Decision Support Algorithm for Evaluating Carbon Dioxide Emissions from Electricity Generation in the United States

13 Pages Posted: 19 Oct 2018

See all articles by Nicole A. Ryan

Nicole A. Ryan

University of Michigan at Ann Arbor

Jeremiah X. Johnson

University of Michigan at Ann Arbor - School of Natural Resources & Environment

Gregory A. Keoleian

University of Michigan at Ann Arbor

Geoffrey M. Lewis

University of Michigan at Ann Arbor

Date Written: December 2018

Abstract

This article presents an algorithm to aid practitioners in determining the most appropriate method to estimate carbon dioxide emissions from an electricity load. Applications include sustainability assessments of products, processes, energy efficiency improvements, changes in generation infrastructure, and changes in electricity demand. Currently, there is no consensus on appropriate methods for calculating greenhouse gas emissions resulting from specific electricity loads. Previous research revealed significant differences in emissions when different methods were used, a situation that could result in divergent sustainability or policy recommendations. In this article, we illustrate the distribution of emissions estimates based on method characteristics such as region size, temporal resolution, average or marginal approaches, and time scales. Informed by these findings, a decision support algorithm is presented that uses a load's key features and an analyst's research question to provide recommendations on appropriate method types. We defined four different cases to demonstrate the utility of the algorithm and to illustrate the variability of methods used in previous studies. Prior research often employed simplifying assumptions, which, in some cases, can result in electricity being allocated to the incorrect generating resources and improper calculation of emissions. This algorithm could reduce inappropriate allocation, variability in assumptions, and increase appropriateness of electricity emissions estimates.

Keywords: electricity generation, electric utility, emissions factor, greenhouse gas (GHG) emissions, industrial ecology marginal emissions

Suggested Citation

Ryan, Nicole A. and Johnson, Jeremiah X. and Keoleian, Gregory A. and Lewis, Geoffrey M., Decision Support Algorithm for Evaluating Carbon Dioxide Emissions from Electricity Generation in the United States (December 2018). Journal of Industrial Ecology, Vol. 22, Issue 6, pp. 1318-1330, 2018, Available at SSRN: https://ssrn.com/abstract=3269455 or http://dx.doi.org/10.1111/jiec.12708

Nicole A. Ryan

University of Michigan at Ann Arbor

500 S. State Street
Ann Arbor, MI 48109
United States

Jeremiah X. Johnson

University of Michigan at Ann Arbor - School of Natural Resources & Environment ( email )

440 Church St.
Ann Arbor, MI 48109
United States

Gregory A. Keoleian

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Geoffrey M. Lewis (Contact Author)

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

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