Numerous wildfires provoked by an unprecedented intensive heat wave caused continuous episodes of extreme air pollution in several Russian cities and densely populated regions, including the Moscow region. This paper analyzes the evolution of the surface concentrations of CO, PM₁₀ and ozone over the Moscow region during the 2010 heat wave by integrating available ground based and satellite measurements with results of a mesoscale model. The CHIMERE chemistry transport model is used and modified to include the wildfire emissions of primary pollutants and the shielding effect of smoke aerosols on photolysis. The wildfire emissions are derived from satellite measurements of the fire radiative power and are optimized by assimilating data of ground measurements of carbon monoxide (CO) and particulate matter (PM₁₀) into the model. It is demonstrated that the optimized simulations reproduce independent observations, which were withheld during the optimisation procedure, quite adequately (specifically, the correlation coefficient of daily time series of CO and PM₁₀ exceeds 0.8) and that inclusion of the fire emissions into the model significantly improves its performance. The model results show that wildfires are the principal factor causing the observed air pollution episode associated with the extremely high levels of daily mean CO and PM₁₀ concentrations (up to 10 mg m⁻³ and 700 μg m⁻³ in the averages over available monitoring sites, respectively), although accumulation of anthropogenic pollution was also favoured by a stagnant meteorological situation. Indeed, ozone concentrations were simulated to be episodically very large (>400 μg m⁻³) even when fire emissions were omitted in the model. It was found that fire emissions increased ozone production by providing precursors for ozone formation (mainly VOC), but also inhibited the photochemistry by absorbing and scattering solar radiation. In contrast, diagnostic model runs indicate that ozone concentrations could reach very high values even without fire emissions which provide "fuel" for ozone formation, but, at the same time, inhibit it as a result of absorption and scattering of solar radiation by smoke aerosols. A comparison of MOPITT CO measurements and corresponding simulations indicates that the observed episodes of extreme air pollution in Moscow were only a part of a very strong perturbation of the atmospheric composition, caused by wildfires, over European Russia. It is estimated that 2010 fires in this region emitted ~10 Tg CO, thus more than 85% of the total annual anthropogenic CO emissions. About 30% of total CO fire emissions in European Russia are identified as emissions from peat fires.

National and European legislation over the past 20 yr, and the modernisation or removal of industrial sources, have significantly reduced European ozone precursor emissions. This study quantifies observed and modelled European ozone annual and seasonal linear trends from 158 harmonised rural background monitoring stations over a constant time period of a decade (1996–2005). Mean ozone concentrations are investigated, in addition to the ozone 5th percentiles as a measure of the baseline or background conditions, and the 95th percentiles that are representative of the peak concentration levels. This study aims to characterise and quantify surface European ozone concentrations and trends and assess the impact of the changing anthropogenic emission tracers on the observed and modelled trends. Significant (p<0.1) positive annual trends in ozone mean, 5th and 95th percentiles are observed at 54 %, 52 % and 45 % of sites respectively (85 sites, 82 sites and 71 sites). Spatially, sites in central and north-western Europe tend to display positive annual ozone trends in mean, 5th and 95th percentiles. Significant negative annual trends in ozone mean 5th and 95th percentiles are observed at 11 %, 12 % and 12 % of sites respectively (18 sites, 19 sites and 19 sites) which tend to be located in the eastern and south-western extremities of Europe. European-averaged annual trends have been calculated from the 158 sites in this study. Overall there is a net positive annual trend in observed ozone mean (0.16±0.02 ppbv yr⁻¹ (2σ error)), 5th (0.13±0.02 ppbv yr⁻¹) and 95th (0.16±0.03 ppbv yr⁻¹) percentiles, representative of positive trends in mean, baseline and peak ozone. Assessing the sensitivity of the derived overall trends to the constituent years shows that the European heatwave year of 2003 has significant positive influence and 1998 the converse effect; demonstrating the masking effect of inter-annual variability on decadal based ozone trends. The European scale 3-D CTM CHIMERE was used to simulate hourly O₃ concentrations for the period 1996–2005. Comparisons between the 158 observed ozone trends to those equivalent sites extracted from regional simulations by CHIMERE better match the observed increasing annual ozone (predominantly in central and north-western Europe) for 5th percentiles, than for mean or 95th ozone percentiles. The European-averaged annual ozone trend in CHIMERE 5th percentiles (0.13±0.01 ppbv yr⁻¹) matches the corresponding observed trend extremely well, but displays a negative trend for the 95th percentile (−0.03±0.02 ppbv yr⁻¹) where a positive ozone trend is observed. Inspection of the EU-averaged monthly means of ozone shows that the CHIMERE model is overestimating the summer month O₃ levels. In comparison to trends in EMEP emissions inventories, with the exception of Austria-Hungary, we do not find that anthropogenic NO_x and VOC reductions have a substantial effect on observed annual mean O₃ trends in the rest of Europe. On a ten year time-scale presented in this study, O₃ trends related to anthropogenic NO_x and VOC reductions are being masked as a result of a number of factors including meteorological variability, changes in background ozone and shifts in source patterns.

