Summary
Greenhouse gas (GHG) emissions drive climate change. In the United States, transportation is the largest source of GHG emissions. Petroleum products account for about 90 percent of U.S. transportation fuels, with biofuels, natural gas, and electricity accounting for the rest.1 To mitigate further effects of climate change, deployment of low-carbon energy technologies, such as fuels with low GHG emissions, is considered to be critical.
There are federal and state programs to reduce GHG emissions from transportation fuels. The Renewable Fuel Standard (RFS) program, which is administered by the U.S. Environmental Protection Agency (EPA), was enacted by Congress in 2005 and amended in 2007. The program aims to reduce lifecycle GHG emissions from transportation fuels, expand the U.S. renewable fuels sector, and reduce reliance on imported oil. At the state level, California and Oregon have adopted low-carbon fuel standards (LCFSs). Recent reports from staff of the House Select Committee on the Climate Crisis2 and from a bipartisan network of former EPA career employees3 indicate interest in a national LCFS.
STUDY PURPOSE AND COMMITTEE’S TASK AND APPROACH
If policies aim to promote low-GHG emissions fuels, the status and capabilities of the methods and assumptions to identify the GHG emissions of fuels need to be understood. A critical part of that understanding is how to use and interpret life-cycle assessment (LCA), that is, the total emissions from any proposed low-carbon fuel.
At the request of Breakthrough Energy, the National Academies of Sciences, Engineering, and Medicine appointed an ad hoc committee to assess current methods for estimating life-cycle GHG emissions associated with transportation fuels (both liquid and nonliquid) for potential use in a national low-carbon fuel program: see Box S-1 for the formal statement of task for the committee.
The committee organized its work by focusing on the methods of LCA and the capabilities needed for potential use in a national low-carbon fuels program. The committee examined general methodological approaches of LCA, key issues for evaluating GHG emissions, issues that arise for transportation fuels, and methodological issues that arise for characteristic types of transportation fuel. Some conclusions and recommendations are given in the next section and all are also provided in a table (sorted by topic) in Appendix A.4
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1EIA 2020, see https://www.eia.gov/energyexplained/use-of-energy/transportation.php.
2 Select Committee on the Climate Crisis, 2020.
3Environmental Protection Network, 2020.
4 Committee member Jason Hill wishes to point out that many other equally important conclusions and recommendations, each of which is also supported by the entire committee, are not shown here. For example, the following three points are fundamentally important to the understanding, design, and application of LCA in LCFS policy:
Conclusion 3-1: The carbon intensities of fuels used in an LCFS are not necessarily equivalent to the full climate consequences of their adoption. Increased use of a fuel with a low carbon intensity, as defined in an LCFS, could potentially decrease or increase carbon emissions relative to the baseline, depending on policy design and other factors. Regulatory impact assessments that use CLCA to project the consequences of policy can help assess the extent to which a given policy design with particular carbon intensity estimates will result in reduced GHG emissions.
Recommendation 9-6: Beyond research on induced land use change and rebound effects, research should be done to identify and quantify the impacts of other indirect effects of biofuel production, including but not limited to market-mediated effects on livestock markets, land management practices, and dietary change of food type, quantity, and nutritional content.
LIFE-CYCLE ASSESSMENT
LCA can address a range of questions regarding GHG emissions of low-carbon transportation fuels. There are two broad approaches to LCA: attributional life-cycle assessment (ALCA) and consequential life-cycle assessment (CLCA), and each require different analysis. ALCA evaluates the emissions that can be attributed to a given fuel while CLCA evaluates how emissions would change if a given policy or set of actions were followed.
Conclusion 2-1: The approach to LCA needs to be guided on the basis of the question the analysis is trying to answer. Different types of LCA are better suited for answering different questions or achieving different objectives, from fine tuning a well-defined supply chain to reduce emissions, to understanding the global, economy-level effect of a technology or policy change.
