Average vs. Marginal Emissions
The scientific consensus is clear: marginal emissions rates are the appropriate metric to use for measuring the consequential impact of load shifting, siting new loads, and building new renewables.
The following papers from peer-reviewed journals, recommended best practices, and other examples dig into the science behind why marginal emissions rates are the proper metric to use for calculating impact, rather than average emissions rates.
"Multiple forms of marginal and average emission factors have been developed to estimate the carbon emissions of adding technologies, such as electric vehicles or solar panels, to the electricity grid. Different methods can produce very different results and conclusions, indicating that choosing between methods is not trivial. // We find that average emission factors have lower accuracy when estimating emissions from demand shifts and observe the same for demand-based marginal emission factors at an hourly resolution. In contrast, incremental and thermal marginal emission factors can reproduce the emission changes of a power grid model under many testing conditions and scenarios."
Alejandro G. N. Elenes et al. "How well do emission factors approximate emission changes from electricity system models?." Environmental Science & Technology. 2022. read more
"Average emissions factors may be a poor representation of the changes in emissions that arise from interventions in the power sector that would lead to small changes in electricity demand. Instead, marginal emission factors (MEF) are likely to provide a better representation. These MEFs estimate the change in emissions from marginal generation, i.e., the electricity generation that increases or decreases to meet a change in demand. These factors provide more accurate assessments especially when analysts or policymakers evaluate interventions that cause changes in electricity demand likely to vary seasonally or time-of-day, such as electric vehicles, air conditioning, or energy efficiency."
Shayak Sengupta et al. "Current and future estimates of marginal emission factors for Indian power generation." Environmental Science & Technology. 2022. read more
"When it comes to policies or behavioral changes that shift electricity demand and that affect new sources of clean generation, the effect on GHG emissions is highly dependent on the emission rates of the specific sources of generation that are displaced or ramped up in response. Existing research shows that marginal emission rates, in contrast to average emissions (i.e., carbon intensity), are critical for the evaluation of electricity-shifting climate policies in the United States."
Matthew Kotchen et al. "Why marginal CO2 emissions are not decreasing for US electricity: Estimates and implications for climate policy." PNAS. 2022. read more
"The consequential method looks at the actual additional or marginal impact that miners create by choosing to draw energy from a specific grid. It avoids arbitrarily sharing responsibility for all emissions among all grid users. It shows the macro impact that the electricity consumption has on the local grid. // For example, what if a miner decides to open a new mining pool on a grid with a lot of clean hydro power—to take advantage of that green electricity—but their added load causes a fossil-fueled peaking plant to ramp up in response? The attributional method would show them using lots of hydro power and a low emissions factor, but the consequential method will expose that their actions actually increased grid emissions overall. // For the consequential method, miners should use marginal emission factors, which are generally more accurate than average emission factors."
Marc Johnson and Sahithi Pingali. "Guidance for accounting and reporting electricity use and carbon emissions from cryptocurrency." Crypto Climate Accord. 2021. read more
"Marginal Emission Rate provides a mathematically sound and transparent way to quantify the carbon footprint of electricity consumption and production. Mathematically, the MER calculation is similar to the calculation of Locational Marginal Prices (LMP) and system lambda, which are used for economic dispatch of power systems across North America. // The marginal emission rate (MER) measures the change in systemwide emissions in response to a marginal increase or decrease in demand at a given location. // The amount of carbon displaced by renewable energy is directly related to the emission rate of the marginal generators, measured as the MER at the renewable’s interconnection node. The average grid emission rate (AER), which is often calculated as total system emissions divided by total generation, does not accurately reflect what is happening at the margin. By its mathematical definition, AER does not measure how incremental renewable energy affects the total carbon emissions of the system, making it difficult to impossible to accurately quantify the true carbon reduction impact of renewable generation."
Hua He et al. "Using marginal emission rates to optimize investment in carbon dioxide displacement technologies." The Electricity Journal. 2021. read more
"Previous work on reducing carbon emissions through load shifting has assumed that prices are directly tied to the fraction of non-renewable energy, or considered average carbon emissions for electricity in a region and/or renewable energy curtailment. A benefit to these metrics is that several companies provide information about the average carbon intensity of electricity or total renewable energy curtailment, which makes the metrics easier to compute. However, these metrics fail to consider important aspects of electric grid operation, such as the impact of a marginal increase or decrease in load or transmission capacity. // ...we propose a new and improved metric to guide geographic load shifting, which we refer to as the locational marginal carbon emission. (a metric that more accurately represents the carbon emissions associated with electricity usage at different locations in the grid)"
Julia Lindberg et al. "A guide to reducing carbon emissions through data center geographical load shifting." Association for Computing Machinery. 2021. read more
"Increasing (or decreasing) demand at a given time affects the operation of only the marginal units in the dispatch order, and not the infra-marginal units. Therefore, emission implications of energy storage, or any other incremental demand- or supply-side resource that leads to load-shifting, depend on marginal operating emission rates, based on the emission intensity of the marginal units, and not the average operating emission rates, based on the average emission intensity of the entire grid."
