Articles | Volume 16, issue 10
https://doi.org/10.5194/essd-16-4655-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-4655-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A 10 km daily-level ultraviolet-radiation-predicting dataset based on machine learning models in China from 2005 to 2020
Yichen Jiang
School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China
Su Shi
School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China
Xinyue Li
School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China
Chang Xu
School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China
Haidong Kan
School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China
Shanghai Key Laboratory of Meteorology and Health, IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai, China
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China
Shanghai Key Laboratory of Meteorology and Health, IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai, China
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Cited
11 citations as recorded by crossref.
- Reconstructing hourly downward surface solar radiation, ultraviolet radiation, and photosynthetically active radiation using a transformer-based deep learning model in China J. Zhang et al. https://doi.org/10.1016/j.atmosres.2026.108862
- Window-specific effects of ultraviolet radiation and air pollution on ovarian reserve in infertile women: A retrospective cohort study Q. Tang et al. https://doi.org/10.1016/j.envpol.2026.128740
- Decoding urban humid heat: temporal attribution of wet-bulb temperature drivers in the Lanzhou–Xining corridor X. Wang et al. https://doi.org/10.3389/feart.2026.1860008
- Increasing residential greenness attenuates the hazard of ultraviolet radiation on age-related macular degeneration in the elderly: A nationwide study in China Y. Qu et al. https://doi.org/10.1016/j.ecoenv.2025.117924
- First high-resolution surface spectral clear-sky ultraviolet radiation dataset across China (1981–2023): development, validation, and variability Q. Qi et al. https://doi.org/10.5194/essd-17-7271-2025
- Associations of personal solar UV exposure with gut microbiota diversity and BMI among preschool children in China J. Liang et al. https://doi.org/10.1515/jpem-2025-0631
- Surface Ozone-Induced Yield Losses and Economic Costs of Winter Wheat Across China: Spatiotemporal Estimates Based on Reconstructed M7 and AOT40 Exposures (2015–2022) H. Zheng et al. https://doi.org/10.3390/agronomy16171671
- Rooting depth projections of global plant functional types and driving factors analysis based on a hybrid modeling framework Q. Han et al. https://doi.org/10.1016/j.ecolind.2025.113674
- Global uncertainty of various downward shortwave solar radiation products W. Xu et al. https://doi.org/10.1016/j.energy.2026.140282
- Deep Learning-Based Forecasting of Ultraviolet Radiation Intensity in Lima, Peru: Implications for Climate Resilience and Public Health J. Ventocilla et al. https://doi.org/10.3390/a19070522
- Photochemical mineralization of sedimentary organic matter potentially contributes to internal nutrient loadings in lakes of northwestern China X. Yao et al. https://doi.org/10.1016/j.envpol.2025.126743
11 citations as recorded by crossref.
- Reconstructing hourly downward surface solar radiation, ultraviolet radiation, and photosynthetically active radiation using a transformer-based deep learning model in China J. Zhang et al. https://doi.org/10.1016/j.atmosres.2026.108862
- Window-specific effects of ultraviolet radiation and air pollution on ovarian reserve in infertile women: A retrospective cohort study Q. Tang et al. https://doi.org/10.1016/j.envpol.2026.128740
- Decoding urban humid heat: temporal attribution of wet-bulb temperature drivers in the Lanzhou–Xining corridor X. Wang et al. https://doi.org/10.3389/feart.2026.1860008
- Increasing residential greenness attenuates the hazard of ultraviolet radiation on age-related macular degeneration in the elderly: A nationwide study in China Y. Qu et al. https://doi.org/10.1016/j.ecoenv.2025.117924
- First high-resolution surface spectral clear-sky ultraviolet radiation dataset across China (1981–2023): development, validation, and variability Q. Qi et al. https://doi.org/10.5194/essd-17-7271-2025
- Associations of personal solar UV exposure with gut microbiota diversity and BMI among preschool children in China J. Liang et al. https://doi.org/10.1515/jpem-2025-0631
- Surface Ozone-Induced Yield Losses and Economic Costs of Winter Wheat Across China: Spatiotemporal Estimates Based on Reconstructed M7 and AOT40 Exposures (2015–2022) H. Zheng et al. https://doi.org/10.3390/agronomy16171671
- Rooting depth projections of global plant functional types and driving factors analysis based on a hybrid modeling framework Q. Han et al. https://doi.org/10.1016/j.ecolind.2025.113674
- Global uncertainty of various downward shortwave solar radiation products W. Xu et al. https://doi.org/10.1016/j.energy.2026.140282
- Deep Learning-Based Forecasting of Ultraviolet Radiation Intensity in Lima, Peru: Implications for Climate Resilience and Public Health J. Ventocilla et al. https://doi.org/10.3390/a19070522
- Photochemical mineralization of sedimentary organic matter potentially contributes to internal nutrient loadings in lakes of northwestern China X. Yao et al. https://doi.org/10.1016/j.envpol.2025.126743
Saved (final revised paper)
Latest update: 12 Sep 2026
Short summary
Limited ultraviolet (UV) measurements hindered further investigation of its health effects. This study used a machine learning algorithm to predict UV radiation with a daily and 10 km resolution of high accuracy in mainland China in 2005–2020. Then, uneven spatial distribution and population exposure risks as well as increased temporal trend of UV radiation were found in China. The long-term and high-quality UV dataset could further facilitate health-related research in the future.
Limited ultraviolet (UV) measurements hindered further investigation of its health effects. This...
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