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      Characterizing local rooftop solar adoption inequity in the US

      , , ,
      Environmental Research Letters
      IOP Publishing

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          Abstract

          Residential rooftop solar is slated to play a significant role in the changing US electric grid in the coming decades. However, concerns have emerged that the benefits of rooftop solar deployment are inequitably distributed across demographic groups. Previous work has highlighted inequity in national solar adopter deployment and income trends. We leverage a dataset of US solar adopter household income estimates—unique in its size and resolution—to analyze differences in adoption equity at the local level and identify those conditions that yield more equitable solar adoption, with implications for policy strategies to reduce inequities in solar adoption. The solar inequities observed at the national and state levels also exist at more granular levels, but not uniformly so; some US census tracts exhibit less solar inequity than others. Some demographic, solar system, and market characteristics robustly lead to more equitable solar adoption. Our findings suggest that while solar adoption inequity is frequently attributed to the relatively high costs of solar adoption, costs may become less relevant as solar prices decline. Results also indicate that racial diversity and education levels affect solar adoption patterns at a local level. Finally, we find that solar adoption is more equitable in census tracts served by specific types of installers. Future research and policy can explore ways to leverage these findings to accelerate the transition to equitable solar adoption.

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          Most cited references29

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          The justice and equity implications of the clean energy transition

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            Income Inequality and Income Segregation

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              Use of census-based aggregate variables to proxy for socioeconomic group: evidence from national samples.

              Increasingly, investigators append census-based socioeconomic characteristics of residential areas to individual records to address the problem of inadequate socioeconomic information on health data sets. Little empirical attention has been given to the validity of this approach. The authors estimate health outcome equations using samples from nationally representative data sets linked to census data. They investigate whether statistical power is sensitive to the timing of census data collection or to the level of aggregation of the census data; whether different census items are conceptually distinct; and whether the use of multiple aggregate measures in health outcome equations improves prediction compared with a single aggregate measure. The authors find little difference in estimates when using 1970 compared with 1980 US Bureau of the Census data or zip code compared with tract level variables. However, aggregate variables are highly multicollinear. Associations of health outcomes with aggregate measures are substantially weaker than with microlevel measures. The authors conclude that aggregate measures can not be interpreted as if they were microlevel variables nor should a specific aggregate measure be interpreted to represent the effects of what it is labeled.
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                Author and article information

                Journal
                Environmental Research Letters
                Environ. Res. Lett.
                IOP Publishing
                1748-9326
                February 25 2022
                March 01 2022
                February 25 2022
                March 01 2022
                : 17
                : 3
                : 034028
                Article
                10.1088/1748-9326/ac4fdc
                bac56a78-46b4-4ec6-8a5f-196a8d7866e9
                © 2022

                http://creativecommons.org/licenses/by/4.0

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