published sequences with high similarity to sample sequences were obtained by

performing a nucleotide-nucleotide BLAST (NCBI) search. The 10 most similar sequences of

known species with E scores lower than 1E-20 were chosen for each sample, with duplicates

removed. Sequences were aligned using ClustalW, with default gap penalties, and manual

inspection and refinement of alignments. A phylogenetic tree was constructed using the

Neighbor Joining method and bootstrapped with 1,000 replicates. Because all known y-

proteobacteria clustered into a distinct branch, this group was selected as the out-group. All

phylogenetic and molecular evolution analyses were conducted using 1VEGA version 3.1 (Kumar

et al. 2004).

Results and Discussion

Biofilter Design

Results of the comparisons of granular activated carbon (GAC), Westvaco Bionuchar and

Calgon F400, using two inoculation methods are shown in Table 4-2. Both inoculation methods

worked well for colonizing the biofilter with an active microbial population. However, the

Bionuchar GAC supported a significantly higher number of and increase in colonies and a visible

biofilm, as compared to the Calgon GAC. The larger particle size of the Bionuchar likely

created larger void spaces within the packed bed, allowing for better transport of oxygen through

the biofilter for maintenance of aerobic inoculum cultures, less plugging with excess biomass,

and increased nutrient availability to attached bacteria.









Based on these results, the Bionuchar GAC was used for all subsequent bioailter

experiments. No apparent difference was observed between the two inoculation methods in their

ability to adequately introduce the microbial inoculum to the GAC packing. Simply for ease of

setup and maintenance, the flood and drain method was selected for subsequent biofilter

experiments.

Biofilter Performance

The performance of the bioHilter for methanol removal is shown in Figure 4-2, where

removal efficiency (%) of both the biologically inoculated biofilter (BB) and non-inoculated

biofilter (NB) is plotted as a function of time, along with the methanol loading rate to the

biofilters. Each of the points plotted in Figure 4-2 represents an average for samples collected in

duplicate over the 13 8-day operation of the biofilters. During the first 46 days of operation (at

10,000 ppmy MeOH and 5 min gas retention time), both biofilters showed excellent removal of

methanol, after a lag time of about four days to achieve 100% methanol removal. The BB

showed lower removal over those first four days, which is probably a result of pre-saturation of

the packing material with methanol-laden medium during inoculation. When the methanol

loading rate was rapidly decreased on day 47 (to 100 ppmy MeOH, with 1 min residence time),

the performance of the NB also fell dramatically, with an almost 10-day period before it returned

to 100% removal. When the methanol loading rate was increased to 5 g/m3 packing/hr at day

109 (corresponding to 1,000 ppmy MeOH, with 1 min residence time), both biofilters continued

to perform well. However, the NB showed another decrease in methanol removal at the

conclusion of the trial, between days 133 and 138.

Although the NB did not receive the specifically enriched methanol degrading bacterial

inoculum, its packing material showed a visible biofilm by day 25 (compared to a biofilm









observed on the NB on day 6), likely due to colonization by opportunistic methanol-degrading

bacteria introduced by operation in non sterile conditions. In addition, the NB performed with

almost equivalent removal efficiency to the BB, which suggests that the novel packing mixture

used in the biofilters provided an excellent support medium for the immobilization of bacteria

and subsequent bacterially mediated methanol removal, even without addition of a cultured

inoculum. Bacterial growth in non-inoculated systems is not uncommon, for example,

Dusenbury and Canon (2004) reported bacterial growth and contaminant removal in a non-

inoculated activated carbon biofilter, even with periodic additions of chlorine bleach solution to

deter biological growth. It is believed that, despite the lack of introduced inoculum to the NB,

the methanol removal was biological in nature, based on results of adsorption isotherms,

discussed previously.

Bacterial Counts over the Length of the Biofilters

Bacterial counts at the inlet, middle, and outlet of both biofilters at the end of the

operating period were compared for three types of mineral medium, with results shown in Figure

4-3 as colony forming units (CFU) per gram of packing (with standard error from triplicate

measurements). The different types of agar media were used to determine if culturable bacteria

in different regions of the biofilters could be differentiated based on their nitrogen and carbon

requirements. With the exception of the BB inlet and NB outlet, more bacteria were enumerated

on the rich nutrient medium in samples removed from all regions of the columns. For all types

of media, the distribution of bacterial abundance varied significantly among the regions of both

biofilters (F=80.4, p<0.001), with significantly higher abundance in the inlet section for the BB

(post-hoc comparison, all p<0.001), and significantly lower abundance in the inlet section of the

NB (post-hoc comparison, all p<0.012). High abundance in the BB inlet (as compared to its









middle or outlet), where methanol concentrations are expected to be highest, was possibly due to

a population from the inoculum used in the BB already being acclimated to high substrate and

nutrient concentration, from the original mill source and in the inoculum culture enrichment.

High colonization per gram of packing material in the BB may also have contributed to its

continual high methanol removal efficiency (Figure 4-2), which would follow the observations

by Song and Kinney (2000) that microbial respiratory activity in a toluene biofilter was directly

proportional to the number of culturable colonies from the packing material, and that activity and

CFUs were higher at the inlet of the biofilter, where the pollutant concentration was the highest.

Bacterial Diversity Comparisons

The PCR-DGGE approach was used to characterize bacterial diversity for (1) different

operating conditions over time for both the BB and NB and (2) different spatial portions of the

BB and NB at the end of operation. Both assessments were performed using mxaF and 16s

rRNA primers to target methanol-degrading bacteria and all bacteria present, respectively.

Results of these comparisons include gel images and the UPGMA clusters and are shown in

Figures 4-4 and 4-5.

Figure 4-4A shows bacterial diversity in both biofilters from the initial inoculum through

the six sampling times (the day the sample was taken is denoted by the corresponding number at

the bottom of each gel column) that span the three operating conditions (Table 4-1). Considering

methylotrophs, the BB showed a visibly higher bacterial diversity than the NB, which appeared

to contain about half as many species. Increased diversity may relate to observations that the BB

was the more reliable system (Figure 4-2). However, only a single band was observed in

common among the inoculum, BB, and NB, indicating that dominant populations amplified from

the inoculum culture were not dominant in the bacterial community that was observed to rapidly









colonize and be maintained in both biofilters. A potential explanation for this observation was

two-fold: 1) the source of bacterial growth in the NB originated from the BB, as the two were

operated in a connected air flow system and in close proximity to each other, and 2) populations

present in the BB represented such a small fraction of the mixed inoculum culture that they were

not sufficiently amplified by PCR for detection using DGGE. It is not unexpected that a change

in conditions from the enriched culture to the biofilter environment could drastically alter the

bacterial community (Devinny et al. 1999) or that PCR-DGGE methods are unable to detect

bacteria comprising less than ~1% of the total bacterial community (Sercu et al. 2006).

Alternatively, all of the bacterial populations in both the NB and BB could have arisen from

sources outside the inoculum, by operating in non sterile conditions. Either of these possibilities

supported the premise that the biofilters' performance could be attributed to use of the novel

GAC mixture as biofilter packing, rather than to a specifically cultured inoculum, and coincided

with the excellent removal efficiency observed for both the NB and the BB (Figure 4-2).

Banding patterns generated by amplifying 16s rRNA from both biofilters were much

more varied and numerous than mxaF (Fig. 4-4A), which was likely due to the presence of non-

methylotrophic bacteria in the biofilters. This result was consistent with the observation in

Figure 4-3 that more CFUs per gram of packing were counted on heterotrophic plates than on

methylotroph-specific plates. However, similar trends were observed for both primer sets, in that

both biofilters appeared to be colonized by some bacterial populations that were dominant in the

inoculum, as well as others that were not amplified from the inoculum, and that the community

structure generally persisted over time and despite varied operating conditions.

Visual observations were supported by cluster analyses (Figure 4-4B) that took into

account the relative intensity of each band, which corresponded to relative abundance of that









band's DNA in the PCR-amplified sample. UPGMA clustering results can be interpreted as the

similarity between two samples based on similarities in their banding patterns. Although BB and

NB shared some of the same species (Figure 4-4A), bacterial communities in each biofilter

differed based on which populations were most dominant. As shown in Figure 4-4B, the greatest

similarity was among populations within each biofilter, rather than within each time period or

each operating condition or between the biofilters. Because there was no shift in populations

over time or in different operating conditions, it was expected that acclimation or succession of

bacteria in the columns occurred quickly, within in the first 22 days of operation (before the first

DNA sample was extracted). Rapid acclimation could have been due to start up of the column

under very high methanol loading concentrations, which may have created selective pressure for

methylotrophic bacteria that became robust colonizers. Although it is uncertain what role, if any,

the specifically enriched inoculum played in the BB performance, the clustering results suggest

that addition of this culture did somehow influence the diversity and community structure of the

consortium of bacteria that ultimately colonize the BB, possibly by changes to the biofilter

microenvironment, such as surface conditioning or facilitating primary adhesion (Dunne 2002).

Figure 4-5A illustrates the bacterial diversity over three spatial regions in both biofilters,

and Figure 4-5B shows the similarity of banding patterns among these regions. For the

inoculated biofilter, results from PCR-DGGE with mxaF-specific primers and with 16S rRNA

primers show opposing trends in diversity over length. The methylotrophic population appeared

to be most diverse at the BB outlet, where methanol concentration is expected to be the lowest,

whereas populations were more diverse at the inlet when assessed using the universal bacterial

primer. Distributional patterns were much less consistent when using 16s rRNA, which showed

more distinct changes among the three areas sampled in the biofilter, a similar result to the









observation by Li and Moe (2004) that relative abundance of species in a methyl ethyl ketone

biofilter differed significantly as a function of height along the biofilter, likely due to selective

pressures of the changing concentration gradient of introduced pollutant over the biofilter length.

No such trend was clearly evident for the NB system. It was also interesting to compare these

results with counts of culturable bacteria in Figure 4-3 and comparisons of the inoculum and the

BB in Figure 4-4A. For methylotrophs, highest counts of CFUs were at the BB inlet, which,

according to Figure 4-5A was primarily dominated by a single species. In addition, this band

was also shown as being dominant in the inoculum (Figure 4-4A), which supports the possibility

put forth earlier that the ability of this species to thrive in the areas expected to have the highest

methanol concentration may be due to its prior acclimation to these conditions.

Figure 4-5B shows hierarchical cluster analysis for the spatial comparisons, and, for both

amplification methods, indicates that the outlet and middle sections of the BB were very similar

in composition, as compared to the inlet region. Despite the comparable abundance results

between the two biofilters, the similarity-based clustering results indicated that the actual

populations that comprise the total bacterial community at the inlet, middle, or outlet were

actually quite different between the BB and the NB. Although a direct correlation cannot be

made with the data available, the results suggest that growth within each column did vary based

on the type of bacteria present and the means in which they were introduced to the biofilter.

However, this variation did not appear to create any significant differences to observed methanol

removal efficiency (Figure 4-3).

Phylogenetic Analysis of Methylotrophic Bacteria

Selected bands, corresponding to the highest relative intensity, or highest DNA

concentration, amplified with mxaF primers, were excised, reamplified, purified, and sequenced









to determine the phylogeny of selected methylotrophic bacteria in the inoculated biofilter. A

representation of phylogenetic relationship among these samples and known methylotrophic

bacteria is shown in Figure 4-6. Samples are identified by their source (inoculum or BB) and

numbered as shown in Figure 4-4, with bands marked with an X corresponding to those unable

to be reamplified or purified. Limited sequencing for bands excised for different days in the BB

and also in the NB indicated that bands occurring at the same vertical gradient had identical

sequences.

Figure 4-6 shows that species obtained from both the inoculum and the biofilter were

widely distributed across known types of methylotrophs. Inoculum 1 and BB1, corresponding to

inoculum band 1 and BB band 1 (Figure 4-4), appeared to be closely related to species within the

genera of2~ethylophilus, M~ethylovorus, and M~ethylobacillus, non-N2 fixing, restrictive

facultative methylotrophs that follow the ribulose monophosphate (RuMP) pathway for

formaldehyde fixation and are classified as beta-Proteobacteria (Doronina et al. 2005; Lidstrom

2001). BB2, corresponding to BB band 2 (Figure 4-4), was grouped with several

Hyphomicrobium species, which are also non-N2 fixing, restrictive facultative methylotrophs, but

follow the serine pathway and are members of the alpha-Proteobacteria (Lidstrom 2006; Rainey

et al. 1998). BB3 and BB4, denoting BB bands 3 and 4 (Figure 4-4), were also classified with

the alpha-Proteobacteria, but not clustered closely with specific known sequences. However,

BB5 and Inoculum 2, corresponding to BB band 5 and inoculum band 2 (Figure 4-4) and having

identical sequences, appeared to be closely related to Beiferinckia mobilis and M~ethylocella

silvestris, both alpha-Proteobacteria. B. mobilis is known to be heterotrophic, N2-fixing, and use

the ribulose bisphosphate (RuBP) pathway (Dedysh et al. 2005a), while M silvestris is known to

be facultatively methanotrophic, moderately N2-fixing, and use the serine pathway (Dedysh et al.









2005b). Interestingly, both of these species are acidophilic and grow in media as low as pH 3

(Dedysh et al. 2005; Dunfield et al. 2003), and, as observed in Figures 4-4 and 4-5, the band

correlating to this species increased in relative intensity over operation time and at the inlet of the

BB, a region potentially growing more acidic due to operation in upflow mode and some

drainage of liquid in the bioHilter, although this observation could not be corroborated with actual

bioHilter pH measurements.

In addition to specific characteristics about the inoculum and biofilter bacterial species

that are hypothesized based on this phylogenetic reconstruction, a more important observation is

that the bioailters were colonized by a genetically, and likely phenotypically, diverse population

of bacteria, expected to thrive in varied C- and N-usage niches. For example, the presence of

expected N2-fixing bacteria would have allowed continued growth and methanol removal even if

localized nutrient supply was diminished. The observed diversity may have contributed to the

continual high performance of the biofilters over time and in varied operating conditions.

Conclusions

A bench-scale inoculated GAC biofilter (BB) system was demonstrated for the removal

of methanol from an artificially contaminated air stream. The methanol removal efficiency for

this system and an identical, non-inoculated biofilter (NB) were similarly high (~100%) for both

biofilters over the maj ority of operating time. Whereas the performance and abundance results

would indicate that the two biofilters were very similar, an examination of the underlying

microbiology using molecular methods shows that, in fact, they were colonized by very different

populations of bacteria that were distributed differently throughout the length of the biofilters.

Unfortunately, we cannot conclusively relate performance data to specific populations observed.

However, from a broader perspective, the results underscore the need to examine microbial









diversity as part of overall design and operation strategies and performance measurements for

bioHilters, rather than looking at removal efficiency alone.

This work also reports the successful use of a novel heterogeneous bioHilter packing

material. The mixture of activated carbon, which contributed to initial adsorption of the

methanol and may have helped to buffer concentration changes, combined with perlite, slow

release nutrient pellets, and water retaining crystals, provided excellent support for the growth

and activity of methanol degrading bacteria over time and during high variability in operating

conditions. These results show the potential for developing activated carbon bioailtrations

systems as potential technological solutions for methanol control in the pulp and paper industry.
















I


'g/m3 packing/hr 5 min
g/m3 packing/hr 1 min
g/m3 packing/hr 1 min


Table 4-1. Summary ofbiofilter operating conditions
Days Average Methanol A
Condition
Concentration
I 1-46 10,000 ppmy 17
II 47-109 100 ppmy 1
III 110-138 1,000 ppmy 5


average Methanol
Loading Rate


Gas Retention
Time


Table 4-2. Comparison of activated carbons and inoculation methods


Method :
Carbon:
Initial Count:
(CFU/g carbon)
Final Count:
(CFU/g carbon)
Factor of
Increase (%)
IParenthetical value is


Circulation
Calgon
1.18E+05
(2.5 8E+04)
8.14E+06
(6.79E+05)
69.2


Circulation
Bionuchar
2.33E+05
(5.13E+04)
5.23E+07
(8.94E+06)
224.3


Flood/Drain
Calgon
1.04E+06
(3 .30E+05)
2. 12E+07
(2.84E+06)
20.3


Flood/Drain
Bionuchar
1.79E+06
(5.67E+05)
4.80E+08
(2.31E+07)
268.1


standard error for measurement in triplicate.


Figure 4-1. Biofilter operation schematic












25 1 r-- -7 2r- m-- -~ b~ rr~ICC --- B 100%

-eg-Average metha8nol loading & 90

20 Eiologically inoculated 81gy1
b~iofilter (BB)
7f t~-6-Nor-inoculalted biofilter (NB)
~- 70%

S15f t 60%

r- 50%











0 20 40 60 .0100 120 140

Days in Operatiion


Figure 4-2. Methanol removal efficiency in the biologically inoculated and non-inoculated
biofilters as a function of time and methanol loading rate. Each point is the average of
two replicates collected consecutively. Standard error was less than 1% for the BB data,
less than 5% for the NB data, and less than 10% for the methanol loading rate.














HISh OrPJMS OrPlrulnl t


1I.0E+10


1.0E+D -



1.0E+D6 -



1 0E+ 1~.



1.0E+2 -


1.0E+DO


Inlet


Middle


Outlet


er (BB)


Inlet Mriddle Outlet


Nion-incularted Biioflite (NB)


Biologically Inoculated Biolilt


Figure 4-3. Abundance of cultivable bacteria in three spatial regions of the biofilters using three
types of culture media. Error bars represent the standard error for measurements made in
triplicate.











PCR-DGGE with mxraF-specific primers


PCR-DGGE with universal 16s rRNA primers


day day day day day day
138 46 77 102 125 138
Non-inoculated biofilter


day day day day day
46 77 102 125 138
Non- inoculated biofilter


day day day day day day
22 46 77 102 125 138
Inoculated biofilter


day day day day
46 77 102 125
Inoculated biofilter


Inoc dany


Figure 4-4. Bacterial diversity of the biofilters over time, measured using PCR-DGGE. A)
Images of DGGE separated DNA fragments sampled from the biological inoculum and
from the biofilters on six days during operation. B) UPGMA cluster analysis of the
relatedness of PCR-DGGE banding patterns of the inoculum and the biofilters on six
days during operation. Numbers at the bottom of each gel lane correspond to the day on
which the packing sample was extracted from the column and used for DNA extraction
and amplification. Bands marked with a circle, were excised, re-amplified, and purified
for sequencing. Numbers in the circles correspond to the numbers used in phylogenetic
analysis, while X in the circles corresponds to bands that were extracted, but unable to be
re-amplified or purified.





PCR-DGGE with mxaF-specific primers


PCR-DGGE with universal 16s rRNA primers





*
C~n~ ---


,,,

OE III L-r


--- L *
--31


Outlet MideInlet Outletidl Inlet
Inoculated Non-inoculated
biofilter biofilter


Outlet MideInlet
Inoculated
biofilter


OutletMiddle Inlet
Non-inoculated
biofilter


BB-outlet

BB-middle

BB-inlet
-I NB-outlet

NB-middle

NB-i nlet


BB-outlet

BB-middle

BB-inlet

NB-outlet

NB-inlet

NB-middle


Figure 4-5. Bacterial diversity of the biofilters in different spatial regions. A) Images of DGGE
separated DNA fragments sampled from three points along the length of the biofilters at
the end of the operating period. B) UPGMA cluster analysis of the relatedness of PCR-
DGGE banding patterns from three points along the length of the biofilters at the end of
the operating period.


911


~I ~ ~---











Methylobacteriumn exto~rquens
951 Clerby lobat ter~iorn rhodinumn
SMethylchacterium dichloromethanicum

91 A il el
-Methylobacteriumn zatmanii
Methylobacte~rium podariumn
Methylobcacterium? organophilumn
rPr*1emplorh -10aus multivorans
Bellernochl mobrilis
Methylocella silvestris
BB5 / Inoculum2
F-letrblowsts~s pervus
1~00 Methylosinus tricho~sponium
a41 I IMlethylosinus spariumn
r.4-invions' CIS aldnichii
88t F..1thdio*csi~s hz*eral
BB3


9g go Methylopila capsulate
8161 ~AlbibYacter methylrovrans
I r lelih~a luilfonomenas nie triv ovra
98~ Schlegelia plan~tlphlla
Angulomicob~iumn tetraedale
91 Paracoccus denitrifi~cars


100 HypFhomicrobiumn zavarzirii
Hyphomnicrobium vulgare
Hyphomicrobium facile
BB2
Hyphomirobiumn denitrificans
e82 Hyphomicrob~ium methylroveum


I~g M3~ ~etylobacllus flagellatus KT
100I Metliylobacillus glycoglenes
Methylophilus methylotrophus
7,I IroculumR1
991 BB1

96 r-le tr Iwloi i us calpsulatu s
I ~~ ?.rrhletnlcaldlum sp E10a
901 1 ~Metlhylomnonas methartica
99 Methylobacter sp 5FB


0.05


Figure 4-6. Phylogenetic reconstruction of known methylotrophic bacteria and unknown biofilter
and inoculum strains using Neighbor Joining method. The inferred phylogeny was
bootstrapped with 1,000 replicates, and bootstrap values greater than 75% are shown on
corresponding branches









CHAPTER 5
LIFE CYCLE ASSESSMENT OF TWO OPTIONS FOR CONTROLLING HAZARDOUS AIR
POLLUTANTS AT PULP AND PAPER MILLS:
A COMPARISON OF THERMAL OXIDATION WITH A NOVEL PHOTOCATALYTIC
OXIDATION AND BIOFILTRATION SYSTEM

Introduction

The forest products industry, including pulp, paper, and paperboard mills, is one of many

industries faced with increasingly stringent regulations on allowable emissions to air and water.

In 1998, the U.S. Environmental Protection Agency (U.S. EPA) promulgated guidelines and

emissions standards, collectively known as the "Cluster Rule," intended to reduce the discharge

of toxic pollutants in wastewaters and emissions of hazardous air pollutants (HAPs) for the forest

products industry (U.S. EPA 1998). To this end, the Cluster Rule requires implementation of

maximum available control technology (MACT) to limit the amount of HAPs emitted from a

variety of mill processes, including chemical pulping (MACT I), papermaking and mechanical

pulping (MACT II), and chemical recovery (MACT III) (EPA 2002). Specifically, MACT I

regulations require pulp and paper mills to collect and treat non-condensable gas from high

volume low concentration (HVLC) sources, which are defined as those producing large volumes

of gas (10,000-30,000 acfm for an entire mill) and dilute concentrations (below the gas mixture's

lower explosion limit) (Varma 2003). These sources include pulp washing, deckers, knotters,

oxygen delignification, and chemical storage tanks. Of the HVLC gases emitted, methanol is a

primary focus of MACT I standards because it is emitted in such high quantities from pulping

processes (over 44,000 tons from the entire forest products industry in 2004) (EPA 2004).

The most common method for MACT I compliance adopted by pulp and paper mills is

the incineration of methanol and other HVLC gases in an existing power boiler or lime kiln or in

a new stand-alone device, such as a regenerative thermal oxidizer (RTO) (Varma 2003). While









effective for destroying HAPs, use of an RTO has the potential to create environmental impacts

associated with the combustion of natural gas and production of nitrogen oxides (NOx), the

oxidation of carbon and reduced sulfur species to carbon dioxide (CO2) and sulfur dioxide (SO2),

the amount of raw materials required to construct ductwork and other infrastructure for gas

collection and transport, and the need to construct and operate a wet scrubber to remove SO2

from the RTO exhaust (Mycock et al. 1995; Schnelle and Brown 2002). Recently, however,

other options for HAP control have been investigated, including a treatment system using a

photocatalytic oxidation (PCO) reactor for primary methanol removal (Stokke et al. 2006) and an

activated carbon biofilter for secondary polishing of the air stream (Babbitt et al. 2007).

Although these new technologies show promise for methanol removal to meet MACT

standards while decreasing energy requirements, how they compare to thermal oxidation in terms

of life cycle environmental impacts is not known. Therefore, the goal of this work was to use a

life cycle assessment (LCA) approach to compare the novel PCO-biofilter system with the more

traditional RTO technology. A better understanding of potential cradle-to-grave environmental

impacts associated with these technologies will not only assist industrial and regulatory

communities in selecting the most environmentally friendly option but will also reveal

opportunities for environmental improvement in the construction and operation of either system.

This paper reports the results of a life cycle inventory, impact assessment, and sensitivity

analysis, for the purpose of comparing a PCO-biofilter and a RTO-scrubber system.

Methods

Life cycle assessment (LCA) is the systematic inventory and analysis of environmental

impacts for the entire life of a process or product for comparison purposes. This LCA was

structured in accordance with ISO 14044:2006 guidelines (ISO 2006), which call for four phases:










1) definition of the assessment goals and scope, 2) inventory of all material and energy inputs

and outputs from the system, 3) assessment of environmental impacts associated with the

inventoried system inputs and outputs, and 4) interpretation of the impacts according to the

defined goal and scope. Each of these phases is described in more detail below.

Goal and Scope Definition

The goal of this LCA was to compare a two-step photocatalytic oxidation and

bioailtration system with a thermal oxidation system for methanol removal, to determine the

environmental impacts over their entire life cycles. Results from this LCA are intended to be

used in comparative assertions intended to be disclosed to the public. Unlike many recent LCA

studies of treatment technologies (e.g., Jorgensen et al. 2004; Munoz et al. 2007; Sauer et al.

2002), this comparative LCA includes not only the impacts of operating the PCO-bioailtration

and RTO-scrubber systems over their expected lifetimes but also of producing the required

infrastructure for these systems. Inclusion of the infrastructure production-related raw materials,

energy, emissions, and impacts will yield a more complete understanding of the benefits or

drawbacks of both systems that are being compared.

Functional unit

The functional unit for this study was "the treatment of 350 scfm of air with a methanol

concentration of 50 ppmy, in order to achieve 98% methanol removal." This volumetric flow

rate and methanol concentration were selected based on recommendations by industry

representatives consulted for this proj ect and the subsequent design of a pilot-scale PCO system

with these specifications. The specified methanol removal rate of 98% is based on the MACT

compliance options, which require thermal oxidation at 1600 oF with a 0.75 second retention









time (necessary for 98% methanol removal) or use of other control technologies provided that a

98% methanol removal is achieved (U.S. EPA 1998).

System boundaries

The system considered for this LCA was the production and operation of two air

pollution control systems for removing HVLC methanol emissions generated from unit processes

involved in the production of brownstock (unbleached) pulp at Kraft pulp mills. These processes

include brownstock pulp washers, screens, knotters, deckers, and weak black liquor storage

tanks. As previously described and as shown in Figures 5-1 and 5-2, the two treatment options

considered are 1) an RTO for methanol removal, followed by a caustic wet scrubber for SO2

control and 2) a photocatalytic oxidation (PCO) reactor for primary methanol removal followed

by an activated carbon biofilter for secondary methanol removal. Life cycle inputs of raw

material and energy and outputs of emissions to air were included for both control systems for

three stages: 1) processing resources extracted from nature to produce primary raw materials; 2)

secondary material processing to convert primary raw materials into chemicals, materials, and

energy directly used for infrastructure or operation of the control systems; and 3) construction

and operation of each control system for an expected 20-year lifetime.

Stage 1, "Primary Raw Material Processing," does not include the direct extraction or

mining of ores or other materials from nature, but does include the processing required to convert

these resources, or "inputs from nature," into useful raw materials. Stage 2, "Secondary Material

Processing," includes the processes required to convert raw materials from Stage 1 directly into

feedstocks or electric energy required for the construction or operation of the control equipment.

Outputs from the Secondary Material Processing stage are also termed "inputs from the

technosphere" in this study. In the case of the PCO-biofilter system, Stage 3 includes the










production and replacement of packing materials for the reactor and the bioHilter as individual

contributing categories to the total PCO-biofilter impact (Figure 5-2). These materials could not

be classified distinctly as either construction or operation, but were rather maj or material inputs

that had several replacement cycles over the lifetime of the proj ect, as described in the

assumptions detailed below. For both systems, Stage 3 also includes the emission of treated

HVLC gases, as the two technologies are expected to have slightly different removal rates for

VOCs other than methanol (as described in the assumptions). The total inputs and outputs from

all three stages are aggregated into categories of "construction" and "operation" for comparison

purposes. Transportation of materials from their point of production to the mill for installation or

use was not included, due to lack of information about this stage.

Assumptions

In addition to the scope and system boundaries defined above, several assumptions about

the system parameters are necessary to facilitate data collection and calculations.

1. Except where specified differently, all capital goods and infrastructure are expected to
have a 20-year lifetime. Where shorter lifetimes are anticipated, total material and
energy flows were adjusted to reflect replacements required to achieve 20 years of
service.

2. VOCs in addition to methanol are present in the effluent air stream (NCASI 2003) and
are included, to the extent known from literature, in estimates of control technology
operation and performance.

3. A ratio of 100 scfm contaminated air generated from brownstock washing processes for
every 1 air dry (short) ton unbleached pulp per day production rate (U.S. EPA 1979) was
used to normalize inventory data given in mass per ton pulp format.

4. The RTO was sized to operate at 1600 oF, with a residence time of 0.75 seconds, for a
corresponding 98% removal of methanol. All VOCs present in the contaminated air
stream are converted to CO2 aCCOrding to stoichiometric ratios and 98% destruction
efficiency. The regenerator beds are packed with ceramic saddles and sized for 95%
thermal efficiency. Natural gas is added to support combustion of the VOCs, based on an
energy balance around the RTO.









5. The RTO is located 200 ft from the brownstock washer HVLC collection point, and
connected with a 3.5 ft diameter stainless steel duct.

6. The photocatalytic oxidation (PCO) reactor was designed for 90% removal of methanol,
followed by an activated carbon biofilter, designed for 80% removal of remaining
methanol, to achieve a total of 98% as required by regulation.

7. While the bioHilter was designed for methanol removal, it also contributes 65-80%
removal of other VOCs present, based on performance of pilot-scale bioHilters reported in
Devinny et al. (1999). This removal rate is a conservative estimate, as the VOCs may
actually be more biodegradable after UV photooxidation than would be expected in their
natural state (Koh et al. 2004; Moussavi and Mohseni 2007). Of the carbon in VOCs
entering the biofilter, 40% was assimilated into biomass, and 60% was converted to CO2.

8. The PCO reactor contains a Eixed bed of silica-titania composite (STC) pellets, expected
to have a 5 year lifetime; and uses 75W UV bulbs with a one-year lifetime for
photocatalytic methanol destruction.

9. The bioailter contains a novel packing mixture of Bionuchar granular activated carbon (a
wood-based carbon chemically activated with phosphoric acid), mixed in a 4:2: 1 volume
ratio with perlite spheres and granules of an ammonium nitrate slow release fertilizer, and
this mixture is expected to have a five-year lifetime.

10. The treatment trains operate continuously, or 8,760 hours per year.

Inventory

All life cycle inventory (LCI) calculations were performed using SimaPro 5.1 (PRe

Consultants, Amersfoort, The Netherlands). However, all data process modules were created

specifically for this life cycle, rather than using existing databases in SimaPro (except where

noted), to maintain a high level of transparency and specificity to the system of interest as well as

consistent data quality levels. Inventory data were collected from interviews of environmental

managers at pulp and paper mills participating in this proj ect and engineers involved with

creating HVLC control solutions for pulp and paper mills, design and operational specifications

of the PCO system, bench- and pilot-scale results for the PCO reactor, bench-scale results for the

biofilter, technical documents provided by the National Council for Air and Stream Improvement

(NCASI), published literature, regulatory agencies, theoretical calculations, and, on a very









limited basis, from the published database by Franklin Associates (Prairie Village, Kansas,

USA), provided in the SimaPro databases. A list of specific data sources is provided in Table 5-

1 for each maj or process included.