Recommendation 2-1: When emissions are to be assigned to products or processes based on modeling choices including functional unit, method of allocating emissions among co-products, and system boundary, ALCA is appropriate. Modelers should provide transparency, justification, and sensitivity or robustness analysis for modeling choices.
Recommendation 2-2: When a decision-maker wishes to understand the consequences of a proposed decision or action on net GHG emissions, CLCA is appropriate. Modelers should provide transparency, justification, and sensitivity or robustness analysis for modeling choices for the scenarios modeled with and without the proposed decision or action.
LIFE-CYCLE ASSESSMENT IN A LOW-CARBON FUEL STANDARD POLICY
Challenges in the application of LCA for regulatory purposes, such as an LCFS—including determinations of system boundaries, modeling choices, and uncertainty management—have long been recognized. Nevertheless, given the desire to design policies that achieve reductions in GHG emissions, LCA has been increasingly applied to policy development, and energy and biofuel policy in particular, in recent decades.
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Recommendation 10-4: Analyses estimating the emissions implications of PEV adoption in future power grid scenarios should consider changes in power grid emissions caused by PEV charging in each power grid scenario.
Conclusion 3-2: More research is needed to evaluate effective methods to collectively leverage the strengths of CLCA, ALCA, and verification methods in achieving LCFS objectives.
Recommendation 3-1: When some emissions consequences of fuel use are excluded from carbon intensity values in an LCFS, the rationale, justification, and implications for these exclusions should be documented.
Recommendation 3-2: Public policy design based on LCA should ensure through regulatory impact assessment that, at a minimum, the consequential life-cycle impact of the proposed policy is likely to reduce net GHG emissions and increase net benefits to society. Regulatory impact assessments should consider changes in production and use of multiple fuel types (e.g., gasoline, electricity, biofuels, hydrogen).
Recommendation 3-3: LCA practitioners who choose to combine attributional and consequential LCA estimates should transparently document these choices and clearly identify the implications of combining these different types of estimates for the given application, scope and research question.
Recommendation 3-4: Research programs should be created to advance key theoretical, computational, and modeling needs in LCA, especially as it pertains to the evaluation of transportation fuels. Research needs include:
- Further development of robust methods to evaluate the GHG emissions from development and adoption of low-carbon transportation fuels, and development or integration of process-based, economic input-output, hybrid, and CLCA methodologies.
- Products could include the following:
- development of national, open-source, transparent CLCA models for use in LCFS development and assessment
- continued development of national, open-source attributional ALCA models from new or existing models
- evaluation of different approaches to creating, using, or combining ALCA, CLCA, and verification for evaluation of policy outcomes
- quantification of variation between marginal and average GHG emissions for various feedstock-to-fuel pathways; and
- quantification and characterization of the implications of approximations and proxies in LCA, such as comparisons of marginal and average emissions.
DIRECT AND INDIRECT EFFECTS
GHG emissions associated with transportation fuels include emissions from producing the fuel, from combusting the fuel, and from the full supply chain for producing and distributing the fuel. GHG emissions also include market effects, including changes in land use, changes in electricity infrastructure and electricity system operations, and changes in the demand for fuel and other products. Researchers differ in what they consider as direct and indirect effects. There is, however, agreement that all emissions should be included in an LCA.
Recommendation 4-1: Because the terms “direct” and “indirect” are used differently in different contexts, these terms should be carefully defined and transparently presented when used in LCA studies or policy. Another option is to avoid using the terms “direct” and “indirect” altogether, as they are not considered necessary elements of LCA and may lead to greater confusion.
UNCERTAINTY AND VARIABILITY
LCAs are subject to considerable uncertainty and variability. LCA methods need to appropriately characterize uncertainty and variability to aid LCA stakeholders’ interpretation of LCA results.
Recommendation 4-2: Current and future LCFS policies should strive to reduce model uncertainties and compare results across multiple economic modeling approaches and transparently communicate uncertainties.
