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Air pollution control strategies directly limiting national health damages in the US

Author

Listed:
  • Yang Ou

    (University of North Carolina at Chapel Hill
    ORISE Participant at the U.S. Environmental Protection Agency
    Joint Global Change Research Institute, Pacific Northwest National Laboratory)

  • J. Jason West

    (University of North Carolina at Chapel Hill)

  • Steven J. Smith

    (Joint Global Change Research Institute, Pacific Northwest National Laboratory)

  • Christopher G. Nolte

    (Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency)

  • Daniel H. Loughlin

    (Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency)

Abstract

Exposure to fine particulate matter (PM2.5) from fuel combustion significantly contributes to global and US mortality. Traditional control strategies typically reduce emissions for specific air pollutants and sectors to maintain pollutant concentrations below standards. Here we directly set national PM2.5 mortality cost reduction targets within a global human-earth system model with US state-level energy systems, in scenarios to 2050, to identify endogenously the control actions, sectors, and locations that most cost-effectively reduce PM2.5 mortality. We show that substantial health benefits can be cost-effectively achieved by electrifying sources with high primary PM2.5 emission intensities, including industrial coal, building biomass, and industrial liquids. More stringent PM2.5 reduction targets expedite the phaseout of high emission intensity sources, leading to larger declines in major pollutant emissions, but very limited co-benefits in reducing CO2 emissions. Control strategies limiting health damages achieve the greatest emission reductions in the East North Central and Middle Atlantic states.

Suggested Citation

  • Yang Ou & J. Jason West & Steven J. Smith & Christopher G. Nolte & Daniel H. Loughlin, 2020. "Air pollution control strategies directly limiting national health damages in the US," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14783-2
    DOI: 10.1038/s41467-020-14783-2
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    Cited by:

    1. He, Sha & Tang, Sanyi & Zhang, Qimin & Rong, Libin & Cheke, Robert A., 2023. "Modelling optimal control of air pollution to reduce respiratory diseases," Applied Mathematics and Computation, Elsevier, vol. 458(C).
    2. Mario Coccia, 2020. "How ( Un )sustainable Environments Are Related to the Diffusion of COVID-19: The Relation between Coronavirus Disease 2019, Air Pollution, Wind Resource and Energy," Sustainability, MDPI, vol. 12(22), pages 1-12, November.
    3. Shirin Kahremany & Lukas Hofmann & Noy Eretz-Kdosha & Eldad Silberstein & Arie Gruzman & Guy Cohen, 2021. "SH-29 and SK-119 Attenuates Air-Pollution Induced Damage by Activating Nrf2 in HaCaT Cells," IJERPH, MDPI, vol. 18(23), pages 1-16, November.
    4. Minyoung Roh & Seungho Jeon & Soontae Kim & Sha Yu & Almas Heshmati & Suduk Kim, 2020. "Modeling Air Pollutant Emissions in the Provincial Level Road Transportation Sector in Korea: A Case Study of the Zero-Emission Vehicle Subsidy," Energies, MDPI, vol. 13(15), pages 1-22, August.
    5. Monika Ziemska-Osuch, 2024. "Analysis of the Relationship between Fuel Prices and Vehicle Numbers in Urban Road Networks," Energies, MDPI, vol. 17(12), pages 1-10, June.
    6. Xialing Sun & Rui Zhang & Geyi Wang, 2022. "Spatial-Temporal Evolution of Health Impact and Economic Loss upon Exposure to PM 2.5 in China," IJERPH, MDPI, vol. 19(4), pages 1-17, February.

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