As noted in Table 5-1, different emission factors were used for electricity production by

pulp and paper mills as compared to the U.S. average production by electric generating facilities.

This distinction is made because it is common practice for pulp mills to self-generate most of the

electricity required on-site using waste products (e.g., bark boilers) and as part of the chemical

recovery process (e.g., recovery boilers for black liquor solids) (Smook 1992). Therefore, air

emissions resulting from energy production on- or off-site are significantly different.

Differences in the U.S. average and mill average fuel mixes for electricity production are shown

in Table 5-2. Assumptions made in this regard included the following: 1) any equipment (fans,

blowers, etc.) required for operating the control systems is powered by electricity generated on

site, 2) any electricity used for primary or secondary material processing is generated according

to the U.S. average fuel mix, and 3) no net CO2 is produced by combustion of bark or other wood

wastes, as these biomass materials contain 'biogenic' carbon that is part of the natural carbon

cycle and that does not contribute to atmospheric concentrations of carbon dioxide.

Impact Assessment

Life cycle impact assessment (LCIA) was performed to connect the mass and energy

input and emission output results from the LCI to broader indicators or categories of impact to

the environment or human health. For this LCIA, categories were selected based on their

relevance to this study's focal areas (raw material requirements, energy use, and emissions to air,

including greenhouse gases, criteria pollutants, and hazardous air pollutants (HAPs)). Therefore,

categories selected include abiotic resource depletion potential (ADP), global warming potential









(GWP), photochemical oxidation potential (POP), acidiaication potential (AP), and human

toxicity potential (HTP). Impacts were calculated based on the published impact factors of CML

2 (The Institute of Environmental Sciences, Leiden University, Leiden, The Netherlands, 2001),

provided in SimaPro 5.1. This method was selected based on its widespread use and because its

problem-oriented (midpoint) approach could be applied to directly relate LCI flows with the

environmental areas to which they contribute impacts. In applying the CML 2 method to this

LCA, characterization factors for methane and nitrous oxide global warming potential were

modified slightly from published values to reflect the updated 100-year global warming

potentials of the Interngovernmental Panel on Climate Change (IPCC) Third Assessment Report

(IPCC 2001). No normalization or weighting of impact assessment values was performed, in

accordance with ISO 14044:2006 guidelines for a LCA intended for comparative assertion

intended to be disclosed to the public (ISO 2006).

Interpretation and Sensitivity Analysis

LCI and LCIA results were interpreted based on the stated goal and scope of the study to

compare the two air emissions control technologies using the environmental and human health

indicators of interest. In addition to this direct interpretation, a sensitivity analysis was

performed on the assumptions and system boundaries used in creating the study's scope. The

assumptions tested are described below.

1. Use of a wood-based activated carbon. The Bionuchar GAC is chemically activated
from wood-based precursors such as sawdust, although many other activated carbons are
produced from coal and other nonrenewable resources and activated using steam. This
analysis will compare LCIA results for use of a bituminous coal-based, steam-activated
GAC (such as Filtrasorb 400, Calgon Corporation, Pittsburgh, PA, USA).

2. Lifetime of STC pellets and biofilter packing. Both of these components for the PCO-
biofilter system are assumed to have a five-year lifetime. However, it is impossible to
determine if this assumption is realistic without full-scale operation in a specific pulp mill









environment. Therefore, this analysis will address possible shorter or longer lifetimes for
these packing materials and the effect of their lifetime on LCIA results.

3. UV bulb energy requirements. The PCO reactor specifications call for 216 UV bulbs
with an energy input of 75 Watts. Given the continuous operation of these bulbs, the
material and energy required and resulting air emissions generated are expected to be
substantial for their use. Therefore, this sensitivity analyses will examine the effect of
using lower wattage bulbs, assuming that photocatalytic methanol removal could be
maintained at required levels.

Results

Inventory

The results of the material and energy inventory, normalized per functional unit of the

treatment of 3 50 scfm of air with a methanol concentration of 50 ppmy, in order to achieve 98%

methanol removal, are shown both as inputs from the technosphere to construction and operation

of the control equipment (Table 5-3) and as inputs from nature to the entire life cycle (Table 5-

4). This distinction between inputs was made to illustrate various processes and materials

ultimately required for both systems. Total solid waste generated is also included in Table 5-3.

Emissions to air per functional unit for greenhouse gases, criteria pollutants, and other air

pollutants are shown in Table 5-5. Raw materials from nature and air emissions generated were

categorized for both the construction and operation phases and aggregated for both control

technologies. For example, air emissions from construction of the RTO-scrubber system

represented the total emissions for constructing the RTO, the scrubber, and all other

infrastructure required for this system, such as duct work. In addition to the complete life cycle

air emissions, the inventory also included comparative emissions of the compounds contributing

99.9% by mass to the total HAP concentration in effluent gas from HVLC sources before and

after treatment by either system (Table 5-6). In all aspects of the LCI, results per functional unit

represented the total input or emission over the 20-year life cycle divided by the number of









functional units occurring in the same 20-year period, to obtain results on the basis of "per

functional unit," or "per 350 scfm air containing 50 ppmy methanol, treated to remove 98% of

methanol."

Impact Assessment

Figure 5-3 shows comparative environmental impacts per functional unit for both

technologies for the five impact categories assessed. Units shown are kg antimony (Sb)

equivalent (abiotic resource depletion potential); kg carbon dioxide (CO2) eqUIValent (global

warming potential); kg ethylene (C2H2) eqUIValent (photochemical oxidation potential; kg sulfur

dioxide (SO2) eqUIValent (acidification potential); and kg 1,4-dichlorobenzene (1,4-DB)

equivalent (human toxicity potential).

Sensitivity Analysis

Results of the sensitivity analysis on coal- versus wood-based granular activated carbon

precursor, lifetime of biofilter packing and STC pellets, and the wattage of UV bulbs in the PCO

reactor are shown in Figures 5-4, 5-5, and 5-6, respectively. All results are presented as a

relative ratio of total impact of the system of interest divided by total impact of the RTO-

scrubber system. Presenting relative results allowed for direct comparison of trends among the

sensitivity analyses and the impact categories and eliminates the variability in units and scale that

would be observed when using absolute results.

Discussion

Inventory

Based on results of the inventory of inputs from the "technosphere" into the construction

and operation of the two systems (Table 5-3), it is evident that the stainless steel required to

construct the RTO, scrubber, and associated ductwork (1.44E-3 kg/functional unit) and the









energy required (5.59E-2 MJ/functional unit) to produce this and other infrastructure material

were substantially higher than any other material or energy input required to produce

infrastructure for the PCO-biofilter system. However, there are 11 materials, in addition to water

and energy, that were unique to the PCO-biofilter system because of the need to produce STC

pellets (including required equipment) and biofilter packing material, both of which were

expected to have a five-year lifetime. In terms of operations, the RTO-scrubber system required

high volumes of water (1.08E-3 m3/functional unit) and natural gas (1.76E-2 m3/functional unit)

to operate the wet scrubber and support VOC incineration, respectively. However, because of

the use of 216 75-W UV bulbs in the PCO reactor, this system required almost an order of

magnitude greater amount of electricity for operations than the RTO system (1.12 as compared

to 0.224 MJ/functional unit). In terms of solid waste, the PCO-biofilter system was also the

greatest contributor, due in large part to the needed replacement of biofilter packing and STC

pellets every five years and the disposal of UV bulbs annually, since there was no assumption

included here for recycle or reuse of any of this material. This solid waste could potentially be

minimized if these materials' useful life was extended or recycling or reactivation opportunities

were pursued.

Raw material inputs from nature required to produce material and energy for the entire

life cycle (including the secondary materials described in Table 5-3) are shown on a per

functional unit basis in Table 5-4. Trends in raw material usage were similar to what was

described in Table 5-3; that is, the construction of the RTO, scrubber, and ductwork system

(1.81E-1 kg/functional unit total) and the operation of the PCO-biofilter system (7.5 1E-1

kg/functional unit total) created the highest demands for resources. Resources for construction

of both systems were distributed relatively evenly across materials required for producing









stainless steel and other metals and materials for infrastructure. On the other hand, resources

required for operating the systems were those needed for producing electricity, such as wood

waste and spent black liquor solids used to produce electricity on-site at the mills, as well as coal

and natural gas used to produce electricity purchased by the mills to supplement their own

supply. Natural gas requirements were higher for operating the RTO-scrubber system, as

compared to the alternate technology, because of the need to add natural gas to support oxidation

of VOCs in the HVLC gas stream. Even with energy recovered by the regenerative capacity of

the system, there is still an energy deficit in the RTO, primarily because the concentration of

VOCs was so low compared to the total volume of gas, that energy produced from combusting

the VOCs was not sufficient to sustain required operating temperatures.

Similar trends were observed for the comparison of air emissions produced over the life

cycle of both control options, per functional unit, as shown in Table 5-5. Total life cycle air

emissions for most of the pollutants considered were slightly higher for the PCO-biofilter

system, again due to the energy required to operate UV bulbs and the processes and chemicals

used to produce the STC pellets and the activated carbon, nutrient, and perlite used as biofilter

packing. Some air emissions, such as vinyl chloride, hydrofluoric acid, and ammonia, were

unique to the PCO-biofilter system, and could be attributed to the secondary material processing

steps used to produce feedstocks and equipment needed for STC pellet and biofilter packing

production. In addition to the life cycle air emissions inventoried, the VOC emissions from

HVLC sources before and after the treatment systems were also estimated per functional unit

(Table 5-6). Regardless of the system used, there was expected to be a significant reduction in

all VOCs present. Although the impact of this reduction was not assessed here, it is expected to

be important for photochemical oxidant production and human toxicity potential. Many of these










compounds have high photochemical oxidant potential factors (e.g., the alcohols, ketones, and

aldehydes) and human toxicity factors (e.g., formaldehyde), in addition to the nuisance odors

associated with the reduced sulfur species, all of which would be significantly reduced by either

of the technologies adopted.

Impact Assessment

As is often the case with LCA studies, the impact assessment results did not point to a

clear winner between the two air emission control systems. Instead, the impact assessment

results in Figure 5-3 illustrate potential environmental tradeoffs of adopting one or the other of

the two options. Expected impacts of the PCO-biofilter system were approximately 20% less

than impacts of the RTO-scrubber system when considering categories of abiotic resource

depletion, photochemical oxidant formation, and acidiaication. On the other hand, the PCO-

bioHilter system results were 25% higher for global warming and over 50% higher for human

toxicity, as compared to the RTO-scrubber. One clear trend that can be observed, however, is

that in all of the impact categories considered, the construction stage of the RTO-scrubber life

cycle contributed to at least 25% of the total impact. If this stage had been excluded from the

system boundaries, the LCA results would have been drastically skewed toward favoring the

RTO system. However, in all but the human toxicity category for the RTO, the operation phase

of both systems' life cycles did contribute the highest impact. This result was due primarily to

the combustion of fossil, biomass, and waste fuels to produce electricity at the pulp and paper

mills that is required to operate fans and pumps required by both systems and the UV bulbs

required by the PCO reactor. Electricity generation not only required the input of nonrenewable

abiotic resources such as coal and crude oil, but also produced greenhouse gases that contribute

to global warming and pollutants such as SO2, which contributes to photochemical oxidation and









acidiaication. In all but the human toxicity category, the production of STC pellets and bioailter

packing only contributed about 10% to the total impact. The increased contribution to human

toxicity is a result of processing hazardous compounds, such as vinyl chloride and hydrofluoric

acid, to produce materials needed for the STC pellets (such as HF) or to produce the equipment

used to produce the pellets (such as PTFE or PVC).

Interpretation

Given the goal of this LCA to compare two methanol control systems based on raw

material and energy inputs, and air emission and solid waste outputs, as well as the resulting

environmental impact, the results shown in Figure 5-3 demonstrated that both control systems

have advantages and disadvantages, depending on the impact category considered. However,

these results and the sensitivity analyses shown in Figures 5-4 through 5-6 could be used to

determine opportunities for minimizing environmental impact for both systems.

Sensitivity analysis

Although this LCA was performed under the assumption that GAC produced from a

wood waste material would be used as the primary bioHilter packing material, mills may

reasonably be expected to use other forms of GAC, based on availability, different process

requirements, or economics. Therefore, impacts for the entire LCA of PCO-biofilter system

were compared for both types of GAC precursor, and results are shown in Figure 5-4,

normalized to the impact results for the RTO-scrubber system for each category. Based on the

inventory information available for this study, the resulting impact assessment showed no real

variation in results for the bioHilter packing stage itself or the total life cycle compared to the

RTO-scrubber system. The slight increase for the coal-based carbon in the ADP category was

due to the use of a nonrenewable fossil fuel rather than a wood waste as precursor. In the other










categories, wood-based GAC impacts were slightly higher, as the wood-based process was more

energy intensive, based on the data available. The difference between wood- and coal-based

GAC results showed no overall impact on the LCA results.

Regardless of the precursor used, requirements for the GAC and other packing material

depended directly on their useful service life and required replacement. For this LCA, the

bioHilter packing and the STC pellets were assumed to be used for Hyve years, thus requiring three

sets of replacement material be produced to achieve a total 20-year system lifetime. However,

there are numerous variables related to the actual full-scale use of these systems that may affect

their lifetime. For example, process changes in the mill could reduce HVLC concentrations, thus

extending the service life of all equipment. Alternatively, the presence of particulate matter or

corrosive compounds in the gas stream may dramatically reduce the service life. To this end, a

sensitivity analysis was performed to compare one-, Hyve- (baseline), and ten-year lifetimes for

both bioHilter packing material and STC pellets, with results shown in Figure 5-5. For all of the

impact categories, there was a 50% or less reduction in impacts when extending the lifetime of

these materials to 10 years. The lower reductions were due to the equipment required for

producing the STC pellets that were included in this life cycle system, as the materials and

emissions associated with equipment production did not change regardless of pellet production

rate. On the other hand, reducing lifetime to one year showed a much higher increase in all

impacts, and, for every category considered, the shorter lifetime resulted in impacts higher than

the total life cycle of the RTO system. For the categories of global warming, photochemical

oxidant formation, and acidiaication potential, the increase in impact was mostly due to the

bioHilter packing material demand, based on the energy required for activation of the carbon and

production of the ammonium nitrate nutrient. However, for the category of human toxicity, the









increased impact for a one-year packing lifetime was attributable to the use of hazardous

chemicals described earlier for the production of materials and chemicals needed to manufacture

the STC pellets. Ultimately, the environmental impacts of the PCO-biofilter system considered

in this LCA appeared to be highly dependent on the lifetime of the packing materials.

Therefore, as this technology continues development towards full-scale application, design

criteria should be established to ensure extended life of all packing materials.

Another consideration in development of this innovative system is the continued use of

UV bulbs and their associated raw materials and electricity requirements (thus resulting in

additional emissions). Results of the sensitivity analysis on bulb energy use are shown in Figure

5-6. These results indicated that, if lower watt bulbs were able to be substituted in the PCO

reactor without compromising methanol destruction, the PCO-bioreactor system would be

environmentally favorable to the traditional RTO system in all impact categories except human

toxicity. Use of 50W bulbs in this LCA, resulted in impacts for the PCO-biofilter system that

were 10-40% less than those for the RTO-scrubber in the categories of resource depletion, global

warming, acidification, and photochemical oxidation potential. These results illustrated an

opportunity to not only minimize the environmental impact associated with this technology but

also reduce the economic cost of operating the PCO reactor, a maj or incentive for the pulp and

paper industry.

Conclusions

The use of life cycle assessment (LCA) for this comparative study provided a valuable

way to compare two potential technologies that have been proposed as methanol control systems

at pulp and paper mills. Although neither option consistently yielded lower impacts, the PCO-

biofilter system showed lower environmental impacts to resource depletion, photochemical









oxidant production, and acidiaication over its entire life cycle, compared to the traditional

approach of using a regenerative thermal oxidizer followed by a caustic scrubber. However, the

RTO-scrubber system consistently showed lower life cycle impacts to global warming. With the

recent increase of public attention to issues of climate change and potential future regulation on

greenhouse gases, careful attention to decreasing greenhouse gas emissions associated with

operational energy requirements of the PCO-biofilter system is recommended. Fortunately,

unlike the more established RTO systems, this innovative methanol control system is still in

development, with numerous opportunities for minimizing resource use, emissions, and life cycle

environmental and human health impacts. Some of these opportunities have been demonstrated

in the sensitivity analysis, particularly the need to minimize electricity use by UV bulbs in the

PCO reactor and to maximize the service life of bioHilter packing media and STC pellets.

Results of this LCA also showed that the impacts of producing infrastructure required for

the RTO and scrubber contributed up to 25% of the total life cycle impacts for this system. From

an environmental perspective, these impacts potentially could be reduced if the amount of steel

required for constructing ducts were minimized by locating the RTO closer to the HVLC source

(although this may not be a feasible solution given limited area near the emissions source). From

a methodological perspective, however, results showing the importance of infrastructure impacts

helped to demonstrate the importance of including this stage in the system boundaries.

Furthermore, results of this LCA can be used to illustrate the benefits of adopting a life cycle

perspective and considering environmental impact of all stages of a process when selecting and

implementing industrial technology.









Table 5-1. List of data sources used for maj or processes in compiling the life cycle inventory of
two alternative technologies for methanol control
Inventory Data Data Source
VOC production and control
VOC emissions from HVLC sources NCASI 2003
Varma 2003; Potlatch Corporation Air Operating
Typical VOC control approaches
Permit (ADEQ 1999); Banks 1998; Santos et al. 1992
RTO and Scrubber Construction and Operation
RTO design and sizing Cooper and Alley 2002; Lewandowski 2000
Scrubber design and sizing Cooper and Alley 2002 Schifftner and Hesketh 1996
Stainless steel production World Stainless Steel LCI (ISSF, 2006)
Caustic (NaOH) production AP 42 Emission Factors (U. S. EPA, 1995)
PCO and Biofilter Construction and Operation
Stokke et al. 2006; other data provided based on design
PCO design and sizing
of pilot scale unit
Aluminum, copper, carbon steel .
'AP 42 Emission Factors (U.S. EPA, 1995)
acrylic, and glass production
Biofilter design and sizing Babbitt et al. 2007; Devinny et al. 1999


STC pellets
Pellet production equipment and
pellet formulation
PVC, CPVC, PTFE production (for
equipment)
HF, HNO3, TEOS production
TiO2 prOduction
Biofilter packing

Bionuchar activated carbon
production
Perlite and ammonium nitrate
fertilizer production
Energy
Pulp and paper mill electricity
production and emission factors
U.S. average electricity production
and process specific emission factors
Life cycle inputs to U.S. average
electricity Production


Stokke et al. 2006; other data provided based on design
of pilot scale unit
AP 4 Emssin Fator (US. EA, 99.
AP 42 Emission Factors (U.S. EPA, 1995)

Morters et al. 2001; Reck and Richards 1999


Menendez-Diaz and Martin-Gullon 2006-'
MeadWestvaco Virginia Corporation Draft Title V
permit (KDEP 2005b)
AP 42 Emission Factors (U.S. EPA, 1995)


E-Grid (U. S. EPA 2006); NCASI GHG spreadsheet
(NCASI 2004); Smook 1992
E-Grid (U. S. EPA 2006)

Franklin Associates LCI Database (in SimaPro)










Table 5-2. Average fuel mix for electricity production in the United States and at an average pulp
and paper mill
Percent of total (%) U.S. Average Pulp Mill Average
Coal 50.2 13.8
Natural gas 17.4 16.4
Fuel oil 3 6.4
Nuclear 20--
Hydropower 6.6--
Non-hydro renewables 2.6--
Black liquor solids --- 40
Bark/wood waste --- 16
Purchased electricity
--- 7.4
(assume U.S. average)
Reference U.S. EPA 2006 Smook 1992










Table 5-3. Material and energy inputs from the "technosphere" directly to and solid waste
outputs from construction and operation of two alternative technologies for methanol
control


RTO and PCO Reactor
Scrubber and Biofilter

1.44E-03 1.97E-04
--- 2. 12E-05
--- 2.53E-04
--- 4.99E-05
2.43E-04--
--- 4.24E-06
--- 3.66E-06
2.25E-05 3.10E-06
5.59E-02 9.36E-03

--- 2.74E-05
--- 9.09E-05
--- 3.38E-06
--- 3.22E-04
--- 1.52E-05
--- 1.35E-05
--- 2.42E-06
--- 2.88E-07
--- 8.11E-07
--- 1.03E-02

--- 8.37E-04
--- 6.83E-04
--- 2.24E-04
--- 9.20E-07
--- 3.94E-02


Inputs (per functional unit)'
Infrastructure
Stainless steel (kg)
Carbon Steel (kg)
Glass (kg)
PVC/CPVC (kg)
Ceramic/Refractory (kg)
Aluminum (kg)
Copper (kg)
Water (m3)
Energy (MJ)
STC Pellet Production
Stainless steel (kg)
PVC/CPVC (kg)
PTFE (kg)
TEOS (kg)
Ethanol (kg)
TiO2 (kg)
HNO3 (kg)
HF (kg)
Water (m3)
Energy (MJ)
Biofilter Packing Production
Nutrient (kg)
Granular activated carbon (kg)
Perlite (kg)
Water (m3)
Energy (MJ)
Operations
NaOH (kg)
Process Water (m3)
Natural gas (m3)
Electricity (MJ)


3.74E-04
1.08E-03
1.76E-02
2.24E-01


4.35E-04

1.12E+00


Solid waste generated (per functional unit)
Total solid waste (kg) 7.28E-04 1.66E-03
All values are normalized to the functional unit of the treatment of 3 50 scfm of air with a
methanol concentration of 50 ppmy, in order to achieve 98% methanol removal











Table 5-4. Raw material inputs, in kg per functional unit from nature into the total life cycle of construction and operation of two


alternative technologies for methanol control
RTO and Scrubber


PCO
Operation



1.13E-02

6.41E-03






6.50E-04




8.81E-03


Reactor and Biofilter


Raw Material (kg)
bauxite
chromium
coal
copper (in ore)
crude oil
dolomite
feldspar
fluorspar
iron (in ore)
lignite
limestone
manganese
molybdenum
SNaCl
natural gas
nickel
perlite
phosphorous
rutile
sand
silica
silicon
soda ash
spent liquor solids
water
wood/wood wastes
Total


Construction
2.27E-04
1.17E-04
5.33E-03

3.56E-03
7.52E-05



4.22E-04
7.54E-05
6.16E-04
2.82E-05
4.03E-05
9.34E-05
3.60E-03
2.86E-05

6.51E-07



1.30E-04
1.08E-05



2.25E-02
5.68E-06


Operation



2.47E-03

1.53E-03


Total Construction
2.27E-04 1.56E-05
1.17E-04 1.60E-05
7.80E-03 8.53E-04
-- 3.84E-06
5.09E-03 6.18E-04
7.52E-05 1.02E-05
-- 1.95E-05


STC Pellets


2.22E-06
8.06E-04

8.68E-04
1.43E-06

5.84E-06
7.99E-06
1.43E-06
5 .23E-05
5.34E-07
7.63E-07
1.44E-04
6.07E-04
5.41E-07

1.23E-08
3.36E-05



4.36E-05



8.11E-04
1.05E-06
3. 39E-03


Biofilter packing



1.27E-04

1.03E-04






7.32E-06




1.22E-03

2.35E-04
6.46E-04




9.0---



9.20E-04

4. 63E-03


Total
1.56E-05
1.82E-05
1.31E-02
3.84E-06
7.99E-03
1.17E-05
1.95E-05
5.84E-06
8.77E-05
1.17E-05
8.49E-04
4.36E-06
6.23E-06
2.44E-04
1.12E-02
4.42E-06
2.35E-04
6.46E-04
3.36E-05
1.90E-04

4.51E-05
5.93E-05
3.32E-02
6.85E-01
1.20E-02
7.65E-01


-- 4.22E-04
-- 7.54E-05
1.43E-04 7.58E-04
-- 2.82E-05
-- 4.03E-05
3.94E-04 4.87E-04
1.72E-02 2.08E-02
-- 2.86E-05


7.97E-05
1.02E-05
1.39E-04
3.83E-06
5 .47E-06
9.97E-05
5.71E-04
3.88E-06


-- 6.51E-07 8.85E-08


-- 1.30E-04
-- 1.08E-05

6.55E-03 6.55E-03
1.51E-01 1.74E-01
2.11E-03 2.12E-03


1.90E-04

1.47E-06
5.93E-05

3.10E-03
9.15E-07


3.32E-02
6.80E-01
1.07E-02


3. 69E-02 1.81E-01 2. 18E-01 5. 80E-03 7.51E-01


1All values are normalized to the functional unit of the treatment of 3 50 scfm
order to achieve 98% methanol removal.


of air with a methanol concentration of 50 ppmy, in













Table 5-5. Emissions to air in kg per functional unit for construction and operation of two alternative technologies for methanol
control


RTO and Scrubber


PCO Reactor and Biofilter


Biofilter
Packmng


3.12E-03
7.13E-06

1.06E-06


1.42E-05
1.30E-05

3.55E-05
3.88E-06


Construction


Operation


5 .46E-02
1.24E-04

6.98E-07


8.85E-05
1.00E-04

6.62E-04
9.01E-06


Total Construction


Operation STC Pellets


Total



9.41E-02
1.30E-04

4.45E-06


1.55E-04
1.80E-04

6.87E-04
4.92E-05


Greenhouse Gases

carbon dioxide (COz

methane (CH4)
nitrous oxide (NzO)
Criteria Pollutants

carbon monoxide (CO)

nitrogen oxides (NOx)
" sulfur dioxide (SOz)

particulate matter (PM)
Other Air Emissions

ammonia (NH3)
chlorine (Clz

hydrochloric acid (HC1)
hydrofluoric acid (HF)
mercury (Hg)

vinyl chloride (VC)
non methane volatile
organic compounds
(NMVOC)


1.98E-02
3.93E-05

6.50E-07


3.12E-05
4.44E-05

1.91E-04
2.37E-05


7.44E-02
1.64E-04

1.35E-06


1.20E-04
1.44E-04

8.53E-04
3.27E-05




4.02E-06
1.20E-06


2.46E-07


3.07E-03
6.38E-06

1.05E-07


5.24E-06
8.71E-06

3.33E-05
4.86E-06


5.76E-10

8.21E-07




3.03E-08

2.48E-07


8.55E-02
1.10E-04

3.16E-06


1.32E-04
1.53E-04

5.88E-04
3.62E-05


2.33E-03
7.26E-06

1.24E-07


3.16E-06
5.23E-06

3.04E-05
4.23E-06


2.88E-09

1.18E-06


3.75E-08
3 .49E-08

8.01E-07


1.16E-06 1.16E-06
--- 2.00E-06


7.70E-07 3.25E-06
--- 1.20E-06


3.75E-08
3.33E-07

1.05E-06


1.89E-07



4.92E-05


5.64E-08


2.63E-07


5.27E-09


1.65E-04 2.14E-04 7.93E-06


1.19E-04 9.08E-06 1.49E-05 1.51E-04


1All values are normalized to the functional unit of the treatment of 3 50 scfm of air with a methanol concentration of 50 ppmy, in
order to achieve 98% methanol removal.










Table 5-6. VOC emissions, in kg per functional unit from HVLC sources in the brownstock
pulp washing process before treatment and estimated VOC emissions resulting from the
two alternative technologies for methanol control


B before
Treatment
6.48E-04
2.49E-04
9.06E-05
4.25E-05
4. 18E-05
2.50E-05
1.51E-05
1.30E-05
1.18E-05
1.17E-05
8.97E-06
6.81E-06
4.52E-06
2.03E-06
1.99E-06
1.65E-06
1.1~7E-03


RTO and
Scrubber
1 .3 0E-05
4.97E-06
1.81E-06
8.50E-07
8.35E-07
5.00E-07
3.02E-07
2.60E-07
2.37E-07
2.35E-07
1.79E-07
1.36E-07
9.04E-08
4.06E-08
3.97E-08
3.29E-08
2. 35E-05


PCO Reactor
and Biofilter
1 .3 0E-05
4.97E-06
1.81E-06
8.50E-06
8.35E-06
5.00E-06
5.29E-06
4.55E-06
2.37E-07
2.35E-06
1.79E-06
2.38E-06
9.23E-07
7. 10E-07
6.96E-07
5.76E-07
6.11E-05


Emission to Air (kg)

methanol
dimethyl sulfide
dimethyl disulfide
Alpha-pinene
acetone
beta-pinene
acetaldehyde
o-cresol
methyl mercaptane
ethanol
methyl ethyl ketone
m-cresol
formaldehyde
1 ,2,4-trichl orob enzene
p-cymene
propionaldehyde
Total VOC emissions


1All values are normalized to the functional unit of the treatment of 3 50 scfm of air with a
methanol concentration of 50 ppmy, in order to achieve 98% methanol removal.


















RTO Scrubber
1 1 Construction Construction
Piary Raw Secondary
Inputs Material Material
from IProcessing Processing (Stage 3)
nature(Stage 1) (Stage 2)


I/ RTO Scrubber
Energy /t/ Operation Operation
Production
(Stage 2)
SMatenial
--- Energy :
Air emission:
...., Solid waste
..t: "Input from 'technosphere"'"
System Boundary
VOC emissions from
Solid Waste
HVLC sources

Figure 5-1. System boundaries for the life cycle of the construction and operation of a
regenerative thermal oxidizer (RTO) and caustic scrubber for the treatment of methanol




















101






















Inputs Material Material t
from 'I Processing I IProcessing .
nature (Stage 1) (Stage 2) I STC
( I I pellet:
I 1- -, reduction:
Energy t I (Stage 3)
Production Biofilter
(Stage 2) I I packing
production:

Material Sae
--- Energy
+PCO I IBiofilter
Air emission I=4
olid wste LOperation Operation
t: "Input from 'technosphere'"


System Boundary::

VOC emissions from
Solid Waste
HVLC sources

Figure 5-2. System boundaries for the life cycle of the construction and operation of a
photocatalytic oxidation (PCO) reactor and biofilter for the treatment of methanol
































1.2E-03


Figure 5-3. Total comparative life cycle impacts, per functional unit of the construction and operation of two alternative technologies
for methanol control
1All impacts are normalized to the functional unit of the treatment of 3 50 scfm of air with a methanol concentration of 50 ppmy, in
order to achieve 98% methanol removal.


