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The gap in knowledge regarding the radiative effects of aerosols in the UV region of the solar spectrum is large, mainly due to the lack of systematic measurements of the aerosol single scattering albedo (SSA) and absorption optical depth (AAOD). In the present study, spectral UV measurements performed in Thessaloniki, Greece by a double monochromator Brewer spectrophotometer in the period 1998–2017 are used for the calculation of the aforementioned optical properties. The main uncertainty factors have been described and there is an effort to quantify the overall uncertainties in SSA and AAOD. Analysis of the results suggests that the absorption by aerosols is much stronger in the UV relative to the visible. SSA follows a clear annual pattern ranging from ~0.7 in winter to ~0.85 in summer at wavelengths 320–360 nm, while AAOD peaks in summer and winter. The average AAOD for 2009–2011 is ~50% above the 2003–2006 average, possibly due to increased emissions of absorbing aerosols related to the economic crisis and the metro-railway construction works in the city center.

From 25 May to 5 June 2015, the 10th regional intercomparison campaign of the Regional Brewer Calibration Center – Europe (RBCC-E) was held at El Arenosillo atmospheric sounding station of the Instituto Nacional de Técnica Aeroespacial (INTA). This campaign was jointly conducted by COST Action ES1207 EUBREWNET and the Area of Instrumentation and Atmospheric Research of INTA. A total of 21 Brewers, 11 single- and 10 double-monochromator instruments from 11 countries participated and were calibrated for total column ozone (TOC) and solar UV irradiance. In this 2015 campaign we have introduced a formal approach to the characterisation of the internal instrumental stray light, the filter non-linearity and the algorithm for correcting for its effects on the TOC calculations. This work shows a general overview of the ozone comparison and the evaluation of the correction of the spectral stray light effect for the single-monochromator Brewer spectrophotometer, derived from the comparison with a reference double-monochromator Brewer instrument. At the beginning of the campaign, 16 out of the 21 participating Brewer instruments agreed within better than ±1 %, and 10 instruments agreed within better than ±0.5 % considering data with ozone slant column between 100 and 900 DU, which does not require instrumental stray light correction.

In this paper, we compare model calculations of ozone profiles and their variability for the period 1998 to 2016 with satellite and lidar profiles at five ground-based stations. Under the investigation is the temporal impact of the stratospheric halogen reduction (chemical processes) and increase in greenhouse gases (i.e., global warming) on stratospheric ozone changes. Attention is given to the effect of greenhouse gases on ultraviolet-B radiation at ground level. Our chemistry transport and chemistry climate models (Oslo CTM3 and EMAC CCM) indicate that (a) the effect of halogen reduction is maximized in ozone recovery at 1–7 hPa and observed at all lidar stations; and (b) significant impact of greenhouse gases on stratospheric ozone recovery is predicted after the year 2050. Our study indicates that solar ultraviolet-B irradiance that produces DNA damage would increase after the year 2050 by +1.3% per decade. Such change in the model is driven by a significant decrease in cloud cover due to the evolution of greenhouse gases in the future and an insignificant trend in total ozone. If our estimates prove to be true, then it is likely that the process of climate change will overwhelm the effect of ozone recovery on UV-B irradiance in midlatitudes.

