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Abstract Background and aims Although studies in mice have suggested that lesion regression is feasible, the underlying mechanisms remain largely unknown. Here we determined the impact of high-density lipoprotein (HDL) on atherosclerosis regression outcome. Methods Atherosclerotic lesion dynamics were studied upon bone marrow transplantation-mediated re-introduction of apolipoprotein E (Apoe) in Apoe knockout mice. Probucol was used to pharmacologically deplete HDL. Results Restoration of Apoe function was associated with an initial growth of atherosclerotic lesions and parallel decrease in lesional macrophage foam cell content (47 ± 4% at 4 weeks versus 72 ± 2% at baseline: p < 0.001), despite the fact that cholesterol levels were markedly reduced. Notably, significant lesion regression was detected from 4 weeks onwards, when plasma cholesterol levels had returned to the normolipidemic range. As a result, lesions were 41% smaller (p < 0.05) at 8 weeks than at 4 weeks after bone marrow transplantation. Regressed lesions contained an even lower level of macrophage foam cells (33 ± 5%: p < 0.001) and were rich in collagen. Probucol co-treatment was associated with a 3.2-fold lower (p < 0.05) plasma HDL-cholesterol level and a more pro-inflammatory (CCR2+) monocyte phenotype. Importantly, probucol-treated mice exhibited atherosclerotic lesions that were larger than those of regular chow diet-fed bone marrow transplanted mice at 8 weeks (186 ± 15*103 μm2 for probucol-treated versus 120 ± 19*103 μm2 for controls: p < 0.05). Conclusions We have shown that probucol-induced HDL deficiency impairs the ability of established lesions to regress in response to reversal of the genetic hypercholesterolemia in Apoe knockout mice. Our studies thus highlight a crucial role for HDL in the process of atherosclerosis regression. Highlights • Reversal of hypercholesterolemia reduces lesional foam cell content in Apoe KO mice. • Normalization of cholesterol levels induces lesion regression in Apoe KO mice. • Probucol treatment is associated with a more pro-inflammatory monocyte phenotype. • Probucol-induced HDL lowering impairs the ability of established lesions to regress. [ABSTRACT FROM AUTHOR]

In this work, a ~21-years self-consistent global dataset from four different satellite sensors with a mid-morning overpass (GOME/ERS-2, SCIAMACHY/ENVISAT, GOME-2/Metop-A and GOME-2/Metop-B) is compiled to study the long-term tropospheric NO2 patterns and trends. The GOME and GOME-2 data are corrected relative to the SCIAMACHY data in order to reproduce what SCIAMACHY would measure if it was in orbit for the period 4/1996–9/2017. The highest tropospheric NO2 concentrations are seen over urban, industrialized and highly populated areas and over ship tracks in the oceans. Tropospheric NO2 has generally decreased during the last two decades over the industrialized and highly populated regions of the Western World (e.g. average decrease of the order of ~49% over the U.S., the Netherlands and the U.K., ~36% over Italy and Japan and ~32% over Germany and France) and increased over developing regions (e.g. average increase of ~160% over China and ~33% over India). It is suggested here that linear trends cannot be used efficiently worldwide for such long periods. Tropospheric NO2 is very sensitive to socioeconomic changes (e.g. environmental protection policies, economic recession, warfare, etc.) which may cause either short term changes or even a reversal of the trends. The application of a method capable of detecting the year when a reversal of trends happened shows that tropospheric NO2 concentrations switched from positive to negative trends and vice versa over several regions around the globe. A country-level analysis revealed clusters of countries that exhibit similar positive-to-negative or negative-to-positive reversals while 29 out of a total of 64 examined megacities and large urban agglomerations experienced a trend reversal at some point within the last two decades. [ABSTRACT FROM AUTHOR]

Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities on the international level. Harmonised, multi-decadal records of NO2 columns and their associated uncertainties can provide crucial information how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best practice NO2 retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO2, a 1° × 1° TM5-MP data assimilation scheme to estimate the stratospheric background, and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO2 algorithm on the most actual level-1 data sets to produce a complete 22-year data record that includes GOME (1995-2003), SCIAMACHY (2002-2012), GOME-2(A) (2007 onwards) and OMI (2004 onwards). The QA4ECV NO2 spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO2 columns amount to typically 40% over polluted scenes. First validation results of the QA4ECV OMI NO2 columns and their uncertainties over Tai'an, China in June 2006 suggests little bias (-27thinsp;%) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO2 long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale. [ABSTRACT FROM AUTHOR]

An operational multi-model forecasting system for air quality including 9 different chemical transport models has been developed and is providing daily forecasts of ozone, nitrogen oxides, and particulate matter for the 37 largest urban areas of China (population higher than 3 million in 2010). These individual forecasts as well as the mean and median concentrations for the next 3 days are displayed on a publicly accessible web site (http://www.marcopolo-panda.eu). The paper describes the forecasting system and shows some selected illustrative examples of air quality predictions. It presents an inter-comparison of the different forecasts performed during a given period of time (1-15 March 2017), and highlights recurrent differences between the model output as well as systematic biases that appear in the median concentration values. Pathways to improve the forecasts by the multi-model system are suggested. [ABSTRACT FROM AUTHOR]

We designed a fast procedure to detect the nitrogen oxides (NOx) sources in the China North Plain and to estimate their NOx emissions through a two-dimensional Gaussian fitting method applied to averaged Ozone Monitoring Instrument (OMI) observations of nitrogen dioxide (NO2) column concentration. The Northern China Plain is a region that has one of the highest densities of anthropogenic NOx sources in the world and therefore the sources are difficult to distinguish. With our procedure we still found 94 individual NOx emission sources. Of these sources Tangshan city has the strongest NOx emission rate (92 Gg N year–1), while the weakest that we are still able to detect is Zhangjiakou city, with a NOx emission rate of 0.4 Gg N year–1. Using the fitting results, we reconstruct the NO2 column concentration distribution map, which matches the OMI observations with an R2 = 0.85 and a slope of 0.78. The derived NOx emission rates for cities and provinces level show good agreement with former studies. [ABSTRACT FROM AUTHOR]

Aircraft measurements of NO2 using an imaging differential optical absorption spectrometer (iDOAS) instrument over the South African Highveld region in August 2007 are presented and compared to satellite measurements from OMI and SCIAMACHY. In situ aerosol and trace-gas vertical profile measurements, along with aerosol optical thickness and single-scattering albedo measurements from the Aerosol Robotic Network (AERONET), are used to devise scenarios for a radiative transfer modelling sensitivity study. Uncertainty in the air-mass factor due to variations in the aerosol and NO2 profile shape is constrained and used to calculate vertical column densities (VCDs), which are compared to co-located satellite measurements. The lower spatial resolution of the satellites cannot resolve the detailed plume structures revealed in the aircraft measurements. The airborne DOAS in general measured steeper horizontal gradients and higher peak NO2 vertical column density. Aircraft measurements close to major sources, spatially averaged to the satellite resolution, indicate NO2 column densities more than twice those measured by the satellite. The agreement between the high-resolution aircraft instrument and the satellite instrument improves with distance from the source, this is attributed to horizontal and vertical dispersion of NO2 in the boundary layer. Despite the low spatial resolution, satellite images reveal point sources and plumes that retain their structure for several hundred kilometres downwind. [ABSTRACT FROM AUTHOR]

