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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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2
Fundamentals of Life-Cycle Assessment

Life-cycle assessment (LCA) is an analysis technique that can be used to quantify a wide variety of environmental and social impacts that can be attributed to the provision of a good or service. This report focuses on the use of LCA to estimate greenhouse gas (GHG) emissions associated with transportation energy sources. According to the definition given by the International Standardization Organization (ISO) in the ISO 14040:2006 series standard, LCA is a “compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle.” (ISO 14040:2006). This chapter provides background on how LCAs are commonly conducted, reviews the foundational concepts in LCA, and disambiguates key terminology that is used throughout this report. Although this chapter describes LCA methods in the context of transportation fuels, the fundamental LCA concepts and guidelines can apply to a wide range of goods and services.

This chapter first describes the four phases involved in conducting an LCA as defined in the ISO 14040/14044 standards. Next, two types of LCA are presented: attributional LCA (ALCA) and consequential LCA (CLCA). The selection of functional units and system boundaries are then discussed in the context of these types of analysis.

THE FOUR PHASES OF CONDUCTING A LIFE-CYCLE ASSESSMENT

The ISO 14040/14044 (ISO, 2006a,b) series is a commonly used standard for LCA. It provides principles and a framework for LCA (ISO 14040:2006) and requirements and guidelines (ISO 14044:2006) for conducting an LCA. Notably, it does not provide specific recommendations for methods, datasets, or tools for conducting an LCA, noting that “there is no single method for conducting LCA” (ISO 14040:2006). In essence, it provides a common language for conducting an LCA and basic guidelines for structuring an analysis without being prescriptive on the details of how an LCA should be performed. Although other standards for LCA exist (e.g., Guinée et al., 2018), ISO is arguably the most widely used and this chapter makes use of ISO terminology in its description of LCA.

Per the ISO standard, an LCA has four phases (see Figure 2-1). The first of these is the goal and scope definition phase. This phase lays the foundation for an LCA, specifying the goal of conducting the analysis. For transportation fuels policy, this goal could be to assign GHG emissions-intensity scores that can be compared across a range of fuel options. Another goal could be to inform and prioritize technology development or operational choices to reduce the environmental impact of a particular fuel. In some other cases, the goal of an LCA may be to conduct regulatory impact assessment to understand how a transportation fuel policy will change system-wide emissions at a national or global scale. Clarity on the goal of the study and how its results will be used helps shape all subsequent decisions for its design. The scope of the study clarifies which systems will be included. In the case of a fuel’s life cycle, a single fuel production route (commonly referred to as a “fuel pathway”) may be considered, or the scope may expand to include all sectors that are linked to the product or action being studied. The resulting differentiation between what sectors/activities are included versus excluded is determined by the system boundary, and any activities outside the system boundary are not included in the analysis.

The second phase of an LCA is a life-cycle inventory (LCI) analysis, which entails cataloging the material and energy flows across a fuel’s life cycle. This may be done in a bottom-up manner using facility-level data, estimated through top-down approaches that rely on sector-level data, or through some combination of the two (see further discussion below). In a bottom-up analysis of fuels produced from petroleum, the LCI may involve compiling data on energy consumed and emissions produced during crude oil extraction and refining, on the transportation of intermediate and final petroleum products, and on the eventual

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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combustion of the fuel in a vehicle. These activities make up the primary supply chain for a petroleum-derived fuel and, when combined, are considered to be a fuel pathway. Each stage in the fuel pathway also has its own supply chain, with corresponding upstream resource consumption and emissions. For example, petroleum refineries consume electricity, which is generated using multiple energy sources. Building materials to construct facilities and purchases from service sectors such as insurance are all part of this extended supply chain and can be important to include. As discussed further in the CLCA section, an LCI may also be used to quantify economy-wide changes in material and energy flows associated with the implementation of a policy or a change in production of an individual fuel.

In systems with mature technologies, these data may be obtained from government or industry reports. In emerging systems that are not yet well established at a commercial scale, LCI data may be generated through a combination of engineering models and empirical data from small-scale pilot or demonstration operations. For analyses seeking to understand economy-wide impacts of an action or policy, general equilibrium models or other economic models and data may also be used to capture market-mediated effects. Examples of market-mediated effects include the land use change (LUC) from production of biofuels and shifts in total market demand for fuels and other co-products as a result of a change in supply. Data sources can vary across an LCI; reporting one’s data sources transparently can increase confidence in LCA results and enable reproducibility. Data quality in an LCI directly influences the quality of LCA results. For studies that are focused on GHG emissions, carbon dioxide (CO2) from combustion can usually be approximated by using information about the fuel type(s) combusted for different activities across the supply chain and the stoichiometry of complete combustion. However, non-combustion emissions also have to be accounted for in the inventory phase and these emission factors often rely on field measurements, satellite data, or self-reported data from industry. For example, natural gas systems emit fugitive methane emissions, and agricultural systems emit nitrous oxide (N2O) and methane (CH4).

