Long-term variability of human health-related solar ultraviolet-B radiation doses for the 1980s to the end of the 21st century.

Solar ultraviolet-B (UV-B) radiation has played a crucial role in the evolution of life on Earth, and potential changes in its levels could affect the health and functionality of humans and the ecosystems. UV exposure presents both risks and benefits to humans. However, optimal UV-B radiation exposure depends on several environmental and physiological factors and cannot be easily determined. The present document provides a review of the current state of knowledge relative to the effects of UV-B radiation on human health. A brief description of the physical mechanisms that control the levels of solar UV-B radiation at the Earth's surface is provided, with special emphasis on the role of ozone and the importance of the Montreal Protocol. A comprehensive review of studies reporting current trends in levels of surface solar UV-B radiation and projections of future levels reveals the dominant role of climatic changes in the long-term variability of UV-B radiation and its impact on the development of melanomas as well as eye disorders. The review provides strong evidence that despite the success of the Montreal Protocol and the expected ozone recovery, the future evolution of the levels of solar UV-B radiation at the Earth's surface is not certain.

Does solar ultraviolet radiation play a role in COVID-19 infection and deaths? An environmental ecological study in Italy.

A significantly stronger impact in mortality and morbidity by COVID-19 has been observed in the northern Italian regions compared to the southern ones. The reasons of this geographical pattern might involve several concurrent factors. The main objective of this work is to investigate whether any correlations exist between the spatial distribution of COVID-19 cases and deaths in the different Italian regions and the amount of solar ultraviolet (UV) radiation at the Earth's surface. To this purpose, in this environmental ecological study a mixed-effect exponential regression was built to explain the incidence of COVID-19 based on the environmental conditions, and demographic and pathophysiologic factors. Observations and estimates of the cumulative solar UV exposure have been included to quantify the amount of radiation available e.g., for pre-vitamin D3 synthesis or SARS-CoV-2 inactivation by sunlight. The analysis shows a significant correlation (p-value <5 × 10-2) between the response variables (death percentage, incidence of infections and positive tests) and biologically effective solar UV radiation, residents in nursing homes per inhabitant (NHR), air temperature, death percentage due to the most frequent comorbidities. Among all factors, the amount of solar UV radiation is the variable contributing the most to the observed correlation, explaining up to 83.2% of the variance of the COVID-19 affected cases per population. While the statistical outcomes of the study do not directly entail a specific cause-effect relationship, our results are consistent with the hypothesis that solar UV radiation impacted on the development of the infection and on its complications, e.g. through the effect of vitamin D on the immune system or virus inactivation by sunlight. The analytical framework used in this study, based on commonly available data, can be easily replicated in other countries and geographical domains to identify possible correlations between exposure to solar UV radiation and the spread of the pandemic.

The 2020 Arctic ozone depletion and signs of its effect on the ozone column at lower latitudes.

The present study discusses the effect of the ozone depletion that occurred over the Arctic in 2020 on the ozone column in central and southern Europe by analysing a data set obtained from ground-based measurements at six stations placed from 79 to 42°N. Over the northernmost site (Ny-Ålesund), the ozone column decreased by about 45% compared to the climatological average at the beginning of April, and its values returned to the normal levels at the end of the month. Southwards, the anomaly gradually reduced to nearly 15% at 42°N (Rome) and the ozone minimum was detected with a delay from about 6 days at 65°N to 20 days at 42°N. At the same time, the evolution of the ozone column at the considered stations placed below the polar circle corresponded to that observed at Ny-Ålesund, but at 42°-46°N, the ozone column turned back to the typical values at the end of May. This similarity in the ozone evolutional patterns at different latitudes and the gradually increasing delay of the minimum occurrences towards the south allows the assumption that the ozone columns at lower latitudes were affected by the phenomenon in the Arctic. The ozone decrease observed at Aosta (46°N) combined with predominantly cloud-free conditions resulted in about an 18% increase in the erythemally weighted solar ultraviolet irradiance reaching the Earth's surface in May.

NILU-UV multi-filter radiometer total ozone columns: Comparison with satellite observations over Thessaloniki, Greece.

This study aims to construct and validate a neural network (NN) model for the production of high frequency (~1min) ground-based estimates of total ozone column (TOC) at a mid-latitude UV and ozone monitoring station in the Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki (LAP/AUTh) for the years 2005-2014. In the first stage of model development, ~30,000 records of coincident solar UV spectral irradiance measurements from a Norsk Institutt for Luftforskning (NILU)-UV multi-filter radiometer and TOC measurements from a co-located Brewer spectroradiometer are used to train a NN to learn the nonlinear functional relation between the irradiances and TOC. The model is then subjected to sensitivity analysis and validation. Close agreement is obtained (R2=0.94, RMSE=8.21 DU and bias=-0.15 DU relative to the Brewer) for the training data in the correlation of NN estimates on Brewer derived TOC with 95% of the coincident data differing by less than 13 DU. In the second stage of development, a long time series (≥1 million records) of high frequency (~1min) NILU-UV ground-based measurements are presented as inputs to the NN model to generate high frequency TOC estimates. The advantage of the NN model is that it is not site dependent and is applicable to any NILU input data lying within the range of the training data. GOME/ERS-2, SCIAMACHY/Envisat, OMI/Aura and GOME2/MetOp-A TOC records are then used to perform a precise cross-validation analysis and comparison with the NILU TOC estimates over Thessaloniki. All 4 satellite TOC dataset are retrieved using the GOME Direct Fitting algorithm, version 3 (GODFIT_v3), for reasons of consistency. The NILU TOC estimates within ±30min of the overpass times agree well with the satellite TOC retrievals with coefficient of determination in the range 0.88≤R2≤0.90 for all sky conditions and 0.95≤R2≤0.96 for clear sky conditions. The mean fractional differences are found to be -0.67%±2.15%, -1.44%±2.25%, -2.09%±2.06% and -0.85%±2.19% for GOME, SCIAMACHY, OMI and GOME2 respectively for the clear sky cases. The near constant standard deviation (~±2.2%) across the array of sensors testifies directly to the stability of both the GODFIT_v3 algorithm and the NN model for providing coherent and robust TOC records. Furthermore, the high Pearson product moment correlation coefficients (0.94