Assessing the potential impact of aerosol scenarios for rooftop PV regional deployment

Bingchun Liu, Shunfan Zhao, Shize Zheng, Fukai Zhang, Zefeng Li, Xu Gao and Ying Wang

Renewable Energy, 2025, vol. 246, issue C

Abstract: The deployment of rooftop photovoltaics (PV) is crucial for achieving net-zero emissions in urban areas, yet its efficiency can be influenced by aerosols. Traditional analyses of rooftop PV potential often concentrate on building models, neglecting the spatial and temporal variations in solar irradiance. Moreover, there are research gaps in studies on the assessment of aerosol changes on rooftop PV potential. In this study, we propose a solar irradiance prediction model based on the Gray correlation analysis-Bidirectional Long Short-Term Memory algorithm, which accurately assesses the potential of urban rooftop PV under different aerosol scenarios. Our experimental results show that this model outperforms existing alternatives. As aerosol concentration decreases, solar irradiance in Shaanxi Province increases, with a maximum potential for power generation reaching 142.11 TWh/year and a reduction in carbon emissions of 113 million tons by 2030. The annual loss in rooftop PV power generation due to aerosol pollution can range from 0.40 to 3.47 TWh. We conclude that aerosols reduce the efficiency of PV conversion and power generation. Based on dimensions of power generation, economic efficiency, and carbon reduction potential, we provide policy recommendations for deploying rooftop photovoltaics in different cities in Shaanxi Province.

Keywords: Aerosol pollution; Photovoltaic capacity factor; Rooftop PV; RCPs; Deep learning (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:246:y:2025:i:c:s0960148125005312

DOI: 10.1016/j.renene.2025.122869

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