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Solar energy resource availability under extreme and historical wildfire smoke conditions

Author

Listed:
  • Kimberley A. Corwin

    (Colorado State University)

  • Jesse Burkhardt

    (Colorado State University)

  • Chelsea A. Corr

    (Springfield College)

  • Paul W. Stackhouse

    (NASA Langley Research Center)

  • Amit Munshi

    (Colorado State University)

  • Emily V. Fischer

    (Colorado State University)

Abstract

By 2050, the U.S. plans to increase solar energy from 3% to 45% of the nation’s electricity generation. Quantifying wildfire smoke’s impact on solar photovoltaic (PV) generation is essential to meet this goal, especially given previous studies documenting sizable PV output losses due to smoke. We quantify smoke-driven changes in baseline solar resource availability [i.e., amount of direct normal (DNI) and global horizontal (GHI) irradiance] at different spatial and temporal scales using radiative transfer model output and satellite-based smoke, aerosol, and cloud observations. We show that irradiance decreases as smoke frequency increases at the state, regional, and national scale. DNI is more sensitive to smoke with sizable losses persisting downwind of fires. Large reductions in GHI–the main PV resource–are possible close to fires, but mean GHI declines minimally (

Suggested Citation

  • Kimberley A. Corwin & Jesse Burkhardt & Chelsea A. Corr & Paul W. Stackhouse & Amit Munshi & Emily V. Fischer, 2025. "Solar energy resource availability under extreme and historical wildfire smoke conditions," Nature Communications, Nature, vol. 16(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-024-54163-8
    DOI: 10.1038/s41467-024-54163-8
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    References listed on IDEAS

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    2. Sarver, Travis & Al-Qaraghuli, Ali & Kazmerski, Lawrence L., 2013. "A comprehensive review of the impact of dust on the use of solar energy: History, investigations, results, literature, and mitigation approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 698-733.
    3. Barbieri, Florian & Rajakaruna, Sumedha & Ghosh, Arindam, 2017. "Very short-term photovoltaic power forecasting with cloud modeling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 242-263.
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