Understanding long-term trends in aerosol loading is essential for evaluating the health and climate effects of airborne particulates as well as the effectiveness of pollution control policies. Here we introduce a method to construct a combined annual and seasonal AOD long time series using the Along-Track Scanning Radiometers (ATSR: ATSR-2 and AATSR) and MODerate resolution Imaging Spectroradiometer Terra (MODIS/Terra), which together cover the period of 1995–2017. The long-term (1995–2017) annual and seasonal combined AOD time series are presented for the all of mainland China, for southeastern (SE) China and for 10 selected regions in China and analyzed to reveal the AOD tendencies during the last 23 years. Linear regression has been applied to individual L3 (1°×1°) pixels of the annual and seasonal combined AOD time series to estimate the AOD tendencies for three periods: 1995–2006 (P1) and 2011–2017 (P2), as regarding the changes in the emission reduction policies, and the whole period 1995–2017 (WP), when combined AOD time series is available. Positive tendencies of annual AOD (0.006, or 2 % of AOD, per year) prevailed across all of mainland China before 2006 due to emission increases induced by rapid economic development. In southeastern China, the annual AOD positive tendency in 1995–2006 was 0.014, or 3 % of AOD, per year in SE China, reaching maxima (0.020, or 4 % of AOD, per year) in Shanghai and the Pearl River Delta regions. Negative AOD tendencies (−0.015, or −6 % of AOD, per year) were identified across most of China after 2011 in conjunction with effective emission reduction in anthropogenic primary aerosols, SO2 and NOx (Jin et al., 2016, van der A et al., 2017). The strongest AOD decrease is observed in Chengdu (−0.045, or −8 % of AOD, per year) and Zhengzhou (−0.046, or −9 % of AOD, per year) areas, while over the North China plane and coastal areas the AOD decrease was lower than −0.03, or ca. −6 % of AOD, per year. In the less populated areas, the AOD decrease was small. The AOD tendencies for the whole period 1995–2017 were much less pronounced compared to P1 and P2. The reason for that is that positive AOD tendency has been observed at the beginning of WP (in P1) and negative AOD tendency has been observed at the end of WP (in P2), which partly cancel each other during 1995–2017. In the WP, AOD was slightly increasing over the Beijing-Tianjin-Hebei area (0.008, or 1.3 % of AOD, per year) and the Pearl River Delta (0.004, or 0.6 % of AOD, per year). A slightly negative AOD tendency (−0.004, or −0.7 % per year) was observed in the Chengdu and Zhengzhou areas. Seasonal patterns in the AOD regional long-term trend are evident. The contribution of seasonal AOD tendencies in annual tendencies was not equal along the year. While the annual AOD tendency was positive in 1995–2006, the AOD tendencies in winter and spring were slightly negative (ca. −0.002, or −1 % of AOD, per year) over the most of China during that period. AOD tendencies were positive in summer (0.008, or 2 % of AOD, per year) and autumn (0.006, or 6 % of AOD, per year) over all mainland China and SE China (0.020, or 4 % of AOD, per year and 0.016, or 4 % of AOD, per year in summer and autumn, respectively). The AOD negative tendencies in 2011–2017 were higher compared to other seasons in summer over China (ca. −0.021, or −7 % of AOD, per year) and over SE China (ca. −0.048, or −9 % of AOD, per year). The results obtained in the current study show that the effect of the changes in the emission regulations policy in China during 1995–2017 is evident in AOD gradual decrease after 2011. The effect is more visible in the highly populated and industrialized regions in SE China. [ABSTRACT FROM AUTHOR]

Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slope=0.74 and 0.64 for the daily mean and daytime only) and the MIX (slope=1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10-40% higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of -30 to 0% on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of the model is comparable over seasons, with a slightly worse spatial correlation in summer due to the difficulties in resolving the more active NOx photochemistry and larger concentration gradients in summer by the model. In addition, the model well captures the daytime diurnal cycle but shows more significant disagreement between simulations and measurements during nighttime, which likely produces a positive model bias of about 15% in the daily mean concentrations. This is most likely related to the uncertainty in vertical mixing in the model at night. [ABSTRACT FROM AUTHOR]