In this study, the tropospheric NO2 vertical column density (VCD) over an urban site in Guangzhou megacity in China is investigated by means of MAX-DOAS measurements during a campaign from late March 2015 to mid-March 2016. A MAX-DOAS system was deployed at the Guangzhou Institute of Geochemistry of the Chinese Academy of Sciences and operated there for about 1 year, during the spring and summer months. The tropospheric NO2 VCDs retrieved by the MAX-DOAS are presented and compared with space-borne observations from GOME-2/MetOp-A, GOME-2/MetOp-B and OMI/Aura satellite sensors. The comparisons reveal good agreement between satellite and MAX-DOAS observations over Guangzhou, with correlation coefficients ranging between 0.795 for GOME-2B and 0.996 for OMI. However, the tropospheric NO2 loadings are underestimated by the satellite sensors on average by 25.1, 10.3 and 5.7 %, respectively, for OMI, GOME-2A and GOME-2B. Our results indicate that GOME-2B retrievals are closer to those of the MAX-DOAS instrument due to the lower tropospheric NO2 concentrations during the days with valid GOME-2B observations. In addition, the effect of the main coincidence criteria is investigated, namely the cloud fraction (CF), the distance (d) between the satellite pixel center and the ground-based measurement site, as well as the time period within which the MAX-DOAS data are averaged around the satellite overpass time. The effect of CF and time window criteria is more profound on the selection of OMI overpass data, probably due to its smaller pixel size. The available data pairs are reduced to half and about one-third for CF ≤ 0.3 and CF ≤ 0.2, respectively, while, compared to larger CF thresholds, the correlation coefficient is improved to 0.996 from about 0.86, the slope value is very close to unity (∼ 0.98) and the mean satellite underestimation is reduced to about half (from ∼ 7 to∼ 3.5 × 1015 molecules cm-2). On the other hand, the distance criterion affects mostly GOME-2B data selection, because GOME-2B pixels are quite evenly distributed among the different radii used in the sensitivity test. More specifically, the number of collocations is notably reduced when stricter radius limits are applied, the r value is improved from 0.795 (d≤ 50 km) to 0.953 (d≤ 20 km), and the absolute mean bias decreases about 6 times for d≤ 30 km compared to the reference case (d≤ 50 km).

The projected large increases in damaging ultraviolet radiation as a result of global emissions of ozone-depleting substances have been forestalled by the success of the Montreal Protocol. New challenges are now arising in relation to climate change. We highlight the complex interactions between the drivers of climate change and those of stratospheric ozone depletion, and the positive and negative feedbacks among climate, ozone and ultraviolet radiation. These will result in both risks and benefits of exposure to ultraviolet radiation for the environment and human welfare. This Review synthesizes these new insights and their relevance in a world where changes in climate as well as in stratospheric ozone are altering exposure to ultraviolet radiation with largely unknown consequences for the biosphere.

In this study, we discuss the short- and the long-term variability of spectral UV irradiance at Thessaloniki, Greece, using a long, quality-controlled data set from two Brewer spectrophotometers. Long-term changes in spectral UV irradiance at 307.5, 324 and 350 nm for the period 1994–2014 are presented for different solar zenith angles and discussed in association with changes in total ozone column (TOC), aerosol optical depth (AOD) and cloudiness observed in the same period. Positive changes in annual mean anomalies of UV irradiance, ranging from 2 to 6 % per decade, have been detected both for clear- and all-sky conditions. The changes are generally greater for larger solar zenith angles and for shorter wavelengths. For clear-skies, these changes are, in most cases, statistically significant at the 95 % confidence limit. Decreases in the aerosol load and weakening of the attenuation by clouds lead to increases in UV irradiance in the summer, of 7–9 % per decade for 64° solar zenith angle. The increasing TOC in winter counteracts the effect of decreasing AOD for this particular season, leading to small, statistically insignificant, negative long-term changes in irradiance at 307.5 nm. Annual mean UV irradiance levels are increasing from 1994 to 2006 and remain relatively stable thereafter, possibly due to the combined changes in the amount and optical properties of aerosols. However, no statistically significant corresponding turning point has been detected in the long-term changes of AOD. The absence of signatures of changes in AOD in the short-term variability of irradiance in the UV-A may have been caused by changes in the single scattering albedo of aerosols, which may counteract the effects of changes in AOD on irradiance. The anti-correlation between the year-to-year variability of the irradiance at 307.5 nm and TOC is clear and becomes clearer as the AOD decreases.

One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32  ×  1015 and 10.21 ± 8.87  × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71  ×  1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01  ×  1015 molecules cm−2.