Life-cycle impact assessment is the third phase of conducting an LCA. In a life-cycle impact assessment, the data from the inventory phase, usually reported in physical units (e.g., kg of pollutant emitted or MJ [megajoule] of a fuel consumed), are used to calculate impact results in terms of multiple so-called indicators, which capture a wide range of human health, climate, and ecological impacts. There are numerous calculation methods available to convert LCI data to indicators, including but not limited to ReCiPe, USEtox, TRACI, and IMPACT 2002+ (Wang et al., 2020). For example, life-cycle GHG emissions may be calculated on an individual basis (separate inventories for CO2, CH4, N2O, refrigerants, and any other relevant GHGs) based on the amounts and types of energy combusted, by process (non-combustion) emissions, and measured or simulated levels of fugitive emissions. These individual emissions totals can then be combined based on their relative climate impact and reported as global warming potential (GWP) in the form of CO2-equivalents (CO2e) (Peters, 2010). This reported CO2e is often referred to as “carbon intensity” (CI), “carbon footprint,” or “GHG footprint”, despite the fact that not all emissions commonly included in the footprint (namely N2O) contain carbon. Impacts can also be converted to costs (or net benefits) by estimating the monetized damages to society associated with each impact. GHG emissions are typically translated into monetized damages by using a value known as the social cost of carbon, which can be helpful in conducting cost–benefit analyses for emissions mitigation efforts, although social cost of carbon estimates may be incomplete in their accounting of potential damages (Bressler 2021; IWG, 2021).

The fourth phase of an LCA is the interpretation phase, in which impact assessment results are translated into meaningful information and guidance. In this phase, LCA practitioners interpret the impact assessment to inform policy or advice on fruitful directions for research and development to reduce system-wide effects. As noted in Figure 2-1, the process is often iterative, and the interpretation phase may highlight the need for collection of additional inventory data to address key sources of uncertainty or even a revision in the study’s goal and scope. Interpretation is not the last phase in LCA but rather part of an iterative process concurrently with the other phases so as to inform LCA design.

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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FIGURE 2-1 Four phases of life-cycle assessment. SOURCE: Adapted from ISO 14040:2006. ©ISO. This material is reproduced from ISO 14040:2006 with permission of the American National Standards Institute (ANSI) on behalf of the International Organization for Standardization. All rights reserved.

TWO BROAD CATEGORIES OF LIFE-CYCLE ASSESSMENT

In defining the goal and scope of an LCA, a practitioner may select from a wide variety of desired outcomes: perhaps two different products are being compared to inform the selection of one based on its environmental impact or an industrial production process is being assessed to identify opportunities for reducing its life-cycle impacts. However, there are two broad categories of LCA that are relevant to this report and require such fundamentally different approaches that they are important to discuss in greater detail: attributional LCA and consequential LCA. ALCA is defined by “environmentally relevant physical flows to and from a life cycle and its subsystem” (Finnveden et al., 2009). ALCA seeks to attribute a portion of total observed environmental impacts from human activities to the provision of a specific good or service. In contrast, CLCA is defined by its aim to describe “how environmentally relevant flows will change in response to possible decisions” (Finnveden et al., 2009). In other words, CLCA captures the consequences of some change in the provision of goods or services. Table 2-1 provides a list of definitions of attributional and consequential LCA from the research literature. Note that one of the examples in Table 2-1 uses the term “hybrid” LCA to refer to a mix of ALCA and CLCA; in this report, the term “hybrid” is used to refer to a combination of process-based and economic input-output (EIO) LCA, as discussed further in the ALCA section. While these definitions of ALCA and CLCA vary slightly, the common thread is that ALCA estimates emissions as they are or could be in some projected future state (among other things, requiring choices about how to assign emissions to co-products), and CLCA estimates how emissions will change in response to a decision or action. Both ALCA and CLCA can be useful in research, analysis, and policy design, but they answer different questions and will produce different results (see Figure 2-2). ALCA and CLCA can be applied to quantify a wide variety of impacts well beyond GHG emissions. Although not discussed in detail here, ALCA and CLCA can be applied to quantify a wide variety of impacts well beyond GHG emissions. Social LCA, for example, estimates social and socio-economic impacts (UNEP-SETAC, 2020) and can be useful in regulatory impact assessment.