Aerosol optical depth (AOD) patterns and interannual and seasonal variations over China are discussed based on the AOD retrieved from the Along-Track Scanning Radiometer (ATSR-2, 1995–2002), the Advanced ATSR (AATSR, 2002–2012) (together ATSR) and the Moderate Resolution Imaging spectrometer (MODIS) aboard the Terra satellite (2000–2017). The AOD products used were the ATSR Dual View (ADV) v2.31 AOD and MODIS/Terra Collection 6.1 (C6.1) merged dark target (DT) and deep blue (DB) AOD product. Together these data sets provide an AOD time series for 23 years, from 1995 to 2017. Differences between the MODIS C6.1 and C6 AOD products with respect to AOD coverage and validation with Aerosol Robotic Network (AERONET) over China are briefly discussed, showing better validation results for C6.1: the correlation coefficient has increased from 0.9 in C6 to 0.92 in C6.1; bias has been slightly lowered from 0.007 to 0.006. ADV and MODIS AOD validation results show similar high correlation with AERONET AOD (0.88 and 0.92, respectively), while the corresponding bias is positive for MODIS (0.06) and negative for ADV (−0.07). Validation of the AOD products in similar conditions, when ATSR and MODIS/Terra overpasses are within 90 minutes from each other and when both ADV and MODIS retrieve AOD, show that ADV performs better than MODIS in autumn, while MODIS performs slightly better in spring and summer. In winter, both ADV and MODIS underestimate AERONET AOD. Similar AOD patterns are observed by ADV and MODIS in annual and seasonal aggregates. ADV-MODIS difference maps show that MODIS AOD is generally higher than that from ADV. During the period 1995–2006, AOD was increasing in the SE of China. Between 2006 and 2011, AOD was not changing much, showing minor minima in 2008–2009. From 2011 onward, AOD is decreasing in the SE of China. Both ADV and MODIS show similar seasonal AOD behavior. The spring AOD maxima in the south is shifting from spring to summer along the eastern coast in the direction to the north. Similar patterns exist in year-to-year ADV and MODIS annual AOD tendencies in the overlapping period. The agreement between sensors in year-to-year AOD changes is quite good. The large AOD differences exist between regions, for both sensors. The consistency between ATSR and MODIS as regards the AOD tendencies in the overlapping period is rather strong in summer, autumn and overall for the yearly average, while in winter and spring, when there is a difference in coverage between the two instruments, the agreement in the AOD tendencies is lower. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to update existing sulfur dioxide (SO2) emission inventories over China using modern inversion techniques, state-of-the-art chemistry transport modelling (CTM) and satellite observations of SO2. Within the framework of the EU Seventh Framework Programme (FP7) MarcoPolo (Monitoring and Assessment of Regional air quality in China using space Observations) project, a new SO2 emission inventory over China was calculated using the CHIMERE v2013b CTM simulations, 10 years of Ozone Monitoring Instrument (OMI)/Aura total SO2 columns and the pre-existing Multi-resolution Emission Inventory for China (MEIC v1.2). It is shown that including satellite observations in the calculations increases the current bottom-up MEIC inventory emissions for the entire domain studied (15-55° N, 102-132° E) from 26.30 to 32.60 Tg annum-1, with positive updates which are stronger in winter (~36 % increase). New source areas were identified in the southwest (25-35° N, 100-110° E) as well as in the northeast (40-50° N, 120-130° E) of the domain studied as high SO2 levels were observed by OMI, resulting in increased emissions in the a posteriori inventory that do not appear in the original MEIC v1.2 dataset. Comparisons with the independent Emissions Database for Global Atmospheric Research, EDGAR v4.3.1, show a satisfying agreement since the EDGAR 2010 bottom-up database provides 33.30 Tg annum-1 of SO2 emissions. When studying the entire OMI/Aura time period (2005 to 2015), it was shown that the SO2 emissions remain nearly constant before the year 2010, with a drift of -0.51 ± 0.38 Tg annum-1, and show a statistically significant decline after the year 2010 of -1.64 ± 0.37 Tg annum-1 for the entire domain. Similar findings were obtained when focusing on the greater Beijing area (30-40° N, 110-120° E) with pre-2010 drifts of -0.17 ± 0.14 and post-2010 drifts of -0.47 ± 0.12 Tg annum-1. The new SO2 emission inventory is publicly available and forms part of the official EU MarcoPolo emission inventory over China, which also includes updated NOx, volatile organic compounds and particulate matter emissions. [ABSTRACT FROM AUTHOR]