-mC


O/
ter



ber

0.0E+00 1.0E-05 2.0E-05 3.0E-05 4.0E-05 5.0E-05
Photochemical Oxidation (kg C2H2 eq)



O Construction

Operation

a STC Pellets

5 Biofilter Packing


RTO/
Scrubber


0.0E+00 5.0E-04 1.0E-03 1.5E-03 2.0E-03 2.5E-03
Human Toxicity(kg 1,4-DB eq)


PCO/
Biofilter


RTO/
Scrubber


PCO/
Biofilter


RTO/
Scrubber


PC(
Biofil


RTO
Scrub~


0.0E+00 2.0E-04 4.0E-04 6.0E-04 8.0E-04
Abiotic Depletion (kg Sb eq)


0.0E+00 3.0E-02 6.0E-02 9.0E-02 1.2E-01
Global Warming (kg CO2 eq)


--RTO/
SScrubber


0.0E+00 3.0E-04 6.0E-04 9.0E-04
Acidification (kg SO2 eq)























so oH o o bo o o o o o


B Biofilter
Packing
STC Pellets

Operation

a Construction


ADP GWP POP


HTP


Impact category and Technology


Figure 5-4. Sensitivity analysis of wood or coal used as precursor material for granular activated
carbon production, based on relative impact of the PCO-biofilter system as compared to
the RTO-scrubber system
All results are divided by the total impact of the RTO-scrubber system for each impact category
to provide a relative impact per functional unit compared to the RTO-scrubber (relative RTO
impacts are equal to 1). RTO=RTO-scrubber system; Wood=PCO-biofilter system using wood
precursor for GAC production; and Coal=PCO-biofilter system using bituminous coal precursor
for GAC production. discreet












g Biofilter
2.0 Packing
I. I I STC Pellets
E 1.5

1.0 -I a III Operation

0~0.5 5 Construto

0.0


ADP GWP POP AP HTP

Impact Category and Technology



Figure 5-5. Sensitivity analysis of the lifetime of biofilter packing media and STC pellets, based
on relative impact of the PCO-biofilter system as compared to the RTO-scrubber system
All results are divided by the total impact of the RTO-scrubber system for each impact category
to provide a relative impact per functional unit compared to the RTO-scrubber (relative RTO
impacts are equal to 1). RTO=RTO-scrubber system; 1 yr, 5 yr, and 10 yr=PCO-biofilter system
with a 1, 5, or 10 year (respectively) lifetime of both the biofilter packing media and the STC
pellets.





Figure 5-6. Sensitivity analysis of the lifetime energy requirement of UV bulbs in the PCO
reactor, based on relative impact of the PCO-biofilter system as compared to the RTO-
scrubber system
All results are divided by the total impact of the RTO-scrubber system for each impact category
to provide a relative impact per functional unit compared to the RTO-scrubber (relative RTO
impacts are equal to 1). RTO=RTO-scrubber system; 75W, 60W, and 50W =PCO-biofilter
system with 75, 60, or 50 W (respectively) UV bulbs used in the PCO reactor. For Figures 5-4
through 5-6, ADP= abiotic resource depletion potential; GWP=global warming potential;
POP-photochemical oxidation potential; AP=acidification potential; and HTP=human toxicity
potential.


g Biofilter
Packing

a STC Pellets


Operation

a~ Construction


ADP GWP POP


AP HTP


Impact Category and Technology









CHAPTER 6
SUMMARY, CONCLUSIONS, RECOMMENDATIONS AND BROADER IMPACTS

Summary

This research was conducted to investigate an activated carbon biofiltration system for

methanol control in the pulp and paper industry, as a more economical and environmentally

friendly alternative to thermal oxidation. This investigation focused on developing and testing a

bench-scale activated carbon bioailtration system containing a novel packing mixture and

capable of removing methanol from an artificially contaminated air stream in concentrations

representative of industrial processes. In addition, design and operation of this bioailter enabled

a more thorough study of the technology at a variety of scales and from both a theoretical and

practical perspective. These studies included 1) culture-dependent and independent microbial

ecology and molecular techniques to characterize biological samples from the pulp and paper

industry on the basis of selecting a bioailter inoculum and optimizing their growth and

biodegradation in mixed culture; 2) characterization of the activity and diversity of bacterial

communities derived from the biofilter under varied operating conditions over different points in

time; and 3) life cycle assessment to compare global environmental impacts of the proposed

system to those associated with thermal oxidation.

Conclusions

The results of this work have shown the following:

Biofilms obtained from a Kraft pulp mill could be enriched to support methanol
degradation in the batch culture as well as to be used as inoculum for an activated carbon
biofilter, as shown in Chapter 2.

Initial phenotypic characterization of the mixed methylotrophic cultures indicated that the
mill biofilms were host to highly diverse populations of bacteria able to rapidly degrade
methanol, which would make for straightforward provision of an inoculum culture if a
biofilter or other biological treatment system is implemented in the mill environment
(Chapter 2).











* The type of nitrogen source used when enriching mixed methylotrophic cultures as
potential bioailter inoculums influenced the growth and methanol degradation ability of
these bacteria, with faster growth and higher methanol removal in cultures enriched with
nitrate as compared to those enriched with ammonium, as shown in Chapter 3.

* Higher concentrations of the nitrogen source also resulted in greater methanol removal in
batch cultures (Chapter 3), although increasing the concentration did not significantly
affect growth rate of the mixed cultures. These results were promising for applications,
such as a bioHilter, where adding nitrogen could enhance methanol removal without
causing biomass overgrowth that could lead to clogging and minimized performance.

* The form of nitrogen used also affected the diversity and community structure of the
methylotrophic populations present in each of the Einal cultures (Chapter 3), as cultures
grown on nitrate maintained a higher diversity, as measured by species richness and
evenness observed from DGGE gels, compared to cultures enriched with ammonium.

* A bench-scale inoculated GAC biofilter (BB) system was successfully demonstrated for
the removal of methanol from an artificially contaminated air stream (Chapter 4). The
methanol removal efficiency for this system and an identical, non-inoculated biofilter
(NB) were similarly high (~100%) for both bioHilters over the maj ority of operating time.

* The excellent methanol removal was believed to be attributable to use of novel
heterogeneous bioHilter packing material containing a mixture of activated carbon, perlite,
slow release nutrient pellets, and water-retaining crystals. This packing material
provided excellent support for the growth and activity of methanol degrading bacteria
over time and during high variability in operating conditions.

* Although performance results for the two biofilters were similarly high, an examination
of the underlying microbiology using molecular methods showed that, in fact, they were
colonized by different populations of bacteria that were distributed differently throughout
the length of the biofilters. Bacterial abundance and diversity were both higher in the
inoculated biofilter, which may have contributed to the robust performance of the BB
over all operating conditions, even when the NB removal efficiency dropped periodically.

* The use of life cycle assessment (LCA) in Chapter 5 showed that a proposed novel
treatment system consisting a photocatalytic oxidation (PCO) reactor and activated
carbon biofilter had lower environmental impacts to resource depletion, photochemical
oxidant production, and acidification associated with its construction and operation, as
compared with a more traditional technology of a regenerative thermal oxidation (RTO)
and wet scrubber system.

* The PCO-biofilter system had higher life cycle impacts to global warming and human
toxicity (Chapter 5), because of the continual electricity input required to operate the UV
bulbs with the PCO reactor and the materials needed to produce the STC pellets. A
sensitivity analysis showed that minimizing electricity requirements for the PCO reactor









and maximizing the service life of bioHilter packing media and STC pellets would greatly
reduce environmental impacts for the PCO-biofilter system.

*Results of the LCA (Chapter 5) also showed that the impacts of producing infrastructure
required for the RTO and scrubber contributed up to 25% of the total life cycle impacts
for this system, which demonstrated the importance of including infrastructure impacts in
the LCA methodological framework.

This research demonstrated that an activated carbon biofilter system is an effective and

environmentally friendly option that could be developed for methanol control for the pulp and

paper industry, as well as other industry sectors that are challenged with controlling HAPs and

other volatile organic compounds (VOCs) in their process streams.

Recommendations and Broader Impacts

Based on results reported throughout this study, an activated carbon bioailter is a

promising technology for meeting methanol control requirements for pulp and paper mills.

However, limitations and additional questions that arose in this work have provoked new

questions that guide recommendations for extension of this investigation. For example, the

results that both an inoculated and non-inoculated biofilter provided excellent methanol removal,

despite different colonizing populations, can naturally be extended into a study that focuses on

the specific roles of the packing and the bacterial community. Additional study on the

interactions of the introduced and colonizing bacteria with the packing and with other types of

packing material could address this question. From a broader perspective, the results underscore

the need to examine microbial diversity as part of overall design and operation strategies and

performance measurements for bioHilters, rather than focusing on removal efficiency alone.

This type of study involving batch culture characterization is important as a first step

towards a better understanding of the ecology of methylotrophic bacteria and their potential use

in biological treatment systems. Results indicating a preference by the batch cultures for nitrate









as the nitrogen source should be extended through additional bench- and pilot-scale observations

of the methanol removal ability and underlying ecology and diversity of methylotrophic bacteria

in biological treatment applications using these and other nitrogen sources and concentrations.

Finally, the results of the LCA illustrated both the environmental and human health

benefits and disadvantages associated with a PCO-biofilter system, and these results can guide

specific modifications to this developing technology, such as reducing operational energy

requirements and increasing service life of the packing materials. Furthermore, this study

illustrates the benefits of adopting a life cycle perspective and considering environmental impact

for all stages of a process when selecting and implementing industrial technology. It is

recommended that this perspective be continually implemented throughout future work on these

systems, beginning at the lab and bench-scale and transcending to full scale technologies.











APPENDIX:
ADDITIONAL FIGURES


35


s 30


S25


rr20






~ 5


S0


100%

90%

80%

70%

60%
E
50%-
c





40%


0 10 20 30 40 50 60 70 80 90
Time (days)


Figure A-1. Methanol removal efficiency as a function of time and methanol loading rate, in a
preliminary trial of a biologically inoculated biofilters using SB as inoculum. Excessive
biomass formation and clogging was observed by day 20, which correlated with loss of
methanol removal performance.
















































y =1.0207x -0.8896 **
R2= 0.7525 + *


t*


Figure A-2. Photograph of preliminary biofilter, clogged by excess biomass when using SB as
inoculum .


Iog (c)


Figure A-3. Freundlich isotherm plot of batch isotherm results for the activated carbon biofilter
packing material.










PCR-DGGE with
mxcaF-specific primers


PCR-DGGE with
universal 16s rRNA primers


~"`"I
c ir


II
--


C I

~J --


BB
day
22


day day day day day day
22 46 77 102 125 138
Inoculum in Batch Culture


BB
day
22


day day day day day day
22 46 77 102 125 138
Inoculum in Batch Culture


Inoc


Inoc


Figure A-4. DGGE analysis of mxaF and 16s rRNA gene sequences from a long-term batch
culture created using the same biofilter inoculum derived from SA as used to inoculate
the activate carbon biofilter "BB."









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BIOGRAPHICAL SKETCH

Callie Whitfield Babbitt received her Bachelor of Science in chemical engineering from

the Georgia Institute of Technology in 2001 and her Master of Engineering in environmental

engineering sciences from the University of Florida (UF) in 2003. Her master' s research focused

on production, disposal, and beneficial use of coal combustion byproducts created during

electricity generation. Callie's current interests are in pollution prevention, life cycle

assessment, industrial ecology, and microbial ecology, specifically addressing the pulp and paper

industry. These topics stem from Callie's experience in the pulp and paper industry, where she

first became interested in pollution prevention. She previously worked for Georgia Pacific and

Buckeye Technologies, a specialty cellulose company. More recently, she worked as an assistant

on air emissions and permitting projects at Golder Associates in Gainesville, FL. Callie has been

a research assistant and teaching assistant for Dr. Angela S. Lindner in environmental

engineering sciences at UF for 5 years. She was also a research assistant with the UF Office of

Sustainability and the M.E. Rinker School of Building Construction.

These experiences shaped Callie's interest in creating environmentally and economically

sustainable solutions for industry and academic institutions. Her recent work as program

coordinator for Offce of Sustainability Initiatives at Arizona State University focused on

examining campus practices to reduce environmental impact and initiating programs to increase

environmental literacy and stewardship on the ASU campus. She recently completed a

university-wide greenhouse gas inventory and assisted in preparing the ASU Strategic Vision for

Sustainability. These projects sparked Callie's interest in social aspects of sustainability, and she

has taken a role as program coordinator for an interdisciplinary research proj ect entitled "Late

Lessons from Early History" in the School of Human Evolution and Social Change at ASU.





PAGE 1

1 PERFORMANCE, MICROBIAL ECOLOGY, AND LIFE CYCLE ASSESSMENT OF AN ACTIVATED CARBON BIOFILTE R FOR METHANOL REMOVAL By CALLIE WHITFIELD BABBITT 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

PAGE 2

2 2007 Callie Whitfield Babbitt

PAGE 3

3 To my grandmother, Mary Lou Whitfield, who in spires my love of learning and appreciation of the past; and to my daughter Nora Caroline Babbi tt, who inspires me to do my part to create a more sustainable world for future generations.

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4 ACKNOWLEDGMENTS I acknowledge and thank Dr. Angela S. Lindner, my supervisory committee chairperson, for her time, hard work, leadership, and guidance. Her passion for teaching and lifelong learning has been an inspiration to me, and her commitment to her students has made it possible for me to attain the goal of completing my Ph.D. I th ank my current and past committee members (Dr. Ben Koopman, Dr. David Mazyc k, Dr. Madeline Rasche, Dr. S pyros Svoronos, and Dr. ChangYu Wu) for their direction, time, and support. I am also very gr ateful to Adriana Pacheco for feedback, instruction, and suppor t throughout this project. I acknowledge and gratefully thank Re becca McLarty, Shweta Patole, Michael Friedlander, Mauricio Arias, and Jennifer Stokke for assistance in laborat ory data collection and sample analysis; the Environmental Engineering Sciences department faculty and staff members for assistance and guidance; Ashok Jain, Jim Stai nfield, and Karen Mentz (NCASI) for technical advisement and data analysis; and Timothy McKe lvey, Chet Thompson, Cecile Hance, and Myra Carpenter (industry representatives ) for tours, technical informa tion, and collection of biofilm and other process samples. This project was supported by the Depart ment of Energy, Award Number: DE-FC3603ID14437, the Sally and William Glick Foundati on 2005 Graduate Research Award, and a 2005 Air & Waste Management Associat ion Graduate Student Scholarship. Finally, and most importantly, I acknowledge and thank Greg Babbitt for his continued support and love; and Nora Babbitt, Sarah Whitfie ld, my parents Diane and Richard Whitfield, and all my family for their moral support, intere st in my work, and belief in my abilities.

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5 TABLE OF CONTENTS Page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........8 LIST OF FIGURES................................................................................................................ .........9 ABSTRACT....................................................................................................................... ............11 CHAPTER 1 INTRODUCTION................................................................................................................1 3 Background and Significance...............................................................................................13 Research Context............................................................................................................... ...16 Research Goals and Objectives............................................................................................19 2 INITIAL PHENOTYPIC CHARACTERIZATION OF METHYLOTROPHIC MIXED CULTURES FROM PULP AND PAPER MILL BIOFILMS.............................................21 Introduction................................................................................................................. .21 Methods...................................................................................................................... ..21 Sample Collection...................................................................................................21 Mixed Culture Enrichment.........................................................................................22 Colony Observations..................................................................................................23 Growth of Mixed Cultures in Liquid Medium with Methanol as the Carbon Source23 Results and Discussion......................................................................................................... 24 Colony Observations..................................................................................................24 Growth of Mixed Cultures in Liquid Medium with Methanol as the Carbon Source25 Conclusions................................................................................................................... ...25 3 EFFECT OF ENRICHMENT NITROGEN SOURCE ON THE GENETIC DIVERSITY AND METHANOL OXIDATION POTENTIAL OF TWO METHYLOTROPHIC MIXED CULTURES FROM PULP AND PAPER MILL BIOFILMS..............................30 Introduction.................................................................................................................. ....30 Methods...................................................................................................................... ..33 Sample Collection...................................................................................................33 Enrichment for Methylotrophic Bacteria....................................................................34 Comparison of Growth and Methanol De gradation Using Two Types of Nitrogen Source.....................................................................................................................34 Diversity of Microbial Populations in Cu ltures Enriched with Different Nitrogen Sources....................................................................................................................36 DNA Separation using DGGE....................................................................................38 DGGE Image Analysis...............................................................................................38 Diversity Measurements.............................................................................................38

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6 DNA Sequencing and Phyl ogenetic Analysis............................................................39 Results and Discussion......................................................................................................... 40 Comparison of Growth and Methanol De gradation Using Two Types of Nitrogen Source.....................................................................................................................40 Diversity of Microbial Populations in Cu ltures Enriched with Different Nitrogen Sources....................................................................................................................41 Phylogenetic Analysis of Dominant Species..............................................................42 Conclusions................................................................................................................... ...44 4 METHANOL REMOVAL EFFICIENCY AND BACTERIAL DIVERSITY OF AN ACTIVATED CARBON BIOFILTER................................................................................50 Introduction.................................................................................................................. ....50 Materials and Methods.........................................................................................................5 2 Selection of Biological Inoculum...............................................................................52 Selection of Packing Material.....................................................................................54 Biofilter Design..................................................................................................55 Biofilter Operation and Performance Measurements.................................................56 Abundance and Diversity of Microbial Populations in the Biofilter..........................57 DNA Extraction and Amplification............................................................................58 DNA Separation and Analysis....................................................................................60 DGGE Image Analysis...............................................................................................60 DNA Sequencing and Phyl ogenetic Analysis............................................................61 Results and Discussion......................................................................................................... 62 Biofilter Design..................................................................................................62 Biofilter Performance.................................................................................................63 Bacterial Counts over the Le ngth of the Biofilters.....................................................64 Bacterial Diversity Comparisons................................................................................65 Phylogenetic Analysis of Methylotrophic Bacteria....................................................68 Conclusions................................................................................................................... ...70 5 LIFE CYCLE ASSESSMENT OF TWO OPTIONS FOR CONTROLLING HAZARDOUS AIR POLLUTANTS AT PULP AND PAPER MILLS: A COMPARISON OF THERMAL OX IDATION WITH A NOVEL PHOTOCATALYTIC OXIDATION AND BIOFILTRATION SYSTEM.........................78 Introduction.................................................................................................................. ....78 Methods...................................................................................................................... ..79 Goal and Scope Definition..........................................................................................80 Inventory.................................................................................................83 Impact Assessment.................................................................................................84 Interpretation and Sensitivity Analysis.......................................................................85 Results..................................................................................................................... .86 Inventory.................................................................................................86 Impact Assessment.................................................................................................87 Sensitivity An alysis....................................................................................................87 Discussion................................................................................................................... .87

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7 Inventory.................................................................................................87 Impact Assessment.................................................................................................90 Interpretation...................................................................................................91 Conclusions................................................................................................................... ...93 6 SUMMARY, CONCLUSIONS, RECOMME NDATIONS AND BROADER IMPACTS107 Summary....................................................................................................................10 7 Conclusions................................................................................................................... .107 Recommendations and Broader Impacts............................................................................109 APPENDIX: ADDITIONAL FIGURES .....................................................................................111 LIST OF REFERENCES............................................................................................................. 114 BIOGRAPHICAL SKETCH.......................................................................................................123

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8 LIST OF TABLES Table page 2-1 Observations of mixed methylotrophic cult ure isolates grown on nitrate mineral salts agar plates.................................................................................................................... .........26 2-2 Growth characteristics of mixed methylotrophic cultures...................................................27 3-1 Bacterial species, divers ity, and evenness for SA and SB cultures in both AMS and NMS media...................................................................................................................... ....45 4-1 Summary of biofilter operating conditions..........................................................................72 4-2 Comparison of activated carbons and inoculation methods.................................................72 5-1 List of data sources used for major processes in compili ng the life cycle inventory of two alternative technologies for methanol control...............................................................95 5-2 Average fuel mix for electricity production in the United States and at an average pulp and paper mill................................................................................................................. ......96 5-3 Material and energy inputs from the “tec hnosphere” directly to and solid waste outputs from construction and operation of two altern ative technologies for methanol control......97 5-4 Raw material inputs, in kg per functional uni t, from nature into th e total life cycle of construction and operation of two alternat ive technologies for methanol control...............98 5-5 Emissions to air in kg per functional un it, for construction a nd operation of two alternative technologies for methanol control......................................................................99 5-6 VOC emissions, in kg per functional unit, from HVLC sources in the brownstock pulp washing process before treatment and estimat ed VOC emissions resulting from the two alternative technologies for methanol control....................................................................100

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9 LIST OF FIGURES Figure page 2-1 Sampling sites in the pulp and pape r mill wastewater treatment system.............................28 2-2 Growth in liquid culture ove r time for five biofilm enrich ment cultures (SA-SE) with initial methanol concentr ations of 0.2% by volume.............................................................29 3-1 Comparison of methanol removal by SA and SB cultures in both AMS and NMS medium with an ini tial methanol concentration of 1,000 mg/L...........................................45 3-2 Comparison of batch growth rates in SA and SB cultures in both AMS and NMS medium with an ini tial methanol concentration of 1,000 mg/L...........................................46 3-3 Bacterial diversity measured using PCR-DGGE analysis....................................................47 3-4 Phylogenetic reconstruction of known met hylotrophic bacteria and unknown culture strains using mxa F gene sequences......................................................................................48 3-5 Phylogenetic reconstruction of known bact eria and unknown culture strains using 16s rRNA gene sequences..........................................................................................................49 4-1 Biofilter operation schematic............................................................................................. .72 4-2 Methanol removal efficiency in the biologically inoculated and non-inoculated biofilters as a function of time and methanol loading rate. ...............................................................73 4-3 Abundance of cultivable bacteria in three sp atial regions of the bi ofilters using three types of culture media......................................................................................................... .74 4-4 Bacterial diversity of the biofilters over time, me asured using PCR-DGGE.......................75 4-5 Bacterial diversity of the biofilt ers in different spatial regions............................................76 4-6 Phylogenetic reconstruction of known met hylotrophic bacteria and unknown biofilter and inoculum strains using Neighbor Jo ining method. The inferred phylogeny was bootstrapped with 1,000 replicates, and bootstra p values greater than 75% are shown on corresponding branches...................................................................................................77 5-1 System boundaries for the life cycle of th e construction and operation of a regenerative thermal oxidizer (RTO) and caustic scr ubber for the treatment of methanol....................101 5-2 System boundaries for the life cycle of the construction and operation of a photocatalytic oxidation (PCO) reactor and biofilter for th e treatment of methanol.........102 5-3 Total comparative life cycle impacts, per functional unit, of the construction and yoperation of two alternative tec hnologies for methanol control......................................103

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10 5-4 Sensitivity analysis of wood or coal used as precursor material for granular activated carbon production, based on relative impact of the PCO-biofilter system as compared to the RTO-scrubber system...............................................................................................104 5-5 Sensitivity analysis of the lifetime of biofilter packing media and STC pellets, based on relative impact of the PCO-biofilter system as compared to the RTO-scrubber system...105 5-6 Sensitivity analysis of the lifetime energy requirement of UV bulbs in the PCO reactor, based on relative impact of th e PCO-biofilter system as co mpared to the RTO-scrubber system......................................................................................................................... ........106 A-1 Methanol removal efficiency as a functi on of time and methanol loading rate, in a preliminary trial of a biologically inoculat ed biofilters using SB as inoculum. Excessive biomass formation and clogging wa s observed by day 20, which correlated with loss of methanol removal performance......................................................................111 A-2 Photograph of preliminary biofilter, clogged by excess biomass when using SB as inoculum....................................................................................................................... ......112 A-3 Freundlich isotherm plot of batch isothe rm results for the acti vated carbon biofilter packing material............................................................................................................... ..112 A-4 DGGE analysis of mxaF and 16s rRNA gene sequences from a long-term batch culture created using the same biofilter inoculum derived from SA as used to inoculate the activate carbon biofilter BB............................................................................................113

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11 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 PERFORMANCE, MICROBIAL ECOLOGY, AND LIFE CYCLE ASSESSMENT OF AN ACTIVATED CARBON BIOFILTE R FOR METHANOL REMOVAL By Callie Whitfield Babbitt December 2007 Chair: Angela S. Lindner Major: Environmental Engineering Sciences The forest products industry is responsible for producing valuable industrial chemicals, wood products, and consumer goods. However, pro cesses involved in creati ng these materials at pulp, paper, and paperboard mills also genera te hazardous air pollutants (HAPs), such as methanol, that are released during wood pulp pro duction. With increasingly stringent regulations on methanol emissions, mills are continually seeki ng effective and cost efficient ways to control its release. Motivated by the need to study eco nomical and environmentally friendly methanol control technologies, a bench-scale activated carbon biofiltration syst em was developed and evaluated for its ability to remove methanol from an artificially contaminated air stream. The biofilter contained a novel packing mixture of activated carbon, perlite, slow release nutrient pellets, and water retaining crys tals, and showed excellent biof ilm growth and close to 100% biological methanol removal, both with and without addition of an inocul um containing enriched methanol-degrading bacteria. Design of the biofilter using an inoculum enri ched for methanol-degrading bacteria also facilitated characterization of biofilm samples from a pulp and paper mill on the basis of selecting a biofilter inoculum and optimizing growth and activity in mixed culture. Studies of

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12 enriched cultures from the biofilm samples s howed higher bacterial co mmunity diversity and methanol removal when using nitrate as the nitrogen source for enrichment, rather than ammonium. Design and operation of this bench-scale system also enabled further investigation with microbial ecology and molecular techniques to ch aracterize diversity of bacterial communities colonizing the biofilter over diffe rent points in time and under varied operational conditions. Amplification and separation of DNA from biof ilter samples, using polymerase chain reaction (PCR) and denaturing gel gradient electrophore sis (DGGE), indicated that although bacterial diversity and abundance varied over the length of the biofilter, the populations rapidly formed a stable community that was maintained over th e entire 138 days of opera tion and in variable operating conditions. Phylogenetic reconstruction of bands exci sed from DGGE gels indicated that the biofilter supported a diverse community of methanol-degrading bacteria. Finally, the design and operati on of the bench-scale biofilte r provided parameters for use in a life cycle assessment (LCA) that compared raw materials and ener gy required and emissions and environmental impacts produced by construc tion and operation of a proposed photocatalytic oxidation (PCO)-biofilter system, to those associ ated with treatment using a more traditional regenerative thermal oxidizer (RTO). LCA results indicated that environmental impacts associated with construction of a RTO far outwe ighed infrastructure requirements of the PCObiofilter system. However, the operating impacts to global warming and human toxicity for the PCO-biofilter system were higher than for the RTO, because of the replacement requirements of packing for the PCO reactor and biofilter, as well as the electricity requirement to operate the PCO reactor.

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13 CHAPTER 1 INTRODUCTION Background and Significance The forest products industry, specifically pu lp and paper mills, produces a variety of industrial and consumer products from wood cellulose, includi ng paper, paperboard, infant, female, and adult hygiene products, high poros ity filters, food casings, rayon filament, and chemicals such as ethers and acetate. Pulp re quired for these products is produced by physical processes that convert whole trees to wood chips and chemical pro cesses that digest the chips to produce either a brownstock or bleached fi nal pulp. Throughout many of these processes, organic compounds that are natu rally present in wood or produ ced during the degradation of cellulose are released to the environment. In 1998, the U.S. Environmental Protection Agency (U.S. EPA) passed a regulation known as the Cluster Rule, whic h regulates the release of thes e compounds to both the air and the water (U.S. EPA 1998). Air emissions included in the Cluster Rule that present established or potential impacts to human or environmental health are known as hazardous air pollutants (HAPs). The HAP of greatest concern is meth anol, which represents over 70% of the total release of HAPs from this industry, amounting to over 44,000 tons each year. (U.S. EPA 2004). Released in this quantity, me thanol can contribute to human health impacts, such as cancer, respiratory irritation, a nd damage to the nervous system (U.S. EPA, 1998). Other emissions include acetaldehyde, formaldehyde, me thyl ethyl ketone (MEK), methyl isobutyl ketone (MIBK), and -pinene, and reduced sulfur speci es including dimethyl sulfide, dimethyl disulfide, and methyl mercaptan, whic h are collectively termed total reduced sulfur (TRS). To prevent potential environmental and health impacts from these emissions, the Cluster

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14 Rule includes a section specifying the maximu m available control tec hnology (MACT) required to limit the amount of HAPs emitted. MACT regulations require that pulp and pa per mills collect and treat non-condensable gas from high volume low concentration sources (HVLC). HVLC gases are those with large volumes (typically 10,000-30,000 acfm for an en tire mill) and relatively dilute compound concentrations (below the lower explosion limit of the gas mixture) and are emitted from pulp washing systems, oxygen delignification systems, deckers, knotters, and black liquor storage tanks, etc. (Varma 2003). MACT regulations give pulp and paper mills flexibility of complying with emission limits with any technology pr oven to perform to at least the minimum requirements of the emission standards (98% me thanol removal) (U.S. EPA 1998). Most mills plan to comply with MACT by collecting the ga ses in vent hoods, using fans or blowers to transport the gases, and eliminating the HAPs by combustion in either an existing power boiler or lime kiln or in new stand-alone thermal oxi dizers (Varma 2003). Albeit effective, thermal oxidation has the drawbacks of requi ring a constant input of natura l gas or other fuel supply to support incineration and increasing th e emissions of carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen oxides (NOx). This technology also has very high capital costs, because of the need to install ductwork and other infr astructure for gas collection and transport. Therefore, a more environmental and economical solution is desired for HAPs control for pulp and paper industry. One technology proposed as an alternative to thermal oxidation is a photocatalytic oxidation (PCO) reactor containing a packed bed of a composite materi al of silica and the photocatalyst titanium dioxide (TiO2) (Stokke et al. 2006), in which the silica provides a catalyst support and adsorbs HAPs from the air stream wh ile the photocatalyst promotes destruction of these compounds when exposed to UV light. However, when the reactor is not functioning with

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15 maximum efficiency or if it is designed to rem ove less than 100% of incoming contaminant, the HAPs will not be completely eliminated from the gas stream, necessitating a secondary or polishing treatment step. This secondary sy stem would consist of a fixed bed granular activated carbon (GAC) biofilter, although such a bi ofilter may also serve as a primary treatment system. GAC is a highly porous adsorbent material th at removes contaminants by nature of van der Waals interactions between the contaminan ts and the carbon surface when they are in intimate contact (Dabrowski 2000). Activated ca rbon is produced from a carbonaceous material (typically wood, coal, or biomass residue) that is carbonized in the absence of oxygen and activated by either a chemical or physical proc ess that increases the porosity and changes the surface chemistry to enable high levels of adsorp tion of target contaminants (Menndes-Diaz and Martin-Gulln 2006). Adsorption is a finite proce ss, however, with a physi cal limit to the extent activated carbon can be used before its capacity is exhausted. One means of extending the GAC service life and the economic advantage of this technology is the incor poration of biological activity to create a synergisti c process by which the GAC adsorbs VOCs from the air stream, creating a favorable environment for the formation and maintenance of a stable microbial biofilm that subsequently degrades adsorbed and in coming organics (Aizpuru et al. 2003; Chang and Rittman 1987; Herzberg et al. 2003; Hodge and Devinny 1994; Weber and Hartmans 1995; Zhang et al. 1991). Considering the nature of the pulp and paper mill system, specifically warm temperatures, high humidity, and predominance of one-carbon compounds, biofilm formation, growth, and activity are expected to be inherent to the system. Based on the design objective to treat low or fl uctuating concentrations of VOCs in large volumes of gas (Kennes and Veiga 2001) and the expected availability of biological inoculum

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16 inherent to the pulp mill environment, an activat ed carbon biofilter would be an ideal solution for the polishing step of the methanol removal train. A biofilter has traditionally been characterized as having a fixed-bed containing in ert organic packing that serves as a carrier for biomass and a nutrient source, where contaminants in polluted air are degraded by the active biomass and where no mobile liquid phase is present (Dev inny et al. 1999; Kennes and Thalasso 1998; Kennes and Veiga 2001). This definition has be en expanded in recent research to include surface-active packing that provides adsorpti on capacity (e.g., for buffering peak loads or process instabilities) as well as inorganic packing with discon tinuous aqueous nutrient addition (Aizpuru et al. 2003; Prado et al. 2002; Teran-Perez et al. 2002; Yang et al. 2002). Use of activated carbon as the primary bi ofilter packing material (not just as inorganic support for compost or other organic packing) falls into both of the latter categories. Research Context A great deal of literature exists that addr esses the design, operation, and performance of biofilters for removal of contaminants from ga seous effluent streams (e.g., Devinny et al. 1999; Kennes and Thalasso 1998; Kennes and Veiga 2001) In many of such studies, a drop in a biofilters performance has been usually hypothesi zed to be due to factors such as excess or limited moisture, nutrients, or substrate, pH excursions, or biomass buildup or clogging (e.g., Gribbins and Loehr 1998; Jin-Yi ng et al. 2005; Teran-Perez et al. 2002; Yang et al. 2002). However, a disconnect exists in the literatu re between hypotheses about bacterial causes of reduced performance and actual observations of the bacterial systems or measurements of bacterial abundance or diversity. In addition, when inorganic ma terial such as activated carbon is used for biofilter packing, it is common to inocul ate the system with biological material able to grow and degrade contaminants under the conditi ons expected in the treatment train, including

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17 particular pH, temperature, and substrate con centration values (Devi nny et al. 1999) Often, these criteria arent explicitly investigated, but, rather, inoculum is derived from enrichment of available activated sludge or other waste materials (Aizpuru et al. 2003; Moe and Qi 2005), obtained from prior lab studies (H erzberg et al. 2003; Thalasso et al. 2000), or added as pure cultures (Speitel and McLay 1993). There is li ttle known about how the microbial populations used as inoculum actually influence the biofilter performance or the ultimate structure of the biofilm colonizing the packing media. Fortunately, more recent work has begun to fo cus on the relationships between biofilter performance and biofilm propertie s, including distribution, activit y, and kinetics of the attached biofilm (Song and Kinney 2000; Veiga et al. 1999) These studies and others focusing on the bacterial abundance and activity in biofilters (Acuna et al. 19 99; Aizpuru et al. 2003) used traditional culture-dependent techniques to enumerate bacteria present in the biofilm and correlate those results with phase s of operation and performance. The major limitation to such culture-dependent technique s is their potential bias to thos e organisms which grow fastest under lab conditions and their inability to adequately represent all microorganisms present (Hugenholz 2002). Therefore, molecular techniques have been increasingly used due to more readily available 16s rRNA sequences for comparison purposes (Clarridge 2004) and ever-improving methods for extracting, amplifying, and sequencing DNA directly from an environmental sample with no culturing required (Torsvik and Ovreas 2002). Examples of these methods include phospholipids fatty acid (PLFA) analysis, de naturing (or temperature) gradient gel electrophoresis (DGGE/TGGE), terminal restri ction length polymorphism (TRFLP), or ribosomal intergenic spacer analysis (RISA) (Torsvik and Ovreas 2002).

