Piedmont Biofuels Final LCA Report Triangle Life Cycle Assessment, LLC. A Partnership for Sustainable Innovation

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1 Piedmont Biofuels Final LCA Report Triangle Life Cycle Assessment, LLC A Partnership for Sustainable Innovation 2012

2 Executive Summary Mr. Estill, We would like to thank you for your help and support with the life cycle assessment which is herein provided. As discussed, this project focused on the life cycle greenhouse gas emissions and the net energy ratio for the Piedmont Biofuel Industrial, LLC facility in Pittsboro, North Carolina. After completing preliminary literature review and determining the scope and goals of the study, a site walk-through was completed to obtain facility operational data for the life cycle inventory. A thorough material and energy balance was completed for the biodiesel product life cycle. The data compiled in the inventory was used to develop a life cycle assessment scenario in the OpenLCA software platform where upstream emissions, avoided emissions and allocated burden calculations were performed. A thorough quality assurance/quality control program was implemented for this study to ensure that emission calculations are correct and material and energy balances were performed accurately. As per our previous conversations, feel free to use this study and all calculated information for internal benchmarking, external marketing and dissemination to stakeholders. We look forward to working with you again in the future. When you need to update this life cycle assessment study due to process changes, incorporation of solar panel use or after a specific period of time we would very much like to conduct this follow-up study with you. Best regards, Jesse Daystar President Triangle Life Cycle Assessment 1

3 Table of Contents Executive Summary Abstract Purpose Methods Results Conclusions Introduction Project Scope System Boundaries Assumptions Methods Data Collection System Modeling PBF and GREET Scenarios Parallel Systems Process Waste Material Balance Life Cycle Assessment Life Cycle Inventory Net Energy Ratio Results Life Cycle Assessment Net Energy Ratio Discussion Greenhouse Gases Net Energy Ratio GREET Comparison Study Limitations Conclusions Future Work References

4 1. Abstract 1.1 Purpose Attributional life cycle assessment (LCA) was used to determine the greenhouse gas (GHG) burdens associated with the production of biodiesel from waste vegetable oil (WVO) on cradle to grave basis. The life cycle stages analyzed included feedstock development, transportation, conversion to biodiesel, and combustion. 1.2 Methods This study used an OpenLCA model to calculate the percent reduction of GHG emissions resulting from the production and use of biodiesel compared to conventional diesel fuels. Biodiesel, from Piedmont Biofuels Industrial LLC (PBF) in Pittsboro NC, was compared to the Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model (GREET) by Argonne National Laboratory for biodiesel and conventional petroleum-based diesel. The net energy ratio (NER) was calculated for the PBF process to compare non-renewable input energy to renewable output energy on a life cycle basis. 1.3 Results It was determined that the production and use of PBF biodiesel reduces greenhouse gas (GHG) emissions from conventional diesel life cycle emissions by 87% and 96% for the feedstock production burden allocated and non-burden allocated scenarios respectively. The NER for the PBF process was determined to be 7.85:1 (renewable energy produced to non-renewable energy inputs). 1.4 Conclusions PBF biodiesel produced from waste vegetable oil (WVO) results in lower environmental burden across the life cycle than biodiesel produced from poultry lipids or conventional fossil-based diesel. Net GHG emissions associated with the PBF biodiesel could be potentially reduced up to 1.20 g CO 2 -eq./mj (98.73% reduction from conventional diesel fuel) for the no feedstock burden scenario if grid electricity was offset by the installation of an on-site solar array. 2. Introduction Life cycle assessment (LCA) is used regularly for product and process evaluations which identify environmental burdens across all life cycle stages from cradle to grave. Previous studies have shown that different biofuel feedstocks have different environmental burden hot-spots, which refer to elevated greenhouse gas (GHG) emissions associated with a specific life cycle stage or facility process. Huo et al. (2009) analyzed four different biofuels scenarios including biodiesel, two renewable diesel fuels and renewable gasoline, all from soybean oil. It was identified that allocation methods for co-products and avoided emissions are critical to the outcome of the study. Additionally, it was shown that well-to-pump energy use was significantly higher than pump-to-wheel, for which they assumed no carbon uptake by the soybean plant and then modeled emissions. 3

