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1 ENVIRONMENTAL AND ECONOMIC SUITABILITY OF FOREST BIOMASSBASED BIOENERGY PRODUCTION IN THE SOUTHERN UNITED STATES By PUNEET DWIVEDI 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 2010
2 2010 Puneet Dwivedi
3 To almighty and all his noble manifestations around me
4 ACKNOWLEDGMENTS I am thankful to several people who helped me in successfully completing my doctoral research at the University of Florida. I am grateful to my advisor, Dr. Janaki R.R. Alavalapati, for his continuous support and guidance. His passion towards research and teaching has always motivated me to test limits of my own scholarly capability. I am also thankful to all other members of my doctoral committee Dr. Douglas R. Carter, Dr. Sherry L. Larkin, Dr. Angela S. Lindner, and Dr. Farid AitSahlia for their continuous encouragement and timely advice. It was a great honor to work with all such wonderful people. I am also thankful to all other faculty members of the University of Florida who gave their expert opinions to me from time to time. I also extend my acknowled gments to all people who participated in surveys. I am also thankful to the staff of School of Forest Resources and Conservation at the University of Florida for all the help and support I also acknowledge the support of Alumni Fellowship and SAFER project for successful completion of my doctoral research at the University of Florida. I am thankful to all my current and former lab members namely Nguyen Thuy, Gregory Parent, Cindy Chandool, Tyler Nesbit, Chad Foster, Andres Susaeta, Pankaj Lal, Ming Yuan Huang, Sidhanand Kukrety, Jean -Gael Emptaz Collomb, and Ilan Kaufer for all the fun that I had while working in the lab. Ultimately, I must thank to my parents for their courage and support to allow me to come to the United States to pursue my dream of doctoral studies. Being a single child, I realize that this must have been a big decision for them. Finally, I must greet my wife for all her love and patience. Without her support, I would have not achieved significantly
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ...................................................................................................... 4 LIST OF TABLES ................................................................................................................ 7 LIST OF FIGURES .............................................................................................................. 8 ABSTRACT .......................................................................................................................... 9 CHAPTER 1 INTRODUCTION TO THE STUDY ............................................................................ 11 Background ................................................................................................................. 11 Renewable Energy Resou rces in the United States ................................................. 13 Ethanol Production in the United States .................................................................... 15 Feedstocks for Ethanol Production ............................................................................ 17 Southern Forestlands and Bioenergy Development .................................................. 18 Problem Statement ..................................................................................................... 20 Research Significance and Objectives ...................................................................... 21 2 CELLULOSIC ETHANOL PRODUCTION IN THE UNITED STATES: CONVERSION TECHNOLOGIES, ECONOMICS, AND FUTURE DEVELOPMENTS ...................................................................................................... 25 Introduction ................................................................................................................. 25 Cellulosic Feedstock Composition ............................................................................. 27 Base Technologies ..................................................................................................... 28 Hydrolysis Technology ......................................................................................... 29 Pretreatment methods (first stage hydrolysis) .............................................. 30 Hydrolysis technologies (second stage hydrolysis) ..................................... 32 Fermentation .................................................................................................. 33 Integrated technologies based on hydrolysis ............................................... 34 Thermo-chemical Conversion Technology ......................................................... 35 Fermentationbased ethanol production ....................................................... 35 Catalyst based ethanol production ............................................................... 36 Current Production Status of Cellulosic Ethanol Production ..................................... 37 Economics of Cellulosic Ethanol Production ............................................................. 38 Hydrolysis -based Technologies .................................................................... 38 Th ermo-chemical Technologies .................................................................... 40 Emerging Developments ............................................................................................ 41 Conclusions ................................................................................................................ 43
6 3 LIFE CYCLE ASSESSMENT FOR EVALUATING ENVIRONMENTAL AND ECONOMIC SUSTAINABILITY OF ETHANOL PRODUCTION FROM FOREST BIOMASS .................................................................................................................... 49 Introduction ................................................................................................................. 49 Methods ...................................................................................................................... 52 Results ........................................................................................................................ 62 Discussions ................................................................................................................. 65 Conclusions ................................................................................................................ 66 4 IMPACT OF EMERGING VOLUNTARY CARBON AND BIOENERGY MARKETS ON NON -INDUSTRIAL PRIVATE FOREST LANDOWNERS PROFITABILITY ......................................................................................................... 76 Introduction ................................................................................................................. 76 CCX Guidelines .......................................................................................................... 79 Forestry Feedstocks ................................................................................................... 80 Literature R eview ........................................................................................................ 82 Methods ...................................................................................................................... 85 Results ........................................................................................................................ 89 Discussions ................................................................................................................. 91 Conclusions ................................................................................................................ 92 5 STAKEHOLDERS PERCEPTIONS ON FOREST BIOMASS-BASED BIOENERGY DEVELOPMENT IN THE SOUTHERN UNITED STATES .............. 101 Introduction ............................................................................................................... 101 Literature Review ...................................................................................................... 105 SWOT -AHP Framework ........................................................................................... 108 Methods .................................................................................................................... 110 Results ...................................................................................................................... 112 Discussions ............................................................................................................... 115 Conclusions .............................................................................................................. 117 6 SUMMARY AND CONCLUSIONS ........................................................................... 126 Introduction ............................................................................................................... 126 Policy Implications .................................................................................................... 127 Limitations of the Study ............................................................................................ 129 Future Research ....................................................................................................... 131 LIST OF REFERENCES ................................................................................................. 132 BIOGRAPHICAL SKETCH .............................................................................................. 149
7 LIST OF TABLES Table page 2 -1 Distribution range of wood components ................................................................ 45 2 -2 Chemical constituents of loblolly pine (%) ............................................................. 45 2 -3 Economics of hydrolysis -based conversion technologies .................................... 46 3 -2 Details of additional transportation steps .............................................................. 68 4 -1 Scenarios for the study .......................................................................................... 94 4 -2 Details of cost streams ........................................................................................... 95 4 -3 Details of revenue streams .................................................................................... 95 4 -4 Emissions (lbs/acre carbon dioxide equivalent) from silvicultural practices ........ 95 4 -5 Sensitivity analysis for Scenario E and Scenario F ............................................... 96 5 -1 Forest biomass ava ilability and energy values from southern timberlands ....... 118 5 -2 Relevant factors identified in each SWOT category ........................................... 119 5 -3 Summary of the priority scores of all SWOT factors and categories .................. 120
8 LIST OF FIGURES Figure page 1 -1 Solar resources of the United States ..................................................................... 23 1 -2 Wind-based power production in the United States until yearend 2008 .............. 24 2 -1 Cellulosic ethanol production using hydrolysis -based technologies .................... 47 2 -2 Cellulosic ethanol production using gasification technology ................................ 47 2 -3 Installed and under construction cellulosic ethanol production capacity .............. 48 3 -1 Year wise planted area (million acres) in the southern region ............................. 69 3 -2 System boundary for the analysis ......................................................................... 70 3 -3 Direct energy use for the production of ethanol and E85 fuel .............................. 71 3 -5 GHG emissions (carbon dioxide equivalent) ......................................................... 73 3 -6 Results of the sensitivity analysis .......................................................................... 74 3 -7 Comparison of different feedstocks ....................................................................... 75 4 -1 Model used for assessing carbon balance in slash pine plantations ................... 97 4 -2 Biomass distribution in different products .............................................................. 98 4 -3 Carbon distribution for a thinned and an unthinn ed slash pine plantation ........... 99 4 -4 Calculated LEVs of different scenarios ............................................................... 100 5 -1 Pairwise comparison of factors under strength category .................................... 121 5 -2 Perception map of the NGO stakeholder group .................................................. 122 5 -3 Perception map of the government stakeholder group ....................................... 123 5 -4 Perception map of the industry stakeholder group ............................................. 124 5 -5 Perception map of the academia stakeholder group .......................................... 125
9 Abstract o f Dissertation Presented t o t he Graduate School of the University o f Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy ENVIRONMENTAL AND ECONOMIC SUITABILITY OF FOREST BIOMASSBASED BIOENERGY PRODUCTION IN THE SOUTHERN UNITED STATES By Puneet Dwivedi May 2010 Chair: Janaki Alavalapati Major: Forest Resources and Conse r vation T his study attempts to ascertain the environmental and economic suitability of utilizing forest biomass for cellulosic ethanol production in the Southern United States The study is divided into six chapters. The first chapter details the background and defines the relevance of the study along with objectives. The second chapter revi ews the exi s ting literature to ascertain the present status of various existing conversion technologies The third chapter assesses the net energy ratio and global warming impact of ethanol produced from slash pine (Pinus elliottii Engelm ) biomass. A life -cycle assessment was applied to achieve the task. The fourth chapter assess es the role of emerging bioenergy and voluntary carbon markets on the profitability of n on-i ndustrial p rivate f orest (NIPF) landowner s by combining the Faustmann and Hartmann model s The fifth chapter assesses perceptions of four stakeholder groups (Non-Government Organization, Academics, Industries, and Government) on the use of forest biomass for bioenergy production in the Southern United States using the SWOT AHP (Strength, Weakness, Opportunity, and Threat Analytical Hierarchy Process) technique Finally, overall conclusions are made in the sixth chapter.
10 Results indicate that currently the production of c ellulosic ethanol is limited as the production cost of cellulosic ethanol is higher than the production cost of ethanol derived from corn. However, it is expected that the production cost of cellulosic ethanol will come down in the future from its current level due to ongoing research efforts The tota l global warming impact of E85 fuel (production and consumption) was found as 10.44 tons where as global warming impact of an equivalent amount of gasoline (production and consumption) was 21.45 tons. Th is suggest s that the production and use of ethanol derived from slash pine biomass in the form of E85 fuel in an automobile saves about 51% of carbon emissions when compared to gasoline. The net e nergy ratio of ethanol produced at the mill was found to be 3.2. The unit cost of production of ethanol was estim ated to be $2.05 per gasoline gallon energy equivalent. The study also found that the emerging bioenergy and voluntary carbon markets will significantly increas e land expectation values and, thus, the profitability of landowners. Results suggest that the optimal rotation age is insensible to alternate m anagement scenarios. Finally, it was found that all stakeholder groups perceive that the overall benefits of forest biomass -based bioenergy development were higher than its weaknesses
11 CHAPTER 1 INTRODUCTION TO THE STUDY Background The United States is the largest consumer of gasoline in the world. About 363 million gallons/day of gasoline were consume d in 2008 which was about 26% more than the total gasoline consumed in 1985 (EIA 2009a). About 110 and 62 million barrels of gasoline w ere imported and exported in 2008, respectively (EIA 2009b). Based on these numbers, it can be easily deduced that the ne t imported gasoline accounted for just 1.51% of total gasoline consum ed in the country in 2008. This implies that the country is almost self sufficient in meeting the domestic demand for gasoline. However, this is not true, as it does not account for the gasoline which was refined from imported crude oil within the country. About 3,581 million barrels of crude oil w ere imported in to the country in the year 2008 which was 207% higher than the crude oil imported in 1985. It was found that Canada, Mexico, Saudi Arabia, Venezuela, Nigeria, and Iraq supplied about 20 %, 12 %, 16 %, 11 %, 10 %, and 7 % of total crude oil imported in 2008, respectively (EIA 2009c). As a barrel of crude oil (42 gallons) yields 18.56 gallons of gasoline (EIA 2009d), therefore 183 million gallons/day of gasoline w ere produced from imported crude oil in 2008. This implies that 52% of the total gasoline consumed in the country in 2008 was produced from imported crude oil after subtracting net quantities of imported gasoline. The prime reason for increasing crude oil imports is the continuously declining domestic crude oil production in the United States. For example, about 1,914 million barrels of crude oil w ere produced in the United States in 2008 out of which about 5% was produced from offs hore oil wells and remaining was produced from oil wells located
12 on the main land. This total production of crude oil was about 40% less than the crude oil produced in 1985 (EIA 2009e). This implies that the country is increasingly becoming dependent on fo reign countries to meet the domestic demand for various petroleum products like gasoline, diesel, heating oil, jet fuel, chemical feedstocks, asphalt, and other products. Dependence on foreign countries for crude oil and other petroleum products increases the vulnerability of the country towards price fluctuations in the international energy market and global conflicts. Additionally, use of various petroleum products raises concern about the emission of various greenhouse gases which are responsible for gl obal warming. For instance, it was reported that the consumption of a gallon of gasoline in an automobile releases 19.56 pounds of carbon dioxide (a primary greenhouse gas) into the atmosphere (EIA 2009f). Therefore, it can be deduced that about 7,101 mill ion pounds of carbon dioxide/day was released into the atmosphere due to daily consumption of gasoline in 2008 alone. Note that the transportation sector alone contributed about 24% of all the carbon dioxide emissions in 2008 at the national level. The con tribution of transportation sector was second highest (2, 220 million tons ) pr oceeded by electrical sector (2, 670 million tons ) and followed by industrial (1, 808 million tons ), residential (1, 378 million tons ), and commercial sectors (1, 199 million tons ) of economy (EIA 2009g). Policy makers have launched several initiatives to ensure energy in dependence and a reduction in the emission of greenhouse gases. Foremost among all the initiatives is to increase the use of various renewable energy sources like solar, wind, geothermal, hydropower, and biopower found in the country It is expected that the use of renewable
13 energy can help the country in reducing greenhouse gas emissions and in achieving energy independence. It is also believed that this will propel ec onomic development in the country by creating local jobs Renewable Energy Resources in the United States The potential of various renewable energy sources to meet the growing energy demand of the nation is enormous. For example, ACORE (2007) reported that about 635 GW of power can be produced from various renewable sources by the end of year 2025 out of which power from wind, solar, hydro, geothermal, and biomass could contribute about 248,164, 23,100, and 100 GW, respectively. Note that the total installed electricity generation capacity in 2008 was about 1,088 GW (EIA 2009h). The section below summarizes the present status of various renewable energy sources in the country Solar energy : The solar energy is by far the Earths most available energy source and is abundantly available in the United States. Figure 1 1 shows the distribution of solar energy available across the United States (EIA 2009i). Solar energy can be used for both heati ng and electricity generation. At yearend 2008, the United States had about 8,800 MW of installed solar capacity. This included about 1,100 MW of photovoltaics, 418 MW of utility -scale concentrating solar power, at least 485 MWTh of solar water heating systems, and over 7,000 MWTh of solar pool heating systems (SEIA 2009). It is expected that use of solar energy to meet nations energy needs will further grow due to the policy support provided by the federal government in the form of the Emergency Economic Stabilization Act of 2008. This act extends the 30% solar investment tax credit for eight years, lifts the cap for residential photovoltaic installations, allows application of the tax credits against the alternative minimum taxes,
14 and removes the prohibition against utilities use of the solar investment tax credits (SEIA 2008). Wind Energy : The total installed capacity of wind power in the country by yearend 200 9 was about 34 863 MW. Figure 1 -2 shows the distribution of wind energy production in the United States (EERE 2009 a ). As obser ved, Texas (9,403 MW) and California (2, 798 MW) are prime producers of the wind power in the c ountry followed by Iowa ( 3,604 ) and Minnesota (1,810 MW). It is expected that existing tax benefits a nd various other policy instruments (e.g., Renewable Portfolio Standards1) will further help in increasing the wind-based power generation in the country. Geothermal Energy : The Earths heat can be utilized to produce electricity. The total potential of geothermal energy by the year 2050 in the United States is estimated to be about 12,486 GWe and 1,249 GWe at 20% and 2% heat recovery rate, respectively (MIT 2006). In 2008 about 0.358 quadrillion Btu of energy was extracted from geothermal sources which was only about 0.36% of total energy consumed in the country in the same year (EIA 2009j). Hydro Power : The total production of hydro electricity was about 2.453 quadrillion Btu in 2008 (EIA 2009j). This corresponds to about 2.47% of total electricity produced in the nation in 2008 It is expected that with an emphasis on micro-hydel projects, the role of hydro power in meeting the future energy needs of the nation will become more important. Additionally, research is going on in developing commercially viable technologies to extract energy contained in ocean and tidal waves. It is hoped that 1 The Renewable Portfolio Standard is a regulation which mandates utilities to source part of their total electricity generation from renewable energy sources like wind, solar, geothermal, hyd r o, or biomass. The percentage of renewable energy varies from state to state. For example, the Renewable Portfolio Standard for the state of California is 33% by 2020 and for the state of New York is 24% by 2013.
15 these technologies will be developed soon. This will further underline the importance of hydro power in meeting the future energy needs of the nation in a sustainable mann er Biopower : Various biomass feedstocks are used for producing electricity. In the y ear 2007, about 28,919 million k Wh of electricity was produced using biomass out of which 95% was consumed by a single sector of economy only i.e., paper and allied produc ts (EIA 2009k). It is expected that in the presence of suitable incentives (e.g., Renewable Portfolio Standards) the electricity production from biomass will go up as several companies are building large scale biomass -based power plants to produce electric ity. For example, Gainesville Regional Utilit ies is planning to build a 100 MW power plant at Gainesville, Florida which will utilize biomass to produce electricity (GRU 2009). The above analysis of various renewable energy sources gives an impression that promoters of renewable technologies are interested in only producing electricity and heat to meet future energy demand. However, recently a lot of emphasis is being made on uti lizing various biomass feedstocks to produce ethanol and biodiesel with an objective of reducing countrys dependence on foreign energy sources. It was also reported that renewable fuels can contribute about 30% to 40% of total petroleum consumption in 202 5 (ACORE 2007) Th is study focus es on ethanol, therefore only details of ethanol derived from various biomass feedstocks in general and forestry feedstocks in particular will be discussed from hereafter. Ethanol Production in the United States Ethanol prod uction got a big support in the country when the Congress passed the F ederal Clean Air Act Amendments of 1990 through which the use of reformulated gasoline in ozone nonattainment areas was made mandatory beginning in 1995. The
16 Congress specified that reformulated gasoline should contain 2% oxygen by weight. Ethanol and M ethyl T ertiary B utyl E ther (MTBE) were the two most commonly used oxygenates in initial years. However, several states banned the use of MTBE and a s a resul t ethanol bec a me the oxygenate of choice in the reformulated gasoline program. The Energy Policy Act of 2005 promulgated a nationwide renewable fuels standard (RFS) in which it was mandated to produce 7.5 billion gallons of renewable fuels by the year 2012. A credit -trading program was also created in which a gallon of ethanol derived from cellulosic biomass or waste was assumed equal to 2.5 gallons of renewable fuel. Additionally, a program for the production of 250 million gallons of cellulosic ethanol by 2013 was also mentioned in the same act. Suitable tax incentives and various grants were also announced to attract investors and researchers in order to increase the success of the entire renewable fuel production program Several states also announced several incentives (tax credits, s ubsidies, etc.) to promote ethanol production in their state. The Energy Independence and Security Act of 2007 further redefined the RFS and mandated t he production of at least 36 billion gallons of renewable fuel by the year 2022 of which 21 billion gallons was required to be obtained in the form of advanced biofuels.2 It was also mention ed that out of 21 billion gallons of advanced biofuels, 16 2 The term advanced biofuel means renewable fuel, other than ethanol derived from corn starch that has at least 50% less greenhouse gas emissions relative to baseline greenhouse gas emissions. This includes a) ethanol derived from cellulose, hemicellulose, or lignin; b) ethanol derived from sugar or starch (other than corn starch); c) ethanol derived from waste material, including crop residue, other vegetative waste material, animal waste, and food waste and yard waste; d) biomass based diesel; e) biogas (including landfill gas and sewage waste treatment gas) produced through the conversion of organic matter from renewable biomass; f) butanol or other alcohols produced through the con version of organic matter from renewable biomass; and g) other fuel derived from cellulosic biomass.
17 billion gallons should qualify as cellulosic biofuels.3 The quantity of conventional renewable fuel i.e., ethanol derived from corn starch was capped at 15 billion gallons. In addition to both acts, ethanol producti on was also facilitated by the Food, C onservation, and E nergy Act of 2008 which provided a subs idy of $1.01 for every gallon of cellulosic ethanol produced and $0.45/gallon on conventional biofuel. Due to these various incentives provided by the federal and various state governments, ethanol production has increased substantially in recent years. For example, national ethanol production was only 175 million gallons in 1990, but jumped to 9,000 million gallons in 2008 (RFA 2009). Feedstocks for Ethanol P roduction Ethanol can be produced from several biomass feedstocks. These biomass feedstocks are eit her sourced from agricultural lands or forestlands. Currently, the majority of ethanol produced in the country comes from corn. U se of corn for ethanol production has raised concerns for food security (Mitchell 2009) and environmental sustainability (Pimentel and Patzek 2005). More recently, the impacts of land use change have been considered in calculating the net emission of greenhouse gases from biofuel production indicating that the conversion of grasslands, peat lands, tropical forests, and other intac t ecosystems to grow energy feedstocks far outweighs the greenhouse gas offsets of burning biofuels rather than fossil fuels ( Fargione 2008; Searchinger 2008). It has also been reported that devoting the entire nations 2005 corn crop to ethanol production would have offset only about 12% of the gasoline consum ed 3 The term cellulosic biofuel means renewable fuel derived from any cellulose, hemicellulose, or lignin that is derived from renewable biomass and that has lifecycle greenhouse gas emissions that are at least 60% less than the baseline lifecycle greenhouse gas emissions.
18 in the same year (Hill 2006). Because of concerns associated with grain -based ethanol production, policy makers are emphasizing the use of various cellulosic feedstocks for ethanol production as manifested through the redefined RFS. Several cellulosic feedstocks like corn stover, switchgrass, wheat residues, sugarcane, and processing residues, etc. can be obtained from agricultural lands. How ever, forestlands will also play a significant role in meeting the growing demand for cellulosic feedstocks to produce ethanol. Perlack et al. (2005) estimated that about 368 million dry tons of forestlandderived biomass can be utilized for bioenergy deve lopment in the nation which is 2.5 times greater than the current consumption. This study also found that logging and other residues, fuel treatments, and fuelwood can alone contribute about 47% of total estimated biomass available from forestlands and oth er 53% can come from urban wood residues, wood processing residues, and pulping liquor. Similarly, Walsh et al. (2000) found that at a market price below $30/dry ton delivered, the total amount of forestry feedstocks available (excluding wood obtained from urban areas but including forest mill residues, dedicated forestry crops, and forestry residues) would account for approximately 24% of all cellulosic biomass available in the nation. However, the amount of available forestry feedstocks would increase to 45% of the total cellulosic feedstocks available at a market price up to $40/dry ton delivered These studies clearly show that forest biomass can play a significant role in meeting the overall feedstock demand for bioenergy development in general and cell ulosic ethanol in particular Southern F orestlands and B ioenergy D evelopment The total forest area of the United States is about 747 million acres out of which 28% (214 million acres) is located in the southern region (Alabama, Arkansas, Florida,
19 Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, Virginia, and West Virginia) The m ajority of the region s forestland (210 million acres) is classified as timberlands as their annual average productivity is greater than 20 ft3/acre/yr. Non-Industrial Private Forest (NIPF) landowners own 151 million acres of forestlands or 143 million acres of timberlands in the region and are major suppliers of roundwood products at the national level (Smith 2001) For exampl e, NIPF landowners supplied 60% of total roundwood production in the country (9.5 billion cubic feet) in 1997 out of which 67% was sourced from southern NIPF lands (6.67 billion cubic feet). This implies that southern NIPF landowners alone supplied about 42% of the total roundwood production at the national level (Smith 2001). This clearly highlights the importance of southern NIPF landowners in meeting the future demand for bioenergy development at the national level. Inspired by the prospectus, various st ate governments in the southern region have created special policy instruments to promote forest biomass -based bioenergy development in their state s For example, three agencies in the state of Georgia (Georgia Environmental Facilities Authority, Georgia F orestry Commission, and Georgia Department of Economic Development) have been grouped under the umbrella of Georgias Bioenergy Partnership to promote forest biomass -based bioenergy development. Similarly, in the state of Florida several grants have been a nnounced by the Florida Energy & Climate Commission to promote biofuel production from cellulosic feedstocks available within the state. However, utilization of forest biomass for bioenergy development also raises concerns. For example, it is expected that the bioenergy markets could intensify the
20 current regimes of forest management leading to adverse consequences for biodiversity and soil moisture conservation (Spangenberg 2008). There are also concerns about the absence of viable commercial technologies for biomass conversion to various energy products (Phillips et al. 2007). Similarly, people are concerned about the absence of a supportive policy in the region that could incorporate the aspirations of various stakeholders about the use of forest biomass -based bioenergy development in the region. Problem Statement F orest biomass available in the S outhern United States will play an important role in meeting the future demand for ethanol in the country. Therefore, it becomes imperative to assess the environmental and economic sustainability of forest biomass based ethanol production in the region. Currently, very limited information exists. Similarly, it is expected that emerging bioenergy market s will affect the profitability of NIPF landowners. The situation becomes more complex due to emergence of another market which provides monetary incentives to NIPF landowners for carbon sequestered on their forestlands. So far, h ow these two markets will affect the supplies of forest biomass and the profitabil ity of an NIPF landowner is not well understood. Additionally, perceptions of various stakeholders about forest biomass based bioenergy markets which are critical for policy and/or program development are not systematically assessed Therefore, there exist s a need for a study that could fill critical ex isting gap in our understanding and can aid in suitable policy formation in the future.