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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TABLE 2-1 Definitions of Attributional and Consequential LCA from the Literature

Source Definitions of Attributional and Consequential LCA
Matthews et al. (2014) Attributional LCAs seek to determine the effects now, or in the past, which inevitably means that our concerns are restricted to average effects. However, emerging practice and need in LCA often seeks to consider the consequences of product systems or changes to them. In consequential LCA studies, marginal, instead of average, effects are considered (Finnveden et al. 2009). Marginal effects are those effects that happen ‘at the margin’, and in economics refer to effects associated with the next additional unit of production. Furthermore, consequential analyses seek to determine what would change or need to change given the influence of changing product systems on markets.”
NRC (2012) Attributional LCA, the more traditional form, traces the material and energy flows of a biofuel supply chain and seeks to attribute environmental impact to a biofuel based upon these flows.

Consequential LCA, on the other hand, considers the environmental effects of the cascade of events that occur as a result of a decision to produce or not to produce a given biofuel.”
RFS2 Regulatory Impact Assessment (EPA, 2010)a “Lifecycle assessments can be divided into two major methodological categories: attributional and consequential. An attributional approach to GHG emissions accounting in products provides information about the GHG emitted directly by a product and its life cycle. The product system includes processes that are directly linked to the product by material, energy flows or services following a supply-chain logic. A consequential approach to GHG emissions accounting in products provides information about the GHG emitted, directly or indirectly, as a consequence of changes in demand for the product. This approach typically describes changes in GHG emissions levels from affected processes, which are identified by linking causes with effects. The definition of lifecycle greenhouse gas emissions established by Congress states that: “The term ‘lifecycle greenhouse gas emissions’ means the aggregate quantity of greenhouse gas emissions (including direct emissions and significant indirect emissions such as significant emissions from land use changes), as determined by the Administrator, related to the full fuel lifecycle, including all stages of fuel and feedstock production and distribution, from feedstock generation or extraction through the distribution and delivery and use of the finished fuel to the ultimate consumer, where the mass values for all greenhouse gases are adjusted to account for their relative global warming potential.” This definition and specifically the clause “(including direct emissions and significant indirect emissions such as significant emissions from land use changes)” requires the Agency to consider a consequential lifecycle analyses and to develop a methodology that accounts for all of the important factors that may significantly influence this assessment, including the secondary or indirect impacts of expanded biofuels use.
British Columbia Low Carbon Fuel Standard Avoided Emissions Policy: Intentions Paper for Consultationb “An attributional LCA accounts for only the direct emissions associated with the fuel lifecycle, including the emissions from production of energy and material inputs to the fuel life cycle. Emissions are allocated between co-products based on a physical quantity and indirect impacts are not considered…A consequential LCA determines the comprehensive greenhouse gas (GHG) emissions of a product by assessing the direct and indirect impacts of the fuel on external markets. A consequential LCA considers the market effects of a change in production, expands the system boundary to include non-fuel system impacts, and includes the indirect effects of the fuel production on the environment (e.g. indirect land use change)... The consequential approach to LCA essentially compares a scenario without the fuel to one with the fuel and attributes the resulting changes in affected markets to the fuel.

Hybrid LCA: Hybrid LCA is a combination of attributional and consequential LCA.”
Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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Source Definitions of Attributional and Consequential LCA
Finnveden et al. (2009) Attributional LCA is defined by its focus on describing the environmentally relevant physical flows to and from a life cycle and its subsystems.

Consequential LCA is defined by its aim to describe how environmentally relevant flows will change in response to possible decisions (Curran et al., 2005). Similar distinctions have been made in several other publications (Ekvall, 1999), but often using other terms to denote the two types of LCA (such as descriptive versus change-oriented) and sometimes including further distinctions of subcategories within the two main types of LCA (Guineé et al., 2002).
Ekvall et al. (2016) Attributional LCI considers the flows in the environment within a chosen temporal window.
Consequential LCI considers how the flows may change in response to decisions.
Ekvall (2019) Attributional LCA: LCA aiming to describe the environmentally relevant physical flows to and from a life cycle and its subsystems.

Consequential LCA: LCA aiming to describe how environmentally relevant flows will change in response to possible decisions. Ekvall has developed these definitions based on Finnveden et al. (2009) and argued that: “These definitions clearly connect ALCA/CLCA not only to methodological choices but also to the goal of the study, because they respond to different questions” described in Figure 2-2.
UNEP-SETAC (2011) The attributional approach attempts to provide information on what portion of global burdens can be associated with a product (and its life cycle). In theory, if one were to conduct attributional LCAs of all final products, one would end up with the total observed environmental burdens worldwide. The consequential approach attempts to provide information on the environmental burdens that occur, directly or indirectly, as a consequence of a decision (usually represented by changes in demand for a product). In theory, the systems analyzed in these LCAs are made up only of processes that are actually affected by the decision.
EUCAR (2020)c Attributional LCA: It depicts the potential environmental impacts that can be attributed to a system (e.g. a product) over its life cycle, i.e. upstream along the supply-chain and downstream following the system’s use and end-of-life value chain.

