Scaling solar photocatalytic hydrogen production in China: Integrated geospatial-meteorological analysis

Yinan Li, Lanyu Li, Hongkuan Yuan, Keji He, Hong Chen, Jianping Xie, Biao Wang and Xiaonan Wang

Applied Energy, 2025, vol. 381, issue C, No S0306261924025637

Abstract: Solar photocatalytic hydrogen production is considered a promising technology owing to its sustainable nature, while facing the challenges of improving and maintaining photocatalytic efficiency under prolonged variable weather conditions. Herein, we screen out the MoTe2/ZrS2 system with a theoretical solar-to‑hydrogen conversion efficiency of 10.37 %. To improve the actual efficiency among all 97,711 grid cells in China, we propose an original meteorological data-driven machine learning model to optimize photocatalytic H2 production and results show that the annual average STH efficiency gives a mean of 3.16 % within a range of 0.44 % – 4.91 %. Incorporating geospatial data, we determine that China's photocatalytic H2 potential is about 216.65 Mt./year, which has been improved by almost sixfold compared to that without optimization, and the country's 2060 hydrogen demand can be met by using 11.08 % of its total land area. Compared with photovoltaic electrolysis, a photocatalyst cost of 23 USD/m2cat/103h would make photocatalysis economically competitive. Last, considering hydrogen production fluctuations, we explore optimal operation of hydrogen storage and utilization facilities to fulfil downstream demands.

Keywords: Solar photocatalytic hydrogen production; Geospatial-meteorological analysis; Machine learning enhanced optimization; Techno-economic benchmark; Photocatalysis temporal variability (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2024.125179

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