Air quality observations by satellite instruments are global and have a regular temporal resolution, which makes them very useful in studying long-term trends in atmospheric species. To monitor air quality trends in China for the period 2005–2015, we derive SO₂ columns and NO_x emissions on a provincial level with improved accuracy. To put these trends into perspective they are compared with public data on energy consumption and the environmental policies of China. We distinguish the effect of air quality regulations from economic growth by comparing them relatively to fossil fuel consumption. Pollutant levels, per unit of fossil fuel, are used to assess the effectiveness of air quality regulations. We note that the desulfurization regulations enforced in 2005–2006 only had a significant effect in the years 2008–2009, when a much stricter control of the actual use of the installations began. For national NO_x emissions a distinct decreasing trend is only visible from 2012 onwards, but the emission peak year differs from province to province. Unlike SO₂, emissions of NO_x are highly related to traffic. Furthermore, regulations for NO_x emissions are partly decided on a provincial level. The last 3 years show a reduction both in SO₂ and NO_x emissions per fossil fuel unit, since the authorities have implemented several new environmental regulations. Despite an increasing fossil fuel consumption and a growing transport sector, the effects of air quality policy in China are clearly visible. Without the air quality regulations the concentration of SO₂ would be about 2.5 times higher and the NO₂ concentrations would be at least 25 % higher than they are today in China.

In October 2017, the Sentinel-5 Precursor (S5P) mission was launched, carrying the TROPOspheric Monitoring Instrument (TROPOMI), which provides a daily global coverage at a spatial resolution as high as 7 km × 3.5 km and is expected to extend the European atmospheric composition record initiated with GOME/ERS-2 in 1995, enhancing our scientific knowledge of atmospheric processes with its unprecedented spatial resolution. Due to the ongoing need to understand and monitor the recovery of the ozone layer, as well as the evolution of tropospheric pollution, total ozone remains one of the leading species of interest during this mission. In this work, the TROPOMI near real time (NRTI) and offline (OFFL) total ozone column (TOC) products are presented and compared to daily ground-based quality-assured Brewer and Dobson TOC measurements deposited in the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Additional comparisons to individual Brewer measurements from the Canadian Brewer Network and the European Brewer Network (Eubrewnet) are performed. Furthermore, twilight zenith-sky measurements obtained with ZSL-DOAS (Zenith Scattered Light Differential Optical Absorption Spectroscopy) instruments, which form part of the SAOZ network (Système d'Analyse par Observation Zénitale), are used for the validation. The quality of the TROPOMI TOC data is evaluated in terms of the influence of location, solar zenith angle, viewing angle, season, effective temperature, surface albedo and clouds. For this purpose, globally distributed ground-based measurements have been utilized as the background truth. The overall statistical analysis of the global comparison shows that the mean bias and the mean standard deviation of the percentage difference between TROPOMI and ground-based TOC is within 0 –1.5 % and 2.5 %–4.5 %, respectively. The mean bias that results from the comparisons is well within the S5P product requirements, while the mean standard deviation is very close to those limits, especially considering that the statistics shown here originate both from the satellite and the ground-based measurements. Additionally, the TROPOMI OFFL and NRTI products are evaluated against already known spaceborne sensors, namely, the Ozone Mapping Profiler Suite, on board the Suomi National Polar-orbiting Partnership (OMPS/Suomi-NPP), NASA v2 TOCs, and the Global Ozone Monitoring Experiment 2 (GOME-2), on board the Metop-A (GOME-2/Metop-A) and Metop-B (GOME-2/Metop-B) satellites. This analysis shows a very good agreement for both TROPOMI products with well-established instruments, with the absolute differences in mean bias and mean standard deviation being below +0.7 % and 1 %, respectively. These results assure the scientific community of the good quality of the TROPOMI TOC products during its first year of operation and enhance the already prevalent expectation that TROPOMI/S5P will play a very significant role in the continuity of ozone monitoring from space.

The influence of smoke on the aerosol loading in the free troposphere over Thessaloniki, Greece is examined in this paper. Ten cases during 2001–2005 were identified when very high aerosol optical depth values in the free troposphere were observed with a UV-Raman lidar. Particle dispersion modeling (FLEXPART) and satellite hot spot fire detection (ATSR) showed that these high free tropospheric aerosol optical depths are mainly attributed to the advection of smoke plumes from biomass burning regions over Thessaloniki. The biomass burning regions were found to extend across Russia in the latitudinal belt between 45° N–55° N, as well as in Eastern Europe (Baltic countries, Western Russia, Belarus, and the Ukraine). The highest frequency of agricultural fires occurred during the summer season (mainly in August). The data collected allowed the optical characterization of the smoke aerosols that arrived over Greece, where limited information has so far been available. Two-wavelength backscatter lidar measurements showed that the backscatter-related Ångström exponent ranged between 0.5 and 2.4 indicating a variety of particle sizes. UV-Raman lidar measurements showed that for smoke particles the extinction to backscatter ratios (so-called lidar ratios) varied between 40 sr for small particles to 100 sr for large particles. Dispersion model estimations of the carbon monoxide tracer concentration profiles for smoke particles indicate that the variability of the optical parameters is a function of the age of the smoke plumes. This information could be useful on the lidar community for reducing uncertainty in the aerosol backscatter coefficient determination due to the lidar ratio assumption, starting from a simply elastic backscatter lidar as the first satellite-borne lidar CALIPSO.

