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Tropospheric NO2 , a key pollutant in particular in cities, has been measured from space since the mid-1990s by the GOME, SCIAMACHY, OMI, and GOME-2 instruments. These data provide a unique global long-term dataset of tropospheric pollution. However, the observations differ in spatial resolution, local time of measurement, viewing geometry, and other details. All these factors can severely impact the retrieved NO2 columns. In this study, we present three ways to account for instrumental differences in trend analyses of the NO2 columns derived from satellite measurements, while preserving the individual instruments' spatial resolutions. For combining measurements from GOME and SCIAMACHY into one consistent time series, we develop a method to explicitly account for the instruments' difference in ground pixel size (40 × 320 km2 vs. 30 × 60 km2 ). This is especially important when analysing NO2 changes over small, localised sources like, e.g. megacities. The method is based on spatial averaging of the measured earthshine spectra and extraction of a spatial pattern of the resolution effect. Furthermore, two empirical corrections, which summarise all instrumental differences by including instrument-dependent offsets in a fitted trend function, are developed. These methods are applied to data from GOME and SCIAMACHY separately, to the combined time series, and to an extended dataset comprising also GOME-2 and OMI measurements. All approaches show consistent trends of tropospheric NO2 for a selection of areas on both regional and city scales, for the first time allowing consistent trend analysis of the full time series at high spatial resolution. Compared to previous studies, the longer study period leads to significantly reduced uncertainties. We show that measured tropospheric NO2 columns have been strongly increasing over China, the Middle East, and India, with values over east-central China tripling from 1996 to 2011. All parts of the developed world, including Western Europe, the United States, and Japan, show significantly decreasing NO2 amounts in the same time period. On a megacity level, individual trends can be as large as +27.2 ± 3.9% yr-1 and +20.7 ± 1.9% yr-1 in Dhaka and Baghdad, respectively, while Los Angeles shows a very strong decrease of -6.00 ± 0.72% yr-1 . Most megacities in China, India, and the Middle East show increasing NO2 columns of +5 to 10% yr-1 , leading to a doubling to tripling within the study period.

Global CO 2 emissions are usually assessed from uncertain bottom-up estimates. A satellite-based top-down estimate suggests that emissions of NO x in East Asia have been reduced relative to those of CO 2 since 2003, probably due to cleaner technology. At present, global CO 2  emission inventories are mainly based on bottom-up estimates that rely, for example, on reported fossil fuel consumptions and fuel types 1 , 2 . The associated uncertainties propagate into the CO 2 -to-NO x  emission ratios that are used in pollution prediction and monitoring 3 , as well as into biospheric carbon fluxes derived by inverse models 4 . Here we analyse simultaneous and co-located satellite retrievals from SCIAMACHY (ref.  5 ; SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) of the column-average dry-air mole fraction of CO 2 (refs  6 , 7 ) and NO 2 (refs  8 , 9 , 10 ) for the years 2003–2011 to provide a top-down estimate of trends in emissions and in the ratio between CO 2 and NO x emissions. Our analysis shows that the CO 2 -to-NO x  emission ratio has increased by 4.2 ± 1.7% yr −1 in East Asia. In this region, we find a large positive trend of CO 2  emissions (9.8 ± 1.7% yr −1 ), which we largely attribute to the growing Chinese economy. This trend exceeds the positive trend of NO x  emissions (5.8 ± 0.9% yr −1 ). Our findings suggest that the recently installed and renewed technology in East Asia, such as power plants, transportation and so on, is cleaner in terms of NO x  emissions than the old infrastructure, and roughly matches relative emission levels in North America and Europe.

The role and potential management of short-lived atmospheric pollutants such as aerosols are currently a topic of scientific and public debates. Our limited knowledge of atmospheric aerosol and its influence on the Earth's radiation balance has a significant impact on the accuracy and error of current predictions of future climate change. In the last few years, there have been several accounts of the changes in atmospheric aerosol derived from satellite observations, but no study considering the uncertainty caused by different/limited temporal sampling of polar-orbiting satellites and cloud disturbance in the trend estimates of cloud-free aerosol optical thickness (AOT). This study presents an approach to minimize the uncertainties by use of weighted least-squares regression and multiple satellite-derived AOTs from the space-born instruments, MODIS (onboard Terra from 2000 to 2009 and Aqua form 2003 to 2008), MISR (Terra from 2000 to 2010), and SeaWiFS (OrbView-2 from 1998 to 2007) and thereby provides more convincing trend estimates for atmospheric aerosols during the past decade. The AOT decreases over western Europe (i.e., by up to about −40% from 2003 to 2008). In contrast, a statistically significant increase (about +34% in the same period) over eastern China is observed and can be attributed to the increase in both industrial output and Asian desert dust.