Recommendation 4-4: When LCA results are used in policy design or policy analysis, the implications of parameter uncertainty, scenario uncertainty, and model uncertainty for policy outcomes should be explicitly considered, including an assessment of the degree of confidence that a proposed policy will result in reduced GHG emissions and increased social welfare.
Recommendation 4-5: Regulatory agencies should formulate a strategy to keep LCAs up to date, which may involve periodic reviews of key inputs to assess whether sufficient changes have taken place to warrant a re-analysis, and agencies should be aware that substantial changes to LCAs on timescales of less than a decade can occur.
Recommendation 4-6: LCA studies used to inform transportation fuel policy should be explicit about the feedstock and regions to which the study applies and to the extent possible should explicitly report sensitivity of results to variation in these assumptions.
Recommendation 4-9: Modelers should conduct sensitivity analysis to understand implications of variation.
Recommendation 4-10: To effectively inform policymaking, LCA studies should document results for a range of input values.
SCALE OF PRODUCTION
Scale of production can affect the life-cycle implications of a fuel or technology in nonlinear ways. When a fuel is produced at high volumes, it may be produced differently and have different effects on supply chains than when produced at low volume.
Recommendation 4-11: Researchers and regulatory agencies should identify additional information to assess impacts of large changes in fuel systems.
Recommendation 4-12: Because LCA-based carbon intensities in current LCFS policy are often not structured to capture nonlinear and non-lifecycle implications of large changes in fuel and fuel pathway production volume, policymakers should consider potential complementary policy mechanisms.
VERIFICATION
An LCA considers emissions across activities that occur in varied sectors and geographic locations. Because many GHG-emitting activities are not regularly monitored, LCAs rely on data from theoretical calculations, experimental measurements, or a small number of field measurements to approximate the magnitude of their emissions.
Confirming LCA results through direct measurement of all activities for an entire fuel pathway is impractical. However, effort can be focused on verification of emissions sources and effects that have the greatest impact for a given fuel.
Recommendation 5-2: The research and policy communities should develop frameworks and methodologies for use of satellite data to characterize national and international land use change that may be in part attributable to an LCFS. Examples of framing questions include:
- Should an LCFS include measures to mitigate undesirable international land use change, or is it sufficient to monitor international land use change that may be due to the LCFS and these GHG emissions to the associated fuel?
- What are the guardrails (e.g., amount and type of land converted to agriculture in a certain region) that a monitoring approach would put in place and, if approached or exceeded, what action would be undertaken as a result?
- How can satellite data and economic modeling be most effectively used synergistically to limit GHG emissions from international land use change?
- What public data sources will be used to track land use change?
- How should uncertainty in land use change estimates be reported?
Programs may use default baseline values for parameters that are to be certified, such as assuming a default amount of diesel consumed when harvesting corn. The certification process will then establish whether a farm consumes less or more than this default amount. The ability to verify lower or higher emissions can result in economic gain or loss for a supply chain actor, which may motivate them to pursue certification or to produce a fuel that complies with the policy.
Conclusion 5-9: Certification protocols that use verification strategies can complement initial fuel pathway modeling with LCA and associated models (e.g., economic models used to estimate land use changes) to lessen the impacts of uncertainty in LCA results and to inform policymakers of the effects of an LCFS as they unfold. This insight can aid in policy adjustments if undesirable effects arise over the course of the policy.
Recommendation 5-6: An LCFS should consider inclusion of a certification protocol with verification. The protocol and its implementation should be overseen by an agency or group of agencies with the complementary expertise sets needed for success. These expertise sets include insights into multiple energy systems and new technologies, economics, environmental effects of fuels and their production routes, agriculture, fossil fuel production, and electricity generation.
Recommendation 5-7: Certification protocols should be revisited periodically to adapt to the emergence of new verification technology, national and global trends in the energy, transportation, and agriculture sectors, and to update baselines as needed based on evolving common practice.
