Open Collections

UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Life cycle and techno-economic assessment of transportation biofuels from hydrothermal liquefaction of… Nie, Yuhao 2018

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
24-ubc_2018_september_nie_yuhao.pdf [ 3.83MB ]
Metadata
JSON: 24-1.0368789.json
JSON-LD: 24-1.0368789-ld.json
RDF/XML (Pretty): 24-1.0368789-rdf.xml
RDF/JSON: 24-1.0368789-rdf.json
Turtle: 24-1.0368789-turtle.txt
N-Triples: 24-1.0368789-rdf-ntriples.txt
Original Record: 24-1.0368789-source.json
Full Text
24-1.0368789-fulltext.txt
Citation
24-1.0368789.ris

Full Text

Life Cycle and Techno-economic Assessmentof Transportation Biofuels from HydrothermalLiquefaction of Forest Residues in British ColumbiabyYuhao NieB.Eng., Harbin Institute of Technology, 2015a thesis submitted in partial fulfillment ofthe requirements for the degree ofmaster of applied scienceinThe Faculty of Graduate and Postdoctoral Studies(Chemical and Biological Engineering)the university of british columbia(Vancouver)July 2018© Yuhao Nie, 2018The following individuals certify that they have read, and recommend to the Facultyof Graduate and Postdoctoral Studies for acceptance, the thesis entitled:Life Cycle and Techno-economic Assessment of Transportation Biofuels from Hydrother-mal Liquefaction of Forest Residues in British Columbiasubmitted by Yuhao Nie in partial fulfillment of the requirements forthe degree of Master of Applied Sciencein Chemical and Biological EngineeringExamining Committee:Xiaotao Bi, Chemical and Biological EngineeringSupervisorVladan Prodanovic, Chemical and Biological EngineeringSupervisory Committee MemberAnthony Lau, Chemical and Biological EngineeringSupervisory Committee MemberAdditional ExaminerAdditional Supervisory Committee Members:Supervisory Committee MemberSupervisory Committee MemberiiAbstractBiofuels from hydrothermal liquefaction (HTL) of abundantly available forest residuesin British Columbia (BC) can potentially make great contributions to reduce the green-house gas (GHG) emissions from the transportation sector. Life cycle and techno-economic assessment are conducted to evaluate the environmental and economic per-formance of a hypothetic 100 million liters per year (MLPY) HTL biofuel system inthe Coast Region of BC based on three different supply chain designs.The life cycle GHG emission of HTL biofuels ranges from 17.0-20.5 g CO2-eq/MJ, cor-responding to 78%-82% reduction compared with petroleum fuels. A further reductionof 6.8 g CO2-eq/MJ can be achieved when by-product biochar is applied for soil amend-ment. The conversion stage dominates the total GHG emissions, making up more than50%. The process emitting most GHGs over the life cycle of HTL biofuels is HTLbuffer production. Transportation emissions can be lowered by 83% if forest residuesare converted to bio-oil before transportation. Process performance parameters (e.g.,HTL energy requirement and biofuel yield) and the location specific parameter (e.g.,electricity mix) have significant influence on the GHG emissions of HTL biofuels.The economic analysis shows that the minimum selling price (MSP) of HTL biofuelsranges from $0.82-$0.90 per liter of gasoline equivalent, which is about 63%-80% higherthan that of petroleum fuels. Converting forest residues to bio-oil and wood pelletsbefore transportation can significantly lower the variable operating cost but not theMSP of HTL biofuels, due to the considerable increase in capital investment. Bio-oil and biofuel yield can significantly influence the MSP of HTL biofuels. Therefore,technology advancement is needed to bring down the production cost of HTL biofuels,otherwise, a high carbon tax can be applied to make HTL biofuels competitive withpetroleum fuels.iiiLay SummaryTo date, there has been nearly no large-scale commercial plants reported for drop-inbiofuels production using sustainable feedstock like forest residues, which are abun-dantly available but under-utilized in British Columbia (BC). Many of the currentstudies on biofuels focus on addressing the technical bottlenecks and there has beenvery limited comprehensive evaluation of the environmental and economic performanceof the conversion technologies, let alone a study based on BC’s specific context.In this thesis, we have identified a promising but under-studied thermochemical con-version technology called hydrothermal liquefaction (HTL) and quantified the envi-ronmental and economic impacts of deploying a HTL biofuel system in BC based ondifferent supply chain designs. Since there has been no similar study before, the re-sults of this study can help provide a preliminary insight for other researchers and localcompanies or investors as well as a reference for government policy makers.ivPrefaceThe research work presented in this thesis was completed under the supervision ofDr. Xiaotao Bi. The author, Yuhao Nie conducted literature review, identified theresearch problems, developed the research goals, and collected the data to build thelife cycle and economic models and analyzed the results. The publications below werefirst drafted by Yuhao Nie and then refined with the help of Dr. Xiaotao Bi.A version of Chapter 3 has been published:Yuhao Nie and Xiaotao Bi. Life-cycle assessment of transportation biofuels fromhydrothermal liquefaction of forest residues in British Columbia. Biotechnology forBiofuels, 11:23, 2018.Part of the results from Chapter 3 has also been presented:Yuhao Nie and Xiaotao Bi. Life cycle assessment of bio-jet fuel production fromhydrothermal liquefaction of forest residues in British Columbia (oral & poster presen-tation), Advanced Biofuels Symposium, Vancouver, Canada, July 2016.A version of Chapter 4 has been published:Yuhao Nie and Xiaotao Bi. Techno-economic assessment of transportation biofuelsfrom hydrothermal liquefaction of forest residues in British Columbia. Energy, 153:464-475, 2018.vTable of ContentsAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiiLay Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ivPreface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vTable of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viList of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ixList of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiiList of Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xivAcknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xviiDedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xviii1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Thermochemical Conversion Pathways . . . . . . . . . . . . . . . . . . 31.3 Environmental and Economic Assessment . . . . . . . . . . . . . . . . . 61.3.1 Life Cycle Assessment (LCA) . . . . . . . . . . . . . . . . . . . 61.3.2 Techno-economic Assessment (TEA) . . . . . . . . . . . . . . . 101.4 Research Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141.5 Objectives and Implications . . . . . . . . . . . . . . . . . . . . . . . . 161.6 Structure of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17vi2 Description of Case Study and Processes . . . . . . . . . . . . . . . . 182.1 Case Study and Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . 182.2 Description of Processes . . . . . . . . . . . . . . . . . . . . . . . . . . 202.2.1 Biomass Collection . . . . . . . . . . . . . . . . . . . . . . . . . 222.2.2 Transportation . . . . . . . . . . . . . . . . . . . . . . . . . . . 242.2.3 Pre-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252.2.4 Conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262.2.5 Distribution and End Use . . . . . . . . . . . . . . . . . . . . . 313 HTL biofuel LCA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323.1 LCA Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323.1.1 Goal and Scope Definition . . . . . . . . . . . . . . . . . . . . . 323.1.2 Life Cycle Inventory Analysis . . . . . . . . . . . . . . . . . . . 333.1.3 Impact Assessment . . . . . . . . . . . . . . . . . . . . . . . . . 343.1.4 Handling of By-product . . . . . . . . . . . . . . . . . . . . . . 353.2 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 353.2.1 Life Cycle GHG Emissions . . . . . . . . . . . . . . . . . . . . . 353.2.2 Comparison with Peer-reviewed Literature . . . . . . . . . . . . 373.2.3 Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 393.2.4 Improving the GHG Performance of HTL Biofuels . . . . . . . . 423.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 444 HTL biofuel TEA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454.1 Economic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454.1.1 Feedstock Delivered Cost . . . . . . . . . . . . . . . . . . . . . . 454.1.2 Capital Investment . . . . . . . . . . . . . . . . . . . . . . . . . 504.1.3 Operating Cost . . . . . . . . . . . . . . . . . . . . . . . . . . . 504.1.4 Minimum Selling Price . . . . . . . . . . . . . . . . . . . . . . . 534.2 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 544.2.1 Cost Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . 544.2.2 Comparison with Peer-reviewed Literature . . . . . . . . . . . . 554.2.3 Impact of Carbon Tax and Technology Advancement . . . . . . 574.2.4 Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 594.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60vii5 Conclusion and Future Work . . . . . . . . . . . . . . . . . . . . . . . 62Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76A Mass and Energy Balances . . . . . . . . . . . . . . . . . . . . . . . . . 76A.1 Stream Flow Diagrams . . . . . . . . . . . . . . . . . . . . . . . 76A.2 Tabulated Mass and Energy Balances Data . . . . . . . . . . . . 77B Process Emission Factors . . . . . . . . . . . . . . . . . . . . . . . . . . 85B.1 Biomass Collection and Transportation . . . . . . . . . . . . . . 86B.2 Pre-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88B.3 Conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92B.4 Biofuels Distribution and End Use . . . . . . . . . . . . . . . . 93B.5 Biochar Application . . . . . . . . . . . . . . . . . . . . . . . . 94C Detail Stage-wise Emission Results . . . . . . . . . . . . . . . . . . . . 95C.1 Biomass Collection . . . . . . . . . . . . . . . . . . . . . . . . . 95C.2 Transportation . . . . . . . . . . . . . . . . . . . . . . . . . . . 96C.3 Pre-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97C.4 Conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98C.5 Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99C.6 End Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100D Detail Stage-wise Cost Results . . . . . . . . . . . . . . . . . . . . . . . 100D.1 Feedstock Delivered Cost . . . . . . . . . . . . . . . . . . . . . . 101D.2 Capital and Operating Costs of Biorefinery . . . . . . . . . . . . 101D.3 Operating Cost of Oil Refinery . . . . . . . . . . . . . . . . . . 105D.4 Capital and Operating Costs of Pellet Plant . . . . . . . . . . . 106E DCFROR Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108viiiList of TablesTable 1.1 Technical comparisons of thermochemical conversion pathways . . . 11Table 1.2 Review of LCA studies on thermochemical conversion of lignocellu-losic biomass to transportation biofuels . . . . . . . . . . . . . . . . 12Table 1.3 Review of TEA studies on thermochemical conversion of lignocellu-losic biomass to transportation biofuels . . . . . . . . . . . . . . . . 15Table 2.1 Annual forest residues availability in BC Coast Region . . . . . . . . 20Table 2.2 Equipment energy input for biomass collection modeling . . . . . . . 22Table 2.3 Parameters for calculating forest residues requirement . . . . . . . . 23Table 2.4 Energy input for feedstock transportation modeling . . . . . . . . . 24Table 2.5 Annual forest residues supply at each FDP for different scenarios (drytonne/yr) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25Table 2.6 Energy input of feedstock pre-processing in biorefinery . . . . . . . . 25Table 2.7 Major inputs and parameters for modeling HTL biorefinery processes 28Table 2.8 Major inputs and parameters for modeling oil refinery proces . . . . 29Table 2.8 Major inputs and parameters for modeling oil refinery proces (con-tinued) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Table 3.1 Contribution of each process to the GHG emissions of HTL biofuels 38Table 3.2 List of parameters used for sensitivity analysis . . . . . . . . . . . . 40Table 4.1 Assumptions for machinery cost estimation . . . . . . . . . . . . . . 47Table 4.2 Annual machinery cost summary ($/yr/machine) . . . . . . . . . . . 48Table 4.3 The number of machines required at each FDP . . . . . . . . . . . . 49Table 4.4 Assumptions for transportation cost estimation . . . . . . . . . . . . 49Table 4.5 Methods for estimating the capital investment of the HTL biofuelsystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51ixTable 4.6 Methods for estimating the operating cost of the studied HTL biofuelsystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52Table 4.7 Major assumptions for DCFROR analysis . . . . . . . . . . . . . . . 53Table 4.8 Estimated costs for the HTL biofuel system . . . . . . . . . . . . . . 57Table A.1 Mass balance of pre-processing for each scenario . . . . . . . . . . . 78Table A.2 Energy balance of pre-processing for each scenario . . . . . . . . . . 78Table A.3 Mass balance of HTL for each scenario . . . . . . . . . . . . . . . . . 79Table A.4 Energy balance of HTL for each scenario . . . . . . . . . . . . . . . 80Table A.5 Mass balance of AD for each scenario . . . . . . . . . . . . . . . . . 81Table A.6 Energy balance of AD for each scenario . . . . . . . . . . . . . . . . 82Table A.7 Mass balance of hydrotreating for each scenario . . . . . . . . . . . . 82Table A.8 Energy balance of hydrotreating for each scenario . . . . . . . . . . . 83Table A.9 Mass balance of hydrogen production for each scenario . . . . . . . . 84Table A.10 Energy balance of hydrogen production for each scenario . . . . . . . 85Table B.1 Diesel and marine diesel production and delivery emission factors . . 86Table B.2 Biomass collection equipment operation emission factors . . . . . . . 87Table B.3 Transportation emission factors . . . . . . . . . . . . . . . . . . . . . 87Table B.4 Wood pellet plant operation Emission factors [1] . . . . . . . . . . . 88Table B.5 British Columbia (BC) electricity mix profile and electricity genera-tion and distribution efficiency . . . . . . . . . . . . . . . . . . . . . 89Table B.6 Alberta electricity mix profile and electricity generation and distri-bution efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Table B.7 British Columbia (BC) electricity generation emission factors [2] . . 90Table B.8 Alberta electricity generation emission factors [2] . . . . . . . . . . . 91Table B.9 Materials production and delivery emission factors of conversion stage 92Table B.10 Downstream emission factors of conversion stage . . . . . . . . . . . 93Table B.11 Biofuels combustion in vehicle and jet engines emission factors . . . 94Table B.12 Nitrogen fertilizer production and delivery emission factors . . . . . 95Table C.1 Emission inventory of biomass collection for each scenario (kg/yr) . 95Table C.2 Emission inventory of feedstock transportation for each scenario (kg/yr) 96Table C.3 Emission inventory of pre-processing for each scenario (kg/yr) . . . . 97Table C.4 Emission inventory of conversion for each scenario (kg/yr) . . . . . . 98Table C.5 Emission inventory of distribution (kg/yr) . . . . . . . . . . . . . . . 99Table C.6 Emission inventory of end use(kg/yr) . . . . . . . . . . . . . . . . . 100xTable D.1 Summary of feedstock delivery cost breakdown for different scenarios($/yr) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101Table D.2 The reference equipment installed and purchased costs of biorefinery 101Table D.3 Capacity, feed rate and productivity of biorefinery and wood pelletplants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102Table D.4 Capital investment of biorefinery for studied scenarios . . . . . . . . 103Table D.5 Operating cost of biorefinery for studied scenarios . . . . . . . . . . 104Table D.6 Operating cost of oil refinery for studied scenarios . . . . . . . . . . 105Table D.7 The reference equipment purchased cost and installation factor ofwood pellet plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106Table D.8 Capital investment of wood pellet plants for Wp-CIR scenario . . . . 107Table D.9 Operating cost of wood pellet plants for Wp-CIR scenario . . . . . . 108Table E.1 The DCFROR analysis spreadsheet for Fr-CIR scenario . . . . . . . 109Table E.2 The DCFROR analysis spreadsheet for Bo-DBR scenario . . . . . . 111Table E.3 The DCFROR analysis spreadsheet for Wp-CIR scenario . . . . . . 113xiList of FiguresFigure 1.1 Schematic diagram of biomass-to-biofuels thermochemical conver-sion processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4Figure 1.2 LCA framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7Figure 1.3 Project cost estimation framework . . . . . . . . . . . . . . . . . . 13Figure 2.1 Schematic diagram of geographic information of HTL biofuel sys-tem (Powell River, Squamish and Chilliwack lie in the South CoastRegion; Port Alberni lies in the West Coast Region) . . . . . . . . . 19Figure 2.2 Supply chain designs of HTL biofuel system for each scenario (thedash line arrows stand for the flow of feedstock or intermediate prod-ucts and the solid line arrows stand for the flow of final biofuel prod-ucts) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Figure 2.3 Process flow diagram of pre-processing and conversion stages forintegrated and distributed system (Fr-CIR and Wp-CIR scenariosbelong to integrated system,while Bo-DBR scenario belongs to dis-tributed system) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26Figure 3.1 The system boundary of different HTL biofuel scenarios (AD: anaer-obic digestion; NG: natural gas; PHWW: post HTL waste water) . 33Figure 3.2 Stage-wise GHG emissions of HTL biofuels from three different sce-narios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36Figure 3.3 Comparison of HTL biofuels life cycle GHG emissions with literatures 39Figure 3.4 Sensitivity analysis of net life cycle GHG emissions of HTL biofuels 41Figure 3.5 Impact of electricity mix on net life cycle GHG emissions of HTLbiofuels for different scenarios . . . . . . . . . . . . . . . . . . . . . 42xiiFigure 4.1 Detailed installed equipment cost and operating cost of studied HTLbiofuel scenarios (the pie chart in part (b) represents the distributionof the feedstock cost) . . . . . . . . . . . . . . . . . . . . . . . . . . 56Figure 4.2 MSP of HTL biofuels from this study and literatures . . . . . . . . 58Figure 4.3 Impact of carbon tax on petroleum fuel and HTL biofuels price (car-bon tax was converted from Canadian dollars to US dollars usingexchange rate of 1 CAD = $0.81; NPP: net petroleum price; NMSP:net minimum selling price) . . . . . . . . . . . . . . . . . . . . . . . 59Figure 4.4 Sensitivity analysis of the MSP of HTL biofuels for different scenarios 61Figure A.1 The stream flow diagram of Fr-CIR scenario . . . . . . . . . . . . . 76Figure A.2 The stream flow diagram of Bo-DBR scenario . . . . . . . . . . . . 77Figure A.3 The stream flow diagram of Wp-CIR scenario . . . . . . . . . . . . 77xiiiList of AcronymsAB AlbertaAD Anaerobic DigestionASTM American Society for Testing and MaterialsBC British ColumbiaBo-DBR Bio-oil from Distributed Biorefineries to Central Oil RefineryCAD Canadian DollarDCFROR Discounted Cash Flow Rate of ReturnFCI Fixed Capital InvestmentFDP Feedstock Delivery PointFOC Fixed Operating CostFr-CIR Forest Residues to Central Integrated RefineryGHG Greenhouse GasGHSV Gas Hourly Space VelocityHHV Higher Heating ValueHTL Hydrothermal LiquefactionIC Indirect CostIPCC Intergovernmental Panel on Climate ChangexivIRR Internal Rate of ReturnLCA Life Cycle AssessmentLGE Liter Gasoline EquivalentLHSV Liquid Hourly Space VelocityLTT Liquid Tanker TruckMACRS Modified Accelerated Cost Recovery SystemMLPY Million Liters Per YearMSP Minimum Selling PriceNG Natural GasNMSP Net Minimum Selling PriceNPP Net Petroleum PriceNPV Net Present ValueNREL National Renewable Energy LaboratoryOC Operating CostPHWW Post HTL Waste WaterPNNL Pacific Northwest National LaboratorySC Start-up CostST Semi-trailerTCI Total Capital InvestmentTEA Techno-economic AssessmentTIC Total Installed CostTSA Timber Supply AreaxvTPEC Total Purchased Equipment CostVOC Variable Operating CostWC Working CapitalWp-CIR Wood Pellet from Distributed Pellet Plants to Central Integrated RefineryWTT Well-to-TankWTW Well-to-WheelWTWa Well-to-WakexviAcknowledgmentsI would like to first give my genuine thanks to my supervisor Dr. Xiaotao Bi. Hispassion and meticulousness about research has been an exceptional example for methroughout my degree and to carry with in my future career. Dr. Bi is not only astrong academic guide for me, but also a mentor who supports my professional devel-opment and career goals. I appreciate many precious research opportunities he gaveme during my time at UBC. I also want to thank Dr. Vladan Prodanovic and Dr.Anthony Lau for serving as my thesis committee members. Thanks to them for takingtime to review my thesis and giving me helpful suggestions to improve it.I am highly grateful for BiofuelNet Canada, the Boeing Company and Mitacs whokindly provided the funding and made this research project possible.Next, I would like to acknowledge the following colleagues from Dr. Bi’s group whogave me insightful suggestions and assistance in my research: Huimin, Siduo, andHaoqi. Thanks to them for unselfish donation of their time to discuss and brainstormwith me about my research problems.I also owe a great deal of gratitude to my friends: Li, Siqi, Acong, Mengshi, Zhenguo,Pu, Yige and Yong. They are always supportive when I am down and being a sourceof happiness. I cannot imagine how solitary the life would be without them.Last but not the least, I would like to give my sincerest thanks to my family, myfather, Youzhang, my mother, Qiaoling, and my girlfriend, Chenfang, for their constant,unconditional love and support. I appreciate their trust and understanding of everyimportant choice I made. Everything I do is because of them.xviiDedicationTo my beloved parentsxviiiChapter 1Introduction1.1 BackgroundBritish Columbia (BC) government released its Bioenergy Strategy in 2008 and recog-nized bioenergy as a critical approach to help BC achieve its greenhouse gas (GHG)emission reduction goals and economic objectives [3]. By 2013, a bioenergy sector hasbeen established in BC, including 726 MW electricity capacity from pulp and papermills, 2400 kW biogas system, 30 community bio-heat installations and 2-million-tonnecapacity of wood pellets [4]. Besides, insights have been shed on developing a liquidbiofuel industry in BC to help the transportation sector get rid of high reliance onfossil fuels and mitigate GHG emissions [5].In BC, transportation consumes nearly 85% of total refined petroleum fuels [6] and gen-erated about 25 million tonnes of carbon dioxide equivalent (CO2-eq) in 2014, whichcorresponds to approximately 38% of total GHG emissions and leads all other economicsectors [7]. To address the concerns of global warming, BC government released its Cli-mate Action Plan in 2008 and set up step-wise GHG emission reduction targets. Theinterim and ultimate targets aim at achieving 33% and 80% GHG reduction below 2007level by 2020 and 2050, respectively [8]. Besides the improvements in technology andoperation efficiencies of transportation, displacing fossil fuels with biofuels is expectedto make important contributions in reducing the GHG emissions. In 2050 RenewableCity Strategy, Vancouver proposed to replace all transportation fossil fuels with re-newable hydro-electricity and biofuels, demanding the development of low-carbon andrenewable transportation fuels [9].1Biofuels that are functionally equivalent to petroleum fuels and are fully compatiblewith existing petroleum infrastructure are called “drop-in” biofuels [10]. This type ofbiofuels is attractive and promising becasue it avoids the huge capital investment associ-ated with retrofitting existing petroleum infrastructure or building new infrastructure.Several pathways to produce drop-in biofuels include: oleochemical pathway, such asthe hydroprocessing of lipid feedstocks extracted from oil seeds or animal fat; thermo-chemical pathway, such as the thermochemical conversion of lignocellulosic biomass tointermdiates (syn-gas or bio-oil) with subsequent catalytic upgrading to hydrocarbons;and biochemical pathway, such as the biological conversion of biomass (e.g., sugar,starch, or lignocellulosic biomass) to longer chain alcohols as intermediates followed