Consequential LCA: It aims at identifying the consequences that a decision in the foreground system has for other processes and systems of the economy, both in the analyzed system’s background system and on other systems. It models the analyzed system around these consequences.

a Renewable Fuel Standard Program (RFS2) Regulatory Impact Assessment. Report number: EPA-420-R-10-006; Date published: February 2010. URL: https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=P1006DXP.TXT.

b See https://www2.gov.bc.ca/assets/gov/farming-natural-resources-and-industry/electricity-alternative-energy/transportation/renewable-low-carbon-fuels/bc_low_carbon_fuel_standard_avoided_emission_policy_-_intentions_paper_for_consultation.pdf.

c European Council for Automotive R&D; see https://www.eucar.be/lca-in-wtt-and-wtw-review-and-recommendations/.

ATTRIBUTIONAL LIFE-CYCLE ASSESSMENT

In an ALCA, an inventory of emissions or impacts that occur along each stage of a supply chain are assigned or attributed to a functional unit. A functional unit is a core characteristic of ALCA (although not exclusive to ALCA) and it is the common basis on which environmental effects are evaluated and reported. Functional units serve as the denominator in LCA results (impact per functional unit), so they must be defined in a manner that captures the value or function provided by a product. In the case of transportation fuels, common functional units are MJ of fuel and vehicle-mile traveled (Chapter 6 discusses in

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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more detail vehicle-fuel combinations and the types of functional units that are appropriate for drawing comparisons across multiple fuels and vehicle technologies). Other functional units may be more appropriate when different modes of transportation are being compared for the movement of freight or people, such as ton-mile or passenger-mile traveled. Use of common functional units is one important step to enable comparison across different ALCAs.

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FIGURE 2-2 Illustration of how attributional (left) and consequential (right) LCA address different questions. NOTE: The yellow circles refer to global environmental burdens. SOURCE: Weidema (2003). Reprinted with permission from Copenhagen: Danish Environmental Protection Agency (Environmental Project no. 863).

The system boundary is a second core characteristic of ALCA. Establishing an appropriate system boundary requires several steps. First, the primary stages of the product’s supply chain has to be selected for analysis. In the case of transportation fuels, it is common to include material extraction, transportation of raw material to point of processing, raw material conversion into fuel, transportation of fuel to points of distribution, and combustion of the fuel. In a system boundary that encompasses multiple fuel systems, this consideration will be more complex.

A second consideration is the time scale of the study. An ALCA may consider an existing technology operating in the context of current infrastructure systems or it may be focused on some future state in which the technology or infrastructure systems have evolved. Finally, a geographic scope has to be established. An ALCA may limit the system boundary to a production and use occurring in one or more specific geographic regions.

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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There are three main techniques for carrying out ALCA: process-based LCA, EIO LCA, and hybrid LCA, which combines elements of the first two.

  • Process-based LCA uses a bottom-up emissions accounting approach, measuring or estimating emissions from each activity within the chosen system boundary.
  • EIO LCA uses a top-down emissions accounting approach, leveraging data on economic trade and emissions from each sector of the economy to estimate emissions associated with economic activity in particular sectors.1
  • Hybrid Process/EIO LCA combines bottom-up process-based LCA estimates with EIO LCA estimates.

These three approaches (process-based LCA, EIO LCA, and hybrid) answer the question “what emissions are attributable to a product or process?” based on decisions made by the modeler about what to include in the system boundary and which emissions to assign to which products or processes when there are co-products (Matthews et al., 2014). Each of the approaches answers this question at differing levels of detail. The most traditional approach to ALCA is process-based LCA, which uses bottom-up emissions accounting to estimate the emissions from material and energy flows for producing a fuel, including a portion of or all of its supply chain. A process-based LCA, by necessity, cannot include every supply chain activity, so system boundaries are drawn to prevent the analysis from continuing indefinitely. The level of detail used for modeling each supply change stage may vary. For example, national-level material and energy flows may be used in some cases (e.g., crude oil extraction, corn agriculture, average petroleum refinery energy and material consumption), facility-specific data may be used in other cases (e.g., from a specific refinery), and, in the absence of such data, a process model may be built to estimate anticipated

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1 Committee member Farzad Taheripour wishes to clarify the following: This report classifies the EIO method as an ALCA approach. This classification is at least inconsistent with some common ALCA definitions provided in Table 2-1 of this report. This table asserts that:

  • “An attributional approach to GHG emissions accounting in products provides information about the GHG emitted directly by a product and its life cycle. The product system includes processes that are directly linked to the product by material, energy flows or services following a supply-chain logic.”
  • “An attributional LCA accounts for only the direct emissions associated with the fuel lifecycle, including the emissions from production of energy and material inputs to the fuel lifecycle.”
  • “The attributional approach attempts to provide information on what portion of global burdens can be associated with a product (and its life cycle).”

