6.5 Fischer-Tropsch Fuel from Coal and Biomass
6.5.2 Results: F-T Jet Fuel from Coal and Biomass
Local sensitivity analysis was conducted on the feedstock type, the quantity of GHG emissions from land use change, CTL process efficiency, biomass weight percentage, torrefaction efficiency, CCS efficiency and CCS compression energy. Each parameter was varied with all others held at their baseline values with the impact on life cycle GHG emissions quantified as a percent change from the baseline value. Figure 10 presents this information in a manner that allows the magnitude of each change to be seen in comparison to the others. The biomass feed rate has the dominant influence. Since the biomass feed rate is a parameter that is chosen by the operator, the emissions from CBTL facilities will be dictated by practical, as opposed to technological, limitations. Overall, the choice of feedstock and the potential for soil carbon sequestration were found to have a larger impact on life cycle GHG emissions than the process efficiencies.
When examining the impacts of changing the plant efficiency (this can be achieved either directly or by changing the energy consumption for biomass pre-processing or carbon dioxide compression) it was found that lower efficiencies lead to lower net emissions. This counter- intuitive result occurs because the plants were chosen to be self-sufficient and CCS is used to capture emissions from gasifying additional biomass to supply syngas for process fuel. The
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Figure 10: Sensitivity analysis of operational specifications and configurations of F-T jet fuel from coal and biomass
The results for the low emissions, baseline and high emissions scenarios for CBTL using switchgrass as the biomass feedstock are shown in Tables 38 and 39. Table 38 gives the results when no soil carbon sequestration credit is given to the switchgrass while Table 39 gives the results when the soil carbon sequestration credit is included. The ‘biomass credit’ represents the CO2 that is absorbed from the atmosphere during biomass growth. Increasing biomass credit reflects larger amounts of biomass being used as feedstock.
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Table 38: Summary of results for F-T jet fuel from coal and biomass without soil carbon sequestration credit
Land Use Change Scenario B0 Low Baseline High
Key Assumptions
Biomass Weight Fraction 40% 25% 10%
Biomass Input Switchgrass Switchgrass Switchgrass
Carbon Capture Efficiency 90% 85% 80%
CBTL Process Efficiency (LHV)
48.9%
(53% without CCS or biomass processing)
46.0%
(50% without CCS or biomass processing)
44.1%
(47% without CCS or biomass processing) Life Cycle CO2 Emissions by Stage
Biomass Credit (gCO2/MJ) -78.6 -44.3 -15.3
Recovery of feedstock (gCO2/MJ) 1.2 1.2 1.1
Transportation of feedstock (gCO2/MJ) 0.3 0.2 0.1
Processing of feedstock to fuel (gCO2/MJ) 14.7 21.9 28.6
Transportation of jet fuel (gCO2/MJ) 0.5 0.5 0.5
Combustion CO2 (gCO2/MJ) 70.4 70.4 70.4
WTT GHG Emissions by Species
WTT CO2 emissions (gCO2/MJ) -62.0 -20.5 14.9
WTT CH4 emissions (gCO2e/MJ) 1.1 4.9 13.6
WTT N2O emissions (gCO2e/MJ) 2.9 2.0 0.9
Total WTW GHG Emissions (gCO2e/MJ) 12.4 56.9 99.8
Life Cycle GHG Emissions Relative to
Baseline Conventional Jet Fuel 0.14 0.65 1.14
Table 39: Summary of results for F-T jet fuel from coal and switchgrass with soil carbon sequestration credit
Land Use Change Scenario B1 Low1 Baseline1 High1
Land use change emissions (gCO2/MJ) -5.5 -3.9 -2.0
WTW CO2 emissions (gCO2/MJ) 2.9 46.0 83.4
Total WTW GHG Emissions (gCO2e/MJ) 6.9 53.0 97.8
Life Cycle GHG Emissions Relative to
Baseline Conventional Jet Fuel 0.08 0.61 1.12
Notes:
1) All other input assumptions (cultivation of switchgrass, F-T processing and carbon capture efficiency) are based on those in the B0 emissions case of the corresponding scenario.
The life cycle GHG emissions of the CBTL pathway range from 0.14 to 1.14 times those of conventional jet fuel when no soil carbon sequestration credit is given. The emissions for this pathway range from 0.08 to 1.12 times those of conventional jet when the soil carbon sequestration credit is included. The large range of this pathway is primarily driven by the variation in biomass weight fraction of the feedstock.
In their assessment of F-T diesel production, Tarka (2009) used a displacement (system expansion) scheme instead of energy-based allocation to account for the benefit of making a reduced carbon, biomass-based F-T naphtha in addition to the F-T diesel. As such, their results differ from those given here. When a common allocation approach and productions assumptions are implemented, both analyses yield similar results.
Figure 11: Dependence of cumulative life cycle emissions and biomass requirements for varied biomass utilization within CBTL
Figure 11 presents the implication of varying biomass weight over a range of 5% to 45%. Life cycle GHG emissions can be reduced to a fraction of conventional jet fuel with considerable biomass usage. For example, provided sufficient CCS is available, a CBTL jet fuel created from 45% biomass could have life cycle GHG emissions that are only 20% of conventional jet fuel;
however, roughly 245 railroad cars of biomass would be needed every day to create sufficient CBTL jet fuel to power the aircraft at Boston Logan airport.37 This large amount of biomass highlights the importance of considering GHG reductions for high biomass weight percentages in conjunction with biomass feeding requirements; it also points to lower biomass percentages being more realistic. Future work will consider the economics of CBTL fuels.
6.5.3 Case Study: Impact of Carbon Capture on GHG Emissions from CBTL Facilities