Atmospheric impacts of the 2010 Russian wildfires: integrating modelling and measurements of an extreme air pollution episode in the Moscow region

Abstract

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.

Impacts of aerosol-radiation feedback on local air quality during a severe haze episode in Nanjing megacity, eastern China

“…Since then, numerous new generations of on-line-coupled models have been developed worldwide, such as Multiscale Climate Chemistry Model (MCCM) (Grell et al, 2000), Weather Research and Forecasting-Chemistry (WRF-Chem) (Grell et al, 2005) and Global Environmental Multi-scale-Modeling Air quality and CHemistry (GEM-MACH) (Moran et al, 2010). These models have been widely used for Europe and North America and they found that the interactions between meteorology and chemistry can be significant during strong air pollution episodes (Grell et al, 2011;Konovalov et al, 2011;Wong et al, 2012;Chen et al, 2014;Kong et al, 2015;Liu et al, 2016).…”

Sensitivity of feedback effects in CBMZ/MOSAIC chemical mechanism

“…On the other hand, depending of the absorbing characteristics of the aerosols (mineral dust, black carbon …) they could energize convective clouds and thus increasing precipitation (Levin and Brenguier, 2009). Feedback effects can be particularly important during strong particles episodes (Konovalov et al, 2011;Chen et al, 2014;Wong et al, 2012).…”

Inverse Modeling of Nitrogen Oxides Emissions from the 2010 Russian Wildfires by Using Satellite Measurements of Nitrogen Dioxide

“…The model documentation and the source code can be downloaded from the CHIMERE website [33]. CHIMERE was successfully used in a number of studies, including those dedicated to investigations of atmospheric effects of wildfires (e.g., [19,21,34,35]). …”

“…Fire emissions were calculated and introduced into CHIMERE by using the emission model that had been successfully used and described in detail earlier [19,21,36]. Briefly, it assumes that the BB emission rate, E s , of a species, s, in a given grid cell of the horizontal domain in an hour, t, is proportional to the daily mean FRP values, Фd, that were inferred from daily maximum FRP values derived from the MODIS measurements (see Section 2.1.1) for a given grid cell:…”

“…We focused on the disastrous mega-fire event that took place in the European part of Russia in 2010. Emissions of some pollutants (such as CO and aerosol) from the Russian 2010 fires were already investigated using inverse methods (e.g., [19][20][21]), but, to the best of our knowledge, there have yet been no similar studies focusing on NOx emissions from those fires.…”