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18 DGGE in particular is a molecular me thod that is becoming very popular for investigating bacterial divers ity and community structure in environmental and applied biological systems. DGGE is an approach used to determine the gene tic diversity of mixed microbial populations by electr ophoresis of PCR-amplified DNA in a polyacrylamide gel with a linear gradient of denaturant (Muyzer et al. 1993 ). This approach has been popularized recently due to the reported abilit y to separate DNA fragments of the same length but slightly different sequences (e.g., single base change s, Myers et al. 1987), as based on the relative electrophoretic mobility associated with the me lting point of a given DNA sequence (Muyzer and Smalla 1998). The resulting banding pattern, when the gel is vi sualized using UV light, provides an illustrative comparison of frequency and presence or abse nce of banding patterns for different conditions investigated. DNA fragments associ ated with a banding pattern of interest can be excised from this gel, re-amplified, and sequenced to assess mutations or pres ence of specific bacterial strains, or the banding patterns can be mathematically assessed to determine relative changes in the diversity or phylogenetic richne ss (Ogram and Sharma 2002) to increase understanding of the microbial ecology of a system. For example, Li and Moe (2004) used DGGE to evaluate the spatial structure throughout the length of two type s of biofilters treating methyl ethyl ketone to explain the superior performance of one configuration ove r another. Others apply this method to determine the acclimation or stability of cultu res in biological treatm ent systems over time (Labb et al. 2003; Rombaut et al. 2001). Another approach has been to compare banding patterns generated from amplified sequences from functional genes to determine the relative abundance or dominance of specific types of bacter ia, such as different types of methanotrophs (Fjellbirkeland et al. 2001; Henckel et al. 1999) or denitrifiers (Goregues et al. 2005). Takaku et al. (2006) were able to relate si gnificant shifts in bacterial community st ructure, as assessed by

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19 DGGE, to distinct temperature changes in thei r system, while Sercu et al. (2005) compared attached biofilm diversity in a biotrickling filter to bacterial communities in the planktonic state. Even with these successes, th ere are also several limitati ons to the use of DGGE as a microbial ecology tool, namely the limitation to DNA fragments of about 500 bp or less, the production of anomalous PCR products from inco rporating a GC clamp into primers, and potential difficulty interpreting or comparing re sults (Gilbride et al. 2006; Bruns et al. 1991; Muyzer and Smalla 1998). In addition, the most common approach is to use 16S rRNA gene sequences for amplification, giving an idea of dive rsity of all bacteria present. Other than a small amount of work done to target specific bacterial groups, as disc ussed above, the use of functional genes has been much more limite d for a combined PCR-DGGE approach. Nevertheless, use of molecular methods such as DGGE can potentially offer a more detailed insight into the microbial ecology of biological systems, such as biofilters, than possible with performance measurements or cu lture-dependent studies alone. Research Goals and Objectives This research was motivated by the need to investigate a more economical and environmentally friendly methanol control technology for the pulp and paper industry, such as an activated carbon biofiltration syst em. With this goal in mind, the research reported herein focused on developing and testing a bench-scale activated carbon bi ofiltration system capable of removing methanol from an artificially contaminated air stream in concentrations representative of industrial processes. Operati on of this bench-scale system en abled further investigation with four specific objectives: 1. Collect and characterize biologi cal samples from the pulp a nd paper industry on the basis of selecting a biofilter inoculum and optimizing their gr owth and biodegradation in mixed culture using different nitr ogen sources and concentra tions (Chapters 2 and 3);

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20 2. Measure the methanol removal efficiency of the bench-scale biofilter containing a novel heterogeneous packing material comprised of granular activated carbon, perlite, slowrelease nutrient pellets, and waterretaining crystals (Chapter 4); 3. Use selected culture-depe ndent and independent micr obial ecology and molecular techniques, such as DGGE, to characteri ze the diversity of bacterial communities colonizing the biofilter over di fferent points in time, under va ried operational conditions, and at different spatial points in the biofilter (Chapter 4); and 4. Perform a life cycle assessment (LCA) to co mpare raw material and energy requirements and emissions and environmental impacts of the proposed photocatalytic oxidation reactor and biofiltration system to those asso ciated with traditiona l treatment systems, specifically regenerative thermal oxida tion and wet scrubbing (Chapter 5). A more thorough understanding of the biofilter technology as pa rt of a novel methanol treatment train promises to yield significant environmental and economic savings for the pulp and paper industry, as well as ot her industry sectors th at are challenged with controlling HAPs and other volatile organic compounds (VOCs) in their process streams.

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21 CHAPTER 2 INITIAL PHENOTYPIC CHARACTERIZATION OF METHYLOTROPHIC MIXED CULTURES FROM PULP AND PAPER MILL BIOFILMS Introduction Use of a biological system, such as a biof ilter, for treating air pollutants requires the presence of active microbial consortia that are cap able of degrading contaminants of interest. When inorganic material such as activated carbon is used, inocul ation with enrichments targeted for degradation of known concentrations of cont aminants under specific temperatures and pH, may be necessary (Devinny et al. 1999). Often, these cr iteria are not explicit ly investigated, but, rather, inoculum is derived from enrichment of available activated sludge or other waste materials (Aizpuru et al. 2003; Moe and Qi 2005), obtained from prior lab studies (Herzberg et al. 2003; Thalasso et al. 2000), or added as pure cultures (Speite l et al. 1993). Pulp and paper mills possess environments expected to be favorable for microbial growth, due to warm, moist conditions and the pres ence of readily degradable organic substrates. In fact, overabundance of biofilms or slimes at these mills often creates operational problems (Lahtinen et al. 2006), yet such biofilms could make ideal inocula for a biological treatment system. This chapter reports an initial characterization of biofilm samples collected from various locations at a southeast pulp, paper, and paperb oard mill that uses a biological wastewater treatment system. Traditional cu lture-dependent characterization me thods were used to evaluate and select potential inocula for s ubsequent biofiltration treatment for methanol removal from air. Methods Sample Collection Seven grab samples of biofilm samples coll ected from this mill were collected during June 2004, from locations believed by mill staff to be representative of methanol-degrading

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22 consortia or having a high number of bacteria present and stor ed on ice in sterilized Teflon collection vessels until they coul d be processed in the lab or st ored over a longer term at 4 deg. C. The locations of these samples, identified as Sample A-G (SA-SG) are as follows: Sample A (SA): Vent tubes of an oxygen activated sludge UNOX reactor Sample B (SB): Return activated sl udge (exiting secondary clarifiers) Sample C (SC): Wet material from cooling tower baffles Sample D (SD): Partially dry material from cooling tower baffles Sample E (SE): Wood wall outside of the cooling tower Sample F (SF): Secondary clarifier weirs Sample G (SG): Mixed liquor exiting the UNOX reactor The wastewater treatment system and se lected sites are shown in Figure 2-1. Mixed Culture Enrichment The samples collected were enriched in the laboratory in batch cu lture in a modified nitrate mineral salts medium (NMS) containing 0.2% methanol (vol/vol) as recommended by Hanson (1998). The basal medium contained, on a g/L basis: MgSO4*7H2O, 1.0; KNO3, 1.0; CaCl2, 0.2; KH2PO4, 0.026; Na2HPO4, 0.033. Trace elements were added, on a mg/L basis: FeSO4*7H2O, 0.5; ZnSO4*H2O, 0.4; EDTA disodium salt, 0.25; CoCl2*6H2O, 0.05; MnCl2*4H2O, 0.02; H3BO3, 0.015; NiCl2*6H2O, 0.01; Na2MoO4*4H2O, 0.005; and FeEDTA, 0.0038. Vitamins added, on a mg/L basis, were the following: biotin, 0.02; folic acid, 0.02; thiamin*HCl, 0.05; calcium pantothenate, 0.05; riboflavin, 0.05; nicotin amide, 0.05; and B12, 0.001. All chemicals used were obtained from Fish er Scientific (Pittsbu rgh, PA, USA) or Sigma Aldrich (St. Louis, MO, USA). Cultures were maintained in a 1:10 ratio of inoculum:medium to a total volume of 55 mL in 250 mL Erlenmeyer flasks at 30 oC on a rotary shaker at 250 rpm. Initial enrichment cultures were incubated for one month, while subsequent transfers to fresh media were prepared on a bimonthly basis. Two cultures, derived from the samples taken from the secondary clarifier (SF)

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23 and the mixed liquor exiting the UNOX reactor (S G), were not easily maintained in batch culture, due to continual creation of pellicles in liquid solution and lack of turbidity formation. For that reason, these two cultu res were not compared with the others for many of the characterization tests. Colony Observations Serially diluted samples from the five remaining cultures were spread-plated on NMS agar plates, two months after ini tial enrichment, and incubated at 30 oC with methanol present in the vapor phase. Colonies appearing to be morphologically unique from each other by inspection under light microscope were transf erred by streaking onto new NMS plates in an attempt to obtain relatively pure isolates. These transfers were conducted so that morphological distinctions between isolates could be obs erved, with the goal of determining how many potentially different strains might be present in th e cultures. Observations included color, shape, transparency, and edge of the colony, as well as Gram stain, and motility. Colonies were also streaked onto tryptic soy and nutrien t agar plates and incubated at 30 oC with no methanol present, to determine the ability of the isolates to grow on multiple carbon sources. Growth of Mixed Cultures in Liquid Medium with Methanol as the Carbon Source In addition to morphological distinctions am ong the cultures, Samples A-E cultures were also observed on their ability to grow in liqui d media with methanol as the sole carbon and energy source. Enriched mixed cultures were grown to log phase, harvested by centrifugation in a J2-HS Beckman floor mode l centrifuge (Beckman Coulter, Inc., Fullerton, CA, USA), then twice washed with phosphate buffer and recentrifuge d to remove residual methanol. Cells were resuspended in the NMS medium to obtain an op tical density of 0.1 at 600 nm, and aliquotted in triplicate into side-arm flasks to a final ratio of 1:10 cells to medium. Liquid methanol was

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24 added to the mixture to a final concentration of 0.2% by volume, and the cultures were incubated for nine days on a rotary shaker at 250 rpm and 30 oC. Growth, assayed by optical density, was measured using a spectrophotometer at 600nm, dir ectly from the sample in the glass vial. Results and Discussion Colony Observations Isolated strains from the five mixed met hylotrophic cultures (S A-SE) were grown on solid agar plates with methanol in the va por phase and observed based on their morphology, motility, and Gram stain (on NMS plates), as we ll as their growth on multi-carbon tryptic soy agar (TSA) and nutrient agar plat es, with results shown in Table 2-1. Cultures from samples SA and SB appear to have the most distinct isol ates as cultured under th ese lab conditions, which possibly may represent higher divers ity in their natural environment, an ideal characteristic of bacterial consortia used for biol ogical treatment systems. All but one of the isolates was Gram negative, and the isolate (number 1 from SB) th at tested Gram positive showed inconclusive results on repeated testing. Only one of the isolates, number 6 fr om SB, showed clear signs of motility. Lack of motility may be related to the enrichment of samples collected from a biofilm environment, which, in the mill environment, may cause selection for bacteria that can attach to surfaces, rather than for those with appendages required for motili ty in a suspended state (Dunne 2002). Colonies obtained from all five samples showed a variety of morphological differences, with colors ranging from clear to beige and op acity from transparent to semi-opaque. The various colonies were both irre gular and circular in shape an d were observed to have edge margins including lobate (irregular lobes), erose (serrated), undul ate (wavy), curled, filamentous, and entire (smooth). Colony elevations ranged from completely flat to convex, to pulvinate (completely rounded). All colonies except three (number 4 in SA and numbers 2 and 3 in SB)

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25 were observed to show at least some growth on TSA and nutrient plates. The ability for growth on multi-carbon source plates indicates that the bacterial cultures enriched from the biofilms likely contain facultative or rest ricted facultative methylotrophs, those bacteria capable of using methanol or other compounds with carbon-carbon bonds as a carbon source (Lidstrom 2001). Growth of Mixed Cultures in Liquid Medium with Methanol as the Carbon Source Growth rates for the five mixed methylotr ophic cultures are shown in Figure 2-2, with error bars representing the standard error for opti cal density measurements in triplicate. In many cases, the error is relatively high because of interference from the suspended and attached pellicles formed by the bacteria in the growth fl ask. Additional parameters extracted from this growth curve are given in Table 2-2, including the lag time, growth ra te, and generation (or doubling) time. Based on these results, culture s from SB and SC exhibited the fastest acclimation and highest biomass production within th e batch culture. Cultures from SA and SB showed the shortest lag time from inoculati on until growth commenced, while cultures from SA, SB, and SC exhibited the fastest growth rate Conclusions Phenotypic observations from this initial char acterization indicated that the mill biofilms may be host to highly diverse populations of b acteria, which would make for straightforward provision of an inoculum culture if a biofilter or other biological treatment system were to be implemented in the mill environment. Based on potential high diversity (as observed by the number of distinct colony isolates), ability fo r isolates to grow on multiple carbon sources, and minimal lag time and rapid growth rate in liquid culture, SA and SB were selected as the best potential biofilter inocula, and were further characterized on the basis of their methanol degradation potential using di fferent nitrogen sources, as reported in Chapter 3.

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26Table 2-1. Observations of mixed met hylotrophic culture isolates grown on nitrate mineral salts agar plates Sample Isolate Color TransparencyForm Elevation Margin Growth on Methanol Growth on Tryptic Soy Agar Growth on Nutrient Agar Gram Stain Motility 1 Clear Transparent Irregular Flat Lobate ++ +++ +++ (-) (-) 2 Pale Yellow Transparent Circular Pulvinate Lobate ++ +++ +++ (-) (-) 3 Pale Yellow Transparent Irregular Pulvinate Lobate ++ +++ +++ (-) (-) 4 Yellow Semi-OpaqueCircular Umbonate Erose ++ + (-) (-) 5 Pale Yellow Transparent Irregular Pulvinate Undulate + +++ ++ (-) (-) 6 Clear Transparent Irregular Flat Undulate +++ +++ ++ (-) (-) A 7 Clear Transparent Irregular Flat Undulate ++ ++ +++ (-) (-) 1 Beige Transparent Irregular Umbonate Curled +++ + + (-) (+/-) 2 Clear Transparent Circular Convex Entire + (-) (-) 3 Clear Transparent Circular Convex Entire ++ (-) (-) 4 Beige Semi-OpaqueFilamentousConvex Filametous++ ++ ++ (-) (-) 5 Yellow Semi-OpaqueCircular Convex Undulate + ++ ++ (-) (-) 6 Yellow Semi-OpaqueCircular Convex Entire +++ ++ ++ (+) (-) B 7 Beige Transparent Circular Umbonate Curled +++ ++ ++ (-) (-) C 1 Clear Transparent Circular Convex Entire ++ + + (-) (-) 1 Pale Yellow Semi-OpaqueCircular Umbonate Entire ++ ++ + (-) (-) 2 Clear Transparent Circular Flat Erose + ++ +++ (-) (-) D 3 Pale Yellow Semi-OpaqueCircular Convex Undulate ++ ++ + (-) (-) 1 Clear Transparent Irregular Flat Lobate +++ + + (-) (-) 2 Yellow Semi-OpaqueCircular Umbonate Erose +++ ++ + (-) (-) 3 Clear Transparent Irregular Umbonate Lobate ++ ++ + (-) (-) 4 Clear Transparent Circular Umbonate Undulate ++ ++ ++ (-) (-) E 5 Clear Transparent Irregular Flat Curled +++ ++ ++ (-) (-) For growth measurements, no sign indicates no growth; + indicates minimal growth; ++ indicates gr owth over at least 50% of the plate; +++ indicates excellent growth over at least 75% of the plate. For motility and gram stain, (+) indicates a positive res ult, (-) indicates a negative result.

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27 Table 2-2. Growth characteristics of mixed methylotrophic cultures Culture Source of Inoculum Lag Phase (hr) Growth Rate (hr-1) Generation Time (hr) A Enclosed Aeration Basin Vent Tube 21.0 0.111 6.26 B Return activated sludge 17.5 0.132 5.24 C WWT cooling tower baffle (wet) 31.0 0.172 4.04 D WWT cooling tower baffle (dry) 25.7 0.093 7.49 E WWT cooling tower wall 25.7 0.062 11.2 Biofilm samples collected from the secondary clarifier weirs (F) and from mixed liquors (G) were not able to be enriched in the lab. A ll samples were obtained from the wastewater treatment (WWT) system of a southeast paper and paperboard mill. Growth parameters are based on liquid culture containing initial methanol concentrations of 0.2% by volume.

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28 Figure 2-1. Schematic of sampling sites in the pulp and paper m ill wastewater treatment system: A: Vent tubes of an oxygen acti vated sludge UNOX reactor; B: Return activated sl udge (exiting secondary clar ifiers); C: Wet material from cooling tower baffles; D: Partially dry material from cooling tower baffles; E: Wood wall outside of th e cooling tower; F: Sec ondary clarifier weirs; G: Mixed liquor exiting the UNOX reactor. C,D,E A G F B

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29 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 020406080100120140160180200220 Time (hr)Optical Density at 600 n m SA SB SC SD SE Figure 2-2. Growth in liquid cultur e over time for five biofilm enri chment cultures (SA-SE) with initial methanol concentr ations of 0.2% by volume.

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30 CHAPTER 3 EFFECT OF ENRICHMENT NITROGEN SO URCE ON THE GENETIC DIVERSITY AND METHANOL OXIDATION POTENTIAL OF TWO METHYLOTROPHIC MIXED CULTURES FROM PULP AND PAPER MILL BIOFILMS Introduction Methylotrophic bacteria are ubiquitous in many aquatic and terrestrial environments and play an important role in the carbon cycle because of their ability to oxidize methane, methanol, and other reduced carbon substrates. Many prev ious studies on methylotrophs have focused on methanotrophs, a functional group of methylotrophs able to utili ze methane as their sole carbon source. Within this body of work (e.g., Conrad 1996; Hanson and Hanson 1996; King 1992), interest has been directed towa rds the role of methanotrophs in oxidizing methane, a greenhouse gas, andingand cometabolizing toxic hydrocarbons. However, less attention has been given to the potential use of methylotr ophs in removing methanol, a co mmon pollutant in aqueous or gaseous industrial effluents. The paper and allied products industry is a major contributor of methanol emissions, where it is produced during wood pulping and released to the ai r and discharged in the mill wastewater (Someshwar and Pinkerton 1992). For example, in 2002, the top three facilities reporting the largest methanol emissions through the Toxic Release Inventory (approximately 10.8 million pounds) were paper and allied product s companies (Scorecard 2007). While most pulp mills comply with regulations to control these methanol emissions by incinerating the methanol in thermal oxidation systems (Varma 2003), environmental and economic advantages potentially are achieved by using a biological treatment system that takes advantage of the natural methanol degradation ab ility of the diverse bacteria classified as methylotrophs.

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31 One biological system of interest is a granul ar activated carbon (GAC ) biofilter, in which the activated carbon provides an adsorptive fixed bed where degrading microorganisms are immobilized. Organic contaminants present in the air flowing thr ough the bed ideally are removed by a synergistic mechanism of adso rption by the GAC and biodegradation by the microorganisms. As such, this biological sy stem requires the presence of active microbial consortia that are capable of de grading contaminants of interest under the conditions expected to be present in the treatment trai n, including specific pH, temperatur e, and substrate concentration values (Devinny et al. 1999) When considering treatment of ga seous methanol from a pulp and paper mill, using as an inoculum mixed methylotrophic bacterial cultures enriched from samples obtained from the mill has been demonstrated to influence the ultimate community structure of bacteria colonizing GAC biofilter, while the speci fic role of the biological community in the biofilter in removing methanol a nd the effects of conditions in the biofilter on the populations have not been entirely iden tified (Babbitt et al. 2007). An important criterion that has not been fully investigated is the importance of the form and concentration of the nitrogen source used in enriching for me thylotrophs or supporting their growth and activity in liquid culture or in app lications such as a biofilter. The intermittent addition of nitrogen in a mineral salts mixture ha s been demonstrated to improve the capacity of biofilters in removing ethanol (Tern Perez et al 2002) and toluene (Prado et al. 2002). Addition of greater concentration of nutrients appears to be most import ant when the biofilter is subjected to high mass loading rates (Gribbins and Loehr 1998). When compar ing nitrogen added as either nitrate or ammonium, Yang et al. (2002) dem onstrated that ammonium resulted in higher elimination capacities in a meth anol biofilter but that, at hi gh nitrogen-to-carbon ratios, the ammonium could also inhibit meth anol removal. The added nitrat e did not show this inhibitory

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32 effect (Yang et al. 2002). Despite the benefit of these studies, it is still unclear how the type and concentration of nitrogen used directly affects the methanol degradation potential of mixed methylotrophic cultures a biofilter application. When considering batch cultures, extensiv e work has been conducted to select and optimize nutrients, growth factors, trace el ements, and substrate concentrations for methanotrophs (Bowman and Sayler 1994; Park et al. 1992; Park et al 1991). Less specific attention has been focused on enrichment of the more general group of methylotrophs. For example, use of specific nutrient sources, particular ly nitrate or ammonium as a nitrogen source, is not consistently repo rted in studies involving methylotr ophs. In part, this inconsistency appears to be due to early work showing better growth of methanotrophic bacteria when using nitrate (Whittenbury et al. 1970), which has been more recently been associated with the possibility that ammonium inhibits methane oxida tion in these bacteria (B oiesen et al. 1993; De Visscher and Van Cleemput 2003; Hi ggins et al. 1991). Therefore, some recommendations for growth of restricted or faculta tive methylotrophic bacteria foll ow those for methanotrophs (e.g., use of nitrate as nitrogen source) (Hanson 1998), whereas other studies re port use of ammonium as the nitrogen source, in varied concentrations (Patt et al. 1974, El-Nawawy et al. 1990). The effect of form and concentration of nitrogen on methanol degradation pote ntial of methylotrophs is also not clearly understood, nor are the effect s on population diversity a nd stability. Selection and enrichment of an appropria te inoculum for biological treat ment systems, such as GAC biofilters, may be greatly impr oved with additional knowledge of optimum nutrient requirements and concentrations. As an initial step towards this goal, this paper reports the effect of the form and concentration of nitrogen in batch enrichment cultures on the growth and methanol removal

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33 potentials and the genetic divers ity of methylotrophic cultures enriched from biofilm samples taken from a Kraft pulp mill. Methods Sample Collection To study the effect of nitrogen source and c oncentration on methylot rophic cultures that could be used as biofilter inoculum, sampling and analysis was focused on biofilms and other biological cultures obtained directly from a pulp mill environment. These biological samples were obtained from a pulp and paperboard co mpany located in the Southeast and with a biological waste water treatment system. Seven grab samples of biofilm were collected during June 2004 from locations believed by mill staff to be representative of methanol-degrading consortia or having a high number of bacteria present, and stor ed on ice in sterilized Teflon collection vessels until they could be processed in the lab or stored over a longer term at 4 oC. Initial culture-dependent growth and isolation techniques demons trated that two of the seven samples could be good candidates for inocula in a methanol treatment system, based on their superior growth and methanol degradation rates and morphologically diverse, culturable community (determined by identification of visibly distinct colonies on agar plates) (as discussed in Chapter 2). These samples, A and B, were named SA and SB and described as follows. The SA biofilm was obtained directly from th e vent tubes of a pure oxygen activated sludge UNOX (Union Carbide Oxidation) reactor, where the conditions would be expected to include temperatures between 32-36 oC, methanol concentrations between 1,000-5,000 mg/L, and nitrogen as ammonium in concentrations be tween 20-140 mg/L (ammonium is added to the reactor to improve performance) SB biofilm was collected from the return activated sludge

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34 system, with conditions expected to in clude ambient outdoor temperatures (26-30 oC), and low methanol (<10-100 mg/L) concentrations. Enrichment for Methylotrophic Bacteria Subsamples (10 mL each) from SA and SB were first homoge nized in 90 mL of sterile phosphate-buffered solution for one hour on a rotary shaker at 30 oC at 250 rpm, then this mixture was used to inoculate batch cultures in both modified nitrate mineral salts (NMS) and ammonium mineral salts (AMS) media, containi ng 0.2% methanol (vol/vol) as recommended by Hanson (1998). The basal medium contained, on a g/L basis: MgSO4*7H2O, 1.0; CaCl2, 0.2; KH2PO4, 0.026; Na2HPO4, 0.033. Trace elements were added, on a mg/L basis: FeSO4*7H2O, 0.5; ZnSO4*H2O, 0.4; EDTA disodium salt, 0.25; CoCl2*6H2O, 0.05; MnCl2*4H2O, 0.02; H3BO3, 0.015; NiCl2*6H2O, 0.01; Na2MoO4*4H2O, 0.005; and FeEDTA, 0.0038. Vitamins were added, on a mg/L basis: biotin, 0.02; folic acid, 0.02; thiamin*HC l, 0.05; calcium pantothenate, 0.05; riboflavin, 0.05; nicotinamide, 0.05; and B 12, 0.001. The nitrogen source was added to the medium as nitrate (1.0 g/L KNO3) or ammonium (0.5 g/L NH4Cl). All chemicals used were obtained from Fisher Scientific (Pittsburgh, PA, USA) or Sigma Aldrich (St. Louis, MO, USA) and were of the highest purity available. Th e cultures were maintained in a 1:10 ratio of inoculum to medium to a total volume of 55 mL in 250 mL Erlenmeyer flasks at 30 oC on a rotary shaker at 250 rpm. Initial enrichment cultures were incubated for one month, while subsequent transfers to fresh medium were made twice, with a tw o-week period between transfers. Comparison of Growth and Methanol Degradation Using Two Types of Nitrogen Source To compare methanol degradation by batc h mixed methylotrophic cultures with two potential nitrogen sources, a factorial (32) design was used. This de sign included either nitrate

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35 added as KNO3 at levels of 0, 1.0, and 2.0 g/L or ammonium added as NH4Cl at levels of 0, 0.5, and 1.0 g/L (these represent 0, 0.13, and 0.26 g N/L), and metha nol added at 10, 100, and 1000 mg/L in the liquid phase. These nitrogen levels reflect common ranges used in both batch and in biofilter applications (Yang et al. 2002; Gribbins and Loehr 1998). Concentrations of 0 g N/L were also included to assess whether the cultures could degrade methanol with only soluble cell nitrogen or atmospheric N2 present, as such a condition might be expected if nutrients become exhausted in a biofilter or even in a batch culture. The last transfer of the enrichment cultu res was made to a 2400 mL flask, in which 500 mL of the culture was grown to log phase, harvested by centrifugation in a J2-HS Beckman floor model centrifuge (Beckman Coulter, Inc., Fullerton, CA, US A), then twice washed with phosphate buffer and recentrifuged to remove re sidual nitrogen and methanol. Cells were resuspended in the appropriate mineral salts medi um with no added nitrogen to obtain an optical density of 0.1 at 600nm. For each combination of nitrogen and carbon concentrations, a master mixture of cells and medium in a 1:10 ratio wa s prepared. Liquid methanol was added to the mixture to the desired concentration, and 4 mL from each master mixture was aliquotted into 20 mL glass vials and sealed with crimp top Teflon-lined septa. Three identical cultures were prepared for each of the nine nitrogen and metha nol combinations. Control vials were prepared with killed cells and with no cells, to account for any methanol that might be removed by physical adsorption to the cells or volatilized during the handli ng and analysis process. The cultures were incubated for 48 hours on a rotary shaker at 250 rpm and 30 oC. Every 4-6 hours during this incubation, growth, assayed by optical density, was measured using a spectrophotometer at 600 nm, directly from the sa mple in the glass vial. At 48 hours, the cells were pelleted using the floor centrifuge, and 2 mL of the liquid supernatant were collected and

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36 analyzed for final methanol concentration. Aque ous methanol concentrations were analyzed by GC/FID using a Clarus 500 (PerkinElmer, Wellesl ey, MA, USA), with helium at 31.3 psig as the carrier gas, and hydrogen and ai r at 45 mL/min and 450 mL/mi n, respectively, as combustion gases. Cyclohexanol was used as the internal standard. Diversity of Microbial Populations in Cultu res Enriched with Different Nitrogen Sources To determine the genetic di versity of the bacterial popul ations enriched from both samples with both nitrogen sources, denatu ring gradient gel elec trophoresis (DGGE) was performed using the polymerase chain reac tion (PCR)-amplified DNA extracted from the enriched cultures and from the original biofilm samples. Genomic DNA was extracted from the same SA and SB cultures in both AMS and NMS that were used to initiate the methanol oxidation study, using UltraClean Microbial DNA kits (MO BIO Laboratories, Carlsbad, CA, USA) and the accompanying protocol for DNA ex traction and purifica tion from microbial samples. In addition, DNA was extracted from the original SA and SB biofilm samples using UltraClean Soil DNA kits (MO BIO Laboratorie s, Carlsbad, CA, USA) and the accompanying protocol for DNA extraction. The polymerase chain reaction (PCR) was used to amplify specific DNA sequences found in expected methylotrophic (methanol-oxidi zing) populations in the biofilm. In all known gram-negative methylotrophic bacteria, methanol oxidation is catalyzed by the enzyme methanol dehydrogenase (MDH), the large sub unit of which is encoded by th e highly conserved functional gene mxaF (Barta and Hanson, 1993; McDonald and Murrell, 1997). Therefore, mxaFspecific primers f1003 (5-3 GCC CGC CGC GCC CCG CGC CCG TCC CGC CGC CCC CGC CCG GCG GCA CCA ACT GGG GCT GGT), which include s a 39-bp GC-clamp at the 5 end, and r1561 (5-3 GGG CAG CAT GAA GGG CTC CC) were used to detect methylotrophs as

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37 described by McDonald and Murrell (1997) a nd McDonald et al. (1995). The 16S rRNA sequences were amplified using primers f27 (5-3 CGC CCG CCG CGC GCG GGC GGG GCG GGG GCA CGG GGG GAG AGT TTG ATC MTG GC T CAG), which includes a 40-bp GC clamp at the 5 end, and r534 (53 ATT ACC GCG GCT GCT GC). Initial PCR and DGGE conditions were based on Henckel et al. (1999) Fjellbirkeland et al. (2001), McDonald et al. ( 1995), and McDonald and Murrell (1997), but optimized for this specific system and primer set. The PCR reac tion mixture was prepared in 0.2 mL thin-walled PCR tubes and contained 1X MgCl2-free PCR buffer, 1.5 mM MgCl2, 100 uM of each dNTP,1U Taq polymerase (all from Invitrogen, Carlsbad, CA, USA), 0.5M of each primer (Integrated DNA Technologies, Inc, Coralville, IA, USA.), 1-2 L of template DNA (50-100 ng), and sterile water to a final volume of 50 L. Amplifications with mxaF primers were carried out using a Mastercycler Personal 5332 thermocycler (Eppe ndorf North America, Westbury, NY, USA) with the block preheated to 92 oC, using a reaction program of initial denaturation at 92 oC for 3 minutes, a total of 30 cycles of denaturation (30 seconds at 92 oC), annealing using a touchdown program (30 seconds per cycle from 60 to 50 oC at -0.5 degrees/cycle fo r the first 20 cycles and 50 oC for the last 10 cycles), and extension (45 seconds at 72 oC), and a final extension at 72 oC for four minutes. The same reaction setup wa s used for the 16s rRNA primers, but with an annealing touchdown temperature profile of the first 10 cycles from 55 to 50 oC at -0.5 degree/ cycle and the last 20 cycles at 50 oC. The touchdown program was used because it increased yield and number of bands observed on s ubsequent DGGE gels, over a set annealing temperature. PCR products were verified on a 1.2% agarose gel, photographed, and their yield estimated using ImageJ software (Rasband, 2006) calibrated with a low DNA marker (50-2,000 bp, BioNexus, Inc, Oakland, CA, USA.).

