Analysis | Published:

Disparities in rooftop photovoltaics deployment in the United States by race and ethnicity

Nature Sustainabilityvolume 2pages7176 (2019) | Download Citation

Abstract

The rooftop solar industry in the United States has experienced dramatic growth—roughly 50% per year since 2012, along with steadily falling prices. Although the opportunities this affords for clean, reliable power are transformative, the benefits might not accrue to all individuals and communities. Combining the location of existing and potential sites for rooftop photovoltaics (PV) from Google’s Project Sunroof and demographic information from the American Community Survey, the relative adoption of rooftop PV is compared across census tracts grouped by racial and ethnic majority. Black- and Hispanic-majority census tracts show on average significantly less rooftop PV installed. This disparity is often attributed to racial and ethnic differences in household income and home ownership. In this study, significant racial disparity remains even after we account for these differences. For the same median household income, black- and Hispanic-majority census tracts have installed less rooftop PV compared with no majority tracts by 69 and 30%, respectively, while white-majority census tracts have installed 21% more. When correcting for home ownership, black- and Hispanic-majority census tracts have installed less rooftop PV compared with no majority tracts by 61 and 45%, respectively, while white-majority census tracts have installed 37% more. The social dispersion effect is also considered. This Analysis reveals the racial and ethnic injustice in rooftop solar participation.

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Data availability

The data that support the findings of this study are available from Google Project Sunroof (https://www.google.com/get/sunroof/data-explorer/) and the 2009–2013 5-year ACS27. The computer codes used for this study are available online at https://github.com/DeborahSunter/Rooftop-PV-Deployment-Disparities.

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Acknowledgements

The authors thank Google’s Project Sunroof team for providing valuable data, and S. Hsiang for insightful discussions. D.A.S. gratefully acknowledges support from the Energy Efficiency and Renewable Energy Postdoctoral Research Award from the US Department of Energy and Berkeley Institute for Data Science. S.C. gratefully acknowledges support from the Berkeley Energy and Climate Institute–Instituto Tecnológico de Estudios Superiores de Monterrey Energy Fellowship. D.M.K. acknowledges support from the Karsten Family Foundation and Zaffaroni Family Foundation.

Author information

Affiliations

  1. Department of Mechanical Engineering, Tufts University, Medford, MA, USA

    • Deborah A. Sunter
  2. Berkeley Institute for Data Science, University of California, Berkeley, CA, USA

    • Deborah A. Sunter
  3. Energy and Resources Group, University of California, Berkeley, CA, USA

    • Deborah A. Sunter
    • , Sergio Castellanos
    •  & Daniel M. Kammen
  4. Renewable and Appropriate Energy Laboratory, University of California, Berkeley, CA, USA

    • Deborah A. Sunter
    • , Sergio Castellanos
    •  & Daniel M. Kammen
  5. California Institute for Energy and Environment, University of California, Berkeley, CA, USA

    • Sergio Castellanos
  6. Escuela de Gobierno y Transformación Pública, Instituto Tecnológico y de Estudios Superiores de Monterrey, San Pedro Garza García, Mexico

    • Sergio Castellanos
  7. Goldman School of Public Policy, University of California, Berkeley, CA, USA

    • Daniel M. Kammen

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Contributions

D.A.S. and S.C. designed and performed the research, analysed the data and wrote the paper. D.M.K. supervised the research, guided the study and edited the paper.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to Deborah A. Sunter or Sergio Castellanos.

Supplementary information

  1. Supplementary Information

    Supplementary Figures 1–5, Supplementary Tables 1–3.

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https://doi.org/10.1038/s41893-018-0204-z