bycatalytic upgrading to hydrocarbons [10].To date, only oleochemical pathway is technically mature, and it has been the mainsupplier of biofuels that have been approved for commercial application in sectors likeaviation and have a defined ASTM (American Society for Testing and Materials) spec-ification [10–12]. It is anticipated that in the near term, the vast majority of drop-inbiofuels will still be produced via oleochemical pathway. However, significant expansionof this pathway is constrained by: (1) the high cost of lipid feedstocks; (2) sustainabilityissues such as occupation of arable lands for producing the feedstocks and food secu-rity; (3) competing with other value-added markets like food and cosmetics industries.Compared with thermochemical pathway, biochemical pathway typically provides loweryield of more oxygenated intermediate products, such as carboxylic acids, alcohols andpolyols, which often possess a higher value in the rapidly growing bio-chemicals marketsthan they do as upgrading to biofuels [10]. Therefore, it is likely that thermochemicalpathway would account for a large amount of growth in drop-in biofuels production inthe mid-to-long term, and probably it will share the markets with biochemical path-way after the bio-based chemicals markets are saturated [10]. The current challengesfor thermochemical pathway lie in the technical side. It requires further technologyadvancement and process optimization to improve the conversion efficiency, addressthe technology risks for scale-up and bring down the high capital investment.Forest residues from logging operations, which contain branches, barks, tree tops, etc.,are generally of no merchantable value and are burned as part of the forestry manage-2ment strategy in BC [13]. According to Industrial Forestry Service Ltd., the volumeof woody biomass potentially available for bioenergy production and surplus to thedemand of existing forestry industry in BC in 2016 is estimated to be around 21 mil-lion m3, of which 15.7% is forest logging residues [14]. Forest residues also make up5%∼10% of the feedstock of BC wood pellet industry, which produces about 2 milliontonnes of pellets annually, representing 61% of the total capacity of Canada [4]. How-ever, 94% of the produced pellets ends up being exported due to a lack of markets inBC, among which 84% is exported to Europe for district heating and power generation[15, 16]. This is because in BC, residential heating is mostly done by electricity andnatural gas (NG), and more than 90% power is generated from hydro [17]. Accordingto Pa et al. [1], the long distance transportation of pellets could also result in a highcarbon footprint (295 kg CO2-eq/tonne of pellets). Thus, the shift of abundant forestresidues in BC for liquid biofuel production can be a promising strategy to meet its2050 renewable transportation target.In view of the overall promise for large-scale commercialization in the mid-to-long termand the abundantly available forest residues as feedstock in BC, only thermochemicalpathway will be focused on in later context of this thesis.1.2 Thermochemical Conversion PathwaysThermochemical conversion of forest residues to intermediate products, such as bio-oiland syngas, with subsequent catalytic upgrading to finished products can be used fordrop-in transportation biofuels production in BC. These thermochemical conversionpathways include gasification followed by Fisher-Tropsch synthesis, pyrolysis followedby hydroprocessing and hydrothermal liquefaction (HTL) followed by hydrotreating[18]. The high-level processes of biomass-to-biofuels thermochemical conversion areshown in Figure 1.1.Table 1.1 shows the comparisons of three different thermochemical conversion path-ways, including gasification, pyrolysis and HTL, based on a few technical criteria, i.e.,feedstock quality requirement, reaction conditions, intermediate products quality, andcurrently reported technology scale. The conversion pathways are ranked based on eachcriterion using characters MF (most favorable), N (neutral) and LF (least favorable)3to indicate their relative favorability.Biomass Feedstock Thermochemical ConversionIntermediate Products: Bio-oil or SyngasCatalytic UpgradingBiofuel ProductsGasolineJet fuelDieselHeavy oil• Pyrolysis• Gasification• Hydrothermal liquefaction• Hydroprocessing• Fisher-Tropsch Synthesis• Hydrotreating• Lignocellulosic biomassFigure 1.1: Schematic diagram of biomass-to-biofuels thermochemical conversion processesFeedstock quality requirement Pyrolysis and HTL generally require fine par-ticle size, i.e., less than or equal to 3 mm [20, 22], while gasification is not that strict,with particle less than 2.0 to 2.5 inch (equivalent to 50.8∼63.5 mm) being preferred [19].Both pyrolysis and gasification require control of the moisture content of feedstock toensure healthy process operation and product quality, so pre-drying is usually needed.In contrast, HTL doesn’t have any requirement for the moisture content of feedstocksince it is essentially a process that decomposes biomass in an aqueous condition, thusavoiding the energy-intensive pre-drying process.Reaction conditions Pyrolysis can be achieved in a simple atmospheric pres-sure with moderate temperature (400∼500 ◦C) [20]. Gasification and HTL need moresevere conditions. HTL happens under moderate temperature (280∼370 ◦C) and highpressure (10∼25 MPa) in order to keep water in a subcritical or critical condition wherewater can have special properties [23]. Gasification also requires high temperature andpressure, typically 600∼1000 ◦C [19, 24] and 20∼70 bar (equivalent to 2∼7 MPa) [22].Intermediate product quality Gasification produces syn-gas which containsmainly carbon monoxide (CO) and hydrogen (H2). Before sent to Fisher-Tropsch syn-thesis, it first needs removal of tar and other impurities to prevent the contaminationof downstream equipment, followed by reforming to a desired H2/CO ratio via water-gas shift reaction. Pyrolysis and HTL both generate a crude-oil-like product called4bio-oil. Although pyrolysis-based bio-oil has nearly two times of yield compared withHTL-based bio-oil, it is generally of low quality, i.e., high oxygen content (35∼40 wt%)[27] and low heating value (16∼18 MJ/kg, higher heating value (HHV) basis) [29].Besides, it requires an additional step of hydrotreating to stabilize before it can beupgraded [26]. In contrast, HTL can produce high quality and stable bio-oil with loweroxygen content (5∼15 wt%) [28] and higher heating value (30∼37 MJ/kg, HHV basis)[23] which has the potential to be directly co-processed with crude oil in a refinery[26, 30, 38].Technology scale The commercialization of gasification of biomass is challengedby huge initial capital investment associated with the facility requirement under hightemperature and pressure as well as the technologies for syn-gas cleaning [24]. Hence,only plant with a large scale can make economic sense. No commercial scale biomassgasification plant has been reported, although there are some pilot- and demonstration-scale plants. Total S.A. and five other companies launched the BioTfueL project whichhas started building a demonstration platform that is scheduled to come on stream in2017 [34]. Pyrolysis is the most mature technology among these three pathways. It hasalready reached the commercial scale as reported by companies like Ensyn-UOP andBTG BioLiquids. Ensyn-UOP’s RTP® technology, essentially fast pyrolysis, with 3million gallons per year bio-oil production, has been proven to be practically and com-mercially feasible [36]. The main hurdle for commercialization of HTL is also the highcapital investment for developing the reaction system [23]. Two well-known corpora-tions who play the leading role in HTL technology development are Licella and SteeperEnergy. In 2016, Licella reported that their HTL facility has successfully demonstratedthe conversion of wood and agriculture wastes at large pilot scale [33], and recently,it has announced to collaborate with a Canadian wood product company Canfor toform a joint venture to integrate its HTL technology with Canfor’s pulp mills in PrinceGeorge, BC, to convert woody biomass to biofuels [39]. The commercial-scale plantis scheduled to be constructed in 2019 with a capacity of 125,000 tonnes of slurry peryear [33]. Steeper Energy Company has also had several sites under development foran industrial scale demonstration plant in Europe and North America to test the per-formance of various feedstock for HTL bio-oil production and optimize its processes toaddress the technical and economic issues for scale-up [40].51.3 Environmental and Economic AssessmentBesides resolving the technology bottlenecks, the environmental and economic impactsof a certain technology are important aspects to be considered before commercializa-tion. This section will introduce a commonly utilized technique for environmental andeconomic assessment, each followed by a literature review of the state-of-art studies onevaluating the environmental and economic performance of the three thermochemicalconversion technologies previously described.1.3.1 Life Cycle Assessment (LCA)Life cycle assessment (LCA) is a technique used to quantitatively assess the environ-mental impacts of a product or a service from cradle to grave, i.e., from raw materialextraction, manufacture to distribution, end use and disposal or recycling. The system-atic and quantitative features have provided LCA an advantage of offering a completeprofile of the environmental impacts of the analyzed products or services and facili-tating the identification of the “hot spots”. Thus, LCA has become a popular tool inrecent years in product design and various decision making processes ([41], [42], [43],[44]). The ISO 14040 [45] has recommended a standard procedure for conducting anLCA, including the following four phases: (1) goal and scope definition; (2) life cycleinventory analysis; (3) impact assessment; and (4) interpretation, which is illustratedby Figure 1.2. A general LCA methodology will be introduced below, and the specificLCA model of this study will be described in Section 3.1 of Chapter 3.Goal and scope definition An LCA starts with the goal and scope definition.The goal is essentially the reason why you want to carry out such an LCA. It shouldbe clearly stated at the beginning and be consistent with the intended application andaudience [45]. The definition of the scope includes the following specific activities:1. Definition of the system boundary This is to delimitate the processes to beincluded and excluded in the analysis of the system. It is subjective and dependson how detailedly you want to study the system as well as the data availability.Any assumptions you made should be specified at this stage. For example, if youconduct an LCA of a certain product, you might need to think about whether ornot to include the construction of the factory in your boundary.6Goal and Scope DefinitionSystem boundary, Functional unit, Allocation  Life Cycle Inventory AnalysisData SourcesIndustrial data, Recognized database, Peer-reviewed articles, Technical reports, etc.Life Cycle InventoryBuild-upExcel SpreadsheetLife Cycle SoftwareGHGenius, GREET, SimaProImpact AssessmentCharacterization, Normalization, WeightingInterpretationFigure 1.2: LCA framework2. Identification of the functional unit Functional unit defines what exactly isbeing studied and indicates the service delivered by the product [46]. The finalenvironmental impact results should be presented based on the functional unit youselected. Furthermore, functional unit enables the comparison of alternative prod-ucts from different systems. For example, if you want to compare the environmentalimpacts of coal and natural gas for power generation, you can set functional unit tobe 1 MWh of electricity generated.3. Selecting the allocation methods Allocation is used to assign the environmentalburdens between the main product and the co- or by-products, which is usually dealtwith in one of the three ways: system expansion, substitution and partition. ISO14041 [47] suggests that partition should be avoided whenever possible throughexpansion of the system or division of the multifunction process into sub-processes.Where partition cannot be avoided, it should be done between the system’s differentproducts based on the physical relationships such as mass and energy content. Ifthe physical relationship cannot be established or used as the basis for partition,7economic value of the products can be used.Life cycle inventory analysis In this phase, a flowchart of the system is usuallyconstructed first. The goal of building the life cycle inventory is to complete the massand energy flows of each process of the system by collecting and compiling the datafrom various sources. Generally, there are two types of data sources, i.e., primary dataand secondary data. Primary data, i.e., the industrial operation or monitoring data,are preferred if they are provided or they can be obtained from survey or interview,because this type of data is more specific and accurate. Otherwise, secondary data canbe used, including recognized LCA database such as Ecoinvent [48] and USLCI [49],peer-reviewed literature, and technical reports from government or authorized scien-tific organizations like PNNL (Pacific Northwest National Laboratory) and NREL (Na-tional Renewable Energy Laboratory), etc. LCA software such as SimaPro, GREETand GHGenius, with built-in process models, can be used to model the processes suchas material manufacture, fuel production and product transportation. Once the datahave been collected, mass and energy balances need to be done to calculate the materialand energy inputs and outputs of each process. Inputs consider resources, materials,energy from nature or technosphere, while outputs cover products, wastes and emis-sions, etc. The emissions of a process can usually be estimated by multiplying theconsumption of materials or secondary energy by its corresponding emission factors,which can be obtained from the LCA databases mentioned above or open literature.Impact assessment With the life cycle inventory compiled, the environmen-tal impacts can be quantified. There are different impact categories, such as globalwarming, ozone layer depletion, aquatic eutrophication, acid rain formation and Non-renewable energy consumption. One or a few impact categories can be choosen de-pending on the goal of the LCA. Each impact category has a benchmark compoundand the environmental impacts can be quantified and presented in the unit of, say,grams of benchmark compound equivalent. For example, the benchmark compoundof global warming impact is carbon dioxide (CO2), while the benchmark compound ofacid rain formation is sulfur dioxide (SO2). The emission data from the life cycle in-ventory can be characterized to the benchmark compound equivalent by the potentialfactors of each impact category. The potential factors indicate the relative capabilityof a certain compound contributing to the environmental impact compared with thebenchmark compound. Taking global warming impact as an example, the potential8factors for methane (CH4) and nitrous oxide (N2O) are 25 and 298, respectively, re-lated to CO2 on a 100-year basis [50]. Normalization (using, for example, the domesticor regional emission as the benchmark to normalize the corresponding characterizedenvironmental impact) and weighting (subjectively assigning weighting factor to eachimpact category) might be done then, if needed, to obtain a single integrated result.Interpretation Interpretation phase is to identify the hot spots and evaluate theinformation from the results of life cycle impact assessment and inventory analysisphases. Besides, the limitations and uncertainties of the study will be reviewed, sen-sitivity of key parameters will be checked, and recommendations for improving theenvironmental performance of the products or services will be communicated.The life cycle of transportation fuels is also referred to as well-to-wheel (WTW) orwell-to-wake (WTWa), and the whole upstream related to biofuel production and dis-tribution is usually called well-to-tank (WTT). Numerous LCA studies has been per-formed to quantify the GHG emissions of transportation biofuels from thermochemicalconversion of lignocellulosic biomass based on a systematic review of the state-of-art lit-erature. The criteria of selecting the literature for review are as follow: (1) only studiesassessing thermochemical conversion technologies, i.e., pyrolysis, gasification and HTLwere included; (2) only studies focused on the lignocellulosic biomass were included,because this type of feedstock is abundantly available in BC with an established supplychain. Other types of feedstock like oil seed or algae are either unsustainable over longterm nor short of stable supply; (3) only LCA studies on the following liquid trans-portation fuels were included: jet, gasoline and diesel, while ethanol was not considered.Wong [51] studied the life cycle GHG emissions of gasification-based bio-jet fuel fromforest residues and corn stover, and the results showed that they could reduce GHGemissions by 86% and 94%, respectively, relative to conventional petroleum jet baseline85 g CO2-eq/MJ. Han et al. [52] conducted an LCA to compare the WTWa GHG emis-sions of fast pyrolysis-based bio-jet and gasification-based jet fuel using corn stover asfeedstock, and found that the net GHG emissions per MJ of pyrolysis-based bio-jet is22.1 g CO2-eq if bio-product biochar is applied for soil amendment or 29.4 g CO2-eq ifbiochar is applied for electricity generation, while the GHG emissions associated witha MJ of gasification-based bio-jet is 10.1 g CO2-eq. Tews et al. [26] quantified and9compared the GHG emissions of HTL-based gasoline and diesel with pyrolysis-basedgasoline and diesel using woody biomass feedstock made up of 50 wt% logging residuesand 50 wt% forest thinnings, and they founded that in a WTW basis, per MJ of HTLbiofuels can produce 27 g CO2-eq, by contrast, per MJ of pyrolysis biofuels can produce34 g CO2-eq. The detail information of the reviewed studies can be found in Table 1.2.1.3.2 Techno-economic Assessment (TEA)Techno-economic assessment (TEA) is one of the most commonly utilized methods toevaluate the economic feasibility of a project [18], and the key outcomes of a TEAinclude the estimates of capital and operating costs. With the capital required andthe cost of production estimated, the profitability of the project can then be assessed.Below is a general introduction of TEA methodology, and the detailed TEA methodswill be described in Section 4.1 of Chapter 4.The basic framework for estimation of a project cost is shown in Figure 1.3, consist-ing of essentially two parts, the total capital investment (TCI) and the operating cost(OC). TCI can be estimated based on factor method, starting with the total purchasedequipment cost (TPEC) on which the estimation of other elements in TCI can bebased. Thus, it is important to ensure that the estimation of TPEC is accurate andcan properly reflect the project scope. The most reliable data source is the equipmentmanufacturer’s quotation, if the specific equipment is known. Otherwise, data frompeer-reviewed literature or software simulation, such as Aspen Plus®, can be used. Italso depends on the accuracy of the estimation. A detailed estimation (i.e., usually withan uncertainty ±5% [53]) may require the specific information of the equipment for abetter estimation of the purchased equipment cost, while for a preliminary estimation(i.e., usually with an uncertainty ±20% [53]), the cost of the equipment with similarcapacity or flow rate from literature or simulation would be suffice. OC includes thevariable parts and the fixed parts. The variable operating cost (VOC) depends on thematerial, utility input and waste output in the daily operation, which can be derivedfrom the mass and energy balances of the system. The fixed operation cost (FOC) ismainly related to the labor and capital of the project. After the capital and operatingcosts of the project been estimated, discounted cash flow rate of return (DCFROR)analysis can be used to evaluate the economic feasibility of the project. The product’s10Table 1.1: Technical comparisons of thermochemical conversion pathwaysTechnical criteria Gasification Pyrolysis HTLFeedstock quality requirement N LF MFMoisture content 10∼20 wt% [19] <10 wt% [20] No requirementParticle size <2.0∼2.5 inch [19] <3 mm [20] <3 mm [21]Reaction conditions N MF LFPressure 20∼70 bar or atmo-spheric [22]Atmospheric [20] 10∼25 MPa [23]Temperature High: 600∼1000 ◦C[24]Moderate:400∼500 ◦C [20]Moderate:280∼370 ◦C [23]Intermediate product quality N LF MFType Syngas Bio-oil Bio-oilYield 1.54∼2.41 m3/kgbiomass [25]50∼70 wt% [20] 30∼35 wt% [26]Oxygen content N/A 35∼40 wt% [27] 5∼15 wt% [28]Higher heating value N/A 16∼18 MJ/kg [29] 30∼37 MJ/kg [23]Upgrading pretreatment Cleanup and reform-ing [24]Hydrotreating tostabilize [26]Potentially co-processed withcrude oil [30]Technology scale LF MF NPilot Bioliq project byKarlsruhe Instituteof Technology (500kg/h biomass) [31]N/A Steeper Energy(half barrel bio-oil/day) [32]; Licella(10,000 tonnes ofslurry/year) [33]Demonstration Total BioTfuelproject (CapacityN/A, scheduled tocome on stream in2017) [34]BTG BioliquidsEmpyro project(aiming at 20million liters bio-oil/year) [35]N/ACommercial N/A Ensyn-UOP (3 mil-lion gallons bio-oil/year) [36]; BTGBioliquids Malaysiaplant (1.2 tonnesbio-oil/hr) [37]N/A (Licella plansto construct acommercial-scaleplant in 2019 with acapacity of 125,000tonnes of slurry peryear) [33]11Table 1.2: Review of LCA studies on thermochemical conversion of lignocellulosic biomass to transportation biofuelsConversionpathwayReference Year Region SystemboundaryFacility ca-pacityFunctionalunit (FU)Software Feed-stockFocusedproductsLife cycle GHGemission (g CO2-eq/FU)Gasification [54] 2007 Europe WTW 200 MW MJ of fuel E3 database FR Diesel 4.8[51] 2008 US WTWa N/A MJ of fuel GREET FR; CS Jet fuel FR: 11.6; CS: 5.4[55] 2009 Europe WTW N/A km Excel FR Diesel 90[56] 2010 US WTWa 300 BPD MJ of fuel GREET FR; SG Jet fuel FR: 12.2; CS: 17.7[57] 2010 Europe WTT N/A MJ of fuel GREET SG Diesel 21.6[52] 2013 US WTWa 3000 DTPD MJ of fuel GREET CS Jet fuel 10.1Pyrolysis [58] 2011 US WTW 200 TPD Hectare oflandGREET CS Gasoline -2.99E+06[59] 2011 US WTW 2000 DTPD MJ of fuel GREET FR Gasoline 42.90[60] 2012 US WTW 2000 DTPD MJ of fuel SimaPro andGREETFR G&D G: 39; D: 39[61] 2012 N/A WTW 500 DTPD MJ of fuel SimaPro SRP G&D -50.54[52] 2013 US WTWa 2000 DTPD MJ of fuel GREET CS Jet fuel 29.4a/22.1b[62] 2013 US WTW 2000 DTPD MJ of fuel GREET FR; CS Gasoline FR: 38c; CS:(10a/-16b)d[26] 2014 US WTW 2000 DTPD MJ of fuel SimaPro andGREETLR&FT G&D G: 33.8; D: 34.0[63] 2014 N/A WTT 2000 DTPD MJ of fuel GREET CS G&D 28.82e; 25.15f ;-18.13g[64] 2017 US WTWa N/A MJ of fuel GREET FR Jet fuel 22h; 37iHTL [26] 2014 US WTW 2000 DTPD MJ of fuel SimaPro andGREETLR&FT G&D G: 27.2; D: 27.3[64] 2017 US WTWa N/A MJ of fuel GREET FR Jet fuel 18h; 20ia Byproduct bio-char is used for power generation; b Byproduct bio-char is used for soil amendment; c H2 is from fuel gas reforming;d H2 is from pyrolysisoil reforming; e Hydrogen comes from external NG reforming, and biofuel yield is 43.5%; f Hydrogen comes from steam reforming of 35% bio-oil, and biofuelyield is 33.1%; g Hydrogen comes from steam reforming of 100% bio-oil, and biofuel yield is 16.1%; h In-situ hydrogen production via steam reforming ofprocess off-gases; i Ex-situ hydrogen production via steam reforming of natural gas; WTWa=Well-to-wake; WTW=Well-to-wheel; WTT=Well-to-Tank;BPD=Barrel per day; TPD=Tonne per day; DTPD=Dry tonne per day; FR=Forest residue; CS=Corn stover; SG=Switchgrass; SRP=Short RotationPolar; LR&FT=Logging residues and forest thinnings; G: gasoline; D: diesel12minimum selling price is calculated, the essence of which is to manipulate the product’sselling price to find the breakeven point where the project net present value (NPV)equals zero. The minimum selling price of the designated product can be used to com-pare with other alternative products in order to see if it is economically competitive.Total Capital InvestmentDepreciable CostTotal Installed CostPurchased EquipmentEquipment InstallationBuildingsAuxiliary FacilitiesIndirect CostEngineeringConstructionContractor FeesContingencyNon-Depreciable CostLand Site DevelopmentStar-up CostWorking CapitalOperating CostVariable Operating CostUtilitiesElectricityFuelFeedstockCatalystWaste Disposal Fixed Operating CostFixed Costs DepreciationProperty TaxInsurancePlant OverheadLaborOperatingMaintenanceSupervisoryMaintenance andSuppliesMaintenance MaterialsOperating SuppliesFigure 1.3: Project cost estimation