Recommendation 5-8: Economic modeling and verification processes are complementary to each other and should both be used. Verification processes to assess international- and national-level land use change should use state-of-the art remote sensing technologies, when appropriate, which are evolving toward increased frequency and spatial resolution.
NEGATIVE EMISSIONS
In life-cycle GHG calculations, it is not always just a matter of adding the emissions from different portions of the life cycle; there are some cases in which quantities are subtracted (i.e., negative emissions).
Fuels assigned net negative carbon intensity values raise important questions that warrant special scrutiny to distinguish between actual carbon dioxide removal and storage and fuels pathways that include credits for avoided emissions.
Conclusion 6-1: The carbon intensity of fuels derived from methane that would otherwise be released (e.g., methane from manure or landfill) is strongly influenced by assumptions in the LCA of the alternative fate of methane pollution and is subject to dramatic change if relevant regulations or practices change.
Biomass removes atmospheric carbon (biogenic carbon) through the photosynthesis process and part or all of the biogenic carbon is released during biomass conversion, transportation, decay, and biofuel combustion. Fossil-based carbon may also be released in the same system, such as GHG emissions from burning fossil fuels to supply heat for biomass drying and conversion.
Recommendation 6-2: All biogenic carbon emissions and carbon sequestration generated during the life cycle of a low-carbon fuel should be accounted for in LCA estimates.
Recommendation 6-3: Research should be conducted to improve the methods for accounting and reporting biogenic carbon emissions.
Land use change, land management, and land management change (e.g., reducing tillage frequency, applying manure as a soil amendment) can alter soil carbon. Changes in soil organic carbon can be a significant contributor to the life-cycle GHG emissions of a biofuel.
Conclusion 6-3: Given the importance of soil organic carbon changes in influencing life-cycle GHG emissions of biofuels, investments are needed to enhance data availability and modeling capability to estimate soil organic carbon. Capabilities to evaluate permanence of soil organic carbon changes should also be developed.
Recommendation 6-4: Research should be conducted to collect existing soil organic carbon data from public and private partners in an open source database, standardize methods of data reporting, and identify highest priority areas for soil organic carbon monitoring. These efforts could align with the recommendations made in the 2019 National Academies report on negative emissions technologies to study soil carbon dynamics at depth, to develop a national on-farm monitoring system, to develop a model-data platform for soil organic carbon modeling, and to develop an agricultural systems field experiment network. These efforts should also be extended internationally.
Recommendation 6-5: Research should be conducted to explore remote-sensing and in situ sensor-based methods of measuring soil carbon that can generate more data quickly.
Fuel production leads to the emission and uptake of carbon dioxide (CO2) and other GHGs at every life- cycle stage. These emissions and uptakes are then aggregated into a common unit. To aggregate different GHG emissions into a common unit (i.e., carbon dioxide equivalent [CO2e]), metrics expressing the relative contribution of GHGs to climate change are used.
Recommendation 6-6: Use of more than one climate change metric should be considered in the analysis of low-carbon fuel policies.
Recommendation 6-7: Further research should be conducted to better understand the suitability of different GHG metrics for LCA.
Recommendation 6-8: Further research should be conducted to develop a framework to include albedo effects from land cover change, and near-term climate forcers, in LCA of low-carbon fuels.
Recommendation 6-9: Further research should be conducted to better understand the climate implications of increased GHG emissions on the short-term (carbon debt) to support the selection of an appropriate approach to account for the timing of GHG emissions and uptakes in LCA.
VEHICLE-FUEL COMBINATIONS AND EFFICIENCIES
Life-cycle GHG emissions of transportation fuels can be compared on a per-unit-energy basis, but such a comparison can be incomplete or misleading without also considering how much energy is needed to propel a vehicle with each type of fuel as well as how much energy is required and emissions are created in the production and maintenance of each type of vehicle. Efficiency and production emissions can vary widely both within and across vehicle fuel type technologies, making fair comparisons with single point estimates challenging.