5 Jørgensen et al. (2012) and Terry et al. (2009) used conversion data from Piedmont Biofuels Industrial, LLC (PBF) to analyze the GHG emissions from the cradle to grave life cycle of biodiesel from poultry fat. PBF previously converted poultry fat to biodiesel on a commercial scale, however, converted to waste vegetable oil (WVO) in The Jørgenson et al. study is a consequential LCA as the main goal of the study was to determine how an increase in biodiesel quantity produced from poultry fat would impact GHG emissions (kg CO 2 eq./tonne). This study found GHG reductions of 16% reduction in net GHG compared to conventional diesel. In addition, Lopez et al. (2010) conducted an LCA on biodiesel converted from rendered lipids. This study primarily focused on energy use; however, study scenarios included agricultural activities, livestock use of agricultural products, slaughter and rendering of the livestock to obtain lipids, conversion of the lipids to biodiesel, and use for transportation fuel. This study also utilized a net energy ratio (NER) to calculate the energy balance. For the base-case, the NER was determined to be 3.6, a value which was compared against the PBF NER value presented later in this study. According to Kim et al. (2005), biodiesel from corn grain, corn stover and soybeans all result in decreases in well-to-wheel GHG emissions and global warming impact (GWI). Their study incorporated LCA, using the TRACI impact assessment method (Bare et al. 2003) and the DAYCENT biogeochemistry model (Del Grosso et al. 2005) to quantify environmental burdens. Similar to the PBF study, Kim et al. (2005) measured displacement of fossil fuel derived glycerin production from co-production of glycerin during the transesterification of feedstock. Lardon et al. (2009) conducted a cradle-to-grave LCA of a hypothetical and virtual conversion process from growth of the algae to combustion of liquid biodiesel. The algae conversion process was found to require less land per ton of dry biomass than other biomass sources for bioenergy conversion such as vegetable oil; however, the energy conversion requirements made it less desirable than biodiesel from vegetable oils. Mu et al. (2010) compared emissions of thermochemical and biochemical conversion of lignocellulosic biomass to ethanol using LCA methodology. Their study of scaled-up conversion technologies determined that biochemical conversion emits less GHGs across the production and use life cycle. From these six somewhat disparate studies of biofuel life cycle emissions it is evident that energy use, transportation, up-stream impacts, and the avoided impacts from displaced coproduct production and use are the main concerns when describing a well-to-wheels biofuel conversion system. It is also evident that the majority of LCA studies previously conducted for biodiesel production utilize a significant amount of simulated or projected data. This study incorporates a high percentage of data from the actual scaled-up operation of a biodiesel facility. Because it is not clear from the existing literature whether WVO biodiesel is less polluting than biodiesel from other feedstocks, a deeper analysis of the WVO to biodiesel life cycle is needed. As background information, biodiesel is standardized in the US by the 4