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38 DNA Separation using DGGE DNA fragments were separated using denatu ring gel gradient electrophoresis (DGGE) with a 16x16 cm, 1 mm thick gel co ntaining 6% acrylamide, 1X TA E, and a linear gradient of 35-65% denaturant (100% denatura nt is equivalent to 7 M urea and 40% formamide), cast for 90 minutes. Approximately 500 ng of PCR product wa s mixed with 10-20 L of 2X gel loading dye (70% glycerol, 0.05% Bromophenol Blue 2mM EDTA), loaded on the gel, and electrophoresed at 60 oC for 5 hours at 150V in 1X TAE, using a DCode Universal Mutation Detection System Model 475 Gradient Delivery Sy stem (Bio-Rad Laboratories, Hercules, CA, USA). Gels were stained with 50 g/mL ethi dium bromide in 1X TAE for 15 minutes and destained in 1X TAE for 10 minut es. Bands were visualized and photographed using a Fisher Biotech Model 88A variable UV intensity Trans illuminator and DCode Do cIt software system (Bio-Rad Laboratories, Hercules, CA, USA). DGGE Image Analysis The digitized gel images were analyzed using ImageJ (Rasband 2006). The background was subtracted using a rolling ball radius of 50. Bands in each lane were automatically detected and plotted. Peak area and rela tive intensity of each band was measured, and bands contributing less than 1% to the total intensity within one lane were omitted from subsequent analysis. Diversity Measurements Diversity in each sample was estimated using measurements of species richness (S), diversity (H), and evenness (E). S was determin ed by simply counting the bands in each lane, with the assumption that a single species woul d migrate to each unique location. Shannons H (Hayek and Buzas 1997) was used as a diversity index (Equation 3-1). i i ip p H ) ln( (3-1)

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39 where pi is the relative intensity of the ith band compared to the total intensity of all bands in that lane. E was calculated from Pielous evenness (Equation 3-2) (Hayek and Buzas 1997). ) ln( S H E (3-2) DNA Sequencing and Phylogenetic Analysis To further characterize the bacteria under bot h nitrogen use profiles, selected bands from the mxa F and 16s rRNA DGGE gels were excised for sequenc ing. Bands were chosen from DNA that showed the highest intensity when vi sualized on the UV transilluminator and were excised using a sterile pipet tip and scalpel. The gel fragment s were eluted overnight at 30 oC at 250 rpm in 30 L of an eluti on buffer containing 10mM Tris-Cl (pH 7.5), 50 mM NaCl, and 1mM EDTA (pH 8.0) (Chory and Pollard 1999). Gel fragments were removed, and DNA was precipitated from the liq uid by adding 50 L of 95% cold et hanol, chilling 30 minutes at -40 oC, and pelleting the DNA by centrifuging 10 minutes at 10,000xg. After pouring off the ethanol supernatant, the pellet was dried at 40 oC for 4-5 hours and resuspended in 30 L of TE buffer (Chory and Pollard 1999). This template was re amplified using the same methods as described previously and checked on a DGGE gel for purity a nd for migration to the same gradient position as in the original sample. Sequencing wa s performed at the University of Florida Interdisciplinary Center for Biotechnology Research (ICBR) using the fluorescent dideoxy terminator method of cycle sequ encing on either a Pe rkin Elmer Applied Biosystems Division (PE/ABD) 373A or 377 automated DNA sequencer, following ABD protocols, with consensus sequences generated using the Sequencher Softwa re from Gene Codes. Sequences of partial mxa F and 16s rRNA gene fragments have been depos ited in the GenBank database. Fragments M1, M3, and M6 were identical to bands sequen ced from biofilter samples (Babbitt et al. 2007), which have previously been submitte d under accession numbers EU099402, EU099404, and

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40 EU099407, respectively. For this study, mxa F fragments M2, M4, and M5 were submitted under accession numbers EU138867, EU138868, and EU 138869, respectively; and 16s rRNA fragments U1-U7 were submitted under acc ession numbers EU138870-EU138876, respectively. Published sequences with high similarity to sample sequences were obtained by performing a nucleotide-nucleotid e BLAST (NCBI) search. The 10 most similar sequences of known species with E scores lower than 1E-20 we re chosen for each sample, with duplicates removed. Sequences were aligned using Clusta lW, with default gap penalties, and manual inspection and refinement of alignments. A phylogenetic tree was constructed using the Neighbor Joining method and bootstrapped w ith 1,000 replicates. Because all known proteobacteria clustered into a distinct branc h, this group was selected as the out-group. All phylogenetic and molecular evolution analyses were conducted using MEGA version 3.1 (Kumar et al. 2004). Results and Discussion Comparison of Growth and Methanol Degradation Using Two Types of Nitrogen Source The two pulp mill biofilm samples (SA and SB ), enriched using different nitrogen sources, were compared on the basis of metha nol degradation under different methanol and nitrogen concentrations. Both samples, regardle ss of nitrogen source or concentration, showed 100% methanol removal for initial methanol c oncentrations of 10 and 100 mg/L. Differences among the cultures became apparent when metha nol was introduced at concentrations of 1,000 mg/L. The percent of methanol removed, based on an initial 1,000 mg/L c oncentration, is shown in Figure 3-1. For all of the cultures, the per cent of methanol removed from the liquid phase increased with increasing nitrogen concentration. In addition, for all of the cultures assessed in medium with added nitrogen, a higher methanol removal was achieved when nitrate served as

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41 the nitrogen source. In fact, the SB culture enriched in NMS medi um with the highest concentration of nitrate (0.26 g N/L) showed 100% removal. On the other hand, after transfer to medium with no added nitrogen, both SA cultures showed signifi cantly higher methanol removal than SB, regardless of the original enrichment N-source. A slightly different trend was observed when comparing growth rate with an initial 1,000 mg/L methanol concentration a nd varied nitrogen sources and concentrations (Figure 3-2). These results showed that the mixed cultures grew almost equally as fast with either ammonium or nitrate present at the high ( 0.26 g N/L) or medium (0.13 g N/L) concentrations te sted. Growth rate slightly increased when NMS was used, but the trends were not as dramatic as when comparing methanol removal. For example, fo r nitrogen levels of 0.26 g N/L, SA exhibited growth at 0.061 hr-1 in AMS and 0.068 hr-1 in NMS; and SB grew at a rate of 0.062 hr-1 in AMS and 0.074 hr-1 in NMS. However, the growth rate was significantly lower when the cultures were cultured in the presence of no adde d nitrogen in either form (Figure 3-2). Diversity of Microbial Populations in Cultu res Enriched with Different Nitrogen Sources To expand growth and activity comparisons to the community level of the enriched samples, DGGE was used to separate DNA fr agments amplified for methylotrophs and all bacteria from the original biofilm samples a nd their enrichments, as shown in Figure 3-3. Quantitative estimates of diversity, based on bandi ng patterns in the DGGE gels, are provided in Table 3-1. Results obtained for methylotrophs and universal bacteria were not compared directly, because different primer sets can am plify entirely different populations; however, both sets of results were used for determining tr ends in the population changes for the nitrogen sources used. The results in Table 3-1 showed consistent trends among the different enrichment and molecular methods, except for the methylotro phs enriched from SA where regardless of

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42 which nitrogen source was used, the diversity of this type of bacteria dropped to zero, with potentially only one dominant methylotrophic spec ies present. When comparing methylotrophs in SB and all bacteria in SA species richness, diversity, a nd evenness generally showed a smaller decrease from the quantitie s observed in the original biofilm culture to the levels shown in the enriched culture. It was interesting to note that in all the cases, the diversity metrics were greater for the mixed cultures enriched using nitr ate, as compared to ammonium, as the nitrogen source. This result could potentially corres pond to the observation that cultures enriched in nitrate also showed higher methanol removal and growth rate. Phylogenetic Analysis of Dominant Species The genetic comparisons among the culture s were expanded by selecting dominant species within each culture and determining their mxa -F or 16s rRNA sequence and phylogenetic relationship to other closely re lated known bacteria. All ex cised and sequenced bands are denoted in Figures 3-3A and 3-3B, as indicated by circles placed adjacent to sequenced bands. The phylogenic relationships among the species dominating the cu ltures in these experiments and known bacteria are shown in Figures 3-4 and 3-5. Figure 3-4 shows the distributi on of selected and recovered dominant bands that were produced by amplifying the functional gene for methanol dehydrogenase. Bands from the six samples show similarity to sequences found in the alpha-, beta-, and gamma-proteobacteria. Dominant bands from the original SA biofilm sp ecies are labeled as M1, which appears closely related to beta-proteobacteria Methylophilus methylotrophus a ribulose monophosphate (RuMP) cycle restricted facultative met hylotroph; and M6, which shows the greatest genetic similarity to a dominant species from the SB biofilm (M 5), and both are grouped with other alphaproteobacteria in the order Rhizobiales. Inte restingly, enriching SA in AMS or NMS produced

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43 similar mxaF profiles that appear to be dominated by a single methylotroph, band M3, which is not visible in the original culture, possibl y because its DNA was present in too small a concentration to be amplified sufficiently for vi sualization in the DGGE gel. Band M3 showed high sequence similarity to one cluster within the genus Hyphomicrobium bacteria also classified as non-N2 fixing, restrictive facultative met hylotrophs, but which use the serine pathway and are members of the alpha-Proteobact eria (Lidstrom 2006; Rainey et al. 1998). The community shift observed when enriching SB in AM S or NMS was not as consistent as with SA. M2, a strong band from enrichments of SB in AMS, appeared to be closely related to a species within the genera of Methylovorus an RuMP pathway, restrictive facultative methylotrophs classified as beta-Proteobacteria (Doronina et al. 2005). However, M3 was also present for SB enriched in NMS, as is band M4, which has a highly similar mxaF sequence. As shown in Figure 3-5, dominant bands obt ained from 16s rRNA of the samples also showed wide distribution among the alpha-, beta -, and gamma-proteobacter ia and no consistent community structure under either enrichment profile. The original SA biofilm sample had three sequenced dominant bands: U3, U4, and U 7. Band U3 was most similar to three Pseudomonas species (gamma-Proteobacteria); band U4 was grouped with a Bradyrhizobium species (alphaProteobacteria); and band U7 was highly similar to several Thiobacillus species (sulfur oxidizing chemolithoautotrophic beta-Prote obacteria). On enrichment in AMS, one dominant band was shown, U5, which was grouped with one cluster of the Hyphomicrobium, a similar result to what was observed when using mxaF primers. Although U5 also appear ed to be present in the SA NMS enrichment, that was not confirmed by se quencing. However, the dominant SA NMS bands were U2 and U6, which we re most similar in 16s rRNA sequence to methylotrophs found in the beta-Proteobacteria, including seri ne cycle methylotrophs in the family Rhodocyclaceae

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44 and RuMP cycle methylotrophs in the family Methylophilaceae respectively. The original SB biofilm sample was dominated by one band, U7, which was also found in SA and described above. SB enriched in AMS produced an intens e band, U1, with a 16s rRNA sequence similar to several Methylobacillus species. SB enriched in NMS produced multiple strong bands, although only one was able to be recovered and sequen ced, U2, which was also found in SA-NMS and shown to be similar to methylotrophic beta-Proteobacteria. Conclusions Results from this study illustrated that the t ype and concentration of nitrogen source used when enriching mixed methylotrophic cultures from samples removed from a pulp mill does influence the growth and methanol degradation ability of these b acteria. Generally, the cultures enriched with nitrate showed faster growth a nd higher methanol removal than those enriched with ammonium. Higher concentrations of nitrog en in either form also resulted in greater methanol removal in all cases. The form of n itrogen used also affected the diversity and community structure of the methylotrophic populati ons present in each of the final cultures. Although the enrichment process did decrease the overall diversity fr om the original samples, the cultures grown with nitrate as nitrogen sour ce preserved a higher level of species number, diversity, and evenness than those grown with a mmonium. Based on the results reported herein, nitrate is recommended to be used as the ni trogen source when enriching or working with methylotrophic cultures from pulp and paper m ills, and should be investigated further as a nutrient addition to biofilters.

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45 Table 3-1. Bacterial species, diversity, and ev enness for SA and SB cultures in both AMS and NMS media Methylotrophs ( mxa F) Universal (16s rRNA) Sample S H E S H E SA 4 1.04 0.75 9 2.02 0.92 SA-AMS 1 0 0 3 1.06 0.96 SA-NMS 1 0 0 7 1.74 0.89 SB 5 1.56 0.97 10 2.09 0.91 SB-AMS 2 0.34 0.49 8 1.48 0.71 SB-NMS 6 1.39 0.78 9 1.90 0.87 Species richness is indicated by S diversity is indicated by H and evenness is indicated by E. 0 10 20 30 40 50 60 70 80 90 100 0 g N/L0.13 g N/L0.26 g N/LNitrogen concentration in growth media Percent Methanol Removed (%) SA NMS SA AMS SB NMS SB AMS Figure 3-1. Comparison of methanol removal by SA and SB cultures in both AMS and NMS medium with an ini tial methanol concentration of 1,000 mg/L.

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46 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.080 g N/L0.13 g N/L0.26 g N/LNitrogen concentration in growth mediaGrowth Rate on Methanol (hr-1) SA NMS SA AMS SB NMS SB AMS Figure 3-2. Comparison of batch growth rates in SA and SB cultures in both AMS and NMS medium with an ini tial methanol concentration of 1,000 mg/L.

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47 SA Biofilm SA AMS SA NMS SB Biofilm SB AMS SB NMS A: PCR-DGGE with mxa F specific primersB: PCR-DGGE with universal 16s rRNAprimers M1 M2 M3 M4 M5 M6 SA Biofilm SA AMS SA NMS SB Biofilm SB AMS SB NMS U1 U2 U3 U4 U5 U6 U7 SA Biofilm SA AMS SA NMS SB Biofilm SB AMS SB NMS A: PCR-DGGE with mxa F specific primersB: PCR-DGGE with universal 16s rRNAprimers M1 M2 M3 M4 M5 M6 SA Biofilm SA AMS SA NMS SB Biofilm SB AMS SB NMS U1 U2 U3 U4 U5 U6 U7 Figure 3-3. Bacterial diversity measured using PCR-DGGE analysis. A) Using mxa F primers. B) Using 16s rRNA primers. Bands marked with a circle were exci sed and sequenced, and all marked bands on a vertical gradient la beled by M (methylotr ophs) or U (universal) were confirmed as identical in sequence.

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48 Figure 3-4. Phylogenetic reconstr uction of known methylotrophic bacteria and unknown culture strains using mxa F gene sequences (Bootstrap valu es represent 1,000 replicates, and values greater than 75% are shown). Methylobacterium extorquens Methylobacterium rhodinum Methylobacterium dichloromethanicum Methylobacterium podarium Methylobacterium zatmanii Afipia felis Methylobacterium organophilum Methylobacterium jeotgali Methylocystis aldrichii Methylocystis heyerii Methylocystis parvus Methylosinus trichosporium Methylosinus sporium Methylorhabdus multivorans Methylocella silvestris Beijerinckia mobilis M5 M6 Angulomicrobium tetraedale Paracoccus denitrificans Methylopila capsulata Albibacter methylovorans Methylosulfonomonas methylovora Hyphomicrobium zavarzinii Hyphomicrobium vulgare Hyphomicrobium aestuarii Hyphomicrobium facile M3 M4 Hyphomicrobium denitrificans Hyphomicrobium methylovorum M2 Methylovorus sp SS1 M1 Methylophilus methylotrophus Methylobacillus flagellatus KT Methylobacillus glycogenes Methylomonas methanica Methylococcus capsulatus Methylocaldum sp E10a 100 98 100 100 100 99 99 99 94 75 90 94 91 81 78 98 87 97 90 100BandDominant In M1SA-biofilm sample M2SB-AMS M3SA-AMS; SA-NMS; SB-NMS M4SA-AMS; SA-NMS; SB-NMS M5SB-biofilm sample M6SA-biofilm sample Methylotrophs ( mxaF)

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49 Figure 3-5. Phylogenetic reconstr uction of known bacteria and unknow n culture strains using 16s rRNA gene sequences (Bootstra p values represent 1,000 repli cates, and values greater than 75% are shown). Methylobacterium extorquens Methylobacterium dichloromethanicum Methylobacterium podarium Methylobacterium organophilum Chelatococcus asaccharovorans U4 Bradyrhizobium sp. Methylocystis parvus Methylocystis aldrichii Methylosinus sporium Methylosinus trichosporium Hyphomicrobium vulgare Hyphomicrobium hollandicum Hyphomicrobium aestuarii Hyphomicrobium zavarzinii Hyphomicrobium methylovorum U5 Hyphomicrobium facile Hyphomicrobium denitrificans Thiobacillus sajanensis Thiobacillus sayanicus U7 Thiobacillus denitrificans U6 Methyloversatilis universalis Cupriavidus sp. cmp2 Leptothrix sp. L18 Methylovorus glucosetrophus Methylovorus mays Methylophilus sp. ECd5s Methylotenera mobila U2 Methylobacillus pratensis U1 Methylobacillus flagellatus U3 Pseudomonas multiresinivorans Pseudomonas alcaligenes Pseudomonas stutzeri 100 86 100 98 80 100 100 98 100 96 88 100 97 89 96 99 98 93 77 92 98 94 94 92 91 88 91 99BandDominant In U1SB-AMS U2SA-NMS and SB-NMS U3SA-biofilm sample U4SA-biofilm sample U5SA-AMS U6SA-NMS U7 SA-biofilm sample and SB-biofilm sample Universal (16s rRNA)

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50 CHAPTER 4 METHANOL REMOVAL EFFICIENCY AND BACTERIAL DIVERSITY OF AN ACTIVATED CARBON BIOFILTER Introduction The forest products industry produces valuab le industrial and consumer products from wood cellulose, including paper, paperboard, hygiene products, high porosity filters, food casings, rayon filament, and chemicals such as ethers and acetate. During the chemical processes that convert wood chip s to cellulose pulp, organic compounds naturally present in wood or produced during pulping are released to air and water (Som eshwar and Pinkerton 1992). In 1998, the U.S. Environmental Protection Agency (U.S. EPA) passed the Cluster Rule to regulate the release of these compounds, includ ing hazardous air pollutants (HAPs), chemicals that pose great risk to human or environmental health (U.S. EPA 1998). Methanol is the primary focus of these regulations, as it is released in quantities of over 44,000 tons per year, over 70% of the total HAPs emitted by this industry (U.S. EPA 2004), and can contribute to human health impacts such as cancer, respiratory irritation, and damage to the nervous system (U.S. EPA 1998). To prevent potential environmental and hea lth impacts from methanol emissions, the Cluster Rule requires implementation of maxi mum available control technology (MACT) to collect and treat non-condensable ga s from high-volume (10,000-30,000 acfm), lowconcentration (below the lower explosion limit of the gas mixture) ( HVLC) sources, including pulp washing and screening, oxygen delignification, and weak black liquor storage tanks (Varma 2003). Most mills comply with MACT regulatio ns by collection of HAPs in vent hoods and subsequent oxidation in power bo ilers, stand-alone thermal oxidi zers, or recovery furnaces (Varma 2003).

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51 Despite the effectiveness of oxidation in destroying HAPs such as methanol, the drawbacks of requiring natural gas to s upport incineration, increas ed production of CO2, SO2, and NOx emissions, and high capital co sts for installation and infrastructure have motivated a desire for more environmentally and economically beneficial technologi es (Mycock et al. 1995; Schnelle and Brown 2002). One pot ential alternative to therma l oxidation is the use of a granular activated carbon (GAC) biofilter as a polishing step in combination with a primary treatment system using photocatalytic oxidation (Stokke et al. 2006; Tao et al. 2006). Although biofilters traditionally have contained a fixed bed of inert organic packing that serves as biomass support and nutrient support (Dev inny et al. 1999; Kennes and Th alasso 1998; Kennes and Veiga 2001), more recent work has shown the potential advantages of using surface active packing such as GAC (Aizpuru et al. 2003 ; Prado et al. 2002; Teran-Perez et al. 2002; Yang et al. 2002). The activated carbon adsorbs VOCs from the proce ss stream, creating a favorable environment for a stable microbial biofilm that subsequently degrades the contaminants (Aizpuru et al. 2003; Chang and Rittman 1987; Herzberg et al. 2003 ; Hodge and Devinny 1994; Weber and Hartmans 1995; Zhang et al. 1991). While recent studies (e.g., Aizpuru et al 2003; Chung 2007; Liang et al. 2007) have demonstrated excellent performance of activated carbon biofilters for c ontaminant removal, a potential challenge to their use is the lack of inherent nutrients, moisture, and microorganisms that would typically be found in an organic p acking such as compost (Devinny et al. 1999). Furthermore, little is known about the struct ure and dynamics of bact erial communities that colonize GAC biofilters. Therefore, the overall goal of this work was to develop and characterize a bench-scale activat ed carbon biofilter in removing methanol at concentrations typically observed in pulp mill air effluents and to observe the bacterial diversity during the

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52 biofilter operation. This benc h-scale biofilter used a novel heterogeneous packing blend containing granular activated carbon as the prim ary filter medium, mixed with perlite, slowrelease ammonium nitrate pellets, and water-reta ining crystals, which were added to minimize pressure drop, provide continuous nutrient inpu t, and minimize biofilter drying, respectively. Studies on this biofilter system were carried out to meet three primary objectives: 1) to demonstrate the methanol removal efficiency of the bench-scale activated carbon biofilter, 2) to use denaturing gel gradient elect rophoresis (DGGE) methods, in addition to culture-dependent methods, to characterize the abundance, diversity, and spatial distribution of bacteria colonizing the novel packing media; and 3) to use DGGE met hods to assess similarities and differences in stable biofilm communities in biofilters with an d without an inoculum specifically cultured for methanol-degrading bacteria. The results of this work are report ed herein and show promise for the development of activated carbon biofiltration systems as an effective option for methanol control for the pulp and paper industry. Materials and Methods Selection of Biological Inoculum Potential biofilter inocula were obtained from a pulp and paperboard company located in the Southeast that uses a biological waste wate r treatment system. Seven grab samples of biofilm were collected during June 2004 from locatio ns at this mill suspected to foster conditions for enrichment of bacteria, including metha nol-degrading consortia, and stored on ice in sterilized Teflon collection vessels until they could be processed in the lab or stored over a longer term at 4 oC. The collection locations of these samples were cooling tower baffles, an oxygen activated sludge reactor (UNOX reactor, or Union Carbide pure oxygen reactor), a secondary clarifier, mixed liquor, and retu rn activated sludge from the clarifier.

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53 From each sample, 10 mL or 10 g was homogenized with a phosphate buffer on a rotary shaker at 30 oC and 250 rpm for one hour. A 5 mL sample of the homogenized mixture was used to start a batch enrichment culture in a modifi ed nitrate mineral salts medium (NMS) containing 0.2% methanol (vol/vol) as recommended by Hans on (1998). The basal medium contained (on a g/L basis MgSO4*7H2O, 1.0; KNO3, 1.0; CaCl2, 0.2; KH2PO4, 0.026; Na2HPO4, 0.033. Trace elements were added, on a mg/L basis: FeSO4*7H2O, 0.5; ZnSO4*H2O, 0.4; EDTA disodium salt, 0.25; CoCl2*6H2O, 0.05; MnCl2*4H2O, 0.02; H3BO3, 0.015; NiCl2*6H2O, 0.01; Na2MoO4*4H2O, 0.005; and FeEDTA, 0.0038. Vitamins were added, on a mg/L basis: biotin, 0.02; folic acid, 0.02; thiamin*HCl, 0.05; calci um pantothenate, 0.05; riboflavin, 0.05; nicotinamide, 0.05; and B12, 0.001. All chemicals us ed were obtained from Fisher Scientific (Pittsburgh, PA, USA) or Sigma Aldrich (St. Louis, MO, USA) and were of analytical grade or higher. Cultures were maintained in a 1:10 ratio of inoculum:medium in a total volume of 55 mL in 250 mL Erlenmeyer flasks at 30 oC on a rotary shaker at 250 rpm. Initial cultures were incubated for one month, and subsequent transfer s to fresh medium were made bimonthly. In order to determine the most suitable biofilter inoculum, a series of culture-dependent growth, methanol depletion, and characte rization studies were performe d on these cultures (Chapters 2 and 3). Based on superior growth and methanol degradation rates and morphologically diverse, culturable community (determined by identification of visibly distin ct colonies on agar plates), the cultures derived from biofilm in the aera ted activated sludge UNOX reactor (SA) and from the return activated sludge (SB) were selected as potential biofilter inoculums. Despite the higher methanol removal rate of SB demonstrated in Chapter 3, initial trials using this sample as an inoculum resulted in excessive biomass fo rmation, plugging, and high pressure drop in a

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54 preliminary biofilter trial (data not shown). Theref ore, SA was selected as the inoculum for the final biofilter experiment reported in this chapter. Selection of Packing Material Two types of GAC packing, MeadWestvaco Bionuchar 120 (MeadWestvaco, Richmond, VA, USA) and Calgon F400 (Calgon Carbon Corporation, Pittsburgh, PA, USA), were compared to determine which would better foster the growth of biofilter bacteria. These two types of GAC were selected because they are commonly available and are recommended by their manufacturers for the removal of organic pol lutants (MeadWestvaco 2002; Calgon 1996). Bionuchar, a wood-based, chemically activat ed GAC with 1.1-1.3 mm particle size, is specifically marketed as having physical characteristics that allow for maximum fixation of beneficial biomass (MeadWestvaco 2002). F 400 is a bituminous coal-based, physically activated carbon with a 0.55-0.75 mm particle size (Calgon 1996). The GACs were compared on the basis of i mmobilization and growth of the biofilter inoculum on the carbon surface, measured first by enumerating bacteria in the liquid culture inoculum and then by enumerating bacteria r ecovered from the GAC surface after inoculation. Two inoculation methods were tested. One met hod involved suspending the biofilter inoculum in the mineral medium and continuously circul ating the inoculum through the packed bed for seven days. The other method involved floodi ng the column with the suspended inoculums incubating the column at 30 oC for four days, followed by drai ning the column and circulating fresh medium with methanol for three days. In both cases, a sterile glass column, measuring 10 mm in diameter and 100 mm in length, was used. The inoculum and/or the mineral medium was delivered to the column from sterile flasks using a peristaltic pump and Teflon tubing.