frameworkSeveral TEA studies have been reported on evaluating the economic performance ofthermochemical conversion pathways, and the details are shown in Table 1.3. Swanson13et al. [65] compared the capital investment and operating cost of corn stover to biofuelsgasification plant with different technologies. The biofuel product value is found to be$1.06/L to $1.32/L, and it further concluded that the technology with a higher fuelyield could lower the product value, although the capital investment will be higher.Wright et al. [66] examined the product value of naphtha and diesel range fuels fromfast pyrolysis of corn stover and subsequent upgrading. The assessment studied twoscenarios, hydrogen from bio-oil on-site reforming versus purchased hydrogen. Theresults showed that in a nth plant design, the product value of purchased hydrogen sce-nario is $0.56/L, lower than that of on-site hydrogen production scenario $0.82/L. Inthe analysis for a pioneer plant, the cost considerably increases to $0.9/L and $1.73/L,respectively. Zhu et al. [67] implemented TEA to assess the economic feasibility of acommercial scale HTL biofuel plant by comparing state-of-technology case with goalcase, and indicated that the potential process improvement can reduce the minimumfuel selling price to $0.74/L from the current technology status of $1.29/L.1.4 Research ProblemsAccording to the comprehensive review of the thermochemical conversion pathways, wecan observe that HTL is overall a very promising technology in terms of its technical,environmental and economic performance compared with pyrolysis and gasification.However, most current researches on HTL biofuels are trying to solve the technicalobstacles, e.g., the design of HTL reactor for scale up [21], the integration of HTLwith other systems [68], process parameters optimization [69] and the co-upgradingpotential of HTL bio-oil with crude oil [30, 70], etc. There has been little investigationof HTL in terms of its GHG emission and economic performance in comparison togasification and pyrolysis.What’s more, the results of the reviewed LCA and TEA varied from study to study,due to the variation in geographic locations, settings of system, feedstock, analyticalmethods, modelling parameters, and the treatment of by- or co-products. A reviewstudy focused on the pyrolysis technologies by Roy and Dias in 2017 [71] has reportedsimilar observations on the variability of LCA and TEA results based on feedstock,technology, etc. Therefore, the specific context of BC needs to be considered in evalu-ating the deployment of HTL biofuel system in BC, but to our best knowledge, there14Table 1.3: Review of TEA studies on thermochemical conversion of lignocellulosic biomass to transportation biofuelsConversionpathwayRegion Facility capacity Feedstock FocusedproductsCapital investment(million $)IRR(%)MFSP($/L)ReferenceGasification US 2000 DTPD CS G&D 498;606 10 1.06;1.32 [65]Canada 2000 DTPD FR G&D 298;552 10 0.78;1.22 [72]Germany N/A LB G&D 344a 7 1.6a [73]Pyrolysis US 2000 DTPD CS N&D (200;287)b;(585;911)c10 (0.56;0.82)b;(0.9;1.73)c[66]US 2000 DTPD CS G&D 429 10 0.68d [74]US 2000 DTPD LR& FT G&D 358 10 0.82d [26]HTL US 2000 DTPD LR& FT G&D 244 10 0.51d [26]US 2000 DTPD WB G&D (275;301)e 10 (0.74;1.29)e [67]Finland 1500 DTPD FR G&D 828g 10 0.96f [75]a Converted from Euro to USD using 1 e=1.3 $; b Nth plant design, capital investment 200 million $ and MFSP $0.56/L are forhydrogen purchased externally, while capital investment 287 million $ and MFSP $0.82/L are for hydrogen produced from bio-oilreforming; c Pioneer plant design, capital investment 585 million $ and MFSP $0.90/L for hydrogen purchase externally, and capitalinvestment 911 million $ and MFSP $1.73 /L for hydrogen produced from bio-oil reforming; d Converted from per gallon basis to perliter basis using 1 gallon=3.78 L; e Capital investment 275 million $ and MFSP $0.74/L are for goal scenario, while capital investment301 million $ and MFSP $1.29/L are for state-of-technology scenario; f Converted from e1.03/kg to $0.96/L by assuming 1 e=1.3 $ andthe gasoline density to be 0.72 kg/L; g Converted from 1.7 million e/MWLHV to 2.21 million $/ MWLHV by assuming 1 e=1.3 $ and thetotal feed consumption is 375.1 MWLHV; IRR=Internal rate of return; MFSP=Minimum fuel selling price; DTPD=Dry tonne per day;CS=Corn stover; FR=Forest residues; LB=Lignocellulosic biomass; LR&FT=Logging residues and forest thinnings mix; WB=Woodybiomass; G&D=Gasoline and diesel; N&D=Naphtha and diesel15has been no such integrated assessment being reported.1.5 Objectives and ImplicationsIn view of the great interest in deploying facility to convert abundant but under-utilized forest residues to biofuels in BC, as well as the gaps mentioned above, specificLCA and TEA are timely needed to evaluate the environmental impact and economicfeasibility of the HTL technology in order to have a comprehensive understanding ofits performance. In short, three basic questions need to be answered by this thesis:1. What is the GHG emission reduction potential associated with producing and usingHTL biofuels in BC?2. What is the economic cost for producing HTL biofuels in BC and is it competitivecompared with petroleum fuels under the current carbon tax scheme in BC?3. What are the potential strategies or policies that can be implemented if the decisionmakers want to promote HTL biofuel production in BC?Specifically, the following points are to be addressed by the LCA: (1) quantification ofthe life cycle GHG emissions of HTL biofuels system based on different scenarios; (2)identification of the “hot spots” of the processes that intensively emit GHGs; (3) anal-ysis of the large proportional change of GHG emissions under different scenarios; (4)comparison of the GHG emissions of HTL biofuels produced in BC with general valuesreported in the literatures; (5) sensitivity analysis on the key parameters impactingthe GHG emissions of HTL biofuels; and (6) making recommendations for improvingthe GHG emission performance of HTL biofuels.The following points are to be addressed by the TEA: (1) estimation of the capitaland operating costs of producing HTL biofuels in BC based on different scenarios andcalculation of the minimum selling price (MSP); (2) comparison of the MSP of HTLbiofuels produced in BC with general values reported in the open literature; (3) iden-tification of the impact of carbon tax and technology advancement on the economicperformance of HTL biofuels; and (4) sensitivity analysis on the key parameters thatinfluence the MSP of HTL biofuels.16To our best knowledge, there has been no similar integrated assessment of HTL bio-fuels from forest residues reported based on the BC context. Therefore, the resultsfrom this study could help provide a preliminary insight for other researchers and localcompanies or investors as well as a reference for government policy makers.1.6 Structure of ThesisThe thesis is organized as follow:Chpater 2 presents the case study we developed with three different scenarios, followedby a thorough description of the processes associated with each stage of the proposedHTL biofuel system, which lays the basis of Chapter 3 and Chapter 4.Chapter 3 and Chapter 4 are the two main contributions of this thesis, presenting theenvironmental and economic assessment case study of the proposed HTL biofuel sys-tem, respectively. In Chapter 3, an LCA is performed to quantify the GHG emissionsof HTL biofuels based on three different supply chain designs. In Chapter 4, a TEA isconducted to estimate the capital and operating costs of HTL biofuels based on threesupply chain designs, and DCFROR analysis is used to calculate the minimum fuelselling prices of HTL biofuel products. Each chapter starts with a description of themodelling methods, followed by results and discussions presented in detail. Conclu-sions for each specific study are given at the end of the corresponding chapter.Chapter 5 draws the conclusions based on the overall environmental and economic per-formance of HTL biofuels, states the limitations of this study and recommends somefuture work to improve the current study.The Appendices summarize all supplementary data and information relevant to thiswork. Appendix A tabulates the detailed mass and energy balances data based onthe process modelling, which lay the basis for the life cycle and economic assessment.Appendix B and Appendix C present the process emission factors used to build the lifecycle inventory and emission inventory of each life cycle stage, respectively. AppendixD shows the detailed stage-wise cost results from economic analysis and Appendix Eattaches the spreadsheet for carrying out the DCFROR analysis.17Chapter 2Description of Case Study andProcesses2.1 Case Study and ScenariosA total liquid biofuel production rate of 100 million liters per year (MLPY) is assumedas the basis for this study, as proposed in an UBC-Boeing joint project on evaluatingthe viability of bio-jet fuel production in Western Canada, based on the availabilityand distribution of forest residues in BC [13]. The Coast Region of BC (see Figure2.1) is chosen as the study area for deploying the 100 MLPY hypothetic HTL biofuelsystem due to the abundantly available forest residues as feedstock, existing oil refininginfrastructure for bio-oil upgrading and local markets for biofuel products consumptionin this area. BC government partitions the Coast Region into several timber supplyareas (TSAs) and a sales office is established for timber marketing in each TSA. Thelocations of these timber sales offices, namely, Chilliwack, Squamish, Powell River andPort Alberni, where biomass feedstock is assumed to be supplied to the conversionfacilities, are referred to as the feedstock delivery points (FDPs) in this study. Thereis an existing Chevron oil refinery in Burnaby with a throughput of 8700 m3/d [76],and we assume that this oil refinery is utilized to upgrade the bio-oil produced in HTLbiorefinery. Four different biofuel products: gasoline, jet fuel, diesel and heavy oilare produced and distributed to local markets for end use, specifically, gasoline anddiesel for light- and heavy-duty vehicles, respectively, at City of Vancouver, jet fuelfor airplanes at Vancouver International Airport, and heavy oil for marine vessels atPort of Vancouver. The geographic locations of all the places mentioned above are18schematically shown in Figure 2.1.Study AreaBritish ColumbiaUnited States     Coast RegionPort Alberni ChilliwackSquamishPowell RiverSouth Coast RegionCanadaChevron oil refineryTSA boundary Feedstock deliver pointCity of VancouverStudy TSAWest Coast RegionVancouver AirportPort of VancouverFigure 2.1: Schematic diagram of geographic information of HTL biofuel system (Powell River,Squamish and Chilliwack lie in the South Coast Region; Port Alberni lies in the WestCoast Region)The forest residues availability for each TSA is estimated using the method proposedby MacDonald et al. in a BC government report [77]. The essence is to multiply theannual logs harvest volume in that TSA by a biomass ratio, which is defined as thevolume of forest residues recovered from unit volume of merchantable logs harvestedin the logging operation. The annual logs harvest volume is retrieved from HarvestBilling System of BC based on 5-year average data of August 2011 to July 2016 [78]. Inthis study, we assume that the biomass ratio is 15% based on the situation that mostof the timbers in the BC Coast Region are second growth Hemlock and the harvestingmode is ground-based and cable [77]. In ground-based harvesting systems, a machinetravelling over the ground is used to carry the fell trees or logs from the stump tothe landing. While in cable systems, the fell trees or logs are carried by a stationarymachine with an overhead cable attached [79]. The density (dry basis) and moisturecontent (wet basis) of forest residues used in this study are 420 kg/m3 and 49 wt%,respectively. Due to the lack of specific feedstock analysis data, i.e., proximate analy-sis and ultimate analyses, for forest residues in the Coast Region of BC, the feedstockanalysis data from Tews et al. [26] were used in our models. The 5-year average an-19nual volume of harvest logs and estimated available forest residues is shown in Table 2.1.Table 2.1: Annual forest residues availability in BC Coast RegionHarvest logsBiomass ratioForest residues availabilitym3/yr m3/yr dry tonne/yr wet tonne/yrChilliwack 1.21E+06 0.15 1.82E+05 7.64E+04 1.50E+05Squamish 4.98E+05 0.15 7.47E+04 3.14E+04 6.14E+04Power River 1.93E+06 0.15 2.89E+05 1.21E+05 2.38E+05Port Alberni 5.24E+06 0.15 7.85E+05 3.30E+05 6.46E+05Total 8.87E+06 0.15 1.33E+06 5.59E+05 1.09E+06The case study is developed based on three different scenarios in order to investigatehow supply chain designs could influence the system’s environmental and economicperformance. The main differences between these three scenarios lie in the configura-tion of biorefinery (integrated with oil refinery or distributed at FDPs) and the type offeedstock (bulky forest residues or forest residues derived bio-oil or wood pellets) sup-plied to conversion facility. For scenario 1 (denoted as Fr-CIR scenario), the collectedbulky forest residues from each FDP are directly transported to the central integratedrefinery for conversion (Figure 2.2(a)). For scenario 2 (denoted as Bo-DBR scenario),forest residues are first converted to bio-oil at distributed biorefineries and then trans-ported to a central oil refinery for upgrading (Figure 2.2(b)). For scenario 3 (denotedas Wp-CIR scenario), forest residues are first densified to wood pellets at distributedpellet plants located at FDPs and then transported to the central integrated refineryfor conversion (Figure 2.2(c)).2.2 Description of ProcessesAlthough the processes vary with each scenario, the basic structure of the proposedHTL biofuel system includes the following stages: biomass collection, transportation,pre-processing, biomass-to-biofuels conversion, and biofuel products distribution andend use. It should be noted that for LCA, all these six stages are considered, whilefor TEA, the biofuel distribution and end use stages are not included. The detailedprocesses associated with each stage are described in the following subsections.20Forest stands FDPsCentralintegrated refineryLocal marketsForest residues flow Biofuel products flow(a) Fr-CIR scenarioForest standsHTL biorefineriesat FDPsCentraloil refineryLocal marketsForest residues flow Biofuel products flowBio-oil flow(b) Bo-DBR scenarioForest standsWood pellet plants at FDPsCentralintegrated refineryLocal marketsForest residues flow Biofuel products flow(c) Wp-CIR scenarioFigure 2.2: Supply chain designs of HTL biofuel system for each scenario (the dash line arrowsstand for the flow of feedstock or intermediate products and the solid line arrows standfor the flow of final biofuel products)212.2.1 Biomass CollectionCollection of biomass feedstock is modeled in two steps. The piled forest residues onforest stands of each TSA are first gathered, chipped to smaller size and loaded todump trucks, and then shuttled to the corresponding FDP. Due to the lack of specificlocation and productivity of each forest stand in corresponding TSA, we simply assumethat the forest residues after logging operation are uniformly distributed around theFDP and 12.5 km is used as the average distance for shuttling forest residues to FDP.The equipment energy input for biomass collection modelling are presented in Table 2.2.Table 2.2: Equipment energy input for biomass collection modelingEquipment Fuel type Process Energy input ReferenceLoader Diesel Load forest residues to chipper 0.82 L/dry tonne [80]Chipper Diesel Chip forest residues 3.01 L/dry tonne [80]In order to meet the 100 MLPY biofuels production target, for Fr-CIR and Bo-DBRscenarios, a total of ∼300,000 dry tonnes of forest residues are needed. While for Wp-CIR scenario, due to the consumption of forest residues as drying fuel in pellet plants,additional ∼36,000 dry tonnes are required. The detailed methods of calculating theannual forest residues requirement are described in the following context. The param-eters used in the calculations of the annual forest residues requirement as well as theirnotations are summarized in Table 2.3. It should be noted that we assume that there isno mass loss in the feedstock collection and transportation stages as well as the biofuelproducts separation process.Forest residues requirement for Fr-CIR, Bo-DBR, Wp-CIR scenarios (Ri, dry tonne/yr,i = {Fr-CIR, Bo-DBR, Wp-CIR}) can be calcualted by Equation 2.1 and Equation 2.2.When i=Fr-CIR, Bo-DBR:Ri =Pv × ρbmαbotd × αfrtb (2.1)22Table 2.3: Parameters for calculating forest residues requirementParameter Notation Value ReferenceAnnual productivity of total biofuels (million liters per year) Pv 100Mass conversion rateForest residues to bio-oil (kg/kg dry forest residues) αfrtb 0.367 [26]Forest residues to wood pellet (kg/kg dry forest residues) αfrtw 0.89 [81]Wood pellet to bio-oil (kg/kg dry wood pellet) αwptb 0.367 [26]Bio-oil to deoxygenated oil (wt%) αbotd 75 [26]Moisture content (wet basis, wt%)Wood pellet MCwp 5.6 [81]Biofuel products distribution (wt%)Gasoline βg 21 [70]Jet fuel βjf 25 [70]Diesel βd 35 [70]Heavy oil βho 19 [70]Biofuel density (kg/m3)Gasoline ρg 739 [2]Jet fuel ρjf 808 [2]Diesel ρd 843 [2]Heavy oil ρho 944 [2]When i=Wp-CIR:Ri =Pv × ρbm(αbotd × αwptb × αfrtw)(1−MCwp) (2.2)Where ρbm is the density of biofuel mix in kg/m3, and ρbm can be calculated byEquation 2.3 below:ρbm =∑jβj∑jβjρj, j = {g, jf, d, ho} (2.3)232.2.2 TransportationThe transportation of biomass feedstock from FDPs to conversion facility varies withscenarios. For Fr-CIR scenario, forest residues arriving at FDPs are reloaded to semi-trailers (STs) and then directly transported to the central integrated refinery for con-version. However, for Bo-DBR and Wp-CIR scenarios, the arriving forest residues arefirst converted to bio-oil and wood pellets in the distributed HTL and pellet plantsat FDPs, respectively, and then the intermediates are loaded to STs or liquid tankertrucks (LTTs) and transported to the refinery for further conversion. It should benoted that transportation from Powell River and Port Alberni to Chevron oil refinerywill undergo marine routes, STs or LTTs are thus assumed to be carried by ferries runby British Columbia Ferry Services Inc. To account for the emission associated withcarrying STs or LTTs and the feedstock, the total emissions of ferry transportationwere allocated by the mass of people, STs or LTTs and other vehicles, which are esti-mated by the information provided on the website of British Columbia Ferry ServicesInc. [82]. The transportation distance from Chilliwack, Squamish, Powell River andPort Alberni to Chevron oil refinery are 102 km, 74 km, 179 km (including 37 kmmarine transportation), and 170 km (including 57 km marine transportation), respec-tively. The energy input factors for feedstock transportation modelling are presentedin Table 2.4.Table 2.4: Energy input for feedstock transportation modelingEquipment Fuel type Process Energy input ReferenceDump truck Diesel Shuttle chipped forest residuesto FDP6279 kJ/Tkm [2]Loader Diesel Load feedstock at FDPs to STsor LTTs1.02 L/dry tonne [80]ST Diesel Transport forest residues orwood pellets to refinery1988 kJ/Tkm [2]LTT Diesel Transport bio-oil to refinery 1988 kJ/Tkm [2]Ferry Marine diesel Carry loaded STs or LTT onthe sea95 L/km [83]To minimize the transportation emissions, the total annual feedstock requirement isapportioned among four FDPs according to their feedstock availability and proximity24to Chevron oil refinery, that is, the closer the FDP to the refinery, the higher priority itwill be assigned for forest residues utilization. The data for the annual forest residuestransported from each FDP to the conversion facility are shown in Table 2.5 below.Table 2.5: Annual forest residues supply at each FDP for different scenarios (dry tonne/yr)FDP Fr-CIR Bo-DBR Wp-CIRChilliwack 7.64E+04 7.64E+04 7.64E+04Squamish 3.14E+04 3.14E+04 3.14E+04Power River 1.21E+05 1.21E+05 1.21E+05Port Alberni 7.12E+04 7.12E+04 1.07E+05Total 3.00E+05 3.00E+05 3.36E+052.2.3 Pre-processingIn biorefinery, the incoming forest residues or wood pellets will first go through thepre-processing step, where the biomass feedstock is unloaded, cleaned and sent to agrinder for further size reduction. Then the ground feedstock is mixed with hot waterrecycled from HTL reaction, producing biomass-water slurry with 8 wt% solid content[26]. The energy input factors for the equipment used in feedstock pre-processing stageare presented in Table 2.6. To make the life cycle stages consistent between differentscenarios, the pellet plant operation process in Wp-CIR scenario is incorporated intothe pre-processing stage.Table 2.6: Energy input of feedstock pre-processing in biorefineryEquipment Fuel type Process Energy input ReferenceFront-end loader Diesel Unload biomass feedstock 0.42 L/dry tonne [26]Grinder Electricity Grind biomass feedstock 71.2 kWh/dry tonne [26]Auxilliary Electricity Chip cleaning, dust collection 5 kWh/dry tonne [26]252.2.4 ConversionConversion stage covers two parts, i.e., thermochemical conversion of biomass feed-stock in biorefinery to produce bio-oil and bio-oil upgrading in the oil refinery. Theprocess design of biorefinery thermochemical conversion and oil refinery upgrading arebased on the study by Tews et al. [26]. Biorefinery conversion includes the followingprocesses: HTL and anaerobic digestion (AD), while oil refinery upgrading includesbio-oil hydrotreating and hydrogen production. An AD unit is integrated with HTLsystem in order to treat and recover energy from the HTL wastewater, and a hydrogenproduction process is designed to meet the hydrogen demand for bio-oil hydrotreat-ing. Figure 2.3 shows the process flows of the pre-processing and conversion stages forintegrated and distributed systems. The parameters used to model the processes ofbiorefinery and oil refinery are given in Table 2.7 and Table 2.8, respectively, and themass and energy balances are detailed in Appendix A.Integrated systemWaste waterPre-processing HTLSlurryHydrotreatingHydrogen plantBio-oilADBio-gas PHWWDigestateH2Off-gasGasolineHeavy oilJetDieselBiocharRecycled waterNGForest residuesOrWood pelletsSteamCentral biorefineryProcess type:Physical process :Thermochemical process:Biochemical processCompound type:Feedstock:Intermediate :By-product:Final productDistributed systemBiocharDigestateBio-oilPre-processing HTLSlurryADBio-gasPHWWRecycled waterGasolineHeavy oilJetDieselHydrotreatingHydrogen plantOff-gasH2Off-gasNGDistributed biorefineriesNGForest residuesSteamWaste waterSystem internalflowCross systems flowCentraloil refineryCentraloil refineryFigure 2.3: Process flow diagram of pre-processing and conversion stages for integrated anddistributed system (Fr-CIR and Wp-CIR scenarios belong to integrated system,while Bo-DBR scenario belongs to distributed system)The HTL process in this study is modelled based on the experimental and simulationdata from PNNL report by Tews et al. [26]. The water-biomass slurry generated inthe pre-processing process is pressurized and sent to the HTL reactor. The HTL pro-cess produces bio-oil, non-condensable gases, biochar as well as water containing high26concentration of dissolved organics, called post HTL waste water (PHWW). Sodiumcarbonate (Na2CO3) is used as the buffer agent to prevent the pH of the slurry fromdropping below 4, thus inhibiting the formation of high molecular weight compoundsand solid wastes [67]. HTL bio-oil has low oxygen content and is thermally stable [26].Therefore, we assume that it is directly co-processed with crude oil in the Chevron oilrefinery without pre-hydrotreating step. Non-condensable gases, referred to as off-gasesin this study, contains the non-condensable volatile compounds, mostly CO2, a mod-erate part of light hydrocarbons (C1∼C4) and a small portion of H2 (see in Table 2.7).The energy in off-gases is assumed to be recovered and reused in conversion processes.For Fr-CIR and Wp-CIR scenarios, off-gases are sent to hydrogen plant as fuel forhydrogen production, and the remaining is used as fuel for heating anaerobic digester.For Bo-DBR scenario, these gases cannot be sent to hydrogen plant, so they are con-sumed as heating fuel for HTL or AD. The solid phase product biochar is assumed tobe collected and applied for soil amendment in local farms for HTL biofuel LCA, whileit is assumed to be sold at the biorefinery gate for HTL biofuel TEA. Panisko et al.