Conclusion 6-5: To make a meaningful comparison of the LCA of transportation fuels, the vehicles that use those fuels should be considered.
Recommendation 6-10: LCA of transportation fuels may include analysis using functional units based on the transportation service provided, such as passenger-mile or ton-mile, or otherwise be based on comparison of comparable transportation services. This may be reported in addition to an energy-based functional unit. LCAs should clearly describe their assumptions for the energy- and service-based functional units, such as through vehicle efficiency, market share, or other factors.
Recommendation 6-11: When comparing life-cycle emissions of different transportation fuels, LCA studies that assess or inform policy should consider the range of vehicle efficiencies within each fuel type to ensure that the comparisons are made on comparable transportation services, such as passenger capacity, payload capacity, or performance.
Recommendation 6-14: For regulatory impact assessment, LCA of transportation fuels and transportation fuel policy should consider a range of estimates for possible changes in the emissions of vehicle production required to convert transportation fuels into transportation services, and the resulting changes in vehicle fleet composition.
Recommendation 6-15: LCA comparing transportation fuels for weight-constrained applications should present a per-ton-mile functional unit and/or explicitly model the logistical implications of payload effects by fuel type.
FOSSIL AND GASEOUS FUELS FOR ROAD TRANSPORTATION
The life-cycle GHG emissions of petroleum fuels – gasoline, diesel, jet fuel – differ by source and by refinery, and could vary over time as petroleum sources change, and as refinery operations change as a result of lower consumption of some petroleum products. The committee recommends that these variations be explicitly included in a low-carbon fuels policy.
Recommendation 7-1: Policymakers may consider recognizing the variation in GHG emissions across different petroleum fuel pathways, and include mechanisms to reduce these emissions in fuel policies.
Conclusion 7-1: Additional data, reporting, and transparency are needed for petroleum sector operations, including improved information on venting and flaring of methane.
Conclusion 7-2: More emissions inventory data from natural gas systems are needed, particularly regarding emissions from storage tanks.
There are multiple steps involved in natural gas recovery and delivery to the point-of-use. In natural gas LCAs, it is important to consider direct methane emissions from each step of this supply chain, which may derive from venting, flaring, or leaking.
Recommendation 7-2: Further research should be done on the key parameters used to assess the climate impacts of natural gas production, such as methane leakage rates. These parameters will evolve as technology advances, data availability increases, and statistical methods may be used to translate the additional data into improved emissions estimates.
Hydrogen can be made from steam-methane reforming or autothermal reforming of methane with (“blue”) or without (“grey”) carbon capture and utilization or storage. In the case of blue and grey hydrogen, the LCA issues pertaining to natural gas can significantly influence hydrogen LCA results. “Green” hydrogen is to be primarily made using electrolysis powered by renewable electricity. This pathway takes into account any energy consumption and associated emissions for delivering and purifying the water.
Recommendation 7-5: In the context of an LCFS, LCAs of hydrogen should be well documented with choices of key parameters supported with facility-measured data or well-supported citations from the literature. These key parameters include the choice of energy source for steam-methane reforming or authothermal reforming, the carbon capture level from the waste gaseous stream, source of upstream electricity, and the rate of methane or CO2 leakage. Where relevant, the approach to quantifying emissions of upstream natural gas production should align with those used elsewhere in an LCFS for other fuels produced from natural gas.
AVIATION FUELS
The life-cycle climate impacts of aviation fuels have been evaluated in the literature and as part of regulatory assessments for several fuels policies. There has been analysis of both conventional, petroleum-derived jet fuel (i.e., “jet fuel”) and of a variety of alternative fuels produced through a wide array of conversion processes (i.e., alternative aviation fuels). Several key areas that may require special consideration beyond the approaches used for alternative fuels used in other sectors include: 1) the non-CO2 effects of aviation fuels when combusted at high altitudes, 2) the impacts of alternative fuels on airplane efficiency, and 3) the impact of a flexible product slate on the life-cycle emissions calculations for aviation fuels.
