Preprint Article Version 1 This version is not peer-reviewed

Surveying the Solar Power Gap: Assessing the Spatial Distribution of Emerging Photovoltaic Solar Adoption in the State of Georgia, U.S.A.

Version 1 : Received: 5 October 2018 / Approved: 9 October 2018 / Online: 9 October 2018 (10:23:08 CEST)

A peer-reviewed article of this Preprint also exists.

Tidwell, J.H.; Tidwell, A.; Nelson, S. Surveying the Solar Power Gap: Assessing the Spatial Distribution of Emerging Photovoltaic Solar Adoption in the State of Georgia, U.S.A.. Sustainability 2018, 10, 4117. Tidwell, J.H.; Tidwell, A.; Nelson, S. Surveying the Solar Power Gap: Assessing the Spatial Distribution of Emerging Photovoltaic Solar Adoption in the State of Georgia, U.S.A.. Sustainability 2018, 10, 4117.

Journal reference: Sustainability 2018, 10, 4117
DOI: 10.3390/su10114117

Abstract

Despite a global push in the development and implementation of widespread alternative energy use, significant disparities exist across given nation-states. These disparities reflect both technical and economic factors, as well as the social, political, and ecological gaps between how communities see energy development and national/global policy goals. Known as the “local-national gap,” many nations struggle with fostering meaningful conversations about the role of alternative energy technologies within communities. Mitigation of this problem first requires understanding the distribution of existing alternative energy technologies at the local level of policymaking. Using the State of Georgia, U.S.A. as a case study, we present a model for analyzing how existing adoption trends enable/limit conversation at the scale of local governance (i.e., county governments). Leveraging existing work on the Gini Coefficient as a metric for measuring energy inequity, we argue these tools can be applied to analyze where gaps exist in ongoing solar adoption trends. As we demonstrate, communities that adopt solar tend to be concentrated in a few counties, indicating existing conversations are limited to a circumscribed set of social networks. This information and the model we demonstrate can enable focused qualitative analyses of existing solar trends, not only amongst high-adoption areas but within communities where little to no adoption has occurred.

Subject Areas

technology adoption; Lorenz curves; Gini coefficient; local-national gap; Georgia; NIMBY; solar energy; community development; soft cost reduction

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