6 American Society for Testing and Materials (ASTM) as defined in ASTM D6751. Additionally, ASTM defines biodiesel as a liquid transportation fuel which contains mono-alkyl esters of long chain fatty acids derived from vegetable oils or animal fats (ASTM, 2012). Biodiesel is produced when free fatty acids are removed from long chain fatty acids and when the transesterification process replaces the ester group with an alcohol group. This reaction occurs in the presence of an aliphatic alcohol (usually methanol) and a base (usually potassium hydroxide), which aids in the binding of the OH - group to the fatty acid (Jørgensen et al. 2012; Knothe 2005). PBF uses methanol to push the reaction with KOH to facilitate biodiesel production. The goal of this study was to compare biodiesel produced from PBF to conventional diesel. Additionally, the impacts of switching from rendered animal fat to WVO feedstock on GHG emissions and NER were compared. A functional unit of 1 MJ of transportation fuel combusted was used for this study. By comparing the fuels on an energy basis, differences in fuel energy density were accounted for fairly. A secondary goal of this LCA was to identify the biggest contributors to net environmental burden across all life cycle stages, to compare the biodiesel production process to conventional diesel fuel, and identify innovative solutions to current waste-streams and emission sources. This study may serve as a basis to qualify PBF biodiesel as renewable under the Renewable Fuels Standards (RFS) and GHG reduction thresholds as outlined by the US Environmental Protection Agency (US EPA, 2012). This qualification may influence the subsidies and governmental benefits PBF could receive in the future. Currently, certain biodiesel quality programs have qualified PBF as the only BQ9000 certified biodiesel producer in North Carolina and the sole in-state supplier of biodiesel for the state government fleet of vehicles (PBF 2012, NBAP 2012). 2.1 Project Scope To compare the GHG implications of using biodiesel produced by PBF to the production and use of conventional diesel, a cradle-to-grave system boundary was selected (Figure 1). Parallel processes represent other production systems such as glycerin, diesel, and electricity. The study sensitivity analysis around the change from poultry lipid waste to WVO was considered using a gate-to-grave analysis alongside the cradle-to-grave LCA study. The effects of biodiesel demand on the regional WVO market are not directly calculated and are considered small at this time; however, the regional market influence may be significant in the future, especially if production levels were to increase rapidly. 5

7 2.2 System Boundaries The biodiesel life cycle for the scenario where no agricultural burdens were allocated to PBF can be represented as a linear flow of materials and energy from WVO collection through to biodiesel combustion. The system boundary in Figure 1 displays the life cycle stages which were included in the PBF study. The results of this LCA are assumed to be valid until the feedstock changes, the baseline data for grid power electricity and GHG emissions for diesel changes, or until the conversion process for WVO to biodiesel changes at PBF. Figure 1: Cradle-to-grave system boundaries of biodiesel production from WVO 2.3 Assumptions It was assumed that the virgin vegetable oil market is not significantly affected by PBF s biodiesel production as the virgin oil market is not affected by the use of a waste-stream that is typically discarded. The market for WVO was assumed to be stable with enough lipid supply to satisfy both the local fat renders and PBF feedstock requirements. The displaced treatment of WVO was assumed to have nominal burdens as compared to the transesterification process. This was assumed only for the 152,164 gallons of WVO used for the PBF conversion facility in Discussions with Lyle Estill (President of PBF) and other biodiesel production facilities have confirmed that no market disruption occurs due to the current levels of WVO use by PBF. The WVO market does not currently utilize all WVO produced for alternative products or services, therefore raw materials for a competing process will not be displaced by use at the PBF facility. A production basis for the material and energy balance will be set at the 2011 annual production level of 126,803 gallons. Furthermore, 2011 GREET values for fuel mileage and emissions associated with biodiesel use are assumed to be representative of emissions for end users of the Piedmont biodiesel. The TRACI impact assessment method was used to calculate the global warming potential (GWP) with updated 100-year GWP values for N 2 O and CH 4 emissions were used: 25 and 298, respectively (IPCC 2007). GWP values are multipliers used to indicate and calculate the magnitude of environmental burden for a substance compared to CO 2. 6