The recent important developments in satellite measurements of the composition of the lower atmosphere open the challenging perspective to use such measurements as independent information on sources and sinks of atmospheric pollutants. This study explores the possibility to improve estimates of gridded NOx emissions used in a continental scale chemistry transport model (CTM), CHIMERE, by employing measurements performed by the GOME and SCIAMACHY instruments. We set-up an original inverse modelling scheme that not only enables a computationally efficient optimisation of the spatial distribution of seasonally averaged NOx emissions (during summertime), but also allows estimating uncertainties in input data and a priori emissions. The key features of our method are (i) replacement of the CTM by a set of empirical models describing the relationships between tropospheric NO2 columns and NOx emissions with sufficient accuracy, (ii) combination of satellite data for tropospheric NO2 columns with ground based measurements of near surface NO2 concentrations, and (iii) evaluation of uncertainties in a posteriori emissions by means of a special Bayesian Monte-Carlo experiment which is based on random sampling of errors of both NO2 columns and emission rates. We have estimated the uncertainty in a priori emissions based on the EMEP emission inventory to be about 1.9 (in terms of geometric standard deviation) and found the uncertainty in a posteriori emissions obtained from our inverse modelling scheme to be significantly lower (about 1.4). It is found also that a priori NOx emission estimates are probable to be persistently biased in many regions of Western Europe, and that the use of a posteriori emissions in the CTM improves the agreement between the modelled and measured data.

Fossil-fuel (FF) burning releases carbon dioxide (CO₂) together with many other chemical species, some of which, such as nitrogen dioxide (NO₂) and carbon monoxide (CO), are routinely monitored from space. This study examines the feasibility of estimation of FF CO₂ emissions from large industrial regions by using NO₂ and CO column retrievals from satellite measurements in combination with simulations by a mesoscale chemistry transport model (CTM). To this end, an inverse modeling method is developed that allows estimating FF CO₂ emissions from different sectors of the economy, as well as the total CO₂ emissions, in a given region. The key steps of the method are (1) inferring "top-down" estimates of the regional budget of anthropogenic NO_x and CO emissions from satellite measurements of proxy species (NO₂ and CO in the case considered) without using formal a priori constraints on these budgets, (2) the application of emission factors (the NO_x-to-CO₂ and CO-to-CO₂ emission ratios in each sector) that relate FF CO₂ emissions to the proxy species emissions and are evaluated by using data of "bottom-up" emission inventories, and (3) cross-validation and optimal combination of the estimates of CO₂ emission budgets derived from measurements of the different proxy species. Uncertainties in the top-down estimates of the NO_x and CO emissions are evaluated and systematic differences between the measured and simulated data are taken into account by using original robust techniques validated with synthetic data. To examine the potential of the method, it was applied to the budget of emissions for a western European region including 12 countries by using NO₂ and CO column amounts retrieved from, respectively, the OMI and IASI satellite measurements and simulated by the CHIMERE mesoscale CTM, along with the emission conversion factors based on the EDGAR v4.2 emission inventory. The analysis was focused on evaluation of the uncertainty levels for the top-down NO_x and CO emission estimates and "hybrid" estimates (that is, those based on both atmospheric measurements of a given proxy species and respective bottom-up emission inventory data) of FF CO₂ emissions, as well as on examining consistency between the FF NO₂ emission estimates derived from measurements of the different proxy species. It is found that NO₂ measurements can provide much stronger constraints to the total annual FF CO₂ emissions in the study region than CO measurements, the accuracy of the NO₂-measurement-based CO₂ emission estimate being mostly limited by the uncertainty in the top-down NO_x emission estimate. Nonetheless, CO measurements are also found to be useful as they provide additional constraints to CO₂ emissions and enable evaluation of the hybrid FF CO₂ emission estimates obtained from NO₂ measurements. Our most reliable estimate for the total annual FF CO₂ emissions in the study region in 2008 (2.71 ± 0.30 Pg CO₂) is found to be about 11 and 5 % lower than the respective estimates based on the EDGAR v.4.2 (3.03 Pg CO₂) and CDIAC (2.86 Pg CO₂) emission inventories, with the difference between our estimate and the CDIAC inventory data not being statistically significant. In general, the results of this study indicate that the proposed method has the potential to become a useful tool for identification of possible biases and/or inconsistencies in the bottom-up emission inventory data regarding CO₂, NO_x, and CO emissions from fossil-fuel burning in different regions of the world.

Long-term satellite measurements of nitrogen dioxide in the troposphere are used in combination with a continental scale air quality model in order to verify and improve available estimates of multi-annual changes of emissions of nitrogen oxides (NO_x) in Europe and the Mediterranean area between 1996 and 2005. As a result, a measurement-based data set of NO_x emissions on a 1° by 1° grid and averaged over summer months is elaborated. The results are compared with emission data based on the EMEP emission inventory. Our data are in agreement with the EMEP estimates suggesting a general decline in the level of NO_x emissions in Western and Central European countries (France, Germany, Great Britain and Poland). Over Southern Europe and for shipping emissions, neutral to positive trends are found both for the inverted and bottom-up emissions. In contrast, considerable differences between both data sets are found in some other countries. In particular, significant negative trends instead of the positive ones in the "bottom-up" inventory are found for the Balkan countries, Russia and Turkey. The NO_x emission trends derived from satellite measurements demonstrate larger spatial heterogeneity than those calculated with the EMEP data, especially in Russia and Ukraine. The obtained estimates of the decadal trends in NO_x emissions for Great Britain are found to be consistent with independent data from the U.K. Automatic Urban and Rural Network (AURN). It is also found that using our emission estimates yields better agreement of model calculations with near-surface ozone measurements of the European EMEP network.