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 elucidating 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 regarding atmospheric evolution of BB aerosol and by using the volatility basis set (VBS) approach to organic aerosol modeling along with a "conventional" approach, we examined the importance of taking gas-particle partitioning and oxidation of semi-volatile organic compounds (SVOCs) into account in simulations of the mesoscale evolution of smoke plumes from intense wildfires that occurred in western Russia in 2010. BB emissions of primary aerosol components were constrained with the 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 (ΔPM 10 and ΔCO) measured in Finland (in the city of Kuopio), nearly 1000 km downstream of the fire emission sources. It is found that while the conventional approach (disregarding oxidation of SVOCs and assuming organic aerosol material to be non-volatile) strongly underestimates values of ΔPM 10 /ΔCO observed in Kuopio (by almost a factor of two), the VBS approach is capable to bring the simulations to a reasonable agreement with the ground measurements both in Moscow and in Kuopio. Using the VBS instead of the conventional approach is also 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.