Jeffrey Shrader et al. "(Not so) clean peak energy standards." SSRN: Social Science Research Network. 2020. read more
"We propose using marginal emission factors instead of average emission factors for determining the impact of adding variable renewable electricity to the generation mix. Average emission factors assume constant emissions over time, which does not reflect reality. Therefore, they cannot be used for e.g. accurately determining the mitigated CO2 emissions by renewables, or for scheduling shiftable loads in order to have the lowest CO2 emissions."
Wouter Schram et al. "On the use of average versus marginal emission factors." Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems. 2019. read more
"The potential of an electricity generation system to reduce emissions has been measured by both marginal emission factors (MEFs) and average emission factors (AEFs). However, the use of AEFs, which reflect grid-average situations, to estimate the effect of an intervention may be problematic, because not all generating technologies would respond to changes in demand proportionally. In studying the electricity generation in the United States, for example, Siler-Evans et al. found that AEFs could significantly misestimate the amount of emissions avoided by an intervention. By contrast, MEFs estimate the emission intensity of marginal power generation that responds to a change in demand, and are a more appropriate metric to assess emission implications of policy and technology interventions, such as electric vehicle tax credits and energy storage, among others."
Timothy Smith et al. "Marginal emission factors considering renewables: a case study of the U.S. Midcontinent Independent System Operator (MISO) System." Environmental Science & Technology. 2017. read more
"Unlike previous optimization approaches, our method considers the marginal GHG emissions caused by load migrations inside the electric grid instead of only considering the average emissions of the electric grid's prior load migrations. Results show that load migrations make it possible to minimize marginal GHG emissions of the cloud computing service. Comparison with the usual approach using average emission factors reveals its inability to truly minimize GHG emissions of distributed data centres."
Thomas Dandres et al. "Consideration of marginal electricity in real-time minimization of distributed data centre emissions." Journal of Cleaner Production. 2016. read more
"When a modeler uses average EF they are effectively assuming that the load has distributed burden on all power plants operating. Marginal emissions factors are used to describe the emissions associated with the generators whose outputs will change as a result of changes to load. // A key decision when selecting the appropriate method for calculating grid emissions is whether to use a marginal factor or an average factor. These factors truly answer two separate research questions. // If the load under analysis represents an incremental increase or decrease, marginal EFs can provide an emissions measurement specific to the change. Thus, for consequential LCAs of new loads, marginal factors are recommended and for attributional LCAs of existing loads an average factor is recommended."
Nicole A. Ryan, Jeremiah X. Johnson, and Gregory A. Keoleian. "Comparative assessment of models and methods to calculate grid electricity emissions." Environmental Science & Technology. 2016. read more
"These [marginal emissions] estimates have important implications for understanding the environmental consequences of many electricity-shifting policies. If, for example, the expansion of electricity generated from renewables displaces existing generation sources, the estimates of marginal emissions can be used to quantify the avoided pollution and how it differs by location and time of day. Similarly, to the extent that policies for energy efficiency, smart grids, and more stringent building codes reduce demand for electricity, estimates of the marginal emissions will help to understand the impacts and quantify the heterogeneous effects of uniform policies. The [marginal emissions] estimates are also relevant for understanding the impacts of activities and policies that increase electricity demand, as with PEVs [plug-in electric vehicles], the application upon which we focus."
Joshua S. Graff Zivin, Matthew Kotchen, and Erin T. Mansur. "Spatial and Temporal Heterogeneity of Marginal Emissions: Implications for Electric Cars and Other Electricity-Shifting Policies." Journal of Economic Behavior & Organization. 2014. read more
"Both supply- and demand-side interventions will displace energy and emissions from conventional generators. Marginal emissions factors (MEFs) give a consistent metric for assessing the avoided emissions resulting from such interventions. // We compare marginal and average emissions factors (AEFs), finding that AEFs may grossly misestimate the avoided emissions resulting from an intervention. We find significant regional differences in the emissions benefits of avoiding one megawatt-hour of electricity.
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Kyle Siler-Evans, Ines Lima Azevedo, and M. Granger Morgan. "Marginal Emissions Factors for the U.S. Electricity System." Environmental Science and Technology. 2012. read more
"The impact of an intervention is often assessed against the CO2 content of either grid-average electricity or a speculative marginal emissions rate. However, a change in demand does not act upon all elements of the electricity system proportionally and as such a system-average emissions factor (AEF) could be misleading, as could a poorly chosen marginal rate. In reality, specific generators respond to system demand changes, and it is the CO2 intensity of these generators that dictates the actual CO2 reduction brought about.The metric that estimates the CO2 intensity of a demand change is called the marginal emissions factor (MEF), and it is a function of specific CO2 intensity of the individual generators that respond to that change."
A.D. Hawkes. "Estimating marginal CO2 emissions rates for national electricity systems." Energy Policy. 2010. read more