Table 2-1 also declares that:

  • “A consequential approach to GHG emissions accounting in products provides information about the GHG emitted, directly or indirectly, as a consequence of changes in demand for the product. This approach typically describes changes in GHG emissions levels from affected processes, which are identified by linking causes with effects.”
  • “A consequential LCA determines the comprehensive greenhouse gas (GHG) emissions of a product by assessing the direct and indirect impacts of the fuel on external markets. A consequential LCA considers the market effects of a change in production, expands the system boundary to include non-fuel system impacts, and includes the indirect effects of the fuel production on the environment.”
  • “The consequential approach attempts to provide information on the environmental burdens that occur, directly or indirectly, as a consequence of a decision (usually represented by changes in demand for a product).”

An EIO analysis, ignoring its limitations and deficiencies, quantifies changes in direct and indirect emissions induced by changes (usually increases) in sectoral demands and or supplies. This approach does not attribute a portion of global burden to a product. It calculates direct and indirect emissions induced by changes in sectoral demands or supplies. Therefore, this method follows a consequential approach. Figure 2-2 of this report also suggests that the EIO method is consequential. Taheripour et al. (2022) have outlined how a typical input-output analysis calculates direct and indirect induced emissions due to changes in sectoral demands or supplies.

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×

flows. Process-based LCAs can provide insight into which steps in a process are responsible for a substantial fraction of total energy consumption or emissions and therefore merit attention from engineers and designers who want to reduce environmental burdens. A limitation of process-based LCAs is their reliance on a wide variety of data sources that may vary in accuracy and representativeness. Public and commercial databases intended for use in process-based LCA can be poorly documented and may convey false precision by reporting values with significant figures well beyond what is appropriate. Another limitation of process-based LCAs is that they do not account for effects on material or energy consumption and corresponding GHG emissions outside the system boundary. Therefore process-based models are subject to truncation error, meaning they do not capture the full extent of economy-level effects and thus will underestimate these effects (Lave et al., 1995; Matthews et al., 2008). It is because of this last point that the approaches of EIO LCA, environmentally extended input–output LCA (EEIO LCA), and hybrid LCA were developed.

The second ALCA approach, EIO LCA or EEIO LCA, uses information about how much each economic sector directly purchases from other economic sectors, assembled in a matrix (input–output table) that can be used to calculate the monetary sum of all inputs that a sector requires directly or indirectly to produce its output. In the United States, this information is published regularly by the Bureau of Economic Analysis in the form of an input–output table, with 71-sector input-output data updated each year and the 405-sector input–output data updated every 5 years. Impact vectors are assembled as a set of linear multipliers that translate dollars of economic activity in each sector to a given environmental metric (e.g., CO2 emissions) (Matthews et al., 2014). Impact vectors (e.g., emissions intensities per dollar) are usually developed by dividing sector-specific emissions totals (or other metrics, such as freshwater withdrawals) by total economic output from that sector to establish direct emissions or other metrics per dollar of economic activity in each sector. EIO LCA models are linear in nature, so each dollar of economic activity within a sector is assigned exactly the same set of impacts. A commonly-used U.S.-based EIO LCA model is national in scope (Matthews et al., 2014, Ch. 8), although multi-regional models are also available (Cicas et al., 2007; Stadler et al., 2018). Together, these data can estimate broader supply chain relationships of economic activity, and corresponding emissions. For example, production of automobiles requires production of steel, which requires production of iron ore, and so forth (Hendrickson et al., 2006).

EIO LCA models lack the technological granularity of process-based models, but can be used to screen for likely hot spots of high environmental impact across a broader system boundary. Another challenge is that flows are typically linked to environmental effects based on monetary value of materials or energy carriers. This linking requires translation of monetary values into mass or energy flows based on an assumed market value, and it does not differentiate different products or activities within an individual economic sector. Market values for any given energy carrier or material fluctuate with time, so EIO LCA results may become unrepresentative of a system when major market value shifts. If major technological advancements occur in one or more sectors, this will only be reflected once updated input–output tables and impact vectors are in place. In EIO LCA models, emissions from each sector are based on average, rather than marginal, emissions in the sector, so these analyses generally do not estimate net emissions implications of changes in fuel use unless marginal emissions are similar to average emissions in the relevant economic sectors (e.g., if emissions are linear with economic output in the relevant sectors).2 The U.S.

