This study is primarily devoted to investigating the effect of aerosols on solar UV radiation. In the ultraviolet range, scattering processes are dominant and lead to a substantial contribution of diffuse UV radiation to the global UV irradiance. The paper introduces a method for estimating solar UV radiation through the UV Index. The proposed technique is first compared with other UV Index estimation methods and subsequently applied to examine the influence of aerosols and ozone on solar UV radiation and on its diffuse component. The exposure of human skin also to diffuse solar UV radiation can be potentially harmful for health.

This study is devoted to investigating the effect of aerosols on solar UV radiation. In the ultraviolet range, scattering processes are dominant and lead to a substantial contribution of diffuse UV radiation to the global UV irradiance. The paper introduces a method for estimating solar UV Index. The proposed method is first compared with other UV Index estimation methods and is subsequently applied to examine the influence of aerosols and ozone on solar UV radiation and on its diffuse component. Human skin exposure to diffuse solar UV radiation can be potentially harmful to health.

Surface solar ultraviolet (UV) radiation represents an essential component of shortwave solar radiation, with important implications for atmospheric chemistry and climate studies. Reliable, high-quality records of surface solar UV radiation are essential for UV-related research and applications; however, ground-based UV observations remain sparse worldwide. This study presents a novel broadband parametric model, based on physical principles, for estimating solar UV irradiance ($0.280–0.400 \mu \mathrm{m}$) under clear-sky conditions. The model is computationally efficient and suitable for practical applications. The proposed approach is based on the SMARTS2 spectral radiative transfer model and employs an interdependent integration scheme to derive broadband UV irradiance from spectrally resolved shortwave radiation. The model performance is evaluated against high-quality measurements from the Baseline Surface Radiation Network (BSRN) and compared with an established parameterization. The proposed model demonstrates improved performance at both validation sites, reducing the mean nRMSE from 8.88% to 7.64% at Izaña and from 60.69% to 29.24% at Payerne, while also substantially decreasing the bias under more challenging atmospheric conditions, although the nRMSE at Payerne remains relatively high. These results highlight the potential of the proposed approach as an efficient and physically consistent tool for clear-sky UV irradiance estimation.