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55 After both inoculation methods were complete, 5 g of GAC was removed from each column and rinsed gently with sterile distil led water to remove particles and non-attached bacteria. The sample was mixed with 5 mL of sterile phosphate-buffered saline (PBS) and vortexed in 10-second pulses at 2500 rpm for two minutes to transfer biomass from the packing surface to a liquid suspension. To measure cult ivable bacteria, 1 mL aliquots from both the biofilter inoculum and from the liquid suspension of biomass from the packing were serially diluted (ten-fold) and spread plated in triplic ate on NMS plates cont aining 0.2% methanol. Plates were incubated at 30oC for seven days, at which time the total colony forming units (CFUs) were quantified. The carbon was dried at 45oC for 14 days and then weighed to obtain an air-dry weight. Biofilter Design The biofilter housing consisted of a clear PV C column with 2-inch diameter, 24-inch length, and 1,235 mL empty bed volume. The pack ing was added to a final volume of 1,100 mL dry packing material, composed of a 4:2:1:1 mixture of GAC, bulking ag ent (Perlite, MiracleGro, Marysville, OH, USA), slow -release ammonium-nitrate fertili zer (Osmocote, Scotts-Sierra Horticultural Products, Marysville, OH, USA) and water-retaining crystals (Agrosoke International, Arlington, TX, USA). This mixt ure had a bulk density of 412 mg/mL. To determine the ability of this material to adso rb methanol with no bacteria present, batch isotherms were performed on small (1-2 g) samp les of the packing, added to a 26 mL vial along with a smaller vial containing 10, 50, or 100 L of methanol. The change in weight of the activated carbon was measured at 24, 48, and 72 hours and at seven days. No change between 48 hours and seven days was observed, and the system was assumed to be at equilibrium. The adsorption capacity was determined by plotting the ratio of adsorbed methanol mass to the GAC

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56 mass as a function of equilibrium concentration, according to the Freundlich isotherm. Results of this analysis (data not shown) indicated that the adsorptive capacity of the packing material would be exhausted in approximately 20 hours and that methanol removal after that time would likely be attributed to the bact erial activity in the biofilter. Biofilter Operation and Performance Measurements The GAC biofilter was inoculated with the sel ected biofilm culture enriched in a mixed medium of ammonia and nitrat e (composition of NMS described previously, but amended with 0.5 g/L NH4Cl), with methanol added to a concentr ation of 0.2% by volume. A second column, identical to the GAC biofilter but without the inoculum, was used in parallel to the biofilter to demonstrate effects, if any, of using a specifica lly enriched inoculum. The inoculated packed column will be referred to as BB (biologi cally-inoculated biofilter), and the non-inoculated packed column will be referred to as NB (noninoculated biofilter) throughout the text. Sterile technique was used in working with the inoculum cultures and in prepari ng the columns, and all tubing, glassware, and the GAC were sterilized by autoclave before use; however, the biofilters were operated in a non-sterile environment and we re periodically exposed to the ambient lab air for sampling or maintenance purposes. The biofilters were operated in up-flow mode with an air stream artificially contaminated with varied methanol concentrations and 90-95% relative humidity (Figure 4-1). The air stream was generated by splitting a stre am from a compressed zero-grade air cylinder, with a small fraction of air diverted through a methanol bubbler (about 1-5% by volume, depending on the desired concentration) and the remaining fraction passing through a water bubbler to add humidity. Upflow mode was sele cted based on the possible need to add liquid nutrients without

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57 creating a leachate stream and to limit potential acidic byproduct buildup from using an ammonium based nutrient to the lower fract ion of the bed (Devinny et al. 1999). Biofilter operation was characterized by three consecutive sets of operating conditions, described here and summarized in Table 4-1. Firs t, the column was operated at a high methanol loading concentration (10,000 ppmv ) and high gas retention time (5 minutes) for 46 days to allow for bacterial colonizat ion of the activated carbon and acclimatization to high concentrations. Subsequently, for days 47108, the operating conditions included methanol concentrations below 100 ppmv and a retention time of one minute. Finally, for the last 30 days, the concentration was incr eased to 1,000 ppmv while maintaini ng a retention time of one minute. The stepwise changes in concentration between each set of operating conditions were used to replicate a wide variability of conditions that could be expected in an industrial setting. Column inlet and outlet gas concentrations were determined by the NCASI chilled impinger method (NCASI, 1998), with two midget im pingers (ARS, Gainesville, FL, USA) in series, each containing 20 mL of nanopure water in an ice bath. Methanol concentrations were analyzed by GC/FID using a Clarus 500 (Perki nElmer, Wellesley, MA, USA), with helium at 31.3 psig as the carrier gas, and hydrogen and ai r at 45 mL/min and 450 mL/min, respectively, as combustion gases. Cyclohexanol was used as the internal standard. Abundance and Diversity of Microbial Populations in the Biofilter Samples were collected from both biofilters by removing about 5 g (wet weight) of packing material from the middle of the colu mn using sterile instruments on days 22, 46, 77, 102, 125, and 138, which provided two samples duri ng each of the three operating conditions described previously The non-inoculated column was not sampled on day 22 because visible growth of biofilm on the carbon surface had not yet formed. At the conclusion of the

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58 experiment, packing material was also sampled fr om the inlet and outlet of the column. Each packing sample was first rinsed gently with st erile distilled water to remove particles and nonattached bacteria. Then the sample was mixe d with 5 mL of sterile phosphate-buffered saline (PBS) and vortexed in 10-second pulses at 2500 rp m for a total of two minutes to transfer biomass from the packing surface to liquid suspension. To determine bacterial abundance as a func tion of length along the column, the liquid suspension from samples at the top, middle, a nd bottom of the biofilters from day 138 were serially diluted eight-fol d, and 100 L aliquots were spread on agar plates. Three types of agar plates were used, nitrate minera l salts and ammonium mineral salts with methanol added in the vapor phase and nutrient agar with mixed Nand C-sources and no methanol added. Plates were incubated at 30 oC for seven days. Results were compared using one-way ANOVA and post-hoc comparisons among all groups, using SPSS 8.0 (Chicago, IL, USA). DNA Extraction and Amplification DNA was extracted from the liquid suspension from column samples using UltraClean Microbial DNA kits (MO BIO Laboratories Carlsbad, CA, USA) and the accompanying protocol. It has been reported that results obtained from this type of indirect approach are comparable to those obtained from direct lysis from cells attached to the packing (Li and Moe 2004). The polymerase chain reaction (PCR) was used to amplify specific DNA sequences found in expected methylotrophic (methanol-oxidi zing) populations in the biofilm. In all known gram-negative methylotrophic bacteria, methanol oxidation is catalyzed by the enzyme methanol dehydrogenase (MDH), the large sub unit of which is encoded by th e highly conserved functional gene mxaF (Barta and Hanson 1993; McDonald and Murrell 1997). Therefore, mxaFspecific primers f1003 (5-3 GCC CGC CGC GCC CCG CGC CCG TCC CGC CGC CCC CGC CCG

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59 GCG GCA CCA ACT GGG GCT GGT), which include s a 39-bp GC-clamp at the 5 end, and r1561 (5-3 GGG CAG CAT GAA GGG CTC CC) were used to detect methylotrophs as described by McDonald and Murrell (1997) a nd McDonald et al. (1995). The 16S rRNA sequences were amplified using primers f27 (5-3 CGC CCG CCG CGC GCG GGC GGG GCG GGG GCA CGG GGG GAG AGT TTG ATC MTG GC T CAG), which includes a 40-bp GC clamp at the 5 end, and r518 (53 ATT ACC GCG GCT GCT GC). Initial PCR and DGGE conditions were based on Henckel et al. (1999) Fjellbirkeland et al. (2001), McDonald et al. (1995) McDonald and Murrell (1997), but optimized for this specific system and primer set. The PCR reaction mi xture was prepared in 0.2 mL thin-walled PCR tubes and contained 1X MgCl2-free PCR buffer, 1.5 mM MgCl2, 100 uM of each dNTP,1U Taq polymerase (all from Invitrogen, Carlsbad, CA, USA), 0.5M of each primer (Integrated DNA Technologies, Inc, Coralville, IA, USA), 1-2 L of template DNA (50-100 ng), and sterile water to a final volume of 50 L. Amplifications with mxaF primers were carried out using a Mastercycler Personal 5332 thermocycler (Eppe ndorf North America, Westbury, NY, USA) with the block preheated to 92 oC, using a reaction program of initial denaturation at 92 oC for 3 minutes, a total of 30 cycles of denaturation (30 seconds at 92 oC), annealing using a touchdown program (30 seconds per cycle from 60 to 50 oC at -0.5 degree/cycle for the first 20 cycles and 50 oC for the last 10 cycles), and extension (45 seconds at 72 oC), and a final extension at 72 oC for four minutes. The same reaction setup wa s used for the 16s rRNA primers, but with an annealing touchdown temperature profile of the first 10 cycles from 55 to 50 oC at -0.5 deg/cycle and the last 20 cycles at 50 oC. The touchdown program was used because it increased yield and number of bands observed on subsequent DGGE ge ls, over a set annealing temperature. PCR products were verified on a 1.2% agarose gel, photographed, and their yield estimated using

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60 ImageJ software (Rasband, 2006) calibrated with a low DNA marker (50-2,000 bp, BioNexus, Inc, Oakland, CA, USA.). DNA Separation and Analysis DNA fragments were separated using denatu ring gel gradient electrophoresis (DGGE) with a 16x16 cm, 1 mm thick gel co ntaining 6% acrylamide, 1X TA E, and a linear gradient of 35-65% denaturant (100% denatura nt is equivalent to 7 M urea and 40% formamide), cast for 90 minutes. Approximately 500 ng of PCR product wa s mixed with 10-20 L of 2X gel loading dye (70% glycerol, 0.05% Bromophenol Blue 2mM EDTA), loaded on the gel, and electrophoresed at 60 oC for 5 hours at 150V in 1X TAE, using a DCode Universal Mutation Detection System Model 475 Gradient Delivery Sy stem (Bio-Rad Laboratories, Hercules, CA, USA). Gels were stained with 50 g/mL ethi dium bromide in 1X TAE for 15 minutes and destained in 1X TAE for 10 minut es. Bands were visualized and photographed using a Fisher Biotech Model 88A variable UV intensity Trans illuminator and DCode Do cIt software system (Bio-Rad Laboratories, Hercules, CA, USA). DGGE Image Analysis The digitized gel images were analyzed using ImageJ (Rasband 2006). The background was subtracted using a rolling ball radius of 50. Bands in each lane were automatically detected and plotted. Peak area and rela tive intensity of each band was measured, and bands contributing less than 1% to the total intensity within one lane were omitted from subsequent analysis. No comparisons were made between different gels, because no internal standard was used. No comparisons were made between gels from the tw o primer sets, although the two were compared based on trends in banding patterns among the sa mples. A distance matrix for pairwise comparisons between lanes was generated by th e unweighted Gowers di stance (Equation 4-1),

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61 P j j j jR y y P D1 2 11 (4-1) where P is the total number of bands being compared, y1 and y2 are the band intensities for the two lanes being compared, and R is the larges t difference found across all bands in the gel (Legendre and Legendre 1998). This matrix, gene rated with Mathcad 13 (Mathsoft, Parametric Technologies Corporation, Needham, MA, USA), wa s used for hierarchical clustering with the unweighted pair group method with arithmetic mean (UPGMA), constructed using MEGA version 3.1 (Kumar et al. 2004). DNA Sequencing and Phylogenetic Analysis To further characterize the community of me thanol-degrading bacteria present during biofilter operation and in the original inoculum, selected bands from mxa F-specific DGGE gels were excised for sequencing. Bands were c hosen from mxaF-amplified DNA that showed the highest intensity when visualized on the UV tran silluminator and were excised using a sterile pipet tip and scalpel. The gel frag ments were eluted overnight at 30 oC at 250 rpm in 30 L of an elution buffer containing 10mM Tris-Cl (pH 7.5), 50 mM NaCl, and 1mM EDTA (pH 8.0) (Chory and Pollard 1999). Gel fragments were removed, and DNA was precipitated from the liquid by adding 50 L of 95% cold ethanol, chilling 30 minutes at -40 oC, and pelleting the DNA by centrifuging 10 minutes at 10,000xg. After pouring off the ethanol supernatant, the pellet was dried at 40 oC for 4-5 hours and resuspended in 30 L of TE buffer (Chory and Pollard 1999). This template was reamplified us ing the same methods as described previously and checked on a DGGE gel for purity and for migrat ion to the same gradie nt position as in the original sample. Sequencing was performed at the University of Florida Interdisciplinary Center for Biotechnology Research (ICBR) using the fluorescent dideoxy terminator method of cycle sequencing on either a Perkin Elmer Applie d Biosystems Division (PE/ABD) 373A or 377

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62 automated DNA sequencer, following ABD protocols, with consensus sequences generated using the Sequencher Software from Gene Codes. Sequences of partial mxa F gene fragments have been deposited in the GenBank database under accession numbers EU099402 through EU099407. Published sequences with high similarity to sample sequences were obtained by performing a nucleotide-nucleotid e BLAST (NCBI) search. The 10 most similar sequences of known species with E scores lower than 1E-20 we re chosen for each sample, with duplicates removed. Sequences were aligned using Clus talW, with default gap penalties, and manual inspection and refinement of alignments. A phylogenetic tree was constructed using the Neighbor Joining method and bootstrapped w ith 1,000 replicates. Because all known proteobacteria clustered into a distinct branch this group was selected as the out-group. All phylogenetic and molecular evolution analyses were conducted using MEGA version 3.1 (Kumar et al. 2004). Results and Discussion Biofilter Design Results of the comparisons of granular ac tivated carbon (GAC), We stvaco Bionuchar and Calgon F400, using two inoculati on methods are shown in Table 42. Both inoculation methods worked well for colonizing the biofilter with an active microbial population. However, the Bionuchar GAC supported a significantly higher number of and increase in colonies and a visible biofilm, as compared to the Calgon GAC. The larger particle size of the Bionuchar likely created larger void spaces within the packed be d, allowing for better transport of oxygen through the biofilter for maintenance of aerobic inoculum cultures, le ss plugging with excess biomass, and increased nutrient availabil ity to attached bacteria.

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63 Based on these results, the Bionuchar GAC was used for all subsequent biofilter experiments. No apparent diffe rence was observed between the two inoculation methods in their ability to adequately introduce the microbial inoc ulum to the GAC packing. Simply for ease of setup and maintenance, the flood and drain me thod was selected for subsequent biofilter experiments. Biofilter Performance The performance of the biofilter for methanol removal is shown in Figure 4-2, where removal efficiency (%) of both the biologically inoculated biofilter (BB) and non-inoculated biofilter (NB) is plotted as a function of time, along with the methanol loading rate to the biofilters. Each of the points plotted in Figure 4-2 represents an average for samples collected in duplicate over the 138-day operation of the biofilters. During th e first 46 days of operation (at 10,000 ppmv MeOH and 5 min gas retention time), both biofilters showed excellent removal of methanol, after a lag time of about four days to achieve 100% methanol removal. The BB showed lower removal over those first four days, which is probably a result of pre-saturation of the packing material with methanol-laden medi um during inoculation. When the methanol loading rate was rapidly decrea sed on day 47 (to 100 ppmv MeOH, with 1 min residence time), the performance of the NB also fe ll dramatically, with an almost 10-day period before it returned to 100% removal. When the methanol loading rate was increased to 5 g/m3 packing/hr at day 109 (corresponding to 1,000 ppmv MeOH, with 1 min residence time), both biofilters continued to perform well. However, the NB showed another decrease in methanol removal at the conclusion of the trial, between days 133 and 138. Although the NB did not receive the specifically enriched methanol degrading bacterial inoculum, its packing material showed a visi ble biofilm by day 25 (compared to a biofilm

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64 observed on the NB on day 6), likely due to co lonization by opportunist ic methanol-degrading bacteria introduced by operation in non sterile co nditions. In addition, the NB performed with almost equivalent removal efficiency to the BB, which suggests that th e novel packing mixture used in the biofilters provided an excellent s upport medium for the immobilization of bacteria and subsequent bacterially mediated methanol removal, even without addition of a cultured inoculum. Bacterial growth in non-inoculat ed systems is not uncommon, for example, Dusenbury and Canon (2004) reported bacterial gr owth and contaminant removal in a noninoculated activated carbon biofilte r, even with periodic additions of chlorine bleach solution to deter biological growth. It is believed that, despite the lack of introduced inoculum to the NB, the methanol removal was biological in natu re, based on results of adsorption isotherms, discussed previously. Bacterial Counts over the Length of the Biofilters Bacterial counts at the inlet, middle, and outlet of both biofilter s at the end of the operating period were compared fo r three types of mineral medium with results shown in Figure 4-3 as colony forming units (CFU) per gram of packing (with standard error from triplicate measurements). The different types of agar medi a were used to determine if culturable bacteria in different regions of the biofilters could be differentiated based on th eir nitrogen and carbon requirements. With the exception of the BB inlet and NB outlet, more bacteria were enumerated on the rich nutrient medium in samples removed from all regions of the columns. For all types of media, the distribu tion of bacterial abundance varied si gnificantly among the regions of both biofilters (F=80.4, p<0.001), with significantly higher abundance in the inlet section for the BB ( post-hoc comparison, all p<0.001), and significantly lower abundance in the inlet section of the NB ( post-hoc comparison, all p<0.012). High abundan ce in the BB inlet (as compared to its

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65 middle or outlet), where methanol concentrations ar e expected to be highest, was possibly due to a population from the inoculum used in the BB already being acclimated to high substrate and nutrient concentration, from the original mill source and in the inoculum culture enrichment. High colonization per gram of packing material in the BB may also have contributed to its continual high methanol removal efficiency (Figure 4-2), whic h would follow the observations by Song and Kinney (2000) that microbial respirator y activity in a toluene biofilter was directly proportional to the number of culturable colonies fr om the packing material, and that activity and CFUs were higher at the inlet of the biofilter, where the pollutant concentration was the highest. Bacterial Diversity Comparisons The PCR-DGGE approach was used to charact erize bacterial diversity for (1) different operating conditions over time for both the BB and NB and (2) different spatial portions of the BB and NB at the end of operation. Bo th assessments were performed using mxa F and 16s rRNA primers to target methanol-degrading bacter ia and all bacteria present, respectively. Results of these comparisons include gel images and the UPGMA clusters and are shown in Figures 4-4 and 4-5. Figure 4-4A shows bacterial diversity in both biofilters from the initial inoculum through the six sampling times (the day the sample was taken is denoted by the corresponding number at the bottom of each gel column) that span the thre e operating conditions (Table 4-1). Considering methylotrophs, the BB showed a visibly higher bact erial diversity than th e NB, which appeared to contain about half as many sp ecies. Increased diversity may re late to observations that the BB was the more reliable system (Figure 4-2). However, only a single band was observed in common among the inoculum, BB, and NB, indicating that dominant populations amplified from the inoculum culture were not dominant in the bacterial community that was observed to rapidly

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66 colonize and be maintained in both biofilters. A potential explanation for this observation was two-fold: 1) the source of bacterial growth in the NB originated from the BB, as the two were operated in a connected air flow system and in cl ose proximity to each other, and 2) populations present in the BB represented such a small fraction of the mixed inoculum cu lture that they were not sufficiently amplified by PCR for detection usi ng DGGE. It is not unexpected that a change in conditions from the enriched culture to the biofilter environm ent could drastically alter the bacterial community (Devinny et al. 1999) or th at PCR-DGGE methods are unable to detect bacteria comprising less than ~1% of the tota l bacterial community (Sercu et al. 2006). Alternatively, all of the bacterial populations in both the NB and BB could have arisen from sources outside the inoculum, by op erating in non sterile conditions. Either of these possibilities supported the premise that the bi ofilters performance could be attributed to use of the novel GAC mixture as biofilter packing, rather than to a specifically cultured inoculum, and coincided with the excellent removal efficiency obser ved for both the NB and the BB (Figure 4-2). Banding patterns generated by amplifying 16s rRNA from both biofilters were much more varied and numerous than mxa F (Fig. 4-4A), which was likely due to the presence of nonmethylotrophic bacteria in the biofilters. This result was consistent with the observation in Figure 4-3 that more CFUs per gram of packi ng were counted on heterotrophic plates than on methylotroph-specific plates. However, similar tre nds were observed for both primer sets, in that both biofilters appeared to be colonized by some bacterial populations that were dominant in the inoculum, as well as others that were not amp lified from the inoculum, and that the community structure generally persisted over time a nd despite varied operating conditions. Visual observations were supported by cluste r analyses (Figure 4-4B) that took into account the relative intensity of each band, which corresponded to relative abundance of that

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67 bands DNA in the PCR-amplified sample. UPGMA clustering results can be interpreted as the similarity between two samples based on similari ties in their banding patterns. Although BB and NB shared some of the same species (Figure 4-4A), bacterial communities in each biofilter differed based on which populations were most dominant. As show n in Figure 4-4B, the greatest similarity was among populations within each biof ilter, rather than within each time period or each operating condition or between the biofilte rs. Because there was no shift in populations over time or in different opera ting conditions, it was expected th at acclimation or succession of bacteria in the columns occurred quickly, within in the first 22 da ys of operation (before the first DNA sample was extracted). Rapid acclimation coul d have been due to start up of the column under very high methanol loading concentrations, which may have created selective pressure for methylotrophic bacteria that becam e robust colonizers. Although it is uncertain what role, if any, the specifically enriched inoculum played in the BB performa nce, the clustering results suggest that addition of this culture did somehow influe nce the diversity and community structure of the consortium of bacteria that ultimately coloni ze the BB, possibly by changes to the biofilter microenvironment, such as surface conditioning or facilitating primary adhesion (Dunne 2002). Figure 4-5A illustrates the bacterial diversity ov er three spatial regions in both biofilters, and Figure 4-5B shows the similarity of banding patterns among these regions. For the inoculated biofilter, resu lts from PCR-DGGE with mxaFspecific primers and with 16S rRNA primers show opposing trends in dive rsity over length. The met hylotrophic population appeared to be most diverse at the BB outlet, where metha nol concentration is expe cted to be the lowest, whereas populations were more diverse at the in let when assessed using the universal bacterial primer. Distributional patterns were much less consistent when using 16s rRNA, which showed more distinct changes among the three areas samp led in the biofilter, a similar result to the

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68 observation by Li and Moe (2004) th at relative abundance of species in a methyl ethyl ketone biofilter differed significantly as a function of height along the bi ofilter, likely due to selective pressures of the changing concentr ation gradient of introduced polluta nt over the biofilter length. No such trend was clearly evident for the NB syst em. It was also interesting to compare these results with counts of culturable bacteria in Figure 4-3 and compar isons of the inoculum and the BB in Figure 4-4A. For methylot rophs, highest counts of CFUs we re at the BB inlet, which, according to Figure 4-5A was primarily dominated by a single species. In addition, this band was also shown as being dominant in the inoculum (Figure 4-4A), which supports the possibility put forth earlier that the ability of this species to thrive in the areas expected to have the highest methanol concentration may be due to its prior acclimation to these conditions. Figure 4-5B shows hierarchical cluster analysis for the spat ial comparisons, and, for both amplification methods, indicates th at the outlet and middle sections of the BB were very similar in composition, as compared to the inlet regi on. Despite the comparable abundance results between the two biofilters, the similarity-based clustering results indicated that the actual populations that comprise the to tal bacterial community at the inlet, middle, or outlet were actually quite different between the BB and th e NB. Although a direct correlation cannot be made with the data available, th e results suggest that growth with in each column did vary based on the type of bacteria present and the means in which they were introduced to the biofilter. However, this variation did not appear to create any significant differenc es to observed methanol removal efficiency (Figure 4-3). Phylogenetic Analysis of Methylotrophic Bacteria Selected bands, correspondi ng to the highest relative intensity, or highest DNA concentration, amplified with mxa F primers, were excised, reamplified, purified, and sequenced

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69 to determine the phylogeny of select ed methylotrophic bacteria in the inoculated biofilter. A representation of phylogenetic re lationship among these sample s and known methylotrophic bacteria is shown in Figure 4-6. Samples ar e identified by their sour ce (inoculum or BB) and numbered as shown in Figure 4-4, with bands marked with an X corresponding to those unable to be reamplified or purified. Limited sequencin g for bands excised for different days in the BB and also in the NB indicated that bands occurrin g at the same vertical gradient had identical sequences. Figure 4-6 shows that species obtained from both the inoculum and the biofilter were widely distributed across known types of methylotrophs. Inoc ulum 1 and BB1, corresponding to inoculum band 1 and BB band 1 (Figure 4-4), appeared to be closely related to species within the genera of Methylophilus Methylovorus and Methylobacillus non-N2 fixing, restrictive facultative methylotrophs that follow the ribulose monophosphate (RuMP) pathway for formaldehyde fixation and are classified as beta -Proteobacteria (Doronina et al. 2005; Lidstrom 2001). BB2, corresponding to BB band 2 (Figure 4-4), was grouped with several Hyphomicrobium species, which are also non-N2 fixing, restrictive facu ltative methylotrophs, but follow the serine pathway and are members of th e alpha-Proteobacteria (Lidstrom 2006; Rainey et al. 1998). BB3 and BB4, denoting BB bands 3 a nd 4 (Figure 4-4), were also classified with the alpha-Proteobacteria, but not clustered closely with specif ic known sequences. However, BB5 and Inoculum 2, corresponding to BB band 5 and inoculum band 2 (Figure 4-4) and having identical sequences, appeared to be closely related to Beijerinckia mobilis and Methylocella silvest ris, both alpha-P roteobacteria. B. mobilis is known to be heterotrophic, N2-fixing, and use the ribulose bisphosphate (RuBP) path way (Dedysh et al. 2005a), while M. silvestris is known to be facultatively methanotrophic, moderately N2-fixing, and use the serine pathway (Dedysh et al.

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70 2005b). Interestingly, both of these species are acidophilic and grow in media as low as pH 3 (Dedysh et al. 2005; Dunfield et al. 2003), and, as observed in Figures 4-4 and 4-5, the band correlating to this species increased in relative in tensity over operation time and at the inlet of the BB, a region potentially growing more acidic due to operation in upflow mode and some drainage of liquid in the biofilte r, although this observation could not be corroborated with actual biofilter pH measurements. In addition to specific characteristics about the inoculum and biofilter bacterial species that are hypothesized based on this phylogenetic reconstruction, a more important observation is that the biofilters were coloni zed by a genetically, and likely ph enotypically, diverse population of bacteria, expected to thrive in varied Cand N-usage niches. For example, the presence of expected N2-fixing bacteria would have allowed conti nued growth and methanol removal even if localized nutrient supply was diminished. The observed diversity may have contributed to the continual high performance of the biofilters over time and in varied operating conditions. Conclusions A bench-scale inoculated GAC biofilter (BB) system was demonstrated for the removal of methanol from an artificially contaminated ai r stream. The methanol removal efficiency for this system and an identical, non-inoculated biof ilter (NB) were simila rly high (~100%) for both biofilters over the majority of operating time. Whereas the performance and abundance results would indicate that the two biofilters were very similar, an examination of the underlying microbiology using molecular methods shows that, in fact, they were colonized by very different populations of bacteria that were distributed di fferently throughout the le ngth of the biofilters. Unfortunately, we cannot conclusively relate perfor mance data to specific populations observed. However, from a broader perspective, the resu lts underscore the need to examine microbial

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71 diversity as part of overall de sign and operation strategies and performance measurements for biofilters, rather than looking at removal efficiency alone. This work also reports the successful use of a novel heterogeneous biofilter packing material. The mixture of activated carbon, wh ich contributed to initial adsorption of the methanol and may have helped to buffer concentr ation changes, combined with perlite, slow release nutrient pellets, and water retaining crys tals, provided excellent support for the growth and activity of methanol degrading bacteria ove r time and during high vari ability in operating conditions. These results show the potential for developing activated carbon biofiltrations systems as potential technological solutions for methanol control in the pulp and paper industry.

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72 Table 4-1. Summary of biofilter operating conditions Condition Days Average Methanol Concentration Average Methanol Loading Rate Gas Retention Time I 1-46 10,000 ppmv 17 g/m3 packing/hr 5 min II 47-109 100 ppmv 1 g/m3 packing/hr 1 min III 110-138 1,000 ppmv 5 g/m3 packing/hr 1 min Table 4-2. Comparison of activated carbons and inoculation methods Method: Circulation Circul ation Flood/Drai n Flood/Drain Carbon: Calgon Bionuchar Calgon Bionuchar Initial Count: (CFU/g carbon) 1.18E+05 (2.58E+04)1 2.33E+05 (5.13E+04) 1.04E+06 (3.30E+05) 1.79E+06 (5.67E+05) Final Count: (CFU/g carbon) 8.14E+06 (6.79E+05) 5.23E+07 (8.94E+06) 2.12E+07 (2.84E+06) 4.80E+08 (2.31E+07) Factor of Increase (%) 69.2 224.3 20.3 268.1 1Parenthetical value is standard error for measurement in triplicate. Figure 4-1. Biofilter operation schematic

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73 Figure 4-2. Methanol removal efficiency in the biologically inoculat ed and non-inoculated biofilters as a function of time and methanol lo ading rate. Each point is the average of two replicates collected consecutively. Standa rd error was less than 1% for the BB data, less than 5% for the NB data, and less than 10% for the methanol loading rate.

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74 Figure 4-3. Abundance of cultivable bacteria in th ree spatial regions of th e biofilters using three types of culture media. Error bars represent the standard error for measurements made in triplicate.

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75 Inoc day 22 day 46 day 77 day 102 day 125 day 138 day 46 day 77 day 102 day 125 day 138 Inoculated biofilterNon-inoculated biofilter Inoc day 22 day 46 day 77 day 102 day 125 day 138 day 46 day 77 day 102 day 125 day 138 Inoculated biofilterNon-inoculated biofilter PCR-DGGE with mxa F specific primersPCR-DGGE with universal 16s rRNAprimersA 1 2 1 3 4 X 5 X X 2 B BB-day 22 BB-day 46 BB-day 77 BB-day 102 BB-day 125 BB-day 138 NB-day 46 NB-day 77 NB-day 102 NB-day 125 NB-day 138 Inoculum BB-day 22 BB-day 46 BB-day 77 BB-day 102 BB-day 125 BB-day 138 NB-day 125 NB-day 138 NB-day 102 NB-day 77 NB-day 46 Inoculum Figure 4-4. Bacterial diversity of the biofilters over time, measured using PCR-DGGE. A) Images of DGGE separated DNA fragments sa mpled from the biological inoculum and from the biofilters on six days during operation. B) UPGMA cluster analysis of the relatedness of PCR-DGGE ba nding patterns of the inoculum and the biofilters on six days during operation. Numbers at the botto m of each gel lane correspond to the day on which the packing sample was extracted from the column and used for DNA extraction and amplification. Bands marked with a circ le, were excised, re-amplified, and purified for sequencing. Numbers in the circles corr espond to the numbers used in phylogenetic analysis, while X in the circle s corresponds to bands that were extracted, but unable to be re-amplified or purified.

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76 Inlet Middle Outlet Inoculated biofilter Non-inoculated biofilter PCR-DGGE with mxa F specific primers PCR-DGGE with universal 16s rRNAprimers Inlet Middle Outlet Inoculated biofilter Non-inoculated biofilter Inlet Middle OutletInlet Middle OutletA B BB-outlet BB-middle BB-inlet NB-outlet NB-middle NB-inlet BB-outlet BB-middle BB-inlet NB-outlet NB-inlet NB-middle Figure 4-5. Bacterial diversity of the biofilters in different spatia l regions. A) Images of DGGE separated DNA fragments sampled from three points along the length of the biofilters at the end of the operating period. B) UPGMA cl uster analysis of the relatedness of PCRDGGE banding patterns from thr ee points along the length of th e biofilters at the end of the operating period.