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2 EIO LCA and process-based LCA are commonly held to be ALCA. For example, Plevin et al. (2014) state, “Conceptually and structurally, EIO is a version of ALCA, with an expanded, more interconnected set of processes than in what might be called ‘traditional’ once-through process-based LCA.” Such a view is supported by Finnveden et al. (2009), who conclude, “With regard to the discussion on attributional and consequential LCA, it can be noted that the average data contained in an IOA [EIO LCA] are adequate for attributional LCA but less so for consequential LCA. They typically do not describe how the resource uses and emissions of a sector are affected by possible decisions.” Indeed, the early developers of the EIO LCA approach note that it has “the advantage of including effects attributable [emphasis added] to the influences of many indirect suppliers, which can be overlooked in process models” (Hendrickson et al. 1998). Nevertheless, because EIO LCA models emissions throughout the economy, some researchers think of it as a type of CLCA. However, as noted above, because EIO LCA models average, rather than marginal, emissions from each sector, it does not meet the definitions in Table 2-1 that require CLCA to estimate the change in emissions resulting from a decision or action.

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×

Environmental Protection Agency (EPA) has established a set of tools based on U.S. EEIO data which is updated on an ongoing basis (Yang et al., 2017a). Recent research has used EEIO methodology to evaluate environmental and socio-economic effects of biofuels and related technologies (Lamers et al., 2021).

The third approach, hybrid process/EIO LCA, is an attributional approach in which process-based LCA modeling for specific processes of interest is combined with economy-wide process modeling from the EIO LCA approach (Heijungs and Suh, 2002). In doing so, it attempts to extend what is known about supply chains beyond the specific process under examination (Suh et al., 2004). The method and extent of integration can vary depending on the study, and methods include tiered hybrid analysis, input–output based hybrid analysis, and integrated hybrid models (Suh et al., 2004). For example, one study may represent only the conversion stage of a fuel’s life cycle with a detailed process model and use an EIO LCA model to estimate effects that occur upstream and downstream of the conversion stage. Another might use detailed process models for both the upstream and conversion stages and turn to EIO LCA to estimate emission from the downstream portions of the supply chain. As an example, EIO LCA could be used to handle the effects of co-products on the broader economy. Although different approaches may be well justified given the goals of each individual study, these inconsistencies in hybrid LCA can complicate cross-study comparisons. The main advantage in pursuing a hybrid approach is to combine the insights available at the process-level from process-based LCA with the broader reach of EIO LCAs to cover a larger swath of the economy and associated environmental effects. Although the limitations of EIO LCA still apply, the hybrid method may help to reduce systematic biases that result from truncation error in purely process-based LCAs. Recent work on hybrid LCA databases is improving the databases and methodology of hybrid LCA (Agez et al., 2021).

It is important to consider the applicability of these types of ALCA in the context of transportation fuels. Process-based, EIO, and hybrid process/EIO LCA all provide approaches to track environmental effects across fuel supply chains. Process-based LCA, for example, can be useful in informing the development of a new fuel production process (e.g., converting lignin to a hydrocarbon fuel). An analysis that is focused on understanding and improving the life-cycle GHG footprint of an industrial process may benefit most from focusing detailed analysis on emissions sources that will be directly affected by changes to the process. Some sectors that are captured in EIO LCA, such as those associated with office workers in the insurance or finance sector, may not be as directly affected by process-level details at the facility. Conversely, an analysis seeking to capture the most comprehensive picture of life-cycle environmental effects would benefit from development of a hybrid process/EIO LCA to capture effects across a broader system boundary. These three types of ALCA can all have a role to play in decision-making, depending on the types of insights sought from the analysis. However, when the question of interest is how emissions will change as a result of a policy action or a change in fuel consumption, an attributional analysis will not provide an answer; a consequential analysis is the only type of analysis targeted to answering that question.

CONSEQUENTIAL LIFE-CYCLE ASSESSMENT

As noted above, CLCA asks a different question from ALCA, focused on how emissions or impacts will change in response to a decision or action (see Table 2-2; Ekvall, 2019; Schaubroeck et al., 2021). It estimates the difference in total emissions or environmental effect between one or more scenarios, in which some action is taken, and one or more counterfactuals in which no action is taken. A CLCA may report results on the basis of a functional unit that corresponds to a given quantity of some product or service (e.g., a gallon of fuel). However, the application of CLCA is not limited to this type of analysis. In the context of this report, the change to be captured by CLCA may be increased fuel supply or implementation of a policy. CLCA can include cascades of effects throughout the economy, as in EIO LCA, as well as other market-mediated effects, such as the effect that increasing fuel supply has on fuel prices and ultimately on demand and emissions (Earles and Halog, 2011; Ekvall, 2019). The defining feature of CLCA that differentiates it

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×

from ALCA is that it estimates the change in emissions induced by a decision or action (Figure 2.2). Often the scope of CLCA studies is broad, estimating economy-wide changes induced by a decision or action, but this is not always the case, and CLCA/ALCA can both use either broad or narrow system boundaries, depending on the LCA goal and scope (Table 2-2).