8 3. Methods 3.1 Data Collection Data was collected directly from PBF for materials and energy into and out of the biodiesel processing facility. WVO, methanol, potassium hydroxide, sulfuric acid, and other chemicals used in the conversion process were quantified as kg/mj of energy delivered by biodiesel combustion. Energy usage was quantified for the facility and converted to kilowatthours per gallon of biodiesel produced. Waste streams, including wooden pallets, plastic WVO containers and WVO pretreatment filters, were quantified on a kg/mj of energy delivered by biodiesel combustion. Non-waste by-products from the transesterification process, including glycerol, were quantified on the basis of kg/mj of biodiesel energy produced. Table 1 outlines the initial material stream data and chemical use data collected from the facility. Process data collected during the PBF site visit included throughput of WVO, filtered WVO and B100 biodiesel production yields, chemicals used for the transesterification process, electrical usage, water usage, and collection and distribution strategies. 3.2 System Modeling PBF and GREET Scenarios Emissions due to the combustion of the biodiesel were modeled using the GREET model created by Argonne National Laboratory (Wang 1999, Wang 2001). For comparison, both biodiesel and conventional diesel were modeled using GREET and compared to biodiesel produced at PBF. Two PBF scenarios were analyzed, the first for which no agricultural burdens were allocated to the scenario, the second for which 100% of the agricultural burdens were allocated to the PBF scenario. To perform burden allocation sensitivities, additional data was needed. Allocating the carbon captured in the crop oils (from photosynthesis during biomass growth) is often a key aspect of biofuels studies. The biogenic carbon from growth of vegetation is often described as carbon neutral once released as CO 2 was extracted from the air during growth. The direct GHG emissions impact from burning this biogenic carbon is typically not allocated to the product. The burdens associated with growing the soybean plant are often attributed to the virgin oil and the original use only. This selective credit and burden giving can be seen as bias and was explored in a sensitivity analysis. To understand the impacts of virgin oil production, GREET data was used to allocate the virgin oil burdens associated with production, transportation and processing of the virgin soybean oil for the burden allocation scenario Parallel Systems There are multiple parallel systems pertaining to this study including diesel production, glycerin co-production, and WVO, free fatty acids (FFA) or biodiesel use for transportation and fuel during the production process or during distribution transport. The glycerin and diesel production systems are modeled using the US Life Cycle Inventory (USLCI) database. (US LCI 2012) 7

9 The impacts of using the WVO for fuels can be approached in two ways. First, the WVO systems/ markets are assumed to be in equilibrium meaning that traditional fat renderers are not under-supplied and have met their feedstock requirements. This means that use of WVO (at current levels) does not disturb this market equilibrium. Due to this assumption, it is assumed that the use of WVO for biodiesel would not alter business or environmental impacts of the parallel systems. The second approach would operate under the assumption that there is a WVO shortage and the fat renderer would use the additional WVO to create additional product. As this study is focused on primarily attributional LCA, the first assumption basis was chosen Process Waste Production waste data was collected from Piedmont Biofuels for plastics, waste-water, pallets, and talc filter waste. To model end-of-life scenarios, USLCI waste processes were used for waste water treatment, landfilling, and recycling. Data from Piedmont Biofuels was used to model waste transportation. Solid and liquid waste treatment was modeled using USLCI data. 3.3 Material Balance A material balance was performed using Microsoft Excel (Microsoft 2012) to confirm collected data accuracy by tracking WVO input, raw materials used during the transesterification process, waste streams resulting from the conversion process, co-product streams and biodiesel produced on a mass and energy basis. It was determined that 98% of materials entering the biodiesel life cycle were accounted for as products or waste. This is well within industry accepted parameters and thus the PBF data collected was used for the LCA portion of this study. 3.4 Life Cycle Assessment OpenLCA, a life cycle assessment modeling framework provided by GreenDeltaTC, coupled with the USLCI database and the Argonne National Laboratory GREET model were used to calculate the net environmental impacts of the PBF process and compare those to the net environmental impacts of the conventional fossil fuel diesel lifecycle (GreenDeltaTC 2007, US Life Cycle Inventory database 2012, Wang 2001). All data was standardized to the functional unit of MJ of transportation fuel combusted in a passenger vehicle. Burden allocation was avoided by use of system expansion for the displacement of glycerin production. 3.5 Life Cycle Inventory Table 1 and table 2 contain data collected from PBF entered into the OpenLCA model to determine the magnitude of impact associated with the PBF biodiesel life cycle. 8