Atmospheric ozone plays a key role in air quality and the radiation budget of the Earth, both directly and through its chemical influence on other trace gases. Assessments of the atmospheric ozone distribution and associated climate change therefore demand accurate vertically-resolved ozone observations with both stratospheric and tropospheric sensitivity, both on the global and regional scales, and both in the long term and at shorter timescales. Such observations have been acquired by two series of European nadir-viewing ozone profilers, namely the scattered-light UV-visible spectrometers of the GOME family, launched regularly since 1995 (GOME, SCIAMACHY, OMI, GOME-2A/B, TROPOMI, and the upcoming Sentinel-5 series), and the thermal infrared emission sounders of the IASI type, launched regularly since 2006 (IASI on Metop platforms and the upcoming IASI-NG on Metop-SG). In particular, several Level-2 retrieved, Level-3 monthly gridded, and Level-4 assimilated nadir ozone profile data products have been improved and harmonised in the context of the ozone project of the European Space Agency's Climate Change Initiative (ESA Ozone_cci). To verify their fitness-for-purpose, these ozone datasets must undergo a comprehensive quality assessment (QA), including (a) detailed identification of their geographical, vertical and temporal domains of validity, (b) quantification of their potential bias, noise and drift and their dependences on major influence quantities, and (c) assessment of the mutual consistency of data from different sounders. For this purpose we have applied to the Ozone_cci Climate Research Data Package (CRDP) released in 2017 the versatile QA/validation system Multi-TASTE which has been developed in the context of several heritage projects (ESA's Multi-TASTE, EUMETSAT's O3M-SAF, and the European Commission's FP6 GEOmon and FP7 QA4ECV). This work, as the second in a series of four Ozone_cci validation papers, reports for the first time on data content studies, information content studies and ground-based validation for both the GOME- and IASI-type climate data records combined. The ground-based reference measurements have been provided by the Network for the Detection of Atmospheric Composition Change (NDACC), NASA's Southern Hemisphere Additional Ozonesonde programme (SHADOZ), and other ozonesonde and lidar stations contributing to the World Meteorological Organisation's Global Atmosphere Watch (WMO GAW). Dependence of the Ozone_cci data quality on major influence quantities - resulting in data screening suggestions to users - and perspectives for the Copernicus Sentinel missions are discussed. [ABSTRACT FROM AUTHOR]

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 one 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 0.76 for GOME-2B and 0.99 for GOME-2A. 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 0.99 from about 0.6, the slope value is almost doubled (~ 0.8) and the mean satellite underestimation is reduced to about half (from ~ 7 to ~ 3.5 × 1015 molecules/cm2). 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 0.76 (d ≤ 50 km) to 0.93 (d ≤ 20 km), and the absolute mean bias decreases about 6 times for d ≤ 30 km compared to the reference case (d ≤ 50 km). [ABSTRACT FROM AUTHOR]

The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e. vertical profiles of extinction coefficients from CALIOP, a lidar flying on board the CALIPSO satellite, and the column-integrated extinction (AOD), available from three radiometers: ESA's ATSR-2, AATSR (together referred to as ATSR) and NASA's MODIS/Terra, together spanning the period 1995-2015. AOD data are retrieved from ATSR using the ADV v2.31 algorithm while for MODIS the Collection 6 (C6) DTDB merged AOD data set is used. These data sets are validated and differences are compared using AERONET version 2 L2.0 AOD data as reference. The results show that, over China, MODIS slightly overestimates the AOD and ATSR slightly underestimates the AOD. Consequently, MODIS AOD is overall higher than that from ATSR, and the difference increases with increasing AOD. The comparison also shows that none of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces where the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 DTDB merged data sets from MODIS/Terra over China is briefly discussed. The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over the whole mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when ENVISAT was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the ENVISAT period in 2012, showing decreasing AOD. [ABSTRACT FROM AUTHOR]