Methodologies used in CLCA may include equilibrium, input–output, and dynamic models (Le Luu et al., 2020) as well as process-based models that estimate changes, rather than averages. For example, while an ALCA approach may assign the average electricity grid mix and emission factors to a process that consumes electricity, a CLCA would attempt to estimate which types of power plants are most likely to increase generation to meet the increase in power demand, or how the power sector infrastructure itself may change (Chapter 10). For biofuel LCAs, LUC is often modeled consequentially (see Chapter 9), even as the biofuel supply chains themselves are modeled using a predominantly ALCA approach. This practice of mixing ALCA and CLCA is discussed in Chapter 3.

The approach for conducting a CLCA will vary depending on the scale of the change being evaluated. When the change in question is small in comparison with an overall market for a fuel or other product, consequential emissions can be estimated using models that capture the effects at the margin. Returning to the electricity grid example, the overall generation mix in any particular region may include substantial quantities of nuclear, hydroelectricity, coal, and renewable energy sources, but depending on the time of day, the marginal grid mix may be mostly or entirely natural gas if those power plants are responsible for meeting marginal increases in demand. Actions or policies that result in larger relative differences in production require different modeling approaches to predict the structural changes needed to accommodate the change. Because the cascade of changes induced by a technology or policy change can be wide reaching and complicated, answering a consequential question may involve high uncertainty. CLCAs that seek to predict net changes of a policy or other action years into the future run the risk of failing to predict other changes that are unrelated to the policy or action but occur in parallel. This possible problem does not necessarily imply that all CLCAs result in greater uncertainty relative to ALCAs, as results will vary on a case-by-case basis. As with ALCA, there is no single approach to conducting a CLCA and the selection of models and datasets needs to be guided by the goal of the study. Table 2-3 summarizes the three types of ALCA and the category of CLCA.

COMPARISON OF ATTRIBUTIONAL AND CONSEQUENTIAL LIFE-CYCLE ANALYSIS

As discussed in the preceding sections, an important difference between ALCA and CLCA pertains to the concept of average versus marginal emissions. Equally important is the fact that CLCA tends to, in many cases, include a larger system boundary because of the need to incorporate market-mediated effects that are not captured in ALCA. Box 2-1 provides examples of system boundaries for both ALCA and CLCA in a particular study, although the presentation of this approach does not imply endorsement by this committee.

TABLE 2-2 Relationship between System Boundary and LCA Type

LCA Type System Boundary
Process and Supply Chain Economy-wide
ALCA: Average emissions attributed to products or services Process-based ALCA Economic input-output-LCA
CLCA: Change in emissions due to a decision or action Process-based CLCA Equilibrium models
Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×

Figure 2-3 shows how attributional and consequential LCA relate to the research question of interest. When an analysis is addressing a question of how emissions will change in response to a decision or action, CLCA is appropriate (see Table 2-3). If the resulting change in a fuel’s consumption is small, marginal emission factors can estimate consequential emissions, but if the change is large, consequential emissions may be non-marginal. In contrast, when addressing the question of how existing emissions can be attributed to fuels, the researcher has a choice: a consequential approach may be appropriate if the primary goal is to attribute to fuels the emissions associated with changes in use of those fuels; an attributional approach may be appropriate if the primary goal is to assign a share of existing emissions to fuels and other co-products. Attributional approaches often, but not always, assign average emission rates to products.

TABLE 2-3 Summary of Major Approaches to LCA

Method Approach Question Addressed System Boundary
Attributional LCA: Process-Based Bottom-up emissions accounting What emissions are attributable to a process or product, as approximated by a supply chain, within the system boundaries? Typically the process in question; potentially including portions of its supply chain
Attributional LCA: Economic Input-Output Top-down emissions accounting What emissions are attributable to a process or product, as approximated by a sector, within the system boundaries? National, multi-regional or global economy
Attributional LCA: Hybrid Process/EIO Both bottom-up and top-down emissions accounting What emissions are attributable to a process or product within the system boundaries, as approximated by a combination of supply chain and economic sector information? National, multi-regional or global economy
Consequential LCA Counterfactual emissions comparison How will emissions change in response to a decision or action? Varies, but ideally as comprehensive as possible, including global effects
Image
FIGURE 2-3 LCA approaches by research question and relationship to average and marginal emission.
Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×

