LIFE CYCLE ANALYSIS OF BIOFUELS WITH THE GREET MODEL

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1 drhgfdjhngngfmhgmghmghjmghfmf LIFE CYCLE ANALYSIS OF BIOFUELS WITH THE GREET MODEL MICHAEL WANG Systems Assessment Group Energy Systems Division Argonne National Laboratory NAS Workshop on Bioenergy with Carbon Capture and Storage Irvine CA, October 23, 2017

2 The GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model Available at Update and release annually Supported by three DOE EERE transportation R&D offices Stochastic Simulation Tool Carbon Calculator for Land Use Change from Biofuels (CCLUB) GREET 1 model: Fuel-cycle (or well-to-wheels, WTW) modeling of vehicle/fuel systems GREET 2 model: Vehicle cycle modeling for vehicles 2

3 GREET outputs include energy use, greenhouse gases, criteria pollutants and water consumption for vehicle and energy systems Energy use Total energy: fossil energy and renewable energy Fossil energy: petroleum, natural gas, and coal (they are estimated separately) Renewable energy: biomass, nuclear energy, hydro-power, wind power, and solar energy Greenhouse gases (GHGs) CO 2, CH 4, N 2 O, black carbon, and albedo CO 2e of the five (with their global warming potentials) Air pollutants VOC, CO, NO x, PM 10, PM 2.5, and SO x They are estimated separately for Total (emissions everywhere) Urban (a subset of the total) Water consumption 3

4 GREET Includes Various Biomass Feedstocks, Conversion Technologies, and Fuels Grains, sugars, and cellulosics Fermentation, Indirect Gasification Fermentation Hydrothermal Liquefaction Ethanol, butanol Renewable diesel Waste feedstock Cellulosics Anaerobic Digestion Combustion Combustion Pyrolysis, Fermentation, Gasification (e.g., FT) Natural gas and derivatives Electricity Drop-in hydrocarbon fuels Gasification (e.g., FT), Alcohol to Jet, Sugar to Jet Aviation and marine fuels Algae and oil crops Transesterification Hydroprocessing, Hydrothermal Liquefaction Hydroprocessing Biodiesel Renewable diesel 1 - Overview 4

5 GREET Approach and Data Sources Approach Build a consistent LCA platform with reliable, widely accepted methods/protocols Address emerging LCA issues Maintain openness and transparency of LCAs by making GREET publicly available Primarily process-based LCA approach (the so-called attributional LCA); some features of consequential LCA are incorporated Data sources Open literature and results from other researchers DOE and other agencies R&D results Fuel producers and technology developers for fuels and automakers for vehicles Simulations with models such as ASPEN Plus for fuel production and ANL Autonomie and EPA MOVES for vehicle operations Baseline technologies and energy systems: EIA Annual Energy Outlook (AEO) projections, EPA egrid for electric systems, etc. Consideration of effects of regulations already adopted by agencies 2 - Approach 5

6 GREET System Boundary for Biofuel LCA: Direct Activities and Indirect Effects Are Included 2 - Approach 6

7 GREET Life-Cycle GHG Emissions of Selected Biofuels: Feedstock Is the Main Driver WTW GHG emissions, g CO 2 e/mj WTP Biogenic CO₂ in Fuel PTW LUC WTW With LUC Without LUC With LUC With LUC With LUC Gasoline Corn ethanol Sugarcane ethanol Corn stover ethanol Switchgrass ethanol Miscanthus ethanol 3 - Accomplishments 7

8 Emission breakout for different biofuels 8

9 GREET biofuel LCA in the context of carbon sequestration Co-production of biofuels and biochar via fast pyrolysis Soil carbon change from biofuel feedstock growth Carbon uptake by biomass growth: biomass additionality 9

10 Yields High Liquid Fuel Yields of Fast Pyrolysis 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Vapor Residence Time Temperature Liquid Char Gas Fast Intermediate Slow Gasification ~1 sec ~10 sec very long very long ~500 C ~500 C ~400 C ~800 C [Bridgewater 2007] A liquid fuel from pyrolysis and subsequent upgrading is a mixture of naphtha-range (gasoline blend stock) and diesel-range (diesel blend stock) products, compatible with current delivery infrastructure and engine technologies Fast pyrolysis pathway is one biofuel pathway of high interest 10

11 Hydrogen Source and Biochar Use are Key Factors for Pyrolysis-Based Fuel GHG Results Fertilizer Production Corn Stover Collection & Transportation Forest Residue Collection & Transportation NG Fuel Gas Fuel Gas & NG Reforming Pyrolysis Oil Reforming H 2 Hydrogen Source Pyrolysis Pyrolysis Oil Recovery Hydrotreating & Upgrading Gasoline/ Diesel T&D Vehicle Operation Biochar Biochar Application Soil Amendment Power Generation C Sequestration Reduced Fertilizer Use Electricity Conventional Fertilizer Production Conventional Electricity Generation Key factors for pyrolysis GHG results Liquid fuel yield Biochar fate For internal steam/power generation vs. soil amendment Biochar properties (e.g., C and N content) H 2 requirement for bio-oil stabilization and upgrading Pyrolysis oil composition and fuel products H 2 sourcing from external NG vs. from internal bio-oil 11

