Richard J. Plevin

Effects of US Maize Ethanol on Global Land Use and Greenhouse Gas Emissions: Estimating Market-mediated Responses

Releases of greenhouse gases (GHG) from indirect land-use change triggered by crop-based biofuels have taken center stage in the debate over the role of biofuels in climate policy and energy security. This article analyzes these releases for maize ethanol produced in the United States. Factoring market-mediated responses and by-product use into our analysis reduces cropland conversion by 72% from the land used for the ethanol feedstock. Consequently, the associated GHG release estimated in our framework is 800 grams of carbon dioxide per megajoule (MJ); 27 grams per MJ per year, over 30 years of ethanol production, or roughly a quarter of the only other published estimate of releases attributable to changes in indirect land use. Nonetheless, 800 grams are enough to cancel out the benefits that corn ethanol has on global warming, thereby limiting its potential contribution in the context of Californias Low Carbon Fuel Standard.

Greenhouse Gas Emissions from Biofuels' Indirect Land Use Change Are Uncertain but May Be Much Greater than Previously Estimated

The life cycle greenhouse gas (GHG) emissions induced by increased biofuel consumption are highly uncertain: individual estimates vary from each other and each has a wide intrinsic error band. Using a reduced-form model, we estimated that the bounding range for emissions from indirect land-use change (ILUC) from US corn ethanol expansion was 10 to 340 g CO(2) MJ(-1). Considering various probability distributions to model parameters, the broadest 95% central interval, i.e., between the 2.5 and 97.5%ile values, ranged from 21 to 142 g CO(2)e MJ(-1). ILUC emissions from US corn ethanol expansion thus range from small, but not negligible, to several times greater than the life cycle emissions of gasoline. The ILUC emissions estimates of 30 g CO(2) MJ(-1) for the California Air Resources Board and 34 g CO(2)e MJ(-1) by USEPA (for 2022) are at the low end of the plausible range. The lack of data and understanding (epistemic uncertainty) prevents convergence of judgment on a central value for ILUC emissions. The complexity of the global system being modeled suggests that this range is unlikely to narrow substantially in the near future. Fuel policies that require narrow bounds around point estimates of life cycle GHG emissions are thus incompatible with current and anticipated modeling capabilities. Alternative policies that address the risks associated with uncertainty are more likely to achieve GHG reductions.

Using Attributional Life Cycle Assessment to Estimate Climate-Change Mitigation Benefits Misleads Policy Makers

Life cycle assessment (LCA) is generally described as a tool for environmental decision making. Results from attributional LCA (ALCA), the most commonly used LCA method, often are presented in a way that suggests that policy decisions based on these results will yield the quantitative benefits estimated by ALCA. For example, ALCAs of biofuels are routinely used to suggest that the implementation of one alternative (say, a biofuel) will cause an X% change in greenhouse gas emissions, compared with a baseline (typically gasoline). However, because of several simplifications inherent in ALCA, the method, in fact, is not predictive of real‐world impacts on climate change, and hence the usual quantitative interpretation of ALCA results is not valid. A conceptually superior approach, consequential LCA (CLCA), avoids many of the limitations of ALCA, but because it is meant to model actual changes in the real world, CLCA results are scenario dependent and uncertain. These limitations mean that even the best practical CLCAs cannot produce definitive quantitative estimates of actual environmental outcomes. Both forms of LCA, however, can yield valuable insights about potential environmental effects, and CLCA can support robust decision making. By openly recognizing the limitations and understanding the appropriate uses of LCA as discussed here, practitioners and researchers can help policy makers implement policies that are less likely to have perverse effects and more likely to lead to effective environmental policies, including climate mitigation strategies.

Bioenergy and climate change mitigation: an assessment

Bioenergy deployment offers significant potential for climate change mitigation, but also carries considerable risks. In this review, we bring together perspectives of various communities involved in the research and regulation of bioenergy deployment in the context of climate change mitigation: Land‐use and energy experts, land‐use and integrated assessment modelers, human geographers, ecosystem researchers, climate scientists and two different strands of life‐cycle assessment experts. We summarize technological options, outline the state‐of‐the‐art knowledge on various climate effects, provide an update on estimates of technical resource potential and comprehensively identify sustainability effects. Cellulosic feedstocks, increased end‐use efficiency, improved land carbon‐stock management and residue use, and, when fully developed, BECCS appear as the most promising options, depending on development costs, implementation, learning, and risk management. Combined heat and power, efficient biomass cookstoves and small‐scale power generation for rural areas can help to promote energy access and sustainable development, along with reduced emissions. We estimate the sustainable technical potential as up to 100 EJ: high agreement; 100–300 EJ: medium agreement; above 300 EJ: low agreement. Stabilization scenarios indicate that bioenergy may supply from 10 to 245 EJ yr−1 to global primary energy supply by 2050. Models indicate that, if technological and governance preconditions are met, large‐scale deployment (>200 EJ), together with BECCS, could help to keep global warming below 2° degrees of preindustrial levels; but such high deployment of land‐intensive bioenergy feedstocks could also lead to detrimental climate effects, negatively impact ecosystems, biodiversity and livelihoods. The integration of bioenergy systems into agriculture and forest landscapes can improve land and water use efficiency and help address concerns about environmental impacts. We conclude that the high variability in pathways, uncertainties in technological development and ambiguity in political decision render forecasts on deployment levels and climate effects very difficult. However, uncertainty about projections should not preclude pursuing beneficial bioenergy options.