Conclusion 8-1: Non-CO2 effects from aviation fuels may be high but remain uncertain. The largest non-CO2 impact from aviation fuel combustion may be aviation-induced cloudiness, with the remaining contributions being much smaller.
Recommendation 8-1: Because the non-CO2 effects from aviation fuels remain uncertain, research should be done to clarify the magnitude and direction of these effects.
Recommendation 8-2: Alternative fuels and airframe combinations, particularly those with large density differences such as battery electric technology and hydrogen, may impact airplane efficiency and thus influence overall emissions. The comparative LCA of these technologies should use functional units based on the transportation service provided or otherwise be based on comparison of consistent transportation services.
Recommendation 8-3: Alternative aviation fuel LCA estimates developed for fuel policy should reflect existing practices at facilities or the expected behavior in response to future policies.
MARITIME FUELS
Marine fuels have similar supply chains to other transportation fuels (e.g., aviation, road transport). The unique aspects of their life cycle that is relevant to quantifying their emissions primarily come in the operations stage, such as methane slip from liquefied natural gas combustion in marine engines. Additionally, the non-CO2 effects of the maritime sector warrant additional analysis. The contribution of aerosols to net radiative forcing from the sector via ship tracks—the clouds from ship exhaust—is highly uncertain and may require further research.5 LCA methodological considerations for marine fuels are similar to those for other transportation fuels.
Recommendation 8-5: The baseline life-cycle GHG emissions for marine fuels should reflect current industry trends stemming from MARPOL Annex VI and potentially be updated after several years’ time once the industry adjusts more fully to the new regulations through, for example, deployment of more liquid natural gas-fueled vessels.
BIOFUELS
Corn and soybeans are the most common feedstocks currently used to produce biofuels in the United States. LCA methods commonly used to estimate GHG emissions associated with crop production in conventional agricultural systems are largely similar regardless of the specific crop in question.
Conclusion 9-1: Improved data on biofuel feedstock production, including energy consumption, yield, and fertilizer application at fine spatial resolutions may be useful for some applications. Data quality improvements may support improved GHG accounting in biofuel feedstock production, especially should a performance-based LCFS be developed that accounts for spatially-explicit fertilizer and energy consumption, and land management practices like cover crop planting, land clearing, overfertilization, manure application, use of nitrification inhibitors, or noncompliance with long-term soil carbon storage incentives.
Woody biomass is one of the most abundant feedstock for bioenergy production in the United States. The GHG emissions associated with the production of woody biomass come from multiple sources, including the use of energy and materials (e.g., fertilizers and soil amendments) for forest management, harvesting, storage and transportation.
Recommendation 9-1: Additional research should be done to assess key parameters and assumptions in forest management practices induced by increased woody biomass demand, including: changes in residue removal rates, stand management and forest productivity, and changes in tree species selection during replanting.
Recommendation 9-2: Research and data collection efforts should be carried out for improved data and modeling related to forest feedstock production and storage, including energy use, yield, inputs, fugitive emissions, and changes in forest carbon stock should be supported.
GHG emissions associated with biomass conversion come from multiple sources, including on-site combustion of fuels (e.g., fossil fuels, biomass, or byproducts), direct emissions from conversion processes,
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5 Glassmeier F., F. Hoffmann, J. S. Johnson, T. Yamaguchi, K. S. Carslaw, and G. Feingold. 2021. Aerosol-cloud-climate cooling overestimated by ship-track data. Science 371(6528):485-489. https://doi.org/10.1126/science.abd3980.
and upstream emissions associated with the production of chemicals, enzymes, and electricity used by biorefineries.
Mass or energy balance are the most common methods used to estimate GHG emissions of biorefineries. Some of the attributional GHG emissions of upstream production of electricity and chemicals used in biomass conversion are available in many life-cycle inventory databases but have large variations depending on the production technologies and market mix. Research articles vary in their assumptions about the potential for carbon sequestration using biorefinery co-products as soil amendments, but many assume 80-85 percent of biochar is stable for at least 100 years whereas digestate and compost are not assumed to result in accumulation of stable carbon in soils.