12 GREET LCA Addresses Key Parameters for Pyrolysis Pathways Several cases are included FN: Fuel Gas/NG reforming for H 2 & biochar combustion for thermal demand PO-Elec: Pyro-oil reforming for H 2 & excess biochar combustion for elec. generation PO-Soil: Pyro-oil reforming for H 2 & excess biochar application for soil amendment H 2 for two feedstocks with Biochar C and Liquid fuel & co-product yields varied bio-oil quality N content 12

13 WTW GHG Emissions of Pyrolysis-Based Liquid Fuels Vary Among Various Technology Options FN (Fuel Gas/NG reforming for H2) reduces GHG emissions by 60% (55-64%) relative to gasoline Reforming pyrolysis oil for H 2 (PO) reduces GHG emissions by 88% (85-91%) relative to gasoline Reforming pyrolysis oil, however, reduces the liquid fuel yields sharply Applying biochar as a soil amendment reduces GHG emissions further by 112% (97-126%) relative to gasoline 13

14 CCLUB Was Developed for GREET to Simulate Soil Organic Carbon (SOC) Change from Land Use Change: Interaction between CCLUB module and main GREET model Field-to-Pump Energy and material inputs Pump-to-Wheel Feedstock production Feedstock logistics, storage and transportation Feedstock conversion Fuel transportation and distribution Fuel combustion GREET GHG emissions w/o LUC emissions Domestic lands: - Surrogate CENTURY for non-forest lands - COLE for forest lands Domestic LUC Domestic LUC GHG emissions GREET GHG emissions w/ LUC emissions GTAP modeled LUC LUC GHG emissions International LUC Harris et al. (2009) for C changes of international land International LUC GHG emissions GREET CCLUB module for LUC GHG emissions 14

15 LUC GHG Emissions (g CO 2 e/mj) CARB 2009 EPA 2010 Laborde 2011 CARB 2015 EU FQD (prop.) 2015 ECOFSY Trend of Estimated LUC GHG Emissions for Corn and Sugarcane Ethanol Critical factors for LUC GHG emissions: Land intensification vs. extensification Crop yields: existing cropland vs. new cropland; global yield differences and potentials Double cropping on existing land Extension to new land types: cropland, grassland, forestland, wetland, etc. Price elasticities Crop yield response to price Food demand response to price 40 Soil organic carbon changes from 35 land conversions and land management Sugarcane Ethanol Corn Ethanol 0 5

16 Production of Bioenergy Feedstock Can Cause Land Use Change or Land Management Change Soy CCLUB

17 SOC modeling a key tool in evaluating potential SOC changes under LUC Capture site- or region-specific soil and climate conditions Examine influence of agricultural practices Control variables that influence SOC systematically Incorporate different time horizons 17 Credit: J. B. Dunn

18 SOC Upon Land Transitions/ Land Management Depends On Many Factors Land use history (to SOC status) Biomass yield Climate Soil depth for measurement and simulation Management practices Credit: P.F. Dunn Credit: National Renewable Energy Laboratory Credit: P.F. Dunn Credit: Ken Goddard 18

19 SOC modeling is done with a surrogate CENTURY model for CCLUB Spatiotemporal database Surrogate CENTURY model Spatiotemporal SOC 19

20 To Corn To Miscanthus Qin et al., GCB Bioenergy, SOC changes upon land transition vary spatially and by feedstock type From Cropland Pasture From Forest SOC rate t ha -1 yr -1

21 Conversion of cropland-pasture to corn with stover removal shows mostly increasing SOC; conversion of grassland or forest shows largely decreasing SOC 21 Qin et al., GCB Bioenergy, 2016.

22 Conversion to energy grasses tends to increase or maintain SOC; conversion to short rotation woody crop production can cause it to decline 22 Qin et al., GCB Bioenergy, 2016.

23 Crop Yield (t/ha) Soil Carbon Removing stover can decrease SOC compared to a reference case; cover crop/manure may maintain/increase SOC Increasing Increasing w/ removal w/o removal Corn Soybean

24 GHG Emissions (g-co 2 e/mj-ethanol) Land management practices affects biofuel s life-cycle GHG emissions What if: 100% removal? Conventional Gasoline SR: stover removal CC: cover crop M: manure 40 60% Reduction % stover removal, conventional tillage SR CC M SR CC M SR CC M SR CC M SR CC M SR CC M Marginal Energy Marginal Energy Marginal Energy Combined Gallon Stover Ethanol Grain Ethanol Other Operations Fertlizer (Energy and N2O) LMC (N2O Emissions) LMC (Energy and Chemical Inputs) LMC (SOC Changes) Net Emissions Qin et al., GCB Bioenergy, in revision

