Abstract. 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, PM 10 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 (PM 10 ) 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 PM 10 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 PM 10 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 sitCorrespondence to: I. B. Konovalov (konov@appl.sci-nnov.ru) uation. 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.

Abstract. Important aspects of the seasonal variations of surface ozone are discussed. The underlying analysis is based on the long-term (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004) ozone records of the Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP) and the World Data Centre of Greenhouse Gases, which provide data mostly for the Northern Hemisphere. Seasonal variations are pronounced at most of the 114 locations at all times of the day. A seasonal-diurnal variations classification using hierarchical agglomeration clustering reveals 6 distinct clusters: clean background, rural, semipolluted non-elevated, semi-polluted semi-elevated, elevated and polar/remote marine. For the "clean background" cluster the seasonal maximum is observed in March-April, both for night and day. For those sites with a double maximum or a wide spring-summer maximum, the spring maximum appears both for day and night, while the summer maximum is more pronounced for daytime and hence can be attributed to photochemical processes. The spring maximum is more likely caused by dynamical/transport processes than by photochemistry as it is observed in spring for all times of the day. We compare the identified clusters with corresponding data from the 3-D atmospheric chemistry general circulation model ECHAM5/MESSy1 covering the period of 1998-2005. For the model output as for the measurements 6 clusters are considered. The simulation shows at most of the sites a spring seasonal maximum or a broad spring-summer maximum (with higher summer mixing ratios). For southern hemispheric and polar remote locations the seasonal maximum in the simulation is shifted to spring, while the absolute mixing ratios are in good agreement with the measurements. The seasonality in the model cluster covering background locations is characterized by a pronounced spring (AprilMay) maximum. For the model clusters which cover rural Correspondence to: O. A. Tarasova (tarasova@mpch-mainz.mpg.de) and semi-polluted sites the role of the photochemical production/destruction seems to be overestimated. Taking into consideration the differences in the data sampling procedure, the comparison demonstrates the ability of the model to reproduce the main regimes of surface ozone variations quite well.

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Numerous wildfires provoked by an unprecedented intensive heat wave caused continuous episodes of extreme air pollution in several Russian cities and densely pullulated regions, including the Moscow megacity region. This paper analyzes the chemical evolution of the atmosphere over the Moscow region during the 2010 heat wave by integrating available ground based and satellite measurements with results of meso-scale modeling. The state-of-the-art CHIMERE CTM is used, which is modified to take into account air pollutant emissions from wildfires and the shielding effect of smoke aerosols. The wild fire 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 results of the analysis show that wildfires were a principal factor causing the observed air pollution episodes associated with the extremely high level 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) in the Moscow region, although accumulation of anthropogenic pollution was also favoured by a stagnant meteorological situation. 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. The analysis of MOPITT CO measurements and of 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 the largest part of European Russia. It is estimated that 2010 fires in the European part of Russia emitted ~9.7 Tg CO, that is more than 85% of the total annual anthropogenic CO emissions in this region. About 30% of total CO fire emissions in European Russia are identified as emissions from peat fires