[84] reported that chemical oxygen demand (COD) of PHWW ranged from 41,000 to77,000 mg/L, compared with 200 to 1200 mg/L of raw municipal waste water. Hence,a dedicated treatment facility must be employed at the processing facility. In thisstudy, we assume that an AD unit is designed for the treatment and energy recovery ofPHWW, while the majority of PHWW is recycled for slurry formation in the biomassfeedstock pre-processing.In the anaerobic digester, the PHWW is converted into biogas and solid and liquiddigestates. Biogas is sent to the HTL unit as heating fuel. The solid and liquid di-gestates are sent to landfill and waste water plant, respectively, for further treatment.Due to the lack of reported data for PHWW as substrate for AD, a large-scale ADoperating at mesophilic temperature (35 ◦C) and using liquid swine manure as feed-stock was used as an approximation to quantify the heat and electricity requirements[85, 86]. A typical large-scale AD can digest 20,000∼60,000 tonnes of raw materialsper year [86]. The PHWW input into the AD unit in this study is ∼409,000 tonnesper year (see Appendix A), which is about ten times larger. While the world’s largestAD plant reported in 2013 being constructed digests 270,000 tonnes organic wastes peryear [87], no energy input data of this plant is available. The energy input of a typicallarge-scale AD is thus the best available data to be used in our study.27Table 2.7: Major inputs and parameters for modeling HTL biorefinery processesParameters Value ReferenceAnnual operating hours, hr 8000Hydrothermal liquefactionMaterial and energy inputBuffer (Na2CO3) content, wt% of slurry 1 [67]Electricity, MW 4.03a/4.10b Scaled from [26]Heat, MW 50.42a/50.24b Scaled from [21]Product yields, kg/kg dry feedstockc [26]Bio-oil 0.367Off-gases 0.173Water (with dissolved organics) 0.404Biochar 0.056Off-gases composition, wt% [26]CO2 90.2H2 0.9CH4 3.0C2H6 2.5C3H8 1.9C4H10 1.5Anaerobic digestionProduct yields, kg/kg waste water [26]Biogas 0.23Solid digestate 0.01Liquid digestate 0.76Material and energy input Average of [85, 86]Electricity, MJ/GJ biogas produced 102.32Heat, MJ/GJ biogas produced 140.89a Applicable to Fr-CIR and Bo-DBR scenarios. For Bo-DBR, this is the total electrici-ty/heat input of the HTL units of four distributed biorefinerie; b Applicable to Wp-CIRscenario; c Wood pellets were assumed to have the same conversion rate as forest residuesThe hydrotreating process is a catalytic reaction process where the oxygenated com-28pounds in bio-oil are exposed to hydrogen under elevated pressure and high tempera-ture [88]. The catalyst utilized in hydrotreating process is assumed to be conventionalNiMo/Al2O3 catalyst which is commonly used in crude oil hydroprocessing. The efflu-ent from hydrotreating reactors is cooled and separated into deoxygenated oil, wastewater and off-gases streams. The off-gases from hydrotreating containing mainly lighthydrocarbons (see in Table 2.8) are sent to hydrogen plant as feedstock for steam re-forming. The deoxygenated oil is then distilled into gasoline, jet, diesel and heavy fueloil as finished products.Hydrogen for bio-oil upgrading is produced by NG steam reforming in a hydrogenplant of the oil refinery. The hydrogen demand is determined by the bio-oil productionfrom HTL. As reported in the study of Zhu et al. [67], per gram of dry bio-oil tobe treated, 0.033 gram of H2 is needed. The hydrogen production process is modeledbased on a NREL report by Spath et al. [89] with scaling to the specific hydrogendemand. Certain modifications are made on the NREL model to accommodate theentire HTL biofuel production system. Specifically, the reformer is fueled mainly bythe combustible off-gases from hydrogen production, while the remaining 4.4 wt% [89]is assumed to be supplied by off-gases from hydrotreating as well as HTL dependingon the specific scenarios, instead of using purchased NG. The electricity requirement ofthe hydrogen plant is modified to be met by BC grid. The catalyst utilized in hydrogenproduction process is assumed to be NiMo/Al2O3.Table 2.8: Major inputs and parameters for modeling oil refinery procesParameters Value ReferenceAnnual operating hours, hr 8000HydrotreatingLHSV, h−1 0.22 [26]Material and energy inputH2, g H2/g dry bio-oil 0.033 [67]Electricity, MW 1.12 Scaled from [26]CatalystLoad, kg catalyst/tonne bio-oil 0.41 Calculated based on LHSVLife, yrs 129Table 2.8: Major inputs and parameters for modeling oil refinery proces (continued)Parameters Value ReferenceProduct distribution, wt% [26]Deoxygenated oil 75Off-gases 7Water 18Off-gases composition, wt% [26]H2 7.8CH4 18.2C2H6 15.1C3H8 13.2C4H10 4.9C5H12 1.5C6H14 39.3Deoxygenated oil distillation streams, wt% [70]Gasoline 21Jet 25Diesel 35Heavy oil 19Hydrogen plantGHSV, h−1 4000 [90]Material and energy inputNG (feedstock), kg/m3 H2 produced 0.24 Scaled from [89]Steam (feedstock), kg/m3 H2 produced 0.76 Scaled from [89]NG (fuel), kg/m3 H2 produced 0.03 Scaled from [89]CatalystLoad, kg catalyst/tonne H2 produced 0.12 Calculated based on GHSVLife, yrs 3Electricity, MW 0.15 Scaled from [89]302.2.5 Distribution and End UseFour different liquid biofuel products: gasoline, jet fuel, diesel and heavy oil, are pro-duced in Chevron oil refinery and distributed to the local markets. The gasoline anddiesel are assumed to be delivered by LTT to a hypothetic refueling station for light-and heavy-duty vehicles, respectively, at City of Vancouver, which is 10 km away fromChevron refinery. The jet fuel is delivered via an existing 40 km oil pipeline fromChevron oil refinery to Vancouver International Airport, for airplanes. The heavy oilis delivered by LTT to Port of Vancouver, 11.3 km away from Chevron refinery, formarine vessels.31Chapter 3HTL biofuel LCA3.1 LCA Model3.1.1 Goal and Scope DefinitionA process-based attributional LCA is conducted to quantify the GHG emissions ofHTL biofuels from forest residues in BC. The analysis follows the international stan-dard ISO 14040 [45] and the functional unit is set to be 1 MJ of HTL biofuels mixproduced. The system boundary of each scenario are shown in Figure 3.1.All emissions from each process and its associated upstream supply chain are accountedfor in this study. However, the emissions associated with construction of infrastructureand manufacture of equipment as well as waste treatment are not included within thescope. Additionally, forest residues as feedstock for biofuels production are consideredto carry no environmental burdens linked with the harvested timber in light of lowvalue of these forest residues, which otherwise will be burned to reduce the risk of wildfire in BC. We also assume that no soil carbon change due to controlled sustainableremoval of forest residues from forest stands to produce biofuels in BC, with 25%of forest residues being left in forest stands to provide nutrients and for the healthof the forests [13]. It is assumed that the carbon released from the utilization of theoff-gases from the conversion stage does not contribute to global warming impact sinceit essentially origins from the carbon intake during trees growth.32Bo-DBRFr-CIRWp-CIRScenarios ConversionCollection End useDistributionTransportation Pre-processingIntegrated refineryCollectionForest residuesFeedstock delivery pointTransportationCollectionCollectionCollectionPre-processing HTLSlurryHydrotreatingHydrogen plantBio-oilADBio-gas PHWWDigestateH2Off-gasGasolineHeavy oilJetDieselBiocharRecycled waterNGProcess type:Physical process :Thermochemical process:Biochemical processCompound type:Feedstock:Intermediate :By-product:Final productTransportationDigestateBiocharBio-oilPre-processing HTLSlurryADBio-gas PHWWRecycled waterOil refineryGasolineHeavy oilJetDieselHydrotreatingHydrogen plantOff-gasH2Off-gasCollectionCollectionCollectionCollectionBiorefineryForest residuesNGNGBiorefineryIntegrated refineryTransportation Pre-processing HTLSlurryHydrotreatingHydrogen plantBio-oilADBio-gas PHWWDigestateH2Off-gasGasolineHeavy oilJetDieselBiocharRecycled waterNGCollectionForest residuesWood pellet plantCollectionCollectionCollectionWood pelletFigure 3.1: The system boundary of different HTL biofuel scenarios (AD: anaerobic digestion;NG: natural gas; PHWW: post HTL waste water)3.1.2 Life Cycle Inventory AnalysisData quality and specificity are generally considered as critical issues for LCA stud-ies. Spatial variation and local environmental uniqueness are one of the concerns that33require special attention [91]. Therefore, to enhance the consistency and accuracy ofthe life cycle inventory data, whenever possible, BC specific data are utilized, e.g., thefeedstock availability, the locations of biofuels supply chain nodes, the transportationand electricity mix. Otherwise, Canadian average, or if not available, U.S. average,data are used with modification on the electricity mix to reflect BC specificity. GH-Genius v4.03 [2], a Canadian-based LCA program, is primarily employed for modelingprocesses such as transportation, energy and fuels production and consumption, bysetting BC as the analyzed region and 2016 as the base year. For the processes lackingbuilt-in models in GHGenius v4.03, e.g., materials production and delivery includingHTL buffer agent, hydrotreating and hydrogen production catalyst, and nitrogen fer-tilizer, the GREET 2015 (Greenhouse gases, Regulated Emissions, and Energy use inTransportation) [92] or SimaPro v8.2 coupled with Ecoinvent v3.2 database [48] is usedto model the process emissions with modification on the electricity mix. When the datacould not be found in the software database described above, they are collected frompeer-reviewed journal articles or reports issued by government and widely recognizedscientific organizations (e.g., PNNL, NREL).The emissions from each process are obtained based on the emission factors method.Concretely, materials and energy consumptions are first calculated for each processthrough mass and energy balances and then multiplied by the corresponding emissionfactors. The detailed mass and energy balances of pre-processing and conversion stagescan be found in Appendix A. The processes emission factors used in modeling are sum-marized in Appendix B.3.1.3 Impact AssessmentThis LCA study only focuses on the global warming impact, quantified by the metricsof GHG emissions. The collected raw data from the various sources described aboveare first compiled in Microsoft Excel to build the life cycle inventory of HTL biofuels,and then IPCC (Intergovernmental Panel on Climate Change) 2007 global warmingpotential factors are used to convert CO2 (1), CH4 (25) and N2O (298) into CO2-eqfor a time horizon of 100 years.343.1.4 Handling of By-productThe method of handling process by-products can significantly influence the life cycleresults of biofuel [52, 62, 93]. The by-product biochar produced in HTL plant is as-sumed to be shipped out to a hypothetic farm 50 km away from biorefinery and appliedfor soil amendment. HTL biochar contains carbon originating from forest residues andis modeled as sequestered carbon in this analysis. Although the stability of carbonin biochar depends on many factors such as feedstock, processing and environmentalconditions, we assume that 80% of the carbon in biochar could be stably sequestratedwhen it is applied for soil amendment as suggested by Roberts et al. [94]. Wang et al.[95] meta-analyzes 24 studies of biochar decomposition in soil and find that about 97%of biochar could contribute to long-term carbon sequestration in soil, hence the 80%assumption we make in this analysis is conservative. Besides the sequestered carboncredit, N in biochar is assumed to displace the same amount of nitrogen fertilizer assuggested by Han et al. [62]. The emissions associated with the nitrogen fertilizerproduction are avoided, thus creating another credit. The average data, rather thanthe marginal data, is used to calculate the credit for replacing nitrogen fertilizer. TheC and N content in biochar are assumed to be 51 wt% and 0.5 wt%, respectively [66].3.2 Results and Discussion3.2.1 Life Cycle GHG EmissionsFigure 3.2 shows the life cycle stage-wise GHG emissions of three different HTL biofuelsproduction scenarios. The life cycle GHG emissions for Fr-CIR, Bo-DBR and Wp-CIRscenarios are 20.5, 17.0 and 19.5 g CO2-eq/MJ, respectively, corresponding to 78%,82% and 79% reduction relative to 2005 gasoline baseline 93 g CO2-eq/MJ [96]. Whenconsidering the credit from biochar applied for soil amendment, the life cycle GHGemissions of HTL biofuels can be further reduced by 6.8 g CO2-eq/MJ, correspondingto 85%, 89% and 86% reduction of the life cycle GHG emissions compared to petroleumfuels for Fr-CIR, Bo-DBR and Wp-CIR scenarios, respectively.The detailed GHG emission profile of individual processes is given in Table 3.1. For allthree scenarios, the most dominant contributor to GHG emissions is biofuel conversion,35Figure 3.2: Stage-wise GHG emissions of HTL biofuels from three different scenarioswhich makes up more than 50%, followed by feedstock delivery, including collectionand transportation of biomass feedstock, accounting for 19% to 39% of total emissionsdepending on specific scenario. The process having the highest global warming impactover the whole life cycle of HTL biofuels is the HTL buffer agent Na2CO3 production.In this study, due to the lack of industrial data of Na2CO3 consumption in the HTLprocess, we use the bench test data reported by Zhu et al. [67] and Panisko et al.[84] from PNNL, i.e., Na2CO3 is consumed at 1wt% of the total feed slurry. Thisvalue could be higher than the demonstration- or industrial-scale data because of theassumed no-recycling of Na2CO3. Although it is assumed that PHWW is recycledfor the slurry formation, we do not consider the remaining Na2CO3 in the recycledwaste water, because no data are currently available about the buffer consumptionrate in the HTL reaction. The contribution of biomass collection is similar among thethree scenarios (13%∼16%), while the transportation varied significantly. In Fr-CIRscenario, feedstock transportation accounts for about 25% of the GHG emissions ofHTL biofuels. The long-distance transportation and the low energy density of bulkyforest residues lead to the high transportation emissions. In contrast, for Bo-DBR andWp-CIR scenarios, the bulky forest residues are first densified into high energy den-sity intermediates, bio-oil and wood pellet, which are transported to refinery for furtherconversion. Compared with Fr-CIR scenario, Bo-DBR and Wp-CIR scenarios can lowerthe transportation emissions by 83% and 44%, respectively. However, the configurationchange also causes increase of GHG emissions in other stages. For Wp-CIR scenario,36due to the use of biomass feedstock as heating fuel in pellet plant operation, moreforest residues need to be collected from forest stands, thus increasing the emissions ofcollection stage. Besides, pellet plant operation is linked with upstream (heating fuelproduction and electricity generation) and downstream (fuel combustion) emissions [1],which contribute to the increased emissions in pre-processing stage compared with theother two scenarios. For Bo-DBR scenario, the off-gases produced in the distributedHTL plants could not be used in the refinery as in integrated systems, i.e., Fr-CIRand Wp-CIR, so NG is needed as a feedstock for hydrogen production, thus increasinghydrogen production emissions. Overall, Bo-DBR and Wp-CIR scenarios can achieve16.9% and 4.7% reduction of total GHG emissions compared with Fr-CIR scenario.In Fr-CIR and Wp-CIR scenarios, AD operation is an important contributor to thelife cycle GHG emissions of HTL biofuels, accounting for around 14%. NG is used asheating fuel for maintaining the AD operating temperature since off-gases producedby HTL are sent to refinery for hydrogen production. However, in Bo-DBR scenario,the impact of AD operation can be considerably reduced due to the use of remainingoff-gases from HTL as heating fuel for AD.3.2.2 Comparison with Peer-reviewed LiteratureTo check whether the GHG emissions of HTL biofuels from this study are consistentwith those from peer-reviewed literature, we have conducted a comparison using theresults from part of the reviewed studies presented in Table 1.2. The studies are cho-sen for comparison only when the following criteria are met: (1) the system boundaryis well-to-wheel or well-to-wake; (2) the functional unit is MJ of biofuel. Figure 3.3presents the analyzed life cycle GHG emissions of this study and those of literatures.The bar in Figure 3.3 stands for the median value of the GHG emissions of all studiesof a specific conversion pathway, instead of the mean value, because we find that themean can be easily influenced by the extreme values of certain studies, and the errorbar represents the standard deviation. It should be noted that the GHG emission re-sults of this study used to compare are the net emission results including the biocharcredit, since the results from majority of the selected literatures consider the by- orco-products credit.According to the results shown in Figure 3.3, gasification generally has the best GHG37Table 3.1: Contribution of each process to the GHG emissions of HTL biofuelsHTL biofuel life cycle stage Fr-CIR (%) Bo-DBR (%) Wp-CIR (%)Feedstock collection 13.12 15.79 15.47Loader and chipper operation 7.53 12.28 12.22Forest residues shuttling to FDPs 5.59 3.51 3.25Feedstock transportation 25.47 5.29 14.90Pre-processsing 2.88 3.47 8.07Grinder and dust collector operation 2.25 2.71 2.36Loader operation 0.63 0.76 0.66Pellet plant operation N/A N/A 5.04Conversion 53.36 69.23 56.11HTL buffer 34.44 41.46 36.15Electricity 4.17 5.02 4.44AD gas combustion in HTL burner 1.10 1.32 1.15AD operation 13.53 5.02 14.24Hydrogen production 0.07 16.34 0.07Hydrotreating catalyst 0.06 0.07 0.06Fuel distribution 0.17 0.20 0.17End use 5.00 6.02 5.28emission performance (11.60±4.14 g CO2-eq/MJ), followed by HTL (12.67±1.46 gCO2-eq/MJ from this study and 23.58±4.18 g CO2-eq/MJ from literatures) and lastlypyrolysis (33.77±16.24 g CO2-eq/MJ). Our results seem to be consistent with the gen-eral trend, although it is about 46% lower than the median value of HTL biofuelsresults from the literature. This could be explained by the much lower emission in-tensity of the BC electricity mix compared with the US electricity mix, which is usedin the two HTL LCA studies we reviewed [26, 64]. Another major reason could bethe credit assigned for by-products. In this study, we assume that by-product biocharapplied for soil amendment could create credits both from carbon sequestration in thesoil as well as the avoidance of nitrogen fertilizer production. In contrast, the othertwo studies do not consider the credit from biochar produced by HTL.38Figure 3.3: Comparison of HTL biofuels life cycle GHG emissions with literatures3.2.3 Sensitivity AnalysisTo investigate key factors influencing the GHG emissions of HTL biofuels, a sensi-tivity analysis is conducted by adjusting the nominal values of uncertain parametersto ±10%. For analyzing the impact of electricity mix, BC electricity mix is entirelydisplaced with Alberta (AB) electricity mix while keeping all other modelling param-eters unchanged. The parameters as well as their values used for sensitivity analysisare categorized and listed in Table 3.2. It should be noted that the life cycle GHGemissions are the net values with the biochar credit considered.As shown in Figure 3.4, although each scenario presented different results, in general,the most sensitive parameters are associated with process performance. The change ofHTL energy requirement and biofuel yield by 10% can lead to more than 10% variationof the GHG emissions for all scenarios. However, it should be noted that for Bo-DBRscenario, the 10% decrease of HTL energy requirement does not have appreciable im-pact on the GHG emissions. This is because at the nominal HTL energy requirementlevel, the HTL and AD units can be self-energized by biogas from AD as well as off-gases from HTL in Bo-DBR scenario. Therefore, further lowering the HTL energyrequirement will not make a difference.The 10% change in biomass content in slurry and carbon sequestrated in biochar showsa moderate impact (range of ±5% to ±10%). With a fixed biomass input, the biomass39Table 3.2: List of parameters used for sensitivity analysisCategory Parameters Nominal -10% +10%Feedstock property Moisture content of forest residues: wt% 48.91 44.02 53.80Feedstock supply Feedstock collection distance: km 12.5 11.25 13.75Process performance Biomass content in slurry for HTL: wt% 8.0 7.2 8.8Bio-oil yield: kg/kg dry wood 0.367 0.330 0.404HTL energy requirement: MW 50.4 45.38 55.46Biofuel yield: kg/kg bio-oil 0.75 0.68 0.83By-product credit Carbon sequestrated in biochar: wt% 80 72 88Location specificity Electricity mix: %BCa: Hydro:90.4; Biomass: 4.9; NG: 2.9; Fuel oil: 1.5; Wind: 0.3ABb: Coal:72.4; NG: 19.6; Wind: 3.6; Hydro: 3.5; Fuel oil: 0.9a From [17], average of 2010–2012, detailed emission factors are shown in Appendix B; b From[17], average of 2010–2012, detailed emission factors are shown in Appendix Bcontent in slurry can influence the total weight of slurry, which further determines theelectricity consumption of pumping as well as the input of HTL buffer Na2CO3. Asthe results in Table 3.1 suggest, the consumption of Na2CO3 is a crucial contributor tothe GHG emissions of HTL biofuels. Biochar, in this study, is assumed to be appliedfor soil amendment and creates GHG credits from carbon sequestration as well as theavoidance of nitrogen fertilizer production. Although there is uncertainty regarding thebiochar carbon stability in the soil, reported studies [95, 97] generally show a stableproperty of the biochar carbon. However, specific models need to be developed in thefuture to verify the carbon sequestration potential of HTL biochar.The 10% change in other parameters such as bio-oil yield, moisture content of forestresidues and feedstock collection distance has modest (within ±5%) impact on theGHG emissions. Although moisture content of forest residues is considerably sensitiveto Fr-CIR scenario, it makes little impact for Bo-DBR and Wp-CIR scenarios. Bio-oilyield does not influence the GHG emissions of HTL biofuels as much as biofuel yield,because the bio-oil yield has larger impact on the biochar credit, which can offset theimpact of other life cycle stages, than biofuel yield. The biochar credit is directly re-lated to biochar yield, which can be influenced by bio-oil yield from two layers. First,the change of bio-oil yield can impact the feedstock requirement, which leads to parallel40change of the yield of all HTL products, i.e., bio-oil, off-gases, biochar and PHWW.The second layer is that the bio-oil yield can influence HTL products profile. For exam-ple, the decrease of bio-oil yield will increase the fraction of biochar in HTL products.In contrast, the change of biofuel yield only has the first layer effect.Moisture content of feedstockDistance for biomass collectionBiomass content in slurryBio-oil yieldHTL energy requirementBiofuel yieldCarbon sequestered by biocharIncrease (+10%)Decrease (-10%)Wp-CIRBase LC GHG emissions=12.67 g CO2eq/MJMoisture content of feedstockDistance for biomass collectionBiomass content in slurryBio-oil yieldHTL energy requirementBiofuel yieldCarbon sequestered by biocharIncrease (+10%)Decrease (-10%)Bo-DBRBase LC GHG emissions=10.21 g CO2eq/MJ-30% -20% -10% 0% 10% 20% 30% 40%Moisture content of feedstockDistance for biomass collectionBiomass content in slurryBio-oil yieldHTL energy requirementBiofuel yieldCarbon sequestered by biocharChange of life cycle (LC) GHG emissions/% Increase (+10%)Decrease (-10%)Fr-CIRBase LC GHG emissions=13.69 g CO2eq/MJFigure 3.4: Sensitivity analysis of net life cycle GHG emissions of HTL biofuels41The significant impact of electricity mix on the HTL biofuels GHG emissions can beobserved in Figure 3.5. With more than 90% renewable composition, BC’s electric-ity mix is more favorable than that of AB. A change from BC electricity mix to ABelectricity mix can lead to a 168%, 225%, 182% increase in the GHG emissions forFr-CIR, Bo-DBR, Wp-CIR scenarios, respectively. Therefore, locating the potentialHTL system in a place with clean electricity mix like BC, can considerably lower theGHG emissions of HTL biofuels.Figure 3.5: Impact of electricity mix on net life cycle GHG emissions of HTL biofuels fordifferent scenarios3.2.4 Improving the GHG Performance of HTL BiofuelsBased on the life cycle “hot spots” and the key parameters impacting the GHG emis-sions of HTL biofuels identified, the following recommendations can be made to helpimprove the GHG emission performance of HTL biofuels produced in BC as well as toprovide insights for companies or investors who want to deploy such a facility:(1) Increase the recycling rate of HTL buffer Na2CO3 with the understanding of energyand materials consumption of the recycling process. Na2CO3 use has been iden-tified to contribute mostly to the life cycle GHG emissions of the proposed HTLplant in BC. According to our analysis, if the recycling rate of the buffer increasesby 25%, the GHG emissions can be reduced by 13%∼17%. This is a promising42way to further increase the environmental performance of HTL biofuels, while theenergy and materials input associated with the recycling need to be first clearlyunderstood.