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Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.

The objective of this study is to investigate the long-term effects of climate change on olive crops in Andalusia, one of the most important olive growing areas worldwide, using tailored climate indices and return period analysis. Both the climatic indices and the occurrence probabilities of bad years in terms of olive yield and olive fly risk are being calculated for the reference period 1971–2000 and for the near (2031–2060) and distant future (2071–2100) under two emission scenarios using an ensemble of five high-resolution, bias-adjusted Regional Climate Models. Three threshold-based temperature related indices (SPR32, SU36, SU40) as well as mean temperature and precipitation related climatic indices (SPRTX, WINRR) have been calculated, revealing increasing changes in the near and distant future and pointing out the challenges faced by the olive sector due to climate change; a robust increase of the threshold-based indices are found in central and northern Andalusia, mainly in the provinces of Seville, Cordoba and Jaen. Although the changes of the precipitation-related index are less pronounced for the near future, robust decreases are projected for the distant future period under a high emission scenario. The identification of the bad years is based on observational data from five monitoring stations in Andalusia (Malaga, Granada, Sevilla, Cordoba and Jaen). The role of certain meteorological parameters (precipitation, temperature, relative humidity) is investigated and the return levels of interest for the calculation of the occurrence probabilities are estimated by the upper tail of the reference distribution. The results indicate an overall tendency for increased occurrence probability of bad years in terms of olive yield due to future decreased precipitation; bad year occurrences with return periods of below 2 years may increase by about 20 % by 2060. Spatial variability is also evident with overall larger changes in western Andalusia. The range of the olive fly is expected to decrease in the northern areas of Andalusia.

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 Long Term Ozone Simulation European Operational Smog (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 14 stations of the National Air Pollution Monitoring Network are compared with surface simulations over the two major cities of Greece, Athens and Thessaloniki. Overall the LOTOS-EUROS NO2 surface simulations compare very well to the in situ measurements showing a mild underestimation of the measurements with a mean relative bias of ∼-10 %, a high spatial correlation coefficient of 0.86 and an average temporal correlation of 0.52. The CTM underestimates the NO2 surface concentrations during daytime by ∼-50 ± 15 %, while it slightly overestimates during night-time ∼ 10 ± 35 %. Furthermore, the LOTOS-EUROS tropospheric NO2 columns are evaluated against ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) NO2 measurements in Athens and Thessaloniki. We report that the CTM tropospheric NO2 column simulations over both urban and rural locations represent the diurnal patterns and hourly levels for both summer and winter seasons satisfactorily. The relative biases range between ∼ −2 % and −35 %, depending on season and relative NO2 load observed. Finally, the CTM was assessed also against space-borne Sentinel-5 Precursor (S5P) carrying the Tropospheric Monitoring Instrument (TROPOMI) tropospheric NO2 observations. We conclude that LOTOS-EUROS simulates extremely well the tropospheric NO2 patterns over the region with very high spatial correlation of 0.82 on average, ranging between 0.66 and 0.95, with negative biases in the summer and positive in the winter. Updated emissions for the simulations and model improvements when extreme values of boundary layer height are encountered are further suggested.

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

In this study, we report on the retrieval of aerosol extinction profiles from ground-based scattered sunlight multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, carried out at Athens, Greece. It is the first time that aerosol profiles are retrieved from MAX-DOAS measurements in Athens. The reported aerosol vertical distributions at 477 nm are derived from the oxygen dimer (O4) differential-slant-column-density observations at different elevation angles by applying the BRemen Optimal estimation REtrieval for Aerosol and trace gaseS (BOREAS) retrieval algorithm. Four case studies have been selected for validation purposes; the retrieved aerosol profiles and the corresponding aerosol optical depths (AODs) from the MAX-DOAS are compared with lidar extinction profiles and with sun-photometric measurements (Aerosol Robotic Network, AERONET, observations), respectively. Despite the different approach of each method regarding the retrieval of the aerosol information, the comparison with the lidar measurements at 532 nm reveals a very good agreement in terms of vertical distribution, with r>0.90 in all cases. The AODs from the MAX-DOAS and the sun photometer (the latter at 500 nm) show a satisfactory correlation (with 0.45 < r < 0.7 in three out of the four cases). The comparison indicates that the MAX-DOAS systematically underestimates the AOD in the cases of large particles (small Ångström exponent) and for measurements at small relative azimuthal angles between the viewing direction and the sun. Better agreement is achieved in the morning, at large relative azimuthal angles. Overall, the aerosol profiles retrieved from MAX-DOAS measurements are of good quality; thus, new perspectives are opened up for assessing urban aerosol pollution on a long-term basis in Athens from continuous and uninterrupted MAX-DOAS measurements.

The Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean during the CHARacterization of Aerosol mixtures of Dust and Marine origin Experiment (CHARADMExp). Three case studies are presented, focusing on dust-dominated, marine-dominated and dust–marine mixing conditions. GARRLiC and LIRIC achieve a satisfactory characterization for the dust-dominated case in terms of particle microphysical properties and concentration profiles. The marine-dominated and the mixture cases are more challenging for both algorithms, although GARRLiC manages to provide more detailed microphysical retrievals compared to AERONET, while LIRIC effectively discriminates dust and marine particles in its concentration profile retrievals. The results are also compared with modelled dust and marine concentration profiles and surface in situ measurements.

To evaluate the role of biomass burning emissions, and in particular of residential wood heating, as a result of the economic recession in Greece, carbon monoxide (CO) atmospheric concentrations from five (5) stations of the National Air Pollution Monitoring Network in Athens, spanning the period 2000-2015, in conjunction with black carbon (BC) concentrations from the NOA (National Observatory of Athens) station at Thissio were analysed. The contribution of the different sources to the diurnal cycle of these two pollutants is clear, resulting to a morning peak, mainly due to traffic, and a late evening peak attributed both to fossil fuel (traffic plus central heating) and biomass combustion. Calculated morning and evening integrals of CO peaks, for the investigated period, show consistent seasonal modulations, characterised by low summer and high winter values. The summer and winter morning CO peak integrals demonstrate an almost constant decreasing trend of CO concentrations over time (by almost 50% since 2000), attributed to the renewal of passenger car fleet and to reduced anthropogenic activities during the last years. On the other hand, an increase of 23%-78% (depending on the monitoring site) in the winter evening integrals since 2012, provides evidence of the significant contribution of biomass combustion, which has prevailed over fossil fuel for domestic heating. CO emitted by wood burning was found to contribute almost 50% to the total CO emissions during night time (16:00-5:00), suggesting that emissions from biomass combustion have gained an increasing role in atmospheric pollution levels in Athens., (Copyright © 2017 Elsevier B.V. All rights reserved.)