21 Research Significance and Objectives This study aims to address some of the fundamental questions related to the produc tion of cellulosic ethanol from forest biomass obtained from southern NIPF lands. These questions include the following : a ) What is the present status of various conversion technologies which are used to produce cellulosic ethanol? b ) What is the energetic content and global warming impact of cellulosic ethanol produced from forest biomass available from NIPF lands in the Southern United States ? c ) How will emerging voluntary carbon and bioenergy markets affect the profitability of an NIPF landowner in the S outhern United States? d ) What are the perceptions of stakeholders about the forest biomass based bioenergy development in the S outhern United States? In order to address the first research question, a comprehensive literature review was done and the status of existing conversion technologies was assessed The process, production cost of ethanol, and adoption rates were recorded for each technology. Emerging conversion technolo gies were also discussed. For the second research question, a detailed life -cycle assessment was undertaken by accounting for all the inputs and emissions from the seed orchard to the point where E854 is used as a fuel in an automobile. An attempt was also made to estimate the unit cost of ethanol produc tion. For the third question, guidelines of Chicago Climate Exchange for Managed Forest Projects were followed to simulate voluntary carbon markets. A detailed carbon model was used to monitor changes in the soil carbon. A benefit -cost analysis and a life -cycle assessment were integrated to assess the effects of carbon and bioenergy markets on an NIPF landowner profitability. Finally, a SWOT -AHP 4 A mixture of 85% ethanol and 15% gasoline by volume.
22 (Strength, Weakness, Opportunity, Threats Analytical Hierarchy P rocess) approach was a pplied to assess stakeholders perceptions with respect to forest biomass based bioenergy markets .
23 Figure 11. Solar resources of the United States
24 Figure 12. Wind-based power production in the United States until yearend 2008
25 CHAPTER 2 CELLULOSIC ETHANOL P RODUCTION IN THE UNI TED STATES: CONVERSI ON TECHNOLOGIES, ECONOM ICS, AND FUTURE DEVE LOPMENTS Introduction Because of rising energy dependency, increasing emission of greenhouse gas es and r isks associated with price fluctuations in the international energy market, federal and various state governments have started to develop new energy strategies which emphasize on the development of various renewable energy sources. Out of many renewable en ergy resources (biomass, solar, wind, geothermal, tidal etc.), biomass is given a high priority as it is the only source which can be directly utilized for the production of various alternative transportation fuels especially ethanol. Using food crops for ethanol production raises concerns of food security (Mitchell 2008) and environmental degradation (Pimentel and Patzek 2005); t herefore majority of petroleum importing countries (e.g., U nited States ) are interested in utilizing cellulosic biomass as a feedstock for ethanol production. As the U nited States has a large cellulosic biomass production base (Perlack et al. 2005), therefore production of ethanol from cellulosic feedstock and utilizing it as a substitute for gasoline could help in promoting rural development, reducing greenhouse gas emissions, and achieving energy independence. Inspired by the potential benefits of utilizing cellulosic biomass for ethanol production, the federal government has announced various policy targets and incentives to promote cellulosic ethanol production in the country. For instance, the Energy Independence and Security Act of 2007 aim s to produce about 21 billion gallons of biofuels from cellulosic feedstocks by 2022. Additionally, the recently enacted the Food, Conservation, and Energy Act of 2008 provides a subsidy of $1.01 on every gallon of produced cellulosic ethanol.
26 Several technologies have been developed to convert different cellulosic feedstocks into ethanol. These technologies range from fermentation (Lin and T anaka 2006) to gasification (Perkins et al. 2008). However, the commercial viability of existing conversion technologies is doubtful (Waltz 2008; Tan et al. 2008; Ruan et al. 2008; Wright and Brown 2007). As a result, the federal and various state governments are providing funding support to several private companies and public institutions to develop a suitable conversion technology through which cost of ethanol production from various cellulosic feedstock s can become comparable to the cost of ethanol produced from different agricultural feedstocks. Already, federal government has provided a funding support of about a billion dollars to develop a commercial viable conversion technology for cellulosic ethanol production (Curtis 2008). It is expected that the successful demonstration of at least one conversion technology on a commercial scale will help in increasing the confidence of investors in cellulosic ethanol production and, thus, in achieving the policy target. In light of the importance given to the development of a commercially viable conversion technology, it is essential to review the status of existing conversion technologies to ascerta in their performance in terms of adoption status and economics. Such an attempt will help in creating a baseline for the emerging conversion technologies and in guiding policy makers to streamline funding and institutional support. Therefore, the present s tudy is an attempt to summarize details of existing conversion technologies for cellulosic ethanol production and to evaluate their performance in terms of unit cost of ethanol produced and adoption status. Recent developments are also identified to facili tate future technology development.
27 In the next section, the composition of cellulosic feedstock is briefly discussed. In the third section, two major conversion technologies or base technologies that are commonly used for converting cellulosic feedstoc ks into ethanol i.e., hydrolysis and thermo -chemical conversion are explained. An attempt is also made to capture the existing versions of both base technologies. In the fourth section, the adoption status of existing conversion technologies is discussed. In the fifth section, economics of existing conversion technologies in terms of unit cost of produced ethanol is discussed. In the sixth section, emerging trends in the technology development and alternate uses of cellulosic biomass are discussed and finally the study is concluded in the seventh section. Cellulosic Feedstock Composition Cellulosic feedstock is composed of cellulose, hemicellulose lignin, and solvent extractives. Lignin acts as a cementing material and binds all other constituents together It is also responsible for providing structural rigidity to a cellulosic feedstock. -D glucopyranose units and is a chief constituent o f the feedstock. Hemicellulose like cellulose is a polysaccharide but is less comp lex and easily hydrolysable. Soluble materials or extractives in the feedstock consist of those components that are soluble in neutral organic solvents. The distribution range of different constituents in softwood and hardwood is reported in Table 2-1 (Ano nymous 2008; Miller 1999). Sugar present in the cellulose is mostly glucose. However, hemicellulose is a mixture of different types of sugars. It contains both C6 (glucose, mannose, and galactose) and C5 (xylose, arabinose, and rhamnose) sugars. Glucose, m annose, and xylose constitute about 9597% of the total sugars. For example, distribution of sugars
28 in loblolly pine ( Pinus taeda), a commercial pine species of the Southern United States is shown in Table 22 (Frederick et al. 2008a). Base Technologies At present, several technologies are in use for converting cellulosic feedstocks into ethanol. They can be grouped into two broad categories hydrolysis and thermo chemical conversion. In hydrolysis -based technologies the polysaccharides (cellulose and hemi cellulose) present in a feedstock are broken down to free sugar molecules (glucose, mannose, galactose, xylose, and arabinose). This process is also known as saccharification. These free sugar molecules are then fermented to produce ethanol. As lignin cann ot be used for ethanol production, it is removed during the conversion process and is generally utilized for meeting electricity or heat requirement of an ethanol mill.1 In thermo -chemical based technologies the feedstock is gasified to produce syngas (a mixture of carbon monoxide, hydrogen, carbon dioxide, methane, and nitrogen) which is either fermented or catalytically converted to obtain ethanol.2 Production of ethanol through thermo -chemical route is independent of the sugar quantities originally pres ent in the feedstock. Details of specific technologies under each broad category of conversion technology i.e., hydrolysis and thermo -chemical conversion are discussed below. 1 Technologies which hydrolyze the sugars to produce ethanol are also known as sugar platform technologies. 2 Gasification is a process that uses heat, pressure, and steam to convert different materials including cellulosic biomass into syngas composed primarily of carbon monoxide and hydrogen (Rezaiyan and Cheremisinoff 2005).
29 Hydrolysis Technology Hemicellulose and lignin present in the feedstock provide a protective covering to the cellulose. This protective cover should be altered for ensuring efficient hydrolysis. Therefore, special provisions are needed to loosen the feedstock structure completely before und ertaking cellulose hydrolysis. Figure 21 explains basic steps generally undertaken while converting cellulosic feedstocks to ethanol through hydrolysis. During feedstock preparation, feedstock is first washed to remove dust and any other impurities. Then it is chipped or milled to increase the surface area so that chemicals/enzymes used in the subsequent steps can easily penetrate the feedstock structure. In the pretreatment process (also called first stage hydrolysis),3 hemicellulose is hydrolyzed into the basic sugars (xylose, mannose, arabinose, and galactose). A small amount of cellulose is also hydrolyzed to glucose during the pretreatment. The mixture obtained at the pretreatment is separated into liquid and solid (lignin + unhyd rolyzed cellulose). The liquid is filtered and sent to a fermentation column for ethanol production. Solids are sent for another round of hydrolysis (also called second stage hydrolysis). Again, at the end of the hydrolysis the mixture is separated into li quid and solid (lignin). After filtration, liquid is sent to a fermentation column for ethanol production and lignin is fed into a boiler for heat production. Different types of microbes are needed for fermenting sugars obtained from cellulose and hemicell ulose and converting it to ethanol. After fermentation is over, the mixture of ethanol and water is distilled to separate ethanol. Ethanol is then dehydrated to produce fuel grade ethanol 3 Pretreat ment also helps in loosening the wood structure completely. As a result, cellulose present in the wood becomes available for hydrolysis in subsequent step.
30 (<1% of water). Water produced as a part of distillation is diverted towards a wastewater treatment facility. The ethanol obtained is then transported for subsequent use. Currently, several versions of hydrolysis technology exist though the basic framework remains the same. Each version is distinguished from another depen ding upon the type of inputs used for hydrolyzing hemicellulose and cellulose into basic sugars. First, different techniques used for feedstock pretreatment (first stage of hydrolysis) are discussed followed by techniques which are commonly used for second stage of hydrolysis. Pretreatment methods (first stage hydrolysis) Thermal pretreatment: In thermal pretreatment, feedstock is heated to about 302-356 F to break down the hemicellulose and lignin. At higher temperatures (above 482F), phenolic compounds are formed which later retard the fermentation process so care is taken not to pretreat the feedstock in severe thermal conditions (Ramos 2003). Four processes are commonly used for accomplishing thermal pretreatment i.e., steam pretreatment/steam explosion, liquid hot water, ammonia fiber explosion, and carbon dioxide explosion. During steam pretreatment, the feedstock is put in a large vessel and then steamed up to a high temperature (464F) and pressurized for few minutes. After a set time, the steam is r eleased and the biomass is quickly cooled down. The difference between steam and steam explosion pretreatment is the quick depressurization and cooling down of the biomass at the end of the steam explosion pretreatment which causes the water in the biomass to explode (Hendriks and Zeeman 2009; Jeoh 1998). In liquid hot water pretreatment, hot water is added to the feedstock in a slightly acidic environment to solubilize hemicellulose and to prevent formation of any inhibitory compounds (Yang and Wyman 2004) In ammonia fiber explosion, processed feedstock
31 is exposed to liquid ammonia at high temperature/pressure for a small time and then the pressure is swiftly reduced. In a typical procedure, t he dosage of liquid ammonia is 2.24.5 pounds ammonia per pound of dry biomass, temperature is 194F, and residence time is about 30 minutes (Sun and Cheng 2002). Similar to steam and ammonia explosion pretreatment, carbon dioxide explosion is also used for pretreatment of processed feedstock. Zheng et al. (1998) repor ted that the carbon dioxide explosion is more cost effective than ammonia explosion and prevents the formation of inhibitory compounds. Acid pretreatment: In acid pretreatment, dilute sulfuric acid is added to the feedstock to hydrolyze hemicellulose (0.5 -1.5%, temperature is greater than 320F). Sometimes, concentrated sulfuric acid is also utilized for feedstock pretreatment. The acid must be removed or neutralized before fermentation. Generally lime is used for neutralizing the medium and therefore gypsum is produced as a byproduct of the reaction. Dilute acid pretreatment is the most preferred method for feedstock pretreatment. Recently, nitric acid has also shown positive results in terms of better yields and solubility of lignin (Xiao and Clarkson 1997). Alkaline pretreatment: Alkaline pretreatment use bases like sodium hydroxide or calcium hydroxide. All lignin and a part of the hemicellulose are removed and the reactivity of cellulose for later hydrolysis is sufficiently increased. Alkalinebased meth ods are generally more effective at solubilizing a greater fraction of lignin while leaving behind much of the hemicellulose in an insoluble polymeric form (Hamelinck et al. 2005; Mosier et al. 2005).
32 Oxidative pretreatment: In oxidative pretreatment, oxid ative like peracetic acid or hydrogen peroxide is used over the feedstock suspended in the water (Gould 1984). Teixeira et al. (1999) reported that the use of peracetic acid at the ambient temperature increased the ethanol yields by about 98%. Organosolve pretreatment: In the organosolve process, an organic or aqueous organic solvent mixture with inorganic acid catalysts (hydrochloric acid or sulfuric acid) is used to break the internal lignin and hemicellulose bonds (Sun and Cheng 2002). The organic solven ts used in the process include methanol, ethanol, acetone, ethylene, glycol, triehylene glycol, and tetrahydrofurfuryl alcohol (Chum et al. 1988; Thring et al. 1990). Biological pretreatment: Brown-, white -, and soft -rot fungi are normally used for degradi ng lignin and hemicellulose present in the feedstock. Recently, Lee et al. (2007) have evaluated the pretreatment effects of three white rot fungi ( Ceriporia lacerata, Stereum hirsutum and Polyporus brumalis ) on the Japanese red pine ( Pinus densiflora). Similarly, Zhang et al. (2007) reported that the biological pretreatment with white rot fungi has a potential for improving enzymatic hydrolysis of wood and grass. They found that fermentable sugar yield of bamboo culms ( Phyllostachys pubescence) pretre ated with two fungi ( Echinodontium taxodii 2538 and Trametes versicolor G20) increased with increasing pretreatment time. Hydrolysis technologies (second stage hydrolysis) Acid hydrolysis: Acid hydrolysis is only applicable when feedstock has been pretreat ed using dilute acid process. Both dilute and concentrated acid options are available for hydrolyzing pretreated feedstock. At this stage, higher temperature (about 419F) and dilute acid (4%) are used for converting cellulose to glucose. The
33 concentrated acid process has a very high sugar yield (90%), can handle diverse feedstock, is relatively rapid (10-12 hours in total), and causes small degradation of sugars. However, the equipment required is more expensive when compared to dilute acid hydrolysis (Ham elinck et al. 2005). Enzymatic hydrolysis: Enzymatic hydrolysis provides many advantages over acid hydrolysis. For example, enzymatic hydrolysis takes place at mild conditions of temperature and pressure. As a result glucose yields are high, chances of fe rmentation inhibiting compounds are less, equipment requirements are not significant, and there is a reduction in the total environmental impact of the whole process. Cellulases4 are usually a mixture of several enzymes. At least three major groups of cell ulases are involved in the hydrolysis process: a) endoglucanase (EG, endo 1,4D glucanohydrolase, or EC 220.127.116.11) which attacks regions of low crystallinity in the cellulose fiber, creating free chain ends; b) exoglucanase or cellobiohydrolase (CBH, 1,4-D -glucan cellobiohydrolase, or EC 18.104.22.168.) which degrades the molecule further by removing cellobiose units from the free chainglucosidase (EC 22.214.171.124) which hydrolyzes cellobioase to produce glucose (Coughlan and Ljungdahl 1988; Sun and Cheng 2002). Fermentation During fermentation, both C5 and C6 sugars are fermented to ethanol under anaerobic/aerobic conditions. Historically, yeast ( Saccharomyces cerevisiae ) and other microbes like Zymomonas mobilis have been used to ferment C6 sugars i.e. glucose. 4 Cellulase refers to a class of enzymes produced chiefly by fungi, bacteria, and protozoans that ca talyze the hydrolysis of cellulose.
34 Other engineered microbes like Escherichhia coli have also been developed to ferment both C6 and C5 sugars. Based on different combinations of technologies adopted at the pretreatment, hydrolysis, and fermentation stages of ethanol synthesis, s everal integrated technologies have been developed. In the section below, existing integrated conversion technologies are discussed. Integrated t echnologies b ased on h ydrolysis Simultaneous saccharification and fermentation: In simultaneous saccharificatio n and fermentation, the feedstock is pretreated by dilute acid (1.1% sulfuric acid at 320F for 10 minutes) to hydrolyze hemicellulose into sugars. The liquor is vented from the system and then neutralized using lime. Then, liquor containing C5 sugars is s ent for fermentation. Residual solids comprise of cellulose and lignin. Yeast and enzymes are subsequently added to the residual solids where the enzymes digest cellulose and produce glucose. Yeast and other microbes ferment glucose to produce ethanol sepa rately (Krishna et al. 2001). Simultaneous saccharification and co-fermentation : In simultaneous saccharification and co -fermentation, the pretreated feedstock is exposed to different enzymes/microbes which not only hydrolyze cellulose and hemicellulose s into different sugars but also ferment sugars into ethanol. This technology is better than the simultaneous saccharification and fermentation technology in terms of cost effectiveness, better yields, and shorter processing time (Wright 1988; Chandel et al. 2007). Two stage dilute sulfuric acid hydrolysis : Kadam (2000) has described the details of two -stage dilute sulfuric acid hydrolysis. In this process, dilute sulfuric acid is
35 used at pretreatment phase to hydrolyze hemicellulose. In the hydrolysis stag e of the process, concentrated sulfuric acid is utilized for hydrolyzing cellulose. After both the stages, the liquid is separated, filtered and then neutralized (using lime) before it is sent for fermentation. Fermentation is conducted in steps. First, gl ucose is fermented to ethanol by the yeast ( Sacromyces cerevisiae). The mixture is then distilled to remove the unconverted xylose. Then second yeast ( Pachysolen tannophilu ) is added to the remaining solution to ferment xylose to ethanol. Ethanol produced from xylose is then distilled (Shleser 1994). Biomass fractionation: In biomass fractionation, feedstock is pretreated using the steam explosion method. The resulting mass is washed by either water or alkali to separate out the components of the biomass i. e., hemicellulose, cellulose, and lignin (Glasser and Wright 1998). Once separated, components containing sugars are further hydrolyzed to produce sugars. Sugars thus produced are fermented to obtain ethanol. Thermo chemical Conversion Technology In ther mo -chemical conversion, constituents of feedstock are first converted into syngas under intense heat and partial supply of air inside a gasifier. The produced syngas is then either fermented or catalytically converted to ethanol. Figure 22 shows the schematic diagram of ethanol formation through thermo-chemical route. Details of both the technologies i.e., fermentationbased and catalyst based are discussed below. Fermentation based ethanol production The feedstock is washed to remove any impurities and then chipped to the required size. Chips are dried to attain a desired moisture level (520% by weight). Sand bed present inside a fluidized bed gasifier is preheated to a temperature of about 1 022F using an external fuel supply. Once optimum temperat ure is achieved, the
36 feedstock is fed into the bed. On coming in contact with the hot sand, the feedstock decomposes producing syngas. The supply of air is simultaneously controlled to prevent complete combustion of feedstock and to raise the temperature o f the sand bed to approximately 1 472F. Once the optimum conditions are achieved, the gasifier can run on its own without any external supply of additional fuel. The syngas so produced is collected from the top of the gasifier. Gas is cleaned to remove tar and ash. Once cleaned, gas is cooled to the normal ambient temperature and stored at a high pressure. Cooled and cleaned gas is fed into an ethanol conversion chamber where microbes ferment the gas into ethanol and acetic acid. After fermentation is complete, the liquid is distilled to separate ethanol from other products. The ethanol produced is then dehydrated to produce fuel quality ethanol. Many microbes have been developed which can successfully ferment the syngas into required compounds like Clostri dium carboxidivorans P7 (Liou et al. 2005), Clostridium ljungdahlii and Clostridium autoethanogenum (Abrini et al. 1994; Vega et al. 1990). Rajagopalan et al. (2002) reported that the fermentation of syngas by the microbe (P7) is sensitive to the syngas c onstituents and proper cleaning of syngas ensures effectiveness of the process. For example, Ahmed et al. (2006) reported that presence of nitric oxide in the syngas (150 ppm) prevents fermentation of gas constituents by the P7. Catalyst -based ethanol prod uction In catalyst based ethanol production, all the processes remain the same until the gas enters into an ethanol conversion chamber. Before entering the chamber, gas is heated to 572F at a pressure of 69 bar. Gas is also mixed with water and methanol to improve yield of higher alcohols. The mixture is passed through the synthetic catalyst (molybdenum disulfide based) to obtain methanol, ethanol, and higher linear alcohols
37 up to pentanol, water, methane, and minor amounts of other hydrocarbon byproducts. The ch amber effluent is finally cooled to 109.4F using cooling water, and excess syngas is diverted to the gas cleaning area. The effluent so obtained is sent to distillation for ethanol recovery. Finally, the ethanol obtained is dehydrated to make it suitable for vehicles (Phillips 2007). Current Production Status of Cellulosic Ethanol Production Encouraged by the subsidies offered by federal government, many private entrepreneurs have ventured into cellulosic ethanol production. Figure 23 shows the details of the total quantities of cellulosic ethanol currently or expected to be produced within the country by employing different conversion technologies (RFA 2009). As observed from Figure 2-3, it is expected that about 405 million gallons of cellulosic ethanol will be produced by the end of 2012 and three conversion technologies (enzymatic hydrolysis; simultaneous saccharification and fermentation; and gasification catalytic conversion and distillation) will dominate the total production. Government has so far s upported existing cellulosic ethanol producers through various grants I t is presumed that the commercial viability of cellulosic ethanol production will be proven to private investors by the end of 2012 (Sandor et al. 2008) and thereafter, the cellulosic ethanol production will shoot up. In addition to commercial cellulosic ethanol units, many small scale cellulosic ethanol mills are coming up at various places to test the efficacy of newly developed conversion technologies or feedstocks. For example, Citr usEnergy, LLC is planning to use citrus waste to produce ethanol in Florida (CitrusEnergy 2009) It was observed that the majority of cellulosic ethanol mills which are under construction have plans to meet their cellulosic feedstock supply either from th e
38 agriculture sector (corn stover, corn cob, wheat straw, rice straw, barley straw, switch grass, sugar cane) or from municipal solid wastes. Based on the current trend, it is expected that there will be only handful of cellulosic ethanol mills which will utilize forest biomass as feedstock in the future. Economics of Cellulosic Ethanol Production Production of ethanol from cellulosic feedstocks is costly when compared to its production from starch-based agricultural feedstocks (McAloon et al. 2000). Theref ore the goal of the several research agencies is to bring down the cost of production of cellulosic ethanol to $1.33/gal or below by the end of 2012 by improving overall efficiency of conversion technologies (EERE 2009 b ). Several authors have attempted to estimate cost of cellulosic ethanol produced through different conversion technologies. Few such studies are discussed below. Hydrolysis -based Technologies Shleser (1994) compared the cost of ethanol produced using seven integrated hydrolysis -based convers ion technologies. Results of their study are summarized in Table 2 3. It becomes clear from Table 2 3 that the production cost of ethanol falls as the scale of the ethanol mill increases. Also, the total production cost of the ethanol is directly related t o the cost of biomass feedstock. It was found that among all the hydrolysis -based conversion technologies, the production cost of ethanol was highest for the concentrated acid hydrolysis, neutralization, and fermentation technology and lowest for simultane ous saccharification and fermentation technology. Recently, Huang et al. (2009) stated that for an ethanol mill based on simultaneous saccharification and co -fermentation technology, the ethanol production cost decreases with increasing plant sizes in the range of 1, 1 00 dry tons /day to 4, 4 00 dry tons /day. It was also found that the
39 production cost of ethanol from hybrid poplar increases if the plant size is more than 4, 4 00 dry tons /day as feedstock costs rise faster than non-feedstock costs. Sassner et al. (2008) have analyzed the cost effectiveness of three cellulosic feedstocks (namely salix, corn stover, and spruce) and concluded that conversion technology used for ethanol production has more important implications for the cost effectiveness of a conversi on process than the type of feedstock used. So and Brown (1999) found that the production cost of ethanol from a 25 million gallon/year ethanol plant was $1.57/gal for fast pyrolysis integrated with a fermentation step, $1.28/gal for simultaneous saccharif ication and fermentation, and $1.35/gal for dilute sulfuric acid hydrolysis and fermentation conversion technologies. Wooley et al. (1999) have found that to minimize the production cost of ethanol produced using corn stover as a feedstock and co -current dilute acid prehydrolysis and enzymatic h ydrolysis as a technology emphasis should be on increasing the conversion efficiencies of hemicelluloses and cellulose to fermentable sugars. Hamelinck et al. (2005) echoed similar thoughts They analyzed four technologies and three scenarios and found that commercial production of cellulosic ethanol was feasible with an increase in sugar conversion efficiencies. Aden et al. (2002) also found that the total cost of ethanol production almost becomes flat i.e., $1.3/gal when plant size crosses a threshold val ue of about 6 ,60 0 metric tons of corn stover/day. They used co -current dilute acid prehydrolysis with simultaneous saccharification (enzymatic) and co -fermentation conversion technology for their analysis. Recently, Aden (2008) for a 55 million gallons/year ethanol production facility found that the total selling price of ethanol is about $2.43/gallon when simultaneous
40 saccharification and co -fermentation technique is used for ethanol production. It was also noted that the selling price has shown continuous declining trends since 2001. Feedstock costs were found to be about 40% of the total selling price of ethanol. Leistritz et al. (2006) analyzed the production cost of ethanol (using enzymatic hydrolysis conversion technology) from wheat straw in North Dakota and estimated the production cost of produced ethanol to be $1.56/gal. Feedstock costs have been found to be significant in determining the final cost of the ethanol especially when the conversion technology costs are falling at a faster pace (Bohlman n 2006). Thermo chemical Technologies There is no commercial scale plant using thermo-chemical conversion, so production costs can only be estimated. Phillips (2007) modeled cellulosic ethanol production through gasification technology and catalytic conversion of syngas to ethanol. The minimum selling price was found to be $1.07/gal based on the anticipated and achievable technology parameters by 2012. Tembo et al. (2003) noted that the breakeven cost for the ethanol produced using thermo-chemical -fermentation technology will be about $0.76/gal. Recently, Piccolo and Bezzo (2009) have estimated that the production cost of ethanol produced using gasification-fermentation based technology will be higher than that of the enzymatic hydrolysis technology. Wei et al. (2009) have found that the cost of ethanol produced using gasification-catalytic conversion technology will be lower than the cost of ethanol produced using hydrolysis fermentation as processing time is lowest in the former technology. The literature review on unit production cost of ethanol clearly reveals that the unit cost of ethanol production has fallen in recent years due to technological advancements and it is expected that the cost of producing ethanol from cellulosic feedstocks will soon
41 beco me comparable to the starch-based ethanol. It was also observed that the scale of operations has an impact on the production cost of ethanol and optimum size of an ethanol mill should be close to 4, 4 00 dry tons /day of feedstock consumption. Furthermore, th e type of feedstock does not appear to be significant in determining the production cost of ethanol compared to the conversion technology. It can be inferred that the future production cost of ethanol will be lowest for gasification-catalytic conversion followed by hydrolysis and then the gasification-fermentation technology. There also exists a need for reducing the cost of transporting feedstocks to the ethanol mill, as feedstock costs constitute significant portion of the total production cost of ethanol Emerging Developments The importance given to the commercial viability of ethanol production from cellulosic feedstocks has attracted many scholars. Several new techniques for ensuring commercial production of ethanol from cellulosic feedstocks are being tried at various levels. Some of these emerging technologies are discussed below. Consolidated bioprocessing: In consolidated bioprocessing only one microbial community is employed both for the production of cellulases and fermentation i.e., cellulose pr oduction, cellulose hydrolysis, and fermentation are carried out in a single step (Cardona and Snchez 2007). Lynd et al. (2005) estimated that consolidated bioprocessing has a potential to provide the lowest cost route for biological conversion of cellulo sic biomass to fuels and other products among all the hydrolysis -based processes. Mobile fast pyrolysis: Reducing transportation costs will help in ensuring cost effective production of cellulosic ethanol because cellulosic biomass is a light density
42 soli d and therefore it occupies a large volume resulting in increased transportation costs. One way to overcome this problem is to densify the feedstock at the harvest site and then transport it to the mill site (Li and Liu 2000; Petrolia 2008; Husain et al. 2 002). Recently, establishment of mobile fast pyrolysis plants at the feedstock source for producing pyrolysis oil has been suggested as a potential solution (Badger and Fransham 2006). It was observed that the energy density of pyrolysis oil is about 67 t imes higher than the energy density of green whole tree chips at 45% and 56% moisture content respectively (Czernik and Bridgwater 2004). Pyrolysis oil can be gasified and syngas can be utilized for ethanol production. However, pyrolysis oil is very compl ex and unstable and therefore, there exists a need of advanced research to successfully utilize pyrolysis oil for ethanol production. Integrated ethanol refineries: Increasing energy efficiency of the whole conversion process is the key towards ensuring t he commercial viability of cellulosic ethanol production. Recently, Frederick et al. (2008b) took a holistic approach and analyzed the whole system of producing ethanol from loblolly pine and using the residual biomass as a fuel for a combined heat and pow er plant. They found that ethanol can be produced at $1.29/gal based on a delivered wood cost of $ 58/dry tons at 95% conversion efficiency of carbohydrates in wood to sugars for a 93 million gallons annual plant capacity. Frederick et al. (2008a) also anal yzed the feasibility of ethanol production in a Kraft Paper mill. They found production cost of ethanol to be between $1.33/gal and $2.92/gal depending upon process conditions and selectivity of hemicelluloses removal. Leistritz et al. (2006) have also evaluated the integrated biorefinery concept in North Dakota and found that the production of cellulose
43 nanowhiskers would be an enhancement to the economic performance of a wheat straw to ethanol mill. Biopower: Cellulose used for ethanol production has to c ompete with alternative uses. One such use is power production. Biopower plays a major role in total renewable electricity produced in the nation as about 16% electricity produced from renewable sources comes from biomass alone (EIA 2008 a ). Fuelled by several incentives announced by the government, the interest in using biomass for electricity production has gone up and many entrepreneurs are establishing new cellulosic feedstock based power plants. For example, Gainesville Regional Utilit ies will establish a 100MW power plant in Gainesville, Florida which will use various cellulosic feedstocks for electricity production (GRU 2009) It is possible that the rise in number of such power plants will increase the competition for available cellulosic biomass and can severely affect the availability of cellulosic biomass for ethanol production. Conclusions Production of cellulosic ethanol presents a challenge in terms of development of a commercially viable conversion technology. However, with the rising interest o f policy makers and researchers, it is expected that such a technology will soon be developed. It is more likely that the developed conversion technology will be based on the thermo chemical platform rather than sugar platform as embedded technologies like gasification and catalytic conversion are already quite mature and only small improvements are needed to customize the present technology for ethanol production. Similarly, it is also expected that efforts in reducing the feedstock costs would bring down the total cost of cellulosic ethanol production.