(2) Lower the transportation emissions by densifying biomass feedstock before trans-portation to conversion facilities. For long distance transportation of feedstockwith high moisture content, we recommend to first convert these raw materialsinto high energy density intermediates such as bio-oil or wood pellet. If such in-frastructure is available within a reasonable distance, it will be ideal to utilizesuch existing facility. Otherwise, the economics of constructing the new infrastruc-ture, or alternatively, purchasing the mobile conversion devices, needed to be firstinvestigated.(3) Increase the process performance of the HTL biofuel system. Specifically, mainefforts need to be put on increasing the energy efficiency of HTL and maximizingthe biofuel yield. This relies on the optimization of system design, e.g., integratedwith AD, to reduce the fossil energy input. Other improvement can be made inincreasing the biomass content in the slurry. With the advancements of pumptechnology, transmission of large scale biomass-water slurry would be feasible.(4) Make full use of the process by-products, i.e., off-gases, biochar and PHWW, tocreate GHG savings. Off-gases can be used as either heating fuel for different op-eration units or feedstock for hydrogen production to avoid the input of externalNG. Biochar applied for soil amendment can create credits from both carbon se-questration and the avoidance of nitrogen production, while specific models needto be developed to verify the carbon sequestration potential of biochar to reducethe uncertainty. HTL can be integrated with an AD unit in order to recover energyfrom the PHWW, hence increase the energy efficiency of HTL.(5) Locate the HTL biofuel system in a place with favorable electricity mix. This canmake a big difference, as shown in the comparison of the impact of electricity mixof BC and AB on the GHG emission of HTL biofuels (Figure 3.5).433.3 ConclusionThis chapter quantifies the life cycle GHG emissions of a hypothetic 100 MLPY HTLbiofuel production system in BC based on three different scenarios. The results suggestthat compared with conventional petroleum fuels, up to 89% GHG emission reductioncan be achieved by HTL biofuels with the biochar credit considered. The conversionstage dominates the total emissions, contributing more than 50%. The process emit-ting most GHGs over the life cycle of HTL biofuels is HTL buffer production, resultedfrom the large amount of buffer consumed to maintain the pH of biomass slurry in theHTL process. Recycling of the HTL buffer thus needs to be further investigated toreduce the impact. Converting forest residues to bio-oil and wood pellet before trans-portation can significantly lower the transportation emissions and contribute to theconsiderable reduction of the life cycle GHG emissions of HTL biofuels. A sensitivityanalysis indicates the importance of process performance parameters, such as HTLenergy requirement and biofuel yield, as well as the location specific parameter suchas the electricity mix. Therefore, main efforts can be put on increasing the energy effi-ciency of HTL and maximizing the biofuel yield to further improve the GHG emissionperformance of HTL biofuels.44Chapter 4HTL biofuel TEA4.1 Economic AnalysisThe following subsections describe the methods for estimating the feedstock deliveredcost, capital investment and operating cost of the three HTL biofuel production sce-narios, as well as the method for calculating the minimum selling price (MSP) of thebiofuel products. The economic analysis is carried out based on each stage as describedin the Chapter 2 and the detailed stage-wise results can be found in Appendix D. Itshould be noted that the costs associated with biofuel distribution and end use are notincluded in the economic analysis.4.1.1 Feedstock Delivered CostThe feedstock delivered cost covers the raw material cost, machinery cost and trans-portation cost to the gate of refinery. To estimate the feedstock delivered cost, themethod proposed by Akhtari [98] is used. It should be noted that the conversion costof forest residues to bio-oil or wood pellet in Bo-DBR and Wp-CIR scenarios is notincluded in feedstock delivered cost, instead it is included in the capital and operatingcosts of the plants to avoid double counting, which will be thoroughly described inlater subsections.45Raw Material CostRaw material cost is the cost for purchasing the forest residues left on logging sites.Usually these forest residues are regarded as a waste of logging operation and wouldbe left onsite and burned as a part of forestry management in BC [9], hence they canbe purchased at a low price, in this study we used $3/dry tonne forest residues [10].The amount of forest residues purchase is shown in Table 2.5. The raw material costis the product of the purchase price and the amount.Machinery CostWe assume that piled forest residues on the forest stands are first chipped for sizereduction and loaded to dump truck, and then transported to the nearby FDP, wherethe chipped residues from different forest stands are unloaded and reloaded to thesemi-trailers for transportation to conversion facility. Therefore, the machinery costincludes the capital and operating costs for loaders and chippers used in forest residuescollection. The capital costs contain the purchase cost, insurance and tax cost of load-ers and chippers, and the operating costs include fuel and lubricant cost, labor andmaintenance cost and annual depreciation. The assumptions for machinery cost esti-mation are listed in Table 4.1.The capital cost is converted to an annuity by multiplying a capital recovery factor(CRF), where i is the interest rate and n is the life time of the machine:CRF =i(i + 1)n(i + 1)n − 1 (4.1)The insurance and tax cost (Ci) is estimated as a fraction of machine purchase price:Ci = P× fi (4.2)Where P is the machine purchase price, fi is the insurance and tax cost fraction ofmachine price. Annual depreciation (D) is calculated as:D = (1− fs)× Pn(4.3)Where fs is the salvage fraction of machine price. Fuel and lubricant cost (Cfl) is46Table 4.1: Assumptions for machinery cost estimationParameter NotationLoaderChipperat forest stands/at FDPsPurchase price ($/machine) P 240000 200000Machine life (years) n 10 10Interest rate (%) i 6.5 6.5Insurance and tax rate (% of purchase price) fi 2.5 2.5Scheduled machine hours (SMH) per year SMH 1200/3000 1200Utilization rate (%) u 65 75Productive machine hours (PMH) per year PMH 780/1950 900Fuel (diesel) consumption (L/PMH) F 7.96/14.24 29.22Fuel cost ($/L) Fc 1.2 1.2Lubricant cost (% of fuel cost) fl 36.8 36.8Number of operators N 1 0Labor rate of operator ($/hr) w 25 25Fringe benefit of operator (% of wage) fb 30 30Salvage value (%) fs 30 20Repair and maintenance (% of depreciation) fr 90 100Productivity of machine (GMT/PMH) MP 19/34 19Note: data from [98] with modification; SMH = Working hours per day × working days per year;PMH = SMH × u; GMT = green metric toncalculated as:Cfl = F× Fc × (1 + fl)× PMH (4.4)Where F is the fuel consumption in L/PMH, Fc is the fuel cost in $/L, and fl is thelubricant cost fraction of fuel cost. Labor cost Cl was calculated as:Cl = N× w × (1 + fb)× SMH (4.5)Where N is the number of operator required, w is the labor rate of operator in $/hr,and fb is the benefit fraction of labor cost. The machine repair cost (Cr) was calculatedusing the following equation, Where fr is the maintenance and repair cost fraction.47Cr = D× fr (4.6)When the annual machinery cost (Ctot) has been calculated, the cost per unit of forestresidues collected can be obtained using the following equation:per unit cost =CtotAnnual biomass production(4.7)and the annual biomass production can be calculated as:Annual biomass production = PMH×MP (4.8)Based on the above calculations, the annualized machinery cost per machine and thenumber of machines required at each FDP are in Table 4.2 and Table 4.3, respectively.Table 4.2: Annual machinery cost summary ($/yr/machine)ParameterLoaderChipperat forest stands/at FDPsCapital cost 3.94E+04 3.28E+04Equipment purchase cost 3.34E+04 2.78E+04Insurance and tax cost 6.00E+03 5.00E+03Operating cost 8.11E+04 / 1.75E+05 7.52E+04Annual depreciation 1.68E+04 1.60E+04Fuel and lubricant cost 1.02E+04 / 4.56E+04 4.32E+04Labor cost 3.90E+04 / 9.75E+04 0.00E+00Repair and maintenance cost 1.51E+04 1.60E+04Total cost 1.20E+05 / 2.14E+05 1.08E+05Annual biomass production (GMT/yr) 1.48E+04 / 6.63E+04 1.71E+04Per unit cost ($/GMT) 8.13 / 3.23 6.32Transportation CostTransportation cost covers the cost of shuttling forest residues from forest stands toFDPs using dump truck and transporting forest residues or bio-oil or wood pellet from48Table 4.3: The number of machines required at each FDPParameterLoaderChipperat forest stands/at FDPsChilliwack 10 / 2 9Squamish 4 / 1 4Powell River 16 / 4 14Port Alberni 9 / 2 8Total 40 / 9 34FDPs to Chevron oil refinery, including trucks rental cost and labor cost, which iscalculated using Equation 4.9 as below:Ct = H× (tt + tw) (4.9)Where Ct is the transportation cost, H is the transportation hourly rate includingtruck rental cost and labor cost, tt is the transportation time, tw is the waiting timefor loading and unloading, etc. The assumptions for estimating transportation cost arelisted in Table 4.4.Table 4.4: Assumptions for transportation cost estimationParameter Dump truck ST or LTT FerryAverage speed (km/h) 40 60 16b;25cWaiting time for loading and unloading, etc. (hr) 2 2 4.3Payload of truck (tonne) 11.8 23.25 30 (m3)Hourly ratea ($/hr) 55d 85e 6.5f($/foot)a Include vehicle rental cost and labor cost; b In the marine route from Powell River to Chevronoil refinery; c In the marine route from Port Alberni to Chevron oil refinery; d From [99]; e From[100]; f Reservation cost of ST or LTT on ferry is based on the length of the truck [101], whichwas assumed to be 23 m; ST: semi-trailer; LTT: liquid tanker truck494.1.2 Capital InvestmentThe capital investment is estimated using the factor method summarized in Table 4.5.The method begins with the total purchased equipment cost (TPEC) of major processequipment or operation unit based on literatures [26, 102] and scales to the specificcapacity using the following cost-capacity relationship:Cnew = Cbase ×(SnewSbase)x(4.10)where Cbase is the base cost of equipment of base capacity Sbase, Cnew is the new cost ofequipment of new capacity Snew and x is the scaling factor, which is assumed to be 0.7in this study [103]. Other capital investment elements are estimated based on TPEC.The reference costs of the specific process equipment or operation unit for biorefineryand wood pellet plant can be found in Table D.2 and Table D.7, respectively, in Ap-pendix D. The capacity, feed rate and productivity of the studied biorefinery and woodpellet plants are shown in Table D.3 of Appendix D.It should be noted that in this study we assume that bio-oil is upgraded in an existingChevron oil refinery, hence, we do not consider the capital investment associated withbuilding the upgrading infrastructure in view of the transition of fossil fuels to renew-able biofuels in the future. Specifically, the capital investment of Chevron refinery isnot considered in neither integrated refinery scenarios, i.e., Fr-CIR and Wp-CIR, nordistributed biorefineries scenario, i.e., Bo-DBR.4.1.3 Operating CostThe major assumptions for estimating the operating cost are summarized in Table4.6. The operating cost includes variable part and fixed part. The variable operatingcost consists of the costs associated with purchasing feedstock, catalyst and chemicals,utilities and the treatment of wastes. The cost of feedstock is essentially the feedstockdelivered cost from forest stands to plant, the estimation of which has been describedin Subsection 4.1.1. The fixed cost covers the costs of labor, maintenance and supplies,property tax and insurance, and plant overhead. Besides, the credit from selling theby-product biochar is also considered. Three types of labor are involved, i.e., operatinglabor, maintenance labor and supervisory labor. The operating and maintenance labor50Table 4.5: Methods for estimating the capital investment of the HTL biofuel systemParameter Methods ReferenceCapital investment Biorefinery/Wood pellet plantDepreciable cost (DepC) TIC+ICTotal installed cost (TIC) 2.47a/Xb*TPECTPEC 100%Indirect cost (IC) 1.2/1.23*TPECEngineering 32%/33% [53]Construction 34%/39% [53]Contractor fees 18%/17% [53]Contingency 36%/34% [53]Non-depreciable cost (NDepC) 3.99%/4.35% of DepCLand cost 1.5% of DepC [53]Site development 2.49%/2.85% of DepC [53]Fixed capital investment (FCI) DepC+NDepCStart-up cost (SC) 9% of FCI [104]Working capital (WC) 20% of FCI [103]Total capital investment (TCI) FCI+SC+WCa from [105]. The installation factor 2.47 was used for all operating units in HTL biorefinery.This factor covers the costs including equipment installation, instrumentation and controls,piping, electrical systems, building and yard improvement; b from [103]. X is the individualfactor varied with specific equipment modules and the details are presented in Appendix D.requirement is estimated by the following equation from US EPA [106].Lnew = Lbase ×(VnewVbase)y(4.11)Where Lbase is the base labor requirement of base plant of capacity Vbase, Lnew is thenew labor requirement of new plant of capacity Vnew and y is the scaling factor, whichis assumed to be 0.25 in this study. The base plant capacity and labor requirement forbiorefinery and wood pellet plant are referenced from study by Tews et al. [26] andHoque et al. [102], respectively. The supervisory labor cost is assumed to be 20% of theoperating labor cost [103]. The maintenance cost, including materials and operatingsupplies, and the property tax and insurance, are estimated as 2.55% and 3% of FCI,respectively [53]. The plant overhead is assumed to be 72% of the total labor cost [53].51Table 4.6: Methods for estimating the operating cost of the studied HTL biofuel systemParameter Methods ReferenceVariable operating cost (VOC)Feedstock delivered cost see Subsection 4.1.1Catalyst and chemicalsNa2CO3 price, $/tonne 275 [107]Ni/Mo/Al2O3 price, $/kg 34 [108]Waste disposalWaste disposal cost, $/tonne 0.73 [26]UtilitiesElectricity price, $/kWh 0.057 [109]Diesel, $/L 0.97 [110]Natural gas, $/GJ 2.84 [111]Propane, $/L 0.54 [112]Wood wastes, $/dry tonne 3a [113]Fixed operating cost (FOC)Labor costOperating labor rate, $/hr 24 [114]Maintenance labor rate, $/hr 28 [114]Supervisory labor rate, $/hr 20% of operating labor cost [103]Maintenance and supplies 2.55% of FCI1 [53]Property tax and insurance 3% of FCI [103]Plant overhead 72% of total labor cost [53]Total operating cost VOC+FOCBy-product (biochar) price, $/tonne 385b [115]a The wood wastes used in the pellet plant operation was assumed to be part of the forest residuesinput; b Took the average of high-end price $500/ton (equivalent to $550/tonne) and low-end price$200/ton (equivalent to $220/tonne)1It can be derived that the maintenance cost of biorefinery equals 0.097*TPEC based on informa-tion provided in Table 4.5. It should be mentioned that we used a different method for estimatingthe maintenance cost for equipment used in feedstock collection. By combining Equation 4.3 and 4.6,it can be derived that the maintenance cost of the feedstock collection machine equals 0.063*TPECbased on the information provided in Table 4.1. We keep using these two different methods for sep-524.1.4 Minimum Selling PriceThe MSP of HTL biofuels is calculated using discounted cash flow rate of return(DCFROR) analysis, which manipulates the fuel selling price to find the breakevenpoint where the project net present value (NPV) equals zero. The calculation is per-formed by iteration in Excel using self-developed Excel VBA code and the detailedspreadsheet can be found in Appendix E. Table 4.7 presents the major assumptionsused in DCFROR analysis.Table 4.7: Major assumptions for DCFROR analysisParameter AssumptionsInternal rate of return (IRR) 10%Plant life time 20 yearsPlant annual operating time 8000 hours/yrPlant financing by equity/debt 40%/60% of total capital investmentInterest rate for debt financing 6.5% annuallyTerm for debt financing 10 yearsSalvage value 0Depreciation schedule 7-year MACRSa scheduleIncome tax rate 26%Construction period (spending schedule) 3 years (year 1: 30%, year 2: 50%, year 3: 20%)Start-up time 3 monthsRevenue and costs during start-up Revenue = 50% of normalVariable operating cost = 75% of normalFixed operating cost = 100% of normala MACRS = Modified Accelerated Cost Recovery SystemIt should be noted that the MSP of HTL biofuels is calculated as the price of biofuelmix, including gasoline, jet, diesel and heavy oil in a unit of $/L. In addition, for a con-sistent comparison with the price of petroleum gasoline, the liter gasoline-equivalent(LGE) price at $/LGE for the biofuel product mix is calculated using Equation 4.12arate parts of this study as the maintenance cost does not contribute much and also the cost formaintaining the equipment used in biorefinery and feedstock collection could be different.53to account for the difference in heating value.MSP($/LGE) =MSP of final product×Gasoline HHVFinal product HHV(4.12)The HHV of biofuel product mix is calculated to be 37.9 MJ/L based on the prod-uct distribution and the HHVs of individual component (34.7, 37.4, 38.6 and 41.35MJ/L for bio-based gasoline, jet, diesel and heavy oil, respectively), while the HHV ofpetroleum gasoline is assumed to be 34.7 MJ/L.4.2 Results and Discussion4.2.1 Cost EstimationTable 4.8 summarizes the major costs of the 100 MLPY HTL biofuel system for theinvestigated scenarios. The TCI is dominated by the installed equipment cost, whichaccounts for about 50% for all scenarios. Fr-CIR scenario has the lowest capital invest-ment as expected, and the other two scenarios have a higher capital investment as aresult of the economy of scale, i.e., several small distributed plants need more capitalinvestment than a large centralized plant of the same total capacity, and additionalinfrastructure construction, i.e., wood pellet plants. The detailed installed equipmentcost of three studied scenarios is shown in Figure 4.1(a). The results indicate that theHTL reactor system requires the most capital expense, making up about 70% of theTIC on average for three scenarios. Therefore, the cost reduction of the HTL reactorsystem is significant for lowering the TCI.Figure 4.1(b) demonstrates the detailed operating cost. Bo-DBR scenario has the low-est operating cost, followed by Fr-CIR scenario and lastly Wp-CIR scenario. The fixedoperating costs of Bo-DBR and Wp-CIR scenarios are both higher than the Fr-CIRscenario, because most of the elements in fixed operating cost, such as plant overheadand the property tax and insurance are estimated based on the FCI (see Table 4.5). Incontrast, the variable operating cost of these two scenarios are 32% and 8% lower. Themain reason is the reduction in feedstock cost. As the pie chart of Figure 4.1(b) shows,54the feedstock cost of Fr-CIR scenario is dominated by the transportation cost, whichmakes up about 73%, indicating that the long-distance transportation of low energydensity bulky forest residues is not a cost-effective option. Bo-DBR and Wp-CIR sce-narios try to address this issue by converting the bulky forest residues into high energydensity intermediates, i.e., bio-oil and wood pellet. This strategy shows a reduction ofthe feedstock cost by 48% and 20% for Bo-DBR and Wp-CIR scenarios, respectively.Bo-DBR scenario successfully reduces the total operating cost by lowering the feed-stock cost, however, Wp-CIR scenario fails to do so as the increase of fixed operatingcost and other variable operating costs outweigh the decrease of feedstock cost.For comparing the overall economic feasibility, MSPs of different studied scenarios arecalculated based on an assumed minimum acceptable IRR of 10% and the results areshown in Table 8. Fr-CIR scenario achieves the lowest MSP at $0.89/L, followed byBo-DBR scenario at $0.97/L and Wp-CIR scenario at $0.98/L. When compared withthe 2016 gasoline wholesale price in Vancouver at $0.50/L [116], the MSPs of HTLbiofuels ($/LGE) are 63% to 80% higher, which means under current circumstance,the HTL biofuels are not economically competitive with petroleum fuels. To promotethe HTL biofuels, government incentives would be needed, or technology should beadvanced to bring down the production cost of HTL biofuels.4.2.2 Comparison with Peer-reviewed LiteratureIn order to check whether the MSP of HTL biofuels from this study agree with thosefrom peer-reviewed literature, we compare our results with the literature data presentedin Table 1.3. For a specific conversion pathway, the median value of the results from allstudies is used instead of the mean, because the mean can be easily influenced as theresults varied from study to study. Figure 4.2 compares the MSP results of differentbiofuel thermochemical conversion pathways. The literature results show that pyrolysishas the best economic performance ($0.82±0.38/L), followed by HTL ($0.85±0.29/L)and lastly gasification ($1.22±0.27/L). The result from our study ($0.97±0.04/L) isabout 12% higher than the median value of literature results for HTL biofuels. This isdue to the variance in the system configuration, factors and parameters used for processmodeling, estimating the capital investment and operating cost as well as calculatingthe MSP. Since this study aims at a preliminary assessment of the economic feasibility55020406080100120140Fr-CIR Bo-DBR Wp-CIROperating cost (million $)Plant overhead Property tax and insurance Maintenance and supplies LaborUtilities Waste Treatment Catalyst FeedstockTransporta-tion47%Machine49%Raw material4%Transportation73%Machine25%Raw material2%Variable costFixed costVariable costFixed costVariable costFixed costTransportation62%Machine35%Raw material3%Fixed cost:Variable cost:(b)0306090120150180210240Fr-CIR Bo-DBR Wp-CIR Pellet PlantInstalled cost (million $)Biomass preparation HTL reactor systemAnaerobic digestion UtilitiesPellet plant totalBiorefineryBiorefineryBiorefinerySolid fuel burner, 8%Rotary drum dryer, 25%Drying fan, 2%Multiclone, 3%Hammer mill, 5%Pellet mill, 23%Pellet cooler, 3%Screen shaker, 1%Packaging unit, 5%Storage bin, 1%Misc. equipment, 8%Front end loader, 8%Fork lift, 6%0%100%(a)BiorefineryFigure 4.1: Detailed installed equipment cost and operating cost of studied HTL biofuel sce-narios (the pie chart in part (b) represents the distribution of the feedstock cost)of HTL biofuels in BC, the factors used in the cost estimation tend to be conservative.56Table 4.8: Estimated costs for the HTL biofuel systemFr-CIR Bo-DBR Wp-CIRCapital investment, million $Total installed cost (TIC) 120.4 178.8 138.0Indirect cost (TIC) 58.5 86.9 68.1Non-depreciable cost 7.1 10.6 8.3Fixed capital investment (FCI) 186.0 276.2 214.4Start-up cost (SC) 16.7 24.9 19.3Working capital (WC) 37.2 55.2 42.9Total capital investment (TCI) 240 356.3 276.6Annual operating cost, million $/yearVariable operating cost 50.7 34.7 46.6Fixed operating cost 16.0 26.4 24.6Total annual operating cost 66.7 61.2 71.2Annual sales, million $/yearMain products – biofuels 89.2 97.4 98.1By-product – biochar 6.5 6.5 6.5Total annual sales 95.7 103.8 104.6Minimum selling price (MSP), $/L 0.89 0.97 0.98Minimum selling price (MSP), $/LGE 0.82 0.89 0.904.2.3 Impact of Carbon Tax and Technology AdvancementTo mitigate the global warming impact, BC government has implemented a carbon taxsince 2008 [117], which is levied based on the life cycle GHG emissions of a fuel. Theinitial carbon tax is 10 Canadian dollar (CAD) per tonne of CO2-eq, and it increased to30 CAD/tonne CO2-eq in 2012. In 2016, BC government implemented a Climate Lead-ership Plan to further enhance GHG emission mitigation and help BC move towards2050 emissions reduction target of 80% below 2007 level [5]. The Climate LeadershipTeam had called for a 10 CAD increase in carbon tax beginning in 2018 [118].570.000.250.500.751.001.251.501.75HTL HTL Gasification PyrolysisThis study LiteraturesMinimum fuel selling price ($/L)Figure 4.2: MSP of HTL biofuels from this study and literaturesFigure 4.3 shows the trend of BC carbon tax with a 10 CAD increase per year startingfrom 2018, the net petroleum price (NPP) and the net minimum selling price (NMSP)of HTL