4.8 Article

Marginal Emissions Factors for Electricity Generation in the Midcontinent ISO

Journal

ENVIRONMENTAL SCIENCE & TECHNOLOGY
Volume 51, Issue 24, Pages 14445-14452

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.est.7b03047

Keywords

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Funding

  1. U.S. Environmental Protection Agency [RD83587301]
  2. Initiative for Renewable Energy & the Environment (IREE) Grant at the University of Minnesota [RL-0011-13]
  3. Center for Climate and Energy Decision Making (CEDM) [SES-0949710, SES-1463492]
  4. Divn Of Social and Economic Sciences
  5. Direct For Social, Behav & Economic Scie [1463492] Funding Source: National Science Foundation

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Environmental consequences of electricity generation are often determined using average emission factors. However, as different interventions are incrementally pursued in electricity systems, the resulting marginal change in emissions may differ from what one would predict based on system-average conditions. Here, we estimate average emission factors and marginal emission factors for CO2, SO2, and NOx from fossil and nonfossil generators in the Midcontinent Independent System Operator (MISO) region during years 2007-2016. We analyze multiple spatial scales (all MISO; each of the 11 MISO states; each utility; each. generator) and use MISO data to characterize differences between the two emission factors (average; marginal). We also explore temporal trends in emissions factors by hour, day; month, and year, as well as the differences that arise from including only fossil generators versus total generation. We find, for example, that Marginal emission factors are generally higher during late-night and early morning compared to afternoons. Overall, in MISO, average emission factors are generally higher than marginal estimates (typical difference: similar to 20%). This means that the true environmental benefit of an energy efficiency program may be similar to 20% smaller than anticipated if one were to use average emissions factors. Our analysis can usefully be extended to other regions to support effective near-term technical, policy and investment decisions based on marginal rather than only average emission factors.

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