Recommendation 9-3: Policymakers should exercise caution in crediting biorefineries for GHG emissions sequestration as a result of exporting co-products such as biochar, digestate, and compost, as it risks over-crediting producers for downstream behavior that is not necessarily occurring. The committee recommends that any credits generated from these activities must be contingent on verification that these activities are being practiced.
Recommendation 9-4: Applying credits for carbon sequestration to soil or reduced use of fertilizer should require robust measurement and verification to prove the co-products are applied in a manner that yields net climate benefits.
Large-scale production of biofuels has an effect on various markets at regional, national, or global scales and can affect prices in these markets. Changes in market prices can trigger other changes in production and consumption decisions that may have positive or negative effects on GHG emissions from those markets. These changes may be included in the modeling of indirect effects. These secondary effects on GHG emissions are of concern because they affect the savings in GHG emissions obtained by displacing fossil fuels by biofuels.
Recommendation 9-7: Though the study of induced land use changes from biofuels has been the topic of intense study over the last decade, substantial uncertainties remain on many key components of economic models used to assess these impacts. Further work is warranted to update these estimates of market-mediated land use change and the models so as to inform the development and implementation of an LCFS.
Recommendation 9-8: Assessment of the consequential effects from a future proposed policy, such as induced land use change, should be further developed in order to assess the risk of market-mediated effects and emissions attributable to the policy. Consequential assessment can inform the implementation of safeguards within policies such as limits on high-risk feedstocks, can inform the development of supplementary policies, identify hotspots, and reduce the likelihood of unintended consequences.
Recommendation 9-9: To improve understanding of market-mediated effects of biofuels, research should be supported on different modeling approaches, including their treatment of baselines and opportunity costs, and to investigate key parameters used in national and international modeling based on measured data, including various elasticity parameters, soil carbon sequestration, land cover, and emission factors and others.
Recommendation 9-10: Because other market-mediated effects of biofuel production, such as livestock market impacts, land management practices, and changes in diets and food availability may be linked to land use and biofuel demand assessed using induced land use change models, additional research should be done and model improvements undertaken to include these effects.
ELECTRICITY AS A VEHICLE FUEL
Plug-in electric vehicles (PEVs) use energy stored in an onboard battery for propulsion and charge the battery using electricity from the power grid. PEVs include battery electric vehicles, and plug-in hybrid electric vehicles. In ALCA approaches, a portion of total power grid GHG emissions is assigned to PEV charging. In contrast, in CLCA approaches power grid emissions are estimated with and without PEV charging, and the difference between emissions in the two scenarios is the consequential effect of PEV charging.
Conclusion 10-1: ALCA is sometimes applied to estimate emissions from electricity consumption because it is easy or because the modeler is interested in an attributional, rather than consequential, question. However, using average emission factors does not answer the question of how emissions will change if PEVs or PEV policy is adopted. CLCA aims to answer how PEV or PEV policy adoption would change emissions from the power sector.
Recommendation 10-1: Regulatory impact assessment or other analyses estimating the emissions implications of a change in PEV charging load should use a CLCA approach to estimate the implications of power grid emissions and clearly characterize uncertainty of estimates due to assumptions, especially for future scenarios.
Recommendation 10-2: Research should be conducted to estimate how upstream emissions in the power sector change in response to changes in generation.
Recommendation 10-3: Analyses estimating the emissions implications of changing PEV adoption or PEV policy should provide a transparent assessment of how sensitive or robust the results of the analyses are to reasonable variations in modeling assumptions and future scenarios.
Recommendation 10-5: LCA to estimate the change in GHG emissions induced by a policy or a change in technology adoption should consider how interaction with existing policies may affect outcomes. For cars and trucks, national fleet standards are key to understanding the net GHG outcomes of technology or policy actions.