Solar irradiance nowcasting and short-term forecasting are important tools for the integration of solar plants into the electricity grid. Understanding the role of clouds and aerosols in those techniques is essential for improving their accuracy. In this study, we introduce improvements in the existing nowcasting and short-term forecasting operational systems SENSE (Solar Energy Nowcasting System) and NextSENSE achieved by using a new configuration and by upgrading cloud and aerosol inputs, and we also investigate the limitations of evaluating such models using surface-based sensors due to cloud effects. We assess the real-time estimates of surface global horizontal irradiance (GHI) produced by the improved SENSE2 operational system at high spatial and temporal resolution (∼ 5 km, 15 min) for a domain including Europe and the Middle East–North Africa (MENA) region and the short-term forecasts of GHI (up to 3 h ahead) produced by the NextSENSE2 system against ground-based measurements from 10 stations across the models' domain for a whole year (2017). Results for instantaneous (every 15 min) comparisons show that the GHI estimates are within ±50 W m−2 (or ±10 %) of the measured GHI for 61 % of the cases after the implementation of the new model configuration and a proposed bias correction. The bias ranges from −12 to 23 W m−2 (or from −2 % to 6.1 %) with a mean value of 11.3 W m−2 (2.3 %). The correlation coefficient is between 0.83 and 0.96 and has a mean value of 0.93. Statistics are significantly improved when integrating on daily and monthly scales (the mean bias is 3.3 and 2.7 W m−2, respectively). We demonstrate that the main overestimation of the SENSE2 GHI is linked with the uncertainties of the cloud-related information within the satellite pixel, while relatively low underestimation, linked with aerosol optical depth (AOD) forecasts (derived from the Copernicus Atmospheric Monitoring Service – CAMS), is reported for cloudless-sky GHI. The highest deviations for instantaneous comparisons are associated with cloudy atmospheric conditions, when clouds obscure the sun over the ground-based station. Thus, they are much more closely linked with satellite vs. ground-based comparison limitations than the actual model performance. The NextSENSE2 GHI forecasts based on the cloud motion vector (CMV) model outperform the persistence forecasting method, which assumes the same cloud conditions for future time steps. The forecasting skill (FS) of the CMV-based model compared to the persistence approach increases with cloudiness (FS is up to ∼ 20 %), which is linked mostly to periods with changes in cloudiness (which persistence, by definition, fails to predict). Our results could be useful for further studies on satellite-based solar model evaluations and, in general, for the operational implementation of solar energy nowcasting and short-term forecasting, supporting solar energy production and management.

The UV-Index (UVI) is aimed at the prevention of skin cancer as well as other negative implications of ultraviolet radiation exposure. In order to support health related applications, assessments and planning that rely on long term data in high spatial resolution and as there exist only limited ground-based measurements, satellite products from reliable atmospheric monitoring services are used as sustainable data sources to create a climatology of the UVI at the local noon. In this study, the (all-sky) UVI as well as the hypothetically clear-sky UVI were analysed for the European region from 30° North to 65° North and from 25° West to 35° East in a spatial resolution of 0.05° for the time period 1983 to 2015. Maps of the monthly mean UVI provide an overview of the distribution of UVI for Europe as well as the spatial and temporal differences and regional variability at local solar noon. Additionally, eight selected locations provide insight into the effects of latitude and altitude on UVI in Europe. Monthly boxplots for each location provide information about regional differences in the variability of UVI, showing maximum variability in Northern and Central Europe in summer, where in Southern Europe this basically occurs in spring. The frequency of the World Health Organization exposure categories moderate, high and very high UVI is provided based on ten-day means for each month. The maximum difference between mean values per decade of 2006–2015 compared to 1983–1992 ranges from −1.2 to +1.2 for UVI and from −0.4 to +0.6 for UVI c l e a r − s k y . All locations, except the Northern European site, show an increase of UVI during spring and early summer months. A statistically significant increase in the annual mean all-sky UVI has been found for four sites, which ranges from +1.2% to +3.6% per decade. The latest eleven-year period of the UVI climatology (2005–2015) has been validated with UVI measured in five sites. The sites that are located north of the Alps show an underestimation of the UVI, likely due to the cloud modification. In the south, the UVI climatology provides values that are on average overestimated, possibly related to the use of climatological aerosol information. For the site within the Alps, a switch between underestimation and overestimation during the course of the year has been found. 7% to 9% of the UVI values of the climatology differ from the measured UVI by more than one unit.