44 In terms of cellulosic ethanol production using different technologies, so far only three technologies have gained broader acceptance among entrepreneurs. This implies that the industry has accepted only handful of technologies to produce cellulosic ethanol and there exists a need to test more technologies to ascertain their commercial viability. Also, attempt should be made towards exploring the efficacy of ethanol production from other feedstocks like woody biomass. This will not only help in diversifying the feedstock portfolio but also add to the energy security of the nation in case of a crop failure due to some natural calamity like pest attach or storms Cellulosic ethanol holds a promise to supplement the growing energy needs of the nation. However, at the same time it is important to strike a harmonious chord with other natural processes that are associated with the production of cellulosic feedstocks. For example, in case of forestry feedstock s, it is important to evaluate the impacts of biomass production on the local biodiversity and on the local watershed. Similarly, in case of agricultural feedstocks, it is important to evaluate the impact on soil and water conservation and nutrient managem ent of soils. Understanding these relationships will help in developing a comprehensive cellulosic feedstock based bioenergy infrastructure in the country.
45 Table 2 1. Distribution range of wood components Wood Components Hardwood (%) Softwood (%) Cellulose 40 50 40 50 Hemicellulose 25 35 25 30 Lignin 20 25 25 35 Pectin 1 2 1 2 Starch Trace Trace Table 2 2. Chemical constituents of loblolly pine (%) Constituents Percentage (%) Cellulose (C6) 43.6 Hemicellulose convertible to sugars Mannan (C6) 10.8 Galactan (C6) 2.2 Xylan (C5) 6.6 Arabinan (C5) 1.6 Acetal 1.1 Uronic anhydride 3.7 Lignin 26.8 Extractives 3.2 Ash 0.4 Total 100.0
46 Table 2 3. Economics of hydrolysis based conversion technologies Conversion Technologies Biomass cost: $50/ton Biomass cost: $108/ton (dry matter) (dry matter) Ethanol ($/gal) Ethanol ($/gal) Ethanol ($/gal) Ethanol ($/gal) 25 Mgal/yr 5 Mgal/yr 25 Mgal/yr 5 Mgal/yr Simultaneous saccharification and fermentation 1.48 1.88 2.11 2.51 Concentrated acid hydrolysis, neutralization and fermentation 2.28 2.76 3.01 3.49 Ammonia disruption hydrolysis and fermentation 1.81 2.4 2.48 3.06 Steam disruption, hydrolysis and fermentation 1.63 2.15 2.25 2.77 Acid disruption and transgenic microorganism fermentation 1.86 2.45 2.5 3.1 Concentrated acid hydrolysis, acid recycle and fermentation 1.86 2.19 2.5 2.83 Acidified acetone extraction, hydrolysis and fermentation 1.7 2.13 2.3 2.72
47 Feedstock Filter Fermentation Distillation Dehydration Hydrolysis Separator Liquid Solids Liquid Separator Solids Boiler Heat Fuel Grade Ethanol Fermentation Pretreatment Air Fuel preparation Gasifier Ash & Char Raw Gas Gas Cleaning Gas Cooling Gasifier Fuel Feedstock Supply Ethanol Conversion C hamber Distillation Dehydration Fuel Grade Figure 21. Cellulosic ethanol production using hydrolysis based technologies Figure 22. Cellulosic ethanol production using gasification technology
48 Figure 23. Installed and under construction cellulosic ethanol production capacity disaggregated by adopted conversion technologies (RFA 2009) 21.1 37.4 2.5 129.75 78 104.9 31.31 0 20 40 60 80 100 120 140 Concentrated acid hydrolysis technology Dilute acid hydrolysis technology Organosolve Gasification, fermentation, and distillation Gasification, catalytic conversion, and distillation Enzymatic hydrolysis Simultaneous saccharification and fermentation million gallons/year
49 CHAPTER 3 LIFE CYCLE A SSESSMENT FOR EVALUATING ENVIRONMENTAL AND EC ONOMIC SUSTAINABILITY OF ET HANOL PRODUCTION FROM FOREST BIOMASS Introduction Incentives provided by the federal government and various other state governments have supported ethanol production in the United States (Solomon et al. 2007). Therefore, the ethanol production has increased from 175 million gallons in 1980 to about 9 billion gallons in 2009 (RFA 2009). Currently, the majority of ethanol produced within the country comes from corn. Using corn for ethanol production raises concerns of food security (Mitchell 2008). As a result the government is encouraging production of ethanol from various cellulosic feedstocks. For example, the Energy Independence and Security Act of 2007 aims to produce about 21 billion gallons of cellulosic ethanol by the year 2022. This act also puts a 15 billion gallon cap on ethanol produced from foodbased crops. Furthermore, recently enacted the Food, Conservation, and Energy Act of 2008 provides a subsidy of $1.01 on every gallon of cellulosic ethanol produced. Forest biomass can play a pivotal role i n meeting the growing demand of various cellulosic feedstocks for ethanol production in the United States. For example, Walsh et al. (2000) found that at a market price of up to $30/dry ton delivered, the total amount of forestry feedstocks available (excl uding wood obtained from urban areas but including forest mill residues, dedicated forestry crops, and forestry residues) would account for approximately 24% of all cellulosic biomass available in the nation. However, the amount of available forestry feeds tocks would increase to 45% of the total cellulosic feedstocks available at a market price of up to $40/dry ton delivered
50 Southern states (Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, Virginia, and West Virginia) are rich in forest resources. Southern forestlands constitute about 30% (about 214 million acres) of total forestlands present in the country but supply the majority of harvested forest biomass at the nationa l level. For example, the total biomass harvested from southern forestlands was about 9.5 billion cubic feet which was about 60% of the total biomass obtained from nations forestlands in the year 1997 (Smith et al. 2001). As Nonindustrial Private Forest (NIPF) landowners own about 70% of the total forestlands in the Southern United States (Smith et al. 2001) ; therefore the role of southern forestlands and NIPF landowners in meeting the future demand for cellulosic feedstocks to produce cellulosic ethanol cannot be ignored. The majority of roundwood production in the southern region is available in four forms softwood sawlogs (30.03%), softwood pulpwood (26.56%), hardwood pulpwood (14.71%), and hardwood sawlogs (11.09%) (Wear et al. 2007). As noticed, about 40% roundwood harvested in the region is in the form of hardwood and softwood pulpwood and therefore, prices of pulpwood are important in ensuring profitability to NIPF landowners. However, a steep decline in the demand for pulpwood was registered in lat e 1990s due to imbalance between supply and demand. The reduction in demand and presence of excess supply in late 1990s led to a sharp fall in the market prices of pulpwood. Reduction in softwood and hardwood pulpwood prices has affected investment in fore st plantations as evident by a recent decline in the annual planting area (Figure 3 1) (Wear et al. 2007).
51 Use of forest biomass for cellulosic ethanol production can help NIPF l andowners by providing them a new market for their small -diameter wood product s like pulpwood and fuelwood (Vogt et al. 2005). This new source of income could improve their financial returns from forestlands. This is especially true when several NIPF landowners (especially who have large land holdings) are interested in financial returns obtained through timber production on their forestlands (Kluender and Walkingstick 2000; Birch 1997). It is expected that the removal of biomass for ethanol production could also provide other ecological benefits as well such as wildfire prevention, wildlife habitat improvement (Mengak and Guynn 2003), and reduction in pest and disease infestations (Covington et al. 1997). In order to be a viable energy source ethanol derived from forest biomass must be environmentally benign and economically compet itive relative to the ethanol produced from other feedstocks like corn, corn stover, and switchgrass. Considering the potential of S outhern forestlands in meeting the national and regional biomass demand for cellulosic ethanol production, this study adopts a case study approach and assesses the environmental and economic suitability of ethanol production from slash pine ( Pinus elliottii Engelm.) biomass. Slash pine is a dominant commercial species of the Southern United States and planted by NIPF landowners for financial benefits. The total area of slash pine plantations under private ownership was about 7 million acres in 2005 (USFS 2005 ) in seven S outhern states. The present study assumes that the biomass for ethanol production will be sourced from an int ensively managed slash pine plantation owned by an NIPF landowner with a rotation age of 25 years. Note that NIPF landowners have
52 considerably augmented intensity of forest plantation management in past few decades especially for pine plantations in the southern region (Siry 2002; Albaugh et al. 2007). Therefore, an assumption of intensive management of slash pine plantation in this study seems logical. It is expected that NIPF landowners will continue to follow the same intensive-management practices in th e near future. The rotation age of 25 years was selected assuming that a landowner will be interested in producing large diameter timber to increase income from their forestland This age also matches with the normal rotation age of slash pine plantation i n the region. The total ethanol produced from an acre of slash pine biomass available in the form of pulpwood and logging residue1 only was selected as a functional unit of the analysis. The selected system boundary for the analysis is outlined in Figure 3-2. A life cycle approach was adopted to assess the Net Energy Ratio (NER) of produced ethanol. Similarly, the total Global Warming Impact (GWI) of produc ed ethanol was also determined A benefit -cost analysis was also undertaken to assess the unit cost of cellulosic ethanol produced at the mill. Additionally, NER and GWI of E85 fuel (85% ethanol and 15% gasoline by volume) which can be produced from the et hanol derived from an acre of requisite slash pine biomass was also calculated The GWI in both the cases was expressed in terms of carbon dioxide equivalent. Furthermore, the total percentage reduction in carbon emission due to the production and consumpt ion of E85 fuel in an automobile was compared with gasoline. Methods This section is divided into 14 components. Details of each component are given below. 1 Diameter at breast height
53 Ethanol yield: The conversion technology selected was two stage dilute sulfuric process (Kadam et al. 2000). Kadam (2000) evaluated the material balance of ethanol produced from sugarcane bagasse using the same conservation technology. The material input and output ratios were suitably adjusted for slash pine biomass to determine ethanol yield from a dr y ton of slash pine biomass with 15% moisture. Ethanol yield was estimated to be 62 gallons/dry ton of biomass. Biomass availability: The total biomass available at the time of harvesting i.e., at the 25th year of plantation was found to be about 198 green tons/acre out of which 36% was available in the form of pulpwood (55.84 green tons) and logging residue (15.77 green tons) (Yin et al. 1998). Therefore, it was estimated that 2,892 gallons of ethanol can be produced from an acre of available biomass. Ener gy and material use at the mill: Production of 2,892 gallons of ethanol at the mill will require different inputs (dry biomass, lime, water, ammonia, diesel, and sulfuric acid) and will produce multiple outputs (ethanol, gypsum, ash, lignin, carbon dioxide and methane). The quantities of different inputs required and outputs produced were estimated using adjusted input output ratios by following Kadam (2000) .2 3 Assuming that 60% of the total water consumed during the production process will be utilized fo r steam production (WSTB 2008), the amount of total heat required to produce steam was calculated. The r emaining 40% of water was assumed to be treated in a wastewater treatment plant. The total electrical energy required to treat wastewater was calculated by multiplying total quantities of treated water with 0.0424 MJ/cubic feet of 2 Inputs (expressed in kg/kg of dry slash pine biomass): Lime (0.013), Water (3.591), Ammonia (0.025), Diesel (0.004), and Sulfuric acid (0.048) 3 Outputs(expressed in kg/kg of dry slash pine biomass) : Ethanol (0.1 9 ), Gypsum (0.03), Ash (0.07), Ligneous Residue (0.6), Methane (0.02), and CO2 (1.31 kg)
54 wastewater (Tchobanoglous et al. 2003). It was assumed that about 0.68 MJ of electrical energy per dry pound of pine biomass will be utilized to convert wood chips into ethanol (Quintero et al. 2008). As lignin obtained at the end of the conversion process has a high calorific value, therefore it is generally utilized to meet the heat and electricity requirement of the mill. Therefore, total heat (the boiler efficiency was assumed as 40%) and electricity (conversion efficiency was taken as 75%) that can be produced from burning lignin was calculated and was subtracted from the total energy requirement of the mill to estimate mills net energy use. Total life of the ethanol mill wa s taken as 15 years and annual capacity of mill was assumed as 50 million gallons. Total construction steel, stainless steel, and concrete used in the ethanol mill were assumed as 1.6, 1.3, and 28 thousand tons, respectively (Hill et al. 2006).4 Total cons truction steel required for the production of required amount of ethanol was calculated by using the formula: allocated construction steel = (2,892 gallons of ethanol total steel used in the ethanol mill)/total production of ethanol in the life time of t he mill.5 Same formula was used for allocating quantities of stainless steel and concrete. Nursery area estimation: Required number of seedlings at the nursery were estimated by assuming a plantation density of 708 seedlings/acre at the plantation site. F urthermore, it was assumed that 15% seedlings will be lost during transportation. Therefore, it was found that about 833 seedlings will be required for the estimated plantation area. For estimating required nursery area, seed density of 28 seeds/square 4 An increase of 10% was assumed from the base values, as forest biomass handling requi res extra efforts. 5 750 million gallons [15 years*50 million gallons of ethanol annually]
55 feet was assumed. The seed density was multiplied with the total number of required seedlings to estimate required nursery area. The value of estimated nursery area was about 1.2E 03 acres.6 Orchard area estimation: The required number of seeds needed to be t ransported to a nursery were ascertained by assuming that 15% of seeds will be damaged during transportation and other 20% will be identified as unviable during collection and processing at orchard. Therefore, total number of seeds were estimated to be 1,4 44. Assuming 100 seeds in a slash pine cone and 65 such cones in a bushel, the total number of bushels were estimated. Assuming a slash pine tree at a seed orchard produces 1.5 bushels/year, total number of required trees were calculated. The total plantat ion density at a seed orchard was found as 48 trees/acre and thus, area needed for required number of seed trees was estimated to be about 2.08E 02 acres. Machinery use: For each practice ( orchard management ; nursery management ; plantation site preparation, planting & forest management ; and harvesting), different activities performed under them were identified by interviewing stakeholders. For example, under harvesting practice five activities were identified i.e., felling and bunching, skidding, delimbing, loading, and chipping of pulpwood and logging residue on the site. Similarly, for plantation site preparation, planting, & forest management practice eight activities were identified i.e., chopping, piling, burning, disking, bedding, herbicide application, planting, and fertilizer application (at year 1 and year 12 of plantation). Next, types of machines used for accomplishing identified activities under a practice were ascertained by interviewing stakeholders. The use (hours/acre) and fuel consumption (gallons/hour) rates of each machine were estimated through interviews. 6 After taking corrections for bedding into account.
56 For example, it was found that machine used for loading harvested pulpwood and logging residue into chipper was TigerCat 234 whose use and fuel consumption rates were about 2 hours/acre and 4 gallons/hour, respectively. Based on these rates, total diesel consumption for each activity was ascertained. For estimating the actual amount of diesel consumed for a practice,7 individual diesel consumption for accomplishing each activity were summe d up and multiplied by the respective area. Company catalogues were referred to estimate other necessary details of identified machines like total weight, total life, etc. For example, the total weight of TigerCat -234 (loader) was about 14 tons with an approximate life of 12,000 hours. The total weight of each machine was divided into mild steel (61.7%), aluminum (6.9%), copper (1.9%), plastics (11.2%), rubber (2.4%), cast iron (11.1%), and glass (2.9%), respectively (Burnham et al. 2006). For activities requiring special agricultural attachments, the weight of attachment was assumed as 10% of the total weight of the machine. The following formula was used for the allocation of material present in various machines: allocated material = (total material present in a machine calculated area) /(total life of machine in hours/use rate). For example, total weight of TigerCat 234 (loader) was distributed as 10.07 tons of mild steel, 1.12 tons of aluminum, 0.31 tons of copper, 1.83 tons of plastics, 0.33 tons of rub ber, 0.39 tons of cast iron, and 0.1 tons of glass. The area needed for harvesting was 1 acre. T otal number of acres for which machine is useful is about 6,000 acres (total life of machine/use rate of machine). Therefore, allocated weight of mild steel pre sent in TigerCat -234 was about 3.36 pound. This way, the allocated material use was calculated for each used machine. The 7 Name of practices: orchard management ; nursery management ; plantation site preparation, planting & forest management ; and harvesting
57 individual material use for each machine was summed to obtain total material allocation for a practice. Material use: For each practic e i.e. orchard management ; nursery management ; and plantation site preparation, planting & forest management the material use was identified by interviewing stakeholders. However, type and quantities of fertilizer use at the plantation site under the pra ctice of plantation site preparation, planting & forest management was determined using Yin et al. (1998). For example, it was found that about 110 pounds/acre of fertilizer (Diammonium phosphate) was used in the first year of slash pine plantation. Simila rly, fertilizer use in the 12th year of plantation was found as about 66 pounds/acre of Nitrogen, 22 pounds/acre of Phosphorus, and 44 pounds/acre of Potassium. Based on the total calculated area for different practices, total quantities of material inputs were determined. Energy use: Apart from energy used in operating different machines (mostly in the form of diesel) other energy inputs associated with practices orchard management and nursery management were also quantified. For example, it was found that certain amount of propane is used in drying seeds at the orchard. Similarly, electricity used at the nursery and orchard to store seedlings and seeds, respectively was also quantified. Transportation: There were three transportation instances within the s elected system boundary. For all instances, it was assumed that a semi -trailer would be used for transporting required cargo. Based on interviews, average distance to be traveled per trip was estimated for each transportation instance. Maximum load capacit y was obtained for each semi trailer. Required number of trips were calculated based on the total quantity of cargo to be transported at various instances. Assuming a hauling rate of
58 50%, the with load and without -load fuel economies of a semi -trailer were taken as 7 miles/gallon and 8 miles/gallon, respectively. Total diesel consumption for a trip was estimated by multiplying distance traveled each side by respective fuel economies. The total diesel consumed was allocated to the transported cargo by using the formula: allocated diesel use = (total diesel consumed*weight of cargo transported)/ (full load capacity of semi -trailer*number of trips required to transport required cargo). Total life of a semi trailer was assumed as 500,000 miles. Total trips that c an be made by a semi trailer in the lifetime were calculated by dividing the total life of a semi -trailer by the total distance traveled in each trip. Based on the percentage distribution of different materials (discussed previously), quantity of each material was calculated by using the following formula for allocation: allocated material use = (total material present in a semi trailer weight of cargo transported)/total quantity of cargo that can be transported in the entire life of a semi -trailer. The c urb weight of a semi -trailer was taken as about 8 tons. Table 3 -1 provides detail of all transportation instances. Allocation of energy and material use: Only 36% of the total biomass was utilized for ethanol production. Therefore, only 36% of all the energy and material inputs starting from the practice of harvesting to orchard management were allocated to ethanol produced. Again, it was found that the mass of produced ethanol was 81.2% of total mass of all the products produced at the mill i.e., ethanol, gypsum, methane.8 Therefore, energy and material use was again allocated based on mass percentage of ethanol produced at the mill. This allocation was done for the steps starting from mill to the practice of orchard management. 8 Lignin was not considered during allocation as it was reused in the mill for producing heat and electricity.
59 Assessing NER: The total energy needed to produce a gallon of diesel and gasoline or embedded energy was found to be 7.75 and 15.83 MJ/gallon, respectively (Furuholt 1995). Similar ly, embodied energy values of other material inputs (e.g., fertilizers, cast steel, herbicides, sulfuric acid, etc.) were also ascertained. Allocated quantities of different input materials were multiplied by their embodied energy values to calculate net embodied energy use associated with the ethanol production. Additionally, the calorific values of different energy products like diesel, gasoline, and prop a ne were found as 155.01, 131.9, and 96.87 MJ/gal, respectively. For estimating direct energy consumption, allocated quantities of diesel, gasoline, and propane were multiplied with their respective calorific values. Allocated energy consumed in the form of electricity was also considered as a part of direct energy. The calorific value of produced ethanol was taken as about 91 MJ/gallon. The total energy content of produced ethanol was divided by the sum of direct and embodied energy consumed to obtain required NER of produced ethanol. Assessing GWI: The total emission of greenhouse gases9 associate d with the production of a unit quantity of an input (or emission factor) was obtained using SimaPra LCA software using TRACI impact factor ( Bare 2003). For example, it was found that about 9 pounds of carbon dioxide equivalent greenhouse gases are emitted for producing a pound of aluminum. Similarly, emissions associated with diesel and gasoline production and consumption were ascertained. Emissions associated with electricity production were also taken into account. Carbon dioxide released during the ethanol production was also considered. Allocated quantities of different inputs were 9 All emissions of GHGs were expressed in carbon dioxide equivalent from here onwards by following Bare et al. (2003).
60 multiplied by their respective emission factors to ascertain the total GWI of produced ethanol. It was found that electricity produced at the mill was in surplus and methane produced can displace natural gas production. Therefore, emissions associated with the displaced electricity from the grid and natural gas production were subtracted from the calculated GWI of the produced ethanol to estimate the net GWI. To compare the G WI impact of produced ethanol with gasoline, it was assumed that the produced ethanol will be utilized to manufacture E85 fuel which will be further utilized in running an automobile for 150,000 miles. It was found that 3,402 gallons of E85 fuel can be pro duced from 2,892 gallons of ethanol after adding about 510 gallons of gasoline. Energy use and emissions associated with two additional transportation steps ( transportation of ethanol from mill to mixing plant and transportation of E85 fuel from mixing plant to the fuel pump ) were taken into account (Table 32). Similarly, energy and emissions associated with mixed gasoline were also considered.10 Data from NREL (1999) was used to ascertain the total quantities of E85 fuel and gasoline consumed to run an aut omobile for 150,000 miles. Required quantities of E85 fuel (9,146.34 gallons) and gasoline (6,437.77 gallons) were estimated based on fuel economies of 16.4 and 23.3 miles/gallon, respectively. Total emission of greenhouse gases associated with the product ion of required quantities of E85 fuel and gasoline were ascertained. Using Table 33 emissions associated with the combustion of E85 fuel and gasoline in an automobile were obtained. The net GWI of E85 fuel was obtained by summing the GWI related with E8 5 fuel production and consumption, respectively. The calculated net GWI of the ethanol produced was converted to carbon 10 The total energy required to produce a gallon of gasoline was 15.83 MJ. The total emission of greenhouse gases to produce a gallon of gasoline was about 2.33 pounds.