biofuels under the impact of increasing carbon tax. The initial MSPs of HTLbiofuels are based on the MSPs of HTL biofuels from three studied scenarios, i.e.,$0.82/LGE, $0.89/LGE and $0.90/LGE for Fr-CIR scenario, Bo-DBR scenario andWp-CIR scenario, respectively. The initial petroleum price is assumed to be $0.50/L[116]. The life cycle GHG emission of petroleum fuel is based on 2005 gasoline base-line 93 g CO2-eq/MJ (equivalent to 3226 g CO2-eq/L) [96], while the life cycle GHGemissions of HTL biofuels are 20.5 g CO2-eq/MJ (equivalent to 778 g CO2-eq/L), 17.0g CO2-eq/MJ (equivalent to 646 g CO2-eq/L) and 19.5 g CO2-eq/MJ (equivalent to739 g CO2-eq/L) for Fr-CIR scenario, Bo-DBR scenario and Wp-CIR scenario, respec-tively, based on the results from Chapter 3.With the impact of carbon tax, the price gap between HTL biofuels and petroleum fuelshrinks year by year. The breakeven points are achieved when the carbon tax reaches$130/tonne CO2-eq in 2030 for Fr-CIR scenario, $154/tonne CO2-eq in 2033 for Bo-DBR scenario and $162/tonne CO2-eq in 2034 for Wp-CIR scenario, corresponding tothe NMSP of HTL biofuels at $0.92/LGE, $0.99/LGE and $1.02/LGE, respectively.The analysis would be conservative without the impact of technology advancement be-58ing accounted for, but even if a 1% cost reduction per year is assumed to be achieved bythe advancement of HTL technology, the breakeven points are achieved in 2026, 2028and 2029 with the NMSP of HTL biofuels at $0.81/LGE, $0.86/LGE and $0.88/LGEfor Fr-CIR, Bo-DBR and Wp-CIR scenario, respectively. Hence, under current tech-nology status, carbon tax should be counted as a key incentive, while from a long-termpoint of view, the technology should be advanced to bring down the production costof HTL biofuels.040801201602002402800.450.550.650.750.850.951.051.151.251.352017 2020 2023 2026 2029 2032 2035 2038Carbon tax ($/tonne CO2-eq)Net fuel price($/LGE)YearNPPNMSP (Fr-CIR)NMSP (Bo-DBR)NMSP (Wp-CIR)Carbon taxBreakeven points informationFr-CIR=(2030, 0.92, 130)Bo-DBR=(2033, 0.99, 154)Wp-CIR=(2034, 1.02, 162)Figure 4.3: Impact of carbon tax on petroleum fuel and HTL biofuels price (carbon tax wasconverted from Canadian dollars to US dollars using exchange rate of 1 CAD = $0.81;NPP: net petroleum price; NMSP: net minimum selling price)4.2.4 Sensitivity AnalysisLarge-scale commercial HTL plants have not been reported. The uncertainty existsin the process design and cost estimation of the proposed HTL biofuel system dueto the reliance on literature data. To investigate key factors influencing the MSP ofHTL biofuels, a sensitivity analysis is conducted by adjusting the nominal values ofuncertain parameters by ±10%.59As shown in Figure 4.4, although each scenario presents different results, in general, themost influencing parameters are associated with conversion processes, i.e., bio-oil andbiofuel yield. The yield of intermediate and final products can significantly influencethe input and output of other materials, as well as the energy consumption associatedwith the entire supply chain of HTL biofuels. It further implies that the technologyadvancement to improve the conversion and energy efficiency of HTL will make keycontributions in reducing the costs of HTL biofuels. The property of raw material,i.e., the moisture content of forest residues, also matters, but shows different effect oneach scenario. Fr-CIR scenario is the most sensitive, because the moisture content offorest residues can largely determine the cost of feedstock transportation, which has asignificant contribution to the total operating cost of Fr-CIR scenario as discussed inthe previously (Figure 4.1(b)). In contrast, the moisture content has less impact onthe other two scenarios since the raw bulky forest residues are first converted to highenergy density intermediate products before transportation. The cost estimation fac-tors, such as debt interest rate and IRR, have a moderate impact on the MSP of HTLbiofuels. Besides, the price of raw material, HTL buffer and by-product show littleinfluence, i.e., the change rates of MSP are within ±1.2% based on a ±10% change ofthe nominal values.4.3 ConclusionThis chapter estimates the capital investment and operating cost of a hypothetic 100MLPY HTL biofuel production system in BC based on three different supply chaindesigns. The MSP of HTL biofuels is estimated to be $0.82/LGE-$0.90/LGE, which isabout 63%-80% higher than that of petroleum fuel. Converting forest residues to bio-oil and wood pellet before being transported to the conversion facility can significantlyreduce the variable operating cost, but the MSPs of HTL biofuels are found to be9%-10% higher, respectively, due to a considerable increase in capital investment. Asensitivity analysis indicates the importance of technology advancement, such as theincreased yield of bio-oil and biofuel, to the economic performance of HTL biofuels.With the increasing carbon tax and technology advancement, HTL biofuels will becomecompetitive with petroleum fuels.60-15% -10% -5% 0% 5% 10% 15%Interest rate 5.9: 6.5: 7.2 (%)IRR 9:10:11 (%)Biochar price 347: 385: 424 ($/tonne)Forest residues price 2.7: 3: 3.3 ($/dry tonne)HTL buffer price 248: 275: 303 ($/tonne)Bio-oil yield 0.33: 0.37: 0.4 (kg/kg dry feedstock)Biofuel yield 0.68: 0.75: 0.83 (kg/kg bio-oil)Forest residues mositure 44: 49: 54 (%)Change of MSP/% Increase (+10%)Decrease (-10%)Base MSP=$0.98/LWp-CIRInterest rate 5.9: 6.5: 7.2 (%)IRR 9:10:11 (%)Biochar price 347: 385: 424 ($/tonne)Forest residues price 2.7: 3: 3.3 ($/dry tonne)HTL buffer price 248: 275: 303 ($/tonne)Bio-oil yield 0.33: 0.37: 0.4 (kg/kg dry feedstock)Biofuel yield 0.68: 0.75: 0.83 (kg/kg bio-oil)Forest residues mositure 44: 49: 54 (%)Increase (+10%)Decrease (-10%)Bo-DBRBase MSP=$0.97/LInterest rate 5.9: 6.5: 7.2 (%)IRR 9:10:11 (%)Biochar price 347: 385: 424 ($/tonne)Forest residues price 2.7: 3: 3.3 ($/dry tonne)HTL buffer price 248: 275: 303 ($/tonne)Bio-oil yield 0.33: 0.37: 0.4 (kg/kg dry feedstock)Biofuel yield 0.68: 0.75: 0.83 (kg/kg bio-oil)Forest residues mositure 44: 49: 54 (%)Increase (+10%)Decrease (-10%)Base MSP=$0.89/LFr-CIRFigure 4.4: Sensitivity analysis of the MSP of HTL biofuels for different scenarios61Chapter 5Conclusion and Future WorkThe transportation sector of British Columbia (BC) is the leading contributor of re-fined petroleum fuels consumption and greenhouse gas (GHG) emissions. Therefore,it has become a hard nut for BC in moving toward its ambitious target of 80% GHGemission reduction by the middle of this century. Drop-in biofuels have been attractingthe government’s attention in mitigating the intensive emissions and high reliance onfossil fuels of the transportation sector. To date, there has been nearly no large-scalecommercial plants reported for drop-in biofuels production using sustainable feedstocklike forest residues, which are abundantly available but under-utilized in BC. Althoughnumerous scientific studies and demonstration projects have been conducted to try tosolve the technical bottlenecks, there has been very limited comprehensive and sys-tematic evaluation on the environmental and economic performance of the conversiontechnologies, let alone a study based on BC’s situation. According to a state-of-the-artreview of the literature, we have identified a promising but under-studied thermochem-ical conversion technology called hydrothermal liquefaction (HTL) and quantified theenvironmental and economic impacts of deploying a HTL biofeul system in BC to fillthe gap. The results of this study can help provide a preliminary insights for otherresearchers and local companies or investors as well as a reference for a governmentpolicy makers.A life cycle assessment (LCA) and a techno-economic assessment (TEA) are conductedto quantify the GHG emission and the minimum selling price (MSP) of biofuels pro-duced from a hypothetic 100 million liters per year (MLPY) HTL biofuel system inBC based on three different supply chain designs. The results suggest that comparing62with conventional petroleum fuel, up to 89% GHG emission reduction can be achievedby HTL biofuel with the by-product biochar credit considered, but at a MSP of $0.82-$0.90/LGE (liter gasoline-equivalent), which is about 63%-80% higher than that ofpetroleum fuels. The conversion stage dominates the total GHG emissions, making upmore than 50%. Converting forest residues to bio-oil and wood pellet before trans-portation to the upgrading facility contributes to a considerable reduction of the lifecycle GHG emissions and the variable operating cost, but not the MSP because of asignificant increase in capital investment. Sensitivity analysis indicates the importanceof process performance parameters, such as the energy requirement of HTL and theyield of biofuel, to both the life cycle GHG emissions and the MSP. Thus, technologyshould be advanced to further reduce the GHG emissions and bring down the produc-tion cost of HTL biofuels. Otherwise, to make HTL biofuels economically competitivewith petroleum fuels, a high carbon tax is needed.The following limitations in this study that need to be addressed in the future work:1. This study relies largely on secondary data from literature for the process modellingand environmental and economic assessment since there are currently no industrialdata available. The key parameters influencing the environmental or economic per-formance of HTL biofuels, such as the energy requirement of HTL, the product yieldand the recycling of HTL buffer agent remain uncertain. For HTL buffer productionfor use in HTL, it is the process which emits most GHGs over the life cycle. Thematerial and energy input associated with the recycling of HTL buffer agent needto be determined. Besides, this study aims at a preliminary economic assessmentof the HTL system, so the parameters used for economic modelling is relativelyconservative. Thus, the data quality ought to be improved in the future to accountfor the industrial practice as well as the specific conditions in BC.2. A more realistic model about the supply of forest residues needs to be built inthe future. In this study, we used an assumed average distance for forest residuescollection due to the lack of the specific location of forest stands, and also theavailability of feedstock was based on an estimated five-year average data. Theuncertainty usually involved in the real-world practice as the supply and the price offorest residues may vary with seasons or other disturbances. The operation of forestresidues supply system needs to be optimized with such uncertainty considered,63and the trade-offs between the environmental and economic objectives need to beaccounted for in order to build a more realistic model.3. In the HTL system, some optimistic assumptions made in the process modellingneed to be checked as the technology matures in the future. For example, the off-gases from HTL and hydrotreating are used as feedstock for hydrogen production,the post HTL waste water (PHWW) can be used to produce biogas from AD, andthe bio-oil produced from HTL can be co-upgraded with crude oil. There have beenno industrial practice of these assumptions so far, therefore, these assumptions needto be validated in the future.4. The following two scenarios are worthwhile to be examined in the future to seewhether it can improve the economic performance of HTL biofuels. First, usingmobile units for HTL of forest residues rather than building the distributed HTLinfrastructure. The operation of these mobile units need to be optimized first basedon the supply of forest residues in BC so it can maximumly reduce the capital andoperating costs. Second, putting the proposed HTL biofuel system in a place ofBC with existing wood pellet industry to avoid building the new pellet plants, suchas Prince George, so that the capital investment of the Wp-CIR scenario can bebrought down.64Bibliography[1] Ann Pa, Jill S. Craven, Xiaotao T. Bi, Staffan Melin, and Shahab Sokhansanj.Environmental footprints of British Columbia wood pellets from a simplified lifecycle analysis. International Journal of Life Cycle Assessment, 17:220–231, 2012.→ pages x, 3, 37, 88[2] M. Delucchi and Levelton. GHGenius v4.03. http://www.ghgenius.com/, 2013.Access on 2015-09-07. → pages x, 23, 24, 34, 86, 87, 89, 90, 91, 92, 93, 94[3] Government of British Columbia. BC Bioenergy Strategy: Growing our naturalenergy advantage. Technical report, 2008. → page 1[4] Kendal Bradburn. 2014 CanBio report on the status of bioenergy in Canada.Technical report, Renewed Energies, 2014. → pages 1, 3[5] Government of British Columbia. Climate Leadership Plan - British Columbia.Technical Report August, 2016. → pages 1, 57[6] Statistics Canada. Report on energy supply and demand in Canada (2014 Revi-sion). Technical report, Statistics Canada, Ottawa, 2017. → page 1[7] Government of British Columbia. Provincial inventory tables, 1990-2014. http://www2.gov.bc.ca/gov/content/environment/climate-change/data/provinical-inventory, 2016. Access on 2017-06-05. → page 1[8] British Columbia Ministry of Environment. Climate Action in British Columbia2014 Progress Report. Technical report, British Columbia Ministry of Environ-ment, 2014. → page 1[9] City of Vancouver. Renewable City Strategy. Technical report, City of Vancou-ver, Vancouver, 2015. → page 1[10] Sergios Karatzos, James D McMillan, and Jack N Saddler. The Potential andChallenges of Drop-in Biofuels. Technical Report July, IEA, 2014. → page 2[11] Wei-Cheng Cheng Wang and Ling Tao. Bio-jet fuel conversion technologies.Renewable and Sustainable Energy Reviews, 53:801–822, Jan 2016.65[12] American Society for Testing and Materials. Standard specification for aviationturbine fuel containing synthesized hydrocarbons. Technical report, ASTM, 2015.→ page 2[13] Jack Saddler, Xiaotao Bi, Shahab Sokhansanj, and Susan van Dyk. An as-sessment of the potential viability of producing biojet from woody biomass inwestern canada (unpublished). Technical report, University of British Columbia,Vancouver, 2015. → pages 3, 18, 32[14] Industrial Forestry Service Ltd. Wood based biomass in British Columbia andits potential for new electricity generation. Technical Report July, 2015. → page3[15] Wood Pellet Association of Canada. British Columbia’s wood pellet industry.https://www.pellet.org/images/WoodPelletFactsheet.pdf, 2011. Access on 2017-01-02. → page 3[16] Arnold Dale. Production and consumption of wood pellets in the EuropeanUnion. https://www.pellet.org/images/2015/ArnoldDaleEkman.pdf, 2015. Accesson 2017-06-11. → page 3[17] Environment Canada. National Inventory Report 1990-2013. Greenhouse gassources and sinks in Canada. Technical report, 2015. → pages 3, 40, 89[18] Madhumita Patel, Xiaolei Zhang, and Amit Kumar. Techno-economic and lifecycle assessment on lignocellulosic biomass thermochemical conversion technolo-gies: A review. Renewable and Sustainable Energy Reviews, 53:1486–1499, 2016.→ pages 3, 10[19] M Worley and J Yale. Biomass gasification technology assessment. http://www.nrel.gov/docs/fy13osti/57085.pdf, 2012. → pages 4, 11[20] Wan Nor Roslam Wan Isahak, Mohamed W.M. Hisham, Mohd Ambar Yarmo,and Taufiq-yap Yun Hin. A review on bio-oil production from biomass by usingpyrolysis method. Renewable and Sustainable Energy Reviews, 16(8):5910–5923,Oct 2012. → pages 4, 11[21] Dan Knorr, John Lukas, and Paul Schoen. Production of advanced biofuels vialiquefaction hydrothermal liquefaction reactor design. Technical Report Novem-ber, 2013. → pages 11, 14, 28[22] Vineet Singh Sikarwar, Ming Zhao, Peter Clough, Joseph Yao, Xia Zhong, Mo-hammad Zaki Memon, Nilay Shah, Edward Anthony, and Paul Fennell. Anoverview of advances in biomass gasification. Energy & Environmental Science,9(10):2939–2977, 2016. → pages 4, 1166[23] Saqib Sohail Toor, Lasse Rosendahl, and Andreas Rudolf. Hydrothermal liquefac-tion of biomass: A review of subcritical water technologies. Energy, 36(5):2328–2342, May 2011. → pages 4, 5, 11[24] Ajay Kumar, David D. Jones, and Milford A. Hanna. Thermochemical biomassgasification: A review of the current status of the technology. Energies, 2(3):556–581, 2009. → pages 4, 5, 11[25] Pengmei Lv, Zhenhong Yuan, Chuangzhi Wu, Longlong Ma, Yong Chen, andNoritatsu Tsubaki. Bio-syngas production from biomass catalytic gasification.Energy Conversion and Management, 48(4):1132–1139, 2007. → page 11[26] I.J. Tews, Y. Zhu, C.V. Drennan, D.C Elliott, L.J. Snowden-Swan, K. Onarheim,Y. Solantausta, and D Beckman. Biomass direct liquefaction options: technoe-conomic and life cycle assessment. Technical Report July, Richland, 2014. →pages 5, 9, 11, 12, 15, 19, 23, 25, 26, 27, 28, 29, 30, 38, 50, 51, 52, 101[27] Jani Lehto, Anja Oasmaa, Yrjo¨ Solantausta, Matti Kyto¨, and David Chiara-monti. Review of fuel oil quality and combustion of fast pyrolysis bio-oils fromlignocellulosic biomass. Applied Energy, 116(8):178–190, March 2014. → pages5, 11[28] F. Goudriaan and D.G.R. Peferoen. Liquid fuels from biomass via a hydrothermalprocess. Chemical Engineering Science, 45(8):2729–2734, 1990. → pages 5, 11[29] Mohammad I. Jahirul, Mohammad G. Rasul, Ashfaque Ahmed Chowdhury, andNanjappa Ashwath. Biofuels production through biomass pyrolysis - A techno-logical review. Energies, 5(12):4952–5001, 2012. → pages 5, 11[30] Claus Uhrenholt Jensen, Jessica Hoffmann, and Lasse A. Rosendahl. Co-processing potential of HTL bio-crude at petroleum refineries - Part 2: A para-metric hydrotreating study. Fuel, 165:536–543, Feb 2016. → pages 5, 11, 14[31] Karlsruhe Institute of Technology. Bioliq-Information and Press. https://www.bioliq.de/english/26.php, 2016. Access on 2017-03-21. → page 11[32] Steeper Energy. Steeper Energy — Commercialization. http://steeperenergy.com/projects/commercialization, 2017. Access on 2017-03-29. → page 11[33] Licella. Commercial Demonstration Plant — Licella – A bridge to a lower carbonfuture. http://www.licella.com.au/commercial-demonstration-plant/, 2016. Accesson 2017-03-29. → pages 5, 11[34] Total. BioTfuel: Developing Second-Generation Biofu-els. http://www.total.com/en/energy-expertise/projects/bioenergies/biotfuel-converting-plant-wastes-into-fuel, 2017. Access on 2017-03-29. →pages 5, 1167[35] BTG Bioliquids. Empyro project. https://www.btg-btl.com/en/company/projects/empyro, 2015. Access on 2017-03-20. → page 11[36] Ensyn. Ontario Facility-Ensyn’s first dedicated fuels facility. http://www.ensyn.com/ontario.html, 2015. Access on 2017-03-21. → pages 5, 11[37] BTG Bioliquids. Malaysia plant. https://www.btg-btl.com/en/company/projects/malaysia, 2017. Access on 2017-03-20. → page 11[38] Jessica Hoffmann, Claus Uhrenholt Jensen, and Lasse A. Rosendahl. Co-processing potential of HTL bio-crude at petroleum refineries - Part 1: Fractionaldistillation and characterization. Fuel, 165:526–535, Feb 2016. → page 5[39] Jon Hernandez. Canfor eyes Prince George for major biofuel facility. http://www.cbc.ca/news/canada/british-columbia/canfor-prince-george-biofuel-1.3660328,2016. Access on 2017-03-29. → page 5[40] Perry Toms and Steen Iversen. Alberta Biofuel Project Example.http://bio.albertainnovates.ca/media/69141/perry toms-alberta biofuel projectexample hydrofaction technology.pdf, 2014. Access on 2016-04-06. → page 5[41] Audi. Life Cycle Assessment. http://www.audi.com/content/dam/com/EN/corporate-responsibility/product/audi a6 life cycle assessment.pdf, 2011. Access on2018-04-24. → page 6[42] Levi Strauss & Co. The Life Cycle Of A Jean. http://levistrauss.com/wp-content/uploads/2015/03/Full-LCA-Results-Deck-FINAL.pdf, 2015. Access on 2018-04-24.→ page 6[43] The Coca-Cola Company. 2016 Sustainability Report. https://www.coca-colacompany.com/content/dam/journey/us/en/private/fileassets/pdf/2017/2016-sustainability-update/2016-Sustainability-Report-The-Coca-Cola-Company.pdf, 2016. Access on 2018-04-25. → page 6[44] Angela Fisher. Strategies for Life Cycle Thinking and Product Sustainabilityat GE. http://c.ymcdn.com/sites/www.naem.org/resource/resmgr/forum2016pres/f-2016-s13-generalelectric.pdf, 2016. Access on 2018-04-25. → page 6[45] The International Standards Organisation. Environmental management - Lifecycle assessment - Principles and framework. Technical report, 2006. → pages6, 32[46] Wikipedia. Life-Cycle Assessment. https://en.wikipedia.org/wiki/Life-cycleassessment, 2018. Access on 2018-04-26. → page 768[47] The International Standards Organisation. Environmental management - Lifecycle assessment - Goal and scope definition and inventory analysis. Technicalreport, 1998. → page 7[48] Gregor Wernet, Christian Bauer, Bernhard Steubing, Ju¨rgen Reinhard, EmiliaMoreno-Ruiz, and Bo Weidema. The ecoinvent database version 3 (part I):overview and methodology. The International Journal of Life Cycle Assessment,21(9):1218–1230, 2016. → pages 8, 34, 95[49] National Renewable Energy Laboratory. U.S. Life Cycle Inventory Database.https://www.nrel.gov/lci/, 2013. Access on 2018-04-26. → page 8[50] IPCC. Climate change 2007: the physical dcience basis. Contribution of work-ing group I to the fourth assessment report of the Intergovernmental Panel onClimate Change. Cambridge University Press, Cambridge, United Kingdom andNew York, NY, USA, 2007. → page 9[51] Hsin Min Wong. Life-cycle assessment of greenhouse gas emissions from alter-native jet fuels. Master thesis, Massachusetts Institute of Technology, 2008. →pages 9, 12[52] Jeongwoo Han, Amgad Elgowainy, Hao Cai, and Michael Q. Wang. Life-cycleanalysis of bio-based aviation fuels. Bioresource Technology, 150:447–456, 2013.→ pages 9, 12, 35[53] Harry Silla. Chemical Process Engineering Design and Economics. Taylor &Francis, New Yourk, 2003. → pages 10, 51, 52[54] R. Edwards, J-F Larive, V. Mahieu, and P. Rounveirolles. Well-to-wheels analysisof alternative fuels and powertrains in the European context Version 2c. TechnicalReport March, 2007. → page 12[55] Oscar P R van Vliet, Andre´ P C Faaij, and Wim C. Turkenburg. Fischer-Tropschdiesel production in a well-to-wheel perspective: A carbon, energy flow and costanalysis. Energy Conversion and Management, 50(4):855–876, 2009. → page 12[56] Russel W Stratton, Hsin Min Wong, and James I Hileman. Life cycle greenhousegas emissions from alternative jet fuels (PARTNER Project 28 report Version1.2). Technical report, Massachusetts Institute of Technology, 2010. → page 12[57] Ric Hoefnagels, Edward Smeets, and Andre´ Faaij. Greenhouse gas footprints ofdifferent biofuel production systems. Renewable and Sustainable Energy Reviews,14(7):1661–1694, Sep 2010. → page 12[58] Nathan Kauffman, Dermot Hayes, and Robert Brown. A life cycle assessmentof advanced biofuel production from a hectare of corn. Fuel, 90(11):3306–3314,Nov 2011. → page 1269[59] J. Han, A. Elgowainy, I. Palou-Rivera, J. B. Dunn, and M. Q. Wang. Well-to-wheels analysis of fast pyrolysis pathways with GREET. Technical report, 2011.→ page 12[60] David D. Hsu. Life cycle assessment of gasoline and diesel produced via fastpyrolysis and hydroprocessing. Biomass and Bioenergy, 45:41–47, Oct 2012. →page 12[61] Diego Iribarren, Jens F. Peters, and Javier Dufour. Life cycle assessment oftransportation fuels from biomass pyrolysis. Fuel, 97:812–821, July 2012. →page 12[62] Jeongwoo Han, Amgad Elgowainy, Jennifer B. Dunn, and Michael Q. Wang.Life cycle analysis of fuel production from fast pyrolysis of biomass. BioresourceTechnology, 133:421–428, 2013. → pages 12, 35[63] Qi Dang, Chunjiang Yu, and Zhongyang Luo. Environmental life cycle assessmentof bio-fuel production via fast pyrolysis of corn stover and hydroprocessing. Fuel,131:36–42, Sep 2014. → page 12[64] Sierk de Jong, Kay Antonissen, Ric Hoefnagels, Laura Lonza, Michael Wang,Andre´ Faaij, and Martin Junginger. Life-cycle analysis of greenhouse gas emis-sions from renewable jet fuel production. 