Satellite observations of nitrogen dioxide (NO2 ) provide valuable information on both stratospheric and tropospheric composition. Nadir measurements from GOME, SCIAMACHY, OMI, and GOME-2 have been used in many studies on tropospheric NO2 burdens, the importance of different NOx emissions sources and their change over time. The observations made by the three GOME-2 instruments will extend the existing data set by more than a decade, and a high quality of the data as well as their good consistency with existing time series is of particular importance. In this paper, an improved GOME-2 NO2 retrieval is described which reduces the scatter of the individual NO2 columns globally but in particular in the region of the Southern Atlantic Anomaly. This is achieved by using a larger fitting window including more spectral points, and by applying a two step spike removal algorithm in the fit. The new GOME-2 data set is shown to have good consistency with SCIAMACHY NO2 columns. Remaining small differences are shown to be linked to changes in the daily solar irradiance measurements used in both GOME-2 and SCIAMACHY retrievals. In the large retrieval window, a not previously identified spectral signature was found which is linked to deserts and other regions with bare soil. Inclusion of this empirically derived pseudo cross-section significantly improves the retrievals and potentially provides information on surface properties and desert aerosols. Using the new GOME-2 NO2 data set, a long-term average of tropospheric columns was computed and high-pass filtered. The resulting map shows evidence for pollution from several additional shipping lanes, not previously identified in satellite observations. This illustrates the excellent signal to noise ratio achievable with the improved GOME-2 retrievals.

Hazardous impact of air pollutant emissions from megacities on atmospheric composition on regional and global scales is currently an important issue in atmospheric research. However, the quantification of emissions and related effects is frequently a difficult task, especially in the case of developing countries, due to the lack of reliable data and information. This study examines possibilities to retrieve multi-annual NOx emissions changes in megacity regions from satellite measurements of nitrogen dioxide and to quantify them in terms of linear and nonlinear trends. By combining the retrievals of the GOME and SCIAMACHY satellite instrument data with simulations performed by the CHIMERE chemistry transport model, we obtain the time series of NOx emission estimates for the 12 largest urban agglomerations in Europe and the Middle East in the period from 1996 to 2008. We employ then a novel method allowing estimation of a nonlinear trend in a noisy time series of an observed variable. The method is based on the probabilistic approach and the use of artificial neural networks; it does not involve any quantitative a priori assumptions. As a result, statistically significant nonlinearities in the estimated NOx emission trends are detected in 5 megacities (Bagdad, Madrid, Milan, Moscow and Paris). Statistically significant upward linear trends are detected in Istanbul and Tehran, while downward linear trends are revealed in Berlin, London and the Ruhr agglomeration. The presence of nonlinearities in NOx emission changes in Milan, Paris and Madrid is confirmed by comparison of simulated NOx concentrations with independent air quality monitoring data. A good quantitative agreement between the linear trends in the simulated and measured near surface NOx concentrations is found in London.

Satellite observations from the SCIAMACHY, GOME-2 and OMI spectrometers have been used to retrieve atmospheric columns of glyoxal (CHOCHO) with the DOAS method. High CHOCHO levels were found over regions with large biogenic and pyrogenic emissions, and hot-spots have been identified over areas of anthropogenic activities. This study focuses on the development of an improved retrieval for CHOCHO from measurements by the OMI instrument. From sensitivity tests, a fitting window and a polynomial degree are determined. Two different approaches to reduce the interference of liquid water absorption over oceanic regions are evaluated, achieving significant reduction of the number of negative columns over clear water regions. The impact of using different absorption cross-sections for water vapour is evaluated and only small differences are found. Finally, a high-temperature (boundary layer ambient: 294 K) absorption cross-section of nitrogen dioxide (NO2) is introduced in the DOAS retrieval to account for potential interferences of NO2 over regions with large anthropogenic emissions, leading to improved fit quality over these areas. A comparison with vertical CHOCHO columns retrieved from GOME-2 and SCIAMACHY measurements over continental regions is performed, showing overall good consistency. However, SCIAMACHY CHOCHO columns are systematically higher than those obtained from the other instruments. Using the new OMI CHOCHO data set, the link between fires and glyoxal columns is investigated for two selected regions in Africa. In addition, mapped averages are computed for a fire event in Russia between mid-July and mid-August 2010. In both cases, enhanced CHOCHO levels are found in close spatial and temporal proximity to elevated levels of MODIS fire radiative power, demonstrating that pyrogenic emissions can be clearly identified in the new OMI CHOCHO product.