61 equivalent. Similar steps were undertaken to calculate net GWI of gasoline in carbon equivalent. It is to be noted that total produced ethanol was derived from forest biomass which sequesters atmospheric carbon during photosynthesis. Therefore, the net allocated value of sequestered carbon was subtracted from the carbon equivalent greenhouse gas emissions associated with the production of required E85 fuel. At the same time, use of lignin in the mill as a source of heat energy displaces emissions from coal. Therefore, net saving in carbon emission due to coal displacement was also subtracted from the previously calculated carbon equivalent greenhouse gas emission value of produced E85 fuel. Furthermore, biomass used for producing ethanol was sourced from a forestland where carbon is sequestered not only in the aboveground biomass but in the soil as well. It was found that about 49.28 tons/ac re of soil organic matter is available in a slash pine plantation at the age of 25 years (Gholz and Fisher 1982). Therefore, the carbon stored in soil was subtracted from the calculated value of GWI (carbon equivalent) to ascertain the net GWI of the produced E85 fuel. Unit cost of production: The annual costs for feedstock, fuel, water, chemicals, and disposal were calculated based on the amounts of each input required to meet the annual plant capacity. Delivered feedstock costs included stumpage value to an NIPF landowner, harvesting, chipping, transportation, and profit to a logger. The value of gypsum produced was taken as $30/ton. Similarly, the value of methane was assumed as $3.59 per million Btu (EIA 2009l). All costs and benefits were scaled up to the annual capacity of the plant over the 15 year plant life to calculate the net present value of the project (Aden 2002). A real discount rate of 10% was chosen for the analysis. Although
62 the appropriate discount rate will vary within the private sector according to the specific risk taking characteristics of the investor, Short et al. (1995) argue that 10% discount rate should be taken for projects with risks similar to renewable energy investments especially in the absence of statistical data on discoun t rates. The unit cost of ethanol was computed by constraining the net present value to $0.00 by allowing the price of ethanol per gallon to vary. Thus, the break even production cost per unit of ethanol was determined. Sensitivity analysis : To analyze the impact of change in harvest age on relative percentage reduction of greenhouse gases (carbon equivalent) for E85 fuel, a sensitivity analysis was done. The harvesting age was changed from year 10 to year 35 in an interval of 1 year. Results The results ar e reported in five parts. The first part reports NER and GWI of ethanol produced at the mill. The second part reports NER and GWI of E85 fuel available at the fuel pump. In the third part, a comparison of GWI of E85 produced and consumed is made with equiv alent amount of gasoline. In the fourth part the unit production cost of ethanol is reported. The last part details sensitivity analysis. Ethanol production: Total energy use for producing 2,892 gallons of ethanol was found as 82,166 MJ. Total direct energ y use was estimated to be 14,713 MJ. The maximum direct energy was consumed due to diesel consumption (about 99%). Similarly, the embodied energy use related with the consumption of various inputs was estimated to be 67,453 MJ. It was noted that the majori ty of total energy used within the system boundary was in the form of embodied energy (about 82%). Consumption of direct and embodied energy is shown in Figure 3-3 and Figure 3 -4, respectively. As
63 observed, the maximum amount of direct energy is consumed a t the mill due to diesel consumption followed by the transportation of required biomass to the mill. It was found that maximum amount of embodied energy is also used at the mill due to consumption of diesel, construction steel, concrete, construction stain less steel, lime, water, ammonia, and sulfuric acid to produce required quantity of ethanol .11 This was followed by the practice of site preparation, planting, & forest management The NER (total output energy/total input energy) was found to be about 3.2. The total greenhouse gas emission for producing 2,892 gallons of ethanol was found to be 41.28 tons or about 0.314 pounds/MJ of ethanol produced. This value includes greenhouse gas emissions saved due to supply of electricity produced at the mill to the gr id and greenhouse gas emissions displaced due to supply of methane from the mill instead of natural gas supplied from a refinery. It does not include carbon credits generated due to displacement of coal and carbon sequestered in the biomass and soil. It wa s found that about 97% of all the greenhouse gas emissions were produced at the mill only followed by the practice of site preparation, planting, & forest management (about 1.5%). Figure 3 -5 gives further details of GHG emission. Production of E85 fuel: To tal energy use for producing 3,402 gallons of E85 fuel was found as 92,468 MJ. Total direct energy was estimated to be 16,788 MJ. Maximum direct energy was consumed due to diesel consumption (about 99%). Similarly, the embodied energy use related with the consumption of various inputs was estimated to be 75,680 MJ including 8,079 MJ of energy spent on mixing 510 gallons of gasoline with 2,892 gallons of ethanol. Note that the majority of total energy used within the system 11 The total heat energy required to produce steam was not considered as direct energy as l ignin was used to produce required heat. Similarly, electrical energy used in the mill was also not considered as direct energy as electricity produced from lignin was used to meet the total electricity requirement.
64 boundary was in the form of embodi ed energy (about 81%). The consumption of direct and embodied energy is shown in Figure 33 and Figure 34, respectively. As observed, the maximum amount of direct energy is consumed at the mill followed by the transportation of required biomass to the mil l. It was found that maximum amount of embodied energy is used at the mill followed by the energy spent in gasoline mixing. The NER was found to be about 3.35. The total greenhouse gas emission for producing 3,402 gallons of E85 fuel was found as 42 tons o r about 0.272pounds/MJ of E85 produced.12 It was found that about 95% of total greenhouse gas emissions were produced at the mill only followed by the practice of site preparation, planting & forest management (about 1.5%). Figure 3 5 gives further details of the GHG emission. The greenhouse gases emitted due to production of required quantities of E85 fuel and gasoline to run an automobile for 150,000 miles were calculated as 112.64 and 7.51 tons, respectively. The total amount of t ailpipe GHGs emissions were also calculated for E85 fuel and gasoline as 65.8 and 71.13 tons, respectively. These greenhouse gas emissions were added and converted into carbon equivalent. The value in terms of carbon equivalent GWI for E85 and gasoline wer e found to be 48.66 and 21.45 tons, respectively. The net carbon present in the allocated biomass i.e., 14.54 tons to produce 2,892 gallons of ethanol was subtracted from the total carbon equivalent GWI of E85 fuel. Similarly, carbon equivalent of displace d coal after making adjusted for allocation i.e., about 9.11 tons was also subtracted. Furthermore, allocate 12 This value includes greenhouse gas emi ssions saved due to supply of electricity produced at the mill to the grid and greenhouse gas emissions displaced due to supply of methane from the mill instead of natural gas supplied from a refinery. It does not include carbon credits generated due to di splacement of coal and carbon sequestered in the biomass and soil.
65 soil carbon present in estimated plantation area (about 14.45 tons) was also subtracted. Therefore, the overall GWI (carbon equivalent) of E85 fuel was found about 10.44 tons only. The value of GWI ratio (GWI of E85 fuel/ GWI of gasoline) was found to be 0.49 which implies that total GWI of E85 fuel is about 51% less than the GWI of equivalent gasoline. Unit cost of production: The calculated unit co st of ethanol produced at the mill was $1.34/gallon using an average delivered feedstock cost of $30.63/green tons. Based on the lower energy content of ethanol relative to gasoline, the cost of an energy equivalent gallon of ethanol was found to be $2.05/ gallon. Sensitivity analysis : It was found that ethanol production from an acre of land is maximum i.e., 3,825 gallons when harvest occurs a t year 16 The maximum reduction in greenhouse gas emissions (carbon equivalent) was found decreasing with respect to harvesting age (Figure 3 6). It was found that net reduction in GWI impact of E85 fuel with respect to gasoline is dependent on methane captured at the mill and total carbon sequestered in the soil. With respect to harvesting age, the carbon sequestered in the soil goes down and as a result of which the net reduction in GWI of E85 fuel with respect to gasoline also shows a negative slope. Discussions Results indicate that the NER of produced ethanol and E85 fuel is 3.2 and 3.35, respectively. Similarly, the GWI of produced ethanol and E85 fuel is 41.28 and 42 tons, respectively. It was found that GWI of production and consumption of E85 fuel in an automobile is about 51% less than the GWI of equivalent gasoline production and consumption in terms of carb on equivalent. The production cost of ethanol at the mill was found as $2.05/gallon in terms of energy equivalent gasoline.
66 It is to be noted that several other authors have also evaluated the environmental and energetic status of ethanol derived from var ious feedstocks. For example, Hill et al. (2006) found that ethanol derived from corn had a NER of 1.25 and reduces GHG emissions by 12% when compared to gasoline. Similarly, Lavigne and Powers (2007) found that ethanol derived from corn stover had a NER o f about 1.7. Sabrina et al. (2005) found that use of corn stover for ethanol reduces the GWI by 65% when compared to gasoline. For ethanol derived from switchgrass, the value of NER and net reduction in GHG emissions when compared to gasoline was found as 5.4 (Schmer et al. 2008) and 90%, respectively. On comparison, the NER of E85 fuel derived from ethanol derived from slash pine biomass was found higher than the ethanol derived from corn and corn stover. However, the NER of switchgrass was found even high er than the NER of slash pine-based ethanol. The percentage reduction in GWI due to the production and consumption of E85 fuel when compared with gasoline was found higher than corn but lower than other feedstocks like corn stover and switchgrass. The results are compared in Figure 3 7. The calculated unit price of ethanol (energy equivalent gasoline) derived from corn, corn stover, and switchgrass have been reported as $1.74/gallon ($0.46/liter) (USDA 2005), $2.08/gallon (Sheehan et al. 2004), and $2.05/gallon (Pimentel and Pimentel 2008), respectively. This implies that ethanol derived from slash pine biomass is costlier to produce when compared with corn but comparable to ethanol produced using other cellulosic feedstocks. Conclusions Demand for energy and food will increase in the future with the rising population of the country (EIA 2008 b ). Continuous reliance on imported crude oil for meeting growing
67 energy needs will have an adverse impact on the economy as demonstrated by the recent surge in global energy prices. It is generally assumed that the utilization of biomass available on NIPFs can help in achieving goals of energy independence and reduction of greenhouse gas emissions. Therefore, the current study attempts to test the validity of this assumpt ion by adopting a detailed life -cycle approach. A cost benefit analysis was also conducted to ascertain the production cost of cellulosic ethanol obtained from slash pine biomass. Suitable assumption s were made to mimic a slash pinebased refinery keeping special nature of feedstock into account. Results suggest that production of ethanol and its use in the form of E85 fuel is beneficial from the environmental perspective. However, research efforts are needed to develop suitable conversion technol ogies so as to reduce the cost of produced ethanol. T he environmental performance of current conversion technologies like enzymatic hydrolysis or gasificationbased catalytic conversion should also be tested to sure that the use of cellulosic ethanol to replace gasoline is a solution to the problem of GHG emissions The ecological impacts of intensely -managed slash pine plantations and subsequent utilization of biomass for ethanol production were not analyzed in this study. It is expected that future resear ch will fill this critical information gap.
68 Table 3 1. Details of transportation steps Table 3 2. Details of additional transportation steps Table 3 3. Tail pipe exhaust of gases from an automobile E85 fuel Gasoline fuel CO (carbon monoxide) 1.48 g/Mile 1.4 g/Mile NOx (nitrogen oxides) 0.12 g/Mile 0.13 g/Mile CO 2 (carbon dioxide) 396.4 g/Mile 428.9 g/Mile CO 2 equivalent 398.72 g/Mile 431.1 g/Mile Transportation steps Code Type Distance Travelled (miles) Fuel Economy (miles/gallon) Total life (miles) Maximum Load (tons) With load Without load With load Without load Transportation of harvested biomass to mill TR_MILL Semi -truck 40 40 7 8 500,000 25 Transportation of seedlings to plantation site TR_SITE Semi -truck 50 50 7 8 500,000 25 Transportation of seeds to nursery from orchard TR_NSY Semi -truck 50 50 7 8 500,000 25 Transportation steps Code Type Distance Travelled (miles) Fuel Economy (miles/gallon) Total life (miles) Maximum Load (gallons) With load Without load With load Without load Transportation of E85 from mixing plant to fuel pump TR_FUEL Tank trucks 75 75 7 8 500,000 8,000 Transportation of ethanol from mill to mixing plant TR_MIX Tank trucks 50 50 7 8 500,000 8,000
69 Figure 3 1. Year wise planted area (million acres) in the southern region 0.5 1 1.5 2 2.5 3 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 million acres Years Total Plantations Industry Plantations NIPF Plantations
70 Production of ethanol at mill Transportation of harvested biomass to mill Plantation site preparation, planting, & forest management Transportation of seedlings to plantation site Nursery Management Transportation of seeds to nursery from orchard Orchard Management Harvesting Figure 32 System boundary for the analysis
71 Figure 33 Direct energy use for the production of ethanol and E85 fuel 0.00 0.00 4780.33 3864.74 2181.23 1964.53 0.85 53.75 0.00 31.61 0.00 1324.39 750.48 4780.33 3864.74 2181.23 1964.53 0.85 53.75 0.00 31.61 0.00 0 1000 2000 3000 4000 5000 6000 MJ Ethanol Production E85 production
72 Figure 3-4 Indirect energy use for the production of ethanol and E85 fuel 0.00 0.00 65144.28 245.25 209.48 1666.62 0.05 35.45 0.01 59.64 0.00 94.74 53.69 65144.28 245.25 209.48 1666.62 0.05 35.45 0.01 59.64 8078.85 0 10000 20000 30000 40000 50000 60000 70000 MJ Ethanol Production E85 production
73 Figure 35 GHG emissions (carbon dioxide equivalent) due to production of ethanol and E85 fuel 0.00 0.00 39.95 0.33 0.19 0.63 0.00 0.01 0.00 0.02 0.00 0.11 0.06 39.95 0.33 0.19 0.63 0.00 0.01 0.00 0.02 0.60 0 5 10 15 20 25 30 35 40 45 tons Ethanol Production E85 production
74 Figure 36. Results of the sensitivity analysis 0 20 40 60 80 100 120 140 160 180 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Reduction in GHG emissions (carbon eq.) wrt to gasoline Age of Plantation Reduction in GHG emission wrt to gasoline (%)
75 Figure 37 Comparison of different feedstocks 1.25 1.7 5.4 3.35 12% 65% 90% 51% 0 10 20 30 40 50 60 70 80 90 100 0 1 2 3 4 5 6 Corn Corn Stover Switchgrass Slash pine (E85 production) NER GWI Reduction (%)
76 CHAPTER 4 IMPACT OF EMERGING V OLUNTARY CARBON AND BIOENERGY MARKETS ON NON-INDUSTRIAL PRIVATE F OREST LANDOWNERS PR OFITABILITY Introduction Forests play an impor tant role in maintaining global climate balance by sequestering atmospheric carbon and storing it in different components like biomass, soils, etc. (Sullivan 2008). Additionally, the wood obtained from sustainable forestlands can be utilized for producing various energy products. These wood based energy products are not only carbon neutral but can substitute for fossil -based fuels resulting in reduced emission of greenhouse gases. Encouraged by the potential role of forests and forestry products in mitigati ng global warming, several initiatives have been pursued by various international institutions, national governments, and individuals to promote either forest based carbon sequestration or expedite forest biomass utilization to produce various energy products. The United States is a leading player in utilizing forestry as a tool for reducing emission of greenhouse gases. A voluntary but legally binding market that is based on the principles of cap and-trade (Colby 2000) has already evolved in the United St ates. This market, facilitated by the Chicago Climate Exchange (CCX), promotes carbon sequestration on forestlands by providing payments to forest landowners for the net carbon sequestered. The United States Congress also passed the Energy Independence and Security Act of 2007 that aims to produce 21 billion gallons of cellulosic ethanol by 2022. Forest biomass is expected to play a major role in meeting the total demand for feedstock for cellulosic ethanol production in the country because large quantities of forest biomass are available from the nations forestlands at a reasonable price (Perlack et al. 2005).
77 Emerging voluntary carbon and bioenergy markets are expected to have a significant impact on the profitability of a forest landowner. Thus, this study attempts to determine the changes in the profitability of a S outhern NonIndustrial Private Forest (NIPF) landowner due to the additional income provided by emerging carbon and bioenergy markets. The impact of additional income on the optimal rotation a ge of plantations is also analyzed. An acre of intensely managed slash pine ( Pinus elliottii) was selected as a reference species. Slash pine is a commercial forest species that is extensively planted by NIPF landowners in the Southern United States. It is estimated that in 2005, NIPF landowners owned about 7 million acres of slash pine plantations in the Southern United States (USFS 2005). An NIPF land located in the southern region of the United States was selected for this study as southern timberlands a ccount for approximately 64% of the national roundwood harvest (Sun and Zhang 2006) and NIPF landowners own about 70% of timberlands in the Southern United States i.e., about 140 million acres (Smith et al. 2001). Therefore, it is expected that southern NI PF landowners and their forests will play a critical role in meeting the nationwide demand for traditional forestry products (i.e., pulpwood, chip -n -saw, and sawtimber) and cellulosic feedstocks for future bioenergy production. Similarly, the high producti vity of S outhern timberlands makes them more attractive for carbon sequestration projects when compared to timberlands located elsewhere in the country. Furthermore, the demand for traditional forestry products in the southern region has also recently decl ined. Changes in domestic consumption patterns, declining exports, increasing imports, and the depreciation or closure of older processing facilities are a few of the factors that are responsible for the
78 decline (Wear et al. 2007). Consequently, prices of some forestry products have fallen or have become stagnant resulting in financial losses to regional NIPF landowners. It is quite likely that unsatisfactory returns from forestlands might cause NIPF landowners to sell their forestlands to some alternative land uses. Such land transformations can have severe consequences on future timber supplies and ecosystem services. Therefore, the assessment of emerging voluntary carbon and bioenergy markets in providing financial security to southern NIPF landowners is critical within the context of changing land uses. This study is organized into s even sections. The next section provides detail of CCX guidelines for carbon payments The third section discusses the possible role of forest biomass in meeting cellulosic f eedstock demand for bioenergy development and states the assumptions of study Analyzed scenarios are also defined. In the fourth section, the literature on the carbon sequestration potential of forests in the Southern United States the role of carbon and bioenergy payments in determining the optimum rotation age and profitability, and total emissions from different silvicultural practices are briefly discussed. Gaps in the literature are also identified. The fifth section discusses the methodology adopted to ascertain optimum harvest age and profitability of an acre of slash pine plantation by incorporating conditions of CCX for carbon payments and payments by the bioenergy industry to a forest landowner for logging residue supply. Results of the study are presented in the sixth section. The final section discusses the results and presents the conclusions.
79 CCX Guidelines Members of the CCX make a legally binding emission reduction commitment and are allocated annual emission allowanc es in accordance with their emission baseline and the CCX emission reduction schedule.1 Members who reduce their emissions beyond their targets have surplus allowances to sell or bank. Those members who do not meet the emissions targets must comply by purc hasing CCX Carbon Financial Instrument (CFI) contracts (a CFI contract is equal to 100 metric tons of carbon dioxide equivalent) (CCX 2009a).2 Currently, the market price of a CFI contract is about $10 or $0.10 per metric ton equivalent (CCX 2009b). In addition to the CCX members, entities and individuals operating in the forestry sector can participate in the CCX by registering offsets. Such entities may join the CCX as offset providers (an owner of an offset project that registers and sells offsets dire ctly on the exchange) or offset aggregators (an entity that serves as the administrative representative for multiple offset generating projects on behalf of multiple project owners). Before offsets from a forestry project are registered on the CCX, the project undergoes a standardized registration, verificatio n, and crediting procedure (CCX 2009c). Three major categories of forestry projects are eligible for earning carbon offsets on the CCX afforestation, longlived wood products, and managed forest projec ts. The focus of this study is on managed forest projects, therefore, only this category will be discussed hereafter. 1 In Phase I (20032006), members are committed to reduce emissions a minimum of 1% per year, for a total reduction of 4% below baseline. In Phase II (2007 2010), CCX members commit to a reduction schedule that requires year 2010 emission reductions of 6% below baseline at minimum. 2 Carbon dioxide equivalency is a quantity that describes, for a given mixture and amount of greenhouse gas, the amount of carbon dioxide that would have the same global warming potential, when measured over a specified timescale (generally, 100 years).
80 Under the category of managed forest projects, the carbon accumulated in the living aboveground biomass (i.e., stem wood, stem bark, branches) and the living underground biomass (coarse root) is considered for carbon offsets. The annual net carbon accumulated is calculated by subtracting total emissions incurred during completion of different silvicultural practices (if any) plus net leakages caused by some catastrophic events (if any) from the total carbon accumulated in the living biomass (aboveground plus underground) in a year. The total annual offsets produced are based on the net carbon sequestered every year. Project owners and ag gregators may earn forestry offsets for managed forest projects during 2003-2010. However, if the CCX is extended after 2010 then enrolled managed forest projects can continue to earn offsets provided the project owner expresses his or her intent of contin uation with the CCX and continues to follow sustainable forestry practices. These practices must meet the standards established by organizations like the FSC (Forest Stewardship Council), the SFI (Sustainable Forestry Initiative), or the ATFS (American Tree Farm System) and must be certified by an independent certification agency. Forestry Feedstocks Perlack et al. (2005) estimated that about 368 million dry tons of forestlandderived biomass can be utilized for bioenergy development in the nation which is 2.5 times greater than the current consumption. This study also found that logging and other residues, fuel treatments, and fuelwood can alone contribute about 47% of total estimated biomass available from forestlands and other 53% can come from urban wood residues, wood processing residues, and pulping liquor. Similarly, Walsh et al. (2000) found that at a market price below $30/dry ton delivered, the total amount of
81 forestry feedstocks available (excluding wood obtained from urban areas but including forest mill residues, dedicated forestry crops, and forestry residues) would account for approximately 24% of all cellulosic biomass available in the nation. However, the amount of available forestry feedstocks would increase to 45% of the total cellulosic feedstocks available at a market price up to $40/dry ton delivered. These studies clearly show that forest biomass can play a significant role in meeting the overall feedstock demand for bioenergy development. It is hypothesized that the payments for the net carbon sequestered in forest biomass and utilization of forest biomass for bioenergy production will improve the profitability of NIPF landowners by providing extra income. It is also hypothesized that such payments will influence the optimum rotation age of plantations. Therefore, six different scenarios (Table 4 -1) have been analyzed to assess the impacts of payments on profitability and optimum economic rotation age. The justification of each scenario is also explained in Table 4 -1. The assumptions of t he study are: CCX will continue after the end of Phase II (i.e., 2010); landowners will continue their affiliation with the CCX and will manage their forestlands based on the principles of sustainable forest management; no catastrophic events will occur; l andowners will belong to the category of offset provider; NIPF landowners will use the ATFS regime for certifying their forestry practices; and only logging residue 3 obtained from forestland will be used for bioenergy production. The last assumption does not allow the use of any other type of forest product (e.g., sawtimber, chipn -saw, or pulpwood) as a feedstock for bioenergy development. This assumption was made to address concerns of the established forest industries and, therefore, to present a more r ealistic scenario. 3 Diameter at breast height 4 and to a merchantable diameter 2 outside bark.
82 Note that the guidelines of the CCX for calculating net carbon sequestered also take into account net carbon dioxide emitted while undertaking various silvicultural practices. Therefore, a life-cycle analysis (LCA) is integrated with a f orest growth and yield model for estimating net carbon sequestered in an acre of intensely managed slash pine plantation. Literature Review Many studies have quantified the carbon stored in southern forestlands. For example, Brown and Schroeder (1999) esti mated that eastern forests accumulated about 174 million tons of carbon annually between late 1980s and early 1990s, without accounting for carbon sequestered in roots and soils. Clark et al. (2004) studied carbon dynamics of slash pine plantations and fou nd that the annual net ecosystem exchange of carbon dioxide was 0.26 lbs C /ft2/yr and 0.18 lbs C/ft2/yr at the clearcut and 0.11 lbs C/ft2/yr and 0.12 lbs C/ft2/yr at mid -rotation age in 1998 and 1999, respectively. Binford et al. (2006) have found that c arbon was accumulated at an average rate of about 2.5 ton/acre annually in the forests of southeastern states. Their results were based on four 15 15 km samples of forested areas in the southeastern coastal plain region from 1975 to 2001. I t was found th at about 130 million tons of carbon is sequestered every year in forest biomass and soils present in the southeast and south central U nited States (Han et al. 2007). The authors also stated that regional forests can act as terrestrial sinks and can capture about 23% o f total regional GHG emissions. All these studies suggest that southern forestlands play an important role in carbon sequestration. Several studie s have examined the impact of carbon payments on the optimal rotation age of forest plantations and associated profitability to an NIPF landowner. For
83 example, Van Kooten et al. (1995) initially analyzed the role of carbon taxes and subsidies on the rotati on age and found that the inclusion of external benefits from carbon uptake results in marginally longer optimal rotations. Alavalapati et al. (2002) have compared the profitability of longleaf ( Pinus palustris ) and slash pine timber production after incor porating payments for carbon sequestration, habitat for the endangered red-cockhead woodpecker, and other amenity benefits. They found that internalizing benefits from carbon sequestration and red-cockaded woodpecker habitat improvement alone are not enoug h for landowners to switch from slash pine to longleaf. Additional payments of $6.4$13.2/ac re /yr will be needed to make longleaf production financially competitive with slash pine. Stainback and Alavalapati (2002) have analyzed the role of carbon payments in determining the profitability to an NIPF landowner managing slash pine plantations. The authors concluded that carbon payments will increase the optimal rotation age, land expectation value (LEV), and the supply of sequestered carbon. In addition, they found that with the rise in value of forestland due to the presence of carbon payments, more land could be devoted to forestry as opposed to other land uses such as agriculture and urban development. In another study, Stainback and Alavalapati (2004) cons idered risk while estimating the role of carbon payments on the LEVs of southern forestlands. They found that risk decreases LEV and optimal rotation age of a slash pine stand at a greater rate when higher carbon prices are present as the presence of risk leads to more pulpwood production and less sawtimber production. This ultimately results in a reduction of the net carbon sequestered by trees. Further, Stainback and Alavalapati (2005) have suggested that a carbon market would induce plantation owners to increase their management intensity
84 which may in turn have significant impacts on the amount of net carbon sequestered. None of the above studies took into account the emissions produced from various silvicultural practices while calculating LEVs and the optimal rotation age. Vogt et al. (2005) focused on using forest biomass for bioenergy development as a potential for providing extra income to forest landowners. Recently, Nesbit et al. (2009) evaluated the role of bioenergy markets on the profitability to an NIPF landowner in the Southern United States. They found that that the bioenergy market opportunity increased land values by $28.56 $37.50/ac re It was also found that the LEV was maximized when only residues were used for bioenergy production. Few s tudies have quantified the total amount of emissions generated due to use of fuel, material, and machinery while performing various silvicultural practices. Markewitz (2006) has used the LCA approach to conclude that emissions of about 1.32 tons C/ac re ove r a 25 year rotation in an intensively managed loblolly pine ( Pinus taeda) plantation in the southeastern United States would largely offset the expected gains in soil carbon or in pulp products due to added productivity. It was also concluded that the growth, harvest, and utilization of saw logs as timber provides a clear benefit for carbon sequestration relative to the carbon emissions incurred from intense silvicultural activities. Similarly, Johnson et al. (2005) evaluated the life cycle inventory (LCI) of different compounds which are released into the atmosphere due to the use of fuel in thinning and harvesting operations for forests located in southeastern and pacific northwest regions of the United States The authors found that transportation-related activities and the use of diesel fuel produced by far the largest contribution to emission outputs. However, fertilizer use also contributed to much of the change in emissions as
85 acreage shifted to higher intensity management alternatives. White et al. ( 2005) also evaluated the LCI of round wood production in northern Wisconsin. The authors noted that carbon budgets for the harvesting process of the Chequamegon Nicolet National Forest, the Northern Highland American Legion State Forest, and non-industrial private forests that participated in the managed forest laws of Wisconsin were 0.04, 0.07 and 0.04 tons C/ac re /yr respectively. It was also found that forests act as a net carbon sink even after including emissions from fossil fuels. The above literature review suggests information is required on the simultaneous impact of emerging voluntary carbon and bioenergy markets on the profitability of an NIPF landowner and the optimum rotation age of their plantation. This study attempts to fulfill the research g ap by developing a case study for an acre of intensely managed slash pine plantation in the Southern United States In particular, the study uses LCA to ascertain the total GHGs produced (carbon dioxide equivalent) from various silvicultural practices unde rtaken to produce slash pine biomass. Then, the LCA and slash pine growth and yield modeling results are integrated with a modified Faustmann formula to assess the impacts of carbon and bioenergy payments on the rotation age and profitability. Methods This section has three parts. The first provides details about the methodology adopted for ascertaining the carbon balance of a slash pine plantation. The second part describes necessary steps involved in estimating total emissions of GHGs (carbon dioxide equi valent) from different silvicultural practices. Finally, the third part explains the methodology for deriving the optimal rotation age and profitability. In view of the
86 uncertainty associated with the cost of registering carbon credits at CCX and carbon pr ices, a sensitivity analysis was also conducted for all the scenarios. An acre of forestland with no initial carbon stock was defined as the unit of analysis. A growth and yield model was used for ascertaining total biomass availability from an acre of sla sh pine plantation (Yin et al. 1998). Using the approach of Pienaar and Rheney (1993), the growth and yield model was suitably modified to accommodate thinning at the 12th year of the plantation.4 The CO2FIX model was adopted for ascertaining the carbon balance of the plantation (Schelhaas et al. 2004). However, out of the four components of the CO2FIX model, only biomass and soils were considered in this study and the remaining two (round wood products and bioenergy) were excluded because the CCX guidelines for managed forest projects do not consider round wood products and bioenergy for calculating net carbon sequestered. The model used for ascertaining the carbon balance in the plantation is expl ained in Figure 4 1. Different parameters that were used at various steps are also shown in Figure 4 -1 .5 Stem biomass was parameterized using the growth and yield model. To parameterize foliage, branch, and root biomass with respect to stem biomass, suitable ratios were calculated from Gholz and Fisher (1982). A turnover rate for each biomass component was derived to estimate the availability of annual dead biomass. Annual turnover rates for foliage, branches, and roots were assumed to be 0.5, 0.082, and 0. 014 respectively (Cropper and Gholz 1993). The turnover rate for stem biomass was assumed equal to 4 Site index was set at 70 feet at year 25 and the number of seedlings at the second year of the plantation was 700/acre. 5 Exposure rate (ER) is defined as the percentage of dead biomass available for decomposition every year.
87 the natural mortality rate of trees in a plantation. The CO2FIX model uses the YASOO model for ascertaining fluxes and stocks of carbon in the soil. The YASO O model consists of three litter compartments describing the physical fractionation of litter and five compartments describing microbial decomposition and humification proce sses in the soil (Masera et al. 2003). The percentage distribution of extractive, c ellulose, and lignin present in the three litter compartments -coarse woody residues, nonwoody residues, and fine woody residues were obtained from Howard (1973). All other required parameters of the study were adapted from Liski et al. (2005) as exact val ues of parameters for slash pine were not available. However, the largest values (from a given range) were considered in the analysis to account for the relatively warm climate of the Southern United States For calculating carbon present in live biomass, the carbon percentage was assumed to be 50% by weight ( ) Silvicultural practices (and activities under each practice) were identified based on Yin et al. (1998). Details of identified silvicultural practices and activities under each practice are site pr eparation (chopping, piling, burning, disking, bedding, herbicide application, and planting), cultural operations (fertilization, twice), mechanized thinning6 (felling & bunching, skidding, delimbing, and loading), and mechanized harvesting (felling & bunc hing, skidding, delimbing, and loading). For determining the total material and machinery usage in identified silvicultural practices, personal interviews were conducted with four loggers and five landowners. Based on usage rates of different machines (hr/ ac re ) and their diesel consumption (gallons/ac re ), total diesel consumption was estimated for each activity. Net emissions associated with the manufacturing of 6 While analyzing the scenario of no thinning, GHG emissions (CO2 equivalent) from the mechanized thinning were not included.
88 each material used (diesel, gasoline, herbicides, and fertilizers) were calculated from the Fran klin Database available with SimaPro 7.1 Multiuser. Similarly, total emissions related with the combustion of gasoline and diesel were also derived. For assessing total quantities of carbon dioxide equivalent emissions for each forestry practice, the TRACI database was used (Bare 2003). Faustmann (1995) derived the formula for ascertaining the LEV of a forest in perpetuity. The Faustmann equations is as follows: ( ) = ( ) [Eq. 4 1] where LEV(t) is the land expectation value or the present value of profit from growing an infinite number of rotations of trees, r is the real discount rate, C is the cost of establishment, and t is the Faustmann rotation that maximizes the sustained annual net timber revenues from using the land in forestry. The variable, val(t) which is the annual net timber revenue, is derived as: ( ) = ( ) + ( ) + ( ) + ( ) [Eq. 4 -2] where prices and quantities of saw timber, chip-n -saw, pulpwood, and logging residue are presented by pst, Qst; pcs, Qcs; ppw, Qpw, and plr, Qlr, respectively. Following Hartman (1976) and Nguyen (1979), the net present value of non-timber benefits, pvk(t) over the length of the rotation are represented by: ( ) = ( ) [ Eq. 4 3] where k(t) is a function of nontimber benefits derived from the stand before harvest. These benefits can include water quality, wildlife habitat or recreational values. The modified Faustmann model with timber and non-timber benefits becomes: ( ) = ( ) + ( ) [Eq. 4 4]
89 The total carbon present in the live biomass, forest floor litter, compounds (extractive, cellulose, lignin) and total carbon lost due to decay of compounds from an acre of slash pine plantation were estimated using a modified CO2FIX model. The present value of carbon benefits of a growing stand was then represented by: ( ) = ( ) [Eq. 4 -5] where pc is the price of carbon and v(t) is the derivative of the volume function. The decay rate of compounds was presented as: = [Eq. 4 6] where Qcompounds is the total quantity of carbon that decays and is lost into the atmosphere. Similarly, the present value of other amenities (e.g., hunting leases) can also be represented by: ( ) = [Eq. 4 7] where ph is the price of other amenities. The resulting model is represented as: ( ) = ( ) + ( ) + ( ) [Eq. 4 8] where D equals C plus the penalty due to carbon released at the time of execution of different practices, annual taxes, annual management costs, annual certification costs, and the costs incurred due to cultural practices.7 Table 4 2 summarizes the cost estimates of different forestry operations and Table 4 3 gives details of the prices of different revenue streams used in this study. The real discount rate was fixed at 5%. Results The growth of various forestry products with and wi thout thinning is shown in Figure 4 2. As shown, the growth of sawtimber is higher in a thinned plantation when 7 All these values have been discounted back to year zero for analysis purposes.
90 compared with an unthinned slash pine plantation. However, growth of other timber products (i.e., chipn -saw, pulpwood, and logging residue ) dec reases with thinning. Annually sequestered carbon for different scenarios without considering emissions is shown in Figure 4 3. As expected, carbon stored at the system level is always higher than carbon stored in the live biomass for both the scenarios of with and without thinning. It is also evident that carbon stored at the system level in a thinned plantation (after thinning) is smaller than the carbon stored at the system level in the corresponding unthinned plantation. The same result was also observed for the carbon stored in the live biomass. Total emissions from an acre of slash pine plantation in terms of carbon dioxide equivalent from different silvicultural practices are reported in Table 4 -4 In case of an unthinned plantation, the use of ferti lizers was found to be significant by accounting for 41.6% of total emissions, followed by emissions incurred at the time of harvesting. However, for a thinned plantation the emissions produced from thinning and harvesting were greater than the emissions produced from fertilizer use. The LEVs and corresponding optimal rotation ages for identified scenarios are summarized in Figure 44 When compared to the base scenarios of A and B, the LEV for scenarios C and D were higher by 49% and 50%, respectively. Si milarly, the LEVs for scenarios E and F were higher by 51% and 52% when compared to the base scenarios of A and B, respectively. The optimal rotation age for all the scenarios was 22 years. Results of the sensitivity analysis in which carbon prices were varied from $0.1 to $7.4 (the highest price on CCX) in an interval of $1 are reported in Table 4 5 Similarly,
91 the registration price of carbon credits at CCX was also varied from $25 to $125 in an interval of $25 and the results are shown in Table 4 5 Furt hermore, prices of logging residue are varied from $1 to $10 in an interval of $1.8 The sensitivity analysis proves that with an increase in carbon and logging residue prices, the LEVs will increase considerably. Similarly, the variation in registration co st affects the LEVs. However, even when the registration cost of carbon credits at CCX were high, the LEVs were higher than the LEVs of the base scenarios (i.e., scenarios A and B). However, it is advisable for small landowners to participate in an offset aggregator project to further reduce the cost of registration and certification. Discussions Results indicate an increase in profits to an NIPF landowner even at a low prices of carbon ($0.1/metric ton of carbon sequestered) and logging residue ($5/ton). I t was also found that in presence of logging residue and carbon payments, the thinning of plantations will yield more benefits to private landowners especially when prices of carbon are low. Several authors have identified that thinning increases benefits to landowners. For example, Dwivedi et al. (2009) analyzed the role of carbon payments on the optimal rotation age and profitability of slash pine plantations and found that thinning increases the net profitability. Susaeta et al. (2009) analyzed the role of bioenergy payments and found that thinning increases landowners profitability. Therefore, the results of the study were found congruent with the results of other studies. 8 For each sensitivity analyses, the other factors were not changed and only changes in the LEV and optimal rotation age of scenarios E and F were recorded
92 No change is the optimal rotation age was observed. This implies that in the pres ence of carbon penalties for emissions related to various silvicultural operations and decomposition, it is not necessary that the optimal rotation age will change. This also implies that there will be no change in timber supplies even in the presence of c arbon and logging residue payments. We found that even at a high cost of registering carbon credits at CCX, profitability was higher when compared to the base case scenarios. This implies that introduction of carbon and logging residue payments will be he lpful to NIPF landowners. It was also found that at higher carbon prices, the LEV of an unthinned plantation was more than the LEV of a thinned plantation. This was primarily due to emissions of GHGs at the time of undertaking thinning and also due to larg e accumulation of carbon in an unthinned plantation when compared to a thinned plantation. Conclusions This study analyzed the impact of emerging voluntary carbon and bioenergy markets on the optimal rotation age of a forest plantation and the profitabilit y to an NIPF landowner. An acre of intensely managed slash pine plantation was selected as a unit of analysis. The CCX guidelines of carbon payments under the managed forest projects category were simulated along with payments for logging residue produced on forestland for assessing the aforementioned impacts. LCA and an updated version of a forest growth and yield model were integrated with a modified Faustmann model to achieve this task. The LCA approach was used to obtain the total emissions associated w ith different silvicultural practices. Similarly, an updated version of a forest growth and yield model was used for ascertaining the carbon balance inside an acre of slash pine plantation. This model mimics the growth of the biomass in branches, roots, and foliage
93 with respect to growth in stem biomass. Also, the model was found helpful in ascertaining soil carbon. Payments from emerging carbon and bioenergy markets will increase profitability of NIPF landowners and thus can help in preventing unwanted land use change, ensuring sustainable timber supplies, and maintaining the ecological integrity of the region. With significant numbers of NIPF landowners in the region, carbon markets have considerable potential to sequester large amounts of carbon from the atmosphere at a minimum cost. Similarly, use of forest biomass -based energy products can help in reducing GHG emissions to the atmosphere. Based on this potential, it would be beneficial to adopt a suitable policy to expand the role of forestry in climate change mitigation. The role of other mechanisms as provided by CCX (i.e., afforestation and long lived wood products) should also be analyzed to assess their efficacy in promoting benefits to NIPF landowners and mitigating the negative impacts of GHG emiss ions. The present study did not consider risk of natural calamities (e.g., insect attacks, hurricanes etc.) in the analysis. Furthermore, because silvicultural practices vary considerably among NIPF landowners results obtained in the study can only be applicable given the assumptions adopted here. Results will likely vary with adopted silvicultural practices and ecological characteristics of forestland.
94 Table 4 1. Scenarios for the study Scenario A S cenario B Scenario C Scenario D Scenario E Scenario F Intensive management Yes Yes Yes Yes Yes Yes Thinning Yes No Yes No Yes No Payment for logging residue No No Yes Yes Yes Yes Emissions No No Yes Yes Yes Yes Payments for carbon sequestration No No Live Live System System Intensive management: NIPF landowners will prefer fast growth of slash pine plantation as carbon and bioenergy payments are dependent on net biomass growth. As a result, intensive management of plantations is considered in all the six scenarios. With and without thinning: Majority of NIPF landowners are not thinning their forestlands due to low prices of traditional forest products. Therefore, understanding the role of payments under both the scenarios of with and without thinning becomes even more critical. Thinning is assumed to be done at the 12 th year of plantation. Payment for logging residue : Scenarios of with and without logging residue payments are considered to assess the impacts on profitability and optimal rotation age. Emissions: GHG emissions associated with energy use on forest site are calculated using life cycle analysis. Then, scenarios of with and without emission penalties are tested to assess the impact on profitability and optimal rotation age. Payments for carbon sequestered: Guidelines of CCX only consider payments for that carbon which is sequestered in the live biomass (underground and aboveground). However, carbon stored in foliage, litter, and decaying matter is significant too. Moreover, carbon is also lost to the atmosphere due to decomposition of dead biomass. Therefore, two scenarios of carbon payment i.e., live (stem with bark, branches, and coarse root) and system (live, foliage, litter, soil, decomposition into carbon dioxide) are considered.
95 Table 4 2 Details of cost streams Activities Frequency Cost estimates ($/acre) Site Preparation: Chopping Year 0 50 Piling Year 0 48 Burning Year 0 60 Disking Year 0 100 Bedding Year 0 105 Herbicides Year 0 60 Planting Year 0 90 Cultural operations: Initial Fertilization Year 1 80 Second Fertilization Year 12 100 Certification: Registration in CCX Year 0 100 Registration for certification scheme Year 0 20 Annual inspection Annual 10 Other: Taxes Annual 7 Management Annual 5 Cost data: M. Simpson, (personal communication, 2008) Certification costs: C. Myers, (personal communication, 2009) Table 4 3 Details of revenue streams (TMS 2009) Table 4 4 Emissions (lbs/ac re carbon dioxide equivalent) from silvicultural practices Silvicultural Practices Emissions Unthinned plantation Thinned plantation Site preparation 1,014 1,104 Thinning 1,436 Harvesting 1,795 1,615.5** Cultural operations 2004 2004 Total 4,813 6,249 *Emissions related to thinning were taken as 80% of harvesting. **Emission related to harvesting in a thinned plantation was taken as 90% of emissions related to harvesting in an unthinned plantation. Price of Carbon $0.1/metric ton Timber products S awtimber $28.55/ton C hip n saw $14.99/ton P ulpwood $8.97/ton Logging residues $5/ton Amenities $20/year/ac
96 Table 4 5 Sensitivity analysis for Scenario E and Scenario F Unthinned Plantation Thinned Plantation Prices LEV ($/acre) ORA (years) LEV ($/acre) ORA (years) Carbon prices at CCX ($/tonne) 0.1 176 22 213 22 1.1 355 22 358 22 2.1 537 21 505 21 3.1 718 21 652 21 4.1 899 21 799 21 5.1 1,081 21 946 21 6.1 1,262 21 1,093 21 7.1 1,446 20 1,240 21 7.4 1,501 20 1,284 21 Registration prices at CCX ($/acre) 25 289 21 327 21 50 251 22 288 21 75 214 22 250 22 100 176 22 213 22 125 139 22 175 22 Logging residue prices ($/ton) 1 142 22 167 22 2 151 22 179 22 3 159 22 190 22 4 168 22 201 22 5 176 22 213 22 6 185 22 224 22 7 193 22 236 21 8 202 21 249 21 9 211 21 261 21 10 221 21 274 21
97 Carbon dioxide Extractive DECOMPOSITION RATES Cellulose Lignin Humus 1 Humus 2 DECOMPOSITION RATES (P) EMISSIVE RATES (1 P) Extractive, Cellulose, Lignin LITTER Total Biomass Growth Foliage Biomass Branch Biomass Root Biomass Stem Biomass Stem Biomass Dead Branch Biomass Dead Foliage Biomass Dead Fine Root Biomass Dead Coarse Root Biomass Dead Coarse Woody Biomass Non Woody Biomass Fine Woody Biomass TURNOVER RATES LIVE BIOMASS REGROUPING EXPOSURE RATES (ER) Figure 4 1. Model used for assessing carbon balance in slash pine plantations
98 Figure 4 2 Biomass distribution in different products for a thinned and an unthinned slash pine plantation 0 10 20 30 40 50 60 70 80 90 100 110 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 100 tons/acre Year WT_ST WT_CS WT_PW WT_FW WoT_ST WoT_CS WoT_PW WoT_FW WT = With Thinning WoT = Without Thinning ST = Saw timber CS = Chip N Saw PW = Pulp wood FW = Fuel wood
99 Figure 4 3. Carbon distribution for a thinned and an unthinned slash pine plantation 0 10 20 30 40 50 60 70 801 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49tons/acreYears Carbon_Sys_WT Carbon_Sys_WoT Carbon_Live_WT Carbon_Live_WoT WT = With Thinning WoT = Without Thinning Live = Carbon present in live components (stem + leaves + branches + root) Sys = Carbon present in the system (Live + dead matter + decomposed matter emissions)
100 Figure 44. Calculated LEVs of different scenarios $141.25 $115.84 $210.69 $173.98 $212.82 $176.24 Scenario A Scenario B Scenario C Scenario D Scenario E Scenario F
101 CHAPTER 5 STAKEHOLDERS PERCEPTIONS ON FOREST BIOMASS-BASED BIOENERGY DEVELOPMENT IN THE SOU T H ERN UNITED STATES Introduction The Energy Independence and Security Act of 2007 aim s to produce 21 billion gallons of cellulosic biofuel by 2022 in the United States. Additionally, the recently enacted the Food, Conservation, and Energy Act of 2008 provides a subsidy of $1.01 on every gallon of cellulosic ethanol. Furthermore, many state and privately owned companies are making investments to produce electricity and ethanol by using cellulosic biomass as a feedstock. For example, the Gainesville Regional Uti lit ies is building a 100 MW power plant in Gainesville, Florida that will primarily utilize cellulosic biomass for electricity production (GRU 2009) Similarly, Range Fuels is building an ethanol plant in Soperton, Georgia to produce 100 million gallons of ethanol per year using various cellulosic feedstocks (Range Fuels 2009) It is expected that the g rowing interest in utilizing cellulosic feedstocks to meet present and future energy needs will create a high demand for the resource. Forestlands occupy ab out 747 million acres of the total geographic area of the United States (Smith et al. 2001) and could contribute significantly to the supply of cellulosic biomass for bioenergy development. Walsh et al. (2000) found that at a market price below $30/dry ton delivered, the total amount of forestry feedstocks available (excluding wood obtained from urban areas but including forest mill residues, dedicated forestry crops, and forestry residues) w ould account for approximately 24% of all cellulosic biomass available in the nation. However, the amount of available forestry feedstocks would increase to 45% of the total cellulosic feedstocks available at a market price of up to $40/dry ton delivered. The role of timberlands present in the Southern
102 United States (Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, Virginia, and West Virginia) in meeting the national forest biomass demand is critical. Southern timberlands occupy approximately 140 million acres and supply the majority of all harvested forest biomass in the country. For example, in 1997 the southern forestlands supplied about 64% of the total forest biomass harvested in the country i.e., 9.5 billion cubic feet (Smith et al. 2001). At present, forest landowners in the Southern United States are facing economic hardships as the prices of various forestry products (pulpwood, chipn -saw, and sawwood) have either g one down or became stagnant (Wear et al. 2007). Consequently, the majority of forest landowners are not undertaking prescribed sustainable forestry practices (like thinning) on their lands. As a result, southern timberlands have accumulated extra biomass i n the recent years. This unutilized biomass is vulnerable to pest attack and wildfire (Laughlin 2005). It is feared that a large scale pest attack or wildfire would severely jeopardize the entire economy and environment of the region. Utilizing extra fore st biomass present on region s forestlands for bioenergy development might provide economic incentives to forest landowners by creating a new market for their unutilized biomass. This will also help in meeting the total regional demand of energy in a sustainable manner, as the use of biomass -based energy products is largely carbon neutral. The Table 51 gives detail about the forest biomass characteristics, availability, and energy values for southern timberlands (Alavalapati et al. 2009). As deduced from T able 5-1, biomass from the southern forestlands can play a
103 significant role in bioenergy production at the regional level. It might also help in maintaining the ecological integrity of forestlands by reducing the likelihood of pest attacks and wildfires. Anticipating future potential and positive impacts several state governments of the region have already announced various incentives to encourage forest biomass -based bioenergy development. For example, in Georgia, three agencies (Georgia Environmental Fa cilities Authority, Georgia Forestry Commission, and Georgia Department of Economic Development) have been grouped under the umbrella of Georgias Bioenergy Partnership to promote forest biomass -based bioenergy development. Similarly, in the state of Flori da several grants have been made by Florida Energy & Climate Commission to promote biofuel production from forestry feedstocks available within the state. However, utilization of forest biomass for bioenergy development also raises concerns. For example, i t is expected that the bioenergy markets could intensify the current regimes of forest management, leading to severe consequences for biodiversity and soil moisture conservation (Spangenberg 2008). There are also concerns about the absence of viable commer cial technologies for biomass conversion to various energy products (Phillips et al. 2007). Similarly, doubts are raised about the environmental impacts of bioenergy related to land use changes (Searchinger et al. 2008). Furthermore, it is feared that the absence of a specific policy on forest biomass -based bioenergy development at the regional or state level might cause failure of the whole initiative. Already, the consumption of alternative fuels in the southern region is showing a declining trend. For ex ample, the total alternative fuel consumed in southern states
104 was about 98 million gasoline equivalent gallons in 2003 but it fell to about 83 million gasoline equivalent gallons in 2006 (EIA 2006). Suitable policy environment is needed for sustaining the growth of any sector in the economy. Policy makers always need critical information for formulating effective and enabling policies which can help in integrated development of any sector. An example of critical information is the perceptions of different stakeholder groups associated with cellulosic feedstock based bioenergy development within the region. Incorporating perceptions of such stakeholder groups is essential for ensuring successful formulation and implementation of any policy (Gregory and Wellm an 2001) including a bioenergy policy which focuses on forest biomass -based bioenergy development in the region. Understanding perceptions of such stakeholders will help in identifying those issues which should be addressed in a future bioenergy policy. Ad dressing such issues will help in reducing conflicts and improving cooperation among different stakeholder groups (Simmons and Lovegrove 2005). This study uses SWOT -AHP (Strength, Weaknesses, Opportunities, and Threats Analytical Hierarchical Process) framework to identify differences among perceptions of four bioenergy stakeholder groups (non-governmental organizations [NGOs], government, industry, and academia) regarding forest biomass -based bioenergy development in the Southern United S tates The sc ope of this study is regional, but the findings of the study may be applicable for other regions which are facing similar situations. Moreover, if needed the same methodology can be replicated in each state to assess perceptions of local stakeholder groups.