We present a 3-D climatology of the desert dust distribution over South-East Asia derived using CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) data. To distinguish desert dust from total aerosol load we apply a methodology developed in the framework of EARLINET (European Aerosol Research Lidar Network), the particle linear depolarization ratio and updated lidar ratio values suitable for Asian dust, on multiyear CALIPSO observations (01/2007-12/2015). The resulting dust product provides information on the horizontal and vertical distribution of dust aerosols over SE (South-East) Asia along with the seasonal transition of dust transport pathways. Persistent high D_AOD (Dust Aerosol Optical Depth) values, of the order of 0.6, are present over the arid and semi-arid desert regions. Dust aerosol transport (range, height and intensity) is subject to high seasonality, with highest values observed during spring for northern China (Taklimakan/Gobi deserts) and during summer over the Indian subcontinent (Thar Desert). Additionally we decompose the CALIPSO AOD (Aerosol Optical Depth) into dust and non-dust aerosol components to reveal the non-dust AOD over the highly industrialized and densely populated regions of SE Asia, where the non-dust aerosols yield AOD values of the order of 0.5. Furthermore, the CALIPSO-based short-term AOD and D_AOD time series and trends between 01/2007 and 12/2015 are calculated over SE Asia and over selected sub-regions. Positive trends are observed over northwest and east China and the Indian subcontinent, whereas over southeast China are mostly negative. The calculated AOD trends agree well with the trends derived from Aqua/MODIS (Moderate Resolution Imaging Spectroradiometer), although significant differences are observed over specific regions. [ABSTRACT FROM AUTHOR]

A three-dimensional global ozone distribution has been derived from assimilation of ozone profiles that were observed by satellite. By simultaneous assimilation of ozone profiles retrieved from the nadir looking satellite instruments Global Ozone Monitoring Experiment 2 (GOME-2) and Ozone Monitoring Instrument (OMI), which measure the atmosphere at different times of the day, the quality of the derived atmospheric ozone field has been improved. The assimilation is using an extended Kalman filter in which chemical transport model TM5 has been used for the forecast. The combined assimilation of both GOME-2 and OMI improves upon the assimilation results of a single sensor. The new assimilation system has been demonstrated by processing 4 years of data from 2008 to 2011. Validation of the assimilation output by comparison with sondes show that biases vary between -5 % and +10 % between the surface and 100 hPa. The biases for the combined assimilation vary between -3 % and +3 % in the region between 100 and 10 hPa where GOME-2 and OMI are most sensitive. This is a strong improvement compared to direct retrievals of ozone profiles from satellite observations. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to update existing sulphur dioxide (SO2), emission inventories over China using novel inversion techniques, state-of-the-art chemistry transport modelling (CTM), and satellite observations of SO2. Within the framework of the EU FP7 Monitoring and Assessment of Regional air quality in China using space Observations, MarcoPolo project, a new SO2 emission inventory over China was calculated using the CHIMERE v2013b CTM simulations, ten years of OMI/Aura total SO2 columns and the pre-existing Multi-resolution Emission Inventory for China (MEIC v1.2). It is shown that including satellite observations in the calculations increases the current bottom-up MEIC inventory emissions for the entire domain studied [102° to 132° E and 15° to 55° N] from 26.30 Tg/annum to 32.60 Tg/annum, with positive updates which are stronger in winter [~ 36 % increase]. New source areas where identified in the South West [25-35° N and 100-110° E] as well as in the North East [40-50° N and 120-130° E] of the domain studied as high SO2 levels were observed by OMI, resulting in increased emissions in the aposteriori inventory that do not appear in the original MEIC v1.2 dataset. Comparisons with the independent Emissions Database for Global Atmospheric Research, EDGAR v4.3.1, show a satisfying agreement since the EDGAR 2010 bottom-up database provides 33.30 Tg/annum of SO2 emissions. When studying the entire OMI/Aura time period [2005 to 2015 inclusive], it was shown that the SO2 emissions remain nearly constant before year 2010 with a drift of -0.51 ± 0.38 Tg/annum and show a statistically significant decline after year 2010 of -1.64 ± 0.37 Tg/Annum for the entire domain. Similar findings were obtained when focusing on the Greater Beijing Area [110° to 120° E and 30° to 40° N] with pre-2010 drifts of -0.17 ± 0.14 and post-2010 drifts of -0.47 ± 0.12 Tg/annum. The new SO2 emission inventory is publicly available and forms part of the official EU MarcoPolo emission inventory over China which also includes updated NOx, VOCs and PM emissions. [ABSTRACT FROM AUTHOR]