The Monitoring Atmospheric Composition and Climate (MACC) project represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu/), which became fully operational during 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5-day forecasts of atmospheric composition fields. It is the only assimilation system worldwide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases covering the period between 2009 and 2012. A validation was performed based on carbon monoxide (CO), nitrogen dioxide (NO2) and ozone (O3) surface observations from the Global Atmosphere Watch (GAW) network, the O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and, furthermore, NO2 tropospheric columns, as well as CO total columns, derived from satellite sensors. The MACC system proved capable of reproducing reactive gas concentrations with consistent quality; however, with a seasonally dependent bias compared to surface and satellite observations – for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the year, with monthly modified normalised mean biases (MNMBs) ranging between −30 and 30 % at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterisation. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at their highest level, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range from values between −110 and 40 % for NO2 and at most −20 % for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterisation and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

The hot summer of 2007 in southeast Europe has been studied using two regional atmospheric chemistry models; WRF-Chem and EMEP MSC-W. The region was struck by three heat waves and a number of forest fire episodes, greatly affecting air pollution levels. We have focused on ozone and its precursors using state-of-the-art inventories for anthropogenic, biogenic and forest fire emissions. The models have been evaluated against measurement data, and processes leading to ozone formation have been quantified. Heat wave episodes are projected to occur more frequently in a future climate, and therefore this study also makes a contribution to climate change impact research. The plume from the Greek forest fires in August 2007 is clearly seen in satellite observations of CO and NO2 columns, showing extreme levels of CO in and downwind of the fires. Model simulations reflect the location and influence of the fires relatively well, but the modelled magnitude of CO in the plume core is too low. Most likely, this is caused by underestimation of CO in the emission inventories, suggesting that the CO/NOx ratios of fire emissions should be re-assessed. Moreover, higher maximum values are seen in WRF-Chem than in EMEP MSC-W, presumably due to differences in plume rise altitudes as the first model emits a larger fraction of the fire emissions in the lowermost model layer. The model results are also in fairly good agreement with surface ozone measurements. Biogenic VOC emissions reacting with anthropogenic NOx emissions are calculated to contribute significantly to the levels of ozone in the region, but the magnitude and geographical distribution depend strongly on the model and biogenic emission module used. During the July and August heat waves, ozone levels increased substantially due to a combination of forest fire emissions and the effect of high temperatures. We found that the largest temperature impact on ozone was through the temperature dependence of the biogenic emissions, closely followed by the effect of reduced dry deposition caused by closing of the plants' stomata at very high temperatures. The impact of high temperatures on the ozone chemistry was much lower. The results suggest that forest fire emissions, and the temperature effect on biogenic emissions and dry deposition, will potentially lead to substantial ozone increases in a warmer climate.

Satellite and aircraft observations made during the 2006 Texas Air Quality Study (TexAQS) detected strong urban, industrial and power plant plumes in Texas. We simulated these plumes using the Weather Research and Forecasting-Chemistry (WRF-Chem) model with input from the US EPA's 2005 National Emission Inventory (NEI-2005), in order to evaluate emissions of nitrogen oxides (NOx = NO + NO2 ) and volatile organic compounds (VOCs) in the cities of Houston and Dallas-Fort Worth. We compared the model results with satellite retrievals of tropospheric nitrogen dioxide (NO2 ) columns and airborne in-situ observations of several trace gases including NOx and a number of VOCs. The model and satellite NO2 columns agree well for regions with large power plants and for urban areas that are dominated by mobile sources, such as Dallas. However, in Houston, where significant mobile, industrial, and in-port marine vessel sources contribute to NOx emissions, the model NO2 columns are approximately 50%-70% higher than the satellite columns. Similar conclusions are drawn from comparisons of the model results with the TexAQS 2006 aircraft observations in Dallas and Houston. For Dallas plumes, the model-simulated NO2 showed good agreement with the aircraft observations. In contrast, the model-simulated NO2 is ~60% higher than the aircraft observations in the Houston plumes. Further analysis indicates that the NEI-2005 NOx emissions over the Houston Ship Channel area are overestimated while the urban Houston NOx emissions are reasonably represented. The comparisons of model and aircraft observations confirm that highly reactive VOC emissions originating from industrial sources in Houston are underestimated in NEI-2005. The update of VOC emissions based on Solar Occultation Flux measurements during the field campaign leads to improved model simulations of ethylene, propylene, and formaldehyde. Reducing NOx emissions in the Houston Ship Channel and increasing highly reactive VOC emissions from the point sources in Houston improve the model's capability of simulating ozone (O3 ) plumes observed by the NOAA WP-3D aircraft, although the deficiencies in the model O3 simulations indicate that many challenges remain for a full understanding of the O3 formation mechanisms in Houston.

Intercontinental long-range transport (LRT) events of NO2 relocate the effects of air pollution from emission regions to remote, pristine regions. We detect transported plumes in tropospheric NO2 columns measured by the GOME-2/MetOp-A instrument with a specialized algorithm and trace the plumes to their sources using the HYSPLIT Lagrangian transport model. With this algorithm we find 3808 LRT events over the ocean for the period 2007 to 2011. LRT events occur frequently in the mid-latitudes, emerging usually from coastal high-emission regions. In the free troposphere, plumes of NO2 can travel for several days to the polar oceanic atmosphere or to other continents. They travel along characteristic routes and originate from both continuous anthropogenic emission and emission events such as bush fires. Most NO2 LRT events occur during autumn and winter months, when meteorological conditions and emissions are most favorable. The evaluation of meteorological data shows that the observed NO2 LRT is often linked to cyclones passing over an emission region.