25 Biomass Additionality Argument Questions Whether Bioenergy Systems Have Carbon Reductions Only additional biomass growth in biophysical systems can result in carbon neutrality for bioenergy Biomass additionality by bioenergy Switch between biomass uses among different purposes vs. additional biomass growth: Productivity of different biophysical systems Biomass growth: managed systems vs. natural biophysical systems Length of carbon cycle of biomass feedstocks is a key dimension Annual: annual crops and perennial grasses A few years: short-rotation trees years: forests 25

26 26 Modeling of Woody Feedstock Growth and Carbon Dynamics for GREET LCA: A collaboration with CORRIM

27 Long Time Between Planting and Harvest Results in Slower Carbon Uptake Compared with Annual Crops CO 2 Trees uptake and store atmospheric carbon Carbon cycle is slower than annual crops Woody feedstock converted to a transportation fuel Vehicles combust fuel and emit CO 2 The growth curve highlights how long it can take to reach preharvest carbon levels. Specific growth curves are dependent on tree species, growth management regime, and other local conditions (climate, soil, etc.). 3 - Accomplishments 27

28 AGWP and dynamic GWP Two Carbon Accounting Methods Were Considered to Address the Temporal Carbon Dynamics Accounting Method 1 Cumulative effects of CO 2 over the growth/harvest Cycle (e.g., 100 yrs) using the time dependent GWP to address warming effect at Yr 100) Fuel/chemical emissions Biomass growth AGWP, W/m2/kg CO2 yr GWP Yr 0 Yr Time horizon of carbon emissions Accounting Method 2 Net present emissions over the growth/harvest cycle (e.g., 100 yrs) by discounting emissions with 2% rate based on annual atmospheric decay rate of CO 2 Yr 0 Yr Accomplishments Yr 0 Time Horizon Boundary Only emissions through year 100 are considered, regardless of when they start Yr 100 Both methods have shortfalls: Even though warming effects continues over long time, Method 1 stops the effect arbitrarily at Yr 100 of the growth/harvest cycle Discounting of emissions in Method 2 has no relation to warming effects 28

29 Summary Both biomass feedstock growth and bioenergy conversion are key stage of bioenergy LCA results Land can be a source or sink of carbon under bioenergy systems While biomass can be used to producing biofuels, biopower, and bioproducts, current strong policy incentives are mainly for biofuels (e.g., federal renewable fuel standard and CA low carbon fuel standard) Bioenergy with carbon capture and storage Energy need for capture and cleaning CO2 transportation Storage vs. utilization (for biofuel production such as algae) 29

30 LUC-Related GHG Emissions Vary Significantly Among Biofuel Feedstocks 31 For cellulosic feedstocks, conversion of cropland and grassland to energy grass fields (e.g., Miscanthus farms) could increase or maintain SOC LUC GHG emissions (g CO 2 eq MJ -1 ) Domestic International Total WTW GHG w/o LUC (g CO 2 e MJ -1 ) WTW GHG w/ LUC (g CO 2 e MJ -1 ) Corn Miscanthus Note: 1) LUC GHG emissions are based on 100cm soil depth; variations reflect types of land impacted and land management practices. 2) Conversion of cropland to cornfield with sustainable stover removal could result in increased SOC; conversion of grassland or forest to cornfield could result in decreased SOC

31 CCLUB contains nine cases for biofuels production Case GTAP modeling BG/year 1) Corn Ethanol ) Stover Ethanol 3) Miscanthus Ethanol 4) Switchgrass Ethanol 5) Corn Ethanol ) Soy Biodiesel_CARB case 8 Increase in corn ethanol production from its 2004 level (3.41 billion gallons [BG]) to 15 BG Increase of ethanol from corn stover (i.e. AdvfE-Stover) by 9 BG, on top of 15 BG corn ethanol (continuous corn) 8.97 Increase of ethanol from miscanthus (i.e. AdvfE-Misc) by 7 BG, on top of 15 BG corn ethanol 7.03 Increase of of ethanol from switchgrass (i.e. AdvfE-Swit) by 7 BG, on top of 15 BG corn ethanol 7.03 Increase in corn ethanol production from its 2004 level (3.41 BG) to 15 BG, with GTAP calibrated CET function Increase in soy biodiesel production by BG, using California Air Resources Board (CARB) case ) Soy Biodiesel_CARB Average Proxy 8) Soy Biodiesel_GTAP ) Soy Biodiesel_GTAP 2011 Increase in soy biodiesel production by BG, using California Air Resources Board (CARB) average of 30 cases Increase in soy biodiesel production by 0.8 BG, using GTAP with land intensification, 2004 database 0.8 Increase in soy biodiesel production by 0.5 BG, using GTAP with land intensification, 2011 database 0.5 GTAP runs generate results at the AEZ level. 32