105 This chapter is divided into five sections. The first section introduces the study and provides the rationale for the study T he second section summarizes the literature and identifies existing literature gap. T he third section detail s the SWOT AHP framework for evaluating stakeholders perception T he fourth section presents the results; and finally, the fifth section discusses the results and concludes the study. Literature Review Kurttila et al. (2000) developed a technique of combin ing SWOT analysis with AHP. This combination yielded analytically determined priorities for all the factors included in the SWOT analysis and made them commensurable to each other. The authors tested their methodology to assess the feasibility of making a transition from a timber -dominant forest management regime to a certified forest management regime in Finland. They concluded that the SWOT -AHP technique is helpful as making pairwise comparisons forces the decision maker to consider the weights of different factors and to analyze the situation more precisely and in more depth. Masozera et al. (2006) used the SWOT -AHP technique to analyze perception of three stakeholders (communities, a government agency, and an environmental organization) regarding the sui tability of a community based management approach at Nyungwe Forest Reserve in Rwanda. They found that the representatives of local communities perceived that the positive aspects of community based management outweighed its negative aspects. However, repr esentatives of a government agency and an environmental organization anticipated that weaknesses associated with the community based management approach outweighed its strengths. Pesonen et al. (2001a) used the SWOT -AHP technique in connection with strateg ic planning of natural resource management at the Finnish Forest and Park
1 06 Service (FFPS). In this case, SWOT analysis was carried out separately by three business units (Forestry, Recreation, and Nature Protection) at the FFPS and with respect to three dim ensions of sustainability (economic, social, and ecological) and for four different strategies (forestry, recreation, protection, and basic). The priorities of the SWOT factors and the suitability of alternate strategies subject to various SWOT factors wer e estimated by pairwise comparisons. The authors determined that each strategy was consistent with the basic principles of ecological sustainability. In the protection strategy, however, environmental aspects had an especially high priority. Pesonen et al. (2001b) also applied the SWOT -AHP technique to assess the decision of a Finnish forest enterprise to invest in North America. They found that consistency ratios (explained in the next section) were greater than 10% in all the cases except one. The authors concluded that these inconsistencies were due to the presence of a large number of SWOT factors resulting in difficult interpretations of each factors importance. They recommended that the number of factors within the four SWOT categories should be limit ed to 10 to ensure consistent responses. It lessens overlapping and user carelessness. Ananda and Herath (2003) used AHP alone to incorporate stakeholders preferences into regional forest planning in Australia. They also did a sensitivity analysis to sho w how the alternatives were prioritized with respect to each objective as well as the overall objective. They concluded that AHP helps the decisionmaking process to become more transparent by simplifying preference structures and eliminating hidden ambigu ities. Rauch (2007) used SWOT analysis to examine strategy formulations in forest owner cooperatives in Austria. The authors concluded that SWOT analysis
107 provides a good overview of the issues and makes it easy to pinpoint important problem areas. A few st udies have analyzed the possible strengths, weaknesses, opportunities, and threats associated with the use of biomass for bioenergy production. Roos et al. (1999) categorized the following factors as critical to bioenergy development integration with other economic activities, scale effects on bioenergy markets, competition in bioenergy markets, competition with other businesses, national policy, local policy, and local opinion. In another study, Varela et al. (1999) identified several factors under differe nt SWOT categories associated with the use of biomass for electricity production in Spain. For example, they identified the low level of atmospheric emissions compared with other alternatives as strength and the need for a more specialized workforce as weakness. Similarly, the authors categorized topographical limitations as threat and increased energy security as an opportunity. Ulmer et al. (2004) assessed the acceptability of ethanol blended gasoline in Alabama. They determined that most respondents believed that ethanol produced from biomass is beneficial to the environment and that the reduction in foreign oil dependency was the greatest potential benefit of using ethanol -blended gasoline. Sims (2003) also identified several barriers and opportunities r elated to bioenergy development. The chances of ecological degradation and land diversion were identified as barriers whereas economic benefits such as rural development were highlighted as opportunities. The literature review clearly shows two trends. Fir st, no study exists that quantifies stakeholders perceptions regarding forest biomass based bioenergy development.
108 Second, the geographical focus for most of the existing studies is on Europe. It is expected that the present study will help in filling thi s critical knowledge gap. SWOT -AHP Framework SWOT analysis is a strategic management tool that helps to identify internal strengths and weaknesses and external opportunities and threats for any organization, project, or individual (Houben et al. 1999; Dyson 2004). Many applications of SWOT analysis exist in strategic management (Weihrich 1982; Nair and Prasad 2004; Sharma and Bhatia 1996). The combination of a brainstorming session and SWOT analysis with a heterogeneous group of stakeholders constitutes a useful strategy to rank different factors and identify relevant issues (Mollenhorst and deBoer 2004). However, one of the main limitations of SWOT analysis is that the importance of each factor in decision making cannot be measured quantitatively and th erefore, it becomes difficult to assess the potential of a factor to influence strategic decisions. When SWOT analysis is combined with AHP, importance of each factor present in the SWOT categories can be quantified and the effect of a single factor on the overall decision can be assessed (Saaty and Vargas 2001). AHP enables the stakeholders to assign a relative priority to each factor through pairwise comparison. From these pairwise comparisons, the relative priority value of each factor within each SWOT group is computed using the eigen value method as explained below. Following Shrestha et al. (2004), information derived from the pairwise comparisons can be represented as a reciprocal matrix of weights where the assigned relative weight enters into the ma trix as an element aij and reciprocal of the entry (1/aij) goes to the opposite side of the main diagonal,
109 [Eq. 5 -1] w here rows indicate ratios of weights of each factor with respect to all others. In the matrix, w hen i=j, then aij =1. When we multiply matrix A by the transpose of the vector of weights w we get the resulting vector nw Aw = n w [Eq. 5 2] w here w = (w1,w2,,wn)T and n is the number of rows or columns. The above equation can also be written as: (A n I ) w = 0 [Eq. 5 3] w here n is also the largest eigen value, max, or trace of matrix A and I is the identity matrix of size n. Saaty (1977) demonstrated that max = n is a necessary and sufficient condition for consistency. Inconsistency may arise when max deviates from n due to varying responses in the pairwise comparisons. Therefore, the matrix A should be tested for consistency using the formula, CI = ( max n)/(n1) [Eq. 5 4] CR = CI / RI [Eq. 5 5] where CI is the consistency index, RI is a random index generated for a random matrix of order n, and CR is the consistency ratio (Saaty 1993; Mawapanga and Debertin 1996). The general rule is that CR should be Homogeneity of factors within each group, a smaller number of factors in each group, and a better understanding of the decision problem improves the CI SWOT -AHP analysis can be conducted even with a small sample of individuals or groups who are
110 knowledgeable of the issue under investigation. In this way, SWOT -AHP differs from other statistical analyses which require large samples to derive confidence intervals around the means and draw infe rences for a relevant population. Methods A contact list of professionals working on different aspects of bioenergy development in the S outhern U nited States was prepared. This list was based on personal contacts, publications, projects awarded by different government and private agencies, state government agencies with a focus on bioenergy development, feedback from previously identified stakeholders, and comprehensive internet search. To identify the factors in each SWOT category, an openended online que stionnaire was administered to all the identified stakeholders. Questionnaire was electronically sent to 258 experts in 14 southern states and responses from 37 experts were obtained. Responses were analyzed and suitable factors under each SWOT category were extracted (Table 5-2). Based on the factors identified in each SWOT category, a second questionnaire was prepared. A brief explanation of each factor was included in the questionnaire to ensure a common understanding among the respondents. This question naire contained pairwise comparisons of each factor in a particular SWOT category against all other factors in the same category. The respondents were asked to evaluate both the factors present in a pairwise comparison and then mark the order of importance of one factor over another based on their own understanding. For example, in the pairwise comparison of promotes energy security vs. reduces greenhouse gas emissions under SWOT category of strength, the respondent would first decide whi ch factor is more important and then assign a weight ranging from one to seven (1, 3, 5, and 7) indicating
111 the relative magnitude of its importance against another factor. The data from pairwise comparisons were used to estimate a priority value for each f actor within each SWOT category. Figure 5-1 represents a section of the used questionnaire. While administrating the questionnaire, the numbers were replaced by more familiar scale of comparison (1= Equal, 3 = Moderate, 5 = Strong, and 7 = Very Strong) to facilitate respondents. This was done based on the findings of a focus group discussion in which participants suggested to reduce the number of comparison scales from five to four and use more familiar comparison scales (in words) rather than numbers. The questionnaire was administered on August 5, 2008 at the Southern Bioenergy Roadmap Stakeholder Meeting convened by the Southeast Agriculture & Forestry Energy Resources Alliance at Memphis, Tennessee. Respondents were classified into four stakehold er groups namely NGOs, government, industry, and academia. Individual responses in each stakeholder group were combined to obtain the geometric mean for that group (Saaty 2001). The number of complete responses for NGOs, government, industry, and academia stakeholder groups were 7, 8, 10, and 10 respectively. The combined responses for each stakeholder group were analyzed using the SWOT -AHP technique. The factor with the highest priority score was identified in each SWOT category and for each stakeholder gr oup. Separate questionnaires for each stakeholder group containing pairwise comparisons between the factors that got highest priority scores in each SWOT category were developed. This was done to estimate the overall priority of different factors with resp ect to each other. These questionnaires were administered at the Biomass South 2008 Conference on September 21, 2008 at Raleigh, North Carolina. Stakeholder group-specific questionnaires were also sent
112 electronically to the participants of the previous conference. The number of complete responses for NGOs, government, industry, and academia stakeholder groups were 6, 5, 7, and 7 respectively. Responses were analyzed using the aforementioned procedure, and the final priority rankings for the factors under ea ch SWOT category for all stakeholder groups were obtained. Results A summary of the factors and their overall priority scores is shown in Table 53. Factors with the highest priority score for each SWOT category in a particular stakeholde r group are highl ighted in bold and the highest overall priority score is also highlighted. For all comparisons, the CR was always less than 0.1. Following Masozera et al. (2006), the scores of strength and opportunity factors can be interpreted as positives while the scor es of weakness and threat factors as negatives for the forest biomass based bioenergy development in the S outhern United States For example, the overall priority scores for strength and opportunities were 0.4643 and 0.3132 for academia stakeholder group. The sum of priority scores was 0.7775 implying that about 78 % of the overall perception about the use of forest biomass for bioenergy development is positive for the academic stakeholder group. The overall priority score of other stakeholder group can be i nterpreted in the same manner. The relative importance of each factor within each SWOT category provides valuable insight for decision making. For example, a priority value of 0.2663 for promotes energy security for academic stakeholder group indicates that this factor accounts for about 27 % of overall strength. The overall perception of each stakeholder group is discussed in detail below.
113 NGOs : The overall perception of NGO stakeholder group regarding the use of forest biomass for bioenergy development in the S outhern U nited States was mostly determined by opportunities (40%). In particular, NGOs preferred two factors within the opportunity category i.e., rural development (37%) and presence of government support/commitment (20%). These two factors explained 57% of NGOs perception regarding opportunities (Figure 5 -2). Weaknesses were the second most significant in determining overall perception (27%). The two factors which got highest priorities within the weakness category were the conversion technologies are still under trial (30%) and the uncertain future of bioenergy markets (26%). Strengths were the third most significant determinant (20%). This stakeholder group gave the highest priority under the strength category to sufficient forest biomass availabi lity (34%) followed by promotes energy security (29%). Threats were not given much importance by this stakeholder group as threats explained only 13% of the overall perception. In the threat category, the highest priority was given to competes with convent ional forest products industry (25%) followed by possible damages to forest ecology (23%). Government : The strengths were the significant determinants of government representatives overall perception (37%). The two strength factors namely less or no compe tition with food production (28%) and promotes energy security (27%) were given highest rankings. The remaining SWOT categories i.e. weaknesses, opportunities, and threats were given almost equal weights by government representatives i.e. 20%, 24%, and 1 9%, respectively (Figure 5 -3). The highest priorit y factors within the weakness category were conversion technologies are still under trial (30%) and still not competitive with coal, gasoline, and cornbased ethanol (25%). Similarly, emerging
114 future carbon markets (26%) and rural development (24%) got highest priorities under the opportunities category. Among threats, the highest priorities were given to competes with conventional forest product industry (24%) and cheap imports from other countries (21%). I ndustry : Strengths (35%) and weaknesses (32%) dominated the overall perception of the industry stakeholder group (Figure 54). The promotes energy security (35%) was the highest priority factor in the strength category while the highest priority was given to conversion technologies are still under trial under the weakness category (43%). Opportunities determined 24% of overall perception. The two highest priorities were given to rural development (27%) and presence of government support/commitment (26%) und er opportunities category. Threats explained only 9% of the total perception associated with the forest biomass -based bioenergy development. Two factors namely competes with conventional forest product products industry (26%) and cheap imports from other c ountries (21%) were emphasized within the category of threats. Academia : The strengths category was the most significant determinant of the overall perception (46%). Interestingly, all factors in the strength category were prioritized nearly equally (Figu re 5 5 ) with the highest weight given to promotes energy security (27%). After strengths the next highlighted category was opportunities (31%). The highest priorities in this category were rural development (33%) and presence of government support/commitme nt (24%). Both weaknesses (10%) and threats (12%) contributed marginally towards the overall perception. The conversion technologies are still under trial (34%) and still not competitive with coal, gasoline, and corn based
115 ethanol (26%) were the highest we akness factors. Among threats, competition from other renewable energy sources (28%) and possible damages to forest ecology (27%) were given highest priorities. The results of this study indicate that all four stakeholder groups are in favor of promoting f orest biomass -based bioenergy development in the S outhern U nited States. Results of the study are consistent with the other studies which have tried to evaluate public preferences for green energy. For example, Borchers et al. (2007) used choice models to evaluate willingness -to pay for voluntary participation in green electricity program. They found a positive willingness -to -pay for green electricity market. Roe et al. (2001) using hedonic analysis concluded that green electricity is an important indicator of price premium charged by companies. Discussions On an average, the overall perception for all stakeholder groups was determined by strengths (35%) and opportunities (30%) followed by weaknesses (22%) and threats (13%). Three strength factors were given the highest preference by all stakeholder groups: promotes energy security sufficient forest biomass availability and less or no competition with food production. It was noted that the factor reduces greenhouse gas emissions was not a high priority fac tor for any stakeholder group. Among weaknesses, all four stakeholder groups gave their highest priority to the conversion technologies are still under trial. All stakeholder groups except government gave the highest priority to rural development under the opportunities category. Government representatives gave highest priority to emerging future carbon markets under the same SWOT category. As future carbon markets might provide incentives to both forest biomass producers and industries, carbon markets are expected to give an impetus to forest biomass based
116 bioenergy development. However, deliberations on this issue are still at the policy level; therefore, the preference of government officials for the opportunities provided by future carbon markets seems t o be logical. The two threats which got the highest priorities scores were competition from other renewable energy sources and competes with conventional forest product industry However possible damages to forest ecology was not a significant determinant of the stakeholders perceptions regarding threats. In the S outhern United States almost every state government has its own b est m anagement p ractices for forestry. These practices are stringent regarding the use of chemic als for maintaining proper water quality and the forest landowners compliance with these practices is monitored regularly (Adams 1998). Thus, this factor might have assured all the stakeholder groups that utilizing forest biomass for bioenergy development will not have negative consequences for forest ecology. Another possibility is that the stakeholders were aware of the accumulated biomass in regional forestlands and the hazard that it presents to the forest ecology and local economy. As such, utilization of forest biomass for bioenergy production was thought to be an appropriate step. All the stakeholder groups recognized government support as one among their top preferences within opportunity category, therefore it can be inferred that in the near future bioenergy policy should provide government support for promoting forest biomass based bioenergy development in the region. This becomes even more critical when markets are evolving and are at nascent stage. Similarly, there also exists a need to address impact of the whole initiative on the other sectors of economy especially those sectors which use forest biomass as feedstock like pulp and paper mills. Any future bioenergy policy should define all the sectors clearly for preventing feedstock
117 overlaps. I t was also found that all stakeholder groups were particularly concerned about the unavailability of commercial scale conversion technology It is expected that successful demonstration of existing or future conversion technologies at a commercial scale wi ll spur growth in forest biomass based bioenergy production on its own. Conclusions This study uses SWOT -AHP approach to assess the perceptions of four stakeholder groups regarding forest biomass -based bioenergy development in the S outhern United States The region was selected due to the existence of a large forestry base, the potential role that the region will play in meeting the future national demand for cellulosic biomass, the rising energy needs of the region, and the emphasis of various state gover nments on promoting cellulosic biomass as a sustainable energy source. It can be concluded that all the stakeholder groups have recognized that the S outhern U nited S tates has a great potential of forest biomass based bioenergy development. Therefore, there exists a need to design a suitable policy which can promote such a development in the region by incorporating issues deemed important by various stakeholder groups. It is however to be kept in mind that the results represent aggregated opinions of respondents belonging to one out of four stakeholder groups. Though the CRs were found consistent for each stakeholder group in this study, the author still feel s that there exists a need for incorporating more stakeholder groups (forest landowners, consumers) to obtain a more clear understanding of perceptions for effective policy formulation.
118 Table 5 1. Forest biomass availability and energ y values from southern timberlands State Timberland Area ( million acres ) Live Biomass ( million dry tons ) Roundwood Production ( million ft 3 ) Timber Removals ( million ft 3 ) Logging Residues ( million ft 3 ) Net Annual Growth ( million ft 3 ) Energy Value (Billion Btu) Alabama 22.6 882.4 1,119.1 1,157.3 254.7 1,512.5 181,500 Arkansas 18.5 761.6 707.3 810.3 184.7 1,027.8 123,336 Florida 16.7 529.0 529.9 574.5 119.2 735.0 88,200 Georgia 24.9 1,032.7 1,203.3 1,340.5 329.1 1,927.6 231,312 Kentucky 12.1 621.2 206.1 296.3 107.4 469.8 56,376 Louisiana 14.1 594.7 741.2 857.9 276.1 832.7 99,924 Mississippi 15.1 590.1 165.7 1,093.9 89.0 1,247.2 149,664 Missouri 19.6 812.6 937.3 187.2 326.8 438.5 52,620 North Carolina 18.6 935.4 858.5 1,075.0 211.6 1,458.6 175,032 Oklahoma 5.4 155.4 334.8 138.5 95.7 243.3 29,196 South Carolina 12.9 573.5 601.8 671.5 151.4 1,037.3 124,476 Tennessee 14.0 726.7 338.9 377.5 67.7 801.2 96,144 Virginia 15.7 859.6 534.9 644.3 155.0 956.8 114,816 West Virginia 12.0 820.1 163.7 158.4 100.7 436.3 52,356 Region Total 222. 2 9,895.2 8,442.4 10,041.9 2,469.0 13,124.6 1,574,952
119 Table 5 2. Relevant factors identified in each SWOT category Strengths Weaknesses S1 Promotes Energy security W1 Conversion technologies are still under trial S2 Reduces greenhouse gas emissions W2 Uncertainties related to forest biomass production S3 Less or no competition with food production W3 Still not competitive with coal, gasoline and corn based ethanol S4 Sufficient forest biomass availability W4 Uncertain future of bioenergy markets Opportunities Threats O1 Emerging future carbon markets T1 Competes with conventional forest products industry O2 Presence of government support/commitment T2 Competition from other renewable energy sources O3 Favorable public opinion T3 Possible damages to forest ecology O4 Improves the sustainability of forests T4 Reduction in prices of fossil based energy resources O5 Rural development T5 Cheap imports from other countries
120 Table 5 3. Summary of the priority scores of all SWOT factors and categories SWOT Categories Factor Priority Overall Priority Academia Government NGO Industry Academia Government NGO Industry Strengths 0.4643 0.3671 0.1991 0.3486 S1 0. 2663 0.2704 0.2906 0.3552 0.1236 0.0993 0.0579 0.1238 S2 0.2475 0.2227 0.1292 0.1891 0.1149 0.0817 0.0257 0.0659 S3 0.2461 0.2857 0.2356 0.2116 0.1143 0.1049 0.0469 0.0737 S4 0.2401 0.2212 0.3446 0.2441 0.1115 0.0812 0.0686 0.0851 Weakness 0.1047 0.2003 0.2745 0.3196 W1 0. 3423 0.2974 0.3036 0.4338 0.0359 0.0596 0.0833 0.1386 W2 0.2350 0.2474 0.1917 0.1818 0.0246 0.0496 0.0526 0.0581 W3 0.2575 0.2563 0.2393 0.1958 0.0270 0.0513 0.0657 0.0626 W4 0.1653 0.1989 0.2654 0.1886 0.0173 0.0398 0.0728 0.0603 Opportunities 0.3132 0.2388 0.3976 0.2423 O1 0.0981 0.2612 0.1618 0.1009 0.0307 0.0624 0.0643 0.0245 O2 0.2387 0.1829 0.2004 0.2660 0.0748 0.0437 0.0797 0.0645 O3 0.1459 0.1542 0.1344 0.1770 0.0457 0.0368 0.0534 0.0429 O4 0.1897 0.1595 0.1295 0.1882 0.0594 0.0381 0.0515 0.0456 O5 0.3276 0.2422 0.3740 0.2679 0.1026 0.0578 0.1487 0.0649 Threats 0.1178 0.1939 0.1289 0.0895 T1 0.1552 0.2427 0.2535 0.2574 0.0183 0.0471 0.0327 0.0230 T2 0.2831 0.1675 0.1335 0.1676 0.0333 0.0325 0.0172 0.0150 T3 0.2667 0.1837 0.2357 0.1742 0.0314 0.0356 0.0304 0.0156 T4 0.1423 0.1971 0.2199 0.1881 0.0168 0.0382 0.0283 0.0168 T5 0.1528 0.2089 0.1574 0.2128 0.0180 0.0405 0.0203 0.0190 S1: Promotes energy Security; S2: Reduces greenhouse gases emissions;S3: Less or no competition with food production;S4: Sufficient forest biomass availability;W1: Conversion technologies are still under trial;W2: Uncertainties related to forest biomass production;W3: Still not competitive with coal, gasoline and corn based eth anol; W4: Uncertain future of bioenergy markets;O1: Emerging future carbon markets;O2: Presence of government support/commitment; O3: Favorable public opinion;O4: Improves the sustainability of forests;O5: Rural development; T1: Competes with conventional forest products industry;T2: Competition from other renewable energy sources;T3: Possible damages to forest ecology;T4: Reduction in prices of fossil based energy resources;T5: Cheap imports from other countries
121 Figure 51. Pairwise comparison of factors under strength category
122 Figure 52. Perception map of the NGO stakeholder group S1 S2 S3 S4 W1 W2 W3 W4 O1 O2 O3 O4 O5 T1 T2 T3 T4 T5 0.4 0.3 0.2 0.1 0 0.1 0.2 0.3 0.4 0.3 0.2 0.1 0 0.1 0.2 0.3 Strengths Weakness Opportunities Threats W1: Conversion technologies... W2: Uncertainties related... W3: Still not competitive... W4: Uncertain future... O1: Emerging future carbon... O2: Presence of government... O3: Favorable public... O4: Improves sustainability... O5: Rural development T1: Competes with conventional... T2: Competition from other... T3: Possible damage to... T4: Reduction in prices... T5: Cheap imports... S1: Promotes energy security S2: Reduces greenhouse gases... S3: Less or no competition... S4: Sufficient forest biomass...
123 Figure 53. Perception map of the government stakeholder group S1 S2 S3 S4 W1 W2 W3 W4 O1 O2 O3 O4 O5 T1 T2 T3 T4 T5 0.3 0.2 0.1 0 0.1 0.2 0.3 0.4 0.3 0.2 0.1 0 0.1 0.2 0.3 0.4 Strengths Weakness Opportunities Threats W1: Conversion technologies... W2: Uncertainties related... W3: Still not competitive... W4: Uncertain future... O1: Emerging future carbon... O2: Presence of government... O3: Favorable public... O4: Improves sustainability... O5: Rural development T1: Competes with conventional... T2: Competition from other... T3: Possible damage to... T4: Reduction in prices... T5: Cheap imports... S1: Promotes energy security S2: Reduces greenhouse gases... S3: Less or no competition... S4: Sufficient forest biomass...
124 Figure 54. Perception map of the industry stakeholder group S1 S2 S3 S4 W1 W2 W3 W4 O1 O2 O3 O4 O5 T1 T2 T3 T4 T5 0.3 0.2 0.1 0 0.1 0.2 0.3 0.4 0.4 0.3 0.2 0.1 0 0.1 0.2 0.3 0.4 Strengths Weakness Opportunities Threats W1: Conversion technologies... W2: Uncertainties related... W3: Still not competitive... W4: Uncertain future... O1: Emerging future carbon... O2: Presence of government... O3: Favorable public... O4: Improves sustainability... O5: Rural development T1: Competes with conventional... T2: Competition from other... T3: Possible damage to... T4: Reduction in prices... T5: Cheap imports... S1: Promotes energy security S2: Reduces greenhouse gases... S3: Less or no competition... S4: Sufficient forest biomass...