10 Table 1: Material flows identified for the LCA and data collected from the facility operator. Table 2: Transportation data for WVO and finished biodiesel. Category Value Units Diesel Transportation kg/year Kilometers Tonne*km Waste Vegetable Oil 529,737 kg/year Pittsboro 37, Filtered WVO 374,316 kg/year Carrboro 30, Biodiesel Produced 331,426 kg/year Raleigh 20, Biodiesel Produced 62,006,311 MJ/year Burlington 12, Methanol 67,920 kg/year Moncure 10, Potassium Hydroxide 6,898 kg/year Private 23, Sulfuric Acid 113 kg/year Four Oaks Wholesaler* 282, Filter Aid 2,150 kg/year Biodiesel at Pump (blended)* 282, Glycerine 118,942 kg/year WVO to Piedmont Biofuels 529, ,660 Process Water 117,861 kg/year Total 1,230, ,471 Waste water 129,180 kg/year * Diesel Transport Used Electricity from Grid 373,921 kwh Electricity from Solar n/a kwh Heat from FFA Boiler 1,636,847 MJ/year 3.6 Net Energy Ratio Past studies have calculated Net Energy Ratio (NER) as parameter to calculate operational efficiency for the biodiesel lifecycle. The NER for this analysis was calculated using NER as defined in Equation 1. (Equation 1) Equation 1: Net Energy Ratio (NER) calculates specific energy balance in/out ratio for PBF facility by dividing the system output by system input energy. NER = Net Energy Ratio (biodiesel energy produced divided by fossil fuel energy input) Ecombustion= embodied energy of the biodiesel produced Etransport = diesel energy used to transport the WVO, wholesale product and mixed product Eelectricity = grid power energy used during conversion of WVO to biodiesel Emethanol = sum of diesel, coal, electricity and crude oil used in the production of methanol EKOH = diesel, coal, electricity and crude oil used in the KOH production process Ewaste = energy used during the end-of-life (EOL) process for the plastic from WVO collection Eglycerol = energy from the avoided fossil-fuel derived glycerol production process The glycerol co-product credit used was -1.3 MJ/kg of biodiesel (Lopez et al. 2010). The remaining values were calculated in this study. 9

11 4. Results The initial results of the LCA indicate a significant decrease in overall environmental burden and a marked decrease in global warming potential from the basecase, which was conventional diesel (low sulfur average scenario) on a cradle-to-grave basis. Figure 2 details the results calculated in the OpenLCA program and the GREET model, as indicated. Additionally, Table 3 compares the different feedstocks across the full life cycle by stage for each of the four fuel scenarios. Table 3: Overview of all four fuel scenarios compared in the study and the global warming potential (in g CO 2 -eq/mj) for each life cycle stage. Process Biodiesel No Burden Biodiesel with Feedstock Burden GREET Biodiesel GREET Diesel Units Feedstock g CO2 eq/mj Fuel Production g CO2 eq/mj Vehicle Operation g CO2 eq/mj Net g CO2 eq/mj Percent reduction over diesel 96% 87% 79% g CO2 eq/mj Biodiesel No Burden Biodiesel with Feedstock Burden GREET Biodiesel GREET Diesel GWP (g CO 2 eq.) Per MJ Fuel Feedstock Fuel Production Vehicle Operation Net Figure 2: Cradle-to-grave net global warming potential for each of the four scenarios. 10

12 4.1 Life Cycle Assessment Cradle to grave GHG emissions resulting from production and use of biodiesel, as seen in Figure 2, were 96% lower than the diesel reference when virgin soybean oil production burdens were omitted. When incorporating 100% of the virgin soybean oil production burdens into the analysis, GHG reductions of 87% were calculated. These values indicated higher GHG reductions than the 79% GHG reductions compared to diesel from GREET. The GHG emissions from the PBF biodiesel life cycle analyzed in this study were 39% and 81% lower than GREET biodiesel results for the burden and no burden scenario, respectively. 4.2 Net Energy Ratio Compared to the 2009 and 2010 life cycle assessments completed for the PBF facility, the net energy ratio (NER) was 2.54:1 renewable energy output to fossil fuel energy input (on a MJ biodiesel : MJ fossil fuel basis). After completing the same calculations for the new feedstock and updated facility, the NER is 7.85:1 (biodiesel to fossil fuel). This was determined by using equation 1 and the no burden scenario. 5. Discussion 5.1 Greenhouse Gases The preliminary results indicate a substantial reduction in GHG emissions across the biodiesel life cycle. Global warming potential (GWP) and greenhouse gas (GHG) emission burdens were calculated on a net basis by summing biogenic and fossil GHGs. Unlike fossil fuel derived CO 2 emissions, biogenic CO 2 originates from plant matter. During soybean and other oil crop plant cultivation, CO 2 is sequestered from the atmosphere through photosynthesis, which offsets the CO 2 released in the combustion: 0 (Equation 2) 5.2 Net Energy Ratio The NER calculation was determined to be the appropriate method for calculating energy use and the process efficiency. It was also appropriate to compare to both previous studies at PBF which used the NER calculation allowing benchmarking against a baseline. This resulted in a 7.85:1 ratio of biodiesel energy produced to fossil fuels consumed. Previous calculations for the PBF facility indicated that the NER might be as low as :1 for the Piedmont Biofuels process. These calculations including human labor as an energy input to the process seemed unnecessary. Additionally, the feedstock for the conversion process was changed from chicken farm fat waste to WVO from soybeans and other plant oils. The feedstock change resulted in greater conversion efficiency. Additionally, the free fatty acid waste stream from the transesterification process is now being utilized in an on-site industrial boiler to create heat, which is used to push the transesterification and water/wvo separation processes. This process change 11

