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. Chemistry transport models (CTMs) are an indispensable tool for studying and predicting atmospheric and climate effects associated with carbonaceous aerosol from open biomass burning (BB); this type of aerosol is known to contribute significantly to both global radiative forcing and to episodes of air pollution in regions affected by wildfires. Improving model performance requires systematic comparison of simulation results with measurements of BB aerosol and elucidation of possible reasons for discrepancies between them, which, by default, are frequently attributed in the literature to uncertainties in emission data. Based on published laboratory data on the atmospheric evolution of BB aerosol and using the volatility basis set (VBS) framework for organic aerosol modeling, we examined the importance of taking gas-particle partitioning and oxidation of semivolatile organic compounds (SVOCs) into account in simulations of the mesoscale evolution of smoke plumes from intense wildfires that occurred in western Russia in 2010. Biomass burning emissions of primary aerosol components were constrained with PM 10 and CO data from the air pollution monitoring network in the Moscow region. The results of the simulations performed with the CHIMERE CTM were evaluated by considering, in particular, the ratio of smoke-related enhancements in PM 10 and CO concentrations ( PM 10 and CO) measured in Finland (in the city of Kuopio), nearly 1000 km downstream of the fire emission sources. It is found that while the simulations based on a "conventional" approach to BB aerosol modeling (disregarding oxidation of SVOCs and assuming organic aerosol material to be non-volatile) strongly underestimated values of PM 10 / CO observed in Kuopio (by a factor of 2), employing the "advanced" representation of atmospheric processing of organic aerosol material resulted in bringing the simulations to a much closer agreement with the ground measurements. Furthermore, taking gas-particle partitioning and oxidation of SVOCs into account is found to result in a major improvement of the agreement of simulations and satellite measurements of aerosol optical depth, as well as in considerable changes in predicted aerosol composition and top-down BB aerosol emission estimates derived from AOD measurements.

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