10(1):64, 2017. → pages 12, 38[65] Ryan M. Swanson, Alexandru Platon, Justinus A. Satrio, and Robert C. Brown.Techno-economic analysis of biomass-to-liquids production based on gasification.Fuel, 89:S11–S19, Nov 2010. → pages 14, 15[66] Mark M. Wright, Daren E. Daugaard, Justinus A. Satrio, and Robert C. Brown.Techno-economic analysis of biomass fast pyrolysis to transportation fuels. Fuel,89:S2–S10, 2010. → pages 14, 15, 35[67] Yunhua Zhu, Mary J. Biddy, Susanne B. Jones, Douglas C. Elliott, and Andrew J.Schmidt. Techno-economic analysis of liquid fuel production from woody biomassvia hydrothermal liquefaction (HTL) and upgrading. Applied Energy, 129:384–394, sep 2014. → pages 14, 15, 27, 28, 29, 36[68] Jessica Hoffmann, Souman Rudra, Saqib S Toor, Jens Bo Holm-Nielsen, andLasse A Rosendahl. Conceptual design of an integrated hydrothermal liquefactionand biogas plant for sustainable bioenergy production. Bioresource technology,129:402–10, Feb 2013. → page 14[69] Jessica Hoffmann. Bio-oil production - process optimization and product quality.PhD thesis, Aalborg University, 2013. → page 1470[70] Douglas Elliott, Rich Hallen, and Andy Schmidt. DOE Bioenergy Tech-nologies Office (BETO) 2015 project peer review hydrothermal process-ing of biomass. http://energy.gov/sites/prod/files/2015/04/f22/thermochemicalconversion hallen 222301.pdf, 2015. Access on 2016-04-04. → pages 14, 23, 30[71] Poritosh Roy and Goretty Dias. Prospects for pyrolysis technologies in thebioenergy sector: A review. Renewable and Sustainable Energy Reviews,77(February):59–69, 2017. → page 14[72] Susanjib Sarkar, Amit Kumar, and Arifa Sultana. Biofuels and biochemicalsproduction from forest biomass in Western Canada. Energy, 36(10):6251–6262,Oct 2011. → page 15[73] Frederik Trippe, Magnus Fro¨hling, Frank Schultmann, Ralph Stahl, EdmundHenrich, and Ajay Dalai. Comprehensive techno-economic assessment of dimethylether (DME) synthesis and Fischer-Tropsch synthesis as alternative process stepswithin biomass-to-liquid production. Fuel Processing Technology, 106:577–586,2013. → page 15[74] Tristan R. Brown, Rajeeva Thilakaratne, Robert C. Brown, and Guiping Hu.Techno-economic analysis of biomass to transportation fuels and electricity viafast pyrolysis and hydroprocessing. Fuel, 106:463–469, April 2013. → page 15[75] Mohamed Magdeldin, Thomas Kohl, and Mika Ja¨rvinen. Techno-economic as-sessment of the by-products contribution from non-catalytic hydrothermal lique-faction of lignocellulose residues. Energy, July 2017. → page 15[76] Wikipedia. List of oil refineries. https://en.wikipedia.org/wiki/List of oil refineries,2017. Access on 2017-06-09. → page 18[77] A.J. Macdonald, Joanna Bernardo, and Stuart Spencer. Assessment of forestfeedstock (biomass) for Campbell River. Technical Report February, FPInnova-tions, British Columbia, 2012. → page 19[78] Government of British Columbia. Harvest billing system. https://a100.gov.bc.ca/pub/hbs/, 2016. Access on 2016-09-02. → page 19[79] A.J. Macdonald. Harvesting Systems and Equipment in British Columbia. BritishColumbia Ministry of Forests, 1999. → page 19[80] Leonard Johnson, Bruce Lippke, and Elaine Oneil. Modeling biomass collectionand woods processing life-cycle analysis. Forest Products Journal, 62(4):258, July2012. → pages 22, 24, 87[81] Ann Pa. Development of British Columbia wood pellet life cycle inventory andits utilization in the evaluation of domestic pellet applications. Master thesis,University of British Columbia, 2010. → page 2371[82] British Columbia Ferry Services Inc. Our fleet-queen of cowichan. http://www.bcferries.com/onboard-experiences/fleet/profile-queen of cowichan.html, 2016. Ac-cess on 2016-09-02. → page 24[83] British Columbia Ministry of Environment. 2014/2015 B.C. best practicesmethodology for quantifying greenhouse gas emissions. Technical report, Vic-toria, 2014. → pages 24, 87[84] Ellen Panisko, Thomas Wietsma, Teresa Lemmon, Karl Albrecht, and DanielHowe. Characterization of the aqueous fractions from hydrotreatment and hy-drothermal liquefaction of lignocellulosic feedstocks. Biomass and Bioenergy,74:162–171, 2015. → pages 27, 36[85] P˚al Bo¨rjesson and Maria Berglund. Environmental systems analysis of biogassystems-Part I: Fuel-cycle emissions. Biomass and Bioenergy, 30(5):469–485,2006. → pages 27, 28[86] Maria Berglund and P˚al Bo¨rjesson. Assessment of energy performance in thelife-cycle of biogas production. Biomass and Bioenergy, 30(3):254–266, 2006. →pages 27, 28[87] Robin Whitlock. ZWEDC develops the world’s largest anaerobic diges-tion facility in San Jose. https://www.renewableenergymagazine.com/biogas/zwedc-develops-the-worlda-s-largest-anaerobic-20131108, 2013. Access on 2017-12-17. → page 27[88] Douglas C. Elliott. Historical Developments in Hydroprocessing Bio-oils. Energy& Fuels, 21(3):1792–1815, May 2007. → page 29[89] Pamela L Spath and Margaret K Mann. Life cycle assessment of hydrogen pro-duction via natural gas steam reforming. Technical Report February, NREL,2001. → pages 29, 30[90] Agus Haryanto, Sandun D Fernando, S D Filip To, Philip H. Steele, and LesterPordesimo. High temperature water gas shift reaction over nickel catalysts forhydrogen production: effect of supports, GHSV, metal loading, and dopant ma-terials. Journal of Thermodynamics & Catalysis, 02(01):1–5, 2011. → page 30[91] John Reap, Felipe Roman, Scott Duncan, and Bert Bras. A survey of unresolvedproblems in life cycle assessment. Part 2: Impact assessment and interpretation.International Journal of Life Cycle Assessment, 13(5):374–388, 2008. → page 34[92] Argonne National Laboratory. The Greenhouse Gases, Regulated Emissions, andEnergy Use in Transportation (GREET) Model. https://greet.es.anl.gov/, 2015.Access on 2016-03-09. → pages 34, 9272[93] Michael Wang, Hong Huo, and Salil Arora. Methods of dealing with co-productsof biofuels in life-cycle analysis and consequent results within the U.S. context.Energy Policy, 39(10):5726–5736, 2011. → page 35[94] Kelli G. Roberts, Brent A. Gloy, Stephen Joseph, Norman R. Scott, and JohannesLehmann. Life cycle assessment of biochar systems: Estimating the energetic,economic, and climate change potential. Environmental Science and Technology,44(2):827–833, 2010. → pages 35, 94[95] Jinyang Wang, Zhengqin Xiong, and Yakov Kuzyakov. Biochar stability in soil:Meta-analysis of decomposition and priming effects. GCB Bioenergy, 8(3):512–523, 2016. → pages 35, 40[96] EPA. Regulation of Fuels and Fuel Additives: RFS Pathways II and TechnicalAmendments to the RFS 2 Standards. https://www.regulations.gov/document?D=EPA-HQ-OAR-2012-0401-0001, 2013. Access on 2017-04-06. → pages 35, 58[97] Yakov Kuzyakov, Irina Bogomolova, and Bruno Glaser. Biochar stability in soil:Decomposition during eight years and transformation as assessed by compound-specific 14C analysis. Soil Biology and Biochemistry, 70:229–236, 2014. → page40[98] Shaghaygh Akhtari. Economic assessment and optimization of forest biomasssupply chain for heat generation in a district heating system. Master thesis,University of British Columbia, 2012. → pages 45, 47[99] Costowl.com. How Much Does it Cost to Rent or Lease a Dump Truck? http://www.costowl.com/automotive/auto-dump-truck-rent-cost.html, 2016. Access on2017-04-14. → page 49[100] Shuva Gautam, Reino Pulkki, Chander Shahi, and Mathew Leitch. Economicand energy efficiency of salvaging biomass from wildfire burnt areas for bioenergyproduction in northwestern Ontario: A case study. Biomass and Bioenergy,34:1562–1572, 2010. → page 49[101] British Columbia Ferry Services Inc. BC Ferries Fare index. http://www.bcferries.com/files/fares/pdf format/BCF Fares.pdf, 2017. Access on 2017-09-22. → page49[102] Mozammel Hoque, Shahab Sokhansanj, Tony Bi, Sudhagar Mani, Ladan Jafari,Jim Lim, Parisa Zaini, Staffan Melin, Taraneh Sowlati, and M Afzal. Economicsof Pellet Production for Export Market. In CSBE/SCGAB 2006 Annual Con-ference, pages 1–15, Edmonton, Alberta, 2006. → pages 50, 51, 106[103] Don W. Green and Robert H. Perry. Perry’s Chemical Engineers’ Handbook.McGraw-Hill, 8th edition, 2007. → pages 50, 51, 52, 10673[104] M S Peters and K D Timmerhaus. Plant Design and Economics for ChemicalEngineers. McGraw-Hill, New York, 4th edition, 1991. → page 51[105] Process design and economics for conversion of lignocellulosic biomass to ethanolthermochemical pathway by indirect gasification and mixed alcohol synthesis.Technical Report May, 2011. → pages 51, 101[106] EPA. EPA Air Pollution Control Cost Manual. EPA, 6th edition, Feb 2002. →page 51[107] Doug Smock. Pressure Builds on Soda Ash Prices. http://www.mypurchasingcenter.com/commodities/commodities-articles/pressure-builds-soda-ash-prices/, 2014. Access on 2017-04-05. → page 52[108] Yihua Li. Production cost and supply chain design for advanced biofuels. Masterthesis, Iowa State University, 2013. → page 52[109] Ontario Chamber Commerce. 2015 Indicative Industrial ElectricityPrices. http://www.occ.ca/wp-content/uploads/2013/05/Industrial-Pricing-Table.pdf, 2015. Access on 2017-04-05. → page 52[110] Natural Resources Canada. Average Retail Prices for Diesel. http://www2.nrcan.gc.ca/eneene/sources/pripri/prices bycity e.cfm?PriceYear=0&ProductID=5&LocationID=66,8,39,17, 2017. Access on 2017-04-05. → page 52[111] InfoMine. 5 Year Natural Gas Prices and Natural Gas Price Charts. http://www.infomine.com/investment/metal-prices/natural-gas/5-year/, 2017. Access on2017-04-05. → page 52[112] Natural Resources Canada. Average Retail Prices for Auto Propane.http://www2.nrcan.gc.ca/eneene/sources/pripri/prices bycity e.cfm?PriceYear=0&ProductID=6&LocationID=66,8,39,17#PriceGraph, 2017. Access on 2017-04-05. → page 52[113] Sarah Ashton, Lauren McDonell, Kiley Barnes, and Matthew Langholtz. Do-It-Yourself Supply Curve: Tools to Help You Get Involved in an EntrepreneurialWoody Biomass Project. In Eleanor K. Sommer, editor, Woody Biomass DeskGuide and Toolkit, chapter 6, pages 55–76. National Association of ConservationDistricts, 2008. → page 52[114] Statistics Canada. Labour force survey estimates (LFS), wages of employees bytype of work, National Occupational Classification (NOC), sex, and age group,unadjusted for seasonality. http://www5.statcan.gc.ca/cansim/a26?lang=eng&retrLang=eng&id=2820151&&pattern=&stByVal=1&p1=1&p2=37&tabMode=dataTable&csid=, 2016. Access on 2017-04-05. → page 5274[115] Nataliya Kulyk. Cost-benefit analysis of the biochar application in the U.S. cerealcrop cultivation. PhD thesis, University of Massachusetts - Amherst, 2012. →page 52[116] Natural Resources Canada. Monthly Average Wholesale Prices for RegularGasoline in 2016-Vancouver. http://www2.nrcan.gc.ca/eneene/sources/pripri/wholesale bycity e.cfm?priceYear=2016&productID=9&locationID=2&frequency=M#priceGraph, 2017. Access on 2017-04-07. → pages 55, 58[117] British Columbia Ministry of Environment. British Columbia’s Climate ActionPlan. Technical report, 2008. → page 57[118] Lien Yeung and Jason Proctor. B.C. Premier Christy Clark’s climate change plandoes not raise carbon tax. http://www.cbc.ca/news/canada/british-columbia/b-c-premier-christy-clark-s-climate-change-plan-does-not-raise-carbon-tax-1.3728317, 2016. Access on 2017-04-07. → page 57[119] Jennifer B Dunn, Amgad Elgowainy, Anant Vyas, Pu Lu, Jeongwoo Han, MichaelWang, Amy Alexander, Rick Baker, Richard Billings, Scott Fincher, Jason Huck-aby, and Susan McClutchey. Update to transportation parameters in GREET.Technical report, Systems Assessment Group, Energy Systems Division, ArgonneNational Laboratory, 2013. → page 9375AppendicesA Mass and Energy BalancesAppendix A contains the following content:1. Stream flow diagrams of biomass to biofuel conversion processes2. Detail mass and energy balance data of each operation unitA.1 Stream Flow DiagramsThe stream flow diagrams of biomass to biofuel conversion processes for the threestudied scenarios are presented in Figure A.1, A.2 and A.3 below.Figure A.1: The stream flow diagram of Fr-CIR scenario76Figure A.2: The stream flow diagram of Bo-DBR scenarioFigure A.3: The stream flow diagram of Wp-CIR scenarioA.2 Tabulated Mass and Energy Balances DataThe detail mass and energy balance data of each operation unit are tabulated as below.77Table A.1: Mass balance of pre-processing for each scenarioMass balance (kg/s)Input Fr-CIR Bo-DBR Wp-CIRForest residuesa/Wood pelletb 20.41 20.41 11.01Recycled water 109.93 109.93 118.88Total 130.34 130.34 129.89OutputBiomass slurry 130.34 130.34 129.89Total 130.34 130.34 129.89a for Fr-CIR and Bo-DBR scenarios; b for Wp-CIR scenario;Table A.2: Energy balance of pre-processing for each scenarioEnergy balance (MW)Input Fr-CIR Bo-DBR Wp-CIRForest residuesa/Wood pelletb 191.98 191.98 192.08Power 2.86 2.86 2.85Recycled water 36.88 36.88 39.88Total 231.72 231.72 234.81OutputBiomass slurry 231.72 231.72 234.81Total 231.72 231.72 234.81a for Fr-CIR and Bo-DBR scenarios; b for Wp-CIR scenario78Table A.3: Mass balance of HTL for each scenarioMass balance (kg/s)Input Fr-CIR Bo-DBR Wp-CIRBiomass slurry 130.34 130.34 129.89Biogas from AD 3.33 3.33 3.32Combustion air 17.07 17.07 17.02Total 150.75 150.75 150.23RecycledOff-gases 0.2 0.2 0.2OutputBio-oil 3.83 3.83 3.83Recycled water 109.93 109.93 118.88PHWW 14.20 14.20 4.80Biochar 0.58 0.58 0.58Off-gas 1.80 1.60 1.59Flue gas 20.41 20.61 20.854Total 150.75 150.75 150.2379Table A.4: Energy balance of HTL for each scenarioEnergy balance (MW)Input Fr-CIR Bo-DBR Wp-CIRBiomass slurry 231.72 231.72 234.81Biogas from AD 49.20 49.20 49.20Power 4.03 4.03 4.10Total 284.96 284.96 287.94RecycledOff-gases 1.21 1.21 1.21OutputBio-oil 148.52 148.52 148.52Recycled water 36.88 36.88 39.88PHWW 61.15 61.15 62.84Biochar 11.68 11.68 11.64Off-gas 9.50 9.50 9.47Heat loss 17.23 17.23 15.58Total 284.96 284.96 287.9480Table A.5: Mass balance of AD for each scenarioMass balance (kg/s)Input Fr-CIR Bo-DBR Wp-CIRPHWW 14.20 14.20 4.80NG 0.08 0.00 0.08Combustion air 1.37 0.00 1.38Total 15.65 14.20 6.26OutputBiogas 3.33 3.33 3.32Solid digestate 0.18 0.17 0.18Liquid digestate 10.78 10.79 1.30Flue gas 1.45 0.00 1.46Total 15.65 14.20 6.2681Table A.6: Energy balance of AD for each scenarioEnergy balance (MW)Input Fr-CIR Bo-DBR Wp-CIROff-gas from HTL 3.48 9.50 3.45PHWW 61.15 61.15 62.84NG 4.22 0.00 4.32Power 5.03 5.03 5.02Total 70.40 75.69 67.86OutputBiogas 49.20 49.20 49.03Heat loss 12.03 17.31 17.72Liquid digestate 9.17 9.17 1.11Total 70.40 75.69 67.86Table A.7: Mass balance of hydrotreating for each scenarioMass balance (kg/s)Input Fr-CIR Bo-DBR Wp-CIRBio-oil 3.83 3.83 3.83Hydrogen 0.13 0.13 0.13Total 3.96 3.96 3.96OutputBiofuels 2.62 2.62 2.62Waste water 1.06 1.06 1.06Off-gas 0.28 0.28 0.28Total 3.96 3.96 3.9682Table A.8: Energy balance of hydrotreating for each scenarioEnergy balance (MW)Input Fr-CIR Bo-DBR Wp-CIRBio-oil 148.52 148.52 148.52Hydrogen 18.49 18.49 18.49Power 1.12 1.12 1.12Total 167.01 167.01 167.01OutputBiofuels 120.22 120.22 120.22Waste water 30.69 30.69 30.88Off-gas 16.11 16.11 16.11Total 167.01 167.01 167.0183Table A.9: Mass balance of hydrogen production for each scenarioMass balance (kg/s)Input Fr-CIR Bo-DBR Wp-CIRNG(feed) 0.00 0.12 0.00Off-gas (feed) 0.92 0.24 0.92Off-gas (fuel) 0.37 0.04 0.37Combustion air 3.01 3.03 3.01Steam required 1.26 1.26 1.26Total 5.56 4.69 5.56RecycledOff-gases 0.91 0.91 0.91OutputSteam produced 1.81 1.81 1.81Flue gas 3.15 2.27 3.15Hydrogen 0.13 0.13 0.13Blowdown 0.48 0.48 0.48Total 5.56 4.69 5.5684Table A.10: Energy balance of hydrogen production for each scenarioEnergy balance (MW)Input Fr-CIR Bo-DBR Wp-CIRNG(feed) 0.00 6.02 0.00Off-gas (feed) 19.94 13.92 19.94Off-gas (fuel) 2.19 2.19 2.19Power 0.15 0.15 0.15Steam required 3.53 3.53 3.53Total 25.81 25.81 25.81RecycledOff-gases 5.81 5.81 5.81OutputSteam produced 5.06 5.06 5.06Hydrogen 18.49 18.49 18.49Heat loss 2.26 2.26 2.26Total 25.81 25.81 25.81B Process Emission FactorsAppendix B summarizes all processes emission factors used in building the life cycleinventory of HTL biofuels. The emissions factors cover all life cycle stages, includingbiomass collection and transportation, pre-processing, conversion, biofuels distributionand end use. Besides, a section is added to describe the emission factors associatedwith by-product biochar application. Emission factors are classified into two types:upstream and downstream. The upstream emission factors account for emissions as-sociated with the upstream supply chain of materials and energy, i.e., production anddelivery, while the downstream emission factors are related to the emissions from thematerials and energy utilization.85B.1 Biomass Collection and TransportationThe emissions from biomass collection and transportation stages are mainly contributedby the operation of diesel-powered and marine diesel-powered equipment. The up-stream is associated with diesel production and delivery, and the downstream is relatedto diesel combustion in the equipment engine. The upstream and downstream emissionfactors are presented in Table B.1, Table B.2 and Table B.3.Table B.1: Diesel and marine diesel production and delivery emission factorsPollutant Diesela Marine dieselbkg/MJ diesel kg/MJ marine dieselCO2 2.05E-02 2.05E-02NMOCs 4.10E-06 4.10E-06CH4 1.31E-04 1.31E-04CO 1.36E-05 1.36E-05N2O 6.00E-07 6.00E-07NO2 5.17E-05 5.17E-05SOx 4.46E-05 4.46E-05PM 3.06E-06 3.06E-06a from [2], “Upstream Results HHV — Hwy diesel, crude oil” model; b from[2], “Upstream Results HHV — Marine/Rail diesel, crude oil” model86Table B.2: Biomass collection equipment operation emission factorsPollutant Chipper and loader onforest standsaDump truckb Loader at FDPsckg/dry tonne biomass kg/Tkm kg/MJ dieselCO2 1.17E+01 4.35E-01 6.82E-02NMOCs 7.10E-03 4.50E-05 2.15E-05CH4 1.15E-02 2.70E-05 1.10E-06CO 1.02E-01 7.50E-05 9.60E-05N2O 0.00E+00 1.90E-05 2.86E-05NO2 2.13E-01 1.64E-04 1.41E-04SOx 1.18E-02 1.50E-05 6.54E-07PM 1.12E-03 8.00E-06 0.00E+00a from [80]; b from [2], “Freight Emissions — Medium Duty Truck” model; c from [2], “EquipEmis Factors — Wheeled loader, diesel powered” modelTable B.3: Transportation emission factorsPollutant Semi-trailera Liquid tanker trucka Ferrybkg/Tkm kg/Tkm kg/tonne dieselCO2 1.38E-01 1.38E-01 3.49E+03NMOCs 1.43E-05 1.43E-05 2.64E+00CH4 8.45E-06 8.45E-06 1.87E-01CO 2.38E-05 2.38E-05 8.14E+00N2O 5.94E-06 5.94E-06 1.28E+00NO2 5.19E-05 5.19E-05 6.67E+01SOx 4.62E-06 4.62E-06 2.20E+01PM 2.54E-06 2.54E-06 1.32E+00a from [2], “Freight Emissions — Heavy Duty Truck” model; b from [83], the total emissionfactors of ferry are the sum of underway, maneuvering and dockside emission factors87B.2 Pre-processingThe emissions from biomass pre-processing stage are contributed by the operation ofequipment in biorefinery, including diesel-powered front-end loader, electricity-poweredgrinder and auxiliary equipment, as well as the operation of wood pellet plant in Wp-CIR scenario. The upstream is associated with diesel and electricity production anddelivery, and the downstream is related to diesel combustion in equipment engines.It should be noted that the emission factors of wood pellet plant operation are pre-sented in a life cycle basis, which cover both the upstream and downstream emissions.Besides, the emission factors of electricity generation in Alberta is summarized blow,which is used in the sensitivity analysis. The upstream emission factors of diesel arethe same as those presented in Subsection B.1 (see Table B.1) and the downstreamemission factors of diesel combustion in front-end loader in biorefinery are same as theemission factors of loader operation at feedstock delivery points (see Table B.2). Theemission factors of wood pellet plant operation and electricity generation are presentedin Table B.4 to Table B.8.Table B.4: Wood pellet plant operation Emission factors [1]Pollutant kg/tonne of wood pelletCO2 8.33E+00NMOCs 1.32E-02CH4 6.05E-02CO 2.95E-01N2O 6.40E-03NO2 1.58E-01SOx 1.89E-02PM 2.07E-0188Table B.5: British Columbia (BC) electricity mix profile and electricity generation and distribution efficiencyNatural gas (Boiler) Natural gas (Turbine) Fuel oil Biomass Hydro WindContribution to BC electricitya (%) 1.43 1.43 1.52 4.91 90.44 0.28Fuel to electricity efficiencyb (%) 42.34 42.34 44.66 20.00 100.00 100.00Electricity distribution efficiencyc (%) 92.00 92.00 92.00 92.00 92.00 92.00a from [17], the average value of 2010-2012, and assume electricity generated by natural gas (boiler) and natural gas (turbine)share 50% of total natural gas generation, respectively; b [17]; c from [2], “Elec Emissions”Table B.6: Alberta electricity mix profile and electricity generation and distribution efficiencyNatural gas (Boiler) Natural gas (Turbine) Fuel oil Coal Hydro WindContribution to BC electricitya (%) 9.78 9.78 0.93 72.40 3.53 3.58Fuel to electricity efficiencyb (%) 33.17 33.17 26.10 29.65 100.00 100.00Electricity distribution efficiencyc (%) 92.00 92.00 92.00 92.00 92.00 92.00a from [17], the average value of 2010-2012, and assume electricity generated by natural gas (boiler) and natural gas (turbine)share 50% of total natural gas generation, respectively; b [17]; c from [2], “Elec Emissions”89Table B.7: British Columbia (BC) electricity generation emission factors [2]Natural gas(Boiler) Natural gas(Turbine) Fuel oil BiomassUp-streamDown-streamTotal Up-streamDown-streamTotal Up-streamDown-streamTotal Up-streamDown-streamTotalPollutant kg/MJ electricity distributedCO2 1.59E-2 1.33E-1 1.49E-1 1.59E-2 1.21E-1 1.37E-1 3.42E-2 1.91E-1 2.26E-1 - - -NMOCs 6.40E-6 3.90E-6 1.03E-5 6.40E-6 6.30E-7 7.03E-6 8.35E-6 2.94E-6 1.13E-5 - 1.93E-5 1.93E-5CH4 1.71E-4 2.57E-6 1.73E-4 1.71E-4 8.93E-6 1.80E-4 2.95E-4 2.17E-6 2.97E-4 - 3.47E-5 3.47E-5CO 1.34E-5 9.40E-5 1.07E-4 1.34E-5 8.51E-5 9.85E-5 2.01E-5 3.87E-5 5.88E-5 - 9.92E-4 9.92E-4N2O 3.66E-7 9.32E-8 4.59E-7 3.66E-7 3.11E-6 3.48E-6 6.48E-7 3.55E-8 6.83E-7 - 1.54E-5 1.54E-5NO2 9.80E-5 1.72E-4 2.70E-4 9.80E-5 1.82E-4 2.80E-4 9.97E-5 1.91E-4 2.91E-4 - 3.64E-4 3.64E-4SOx 1.26E-5 1.40E-6 1.40E-5 1.26E-5 1.28E-6 1.38E-5 6.76E-5 2.07E-4 2.75E-4 - 3.46E-4 3.46E-4PM 6.63E-7 8.51E-6 9.17E-6 6.63E-7 6.85E-6 7.52E-6 3.38E-6 3.48E-5 3.81E-5 - 1.32E-4 1.32E-4Hydro WindBC mixPollutant Up-streamDown-streamTotal Up-streamDown-streamTotalCO2 3.26E-3 4.53E-3 7.79E-3 - - 3.32E-3 1.46E-2NMOCs - - - - - - 1.37E-6CH4 - 2.72E-4 2.72E-4 - - - 2.57E-4CO - - - - - - 5.25E-5N2O - - - - - - 8.21E-7NO2 - - - - - - 3.01E-5SOx - - - - - - 2.15E-5PM - - - - - - 7.31E-690Table B.8: Alberta electricity generation emission factors [2]Natural gas(Boiler) Natural gas(Turbine) Fuel oil CoalUp-streamDown-streamTotal Up-streamDown-streamTotal Up-streamDown-streamTotal Up-streamDown-streamTotalPollutant kg/MJ electricity distributedCO2 2.03E-2 1.33E-1 1.53E-1 2.03E-2 1.21E-1 1.41E-1 5.86E-2 1.91E-1 2.50E-1 1.55E-2 2.82E-1 2.97E-1NMOCs 8.17E-6 3.90E-6 1.21E-5 8.17E-6 6.30E-7 8.80E-6 1.43E-5 2.94E-6 1.72E-5 1.09E-6 2.69E-6 3.78E-6CH4 2.18E-4 2.57E-6 2.21E-4 2.18E-4 8.93E-6 2.27E-4 5.05E-4 2.17E-6 5.07E-4 1.02E-4 2.76E-6 1.05E-4CO 1.71E-5 9.40E-5 1.11E-4 1.71E-5 8.51E-5 1.02E-4 3.44E-5 3.87E-5 7.31E-5 8.01E-6 3.45E-5 4.25E-5N2O 4.67E-7 9.32E-8 5.60E-7 4.67E-7 3.11E-6 3.58E-6 1.11E-6 3.55E-8 1.14E-6 5.56E-7 1.18E-7 6.74E-7NO2 1.25E-4 1.72E-4 2.97E-4 1.25E-4 1.82E-4 3.07E-4 1.71E-4 1.91E-4 3.62E-4 4.82E-6 8.21E-4 8.26E-4SOx 1.60E-5 1.40E-6 1.74E-5 1.60E-5 1.28E-6 1.73E-5 1.16E-4 2.07E-4 3.23E-4 2.41E-6 4.21E-4 4.23E-4PM 8.47E-7 8.51E-6 9.35E-6 8.47E-7 6.85E-6 7.70E-6 5.78E-6 3.48E-5 4.05E-5 1.30E-6 5.83E-5 5.96E-5Hydro WindBC mixPollutant Up-streamDown-streamTotal Up-streamDown-streamTotalCO2 3.26E-3 4.53E-3 7.79E-3 - - 3.32E-3 2.47E-1NMOCs - - - - - - 4.94E-6CH4 - 2.72E-4 2.72E-4 - - - 1.34E-4CO - - - - - - 5.23E-5N2O - - - - - - 9.04E-7NO2 - - - - - - 6.60E-4SOx - - - - - - 3.13E-4PM - - - - - - 4.52E-591B.3 ConversionThe emissions from conversion stage are contributed by the following processes:Upstream processes The production and delivery of materials, including HTLbuffer agent Na2CO3, natural gas (NG) as heating fuel for anaerobic digestion (AD),hydrotreating catalyst NiMo/Al2O3, hydrogen production catalyst NiMo/Al2O3. Ad-ditionally, for Bo-DBR scenario, NG is required as feedstock for hydrogen production.Upstream emission factors are summarized in Table B.9. The production and deliveryof energy, i.e., electricity. See Table B.7 for BC electricity mix emission factors.Table B.9: Materials production and delivery emission factors of conversion stagePollutant AD heatinga HTL heatingb Hydrogen productionc Hydrogen productiond(HTL) (AD) (Hydrotreating) (Hydrogen production)kg/kg Na2CO3 kg/MJ NG kg/kg NiMo/Al2O3 kg/kg NiMo/Al2O3CO2 6.94E-01 6.55E-03 9.37E-01 3.35E+00NMOCs 9.63E-05 3.27E-06 6.53E-05 3.90E-04CH4 7.59E-04 1.49E-04 7.85E-04 7.81E-03CO 5.40E-04 6.57E-06 3.28E-04 1.42E-03N2O 1.17E-06 2.15E-07 5.82E-06 5.29E-05NO2 4.23E-04 3.92E-05 3.65E-04 2.37E-03SOx 4.50E-04 5.37E-06 1.69E-04 3.42E-03PM 1.72E-04 4.36E-07 6.72E-05 3.30E-04a from [92], “Soda ash production for use in US” model, with US electricity mix changed to BCelectricity mix; b from [2], “Upstream Results HHV — CNG, NG” model, also applied for NG asfeedstock in Bo-DBR scenario; c from [92], “Mo/Ni spent catalyst-biobased” model, with US electricitymix changed to BC electricity mix; d from [92], ”Mo/Ni spent catalyst-petrochemical” model, withUS electricity mix changed to BC electricity mixDownstream processes The combustion of NG for heating AD, the combus-tion of biogas for heating HTL, hydrogen production via steam reforming using NG asfeedstock (Bo-DBR scenario), hydrogen production via steam reforming using off-gasesfrom HTL and hydrotreating as feedstock (Fr-CIR and Wp-CIR scenarios). Down-stream emission factors are summarized in Table B.10.92Table B.10: Downstream emission factors of conversion stagePollutant AD heatinga HTL heatingb Hydrogen productionc Hydrogen productiond(NG as fuel) (biogas as fuel) (NG as feedstock) (off-gases as feedstock)kg/MJ NG kg/MJ biogas kg/MJ NG kg/MJ off-gasesCO2 5.02E-02 0.00E+00 5.02E-02 0.00E+00NMOCs 3.69E-06 3.69E-06 9.72E-06 9.72E-06CH4 9.74E-07 9.74E-07 3.79E-07 3.79E-07CO 3.56E-05 3.56E-05 7.58E-06 7.58E-06N2O 4.91E-07 4.91E-07 2.37E-07 2.37E-07NO2 6.19E-05 6.19E-05 1.90E-05 1.90E-05SOx 2.67E-07 2.67E-07 9.48E-08 9.48E-08PM 3.22E-06 3.22E-06 2.84E-06 2.84E-06a from [2], “Equip Emis Factors — Industrial boiler — NG” model; b from [2], “Equip Emis Factors— Industrial boiler — NG” model; CO2 emission is modified to be 0 since the carbon in biogas isbiogenic; c from [2], “Equip Emis Factors — Hydrogen Production Plants — NG” model; d from [2],“Equip Emis Factors — Hydrogen Production Plants — NG” model; CO2 emission is modified to be0 since the carbon in off-gases is biogenicB.4 Biofuels Distribution and End UseThe emissions from biofuel distribution stage are contributed by the operation ofdiesel-powered liquid tanker truck (distribution of gasoline, diesel and heavy oil) andelectricity-powered pipeline (distribution of jet fuel). The upstream is associated withdiesel and electricity production and delivery, and the downstream is related to dieselcombustion in the truck engine. The upstream and downstream emission factors ofdiesel are the same as those presented in Subsection B.1 (see Table B.1 and Table B.3,respectively). The pipeline transportation consumes electricity from BC grid and theenergy consumption for transporting 1 tonne of biofuel via pipeline for 1 km is 404 Btu[119], which is equivalent to 0.292 MJ/Tkm. The BC electricity mix emission factorsare presented in Table B.7. The emissions from biofuels end use stage are associatedwith biofuels combustion in the vehicle and airplane engines, which are summarized inTable B.11 as follow:93Table B.11: Biofuels combustion in vehicle and jet engines emission factorsPollutant Gasolinea Jet fuelb Dieselc Heavy oildkg/MJ kg/MJ kg/MJ kg/MJCO2 2.87E-04 0.00E+00 7.31E-04 0.00E+00NMOCs 4.07E-05 1.08E-06 5.78E-06 2.94E-05CH4 3.28E-06 1.68E-06 3.79E-06 7.15E-07CO 1.64E-03 7.00E-06 7.71E-06 1.91E-04N2O 1.32E-06 1.90E-06 2.96E-06 1.99E-06NO2 3.56E-05 2.50E-04 2.45E-05 1.79E-03SOx 1.20E-06 0.00E+00 2.07E-06 6.76E-07PM 2.32E-06 2.50E-06 9.60E-07 3.58E-05a from [2], “LDV Summ — Biomass Fuels, Gasoline, Wood Res” model. The emission factors arepresented in unit of g/km originally, and they are converted to kg/MJ base by assuming that theenergy intensity of light duty vehicle (LDV) is 2.21 MJ/(person*km) and average 3 persons aretransported; b from [2], “Freight Emissions — Airplanes, BTL, Wood Res” model. The emissionfactors are presented in unit of g/Tkm originally, and they are converted to kg/MJ base by assumingthat the energy intensity of airplane is 15 MJ/Tkm; c from [2], “HDV Summ — Biomass Fuels, FTDiesel, Wood Res” model. The emission factors are presented in unit of g/km originally, and theyare converted to kg/MJ base by assuming that the fuel efficiency of heavy duty vehicle (HDV) is40 L/100km and higher heating value of diesel is 38.65 MJ/L; d from [2], “Freight Emissions —Marine Liquids and Bulk Freight, Fuel oil (0.002% S), Crude oil” model. The emission factors arepresented in unit of g/Tkm originally, and they are converted to kg/MJ base by assuming that theenergy intensity of marine vessel is 60 KJ/Tkm. Besides, the CO2 emission in the original modelis modified to be 0 as the carbon in biofuels are biogenicB.5 Biochar ApplicationBiochar produced from HTL of forest residues as a by-product is assumed to be shippedout to a hypothetic farm for soil amendment. The emissions associated with the biocharapplication are transportation emissions, which use the same upstream and downstreamemission factors as those described in Subsection B.1 (see Table B.1 and Table B.3).Meanwhile, the application of biochar can create greenhouse gas emissions reductioncredit. According to the assumption made by Roberts et al. [94], 80% of the carbon inbiochar can be viewed as stable sequestered carbon. Besides, N in biochar was assumedto displace the same amount of nitrogen fertilizer, so the upstream emissions of nitrogenfertilizer can be avoided. Table B.12 tabulates the emission factors associated with theproduction and delivery of nitrogen fertilizer.94Table B.12: Nitrogen fertilizer production and delivery emission factorsPollutant kg/tonne of wood pelletCO2 4.47E+00NMOCs 1.55E-03CH4 7.80E-03CO 7.39E-03N2O 2.01E-02NO2 1.94E-02SOx 1.89E-02PM 3.90E-03from [48], “Nitrogen fertilizer, as N {GLO}—market for—Alloc Def, S” modelC Detail Stage-wise Emission ResultsAppendix C tabulates the detail emission results associated with each life cycle stageof three studied scenarios.C.1 Biomass CollectionTable C.1: Emission inventory of biomass collection for each scenario (kg/yr)Biomass CollectionPollutant Fr-CIR Bo-DBR Wp-CIRCO2 9.62E+06 9.62E+06 1.08E+07NMOCs 3.14E+03 3.14E+03 3.51E+03CH4 1.71E+04 1.71E+04 1.92E+04CO 3.37E+04 3.37E+04 3.78E+04N2O 5.40E+02 5.40E+02 6.04E+02NO2 7.21E+04 7.21E+04 8.08E+04SOx 8.23E+03 8.23E+03 9.21E+03PM 7.08E+02 7.08E+02 7.93E+02CO2-eq 1.02E+07 1.02E+07 1.14E+0795C.2 TransportationTable C.2: Emission inventory of feedstock transportation for each scenario (kg/yr)Feedstock TransportationPollutant Fr-CIR Bo-DBR Wp-CIRCO2 1.84E+07 3.19E+06 1.02E+07NMOCs 5.44E+03 8.39E+02 3.13E+03CH4 2.72E+04 4.84E+03 1.50E+04CO 1.56E+04 2.36E+03 8.99E+03N2O 2.28E+03 3.43E+02 1.32E+03NO2 1.06E+05 1.53E+04 6.17E+04SOx 3.95E+04 5.87E+03 2.29E+04PM 2.60E+03 3.95E+02 1.50E+03CO2-eq 1.98E+07 3.42E+06 1.10E+0796C.3 Pre-processingTable C.3: Emission inventory of pre-processing for each scenario (kg/yr)Pre-processingPollutant Fr-CIR Bo-DBR Wp-CIRCO2 1.63E+06 1.63E+06 4.27E+06NMOCs 2.38E+02 2.38E+02 4.42E+03CH4 2.19E+04 2.19E+04 4.10E+04CO 4.86E+03 4.86E+03 9.84E+04N2O 2.10E+02 2.10E+02 2.24E+03NO2 3.42E+03 3.42E+03 5.35E+04SOx 1.99E+03 1.99E+03 7.98E+03PM 6.17E+02 6.17E+02 6.62E+04CO2-eq 2.24E+06 2.24E+06 5.96E+0697C.4 ConversionTable C.4: Emission inventory of conversion for each scenario (kg/yr)ConversionPollutant Fr-CIR Bo-DBR Wp-CIRCO2 3.73E+07 4.03E+07 3.73E+07NMOCs 3.08E+04 3.33E+04 3.08E+04CH4 1.29E+05 1.37E+05 1.29E+05CO 2.37E+05 2.55E+05 2.36E+05N2O 3.16E+03 3.42E+03 3.15E+03NO2 3.82E+05 4.15E+05 3.80E+05SOx 2.55E+04 2.59E+04 2.54E+04PM 2.82E+04 2.99E+04 2.81E+04CO2-eq 4.15E+07 4.47E+07 4.14E+0798C.5 DistributionTable C.5: Emission inventory of distribution (kg/yr)Pollutant DistributionCO2 1.18E+05NMOCs 1.10E+03CH4 2.35E+02CO 4.53E+01N2O 4.77E+00NO2 1.06E+02SOx 6.49E+01PM 7.28E+00CO2-eq 1.25E+0599C.6 End UseTable C.6: Emission inventory of end use(kg/yr)Pollutant End UseCO2 1.20E+06NMOCs 6.23E+04CH4 9.80E+03CO 1.48E+06N2O 8.20E+03NO2 1.54E+06SOx 4.19E+03PM 3.04E+04CO2-eq 3.89E+06D Detail Stage-wise Cost ResultsThe results summarized in the tables below are the detailed cost associated with eachstage of HTL biofuels production, including forest residues collection, feedstock trans-portation and biomass to biofuels conversion. The costs of first two stages are coveredin the feedstock delivered cost, while the costs of biomass to biofuels conversion consistof the capital investment and operating cost of biorefinery, oil refinery and wood pelletplant. It should be noted that the capital investment of oil refinery is not consideredin this study since we assume that bio-oil is co-upgraded with crude oil in an existingoil refinery.100D.1 Feedstock Delivered CostTable D.1: Summary of feedstock delivery cost breakdown for different scenarios ($/yr)ScenarioFeedstockdelivered costName of FDPsTotalChilliwack Squamish Powell River Port AlberniFr-CIR Raw material 2.29E+05 9.41E+04 3.64E+05 2.14E+05 9.01E+05Machinery 2.75E+06 1.13E+06 4.37E+06 2.57E+06 1.08E+07Transportation 4.78E+06 1.75E+06 1.58E+07 8.73E+06 3.10E+07Bo-DBR Raw material 2.29E+05 9.41E+04 3.64E+05 2.14E+05 9.01E+05Machinery 2.75E+06 1.13E+06 4.37E+06 2.57E+06 1.08E+07Transportation 2.25E+06 8.93E+05 4.72E+06 2.70E+06 1.06E+07Wp-CIR Raw material 2.29E+05 9.41E+04 3.64E+05 3.21E+05 1.01E+06Machinery 2.75E+06 1.13E+06 4.37E+06 3.86E+06 1.21E+07Transportation 3.25E+06 1.23E+06 9.10E+06 7.66E+06 2.12E+07D.2 Capital and Operating Costs of BiorefineryTable D.2: The reference equipment installed and purchased costs of biorefineryOperation unit Reference equipmentinstalled costa (million $)Reference equipmentpurchased cost (million $)Biomass handling and preparation 22.5 9.11HTL reactor system 150.8 61.05Wastewater treatment 22.0 8.91Utilities 7.9 3.20a from [26], based on the plant capacity of 735 tonne bio-oil/day; The equipment installed cost isthe product of the equipment purchased cost and an installation factor, which was assumed to be2.47 as suggested by Dutta et al. [105]101Table D.3: Capacity, feed rate and productivity of biorefinery and wood pellet plantsPlant capacity Feed rate Production rateBiorefinery tonne bio-oil/day dry tonne forest residues/day tonne bio-oil/dayCo-locate with refinery 348 901a/898b 331Chilliwack 89 229 84Squamish 36 94 34Powell River 141 364 133Port Alberni 82 214 78Wood pellet plant tonne pellet/yr dry tonne forest residues/yr tonne pellet/yrChilliwack 7.58E+04 7.64E+04 7.20E+04Squamish 3.11E+04 3.14E+04 2.96E+04Powell River 1.20E+05 1.21E+05 1.14E+05Port Alberni 1.06E+05 1.07E+05 1.01E+05a Forest residues as feedstock for central integrated refinery; b Wood pellet as feedstock for centralintegrated refinery102Table D.4: Capital investment of biorefinery for studied scenariosCapital investment/million $ Fr-CIR Bo-DBR Wp-CIRDepreciable cost (DepC) 178.9 265.6 178.9Total installed cost (TIC) 120.4 178.8 120.4Total purchased equipment cost (TPEC) 48.7 72.4 48.7Indirect cost (IC) 58.5 86.9 58.5Engineering 15.6 23.2 15.6Construction 16.6 24.6 16.6Contractor fees 17.5 26.1 17.5Contingency 8.8 13.0 8.8Non-depreciable cost (NDepC) 7.1 10.6 7.1Land cost 2.7 4.0 2.7Site development 4.5 6.6 4.5Fixed capital investment (FCI) 186 276.2 186Star-up cost (SC) 16.7 24.9 16.7Working capital (WC) 37.2 55.2 37.2Total capital investment (TCI) 240 356.3 240103Table D.5: Operating cost of biorefinery for studied scenariosOperating cost/million $/yr Fr-CIR Bo-DBR Wp-CIRVariable operating cost (VOC) 48.7 29.2 24.7Feedstock 34.8 15.3 10.8aCatalyst 10.3 10.3 10.3Waste treatment 0.3 0.3 0.3Utilities 3.3 3.3 3.3Fuel 0.1 0.1 0.1Electricity 3.1 3.1 3.1Fixed operating cost (FOC) 13.4 23.9 13.4Labor 1.8 4.9 1.8Operating labor 0.8 2.1 0.8Supervisory labor 0.2 0.4 0.2Maintenance labor 0.9 2.4 0.9Maintenance and supplies 4.7 7.1 4.7Maintenance materials 3.3 5.0 3.3Operating supplies 1.4 2.1 1.4Property tax and insurance 5.6 8.3 5.6Plant overhead 1.3 3.6 1.3Total operating cost (TOC) 62.1 53.1 38.0Biochar credit (BC) 6.47 6.48 6.47a The feedstock cost of Wp-CIR scenario stands for pellet transportation cost from FDP to integrated refinery104D.3 Operating Cost of Oil RefineryTable D.6: Operating cost of oil refinery for studied scenariosOperating cost/million $/yr Fr-CIR Bo-DBR Wp-CIRVariable operating cost (VOC) 2.1 5.5 2.1Feedstock 0 2.7a 0Catalyst 1.5 1.7 1.5Waste treatment 0.04 0.04 0.04Utilities 0.6 1.1 0.6Fuel 0 0.5 0Electricity 0.6 0.6 0.6Fixed operating cost (FOC) 2.6 2.6 2.6Labor 0.5 0.5 0.5Operating labor 0.2 0.2 0.2Supervisory labor 0 0 0Maintenance labor 0.2 0.2 0.2Maintenance and supplies 0.8 0.8 0.8Maintenance materials 0.6 0.6 0.6Operating supplies 0.2 0.2 0.2Property tax and insurance 1.0 1.0 1.0Plant overhead 0.4 0.4 0.4Total operating cost (TOC) 4.7 8.1 4.7a The feedstock cost of Bo-DBR scenario stands for bio-oil transportation cost from FDP to oil refinery105D.4 Capital and Operating Costs of Pellet PlantTable D.7: The reference equipment purchased cost and installation factor of wood pellet plantsOperation unit Reference equipmentpurchased cost ($)aInstallation factorbSolid fuel burner 184545 2.1Rotary drum dryer 566813 2.3Drying fan 49766 2.2Multiclone 49766 3Hammer mill 95881 2.8Pellet mill 510760 2.3Pellet cooler 51050 2.7Screen shaker 38352 2Packaging unit 138380 2Storage bin 38352 2Misc. equipment 170112 2.5Front end loader 200000 2Fork lift 164000 2a from [102], based on the plant capacity of 1.00E+05 tonnes wood pellet/yr; b from [103]106Table D.8: Capital investment of wood pellet plants for Wp-CIR scenarioCapital investment/million $ Values/million $Depreciable cost (DepC) 27.2Total installed cost (TIC) 17.6Total purchased equipment cost (TPEC) 7.8Indirect cost (IC) 9.6Engineering 2.6Construction 3.0Contractor fees 2.6Contingency 1.3Non-depreciable cost (NDepC) 1.2Land cost 0.4Site development 0.8Fixed capital investment (FCI) 28.4Star-up cost (SC) 2.6Working capital (WC) 5.7Total capital investment (TCI) 36.6107Table D.9: Operating cost of wood pellet plants for Wp-CIR scenarioOperating cost/million $/yr Values/million $/yrVariable operating cost (VOC) 19.9Feedstock 17.2Catalyst 0.0Waste treatment 0.0Utilities 2.7Fuel 0.2Electricity 2.5Fixed operating cost (FOC) 8.6Labor 4.1Operating labor 2.7Supervisory labor 0.5Maintenance labor 0.9Maintenance and supplies 0.7Maintenance materials 0.5Operating supplies 0.2Property tax and insurance 0.9Plant overhead 2.9Total operating cost (TOC) 28.5E DCFROR AnalysisThe tables below summarize the DCFROR analysis for each studied scenario. Theunit for the values in the table is million $/year. The MSP of biofuels from Fr-CIR,Bo-DBR and Wp-CIR scenarios is $0.89/L, $0.98/L and $0.95/L, respectively.108Table E.1: The DCFROR analysis spreadsheet for Fr-CIR scenarioYear -2 -1 0 1 2 3 4 5 6 7 8 9 10Fixed capital investment (equity) 22.33 37.21 14.88Debt (60% of TCI) 43.20 72.00 28.80Loan payment 21.49 21.49 21.49 21.49 21.49 21.49 21.49 21.49 21.49 21.49Interest 2.81 7.67 10.04 10.04 9.30 8.50 7.66 6.76 5.80 4.79 3.70 2.54 1.31Loan principal 43.20 118.01 154.48 143.03 130.84 117.86 104.03 89.30 73.62 56.91 39.12 20.18 0.00Start-up 16.74Working capital 31.21RevenueBiofuel sales 78.03 89.17 89.17 89.17 89.17 89.17 89.17 89.17 89.17 89.17Biochar (by-product) credit 5.67 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47Total annual revenue 83.69 96.65 96.65 96.65 96.65 96.65 96.65 96.65 96.65 96.65Annual operating costRaw materials 32.52 34.69 34.69 34.69 34.69 34.69 34.69 34.69 34.69 34.69HTL buffer 9.68 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32Hydrotreating catalyst 1.42 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52Hydrogen production catalyst 0.04 0.00 0.00 0.05 0.00 0.00 0.05 0.00 0.00 0.05Wastewater treatment 0.28 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30Utility 3.61 3.85 3.85 3.85 3.85 3.85 3.85 3.85 3.85 3.85Fixed operating cost 16.01 16.01 16.01 16.01 16.01 16.01 16.01 16.01 16.01 16.01Total annual operating cost 63.57 66.69 66.69 66.74 66.69 66.69 66.74 66.69 66.69 66.74Annual depreciationDepreciable cost 178.91MACRS schedule (%) 14.29 24.49 17.49 12.49 8.93 8.92 8.93 4.46Depreciation 25.57 43.82 31.29 23.35 15.98 15.96 15.98 7.98Net revenue -15.49 -24.16 -10.84 -1.10 6.22 7.19 8.15 17.28 26.41 27.60Loss forwarad 0.00 -15.49 -39.65 -50.49 -51.59 -45.37 -38.18 -30.03 0.00 0.00Taxble income -15.49 -39.65 -50.49 -51.59 -45.37 -38.18 -30.03 -12.75 26.41 27.60Annual income tax 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.87 7.18Annual cash flow -22.33 -37.21 -14.88 -1.37 7.47 7.47 7.42 7.47 7.47 7.42 7.47 0.60 0.25Discount factor 1.21 1.10 1.00 0.91 0.83 0.75 0.68 0.62 0.56 0.51 0.47 0.42 0.39Annual present value -27.01 -40.93 -14.88 -1.25 6.17 5.61 5.07 4.64 4.21 3.81 3.48 0.25 0.09Net present value 0.00Note: Net revenue = Total annual revenue - Total annual operating cost - Interest - Depreciation; Taxable income = Net revenue + Loss forward; Annual income tax =Taxable income × Income tax rate; Annual cash flow = Total annual revenue - Total annual operating cost - Loan Payment - Annual income tax.109Year 11 12 13 14 15 16 17 18 19 20Fixed capital investment (equity)Debt (60% of TCI)Loan paymentInterestLoan principalStart-upWorking capitalRevenueBiofuel sales 89.17 89.17 89.17 89.17 89.17 89.17 89.17 89.17 89.17 89.17Biochar (by-product) credit 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47Total annual revenue 96.65 96.65 96.65 96.65 96.65 96.65 96.65 96.65 96.65 96.65Annual operating costRaw materials 34.69 34.69 34.69 34.69 34.69 34.69 34.69 34.69 34.69 34.69HTL buffer 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32Hydrotreating catalyst 1.42 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52Hydrogen production catalyst 0.00 0.00 0.05 0.00 0.00 0.05 0.00 0.00 0.05 0.00Wastewater treatment 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30Utility 3.61 3.85 3.85 3.85 3.85 3.85 3.85 3.85 3.85 3.85Fixed operating cost 16.01 16.01 16.01 16.01 16.01 16.01 16.01 16.01 16.01 16.01Total annual operating cost 66.69 66.69 66.74 66.69 66.69 66.74 66.69 66.69 66.74 66.69Annual depreciationDepreciable costMACRS schedule (%)DepreciationNet revenue 28.96 28.96 28.91 28.95 28.95 28.91 28.95 28.95 28.91 28.95Loss forwarad 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Taxble income 28.96 28.96 28.91 28.95 28.95 28.91 28.95 28.95 28.91 28.95Annual income tax 7.53 7.53 7.52 7.53 7.53 7.52 7.53 7.53 7.52 7.53Annual cash flow 21.43 21.43 21.39 21.43 21.43 21.39 21.43 21.43 21.39 21.43Discount factor 0.35 0.32 0.29 0.26 0.24 0.22 0.20 0.18 0.16 0.15Annual present value 7.51 6.83 6.20 5.64 5.13 4.66 4.24 3.85 3.50 3.18Net present value110Table E.2: The DCFROR analysis spreadsheet for Bo-DBR scenarioYear -2 -1 0 1 2 3 4 5 6 7 8 9 10Fixed capital investment (equity) 33.15 55.24 22.10Debt (60% of TCI) 64.14 106.90 42.76Loan payment 31.90 31.90 31.90 31.90 31.90 31.90 31.90 31.90 31.90 31.90Interest 4.17 11.39 14.91 14.91 13.80 12.63 11.37 10.04 8.62 7.10 5.49 3.78 1.95Loan principal 64.14 175.21 229.35 221.36 194.26 174.98 154.45 132.58 109.30 84.50 58.09 29.96 0.00Start-up 24.86Working capital 55.24RevenueBiofuel sales 85.19 97.36 97.36 97.36 97.36 97.36 97.36 97.36 97.36 97.36Biochar (by-product) credit 5.67 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47Total annual revenue 90.85 103.83 103.83 103.83 103.83 103.83 103.83 103.83 103.83 103.83Annual operating costRaw materials 16.95 18.08 18.08 18.08 18.08 18.08 18.08 18.08 18.08 18.08HTL buffer 9.68 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32Hydrotreating catalyst 1.54 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65Hydrogen production catalyst 0.02 0.00 0.00 0.02 0.00 0.00 0.02 0.00 0.00 0.02Wastewater treatment 0.28 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30Utility 4.07 4.35 4.35 4.35 4.35 4.35 4.35 4.35 4.35 4.35Fixed operating cost 26.44 26.44 26.44 26.44 26.44 26.44 26.44 26.44 26.44 26.44Total annual operating cost 58.98 61.13 61.13 61.15 61.13 61.13 61.15 61.13 61.13 61.15Annual depreciationDepreciable cost 265.62MACRS schedule (%) 14.29 24.49 17.49 12.49 8.93 8.92 8.93 4.46Depreciation 37.96 65.05 46.46 33.18 23.72 23.69 23.72 11.85Net revenue -20.99 -36.15 -16.38 -1.86 8.95 10.39 11.86 25.37 38.93 40.74Loss forwarad 0.00 -20.99 -57.14 -73.52 -74.38 -66.43 -56.04 -44.18 0.00 0.00Taxble income -20.99 -57.14 -73.52 -75.38 -66.43 -56.04 -44.18 -18.81 39.93 40.74Annual income tax 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10.12 10.59Annual cash flow -33.15 -55.24 -22.10 -0.03 10.80 10.80 10.78 10.80 10.80 10.78 10.80 0.68 0.19Discount factor 1.21 1.10 1.00 0.91 0.83 0.75 0.68 0.62 0.56 0.51 0.47 0.42 0.39Annual present value -40.11 -60.77 -22.10 -0.02 8.93 8.11 7.37 6.71 6.20 5.53 5.04 0.29 0.07Net present value 0.00111Year 11 12 13 14 15 16 17 18 19 20Fixed capital investment (equity)Debt (60% of TCI)Loan paymentInterestLoan principalStart-upWorking capitalRevenueBiofuel sales 97.36 97.36 97.36 97.36 97.36 97.36 97.36 97.36 97.36 97.36Biochar (by-product) credit 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47Total annual revenue 103.83 103.83 103.83 103.83 103.83 103.83 103.83 103.83 103.83 103.83Annual operating costRaw materials 18.08 18.08 18.08 18.08 18.08 18.08 18.08 18.08 18.08 18.08HTL buffer 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32Hydrotreating catalyst 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65 1.65Hydrogen production catalyst 0.00 0.00 0.02 0.00 0.00 0.02 0.00 0.00 0.02 0.00Wastewater treatment 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30 0.30Utility 4.35 4.35 4.35 4.35 4.35 4.35 4.35 4.35 4.35 4.35Fixed operating cost 26.44 26.44 26.44 26.44 26.44 26.44 26.44 26.44 26.44 26.44Total annual operating cost 61.13 61.13 61.15 61.13 61.13 61.15 61.13 61.13 61.15 61.13Annual depreciationDepreciable costMACRS schedule (%)DepreciationNet revenue 42.70 42.70 42.69 42.70 42.70 42.69 42.70 42.70 42.69 42.70Loss forwarad 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Taxble income 42.70 42.70 42.69 42.70 42.70 42.69 42.70 42.70 42.69 42.70Annual income tax 11.10 11.10 11.10 11.10 11.10 11.10 11.10 11.10 11.10 11.10Annual cash flow 31.60 31.60 31.59 31.60 31.60 31.59 31.60 31.60 31.59 31.60Discount factor 0.35 0.32 0.29 0.26 0.24 0.22 0.20 0.18 0.16 0.15Annual present value 11.08 10.07 9.15 8.32 7.57 6.87 6.25 5.68 5.17 4.70Net present value112Table E.3: The DCFROR analysis spreadsheet for Wp-CIR scenarioYear -2 -1 0 1 2 3 4 5 6 7 8 9 10Fixed capital investment (equity) 25.73 42.89 17.16Debt (60% of TCI) 49.79 82.99 33.20Loan payment 24.77 24.77 24.77 24.77 24.77 24.77 24.77 24.77 24.77 24.77Interest 3.24 8.84 11.57 10.72 9.80 8.83 7.79 6.69 5.52 4.26 2.93 1.51 0.00Loan principal 49.79 136.02 178.06 164.87 150.81 135.85 119.91 102.93 84.85 65.60 45.10 23.26 0.00Start-up 19.30Working capital 42.89RevenueBiofuel sales 85.86 98.13 98.13 98.13 98.13 98.13 98.13 98.13 98.13 98.13Biochar (by-product) credit 5.67 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47Total annual revenue 91.53 104.60 104.60 104.60 104.60 104.60 104.60 104.60 104.60 104.60Annual operating costRaw materials 26.15 27.89 27.89 27.89 27.89 27.89 27.89 27.89 27.89 27.89HTL buffer 9.68 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32Hydrotreating catalyst 1.42 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52Hydrogen production catalyst 0.04 0.00 0.00 0.05 0.00 0.00 0.05 0.00 0.00 0.05Wastewater treatment 0.29 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31Utility 6.14 6.55 6.55 6.55 6.55 6.55 6.55 6.55 6.55 6.55Fixed operating cost 24.56 24.56 24.56 24.56 24.56 24.56 24.56 24.56 24.56 24.56Total annual operating cost 68.29 71.20 71.20 71.20 71.20 71.20 71.20 71.20 71.20 71.20Annual depreciationDepreciable cost 206.12MACRS schedule (%) 14.29 24.49 17.49 12.49 8.93 8.92 8.93 4.46Depreciation 29.46 50.48 36.05 25.75 18.41 18.39 18.41 9.19Net revenue -16.93 -26.88 -11.48 -0.14 8.30 9.50 10.73 21.27 31.89 33.40Loss forwarad 0.00 -16.93 -43.82 -55.30 -55.44 -47.14 -37.64 -26.92 0.00 0.00Taxble income -16.93 -43.82 -55.30 -55.44 -47.14 -37.64 -26.92 -5.64 31.89 33.40Annual income tax 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 8.29 8.68Annual cash flow -25.73 -42.89 -17.16 -1.53 8.63 8.63 8.63 8.63 8.63 8.63 8.63 0.34 -0.05Discount factor 1.21 1.10 1.00 0.91 0.83 0.75 0.68 0.62 0.56 0.51 0.47 0.42 0.39Annual present value -31.14 -47.18 -17.16 -1.39 7.13 6.48 5.89 5.36 4.87 4.43 4.03 0.14 -0.02Net present value 0.00113Year 11 12 13 14 15 16 17 18 19 20Fixed capital investment (equity)Debt (60% of TCI)Loan paymentInterestLoan principalStart-upWorking capitalRevenueBiofuel sales 98.13 98.13 98.13 98.13 98.13 98.13 98.13 98.13 98.13 98.13Biochar (by-product) credit 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47 6.47Total annual revenue 104.60 104.60 104.60 104.60 104.60 104.60 104.60 104.60 104.60 104.60Annual operating costRaw materials 27.89 27.89 27.89 27.89 27.89 27.89 27.89 27.89 27.89 27.89HTL buffer 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32 10.32Hydrotreating catalyst 1.42 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52 1.52Hydrogen production catalyst 0.00 0.00 0.05 0.00 0.00 0.05 0.00 0.00 0.05 0.00Wastewater treatment 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31Utility 6.55 6.55 6.55 6.55 6.55 6.55 6.55 6.55 6.55 6.55Fixed operating cost 24.56 24.56 24.56 24.56 24.56 24.56 24.56 24.56 24.56 24.56Total annual operating cost 71.20 71.20 71.20 71.20 71.20 71.20 71.20 71.20 71.20 71.20Annual depreciationDepreciable costMACRS schedule (%)DepreciationNet revenue 33.40 33.40 33.40 33.40 33.40 33.40 33.40 33.40 33.40 33.40Loss forwarad 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Taxble income 33.40 33.40 33.40 33.40 33.40 33.40 33.40 33.40 33.40 33.40Annual income tax 8.68 8.68 8.68 8.68 8.68 8.68 8.68 8.68 8.68 8.68Annual cash flow 24.71 24.71 24.71 24.71 24.71 24.71 24.71 24.71 24.71 24.71Discount factor 0.35 0.32 0.29 0.26 0.24 0.22 0.20 0.18 0.16 0.15Annual present value 8.66 7.87 7.16 6.51 5.92 5.38 4.89 4.45 4.04 3.67Net present value114

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
https://iiif.library.ubc.ca/presentation/dsp.24.1-0368789/manifest

Comment

Related Items