13 eliminated the need for natural gas combustion reducing the GHG burdens associated with the conversion process. Methanol addition was reduced through an optimization of the transesterification process which resulted in less annual use and up-stream GHG burdens for this raw material. 5.3 GREET Comparison In contrast to the GREET model, B100 biodiesel was used for much of the collection and distribution transportation resulting in primarily biogenic CO 2 emissions not counted towards the net GWP. Process heat for the PBF facility was produced from Free Fatty Acid (FFA) waste from the separation and transesterification process. In the GREET biodiesel production process; however, FFAs were not utilized for heat and fossil fuels are burned instead, resulting in higher GHG emissions from fuel production. 6. Study Limitations By comparing the PBF biodiesel with feedstock burdens against the PBF biodiesel without feedstock burdens, it was determined that allocating the agricultural burdens of the virgin vegetable oil, even at 100%, increases the net environmental impact of the fuel by only 9% (GREET data). The agricultural burdens; however, are highly sensitive to land use change emissions not incorporated in this study (Daystar et al. 2012, Searchinger et al. 2008). 7. Conclusions The production and use of biodiesel on a cradle to grave basis from Piedmont biofuels can significantly lower GHG emissions and fossil energy required to produce transportation fuel. These results are specific to the Piedmont Biofuels based on production data from It is worth noting these results may not be valid for future years and larger production levels. Increased production would result in increased WVO demand impacting the rendered fats industry. As previously discussed, the global warming potential impacts of reducing rendered lipids are significant and could negate much of the projected GHG savings. The impact of using virgin soybean oil as opposed to WVO was found to be significant, increasing the net GHGs by around 9%. This increase does not include impacts of land use change. In some biofuels studies indirect land use change has been cited (Daystar et al. 2012, Searchinger et al. 2008) to diminish the net GHG to negligible levels when using virgin oils or result in additional GHG emissions in comparison to diesel. The GHG emissions uncertainty surrounding virgin oil production and consequential land use change further supports the use of WVO as a feedstock for biodiesel production. As GHG emissions reductions were larger than 50% compared to conventional diesel, biodiesel produced by Piedmont biofuels may qualify as an advanced biofuel under the Renewable Fuels Standard. Beyond GHG emission reductions, the production 12

14 and use of PBF biodiesel resulted in significant fossil fuel energy reduction. This reduction in fossil fuel usage has been proposed to increase energy independence, national security, and bolster local economies. 8. Future Work Further analysis will include the retrieval or calculation of additional data such as the electrical production from the PBF solar array, which will offset the grid electricity used at the PBF facility and with it the GWP and other environmental indicators. Although the solar array electricity offset was not calculated for this 2011 study (the array was not installed until 2012) it was determined during this study that electricity is a large portion of the GHG burden associated with biodiesel. A significant amount of grid power is used in the conversion process and offsetting some portion of this grid power, especially for the no-burden scenario, could reduce the GHG burden possibly by 50% of 2011 levels. 13