Tropospheric vertical column densities (VCDs) of NO₂, SO₂ and HCHO derived from the Ozone Monitoring Instrument (OMI) on AURA and the Global Ozone Monitoring Experiment 2 aboard METOP-A (GOME-2A) and METOP-B (GOME-2B) are widely used to characterize the global distributions, trends and dominating sources of these trace gases. They are also useful for the comparison with chemical transport models (CTMs). We use tropospheric VCDs and vertical profiles of NO₂, SO₂ and HCHO derived from MAX-DOAS measurements from 2011 to 2014 in Wuxi, China, to validate the corresponding products (daily and bi-monthly-averaged data) derived from OMI and GOME-2A/B by different scientific teams. Prior to the comparison, the spatial and temporal coincidence criteria for MAX-DOAS and satellite data are determined by a sensitivity study using different spatial and temporal averaging conditions. Cloud effects on both MAX-DOAS and satellite observations are also investigated. Our results indicate that the discrepancies between satellite and MAX-DOAS results increase with increasing effective cloud fraction and are dominated by the effects of clouds on the satellite products. In comparison with MAX-DOAS, we found a systematic underestimation of all SO₂ (40 to 57 %) and HCHO products (about 20 %), and an overestimation of the GOME-2A/B NO₂ products (about 30 %), but good consistency with the DOMINO version 2 NO₂ product. To better understand the reasons for these differences, we evaluated the a priori profile shapes used in the OMI retrievals (derived from CTM) by comparison with those derived from the MAX-DOAS observations. Significant differences are found for the SO₂ and HCHO profile shapes derived from the IMAGES model, whereas on average good agreement is found for the NO₂ profile shapes derived from the TM4 model. We also applied the MAX-DOAS profile shapes to the satellite retrievals and found that these modified satellite VCDs agree better with the MAX-DOAS VCDs than the VCDs from the original data sets by up to 10, 47 and 35 % for NO₂, SO₂ and HCHO, respectively. Furthermore, we investigated the effect of aerosols on the satellite retrievals. For OMI observations of NO₂, a systematic underestimation is found for large AOD, which is mainly attributed to effect of the aerosols on the cloud retrieval and the subsequent application of a cloud correction scheme (implicit aerosol correction). In contrast, the effect of aerosols on the clear-sky air mass factor (explicit aerosol correction) has a smaller effect. For SO₂ and HCHO observations selected in the same way, no clear aerosol effect is found, probably because for the considered data sets no cloud correction is applied (and also because of the larger scatter). From our findings we conclude that for satellite observations with cloud top pressure (CTP) > 900 hPa and effective cloud fraction (eCF) < 10 % the application of a clear-sky air mass factor might be a good option if accurate aerosol information is not available. Another finding of our study is that the ratio of morning-to-afternoon NO₂ VCDs can be considerably overestimated if results from different sensors and/or retrievals (e.g. OMI and GOME-2) are used, whereas fewer deviations for HCHO and SO₂ VCDs are found.

[1] The Global Ozone Monitoring Instrument (GOME‐2) was launched on EUMESAT's MetOp‐A satellite in October 2006. This paper is concerned with the retrieval algorithm GOME Data Processor (GDP) version 4.4 used by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M‐SAF) for the operational generation of GOME‐2 total ozone products. GDP 4.4 is the latest version of the GDP 4.0 algorithm, which is employed for the generation of official Level 2 total ozone and other trace gas products from GOME and SCIAMACHY. Here we focus on enhancements introduced in GDP 4.4: improved cloud retrieval algorithms including detection of Sun glint effects, a correction for intracloud ozone, better treatment of snow and ice conditions, accurate radiative transfer modeling for large viewing angles, and elimination of scan angle dependencies inherited from Level 1 radiances. Furthermore, the first global validation results for 3 years (2007–2009) of GOME‐2/MetOp‐A total ozone measurements using Brewer and Dobson measurements as references are presented. The GOME‐2/MetOp‐A total ozone data obtained with GDP 4.4 slightly underestimates ground‐based ozone by about 0.5% to 1% over the middle latitudes of the Northern Hemisphere and slightly overestimates by around 0.5% over the middle latitudes in the Southern Hemisphere. Over high latitudes in the Northern Hemisphere, GOME‐2 total ozone has almost no offset relative to Dobson readings, while over high latitudes in the Southern Hemisphere GOME‐2 exhibits a small negative bias below 1%. For tropical latitudes, GOME‐2 measures on average lower ozone by 0% to 2% compared to Dobson measurements.