Impact of Solar Radiation Intensity on Human Health: A Data-Driven Analysis
DOI:
https://doi.org/10.29284/0tvrjd89Keywords:
Solar Radiation, Ultraviolet Index, Skin Health, Risk Stratification, Predictive Modeling, Machine Learning, Environmental Health.Abstract
Solar radiation is simultaneously beneficial and hazardous to human health. Daylight exposure supports circadian alignment and limited ultraviolet exposure contributes to vitamin D synthesis, but excessive ultraviolet radiation can rapidly generate acute skin injury and cumulative long-term damage. This revised manuscript presents a more structured data-driven framework for interpreting solar radiation intensity by combining ultraviolet index (UVI), atmospheric modifiers, exposure duration, and skin-type sensitivity. To strengthen the original paper, the study is expanded with literature-grounded discussion, a nonlinear skin-damage model, structured risk categories, and richer visual representation. Because no harmonized patient-level dataset was supplied with the original manuscript, the quantitative illustrations are demonstrated using a literature-informed representative dataset of integrated exposure scenarios. In this proof-of-concept setting, the proposed ensemble classifier reached 94.4% accuracy with an area under the curve (AUC) of 0.989 for high-risk event detection. The results show that risk rises nonlinearly as UVI and exposure time increase together, with a pronounced acceleration once UVI enters the high and very high ranges. The combined framework provides a scalable basis for personalized alerts, mobile health applications, outdoor occupational safety, and future wearable photoprotection systems.
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This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
