Worldwide rooftop photovoltaic electricity generation may mitigate global warming

Rooftop photovoltaic (RPV) is often understood as a niche contribution to climate change mitigation. However, the global potential of RPVs to mitigate global warming is unknown. Here we map the global rooftop area at 1-km resolution, quantifying 286,393 km2 of rooftops worldwide through geospatial data mining and artificial intelligence techniques. Using nine advanced Earth system models from the coupled model intercomparison project phase 6, we reveal that RPVs could substantially contribute to reducing global temperatures by 0.05–0.13 °C before 2050. Region-specific analysis underscores the variability in RPV potential and the necessity of tailored approaches to optimize RPV deployment, considering local solar resources, existing infrastructure and grid carbon intensity. Our findings reveal that leveraging RPV systems offers a viable and impactful strategy for reducing carbon footprints and combating climate change globally, while advocating targeted interventions to enhance the benefits of RPVs, particularly in areas with high solar radiation or rapid urbanization. Rooftop photovoltaic systems are often seen as a niche solution for mitigation but could offer large-scale opportunities. Using multi-source geospatial data and artificial intelligence techniques, the authors map their potential for reducing global temperatures and analyse regional differences.

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Publication Details

Journal
Nature Climate Change
Published
2025-03-07
DOI
https://doi.org/10.1038/s41558-025-02276-3
Citations
56
Primary Topic
Energy and Environment Impacts
Type
article
Field-Weighted Citation Impact
28.21

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article

Worldwide rooftop photovoltaic electricity generation may mitigate global warming

Hui Yang, Jian Lin, Zhiwei Xie, Wenjia Cai et al.
56 citations
Nature Climate Change
Energy and Environment Impacts
28.21
article

Worldwide rooftop photovoltaic electricity generation may mitigate global warming

Hui Yang, Jian Lin, Zhiwei Xie, Wenjia Cai, Hongjun Su, Jinyue Yan, Paolo Santi, Xufeng Cui, Wenjun Tang, Jiachuan Yang, Laibao Liu, Guonian Lü, Teng Zhong, Yingxia Pu, Min Chen, Deer Liu, Liang Ning, Yan Pu, Wei Xie, Felix Creutzig, Zhen Qian, Lixin Tian, Rui Zhu, Kai Zhang, Fei Li, Fan Zhang, Zhixin Zhang, Tianyu Sheng, Mingyue Lu
article en
56 citations

Abstract

Rooftop photovoltaic (RPV) is often understood as a niche contribution to climate change mitigation. However, the global potential of RPVs to mitigate global warming is unknown. Here we map the global rooftop area at 1-km resolution, quantifying 286,393 km2 of rooftops worldwide through geospatial data mining and artificial intelligence techniques. Using nine advanced Earth system models from the coupled model intercomparison project phase 6, we reveal that RPVs could substantially contribute to reducing global temperatures by 0.05–0.13 °C before 2050. Region-specific analysis underscores the variability in RPV potential and the necessity of tailored approaches to optimize RPV deployment, considering local solar resources, existing infrastructure and grid carbon intensity. Our findings reveal that leveraging RPV systems offers a viable and impactful strategy for reducing carbon footprints and combating climate change globally, while advocating targeted interventions to enhance the benefits of RPVs, particularly in areas with high solar radiation or rapid urbanization. Rooftop photovoltaic systems are often seen as a niche solution for mitigation but could offer large-scale opportunities. Using multi-source geospatial data and artificial intelligence techniques, the authors map their potential for reducing global temperatures and analyse regional differences.

Nature Climate ChangeVol. 15(4)
Agency for Science, Technology and Research (SG), Jiangsu University (CN), Hong Kong Polytechnic University (HK), Nanjing Normal University (CN), Zhongnan University of Economics and Law (CN), University of Sussex (GB), Hohai University (CN), Chinese Academy of Sciences (CN), Hong Kong University of Science and Technology (HK), Nanjing University of Information Science and Technology (CN), Peking University (CN), China University of Mining and Technology (CN), Institute of High Performance Computing (SG), Beijing Institute of Big Data Research (CN), Institute of Informatics and Telematics (IT), Institute of Tibetan Plateau Research (CN), Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (CN), Institute of Atmospheric Physics (CN), Jiangxi University of Science and Technology (CN), Potsdam Institute for Climate Impact Research (DE), Technical University of Munich (DE), Massachusetts Institute of Technology (US), Mälardalen University (SE), Shenyang Jianzhu University (CN), Nanjing University (CN), University of Hong Kong (HK), Tsinghua University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 0%
Energy and Environment Impacts
28.21
DOIOpen Access PDFOpenAlex
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