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Evolution of the United States Energy System and Related Emissions under Varying Social and Technological Development Paradigms: Plausible Scenarios for Use in Robust Decision Making

  • Kristen E. Brown
    Kristen E. Brown
    U.S. Environmental Protection Agency, Office of Research and Development, 109 TW Alexander Drive, Research Triangle Park, North Carolina 27711, United States
  • Troy A. Hottle
    Troy A. Hottle
    Eastern Research Group, Inc., 110 Hartwell Avenue, Lexington, Massachusetts 02421, United States
    Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, North Carolina 27711, United States
  • Rubenka Bandyopadhyay
    Rubenka Bandyopadhyay
    North Carolina Advanced Energy Corporation, 909 Capability Drive, Suite 2100, Raleigh, North Carolina 27606, United States
    Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, North Carolina 27711, United States
  • Samaneh Babaee
    Samaneh Babaee
    Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, North Carolina 27711, United States
  • Rebecca S. Dodder
    Rebecca S. Dodder
    U.S. Environmental Protection Agency, Office of Research and Development, 109 TW Alexander Drive, Research Triangle Park, North Carolina 27711, United States
  • P. Ozge Kaplan
    P. Ozge Kaplan
    U.S. Environmental Protection Agency, Office of Research and Development, 109 TW Alexander Drive, Research Triangle Park, North Carolina 27711, United States
  • Carol S. Lenox
    Carol S. Lenox
    U.S. Environmental Protection Agency, Office of Research and Development, 109 TW Alexander Drive, Research Triangle Park, North Carolina 27711, United States
  • , and 
  • Daniel H. Loughlin*
    Daniel H. Loughlin
    U.S. Environmental Protection Agency, Office of Research and Development, 109 TW Alexander Drive, Research Triangle Park, North Carolina 27711, United States
    *Phone 919-541-3928; e-mail: [email protected]; fax 919-541-7885.
Cite this: Environ. Sci. Technol. 2018, 52, 14, 8027–8038
Publication Date (Web):June 21, 2018
https://doi.org/10.1021/acs.est.8b00575
Copyright © 2018 American Chemical Society

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    Abstract

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    The energy system is the primary source of air pollution. Thus, evolution of the energy system into the future will affect society’s ability to maintain air quality. Anticipating this evolution is difficult because of inherent uncertainty in predicting future energy demand, fuel use, and technology adoption. We apply scenario planning to address this uncertainty, developing four very different visions of the future. Stakeholder engagement suggested that technological progress and social attitudes toward the environment are critical and uncertain factors for determining future emissions. Combining transformative and static assumptions about these factors yields a matrix of four scenarios that encompass a wide range of outcomes. We implement these scenarios in the U.S. Environmental Protection Agency MARKet ALlocation (MARKAL) model. Results suggest that both shifting attitudes and technology transformation may lead to emission reductions relative to the present, even without additional policies. Emission caps, such as the Cross-State Air-Pollution Rule, are most effective at protecting against future emission increases. An important outcome of this work is the scenario-implementation approach, which uses technology-specific discount rates to encourage scenario-specific technology and fuel choices. End-use energy demands are modified to approximate societal changes. This implementation allows the model to respond to perturbations in manners consistent with each scenario.

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    The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.8b00575.

    • Additional details, tables, and figures on the process flowchart, hurdle rate description and calculation, and additional results. (PDF)

    • A table showing damages associated with NOx, SO2, and PM2.5 for each energy sector in each case for each year and a table with the hurdle rate for each technology and scenario. (XLSX)

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    2. Jidong Kang, Tsan Sheng Ng, Bin Su, Rong Yuan. Optimizing the Chinese Electricity Mix for CO2 Emission Reduction: An Input–Output Linear Programming Model with Endogenous Capital. Environmental Science & Technology 2020, 54 (2) , 697-706. https://doi.org/10.1021/acs.est.9b05199
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