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  Decay radius of climate decision for solar panels in the city of Fresno, USA

Barton-Henry, K., Wenz, L., Levermann, A. (2021): Decay radius of climate decision for solar panels in the city of Fresno, USA. - Scientific Reports, 11, 8571.
https://doi.org/10.1038/s41598-021-87714-w

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 Urheber:
Barton-Henry, Kelsey1, Autor              
Wenz, Leonie1, Autor              
Levermann, Anders1, Autor              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: To design incentives towards achieving climate mitigation targets, it is important to understand the mechanisms that affect individual climate decisions such as solar panel installation. It has been shown that peer effects are important in determining the uptake and spread of household photovoltaic installations. Due to coarse geographical data, it remains unclear whether this effect is generated through geographical proximity or within groups exhibiting similar characteristics. Here we show that geographical proximity is the most important predictor of solar panel implementation, and that peer effects diminish with distance. Using satellite imagery, we build a unique geo-located dataset for the city of Fresno to specify the importance of small distances. Employing machine learning techniques, we find the density of solar panels within the shortest measured radius of an address is the most important factor in determining the likelihood of that address having a solar panel. The importance of geographical proximity decreases with distance following an exponential curve with a decay radius of 210 meters. The dependence is slightly more pronounced in low-income groups. These findings support the model of distance-related social diffusion, and suggest priority should be given to seeding panels in areas where few exist.

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Sprache(n): eng - Englisch
 Datum: 2021-04-012021-04-212021
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: PIKDOMAIN: RD4 - Complexity Science
DOI: 10.1038/s41598-021-87714-w
Working Group: Data-based analysis of climate decisions
Research topic keyword: Energy
Research topic keyword: Mitigation
Research topic keyword: Sustainable Development
Regional keyword: North America
Model / method: Machine Learning
Model / method: Nonlinear Data Analysis
Model / method: Quantitative Methods
MDB-ID: pending
OATYPE: Gold - DEAL Springer Nature
 Art des Abschluß: -

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Projektname : ImpactEE
Grant ID : Az.: 93350
Förderprogramm : -
Förderorganisation : Volkswagenstiftung VW foundation

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Titel: Scientific Reports
Genre der Quelle: Zeitschrift, SCI, Scopus, p3, OA
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Seiten: - Band / Heft: 11 Artikelnummer: 8571 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals2_395
Publisher: Springer Nature