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77 Figure 4-6. Phylogenetic reconstruction of know n methylotrophic bacter ia and unknown biofilter and inoculum strains using Neighbor Join ing method. The inferred phylogeny was bootstrapped with 1,000 replicates, and bootstra p values greater than 75% are shown on corresponding branches

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78 CHAPTER 5 LIFE CYCLE ASSESSMENT OF TWO OPTIONS FOR CONTROLLING HAZARDOUS AIR POLLUTANTS AT PULP AND PAPER MILLS: A COMPARISON OF THERMAL OXIDATIO N WITH A NOVEL PHOTOCATALYTIC OXIDATION AND BIOFILTRATION SYSTEM Introduction The forest products industry, including pulp, paper, and paperboard mills, is one of many industries faced with increasingly stringent regulations on allowable emissions to air and water. In 1998, the U.S. Environmental Protection Ag ency (U.S. EPA) promulgated guidelines and emissions standards, collectively known as the C luster Rule, intended to reduce the discharge of toxic pollutants in wastewaters and emissions of hazardous air pollutants (HAPs) for the forest products industry (U.S. EPA 1998). To this end, the Cluster Rule requires implementation of maximum available control technology (MACT) to limit the amount of HAPs emitted from a variety of mill processes, including chemical pulping (MACT I), papermaking and mechanical pulping (MACT II), and chemical recovery (MACT III) (EPA 2002). Specifically, MACT I regulations require pulp and paper mills to co llect and treat non-condensable gas from high volume low concentration (HVLC) sources, which are defined as those producing large volumes of gas (10,000-30,000 acfm for an entire mill) and d ilute concentrations (below the gas mixtures lower explosion limit) (Varma 2003). These sour ces include pulp washing, deckers, knotters, oxygen delignification, and chemical storage tanks. Of the HVLC gases emitted, methanol is a primary focus of MACT I standards because it is emitted in such high quantities from pulping processes (over 44,000 tons from the entire forest products industr y in 2004) (EPA 2004). The most common method for MACT I complia nce adopted by pulp and paper mills is the incineration of methanol and other HVLC gases in an existing power boiler or lime kiln or in a new stand-alone device, such as a regenerativ e thermal oxidizer (RTO) (Varma 2003). While

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79 effective for destroying HAPs, use of an RTO has the potential to create environmental impacts associated with the combustion of natura l gas and production of nitrogen oxides (NOx), the oxidation of carbon and reduced sulf ur species to carbon dioxide (CO2) and sulfur dioxide (SO2), the amount of raw materials required to constr uct ductwork and other infrastructure for gas collection and transport, and the need to cons truct and operate a wet scrubber to remove SO2 from the RTO exhaust (Mycock et al. 1995; Sc hnelle and Brown 2002). Recently, however, other options for HAP control have been invest igated, including a treatment system using a photocatalytic oxidation (PCO) react or for primary methanol removal (Stokke et al. 2006) and an activated carbon biofilter for secondary polishi ng of the air stream (Babbitt et al. 2007). Although these new technologies show promis e for methanol removal to meet MACT standards while decreasing energy requirements, how they compare to thermal oxidation in terms of life cycle environmental impact s is not known. Therefore, the goal of this work was to use a life cycle assessment (LCA) approach to compare the novel PCO-biofilter system with the more traditional RTO technology. A better understandi ng of potential cradle-t o-grave environmental impacts associated with these technologies wi ll not only assist i ndustrial and regulatory communities in selecting the most environmen tally friendly option but will also reveal opportunities for environmental improvement in the construction and operation of either system. This paper reports the results of a life cycle inventory, impact assessment, and sensitivity analysis, for the purpose of comparing a PCO-biofilter and a RTO-scrubber system. Methods Life cycle assessment (LCA) is the systematic inventory and analysis of environmental impacts for the entire life of a process or product for comparison purposes. This LCA was structured in accordance with ISO 14044:2006 guideli nes (ISO 2006), which call for four phases:

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80 1) definition of the assessment goals and scope, 2) inventory of all mate rial and energy inputs and outputs from the system, 3) assessment of environmental impacts associated with the inventoried system inputs and outputs, and 4) interpretation of the impacts according to the defined goal and scope. Each of these phase s is described in mo re detail below. Goal and Scope Definition The goal of this LCA was to compare a two-step photocatalytic oxidation and biofiltration system with a thermal oxidation syst em for methanol removal, to determine the environmental impacts over their entire life cycles. Results from this LCA are intended to be used in comparative assertions intended to be disclosed to the public. Unlike many recent LCA studies of treatment technologies (e.g., Jorgensen et al. 2004; M unoz et al. 2007; Sauer et al. 2002), this comparative LCA incl udes not only the impacts of operating the PCO-biofiltration and RTO-scrubber systems over their expected lif etimes but also of producing the required infrastructure for these systems. Inclusion of the infrastructure production-related raw materials, energy, emissions, and impacts will yield a more complete understanding of the benefits or drawbacks of both systems that are being compared. Functional unit The functional unit for this st udy was the treatment of 350 sc fm of air with a methanol concentration of 50 ppmv, in order to achieve 98% methanol removal. This volumetric flow rate and methanol concentration were se lected based on recommendations by industry representatives consulted for this project and the subsequent desi gn of a pilot-scale PCO system with these specifications. The specified metha nol removal rate of 98% is based on the MACT compliance options, which require thermal oxidation at 1600 oF with a 0.75 second retention

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81 time (necessary for 98% methanol removal) or use of other control technologies provided that a 98% methanol removal is achieved (U.S. EPA 1998). System boundaries The system considered for this LCA was the production and operation of two air pollution control systems for removing HVLC metha nol emissions generated from unit processes involved in the production of br ownstock (unbleached) pulp at Kr aft pulp mills. These processes include brownstock pulp washers, screens, knott ers, deckers, and weak black liquor storage tanks. As previously described and as shown in Figures 5-1 and 5-2, the two treatment options considered are 1) an RTO for methanol removal, followed by a caustic wet scrubber for SO2 control and 2) a photocatalytic oxidation (PCO) reactor for primary methanol removal followed by an activated carbon biofilter for secondary methanol removal. Life cycle inputs of raw material and energy and outputs of emissions to air were included for both control systems for three stages: 1) processing resources extracted fr om nature to produce prim ary raw materials; 2) secondary material processing to convert primary raw materials into chemicals, materials, and energy directly used for infrastr ucture or operation of the contro l systems; and 3) construction and operation of each control system fo r an expected 20-year lifetime. Stage 1, Primary Raw Materi al Processing, does not incl ude the direct extraction or mining of ores or other materials from nature, bu t does include the processing required to convert these resources, or inputs from nature, into usef ul raw materials. Stage 2, Secondary Material Processing, includes the processes required to convert raw material s from Stage 1 directly into feedstocks or electric energy required for the co nstruction or operation of the control equipment. Outputs from the Secondary Material Processi ng stage are also termed inputs from the technosphere in this study. In the case of the PCO-biofilter system, Stage 3 includes the

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82 production and replacement of pack ing materials for the reactor and the biofilter as individual contributing categories to the total PCO-biofilter impact (Figure 5-2). These materials could not be classified distinctly as eith er construction or operation, but were rather major material inputs that had several replacement cycles over the lif etime of the project, as described in the assumptions detailed below. For both systems, Stage 3 also includes the emission of treated HVLC gases, as the two technologie s are expected to have slightly different removal rates for VOCs other than methanol (as described in the assumptions). The total inputs and outputs from all three stages are aggregated into categories of construction and operation for comparison purposes. Transportation of materials from their point of production to the mill for installation or use was not included, due to lack of information about this stage. Assumptions In addition to the scope and system boundaries defined above, several assumptions about the system parameters are necessary to fac ilitate data collection and calculations. 1. Except where specified differently, all capital goods and infrastructure are expected to have a 20-year lifetime. Where shorter lifetimes are anticipated, total material and energy flows were adjusted to reflect repla cements required to achieve 20 years of service. 2. VOCs in addition to methanol are present in the effluent air stream (NCASI 2003) and are included, to the extent known from literature, in estimates of control technology operation and performance. 3. A ratio of 100 scfm contaminated air generated from brownstock washing processes for every 1 air dry (short) ton unbleached pulp pe r day production rate (U.S. EPA 1979) was used to normalize inventory data gi ven in mass per ton pulp format. 4. The RTO was sized to operate at 1600 oF, with a residence time of 0.75 seconds, for a corresponding 98% removal of methanol. A ll VOCs present in the contaminated air stream are converted to CO2 according to stoichiometric ratios and 98% destruction efficiency. The regenerator beds are pack ed with ceramic saddles and sized for 95% thermal efficiency. Natural gas is added to support combustion of the VOCs, based on an energy balance around the RTO.

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83 5. The RTO is located 200 ft from the brow nstock washer HVLC collection point, and connected with a 3.5 ft diameter stainless steel duct. 6. The photocatalytic oxidation (PCO) reactor was designed for 90% removal of methanol, followed by an activated carbon biofilter, designed for 80% removal of remaining methanol, to achieve a total of 98% as required by regulation. 7. While the biofilter was designed for methanol removal, it also contributes 65-80% removal of other VOCs present, based on perfor mance of pilot-scale biofilters reported in Devinny et al. (1999). This removal rate is a conservative estimate, as the VOCs may actually be more biodegradable after UV photooxi dation than would be expected in their natural state (Koh et al. 2004; Moussavi and Mohseni 2007). Of the carbon in VOCs entering the biofilter, 40% was assimilated in to biomass, and 60% was converted to CO2. 8. The PCO reactor contains a fixed bed of silic a-titania composite (STC) pellets, expected to have a 5 year lifetime; and uses 75W UV bulbs with a one-year lifetime for photocatalytic methanol destruction. 9. The biofilter contains a novel packing mixture of Bionuchar granular activated carbon (a wood-based carbon chemically activated with phosphoric acid), mixed in a 4:2:1 volume ratio with perlite spheres and gr anules of an ammonium nitrat e slow release fertilizer, and this mixture is expected to have a five-year lifetime. 10. The treatment trains operate con tinuously, or 8,760 hours per year. Inventory All life cycle inventory (LCI) calculations were performed using SimaPro 5.1 (PRe Consultants, Amersfoort, The Netherlands). Ho wever, all data process modules were created specifically for this life cycle, rather than using existing databases in SimaPro (except where noted), to maintain a high level of transparency and specificity to the system of interest as well as consistent data quality levels. Inventory data were collected from interviews of environmental managers at pulp and paper mills participating in this project and engineers involved with creating HVLC control solutions for pulp and pape r mills, design and operational specifications of the PCO system, benchand pi lot-scale results for the PCO react or, bench-scale results for the biofilter, technical documents provided by the Na tional Council for Air and Stream Improvement (NCASI), published literature, regulatory agenci es, theoretical calculations, and, on a very

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84 limited basis, from the published database by Franklin Associates (Prairie Village, Kansas, USA), provided in the SimaPro databases. A list of specific data sources is provided in Table 51 for each major process included. As noted in Table 5-1, different emission f actors were used for el ectricity production by pulp and paper mills as compared to the U.S. average production by electric generating facilities. This distinction is made because it is common pract ice for pulp mills to se lf-generate most of the electricity required on-site using waste products (e.g., bark boilers) and as part of the chemical recovery process (e.g., recovery boilers for black liquor solids ) (Smook 1992). Therefore, air emissions resulting from energy production onor off-site are signi ficantly different. Differences in the U.S. average and mill averag e fuel mixes for electricity production are shown in Table 5-2. Assumptions made in this regard included the following: 1) any equipment (fans, blowers, etc.) required for opera ting the control systems is power ed by electricity generated on site, 2) any electricity used for primary or s econdary material processing is generated according to the U.S. average fuel mix, and 3) no net CO2 is produced by combustion of bark or other wood wastes, as these biomass materials contain bioge nic carbon that is part of the natural carbon cycle and that does not cont ribute to atmospheric con centrations of carbon dioxide. Impact Assessment Life cycle impact assessment (LCIA) was performed to connect the mass and energy input and emission output results from the LCI to broader indicators or ca tegories of impact to the environment or human health. For this LCIA, categories were selected based on their relevance to this studys focal area s (raw material requirements, energy use, and emissions to air, including greenhouse gases, criteri a pollutants, and hazardous air po llutants (HAPs)). Therefore, categories selected include abiotic resource deple tion potential (ADP), global warming potential

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85 (GWP), photochemical oxidation potential (POP), acidificati on potential (AP), and human toxicity potential (HTP). Impacts were calculat ed based on the published impact factors of CML 2 (The Institute of Environmental Sciences, Le iden University, Leiden, The Netherlands, 2001), provided in SimaPro 5.1. This method was select ed based on its widespread use and because its problem-oriented (midpoint) approach could be a pplied to directly rela te LCI flows with the environmental areas to which they contribute impacts. In a pplying the CML 2 method to this LCA, characterization factors for methane and nitrous oxide global wa rming potential were modified slightly from published values to reflect the updated 100-year global warming potentials of the Interngovernmental Panel on Climate Change (IPCC) Third Assessment Report (IPCC 2001). No normalization or weighting of im pact assessment values was performed, in accordance with ISO 14044:2006 guidelines for a LCA intended for comparative assertion intended to be disclosed to the public (ISO 2006). Interpretation and Sensitivity Analysis LCI and LCIA results were interpreted based on the stated goal and sc ope of the study to compare the two air emissions control technologies using the environmental and human health indicators of interest. In a ddition to this direct interpretation, a sensitivity analysis was performed on the assumptions and system bounda ries used in creating the studys scope. The assumptions tested are described below. 1. Use of a wood-based activated carbon. The Bionuchar GAC is chemically activated from wood-based precursors such as sawdus t, although many other activated carbons are produced from coal and other nonrenewable re sources and activated using steam. This analysis will compare LCIA results for use of a bituminous coal-based, steam-activated GAC (such as Filtrasorb 400, Calgon Corporation, Pittsburgh, PA, USA). 2. Lifetime of STC pellets and biofilter packing. Both of these components for the PCObiofilter system are assumed to have a five-year lifetime. However, it is impossible to determine if this assumption is realistic w ithout full-scale operation in a specific pulp mill

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86 environment. Therefore, this analysis will address possible shorter or longer lifetimes for these packing materials and the effect of their lifetime on LCIA results. 3. UV bulb energy requirements. The PCO reactor specifications call for 216 UV bulbs with an energy input of 75 Watts. Given the continuous operation of these bulbs, the material and energy required and resulting ai r emissions generated are expected to be substantial for their use. Therefore, this se nsitivity analyses will examine the effect of using lower wattage bulbs, assuming that photocatalytic methanol removal could be maintained at required levels. Results Inventory The results of the material and energy inve ntory, normalized per functional unit of the treatment of 350 scfm of air with a methanol concentration of 50 ppmv, in order to achieve 98% methanol removal, are shown both as inputs from the technosphere to construction and operation of the control equipment (Table 5-3) and as inputs from nature to the entire life cycle (Table 54). This distinction between inputs was made to illustrate various processes and materials ultimately required for both systems. Total solid waste generated is also included in Table 5-3. Emissions to air per functional unit for greenhou se gases, criteria pollutants, and other air pollutants are shown in Table 5-5. Raw material s from nature and air emissions generated were categorized for both the construction and opera tion phases and aggregated for both control technologies. For example, air emissions fr om construction of the RTO-scrubber system represented the total emissions for constructing the RTO, the scrubber, and all other infrastructure required for this system, such as duc t work. In addition to the complete life cycle air emissions, the inventory also included comp arative emissions of the compounds contributing 99.9% by mass to the total HAP concentration in effluent gas from HVLC sources before and after treatment by either system (Table 5-6). In all aspects of the LCI, results per functional unit represented the total input or emission over th e 20-year life cycle divi ded by the number of

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87 functional units occurring in the same 20-year pe riod, to obtain results on the basis of per functional unit, or per 350 scfm air containing 50 ppmv methanol, treated to remove 98% of methanol. Impact Assessment Figure 5-3 shows comparativ e environmental impacts pe r functional unit for both technologies for the five impact categories assessed. Units shown are kg antimony (Sb) equivalent (abiotic resource deple tion potential); kg carbon dioxide (CO2) equivalent (global warming potential); kg ethylene (C2H2) equivalent (photochemical ox idation potential; kg sulfur dioxide (SO2) equivalent (acidification potential); and kg 1,4-dichlorobenzene (1,4-DB) equivalent (human toxicity potential). Sensitivity Analysis Results of the sensitiv ity analysis on coalversus woodbased granular activated carbon precursor, lifetime of biofilter packing and STC pe llets, and the wattage of UV bulbs in the PCO reactor are shown in Figures 5-4, 5-5, and 5-6, respectively. All resu lts are presented as a relative ratio of total impact of the system of interest divided by total impact of the RTOscrubber system. Presenting relative results allo wed for direct comparison of trends among the sensitivity analyses and the impact categories and e liminates the variability in units and scale that would be observed when using absolute results. Discussion Inventory Based on results of the inventory of inputs fr om the technosphere into the construction and operation of the two systems (T able 5-3), it is evident that th e stainless steel required to construct the RTO, scrubber, and associated ductwork (1.44E-3 kg/f unctional unit) and the

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88 energy required (5.59E-2 MJ/functio nal unit) to produce this and ot her infrastructure material were substantially higher than any other ma terial or energy input required to produce infrastructure for the PCO-biofilter system. Howeve r, there are 11 materials, in addition to water and energy, that were unique to the PCO-biof ilter system because of the need to produce STC pellets (including required equipment) and biofilter packing material, both of which were expected to have a five-year lifetime. In te rms of operations, the RTO-scrubber system required high volumes of water (1.08E-3 m3/functional unit) and na tural gas (1.76E-2 m3/functional unit) to operate the wet scrubber and support VOC inci neration, respectively. However, because of the use of 216 75-W UV bulbs in the PCO reactor this system required almost an order of magnitude greater amount of electricity for opera tions than the RTO system (1.12 as compared to 0.224 MJ/functional unit). In terms of solid waste, the PCO-biofilte r system was also the greatest contributor, due in large part to the needed replacement of biofilter packing and STC pellets every five years and the disposal of UV bulbs annually, since there was no assumption included here for recycle or reuse of any of this material. This solid waste could potentially be minimized if these materials useful life was ex tended or recycling or reactivation opportunities were pursued. Raw material inputs from nature required to produce material and energy for the entire life cycle (including the secondary materials described in Table 53) are shown on a per functional unit basis in Table 5-4. Trends in raw material usage were similar to what was described in Table 5-3; that is, the construction of the RTO, scrubber, and ductwork system (1.81E-1 kg/functional unit total) and the operation of the PCO-biofilter system (7.51E-1 kg/functional unit total) created the highest dema nds for resources. Reso urces for construction of both systems were distributed relatively evenly across materials required for producing

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89 stainless steel and other metals and materials for infrastructure. On the other hand, resources required for operating the systems were those ne eded for producing elect ricity, such as wood waste and spent black liquor solids used to produce el ectricity on-site at the mills, as well as coal and natural gas used to produce electricity pu rchased by the mills to supplement their own supply. Natural gas requirements were high er for operating the RTO-scrubber system, as compared to the alternate technology, because of the need to add natural gas to support oxidation of VOCs in the HVLC gas stream. Even with energy recovered by the regenerative capacity of the system, there is still an ener gy deficit in the RTO, primarily because the concentration of VOCs was so low compared to the total volume of gas, that energy produced from combusting the VOCs was not sufficient to sustain required operating temperatures. Similar trends were observed for the compar ison of air emissions produced over the life cycle of both control options, per functional unit, as shown in Tabl e 5-5. Total life cycle air emissions for most of the pollutants considered were slightly higher for the PCO-biofilter system, again due to the energy required to ope rate UV bulbs and the processes and chemicals used to produce the STC pellets and the activated carbon, nutrient, and pe rlite used as biofilter packing. Some air emissions, such as vinyl chloride, hydrofluoric acid, and ammonia, were unique to the PCO-biofilter system, and could be at tributed to the secondary material processing steps used to produce feedstocks and equipment needed for STC pellet and biofilter packing production. In addition to the life cycle air emissions inventoried, the VOC emissions from HVLC sources before and after the treatment sy stems were also estimated per functional unit (Table 5-6). Regardless of the system used, ther e was expected to be a significant reduction in all VOCs present. Although the imp act of this reduction was not asse ssed here, it is expected to be important for photochemical oxidant production a nd human toxicity potential. Many of these

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90 compounds have high photochemical oxidant potentia l factors (e.g., the al cohols, ketones, and aldehydes) and human toxicity factors (e.g., fo rmaldehyde), in addition to the nuisance odors associated with the reduced sulfur species, all of which would be significantly reduced by either of the technologies adopted. Impact Assessment As is often the case with LCA studies, the im pact assessment results did not point to a clear winner between the two air emission contro l systems. Instead, the impact assessment results in Figure 5-3 illustrate potential environm ental tradeoffs of adopti ng one or the other of the two options. Expected impacts of the PCObiofilter system were approximately 20% less than impacts of the RTO-scrubber system when considering categorie s of abiotic resource depletion, photochemical oxidant formation, a nd acidification. On the other hand, the PCObiofilter system results were 25% higher for global warming and over 50% higher for human toxicity, as compared to the RTO-scrubber. One clear trend that can be observed, however, is that in all of the impact cate gories considered, the construction stage of the RTO-scrubber life cycle contributed to at least 25% of the total impact. If this stage had been excluded from the system boundaries, the LCA results would have been drastically skewed toward favoring the RTO system. However, in all but the human toxi city category for the RTO, the operation phase of both systems life cycles did contribute the hi ghest impact. This result was due primarily to the combustion of fossil, biomass, and waste fuel s to produce electricity at the pulp and paper mills that is required to operate fans and pumps required by both systems and the UV bulbs required by the PCO reactor. Electricity generati on not only required the input of nonrenewable abiotic resources such as coal and crude oil, but also produced greenhouse gases that contribute to global warming and pollutants such as SO2, which contributes to photochemical oxidation and

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91 acidification. In all but the human toxicity categ ory, the production of STC pellets and biofilter packing only contributed about 10% to the total impact. The increased contribution to human toxicity is a result of proces sing hazardous compounds, such as vinyl chloride and hydrofluoric acid, to produce materials needed for the STC pe llets (such as HF) or to produce the equipment used to produce the pellets (such as PTFE or PVC). Interpretation Given the goal of this LCA to compare two methanol control systems based on raw material and energy inputs, and air emission and solid waste outputs, as well as the resulting environmental impact, the results shown in Figur e 5-3 demonstrated that both control systems have advantages and disadvant ages, depending on the impact category considered. However, these results and the sensitivity analyses shown in Figures 5-4 through 5-6 could be used to determine opportunities for minimizing envir onmental impact for both systems. Sensitivity analysis Although this LCA was performed under th e assumption that GAC produced from a wood waste material would be used as the pr imary biofilter packing material, mills may reasonably be expected to use other forms of GAC, based on availabil ity, different process requirements, or economics. Therefore, impacts for the entire LCA of PCO-biofilter system were compared for both types of GAC precurs or, and results are shown in Figure 5-4, normalized to the impact results for the RTO-scrubber system for each category. Based on the inventory information available for this study, th e resulting impact assessment showed no real variation in results for the biofilter packing stag e itself or the total lif e cycle compared to the RTO-scrubber system. The slight increase for the coal-based carbon in the ADP category was due to the use of a nonrenewable fossil fuel rather than a wood waste as precursor. In the other

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92 categories, wood-based GAC impact s were slightly higher, as th e wood-based process was more energy intensive, based on the data available. The difference between woodand coal-based GAC results showed no overall impact on the LCA results. Regardless of the precursor used, requiremen ts for the GAC and other packing material depended directly on their useful service life and required replacement. For this LCA, the biofilter packing and the STC pellets were assumed to be used for five years, thus requiring three sets of replacement material be produced to achieve a total 20-year system lifetime. However, there are numerous variables related to the actual full-scale use of these systems that may affect their lifetime. For example, process changes in the mill could reduce HVLC concentrations, thus extending the service life of all equipment. Alte rnatively, the presence of particulate matter or corrosive compounds in the gas stream may dramatic ally reduce the service lif e. To this end, a sensitivity analysis was performed to compare one -, five(baseline), and ten-year lifetimes for both biofilter packing material a nd STC pellets, with results shown in Figure 5-5. For all of the impact categories, there was a 50% or less reduc tion in impacts when extending the lifetime of these materials to 10 years. The lower reductions were due to the equipment required for producing the STC pellets that were included in this life cycle system, as the materials and emissions associated with equipment production did not change regardless of pellet production rate. On the other hand, reduci ng lifetime to one year showed a much higher increase in all impacts, and, for every category considered, the shorter lifetime resulted in impacts higher than the total life cycle of the RTO system. For the categorie s of global warming, photochemical oxidant formation, and acidifica tion potential, the increase in impact was mostly due to the biofilter packing material demand, based on the energy required for activation of the carbon and production of the ammonium nitrate nutrient. Ho wever, for the category of human toxicity, the

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93 increased impact for a one-year packing lifetim e was attributable to the use of hazardous chemicals described earlier for the production of materials and chemicals needed to manufacture the STC pellets. Ultimately, the environmental impacts of the PCO-biofilter system considered in this LCA appeared to be highly dependent on the lifetime of the packing materials. Therefore, as this technology continues deve lopment towards full-scal e application, design criteria should be established to ensure extended life of all packing materials. Another consideration in devel opment of this innovative syst em is the continued use of UV bulbs and their associated raw materials a nd electricity requirement s (thus resulting in additional emissions). Results of the sensitivity analysis on bulb energy use are shown in Figure 5-6. These results indicated that, if lower watt bulbs were able to be substituted in the PCO reactor without compromising methanol destruc tion, the PCO-bioreactor system would be environmentally favorable to the traditional RT O system in all impact categories except human toxicity. Use of 50W bulbs in this LCA, resulted in impacts for the PCO-biofilter system that were 10-40% less than those for th e RTO-scrubber in the categories of resource depletion, global warming, acidification, and photochemical oxidati on potential. These re sults illustrated an opportunity to not only minimize the environmenta l impact associated w ith this technology but also reduce the economic cost of operating the PC O reactor, a major incentive for the pulp and paper industry. Conclusions The use of life cycle assessment (LCA) fo r this comparative study provided a valuable way to compare two potential techno logies that have been proposed as methanol control systems at pulp and paper mills. Although neither option consistently yielded lower impacts, the PCObiofilter system showed lower environmental impacts to resource depletion, photochemical

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94 oxidant production, and acidification over its entire life cycle, compared to the traditional approach of using a regenerative thermal oxidizer followed by a cau stic scrubber. However, the RTO-scrubber system consistently showed lower life cycl e impacts to global warming. With the recent increase of public attention to issues of climate change and potential future regulation on greenhouse gases, careful attention to decreasi ng greenhouse gas emissions associated with operational energy requirements of the PCO-biofilt er system is recommended. Fortunately, unlike the more established RTO systems, this innovative methanol contro l system is still in development, with numerous opportunities for mi nimizing resource use, emissions, and life cycle environmental and human health impacts. Some of these opportunities have been demonstrated in the sensitivity analysis, particularly the n eed to minimize electricity use by UV bulbs in the PCO reactor and to maximize the service life of biofilter packing media and STC pellets. Results of this LCA also showed that the im pacts of producing infras tructure required for the RTO and scrubber contributed up to 25% of the total life cycle impacts fo r this system. From an environmental perspective, these impacts poten tially could be reduced if the amount of steel required for constructing ducts were minimized by locating the RTO closer to the HVLC source (although this may not be a feasible solution give n limited area near the emissions source). From a methodological perspective, howev er, results showing the importan ce of infrastructure impacts helped to demonstrate the im portance of including this stage in the system boundaries. Furthermore, results of this LCA can be used to illustrate the benefits of adopting a life cycle perspective and considering environmental impact of all stages of a process when selecting and implementing industrial technology.

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95 Table 5-1. List of data sources used for major processes in compiling the life cycle inventory of two alternative technologi es for methanol control Inventory Data Data Source VOC production and control VOC emissions from HVLC sources NCASI 2003 Typical VOC control approaches Varma 2003; Potlatch Cor poration Air Operating Permit (ADEQ 1999); Banks 1998; Santos et al. 1992 RTO and Scrubber Construction and Operation RTO design and sizing Cooper and Alley 2002; Lewandowski 2000 Scrubber design and sizing Cooper a nd Alley 2002 Schifftner and Hesketh 1996 Stainless steel production World Stainless Steel LCI (ISSF, 2006) Caustic (NaOH) production AP 42 Emission Factors (U.S. EPA, 1995) PCO and Biofilter Constr uction and Operation PCO design and sizing Stokke et al. 2006; other data provided based on design of pilot scale unit Aluminum, copper, carbon steel, acrylic, and glass production AP 42 Emission Factors (U.S. EPA, 1995) Biofilter design and sizing Babbitt et al. 2007; Devinny et al. 1999 STC pellets Pellet production equipment and pellet formulation Stokke et al. 2006; other data provided based on design of pilot scale unit PVC, CPVC, PTFE production (for equipment) AP 42 Emission Factors (U.S. EPA, 1995) HF, HNO3, TEOS production AP 42 Emissi on Factors (U.S. EPA, 1995) TiO2 production Morters et al. 2001; Reck and Richards 1999 Biofilter packing Bionuchar activated carbon production Menendez-Diaz and Martin-Gullon 2006; MeadWestvaco Virginia Corporation Draft Title V permit (KDEP 2005b) Perlite and ammonium nitrate fertilizer production AP 42 Emission Factors (U.S. EPA, 1995) Energy Pulp and paper mill electricity production and emission factors E-Grid (U.S. EPA 2006); NCASI GHG spreadsheet (NCASI 2004); Smook 1992 U.S. average electricity production and process specific emission factors E-Grid (U.S. EPA 2006) Life cycle inputs to U.S. average electricity production Franklin Associates LCI Database (in SimaPro)

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96 Table 5-2. Average fuel mix for electricity produc tion in the United States and at an average pulp and paper mill Percent of total (%) U.S. Average Pulp Mill Average Coal 50.2 13.8 Natural gas 17.4 16.4 Fuel oil 3 6.4 Nuclear 20 --Hydropower 6.6 --Non-hydro renewables 2.6 --Black liquor solids --40 Bark/wood waste --16 Purchased electricity (assume U.S. average) --7.4 Reference U.S. EPA 2006Smook 1992

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97 Table 5-3. Material and energy inputs from the technosphere directly to and solid waste outputs from construction and operation of tw o alternative technologies for methanol control Inputs (per functional unit)1 RTO and Scrubber PCO Reactor and Biofilter Infrastructure Stainless steel (kg) 1.44E-03 1.97E-04 Carbon Steel (kg) --2.12E-05 Glass (kg) --2.53E-04 PVC/CPVC (kg) --4.99E-05 Ceramic/Refractory (kg) 2.43E-04 --Aluminum (kg) --4.24E-06 Copper (kg) --3.66E-06 Water (m3) 2.25E-05 3.10E-06 Energy (MJ) 5.59E-02 9.36E-03 STC Pellet Production Stainless steel (kg) --2.74E-05 PVC/CPVC (kg) --9.09E-05 PTFE (kg) --3.38E-06 TEOS (kg) --3.22E-04 Ethanol (kg) --1.52E-05 TiO2 (kg) --1.35E-05 HNO3 (kg) --2.42E-06 HF (kg) --2.88E-07 Water (m3) --8.11E-07 Energy (MJ) --1.03E-02 Biofilter Packing Production Nutrient (kg) --8.37E-04 Granular activated carbon (kg) --6.83E-04 Perlite (kg) --2.24E-04 Water (m3) --9.20E-07 Energy (MJ) --3.94E-02 Operations NaOH (kg) 3.74E-04 --Process Water (m3) 1.08E-03 4.35E-04 Natural gas (m3) 1.76E-02 --Electricity (MJ) 2.24E-01 1.12E+00 Solid waste generated (p er functional unit) Total solid waste (kg) 7.28E-04 1.66E-03 1All values are normalized to th e functional unit of the treatm ent of 350 scfm of air with a methanol concentration of 50 ppmv, in order to achieve 98% methanol removal

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98Table 5-4. Raw material input s, in kg per functional unit1, from nature into the total life cy cle of construction and operation of two alternative technologies for methanol control RTO and Scrubber PCO Reactor and Biofilter Raw Material (kg) Construction Operation Total Cons truction Operation STC Pellets Biofilter packing Total bauxite 2.27E-04 --2.27E-04 1.56E-05 ------1.56E-05 chromium 1.17E-04 --1.17E-04 1.60E-05 --2.22E-06 --1.82E-05 coal 5.33E-03 2.47E-03 7.80E-03 8.53E-04 1.13E-02 8.06E-04 1.27E-04 1.31E-02 copper (in ore) ------3.84E-06 ------3.84E-06 crude oil 3.56E-03 1.53E-03 5.09E-03 6.18E-04 6.41E-03 8.68E-04 1.03E-04 7.99E-03 dolomite 7.52E-05 --7.52E-05 1. 02E-05 --1.43E-06 --1.17E-05 feldspar ------1.95E-05 ------1.95E-05 fluorspar ----------5.84E-06 --5.84E-06 iron (in ore) 4.22E-04 --4.22E-0 4 7.97E-05 --7.99E-06 --8.77E-05 lignite 7.54E-05 --7.54E-05 1. 02E-05 --1.43E-06 --1.17E-05 limestone 6.16E-04 1.43E-04 7.58E-04 1.39E-04 6.50E-04 5.23E-05 7.32E-06 8.49E-04 manganese 2.82E-05 --2.82E-05 3. 83E-06 --5.34E-07 --4.36E-06 molybdenum 4.03E-05 --4.03E-05 5.47E-06 --7.63E-07 --6.23E-06 NaCl 9.34E-05 3.94E-04 4.87E-04 9.97E-05 --1.44E-04 --2.44E-04 natural gas 3.60E-03 1.72E-02 2.08E-02 5.71E-04 8.81E-03 6.07E-04 1.22E-03 1.12E-02 nickel 2.86E-05 --2.86E-05 3. 88E-06 --5.41E-07 --4.42E-06 perlite ------------2.35E-04 2.35E-04 phosphorous 6.51E-07 --6.51E-07 8.85E -08 --1.23E-08 6.46E-04 6.46E-04 rutile ----------3.36E-05 --3.36E-05 sand ------1.90E-04 ------1.90E-04 silica 1.30E-04 --1.30E-04 ----------silicon 1.08E-05 --1.08E-05 1. 47E-06 --4.36E-05 --4.51E-05 soda ash ------5.93E-05 ------5.93E-05 spent liquor solids --6.55E-03 6.55E-03 --3.32E-02 ----3.32E-02 water 2.25E-02 1.51E-01 1.74E-01 3.10E-03 6.80E-01 8.11E-04 9.20E-04 6.85E-01 wood/wood wastes 5.68E-06 2.11E-03 2.12E-03 9.15E-07 1.07E-02 1.05E-06 1.37E-03 1.20E-02 Total 3.69E-02 1.81E-01 2.18E-01 5.80E-03 7.51E-01 3.39E-03 4.63E-03 7.65E-01 1All values are normalized to th e functional unit of the treatmen t of 350 scfm of air with a meth anol concentration of 50 ppmv, in order to achieve 98% methanol removal.