Modeling Corn Ethanol and Climate

New fuel regulations based on life cycle greenhouse gas (GHG) emissions have focused renewed attention on life cycle models of biofuels. The BESS model estimates 25% lower life cycle GHG emissions for corn ethanol than does the well-known GREET model, which raises questions about which model is more accurate. I develop a life cycle metamodel to compare the GREET and BESS models in detail and to explain why the results from these models diverge. I find two main reasons for the divergence: (1) BESS models a more efficient biorefinery than is modeled in the cases to which its results have been compared, and (2) in several instances BESS fails to properly count upstream emissions. Adjustments to BESS to account for these differences raise the estimated global warming intensity (not including land use change) of the corn ethanol pathway considered in that model from 45 to 61 g COe MJ1. Adjusting GREET to use BESSs biorefinery performance and coproduct credit assumptions reduces the GREET estimate from 64 to 61 g COe MJ1. Although this analysis explains the gap between the two models, both models would be improved with better data on corn production practices and by better treatment of agricultural inputs.

Do biofuel policies seek to cut emissions by cutting food

Major models should make trade-offs more transparent Debates about biofuels tend to focus separately on estimates of adverse effects on food security, poverty, and greenhouse gas (GHG) emissions driven by land-use change (LUC) (1–4). These estimates often rely on global agriculture and land-use models. Because models differ substantially in their estimates of each of these adverse effects (2, 3, 5), some argue that each individual effect is too uncertain to influence policy (6, 7). Yet these arguments fail to recognize the trade-offs; much of the uncertainty is only about which adverse effects predominate, not whether adverse effects occur at all. Our analysis of the three major models used to set government policies in the United States and Europe suggests that ethanol policies in effect are relying on decreases in food consumption to generate GHG savings (1).

The climate impacts of bioenergy systems depend on market and regulatory policy contexts.

Biomass can help reduce greenhouse gas (GHG) emissions by displacing petroleum in the transportation sector, by displacing fossil-based electricity, and by sequestering atmospheric carbon. Which use mitigates the most emissions depends on market and regulatory contexts outside the scope of attributional life cycle assessments. We show that bioelectricitys advantage over liquid biofuels depends on the GHG intensity of the electricity displaced. Bioelectricity that displaces coal-fired electricity could reduce GHG emissions, but bioelectricity that displaces wind electricity could increase GHG emissions. The electricity displaced depends upon existing infrastructure and policies affecting the electric grid. These findings demonstrate how model assumptions about whether the vehicle fleet and bioenergy use are fixed or free parameters constrain the policy questions an analysis can inform. Our bioenergy life cycle assessment can inform questions about a bioenergy mandates optimal allocation between liquid fuels and electricity generation, but questions about the optimal level of bioenergy use require analyses with different assumptions about fixed and free parameters.

Assessing the Climate Effects of Biofuels Using Integrated Assessment Models, Part I: Methodological Considerations

Summary Estimates of the climate-change mitigation benefits of biofuels are varied and controversial. Some analysts rely on attributional life cycle assessment (ALCA), limiting the analytic scope to the direct supply chain, whereas others supplement an ALCA result with an estimate of land-use change (LUC) emissions intensity. Other analysts have used consequential life cycle assessment (CLCA), with methods ranging from static market assessments to identify the likely marginal product and supplier, to running partial and general equilibrium models to estimate changes in global production and consumption. In this article, we consider another alternative—using an integrated assessment model (IAM) as a platform for CLCA of biofuels. In this article (part I of II), we focus on the methodological challenges of this approach. In part II, we present a case study using one IAM—the global change assessment model (GCAM)—to estimate the climate effects of several biofuels.

Response to “On the uncanny capabilities of consequential LCA” by Sangwon Suh and Yi Yang (Int J Life Cycle Assess, doi: 10.1007/s11367-014-0739-9)

To the editor: We thank our colleagues Sangwon Suh and Yi Yang for presenting an opportunity to clarify aspects of our recent paper Using Attributional Life Cycle Assessment to Estimate Climate-Change Mitigation Benefits Misleads Policy Makers, published in the Journal of Industrial Ecology (Plevin et al. 2013). We encourage readers to compare the claims made by Suh and Yang to what actually appeared in our article. We focus in this letter on what we see as the key problems with Suh and Yang’s commentary: they present straw-man arguments and do not address our actual claims about consequential LCA (CLCA) and attributional LCA (ALCA). Suh and Yang present straw-man arguments. The title of the article by Suh and Yang notwithstanding, we do not believe and in our paper did not imply that CLCA possesses uncanny abilities. Indeed, we presented important limitations of CLCA. For example, we wrote:

Indirect Land Use and Greenhouse Gas Impacts of Biofuels

Bioenergy crops produced on productive cropland can displace the production of food, feed, and fiber, increasing the price of the displaced commodities and inducing farmers elsewhere to plant replacement crops. This process is referred to as indirect land-use change (ILUC). If forests or grasslands are converted to crop production, enough CO 2 may be released from the disturbed soil and biomass to negate the climate benefits of displacing petroleum-based fuels with biofuels. Although estimates of ILUC emissions remain uncertain, ILUC can be reduced or possibly avoided by minimizing the competition between bioenergy feedstocks and agricultural commodities that are in high demand.