15 9. References ASTM, (2012) "D b Standard Specification for Biodiesel Fuel Blend Stock (B100) for Middle Distillate Fuels." ASTM D6751.American Society for Testing and Materials.< htm>. Bare, Jane C, Gregory A Norris, and David W Pennington. (2003) TRACI 2.0:The Tool for the Reduction of Chemical and other Environmental Impacts. Journal of Industrial Ecology 6.3-4: Daystar, Jesse S., Carter W. Reeb, Ronalds Gonzalez, Trevor Treasure, Richard Venditti, Stephen Kelley and Bob Abt. (2012) Integrated supply chain, delivered costs and life cycle assessment of several lignocellulosic supply systems for biofuels, bioenergy and bioproducts in the southern U.S. Biofuels, Biorefinery & Bioresources. In Print. Del Grosso, S. J., Mosier, A. R., Parton, W. J., & Ojima, D. S. (2005). Daycent model analysis of past and contemporary soil n2o and net greenhouse gas flux for major crops in the USA. Soil and Tillage Research, 83, Ecoinvent Database. (2012). Swiss Centre for Life Cycle Inventories, < GreenDeltaTC (2007) "The OpenLCA Project and Software."Modular Open Source Software for Sustainability Assessment.Web.< Huo, Hong, Michael Wang, Cary Bloyd, and Vicky Putsche. (2009). "Life-Cycle Assessment of Energy Use and Greenhouse Gas Emissions of Soybean-Derived Biodiesel and Renewable Fuels." Environmental Science and Technology 43: IPCC, (2007) "Changes in Atmospheric Constituents and in Radiative Forcing."IPCC Fourth Assessment Report (AR4).Online, Inter-governmental Panel on Climate Change.Web.< Jørgensen, Andreas, Paul Bikker, and Ivan T. Herrmann. (2005) Assessing the greenhouse gas emissions from poultry fat biodiesel. Journal of Cleaner Production 24:

16 Kim, S. and B.E. Dale, (2005) Life cycle assessment of various cropping systems utilized for producing biofuels: Bioethanol and biodiesel. Biomass and Bioenergy, 29(6): p Knothe, Gerhard. "Dependence of Biodiesel Fuel Properties on the Structure of Fatty Acid Alkyl Esters. (2005) "Fuel Processing Technology 86: Web.< Lardon, L., Helias, A., Sialve, B., Steyer, J.-, & Bernard, O. (2009). Life cycle assessment of biodiesel production from microalgae. Environmental Science & Technology, 43(17), Retrieved from Lopez, Dora E, Joseph C Mullins, and David A Bruce. (2010). Energy Life Cycle Assessment for the Production of Biodiesel from Rendered Lipids in the United States. Industrial & Engineering Chemistry Research 49: Microsoft. (2010). Microsoft Excel Software. Redmond, Washington: Microsoft. Mu, Dongyan, Thomas Seager, P S. Rao, and Fu Zhao. (2010). "Comparative Life Cycle Assessment of Lignocellulosic Ethanol Production: Biochemical versus Thermochemical Conversion." Environmental Management 46: National Renewable Energy Labs (2012), United States Life Cycle Inventory, downloaded database. National Biodiesel Accreditation Program (2012) BQ Biodiesel Quality Management System. ORNL, "Bioenergy Conversion Factors."(2012) Oak Ridge National Laboratory, < Piedmont Biofuels Industrial, LLC. (2012) BQ 9000 Accreditation. website: Terry, S.D., A. Hobbs, Rachel Burton and M. Flickinger. (2009). Energy Balance for Piedmont Biofuels in the Production of Biodiesel Using Rendered Chicken Fat for White Paper: 1-8. US EPA."Renwable Fuels Standard."Fuels And Fuel Additives. United State Environmental Protection Agency, 22 Mar Web.< 15

17 "US Life Cycle Inventory. (2012) " National Renewable Energy Laboratory, Web. < Wang, M. (2001). Development and use of GREET 1.6 fuel-cycle model for transportation fuels and vehicle technologies, Argonne National Lab., IL (US). Wang, Michael. (1999) "The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) Model Version 1.5." Center for Transportation Research, Argonne National Laboratory, < 16