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99 Table 5-5. Emissions to air in kg per functional unit1, for construction and operation of two a lternative technologies for methanol control RTO and Scrubber PCO Reactor and Biofilter Construction Operation Total C onstruction Operation STC Pellets Biofilter Packing Total Greenhouse Gases carbon dioxide (CO2) 1.98E-02 5.46E-02 7.44E-02 3.07E-03 8.55E-02 2.33E-03 3.12E-03 9.41E-02 methane (CH4) 3.93E-05 1.24E-04 1.64E-04 6.38E-06 1.10E-04 7.26E-06 7.13E-06 1.30E-04 nitrous oxide (N2O) 6.50E-07 6.98E-07 1.35E-06 1.05E-07 3.16E-06 1.24E-07 1.06E-06 4.45E-06 Criteria Pollutants carbon monoxide (CO) 3.12E-05 8.85E-05 1.20E-04 5.24E-06 1.32E-04 3.16E-06 1.42E-05 1.55E-04 nitrogen oxides (NOx) 4.44E-05 1.00E-04 1.44E-04 8.71E-06 1.53E-04 5.23E-06 1.30E-05 1.80E-04 sulfur dioxide (SO2) 1.91E-04 6.62E-04 8.53E-04 3.33E-05 5.88E-04 3.04E-05 3.55E-05 6.87E-04 particulate matter (PM) 2.37E-05 9.01E-06 3.27E-05 4.86E-06 3.62E-05 4.23E-06 3.88E-06 4.92E-05 Other Air Emissions ammonia (NH3) ------5.76E-10 --2.88E-09 1.16E-06 1.16E-06 chlorine (Cl2) 7.70E-07 3.25E-06 4.02E-06 8. 21E-07 --1.18E-06 --2.00E-06 hydrochloric acid (HCl) --1.20E-06 1.20E-06 ----------hydrofluoric acid (HF) ----------3.75E-08 --3.75E-08 mercury (Hg) 1.89E-07 5.64E-08 2.46E-07 3.03E-08 2.63E-073.49E-08 5.27E-09 3.33E-07 vinyl chloride (VC) ------2.48E-07 --8.01E-07 --1.05E-06 non methane volatile organic compounds (NMVOC) 4.92E-05 1.65E-04 2.14E-04 7.93E-06 1.19E-049.08E-06 1.49E-05 1.51E-04 1All values are normalized to th e functional unit of the treatmen t of 350 scfm of air with a meth anol concentration of 50 ppmv, in order to achieve 98% methanol removal.

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100 Table 5-6. VOC emissions, in kg per functional unit1, from HVLC sources in the brownstock pulp washing process before treatment and estimated VOC emissions resulting from the two alternative technologi es for methanol control Emission to Air (kg) Before Treatment RTO and Scrubber PCO Reactor and Biofilter methanol 6.48E-04 1.30E-05 1.30E-05 dimethyl sulfide 2.49E-04 4.97E-06 4.97E-06 dimethyl disulfide 9.06E-05 1.81E-06 1.81E-06 Alpha-pinene 4.25E-05 8.50E-07 8.50E-06 acetone 4.18E-05 8.35E-07 8.35E-06 beta-pinene 2.50E-05 5.00E-07 5.00E-06 acetaldehyde 1.51E-05 3.02E-07 5.29E-06 o-cresol 1.30E-05 2.60E-07 4.55E-06 methyl mercaptane 1.18E-05 2.37E-07 2.37E-07 ethanol 1.17E-05 2.35E-07 2.35E-06 methyl ethyl ketone 8.97E-06 1.79E-07 1.79E-06 m-cresol 6.81E-06 1.36E-07 2.38E-06 formaldehyde 4.52E-06 9.04E-08 9.23E-07 1,2,4-trichlorobenzene 2.03E-06 4.06E-08 7.10E-07 p-cymene 1.99E-06 3.97E-08 6.96E-07 propionaldehyde 1.65E-06 3.29E-08 5.76E-07 Total VOC emissions 1.17E-03 2.35E-05 6.11E-05 1All values are normalized to th e functional unit of the treatm ent of 350 scfm of air with a methanol concentration of 50 ppmv, in order to achieve 98% methanol removal.

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101 Figure 5-1. System boundaries for the life cy cle of the constructi on and operation of a regenerative thermal oxidizer (RTO) and caustic scrubber for the treatment of methanol Primary Raw Material Processing (Stage 1) Secondary Material Processing (Stage 2) Energy Production (Stage 2) RTO Construction Air Emissions Scrubber Construction RTO Operation Scrubber Operation VOC emissions from HVLC sources Inputs from nature Solid Waste Material Energy Air emission Solid waste System Boundary (Stage 3) t t t: Input from technosphere

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102 Figure 5-2. System boundaries for the life cy cle of the constructi on and operation of a photocatalytic oxidation (PCO) reactor and biofilter for th e treatment of methanol Primary Raw Material Processing (Stage 1) Secondary Material Processing (Stage 2) Energy Production (Stage 2) PCO Construction Air Emissions Biofilter Construction PCO Operation Biofilter Operation VOC emissions from HVLC sources Inputs from nature Solid Waste Material Energy Air emission Solid waste System Boundary STC pellet p roduction Biofilter packing p roduction ( Sta g e 3 ) (Stage 3) t: Input from technosphere t t (Stage 3)

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103 0.0E+002.0E-044.0E-046.0E-048.0E-04RTO/ Scrubber PCO/ Biofilter Abiotic Depletion (kg Sb eq) 0.0E+003.0E-026.0E-029.0E-021.2E-01RTO/ Scrubber PCO/ Biofilter Global Warming (kg CO2 eq) 0.0E+001.0E-052.0E-053.0E-054.0E-055.0E-05RTO/ Scrubber PCO/ Biofilter Photochemical Oxidation (kg C2H2 eq) 0.0E+003.0E-046.0E-049.0E-041.2E-03RTO/ Scrubber PCO/ Biofilter Acidification (kg SO2 eq) 0.0E+005.0E-041.0E-031.5E-032.0E-032.5E-03RTO/ Scrubber PCO/ Biofilter Human Toxicity (kg 1,4-DB eq) Construction Operation STC Pellets Biofilter Packing Figure 5-3. Total comparative life cycle impacts, per functional unit1, of the construction and operation of two alternat ive technologies for methanol control 1All impacts are normalized to the functional unit of the treatment of 350 scfm of air with a meth anol concentration of 50 ppmv, in order to achieve 98% methanol removal.

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104 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6RTO Wood Coal RTO Wood Coal RTO Wood Coal RTO Wood Coal RTO Wood Coal ADPGWPPOPAPHTP Impact category and TechnologyRelative Impact Biofilter Packing STC Pellets Operation Construction Figure 5-4. Sensitivity analysis of wood or coal used as precursor material for granular activated carbon production, based on relative impact of the PCO-biofilter system as compared to the RTO-scrubber system All results are divided by the total impact of the RTO-scrubber system for each impact category to provide a relative impact pe r functional unit compared to the RTO-scrubber (relative RTO impacts are equal to 1). RT O=RTO-scrubber system; Wood=PCObiofilter system using wood precursor for GAC production; and Coal=PCO-biof ilter system using bituminous coal precursor for GAC production. discreet

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105 0.0 0.5 1.0 1.5 2.0 2.5RTO 1 yr 5 yr 10 yr RTO 1 yr 5 yr 10 yr RTO 1 yr 5 yr 10 yr RTO 1 yr 5 yr 10 yr RTO 1 yr 5 yr 10 yr ADPGWPPOPAPHTP Impact Category and TechnologyRelative Impact Biofilter Packing STC Pellets Operation Construction Figure 5-5. Sensitivity analysis of the lifetime of biofilter packing media and STC pellets, based on relative impact of the PCObiofilter system as compared to the RTO-scrubber system All results are divided by the total impact of the RTO-scrubber system for each impact category to provide a relative impact pe r functional unit compared to the RTO-scrubber (relative RTO impacts are equal to 1). RTO=RTO-scrubber syst em; 1 yr, 5 yr, and 10 yr=PCO-biofilter system with a 1, 5, or 10 year (resp ectively) lifetime of both the biofilter packing media and the STC pellets.

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106 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6RTO 75 W 60 W 50 W RTO 75 W 60 W 50 W RTO 75 W 60 W 50 W RTO 75 W 60 W 50 W RTO 75 W 60 W 50 W ADPGWPPOPAPHTP Impact Category and TechnologyRelative Impact Biofilter Packing STC Pellets Operation Construction Figure 5-6. Sensitivity analysis of the lifetim e energy requirement of UV bulbs in the PCO reactor, based on relative impact of the PCO-biofilter system as compared to the RTOscrubber system All results are divided by the total impact of the RTO-scrubber system for each impact category to provide a relative impact pe r functional unit compared to the RTO-scrubber (relative RTO impacts are equal to 1). RTO=RTO-scrubber system; 75W, 60W, and 50W =PCO-biofilter system with 75, 60, or 50 W (respectively) UV bulbs used in the PCO reactor. For Figures 5-4 through 5-6, ADP= abiotic resource deplet ion potential; GWP=global warming potential; POP=photochemical oxidation potential; AP=acidifi cation potential; and HTP=human toxicity potential.

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107 CHAPTER 6 SUMMARY, CONCLUSIONS, RECOMME NDATIONS AND BROADER IMPACTS Summary This research was conducted to investigate an activated carbon biofiltration system for methanol control in the pulp and paper industr y, as a more economical and environmentally friendly alternative to thermal oxidation. This investigation focused on developing and testing a bench-scale activated carbon biofiltration system containi ng a novel packing mixture and capable of removing methanol from an artificially contaminated air stream in concentrations representative of industrial processes. In addi tion, design and operation of this biofilter enabled a more thorough study of the technology at a variety of scales and from both a theoretical and practical perspective. These studies included 1) culture-dependent a nd independent microbial ecology and molecular techniques to characteri ze biological samples from the pulp and paper industry on the basis of selecting a biofilter inoculum and optimizing their growth and biodegradation in mixed culture; 2) characteriza tion of the activity and diversity of bacterial communities derived from the biofilter under vari ed operating conditions ove r different points in time; and 3) life cycle assessment to compare global environmental impacts of the proposed system to those associated with thermal oxidation. Conclusions The results of this work have shown the following: Biofilms obtained from a Kraft pulp mill could be enriched to support methanol degradation in the batch culture as well as to be used as inoculum for an activated carbon biofilter, as shown in Chapter 2. Initial phenotypic characterizat ion of the mixed methylotrophi c cultures indicated that the mill biofilms were host to highly diverse populati ons of bacteria able to rapidly degrade methanol, which would make for straightforw ard provision of an i noculum culture if a biofilter or other biological treatment system is implemented in the mill environment (Chapter 2).

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108 The type of nitrogen source used when en riching mixed methylotrophic cultures as potential biofilter inoculums influenced the gr owth and methanol degradation ability of these bacteria, with faster growth and higher methanol removal in cultures enriched with nitrate as compared to those enriched w ith ammonium, as shown in Chapter 3. Higher concentrations of the nitrogen source also resulted in greater methanol removal in batch cultures (Chapter 3), although increasi ng the concentration did not significantly affect growth rate of the mixed cultures. These results were promising for applications, such as a biofilter, where adding nitrogen could enhance methanol removal without causing biomass overgrowth that could lead to clogging and minimized performance. The form of nitrogen used also affected the diversity and community structure of the methylotrophic populations present in each of th e final cultures (Chapter 3), as cultures grown on nitrate maintained a higher diversity as measured by species richness and evenness observed from DGGE gels, compared to cultures enriched with ammonium. A bench-scale inoculated GAC biofilter (BB) system was successfully demonstrated for the removal of methanol from an artificially contaminated air stream (Chapter 4). The methanol removal efficiency for this system and an identical, non-inoculated biofilter (NB) were similarly high (~100%) for both biofi lters over the majority of operating time. The excellent methanol removal was believe d to be attributable to use of novel heterogeneous biofilter packing material cont aining a mixture of ac tivated carbon, perlite, slow release nutrient pellets, and water-ret aining crystals. This packing material provided excellent support for the growth a nd activity of methanol degrading bacteria over time and during high vari ability in operating conditions. Although performance results for the two biofilters were sim ilarly high, an examination of the underlying microbiology using molecular me thods showed that, in fact, they were colonized by different populati ons of bacteria that were di stributed differently throughout the length of the biofilters. Bacterial abundance and diversity were both higher in the inoculated biofilter, which may have contri buted to the robust performance of the BB over all operating conditions, even when the NB removal efficiency dropped periodically. The use of life cycle assessment (LCA) in Chapter 5 showed that a proposed novel treatment system consisting a photocatalytic oxidation (PCO) r eactor and activated carbon biofilter had lower envir onmental impacts to resource depletion, photochemical oxidant production, and acidifi cation associated with its construction and operation, as compared with a more traditional technology of a regenerative thermal oxidation (RTO) and wet scrubber system. The PCO-biofilter system had higher life cycle impacts to global warming and human toxicity (Chapter 5), because of the continua l electricity input required to operate the UV bulbs with the PCO reactor and the material s needed to produce the STC pellets. A sensitivity analysis showed that minimizing electricity requirements for the PCO reactor

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109 and maximizing the service life of biofilter packing media and STC pellets would greatly reduce environmental impacts for the PCO-biofilter system. Results of the LCA (Chapter 5) also showed that the impact s of producing infrastructure required for the RTO and scrubber contributed up to 25% of the to tal life cycle impacts for this system, which demonstrated the impor tance of including infrastructure impacts in the LCA methodological framework. This research demonstrated that an activated carbon biofilter system is an effective and environmentally friendly option th at could be developed for meth anol control for the pulp and paper industry, as well as other industry sectors that are challe nged with controlling HAPs and other volatile organic compounds ( VOCs) in their process streams. Recommendations and Broader Impacts Based on results reported throughout this st udy, an activated carbon biofilter is a promising technology for meeting methanol cont rol requirements for pulp and paper mills. However, limitations and additional questions that arose in this work have provoked new questions that guide recommendati ons for extension of this inve stigation. For example, the results that both an inoculated and non-inoculated biofilter provided excellent methanol removal, despite different colonizing populat ions, can naturally be extended into a study that focuses on the specific roles of the p acking and the bacterial comm unity. Additional study on the interactions of the introduced and colonizing bacteria with the packing and with other types of packing material could address this question. Fr om a broader perspective, the results underscore the need to examine microbial diversity as part of overall design and operation strategies and performance measurements for bi ofilters, rather than focusing on removal efficiency alone. This type of study involving ba tch culture character ization is important as a first step towards a better understanding of the ecology of methylotrophic ba cteria and their potential use in biological treatment systems. Results indicating a preference by the batch cultures for nitrate

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110 as the nitrogen source should be extended through additional benchand pilot-scale observations of the methanol removal ability and underlying ecology and diversity of methylotrophic bacteria in biological treatment applications using these and other nitrogen sources and concentrations. Finally, the results of the LCA illustrated both the environmental and human health benefits and disadvantages associated with a PCO-biofilter system, and these results can guide specific modifications to this developing tec hnology, such as reduc ing operational energy requirements and increasing serv ice life of the packing materi als. Furthermore, this study illustrates the benefits of adopting a life cycle perspective and considering environmental impact for all stages of a process when selecting and implementing industrial technology. It is recommended that this perspective be continua lly implemented throughout future work on these systems, beginning at the lab and bench-scale and transcending to full scale technologies.

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111 APPENDIX: ADDITIONAL FIGURES 0 5 10 15 20 25 30 35 0102030405060708090 Time (days)Inlet Methanol Loading Rate (g/m3 packing/hr)0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%Methanol Removal Efficiency (%) Average Removal Efficiency Average methanol loading rate (g/m3-packing/hr) Figure A-1. Methanol removal efficiency as a fu nction of time and metha nol loading rate, in a preliminary trial of a biologically inoculated biofilters using SB as inoculum. Excessive biomass formation and clogging was observed by day 20, which correlated with loss of methanol removal performance.

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112 Figure A-2. Photograph of prelim inary biofilter, clogged by excess biomass when using SB as inoculum. y = 1.0207x 0.8896 R2 = 0.7525 0 0.5 1 1.5 2 2.5 00.511.522.53 log (c)log (q) Figure A-3. Freundlich isotherm pl ot of batch isotherm results fo r the activated carbon biofilter packing material.

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113 PCR-DGGE with mxa F specific primers PCR-DGGE with universal 16s rRNAprimers Inoc BB day 22 day 46 day 77 day 102 day 125 day 138 Inoculum in Batch Culture day 22 Inoc BB day 22 day 46 day 77 day 102 day 125 day 138 Inoculum in Batch Culture day 22 1 3 2 PCR-DGGE with mxa F specific primers PCR-DGGE with universal 16s rRNAprimers Inoc BB day 22 day 46 day 77 day 102 day 125 day 138 Inoculum in Batch Culture day 22 Inoc BB day 22 day 46 day 77 day 102 day 125 day 138 Inoculum in Batch Culture day 22 1 3 2 Figure A-4. DGGE analysis of mxaF and 16s rRNA gene sequences from a long-term batch culture created using the same biofilter inoculum derived from SA as used to inoculate the activate carbon biofilter BB.

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114 LIST OF REFERENCES Arkansas Department of Environmental Quality (ADEQ) (1999) Potlatc h Corporation Cypress Bend Mill Air Operating Permit. Permit number 271-AOP-R2 Aizpuru A, Malhautier L, Roux J, Fanio J (2003) Biofiltration of a mixture of volatile organic compounds on granular activated carbon. Biotechnol Bioeng 83: 479-488 Babbitt CW, Pacheco A, Lindner AS (2007) Methanol removal performance and bacterial diversity in an activated car bon biofilter. In preparation Banks D (1998) Problems with Kraft mill pulp mill non-condensable gas incinerators. Banks Engineering, Tulsa, OK Barta TM, Hanson RS (1993) Genetics of meth ane and methanol oxidation in Gram-negative methylotrophic bacteria. Anton Leeuw Int J G 64: 109-120 Boiesen A, Arvin E, Broholm K ( 1993) Efect of mineral nutrients on the kinetics of methane utilization by methanotr ophs. Biodegradation 4: 163-170 Bouwer EJ, McCarty PL (1982) Removal of tr ace chlorinated organic compounds by activated carbon and fixed-film bacteria. Environ Sci Technol 16: 836-843 Bowman JP, Sayler GS (1994) Maximization of Methylosinus tric hosporium OB3b soluble methane monooxygenase production in batch cu lture. In: Hydrocarbon Bioremediation. Hinchee RE, Alleman BC, Hoeppel RE, Miller RN, eds. Lewis Publishers, Boca Raton, pp. 267-273 Bruns MA, Hanson JR, Mefford J, Scow KM ( 2001) Isolate PM1 populations are dominant and novel methyl tert-butyl ether-degrading bact eria in compost biofilter enrichments. Environ Microbiol 3:220-225 Calgon Carbon Corporation (1996) Product Bulleti n: Filtrasorb 300 & 400. Pittsburgh, PA Chang H, Rittmann B (1987) Verification of the m odel of biofilm on activated carbon. Environ Sci Technol 21: 280-288 Chory J, Pollard JD (1999) Resolution and recovery of small DNA fragments. In: Current Protocols in Molecular Biology, Ausubel FM Brent R, Kingston RE, Moor DD, Seidman JG, Smith JA, Struhl K, eds, John Wiley & Sons, Inc. Hoboken, New Jersey, pp:2.7.12.7.8 Chung YC (2007) Evaluation of gas removal and bacterial community di versity in a biofilter developed to treat composting ex haust gases. J Haz Mat 144: 377-385

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115 Conrad R (1996) Soil microorganisms as controllers of atmospheric trace gases (H2, CO, CH4, OCS, N2O, and NO). Mi crobiol Rev 60: 609-649 Cooper CD, Alley FC (2002) Air pollution contro l: A design approach. Third edition. Waveland Press, Inc. Long Grove, IL Dabrowski A (2001) Adsorption from theory to practice. Adv. Colloid. Interfac. Sci. 93:135274 De Visscher A, Van Cleemput O (2003) Induction of enhanced CH4 oxidation in soils: NH4+ inhibition patterns. Soil Biol Biochem 35: 907-913 Dedysh SN, Knief C, Dunfield PF (2005b) Methylocella specie s are facultatively methanotrophic. J Bact 187: 4665-4670 Dedysh SN, Smirnova KV, Khmelenina VN, Su zina NE, Liesach W, Trotsenko YA (2005a) Methylotrophic autotrophy in Beijerinc kia mobilis. J. Bact. 187: 3884-3888 Devinny JS, Deshusses MA, Webster TS (1999) Bi ofiltration for Air Pollution Control. Lewis Publishers, Boca Raton, FL Doronina NV, Ivanova EG, Trotsenko YA (2005) Phylogenetic position and emended description of the genus Methylovorus. Int J Sys Evol Microbiol 55: 903 Dunfield PF, Khmelenina VN, Suzina NE, Trotsenko YA, Dedysh SN (2003) Methylocella silvestris sp. nov., a novel methanotroph isolated from an acidic forest cambisol. Int J Sys Evol Microbiol 53: 1231-1239 Dunne WM Jr. (2002) Bacteria adhesion: Seen any good biofilms lately? Clin Microbiol Rev 15:155-166 Dusenbury JS, Cannon FS (2004) Effect of advanced oxidants generated via ultraviolet light on a sequentially loaded and regenerated granul ar activated carbon bi ofilter. J Air Waste Manage Assoc 54: 871-889 El-Nawawy AS, Banat IM, Elrayes EG, Hamdan IY (1990) Isolation and char acterization of four methylotrophic bacterial strains. J Basic Microb iol 5: 321-331 Fjellbirkeland A, Torsvik V, Ovreas L (2001) Meth anotrophic diversity in an agricultural soil as evaluated by denaturing gradie nt gel electrophoresis profil es of pmoA, mxaF and 16S rDNA sequences. Anton Van Leeuwen 79: 209-217 Gilbride KA, Frigon D, Cesnik A, Gawat J, Fult horpe RR (2006) Effect of chemical and physical parameters on a pulp mill biotreatment bacterial community. Wat Res 40: 775-787

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116 Gribbins MJ, Loehr RC (1998) Effect of media nitrogen concentration on biofilter performance. J Air Waste Manage Assoc 48: 216-226 Hanson RS (1998) Ecology of me thylotrophic bacteria. In: Tec hniques in Microbial Ecology, Burlage RS, Atlas R, Stahl D, Geesey G, Sayl er G, eds, Oxford Un iversity Press: New York, pp: 337-353 Hanson RS, Hanson TE (1996) Methanotroph ic bacteria. Microbiol Rev 60: 439-471 Hayek LC, Buzas MA (1996 Surveying Natural P opulations. Columbia University Press: New York City, New York. Henckel T, Friedrich M, Conrad R (1999) Mo lecular analyses of the methane-oxidizing microbial community in rice field soil by targeting the gene s of the 16S rRNA, particulate methane monooxygenase, and me thanol dehydrogenase. Appl Environ Microbiol 65:1980-1990 Herzberg M, Dosoretz C, Tarre S, Green M (2003) Patchy biofilm coverage can explain the potential advantage of BGAC reactor s. Environ Sci Technol 37: 4274-4280 Higgins IJ, Best DJ, Hammond RC, Scott D (1991) Methane-oxidizing microorganisms. Microbiol Rev 45: 556-590 Hodge DS, Devinny JS (1994) Biof ilter treatment of ethanol vapors. Environ Prog 13: 167-173 Intergovernmental Panel on Climate Change (IPCC) (2001) Climate Change 2001: The Scientific Basis. Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Johnson CA, and Maskell K, eds.; Cambridge University Press. Cambridge, U.K International Organization of St andardization (ISO) (2006) Environmental management Life cycle assessment Principles and fram ework. International Organization of Standardization, Geneva, Switzerland (International Standard ISO14044:2006) International Stainless Steel Forum (ISSF) (2006) World stainless steel LCI. Requested from < www.worldstainless.org > Accessed July 20, 2007 Jin-Ying X, Hong-Ying H, H ong-Bo Z, Yi Q (2005) Effects of a dding inert spheres into the filter bed on the performance of biofilters for ga seous toluene removal. Biochem Eng J 23:123130 Jorgensen KR, Villanueva A, Wenzel H (2004) Use of a life cycle assessment as decisionsupport tool for water reuse and handling of re sidues at a Danish i ndustrial laundry. Wat Manage Res 22: 334-345 Kentucky Department of Environmental Protection (KDEP) (2005a) Calgon Carbon Corporation, Catlettsburg Plant Draft Ai r Quality Permit. Permit number V-06-020

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117 Kentucky Department of Environmental Protec tion (KDEP) (2005b) Mead Westvaco Virginia Corporation, Wycliffe Carbon Draft Ai r Quality Permit. Permit number V-06-009 Kennes C, Thalasso F (1998) Waste gas bi otreatment technology. J Chem Technol and Biotechnol 72:303-319 Kennes C, Veiga MC (2001) Bioreactors for Waste Gas Treatment. Kluwer Academic Publishers, Dordrecht, The Netherlands King GM (1992) Ecological aspects of methane oxidation, a ke y determinant of global methane dynamics. Adv Microbial Ecol 12: 431-438 Koh L-H, Kuhn DCS, Mohseni M, Allen DG (20 04) Utilitizing ultrav iolet photooxidation as a pre-treatment of volatile organic compounds upstream of a biological gas cleaning operation. J Chem Technol Biotechnol 79: 619-625 Kramer MF, Coen DM (2001) Enzymatic amplif ication of DNA by PCR: Standard procedures and optimization. In: Current Protocols in Molecular Biology. Ausubel FM, Brent R, Kingston RE, Moor DD, Seidman JG, Smith JA, Struhl K, eds, John Wiley & Sons, Inc, Hoboken, New Jersey Kumar S, Tamura K, Nei M (2004) MEGA3: Integr ated software for Molecular Evolutionary Genetics Analysis and sequence alignmen t. Briefings in Bioinformatics 5:150-163 Labbe N, Juteau P, Parent S, Villemur R (2003) Bacterial diversity in a marine methanol-fed denitrification reactor at the Montreal Biodome, Canada. Mi crobiol Ecol 46:12-21 Lahtinen T, Kosonen M, Tiirola M, Vuento M, Oker-Blom C (2006) Diversity of bacteria contaminating paper machines J Ind Microbiol Biotechnol 33:734-740 Legendre P, Legendre L (1998) Nu merical Ecology. Second English Edition. Elsevier Science B.V., Amsterdam, The Netherlands Lewandowski DA (2000) Design of thermal oxida tion systems for volatile organic compounds. CRC Press, LLC. Boca Raton, FL Li C, Moe WM (2004) Assessment of microbial populations in methyl ethyl ketone degrading bibofilters by denaturing gradient el elec trophoresis. Appl Microbiol Biotechnol 64: 568575 Liang J, Koe L, Chiaw C, Ning XG (2007) Applicat ion of biological activa ted carbon as a low pH biofilter medium for gas mixture treatment. Biotechnol. and Bioeng. 96: 1092-1100

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123 BIOGRAPHICAL SKETCH Callie Whitfield Babbitt received her Bachelor of Science in chemical engineering from the Georgia Institute of Tec hnology in 2001 and her Master of Engineering in environmental engineering sciences from the Univ ersity of Florida (UF) in 2003. Her masters research focused on production, disposal, and beneficial use of coal combustion byproducts created during electricity generation. Callies current inte rests are in pollution prevention, life cycle assessment, industrial ecology, a nd microbial ecology, specifically addressing the pulp and paper industry. These topics stem from Callies expe rience in the pulp and paper industry, where she first became interested in pollution prevention. She previously worked for Georgia Pacific and Buckeye Technologies, a specialty cellulose company. More recently, she worked as an assistant on air emissions and permitting projects at Golder Associates in Gainesville, FL. Callie has been a research assistant and teach ing assistant for Dr. Angela S. Lindner in environmental engineering sciences at UF for 5 years. She was also a research assistant with the UF Office of Sustainability and the M.E. Rinke r School of Building Construction. These experiences shaped Callies interest in creating environmentally and economically sustainable solutions for industry and academic institutions. Her recent work as program coordinator for Office of Sustai nability Initiatives at Arizona State University focused on examining campus practices to reduce environmenta l impact and initiating programs to increase environmental literacy and stewardship on the ASU campus. She recently completed a university-wide greenhouse gas inve ntory and assisted in prepari ng the ASU Strategic Vision for Sustainability. These projects sparked Callies inte rest in social aspects of sustainability, and she has taken a role as program coordinator for an in terdisciplinary research project entitled Late Lessons from Early History in the School of Human Evolution and Social Change at ASU.


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