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The aim of this paper is to evaluate the surface concentration of nitrogen dioxide (NO2) inferred from the Sentinel-5 Precursor Tropospheric Monitoring Instrument (S5P/TROPOMI) NO2 tropospheric column densities over Central Europe for two time periods, summer 2019 and winter 2019–2020. Simulations of the NO2 tropospheric vertical column densities and surface concentrations from the Long-Term Ozone Simulation–European Operational Smog (LOTOS-EUROS) chemical transport model are also applied in the methodology. More than two hundred in situ air quality monitoring stations, reporting to the European Environment Agency (EEA) air quality database, are used to carry out comparisons with the model simulations and the spaceborne inferred surface concentrations. Stations are separated into seven types (urban traffic, suburban traffic, urban background, suburban background, rural background, suburban industrial and rural industrial) in order to examine the strengths and shortcomings of the different air quality markers, namely the NO2 vertical column densities and NO2 surface concentrations. S5P/TROPOMI NO2 surface concentrations are inferred by multiplying the fraction of the satellite and model NO2 vertical column densities with the model surface concentrations. The estimated inferred TROPOMI NO2 surface concentrations are examined further with the altering of three influencing factors: the model vertical leveling scheme, the versions of the TROPOMI NO2 data and the air mass factors applied to the satellite and model NO2 vertical column densities. Overall, the inferred TROPOMI NO2 surface concentrations show a better correlation with the in situ measurements for both time periods and all station types, especially for the industrial stations (R > 0.6) in winter. The calculated correlation for background stations is moderate for both periods (R~0.5 in summer and R > 0.5 in winter), whereas for traffic stations it improves in the winter (from 0.20 to 0.50). After the implementation of the air mass factors from the local model, the bias is significantly reduced for most of the station types, especially in winter for the background stations, ranging from +0.49% for the urban background to +10.37% for the rural background stations. The mean relative bias in winter between the inferred S5P/TROPOMI NO2 surface concentrations and the ground-based measurements for industrial stations is about −15%, whereas for traffic urban stations it is approximately −25%. In summer, biases are generally higher for all station types, especially for the traffic stations (~−75%), ranging from −54% to −30% for the background and industrial stations. [ABSTRACT FROM AUTHOR]

The Eurodelta-Trends multi-model experiment, aimed to assess the efficiency of emission mitigation measures in improving air quality in Europe during 1990-2010, was designed to answer a series of questions regarding European pollution trends. i.e. were there significant trends detected by observations? do the models manage to reproduce observed trends? how close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to PM pollution. An in-depth trend analysis has been performed forPM2.5 and PM2.5 for the period of 2000-2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the models simulated trends could be regarded as an indicator for modelling uncertainty. The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5, with reduction by between 2 and 6 µg m-3 m-3 (or between 10 and 30%) from 2000 to 2010. Compared to PM2.5, relative PM10 trends are weaker due to large inter-annual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is a reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30-40% over most of Europe, increasing to 50-60% in northern and eastern parts of EDT domain. Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble simulated trends are -0.24 and -0.22 µg m-3 year-1 for PM10 and PM2.5, which are somewhat weaker than the observed trends of -0.35 and -0.40 µg m-3 year-1, respectively, partly due to models underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are -1.7 and -2.0 % year-1 from the model ensemble and -2.1 and -2.9 %year--1 from the observations, respectively. The observations identify significant trends for PM10 at 56 % of the sites and for PM2.5 at 36% of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries. The strongest decreasing PM trends and the largest number of sites with significant trends is found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. One important reason for that is the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modeled versus observed PM trends are limited the regions where the sites are located. The analysis reveals a considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in SO-2 4 concentrations playing an overall dominant role. Also, we see relatively large contributions of the trends of NH+4 and NO-3 to PM10 decreasing trends in Germany, Denmark, Poland and the Po Valley, while the reductions of primary PM emissions appears to be a dominant factor in bringing down PM10 in France, Norway, Portugal, Greece and parts of the UK and Russia. Further discussions are given with respect to emission uncertainties and the effect of inter-annual meteorological variability on the trend analysis. [ABSTRACT FROM AUTHOR]

The evaluation of chemical transport models, CTMs, is essential for the assessment of their performance regarding the physical and chemical parameterizations used. While regional CTMs have been widely used and evaluated over Europe, their validation over Greece is limited. In this study, we investigate the performance of the LOTOS-EUROS v2.2.001 regional chemical transport model in simulating nitrogen dioxide, NO2, over Greece from June to December 2018. In-situ NO2 measurements obtained from the National Air Pollution Monitoring Network are compared with surface simulations over the two major cities of Greece, Athens and Thessaloniki. The model reproduces well the spatial variability of the measured NO2 with a spatial correlation coefficient of 0.85 for the period between June and December 2018. About half of the 14 air quality monitoring stations show a good temporal correlation to the simulations, higher than 0.6, during daytime (12–15 p.m. local time), while the corresponding biases are negative. Most stations show stronger negative biases during winter than in summer. Furthermore, the simulated tropospheric NO2 columns are evaluated against ground-based MAX-DOAS NO2 measurements and space-borne Sentinel 5-Precursor TROPOMI tropospheric NO2 observations in July and December 2018. LOTOS-EUROS captures better the NO2 temporal variability in December (0.61 and 0.81) than in July (0.50 and 0.21) when compared to the corresponding measurements of the MAX-DOAS instruments in Thessaloniki and the rural azimuth viewing direction in Athens respectively. The urban azimuth viewing direction in Athens region however shows a better correlation in July than in December (0.41 and 0.19, respectively). LOTOS-EUROS NO2 columns over Athens and Thessaloniki agree well with the TROPOMI observations showing higher spatial correlation in July (0.95 and 0.82, respectively) than in December (0.82 and 0.66, respectively) while the relative temporal correlations are higher during winter. Overall, the comparison of the simulations with the TROPOMI observations shows a model underestimation in summer and an overestimation in winter both in Athens and Thessaloniki. Updated emissions for the simulations and model improvements when extreme values of boundary layer height are encountered are further suggested. [ABSTRACT FROM AUTHOR]

The unprecedented order, in modern peaceful times, for near-total lockdown of the Greek population, as means of protection against the Severe Acute Respiratory Syndrome CoronaVirus-2, commonly known as COVID-19, infection, has brought unintentional positive side-effects to the country's air quality levels. S5P/TROPOMI monthly mean tropospheric nitrogen dioxide (NO2) observations show an average decrease of -3 % to -26 % [-1 % to -27 %] with an average of -22 % [-11 %] for March and April 2020 respectively, compared to the previous year, over the six larger Greek metropolitan areas, attributable mostly to vehicular emission reductions. Furthermore, significant effects for shipping emissions over the Aegean Sea as well as the areas surrounding major Greek ports were observed, of approximately -12 % [-5 %]. For the capital city of Athens, weekly analysis was possible and it revealed a marked decline in NO2 load between -8 % and -43 % for seven of the eight weeks studied. Chemical transport modelling, provided by the LOTOS-EUROS CTM, shows that the magnitude of these reductions cannot solely be attributed to the difference in meteorological factors affecting NO2 levels during March and April 2020 and the equivalent time periods of the previous year. Taking this factor into account, the resulting decline was estimated to range between 0 % and -37 % for the five largest cities, with an average of ~ -10 %. As transport is the second largest sector that affects Greece's air quality, this occasion may well help policy makers in enforcing more targeted measures to aid Greece in further reducing emissions according to international air quality standards. [ABSTRACT FROM AUTHOR]