Figure 2-4 illustrates consequential GHG emissions from increased production of a fuel for which GHG emissions increase non-linearly with production. The first scenario (current) has no change, decision, or action that would influence fuel production. The second scenario (result) includes such a change, decision, or action. Figure 2-4a shows the difference in emissions between the two scenarios. Figure 2-4b illustrates that using average emissions estimates from an attributional LCA in this situation can produce poor estimates of the emissions consequences of the change unless emissions rise linearly with volume. Marginal emissions are shown in Figure 2-4c and represent the slope of the emissions curve at current levels. Marginal emissions can produce good estimates of consequential emissions when changes are small or when or the emissions curve is linear but can produce poor estimates when changes are large and the emissions curve is nonlinear, as in the illustration. Non-marginal consequential analysis can estimate the consequential change directly (Figure 2-4a) by estimating the difference between emission levels with and without a proposed change, decision or action.

Importantly, in practice, many LCAs draw on elements from more than one of these approaches. For example, many CLCAs make use of average estimates for particular products or processes when consequential estimates are unavailable. Additionally, some largely process-based LCAs attempt to account for some consequential effects, such as LUC, credits for avoided burdens from co-product displacement or substitution, and other estimated changes relative to the counterfactual (baseline).

As a consequence of the variety of approaches that an LCA practitioner can adopt, it is unsurprising that LCA studies of the same product or system can produce conflicting results. At a high-level, these differences can result from (1) different questions being asked, (2) different methods being used to answer these different questions, (3) different underlying data or (4) different scope and assumptions.3

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.

Conclusion 2-2: Process-based ALCAs entail bottom-up accounting where emissions are assigned to products or processes based on modeling approach of a static world. Process-based ALCA can identify major sources of emissions in well-defined supply chains and identify opportunities to reduce supply chain carbon intensity, especially when case-specific process-data can be used instead of generic data. Economic input-output life-cycle assessment (EIO LCA) identifies implications of interactions across broad sectors of the economy. It can capture emissions that may not be immediately apparent if only a well-defined supply chain is evaluated. It also is helpful in flagging emissions sources that are far-removed from the foreground system but are major contributors to total environmental effects. Hybrid Process/EIO ALCA identifies major sources of emissions beyond well-defined supply chains to include economy-wide effects. CLCA assesses the net effect of a decision or action, such as a change in fuel use or a change in policy, on total GHG emissions.

Conclusion 2-3: LCA results can vary depending on which methods are used, which data are used, which assumptions are made, what scope is defined, and what question is asked.

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.

___________________

3 For a detailed description of this effect, see Box 2-2 and Chapter 5 in National Research Council (2011).

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×

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/robustness analysis for modeling choices for the scenarios modeled with and without the proposed decision or action.

Image
FIGURE 2-4 Illustration of the hypothetical relationships between attributional and consequential emissions and average and marginal emission factors for a single fuel, shown for one possible case when GHG emissions from increased production of this fuel are convex with fuel production volume. The figure is not intended to imply that GHG emissions are always convex with production volume. Emissions’ response to production volumes, particularly when large shifts in production occur, may take other shapes, including concave, linear, or nonconcave/nonconvex. The implementation of these models may or may not translate analytically in results depicted by these figures, as each model differs in how it represents emissions and production volumes, as well as their relationship.

Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×

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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
×
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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Suggested Citation:"2 Fundamentals of Life-Cycle Assessment." National Academies of Sciences, Engineering, and Medicine. 2022. Current Methods for Life-Cycle Analyses of Low-Carbon Transportation Fuels in the United States. Washington, DC: The National Academies Press. doi: 10.17226/26402.
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Transportation is the largest source of greenhouse gas emissions in the United States, with petroleum accounting for 90 percent of transportation fuels. Policymakers encounter a range of questions as they consider low-carbon fuel standards to reduce emissions, including total emissions released from production to use of a fuel or the potential consequences of a policy. Life-cycle assessment is an essential tool for addressing these questions. This report provides researchers and practitioners with a toolkit for applying life-cycle assessment to estimate greenhouse gas emissions, including identification of the best approach to use for a stated policy goal, how to reduce uncertainty and variability through verification and certification, and the core assumptions that can be applied to various fuel types. Policymakers should still use a tailored approach for each fuel type, given that petroleum-based ground, air, and marine transportation fuels necessitate different considerations than alternative fuels including biofuels, hydrogen, and electricity. Ultimately, life-cycle assessments should clearly document what assumptions and methods are used to ensure transparency.

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