125 Figure 55. Perception map of the academia stakeholder group S1 S2 S3 S4 W1 W2 W3 W4 O1 O2 O3 O4 O5 T1 T2 T3 T4 T5 0.4 0.3 0.2 0.1 0 0.1 0.2 0.3 0.4 0.5 0.4 0.3 0.2 0.1 0 0.1 0.2 0.3 0.4 0.5 Strengths Weakness Opportunities Threats W1: Conversion technologies... W2: Uncertainties related... W3: Still not competitive... W4: Uncertain future... O1: Emerging future carbon... O2: Presence of government... O3: Favorable public... O4: Improves sustainability... O5: Rural development T1: Competes with conventional... T2: Competition from other... T3: Possible damage to... T4: Reduction in prices... T5: Cheap imports... S1: Promotes energy security S2: Reduces greenhouse gases... S3: Less or no competition... S4: Sufficient forest biomass...
126 CHAPTER 6 SUMMARY AND CONCLUSIONS Introduction Forest biomass available on NonIndustrial Private Forest (NIPF) l ands located in the S outhern United States can play an important role in meeting the scheduled production target of cellulosic ethanol at the national level Therefore, this study took a holistic approach in analyzing various issues related to the whole initiative of producing cellulosic ethanol from f orest biomass Specifically, the present status of existing conversion technologies was reviewed and their performance in terms of unit production cost of ethanol and adoption was ascertained. An attempt was also made to capture the future trajectory of te chnology development. Next, the percentage reduction in greenhouse gas emission was ascertained for ethanol produced from slash pine biomass. The net energy ratio for the ethanol produced at the mill was also calculated. Suitable comparisons of calculated net energy ratio and net reduction in global warming were made with cellulosic and agricultural feedstocks. Next, the impact of emerging voluntary carbon and bioenergy markets on the profitability of NIPF landowner s was ascertained. A case study approach w as adopted and an acre of slash pine plantation was selected as a representative species. The changes in land expectation value and optimal rotation age were recorded for several scenarios of carbon and logging residue payments. This was followed by a stud y which captured perceptions of four different stakeholder groups about the use of forest biomass -based bioenergy development in the Southern region using SWOT -AHP technique.
127 It is expected that the results of this study would enhance our understanding ab out the utilization of forest biomass for cellulosic ethanol production and help in achieving the goals of energy independence and reduction in greenhouse gas emissions Policy Implications The findings of the first chapter clearly reveal that policy makers are interested in promoting use of cellulosic feedstocks for ethanol production. Several acts have been passed in recent years which attempt to facilitate production of cellulosic ethanol in the country. It can be deduced that subsidies, grants, and other incentives provided to corporations and research organizations w ould help in overcoming initial challenges related with cellulosic ethanol production in the country. The findings of the se cond chapter suggest that no commercially viable conversion technology exists for cellulosic ethanol production in the country. Therefore, a need exists to develop a suitable conversion technology through which cost of cellulosic ethanol production becomes comparable to the ethanol obtained from corn. Both public and private sectors are investing a lot in the technology development and it can be expected that such a technology will be developed in coming years. In addition to conversion technology, research is also needed to reduce the transportation cost of the feedstock so that the production cost of the ethanol can be reduced further. It is also expected that the future technology will be based on an integrated industr ial framework in which cellulosic eth anol will be a byproduct of a main product. For example, an integrated paper mill can produce ethanol from the waste generated during the paper manufacturing process. Additionally, more feedstocks need to be tested for accessing their feasibility in ethano l production. This will help in reducing risk s associated with crop failure in case of a natural calamity.
128 T he focus of policy makers should also be on developing suitable guidelines for forest management to ensure integrated development of the region. Thi s becomes especially true when it is expected that the use of forest biomass for bioenergy development might affect existing forest industr y of the region. Also, it might be possible that intensive management of forestlands for producing required biomass f or emerging bioenergy market could lead to several ecological problems like soil degradation, water quality deterioration, etc. In absence of such guidelines, the emerging bioenergy market in the region can cause adverse impacts on the local economy and ec ology. The findings of the third chapter suggest that production of ethanol from the biomass obtained from an intensively managed forestland will help in reducing emissions of greenhouse gases. Findings suggest that the ethanol produced from forest biomass has a high energy ratio when compared to other feedstocks Th ese findings imply that the ethanol production from forest biomass is environmental friendly. However, special precautions are needed to cap ture methane emissions at the mill otherwise the ethanol production from forest biomass will not be able to serve the intended objective of reduction in greenhouse gas emissions.1 This implies that policy makers should emphasize capturing emissions at the mill by making suitable provisions in existing pollution and environmental laws. Additionally, the cost of ethanol production from slash pine biomass and using the two-stage dilute sulfuric acid conversion technology was found to be higher than the cost of ethanol produced from corn. This suggests that more efforts are needed to further reduce the production cost of ethanol. Reduc ing the cost of biomass feedstocks by increasing the energy density and 1 When compared with equivalent amount of carbon dioxide, the global warming impact of methane is about 23 times more than carbon dioxide.
129 improving the hydrolysis efficiency can significantly hel p in reducing the production cost of cellulosic ethanol. The findings of the fourth chapter indicate that emerging voluntary carbon and bioenergy markets will help in increasing the profitability of NIPF landowners to a great extent without any noticeabl e change in forest rotation age. This implies that NIPF landowners will be interested in producing biomass for emerging bioenergy markets even in the presence of voluntary carbon markets. The findings of the fifth chapter suggest that all the major stakeholders are in favor of forest biomass -based bioenergy development in the S outhern region. For example, all stakeholder groups agreed that use of forest biomass for bioenergy development will promote energy security and sufficient forest biomass i s available which can be utilized to produce bioenergy. However, it would be critical to address the weaknesses and threats perceived by these stakeholders in order to scale up forest bioenergy markets in the region. Limitations of the Study Although the present stud y attempted to be relatively comprehensive while analyzing various issues related to the use of forest biomass for bioenergy development in the Southern region of the United States, many limitations of the study remain. I n the second chapter of the study more specific details of some emerging conversion technologies (e.g., biomass fractionation) were not found. Similarly, feedstock details for some upcoming cellulosic ethanol mill were unavailable in an objective manner. In some cases, the conversion technology that will be employed for producing cellulosic ethanol was also not explicitly mentioned
130 In the third chapter, the global warming impact of cellulosic ethanol produced from slash pine biomass was ascertained. The system boundary included all the st eps starting from seed orchard management to the point where produced E85 fuel is consumed in an automobile. For many intermediate steps, the values of energy and material use were approximated by interviewing managers. This might have an effect on obtained result s due to presence of subjectivity in responses. Additionally, other impacts like eco -toxicity, eutrophication, etc. were not ascertained in the study. Similarly, production cost of the ethanol does not include any nonmarket values associated with the existence or aesthetics of the forest It only includes t hose values which were representative of prevailing conditions of Southern pine plantation at the time of study. Production cost is not the only economic factor to consider. Impacts of government incentives such as tax rebates and subsidies should also be evaluated in order to make a fair comparison of economic viability. In the fourth chapter, the carbon model used for assessing soil carbon was parameterized by importing parameters from European studies, as several parameters values were not available for the Southern United States. Similarly, the real price of registering carbon credits at the Chicago Climate Exchange (CCX) was not available. Apart from that, the values of emissions at the time of harvesting and thinning were approximated based on interviews with forest landowners and loggers. This raises small concerns about the validity of calculated emission values. In the fifth chapter, perceptions of only four stakeholder groups (industry, a cademia, government, and nongovernmental organizations) have been analyzed More number of stakeholder groups should have been included to ascertain their
131 perceptions like forest landowners. This would have given more credibility to the overall findings. Future Research It is expected that the production of cellulosic ethanol from forest biomass will have an impact on the existing land cover in the Southern region Similarly, the emergence of forest biomass -based bioenergy industry will have an impact on t he existing forest industry, as both these industries will compete for the same biomass to meet their demand. This study does not quantify these impacts and it is expected that future research work will focus on the same. Additionally, no risk was consider ed while evaluating the economic impact of emerging voluntary carbon and bioenergy markets on an NIPF landowner Assessing impact of risk on the profitability of landowners is essential, as this determine s the willingness of a landowner about participating in bioenergy markets. In case of high risk and low profitability, a landowner can select an alternate but more profitable land use. This might severely affect the whole premise of forest biomass -based bioenergy development in the Southern region. Furthermore, no correlation among SWOT categories was assumed in this study. It might be possible that there exists a strong correlation among various factors present in different SWOT categories. Therefore, the obtained values are not true values. In the future research, a new technique of analytical network process can be used to ascertain the correlation among different SWOT categories for deriving the priorities of different factors.
132 LIST OF REFERENCES Abrini, H., Naveau, H., and Nyns, E. J.1994. Clost ridium autoethanogenum, sp. nov., an anaerobic bacterium that produces ethanol from carbon monoxide. Arch. Microbiol. 161 : 345 351. doi: 10.1007/BF00303591. ACORE (American Council on Renewable Energy). 2007. The outlook on renewable energy in America volum e II: joint summary report [online]. Available from http://www.acore.org/files/RECAP/docs/JointOutlookReport2007.pdf [accessed 12 December 2009] Adams, T. O. 1998. Implementation monitoring of forestry best management practices for site preparation in South Carolina. South J Appl For. 22 (2): 7480. Aden, A. 2008. Biochemical production of ethanol from corn stover: 2007 state of technology model. General Technical Report NREL/T P-51043205. National Renewable Energy Laboratory. Golden, Colorado. Aden, A., Ruth, M., Ibsen, K., Jechura, J., Neeves, K., Sheehan, J., and Wallace, B. 2002. Lignocellulosic biomass to ethanol process design and economics utilizing co -current dilute acid prehydrolysis and enzymatic hydrolysis for corn stover. Technical Report NREL/TP 510-32438. National Renewable Energy Laboratory. Golden, Colorado. Ahmed, A., Cateni, B. G., Huhnke, R. L., and Lewis, R. S. 2006. Effects of biomass generated producer gas c onstituents on cell growth, product distribution and hydrogenase activity of Clostridium carboxidivorans P7T. Biomass Bioenergy. 30(7): 665-672. doi:10.1016/j.biombioe.2006.01.007. Alavalapati, J. R. R., Hodges, A. W., Lal, P., Dwivedi, P., Rahmani, M., Kaufer, I., Matta, J. R., Susaeta, A., Kukrety, S., and Stevens, T. J. 2009. Bioenergy roadmap for Southern United States. Southeast Agriculture & Forestry Energy Resources Alliance ( SAFER), Southern Growth Polices Board, North Carolina. Alavalapati, J.R.R., Stainback, G.A., and Carter, D.R. 2002. Restoration of the longleaf pine ecosystem on private lands in the US South: an ecological economic analysis. Ecological Economics. 40 (3): 4 11 -419. doi:10.1016/S0921 8009(02)000125. Albaugh, T.J., Allen, H.L., and Fox, T.R. 2007. Historical patterns of forest fertilization in the Southeastern United States from 1969 to 2004. South. J Appl For 31(3):129-137. Ananda, J., and Herath, G. 2003. The use of analytic hierarchy process to incorporate stakeholder preferences into regional forest planning. Forest Policy and Economics. 5 (1):1326. doi:10.1016/S1389 -9341(02)00043-6.
133 Anonymous. 2008. Properties of wood [online]. Available from http://www.paperonweb.com/wood.htm [accessed 24 October 2008]. Badger, P. C., and Fransham, P. 2006. Use of mobile fast pyrolysis plants to densify biomass and reduce biomass handling costs a preliminary assessment. Biomass Bioenergy. 30 :321-325. doi:10.1016/j.biombioe.2005.07.011. Bare, J.C., Norris, G.A., Pennington, D.W., and McKone, T. 2003. TRACI The tool for the reduction and assessment of chemical and other environmental impacts. J Ind Ecol. 6 :4978. Bin ford, M.W., Gholtz, H.L., Starr, G., and Martin, T.A. 2006. Regional carbon dynamics in the southeastern U.S. coastal plain: b alancing land cover types, timber harvesting, fire, and environmental variation. J Geophys Res. 111 : D24S92 (112). doi:10.1029/ 2005JD006820. Birch, T. 1997. Private forest landowners of the Southern United States. Resource Bulletin NE 138.USDA Forest Service Northeastern Forest Experiment Station, Newton Square, PA. Bohlmann, G. M. 2006. Process economic considerations for product ion of ethanol from biomass feedstocks. Ind. Biotechnol. 2 (1):14-20. doi: 10.1089/ind.2006.2.14. Borchers, A. M.,Duke, J. M., and Parsons, G. R. 2007. Does willingness to pay for green energy differ by source? Energy Policy. 35 : 33273334. doi:10.1016/j.enp ol.2006.12.009. Brown, S.L., and Schroeder, P.E. 1999. Spatial patterns of aboveground production and mortality of woody biomass for eastern U.S. forests. Ecological Applications. 9 (3): 968980. doi: 10.1890/1051 -0761. Burnham, A., Wang, M., and Wu, Y. 2006. Development and applications of GREET 2.7 the transportation vehicle -cycle model. Argonne National Laboratory, Chicago, IL. Cardona, C. A., and Snchez, O. J. 2007. Fuel ethanol production: process design trends and integration opportunities. Bioresour Technol. 98 :2415 -2457. doi:10.1016/j.biortech.2007.01.002. CCX (Chicago Climate Exchange). 2009a. About CCX and trade on CCX [online]. Available from http://www.chicagoclimatex.com/about/pdf/CCX_Overview_Brochure.pdf [accessed 14 October 2009]
134 CCX (Chicago Climate Exchange). 2009b. CCX carbon financial instrument (CFI) contracts by daily report [online]. Available from http://www.chicagoclimatex.com/market/data/summary.jsf [accessed 14 October 2009] CCX (Chicago Cl imate Exchange). 2009c. Offset project registration, v erification & crediting procedure [online].Available fr om http://www.chicagoclimatex.com/content.jsf?id=104 [accessed 14 October 2009] Chandel, A. K., Es, C., Rudravaram, R., Narasu, M. L., Rao, L. V., and Ravindra, P. 2007. Economics and environm ental impact of bioethanol production technologies: an appraisal. Biotechnol. Mol. Biol. Rev. 2 (1): 1432. Chum, H. L., Johnson, D. K., Black, S., Baker, J., Grohmann, K., Sarkanen, K. V., Wallace, K., and Schroeder, H. A. 1998. Organosolv pretreatment for enzymatic hydrolysis of poplars: I. enzyme hydrolysis of cellulosic residues. Biotechnol Bioeng. 31 :643649. doi: 10.1002/bit.260310703. CitrusEnergy. 2009. Welcome to CitrusEnergy [online].Available from http:/ /www.citrusenergy.net/ [accessed 14 December 2009]. Clark, K.L., Gholtz, H.L., and Castro, M.S. 2004. Carbon dynamics along a chronosequence of slash pine plantations in north Florida. Ecological Applications. 14(4): 1154-1171. doi: 10.1890/025391 Colby, B.G. 2000. Cap and-Trade policy challenges: a tale of three markets. Land Economics. 76 (4): 638 -658. Coughlan, M. P., and Ljungdahl, L. G. 1988. Comparative biochemistry of fungal and bacterial cellulolytic enzyme system. In Biochemistry and genetics of c ellulose degradation. Edited by J.P. Aubert, P. Beguin and J. Millet. Academic Press. London, UK. pp. 1130. Covington, W. W., Ful, P.Z., Moore, M.M., Hart, S.C.,Kolb, T.E., Mast, J.N., Sackett, S.S., and Wagner, M.R. 1997. Restoring ecosystem health in ponderosa pine forests of the Southwest. J For 95 : 23 29. Cropper, W.P., and Gholz, H.L. 1993. Simulation of the carbon dynamics of a Florida slash pine plantation. Ecol Modell 66 : 231-249. Curtis, B. 2008. U.S. Ethanol industry: the next inflection point. United States Department of Energy (USDOE), Washington D.C., USA. Czernik, S., and Bridgwater, A. V. 2004. Overview of applications of biomass fast pyrolysis oil. Energy & Fuels. 18: 590598. doi: 10.1021/ef034067u.
135 Dwivedi, P., Alavalapati, J.R.R., Su saeta, A., and Stainback, A. 2009. Impact of carbon value on the profitability of slash pine plantations in the Southern United States: an integrated life cycle and Faustamann analysis. Can J For Res. 39 (5):9901000. Dyson, R. G. 2004. Strategic development and SWOT analysis at the University of Warwick. European Journal of Operational Research. 153(3): 631640. doi:10.1016/S0377 -2217(03)000626. EERE (Energy Efficiency & Renewable Energy). 2009a. Wind powering America [online]. Available from http://www.windpoweringamerica.gov/wind_installed_capacity.asp [accessed 13 December 2009] EERE (Energy Efficiency and Renewable Energy). 2009b. Biomass: multi year program plan. United States Department of Energy (USDOE), Washington D.C., USA. EIA (Energy Information Administration). 2006. Alternatives to traditional transportation fuels 2006 [online]. Available from http://www.eia.doe.gov/cneaf/alternate/page/atftables/afvtransfuel_II.html#consu mption [accessed 02 October 2008]. EIA (Energy Information Administration). 2008a. Electricity net generation from renewable energy by energy use sector and energy source [online]. Available from http://www.eia.doe.gov/cneaf/alternate/page/renew_energy_consump/table3.html accessed 26 November 2008] EIA (Energy Information Administration). 2008b. Annual energy outlook 2008 with projections to 2030 [online]. Available from http://126.96.36.199/Main/Blurbs/Annual_Energy_Outlook_2008_with_Projectio ns_to_203_157084.aspx [accessed 29 October 2009]. EIA (Energy Informatio n Administration). 2009a.Most of the petroleum we use is imported [online]. Available from http://tonto.eia.doe.gov/energyexplained/index.cfm?page=oil_imports [accessed 12 December 2009] EIA (Energy Information Administration). 2009b.Annual energy r eview [online]. Available from http://www.eia.doe.gov/emeu/aer/petro.html [accessed 12 December 2009] EIA (Energy Informatio n Administration). 2009c.How dependent are we on foreign oil [online]. Available from http://tonto.eia.doe.gov/energy_in_brief/foreign_oil_dependence.cfm [accessed 12 December 2009]
136 EIA (Energy Information Administration). 2009d.Oil: crude and energy products energy e xplained [online]. Available from http://tonto.eia.doe.gov/energyexplai ned/index.cfm?page=oil_home#tab1 [accessed 12 December 2009] EIA (Energy Information Administration). 2009e.Crude oil production [online]. Available from http://tonto.eia.doe.gov/dnav/pet/pet_crd_crpdn_adc_mbblpd_a.htm [accessed December 12 2009] EIA (Energy Information Administration). 2009f.Voluntary reporting of greenhouse gases program [online]. Available from h ttp://www.eia.doe.gov/oiaf/1605/coefficients.html [accessed 12 December 2009] EIA (Energy Information Administration). 2009g. U.S. emissions data [online]. Available from http://www.eia.doe.gov/environm ent.html [accessed 12 December 2009] EIA (Energy Information Administration). 2009h.Existing capacity by producer type [online]. Available from http://www.eia.doe.gov/cneaf/electricity /epa/epat2p3.html [accessed 12 December 2009] EIA (Energy Information Administration). 2009i.Where solar is foundenergy explained [online]. Available from http://tonto.eia.doe.gov/energyexplained/index.cfm?page=solar_where [accessed 12 December 2009] EIA (Energy Information Administration). 2009j. U.S. energy consumption by energy source [online]. Available from http://www.eia.doe.gov/cneaf/alternate/page/renew_energy_consump/table1.html [accessed 12 December 2009] EIA (Energy Information Administration). 2009k. Industrial biomass energy consumption and electricity net generation by industry and energy sources, 2007 [online]. Available from http://www.eia.doe.gov/cneaf/solar.renewables/page/trends/table1_8.pdf [accessed 12 December 200 9]. EIA (Energy Information Administration).2009l. Natural gas weekly update. [online]. Available from http://tonto.eia.doe.gov/oog/info/ngw/ngupdate.asp [accessed 14 November 2009]. Department of Energy, Washington, DC. Fargione, J., Hill, J., Tilman, D., Polasky, S., and Hawthorne, P. 2008. Land clearing and the biofuel carbon debt. Science 319(5867): 12351238. doi: 10.1126/science.1152747. Faustmann, M. 1995. Calculation of the value whic h forest land and immature stands possess for forestry (Republication of original article 1849). J For Econ. 1 : 7 44.
137 Frederick, W. J. Jr., Lien, S. J., Courchene, C. E., DeMartini, N. A., Ragauskas, A. J., and Lisa, K. 2008b.Production of ethanol from carbohydrates from loblolly pine: a technical and economic assessment. Bioresour Technol 99:5051 -5057. doi:10.1016/j.biortech.2007.08.086. Frederick, W. J., Lien, S. J., Courchene, C. E., DeMartini, N. A, Ragauskas, A. J., and Lisa, K. 2008a. Co produc tion of ethanol and cellulose fiber from southern pine: a technical and economic assessment. Biomass Bioenergy. 32 (12):1293 -1302. doi:10.1016/j.biombioe.2008.03.010. Furuholt, E. 1995. Life cycle assessment of gasoline and diesel. Resour., Conserv. Recycl. 14 :251 -263. Gholz, H.L., and Fisher, R.F. 1982. Organic matter production and distribution in slash pine (P inus elliottii) plantations. Ecology. 63 (6): 1827 1839. doi: 10.2307/1940124. Glasser, W. G., and Wright, R. S. 1998. Steam assisted biomass fraction ation. II. fractionation behavior of various biomass resources. Biomass Bioenergy. 14 (3): 219-235. doi:10.1016/S0961 -9534(97)10037X. Gould, J. M. 1984. Alkaline peroxide delignification of agricultural residues to enhance enzymatic saccharification. Biote chnol Bioeng 26 :4652. doi: 10.1002/bit.260260110. Gregory, R., and Wellman, R. 2001. Bringing stakeholder values into environmental policy choices: a community based estuary case study. Ecological Economics. 39(1): 3752. doi:10.1016/S0921 -8009(01)00214-2. GRU (Gainesville Regional Utilit ies ). 2009. Biomass generation: meeting Gainesvilles future energy needs [online]. Available from http://www.gru.com/OurCommunity/Environment/RenewableEnergy/biomassPlan t.jsp [accessed 13 December 2009]. Hamelinck, C. N., Hooijdonk, G. V., and Faaji, A. P. C. 2005. Ethanol from lignocellulosic biomass: techno economic performance in short middle and long -term. Biomass Bioenergy. 28 :384410. d oi:10.1016/j.biombioe.2004.09.002. Han, F.X., Plodinec, M.J., Su, Y., Monts, D.L., and Li, Z. 2007. Terrestrial carbon pools in southeast and south-central United States. Climate Change. 84 (2): 191202. doi: 10.1007/s10584007-9244 5. Hartman, M.E. 1976. The harvesting decision when a standing forest has value. Economic Inquiry. 14(1):5258.
138 Hendricks, A. T. W. M., and Zeeman, G. 2009. Pretreatments to enhance the digestibility of lignocellulosic biomass. Bior esour Technol 100:10 18. doi:10.1016/j.biortech.2008.05.027. Hill, J., Nelson, E., Tilman, D., Polasky, S., and Tiffany, S. 2006. Environmental, economic, and energetic costs and benefits of biodiesel and ethanol biofuels. Proc. Natl. Acad. Sci. U.S.A. 1 03 : 11206 -11210. doi: 10.1073/pnas.0604600103. Houben, G., Lenie, K., and Vanhoof, K. 1999. A knowledge-based SWOT -analysis system as an instrument for strategic planning in small and medium sized enterprises. Decision Support Systems. 26 (2): 125 -135. doi : 10.1016/S0167 9236(99)00024X. Howard, E.T. 1973. Physical and chemical properties of slash pine parts. Wood Sci. 5 (4): 321317. Huang, H. J., Ramaswamy, S., Dajani, W. A., Tschirner, U., and Cairncross, R. A. 2009. Effect of biomass species and plant siz e on cellulosic ethanol: a comparative process and economic analysis. Biomass Bioenergy. 33(2): 234246. doi:10.1016/j.biombioe.2008.05.007. Husain, Z., Zainac, Z., and Abdullah, Z. 2002. Briquetting of palm fiber and shell from the processing of palm nuts to palm oil. Biomass Bioenergy. 22 (6): 505509. doi:10.1016/S0961 -9534(02)000223. Jeoh, T., 1998. Steam explosion pretreatment of cotton g in waste for fuel ethanol production. MS Thesis, Biological Systems Engineering, The Virginia Polytechnic Institute and State University, Blacksburg, VA. Johnson, L.R., Lippke, B., Marshall, J.D., and Comnick, J. 2005. Life cycle impacts of forest resource activities in the pacific northwest and southeast United States. Wood Fiber Sci 37 :30 -46. Kadam, K. L. 2000. Environmental life cycle implications of using bagasse derived ethanol as a gasoline oxygenate in Mumbai (Bombay). NREL Report # NREL/TP -580 -2870 5, National Renewable Energy Laboratory Golden, Colorado. Kadam, K.L., Wooley,R.J., Aden, A., Nguyen, Q.A., Yancey, M.A., and Ferraro, F.M. 2000. Softwood forest thinning as a biomass source for ethanol production: a feasibility study for California. Biote chnol Prog 16 :947-957. Kluender, R.A., and Walkingstick, T.L. 2000. Rethinking how nonindustrial landowners view their lands. South J of Appl For 24 (3): 150 -158. Krishna, S. H., Reddy, T. J., and Chowdary, G. V. 2001. Simultaneous saccharification and fermentation of lignocellulosic wastes to ethanol using a thermotolerant yeast. Bioresour Technol. 77 (2):193196. doi: 10.1016/S09608524(00)001516.
139 Kurttila, M., Pesonen, M., Kangas, J., and Kajanus, M. 2000. Utilizing the analytic hierarchy process (AHP) in SWOT analysis a hybrid method and its application to a forest -certification case. Forest Policy and Economics. 1 (1): 41 52. doi:10.1016/S1389 -9 341(99)000040. Laughlin, J. O. 2005. Forest health, risk assessment, and the national fire plan. Perspectives on Americas f orests. Roundtable on Sustainable Forests. December 1314, 2005. Washington, D.C., USA. Lavigne, A., and Powers, S.E. 2007. Evalua ting fuel ethanol feedstocks fr om energy policy perspectives: a comparative energy assessment of corn and corn stover. Energy Policy 35 :5918 -5930. doi:10.1016/j.enpol.2007.07.002. Lee, J. W., Gwakl, K. S., Park, J. Y, Park, M. J., Choi, D. H., Kwon, M., a nd Choil, I. G. 2007. Biological pretreatment of softwood Pinus densiflora by three white rot fungi. The Journal of Microbiology. 45 (6):485 491. Leistritz, F. L., Senechal, D. M., Stowers, M. D., McDonald, W. F., Saffron, C. M., and Hodur, N. M. 2006. Preliminary feasibility analysis for an integrated biomaterials and ethanol biorefinery using wheat straw feedstock. Agribusiness & Applied Economics Report No. 590. Department of Agribusiness and Applied Economics Agricultural Experiment Station, North Dakota State University, Fargo, ND. Li, Y., and Liu, H. 2000. Highpressure densification of wood residues to form an upgraded fuel. Biomass Bioenergy. 19(3):177-186. doi:10.1016/S0961 9534(00)00026X. Lin, Y., and Tanaka, S. 2006. Ethanol fermentation from biomass resources: current state and prospects. Appl Microbiol Biotechnol. 69 :627-642. doi: 10.1007/s00253005-0229 x. Liou, J.S.C., Balkwill, D.L., Drake, G.R., and Tanner, R.S. 2005. Clostridium carboxidivorans sp. nov., a solvent producing clostridium isolated from an agricultural settling lagoon, and reclassification of Clostrdidium scatologenes strain SL1 as Clostrdium drakei sp. nov. Int. J. Syst. Evol. Microbiol 55:2085 2091. doi: 10.1099/ijs.0.63482-0. Liski,J., Palosuo,T., Peltoniemi,M., and Si evnen, R. 2005. Carbon and decomposition model Yasso for forest soils. Ecol Modell 189 :168 -182. doi:10.1016/j.ecolmodel.2005.03.005. Lynd L.R., Zyl, W.H.V., McBride, J.E., and Laser, M. 2005.Consolidated bioprocessing of cellulosic biomass: an update. C urr. Opin. Biotechnol 16 :577583. doi:10.1016/j.copbio.2005.08.009. Markewitz, D. 2006. Fossil fuel carbon emissions from silviculture: impacts on net carbon sequestration in forests. For Ecol Manage. 236:153 -161. doi:10.1016/j.foreco.2006.08.343.
140 Mas era,O., Garza -Caligaris, J.F., Kanninen, M., Karjalainen, T., Liski, J., Nabuurs, G.J., Pussinen, A., and Jong, B.J. 2003. Modelling carbon sequestration in afforestation, agroforestry and forest management projects: the CO2FIX V.2 approach. Ecol Modell 164:177199. doi:10.1016/S03043800(02)004192. Masozera, M. K., Alavalapati, J. R. R., Jacobson, S. K., and Shrestha, R. K. 2006. Assessing the suitability of community based management for the Nyungwe Forest Reserve, Rwanda. Forest Policy and Economics. 8 (2):206 -216. doi:10.1016/j.forpol.2004.08.001. Mawapanga, M. N., and Debertin, D. L. 1996. Choosing between alternative farming systems: an application of the analytic hierarchy process. Review of Agricultural Economics. 18 :385 401. McAloon, A., Taylor, F., Yee, W., Ibsen, K., and Wooley, R. 2000. Determining the cost of producing ethanol from corn starch and lignocellulosic feedstocks. Technical Report NREL/TP 580-28893. National Renewable Energy Laboratory. Golden, Colorado. Mengak, M.T., and Guynn, D.C Jr. 2003. Small mammal microhabitat use on young loblolly pine regeneration areas. For Ecol Manage. 173:309-317. doi:10.1016/S0378 -1127(02)000087. Miller, R.B. 1999. Structure of wood. In Wood handbook: wood as an engineering material. Edited by M.A. Dietenberger, D.W. Green, D.E. Kretschmann, R. Hernandez, T.L Highley, R.E.Ibach, J.Y.Liu, K.A.McDonald,R.B. Miller,R.C. Moody, R.M.Rowell, W.T.Simpson, L.A.Soltis, A.TenWolde,R.W. Wolfe, C.B.Vick, R.H.White, R.S.Williams, J.E.Winandy and J.A.Youngq u ist. General Technical R eport FPL GTR -113, Forest Products Laboratory, USDA Forest Service, Madison, WI. pp. 2.12.4. MIT (Massachusetts Institute of Technology). 2006. The future of geothermal energy: impact of enhanced geothermal systems (EGS) on the Uni ted States in the 21st century [online]. Available from http://geothermal.inel.gov/publications/future_of_geothermal_energy.pdf [accessed 13 December 2009] Mitchell, D. 2008. A note of rising food prices. Policy research working paper # 4682. Development Prospects Group. The World Bank, Washington D.C., USA. Mollenhorst, H., and de Boer, I. J. M. 2004. Identifying sustainability issues using participatory SWO T analysis: A case study of egg production in the Netherlands. Outlook Agric. 33 (4):267276. Mosier, N., Wyman, C., Dale, B., Elander, R., Lee, Y.Y., Holtzapple, and Ladisch, M. 2005. Features of promising technologies for pretreatment of lignocellulosic b iomass. Bioresour Technol. 96 (6):673 -686. doi:10.1016/j.biortech.2004.06.025.
141 Nair, K. G. K., and Prasad, P. N. 2004. Offshore outsourcing: a SWOT analysis of a state in India. Information Systems Management. 21 (3):34-40. Nesbit, T.S., Alavalapati, J.R.R ., Dwivedi, P., and Marinescu, M. 2009. Economics of ethanol production using feedstock from slash pine ( Pinus elliottii) plantations in the Southern United States. South J of Appl For (in press) Nguyen, D. 1979. Environmental services and the optimum rotation problem in forest management. J. Environ. Manage. 8 :127136. NREL ( National Renewable Energy Laboratory ). 1999. Fact sheet Ford Taurus: ethanol fueled sedan. Department of Energy, Washington, DC. Perkins, C.M., Woodruff, B., Andrews, L., Lichty, P ., Lancaster, B., Bingham, C., and Weimer, A.W. 2008. Synthesis gas production by rapid solar thermal gasification of corn stover. In Proceedings of the 14th Biennial CSP SolarPACES (Solar Power and Chemical Energy Systems) Symposium, 47 March 2008, Las V egas, Nevada. Perlack, R. D., Wright, L. L., Turholllow, A. F., Graham, R. L., Stokes, B. J., and Erbach, D. C. 2005. Biomass as a feedstock for a bioenergy and bioproducts industry: The technical feasibility of a billion -ton annual supply. Oak Ridge Natio nal laboratory. US Department of Energy/US Department of Agriculture, Washington, D.C., USA. Pesonen, M., Ahola, J., Kurttila, M., Kajanus, M., and Kangas, J. 2001b. Applying AWOT to forest industry investment strategies: case study of a Finnish company i n North America. In The analytical hierarchy process in natural resource and environmental decision making. Edited by D.L. Schmoldt, J. Kangas, G.H. Mendoza, M. Pesonen. Kluwer Academic Publisher, Dordrecht, Netherlands. pp. 187-198. Pesonen, M., Kurttila, M., Kangas, J., Kajanus, M., and Heinonen, P. 2001a. Assessing the priorities using AWOT among resource management strategies at the Finnish Forest and Park Service. For Sci. 47(4):534-541. Petrolia, D.R. 2008. The economics of harvesting and transporting corn stover for conversion to fuel ethanol: A case study for Minnesota. Biomass Bioenergy. 32(7):603-612. doi:10.1016/j.biombioe.2007.12.012. Phillips, S., Aden, A., Jechura, J., and Dayton, D. 2007. Thermochemical ethanol via indirect gasification and mixed alcohol synthesis of lignocellulosic biomass. Technical Report TP -510 -41168. National Renewable Energy Laboratory, Golden, Colorado. Phill ips, S.D. 2007. Technoeconomic analysis of a lignocellulosic biomass indirect gasification process to make ethanol via mixed alcohols synthesis. Industrial and Engineering Chemistry Research. 46 :8887 8897. doi:10.1021/ie071224u.
142 Piccolo, C., and Bezzo, F. 2009. A technoeconomic comparison between two technologies for bioethanol production from lignocelluloses. Biomass Bioenergy. 33(3):478-491. doi:10.1016/j.biombioe.2008.08.008. Pienaar, L.V., and Rheney, J.W. 1993. Yield prediction for mechanically site p repared slash pine plantations in the southeastern coastal plain. South J Appl For 17(4):163-173. Pimentel, D., and Patzek, T. W. 2005. Ethanol production using corn, switchgrass, and wood; Biodiesel production using soybean and sunflower. Nat. Resour. Res. 14(1):6576. doi: 10.1007/s11053 005-4679 -8. Pimentel, D., and Pimentel, M. 2008. Food, energy, and society.CRC Press. Boca Raton, FL. Quintero, J.A., Montoya, M.I., Snchez, O.J., Giraldo, O.H., and Cardona, C.A. 2008. Fuel ethanol production from sugarcane and corn: comparative analysis for a Columbian case. Energy. 33 :385 -399. Rajagopalan, S.P., Datar, R., and Lewis, R.S. 2002. Formation of ethanol from carbon monoxide via a new microbial catalyst. Biomass Bioenergy. 23 :487 493. doi:10.1016/S0961 -9534(02)000715. Ramos, L.P. 2003. The chemistry involved in the steam treatment of lignocellulosic materials. Qum Nova. 26(6):863-871. doi:10.1590/S0100 40422003000600015. Range Fuels. 2009. Our first commercial plant: a new plant, a new vision [onlin e]. Available from http://www.rangefuels.com/our -first -commercial -plant.html [accessed 14 December 2009] Rauch, P. 2007. SWOT analyses and SWOT strategy formulation for forest owner co operations in Austria. Eur. J. For. Res. 126:413420. doi: 10.1007/s1034200601622. Rezaiyan, J., and Cheremisinoff, N.P. 2005. Gasification technologies: a primer for engineers and scientists. CRC Press, Taylor & Francis Group, Boca Raton, Florida. RFA (Renewable Fuel Association). 2009. Historic U.S. fuel ethanol production [online]. Available from http://www.ethanolrfa.org/industry/statistics/#F [accessed 13 December 2009]. RFA (Renewable Fuel Association). 2009. List of U.S. cellulosic ethanol projects: under development and construction [online]. Available from http://www.ethanolrfa.org/resource/cellulosic/documents/CurrentCellulosicEthano lProjects -January2009.pdf [accessed 18 June 2009].
143 Roe, B.,Teisl, M. F., Levy, A., and Russell, M. 2001. US consumenrs willingness to pay for green electricity. Energy Policy. 29 :917925. doi:10.1016/S03014215(01)000064. Roos, A., Graham, R. L., Hektor, B., and Rako, C. 1999. Critical factors to bioenergy implementation. Biomass Bioenergy. 17(2):113-126. doi:10.1016/S0961 9534(99)000288. Ruan, R., Chen, P., Hemmingsen,R., Morey, V., and Tiffany, D. 2008. Size matters: small distributed biomass energy production systems for economic viability. Int. J. Agric. Biol. Eng. 1 (1): 64 -68. d oi: 0.3965/j.issn.1934-6344.2008.01.064-068. Saaty, T. L. 1977. A scaling method for priorities in hierarchical structure. Journal of Mathemat ical Psychology. 15 :234 281. doi:10.1016/0022 -2496(77)900335. Saaty, T. L. 1993. The analytic hierarchy process: a 1993 overview. Central European Journal of Operation Research and Economics. 2 (2): 119 137. Saaty, T. L. 2001. The seven pillars of the analy tical hierarchy process. In Models, methods, concepts & applications of analytical hierarchy process. Edited by T.L. Saaty and L.G. Vargas. Kluwer Academic Publisher. Dordrecht, Netherlands. pp. 2746. Saaty, T. L., and Vargas, L. G. 2001. Models, methods, concepts & applications of the analytical hie rarchy p rocess. Kluwer Academic Publisher. Dordrecht, Netherlands. Sabrina, S., Zhang, Y., Heather, M.L.2005. Life cycle assessment of switchgrass and corn stover derived ethanol -fueled automobiles. Environment al Science & Technology 39 :97509758. doi: 10.1021/es048293+. Sandor, D., Wallace, R., and Peterson, S. 2008. Understanding the growth of the cellulosic ethanol industry. Technical Report NREL/TP -15042120. National Renewable Energy Laboratory. Golden, Colorado. Sassner,P., Galbe, M., and Zacchi, G. 2008. Techno economic evaluation of bioethanol production from three different lignocellulosic materials. Biomass Bioenergy. 32(5): 422-430. doi:10.1016/j.biombioe.2007.10.014. Schelhaas, M.J., Esch, P.W., G roen, T.A., Kanninen, M., Liski, J., Masera, O., Mohren, G.M.J., Nabuurs, G.J., Pedroni, L., Pussinen, A., Vallejo, A., Palosuo, T., and Viln, T. 2004. CO2FIX V 3.1 A modeling framework for quantifying carbon sequestration in forest ecosystems. ALTERRA Report 1068. Wageningen, The Netherlands. Schmer, M.R., Vogel, K.P., Mitchell, R.B., and Perrin, R.K. 2008. Net energy of cellulosic ethanol from switchgrass. Proc. Natl. Acad. Sci. U.S.A 105 : 464469. doi: 10.1073/pnas.0704767105.
144 Searchinger, T., Heimlich, R., Houghton, R. A., Dong, F., Elobeid, A., Fabiosa, J., Tokgoz, S., Hayes, D., and Yu, T. H. 2008. Use of U.S. croplands for biofuels increases greenhouse gases through emissions from landuse change. Science. 319(5867):1238124 0. doi: 10.1126/science.1151861. SEIA (Solar Energy Industries Association). 2008. US Solar Industry year in review 2008 [online]. Available from http://seia.org/galleries/pdf/2008_Y ear_in_Review small.pdf [accessed 13 December 2009] SEIA (Solar Energy Industries Association). 2009. About solar energy [online]. Available from http://www.seia.org/cs/about_solar_energ y/industry_data [accessed 13 December 2009] Sharma, M., and Bhatia, G. 1996. The voluntary commu nity health movement in India: a strengths, weaknesses, opportunities, and threats (SWOT) analysis. Journal of Community Health. 21 (6): 453464. doi:10.1007/BF01702605. Sheehan, J., Aden, A., Paustian, K., Killian, L., Brenner, J., Walsh, M., and Nelson, R. 2004. Energy and environmental aspects of using corn stover for fuel ethanol. J Ind Ecol 7 :117-146. Shleser, R. 1994. Ethanol production in Hawaii: processes, feedstocks, and current economic feasibility of fuel grade ethanol production in Hawaii. Final Report. Department of Business, Economic Development & Tourism, State of Hawaii. Short, W., Packey, D., and Holt, T. 1995. A manual for the economic evaluation of energy efficiency and renewable energy technologies. NREL Publication # TP 462-5173. National Renewable Energy Laboratory (NREL). Golden, CO. Shrestha, R. K., Alavalapati, J. R. R., and Kalmbacher, R. S. 2004. Exploring the potential for silvo pasture adoption in south-central Florida: an application of SWOT AHP method. Agricultural Systems. 81(3): 185199. doi:10.1016/j.agsy.2003.09.004. Simmons, J., and Lovegrove, I. 2005. Bridging the conceptual divide: lessons from stakeholder analysis. Jour nal of Organizational Change Management. 18 (5): 495-513. Sims, R. E. H. 2003. Bioenergy to mitigate for climate change and meet the needs of society, the economy and the environment. Mitigation and Adaptation Strategies for Global Change. 8 :349 -370. doi:10 .1023/B:MITI.0000005614.51405.ce. Siry, J.P. 2002. Intensive timber management practices. In Southern forest resource assessment. Edited by D.N. Wear and J.G. John. General Technical Report SRS-53. U.S. Department of Agriculture Forest Service, Southern Re search Station. Asheville, NC pp. 327340.
145 Smith, W. B., Vissage, J. S., Darr, D. R., and Sheffield, R. M. 2001. Forest resources of the United States, 1997. General Technical Report # NC -219. USDA Forest Service Northern Central Research Station, St. Paul, MN. So, K. S., and Brown, R.C. 1999. Economic analysis of selected lignocellulose-to ethanol conversion technologies. Appl Biochem Biotechnol. 79(1 3):633-640. doi: 10.1385/ABAB:79:1-3:633. Solomon, B.D., Barnes, J.R., and Halvorsen. 2007. Grain an d cellulosic ethanol: history, economics, and energy policy. Biomass Bioenergy. 31 :416425. doi:10.1016/j.biombioe.2007.01.023. Spangenberg, J. H. 2008. Biomass or biomess? The promises and limits of bioenergy. In Sustainable energy production and consumpt ion. Edited by F. Barbir and S. Ulgiati. Springer Science + Business Media B.V., Netharlands. pp. 55 -65. Stainback, G.A., and Alavalapati, J.R.R. 2002. Economic analysis of slash pine forest carbon sequestration in the southern U. S. J For Econ. 8 (2):105117. doi:10.1078/1104 -6899 -00006. Stainback, G.A., and Alavalapati, J.R.R. 2004. Modeling catastrophic risk in economic analysis of forest carbon sequestration. Natural Resource Modeling. 17(3): 299317. doi: 10.1111/j.1939-7445.2004.tb00138.x. Stainback G.A., and Alavalapati, J.R.R. 2005. Effects of carbon markets on the optimal management of slash pine ( Pinus elliottii) plantations. South. J Appl For 29 (1): 2732. Sullivan, R.O. 2008. Reducing emissions from deforestation in developing countries: an introduction. In Climate Change and Forests. Edited by C. Streck, R. O. Sullivan, T. J. Smith, and R. Tarasofsky. Chatham House (London) and Brookings Institution Press (Washington, D.C.). Sun, C., and Zhang, D. 2006. Timber harvesting margins in the South U.S.: A temporal and spatial analysis. For Sci. 52 (3): 273 -280. Sun, Y., and Cheng, J. 2002. Hydrolysis of lignocellulosic materials for ethanol production: a review. Bioresour Technol. 83:1 11. doi:10.1016/S09608524(01)002127. Susaeta, A., Alavalapati, J.R.R., and Carter, D.R. 2009. Modeling impacts of bioenergy markets on nonindustrial private forest management in the southeastern United States. Natural Resource Mo deling. 22 (3): 345369. doi: 10.1111/j.19397445.2009.00040.x. Tan, K.T., Lee, K.T., and Mohamed, A.R. 2008. Role of energy policy in renewable energy accomplishment: the case of secondgeneration bioethanol. Energy Policy. 36 (9):3360-3365. doi:10.1016/j.enp ol.2008.05.016.
146 Tchobanoglous,G., Burton, F.L.,Stensel, H.D., and Metcalf & Eddy. 2003. Wastewater engineering, treatment and reuse. Tata McGraw -Hill, USA. Teixeira, L.C., Linden, J.C., and Schroeder, H.A. 1999. Alkaline and peracetic acid pretreatments of biomass for ethanol production. Appl Biochem Biotechnol. 77:19 -34. doi:10.1385/ABAB:77:1-3:19. Tembo, G., Epplin, F.M., and Huhnke, R.L. 2003. Integrative investment appraisal of a lignocellulosic biomass -to ethanol industry. Journal of Agricultural and Resource Economics. 28 (3):611633. Thring, R.W., Chorent, E., and Overend, R. 1990. Recovery of a solvolytic lignin: effects of spent liquor/acid volume ration, acid concentration and temperature. Biomass. 23:289305. TMS (Timber Mart South). 2009. Southeastern average stumpage prices US $/ton [online]. Available from http://www.tmart -south.com/tmart/prices.html [accessed 14 October 2009]. Ulmer, J. D., Huhnke, R. L., Bellmer, D. D., and Cartmell D. D. 2004. Acceptance of ethanol blended gasoline in Oklahoma. Biomass Bioenergy. 27(5): 437444. doi:10.1016/j.biombioe.2004.04.005. USDA (United States Department of Agriculture). 2005. Feed grains d atabase. National Agricultural Statistics Service, United States Department of Agriculture, Washington, DC. USFS (United States Forest Service), 2005. Forest Inventory and Analysis National Program: Forest Inventory Data Online (FIDO). USDA Forest Service, Arlington, Virginia. Van Kooten, G.C., Binkley, C. S., and Delcourt, G. 1995. Effect of carbon taxes and subsidies on optimal forest rotation age and supply of carbon services. American Journal of Agricultural Economics. 77: 365374. Varela, M., Lechn, Y., and Sez, R.1999. Environmental and socioeconomic aspects in the strategic analysis of a biomass power plant integration. Biomass Bioenergy. 17 (5): 405 -413. doi:10.1016/S0961 -9534(99)00058-6. Vega, J.L., Clausen, E.C., Gaddy, J.L. 1990. Design of bioreactors for coal synthesis gas fermentations. Resour Conserv Recycl. 3 :149 160. Vogt, K.A, Andreu, M.G., Vogt, D.J., Sigurdardottir, R., Edmonds, R.L., Schiess, P., and Hodgson, K. 2005. Return added for forest owners by linking forests to bioenergy production. J For 103 (1):21 -27.
147 Walsh, M. E., Perlack, R. L., Turhollow, A., Ugarte, D. de la T., Becker, D. A., Graham, R. L., Slinsky, S. E., and Ray, D. E. 2000. Biomass feedstock availability in the United States: 1999 State level analysis [online]. Available from http://bioenergy.ornl.gov/resourcedata/index.html [accessed 02 October 2008]. Waltz, E. 2008. Cellulosic ethanol booms despite unproven business models. Nat Biotechnol. 26:8 9. doi:10.1038/nbt01088. Wear, D. N., Carter, D. R., and Prestemon, J. 2007. The U.S. Souths timber sector in 2005. A prospective analysis of recent change. USDA Forest Service Southern Research Station, Asheville, NC. Wei,L., Pordesimo, L.O., Igathinathane,C., and Batchelor,W.D. 2009. Process engineering evalu ation of ethanol production from wood through bioprocessing and chemical catalysis. Biomass Bioenergy. 33 (2):255266.doi: doi:10.1016/j.biombioe.2008.05.017. Weihrich, H. 1982. The TOWS matrix a tool for situational analysis. Long Range Planning. 15(2): 5466. doi:10.1016/0024 -6301(82)90120-0. White, M.K., Gower, S.T., and Ahl, D.E. 2005. Life cycle inventories of roundwood production in northern Wisconsin: inputs into an industrial forest carbon budget. For Ecol Manage. 219 :13 -28. doi:10.1016/j.forec o.2005.08.039. Wooley, R., Ruth, M., Sheehan, J., Ibsen, K., Majdeski, H., and Galvez, A. 1999. Lignocellulosic biomass to ethanol process design and economics utilizing cocurrent dilute acid prehydrolysis and enzymatic hydrolysis current and futuristic s cenarios. Technical Report NREL/ A035634. National Renewable Energy laboratory. Golden, Colorado. Wright, J.D. 1988. Ethanol from lignocellulosics: an overview. Energy Prog. 84 :71 -80. Wright, M.M., and Brown, R.C. 2007. Comparative economics of biorefineries based on the biochemical and thermochemical platforms. Biofuels, Bioproducts & Biorefining. 1 :49 -56. doi: 10.1002/bbb.8. WSTB ( Water Science and Technology Board). 2008. Water impli cations of biofuels production in the United States The National Academy Press, Washington DC. Xiao, W., and Clarkson, W.W. 1997. Acid solubilization of lignin and bioconversion of treated newsprint to methane. Biodegradation. 8 :61 -66. doi: 10.1023/A:1008297211954. Yang, B., and Wyman, C.E. 2004. Effect of xylan and lignin removal by batch and flow through pretreatment on the enzymatic digestibility of corn stover cellulose. Biotechnol Bioeng. 86 :88 -95. doi: 10.1002/bit.20043.
148 Yin,R., Pienaar,L.V., and Aronow, M.E. 1998. The productivity and profitability of fiber farming. J For 96 (11):13 18. Zhang, X., Yu, H., Huang, H., and Liu, Y. 2007. Evaluation of biological pretreatment with white rot fungi for the enzymatic hydrolysis of bamboo culm s. International Biodeterioration & Biodegradation. 60 (3):159-164. doi:10.1016/j.ibiod.2007.02.003. Zheng, Y.Z., Lin, H.M., and Tsao, G.T. 1998. Pretreatment for cellulose hydrolysis by carbon dioxide explosion. Biotechnol Prog. 14 :890896. doi: 10.1021/bp980087g.
149 BIOGRAPHICAL SKETCH Puneet Dwivedi was born in Kanpur, India. He is the only child of Mrs. Usha Dwivedi and Mr. Ashok Kumar Dwivedi. He completed his schooling in 1998 from Kendriya Vidyalaya, Indian Telephone Industries Limited, Mankapur ( D istrict Gonda) India H e joined the Institute of Engineering & Technology, Devi Ahilya University, Indore, India in 1999 to complete his four year degree program in Mechanical Engineering. He finished his engineering program in May of 2003 with a silver m edal and a distinction. In July of 2003, he joined Indian Institute of Forest Management, Bhopal, India for pursuing a graduate degree in forestry managemen t After finishing his two year graduate program in 2005 with a silver medal he took employment wit h Winrock International India (WII) Puneet left WII in July of 2006 to pursue doctoral studies at the School of Forest Resources and Conservation University of Florida, Gainesville Florida, United States After finishing his doctoral studies, Puneet has plans to pursue a research and teaching car e e r in the area of forest economics environment management and bioenergy development