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.

[1] In this paper we present a model of the dissolved organic carbon (DOC) concentrations and fluxes in mire water based on the convection-dispersion equation. The dynamics of sorbed, potentially soluble organic carbon (SPSOC) in the peat matrix are simulated in parallel with DOC. First, the model is applied solely to stagnant water conditions in order to interpret the results of laboratory peat incubations, with the focus on sorption processes. Some important model parameters are derived using literature data complemented by information from new incubation experiments. Second, the model is fully applied to simulate the DOC concentrations in the outlet of a steam draining a small headwater mire in northern Sweden during the period 1993-2001. A relatively good model fit (mean bias error (MBE) = À0.6-2.2 mg L À1 , Willmott index of agreement d > 0.7 for the daily concentrations) was found for all the categories of stream discharge, except periods with very low flow (q < 0.3 mm d À1 ). When seeking explanations for the interannual variability in DOC concentrations, we, like previous authors, could find the influence of temperature, flow path, and intensity. However, the model has helped to demonstrate that the system also has a ''memory'': the store of sorbed, potentially soluble organic carbon in a year affects the DOC concentrations and fluxes in the following year.

A B S T R A C T Possible future changes in Baltic Sea acidÁbase (pH) and oxygen balances were studied using a catchmentÁsea coupled model system and numerical experiments based on meteorological and hydrological forcing datasets and scenarios. By using objective statistical methods, climate runs for present climate conditions were examined and evaluated using Baltic Sea modelling. The results indicate that increased nutrient loads will not inhibit future Baltic Sea acidification; instead, the seasonal pH cycle will be amplified by increased biological production and mineralization. All examined scenarios indicate future acidification of the whole Baltic Sea that is insensitive to the chosen global climate model. The main factor controlling the direction and magnitude of future pH changes is atmospheric CO 2 concentration (i.e. emissions). Climate change and land-derived changes (e.g. nutrient loads) affect acidification mainly by altering the seasonal cycle and deep-water conditions. Apart from decreasing pH, we also project a decreased saturation state of calcium carbonate, decreased respiration index and increasing hypoxic area Á all factors that will threaten the marine ecosystem. We demonstrate that substantial reductions in fossil-fuel burning are needed to minimise the coming pH decrease and that substantial reductions in nutrient loads are needed to reduce the coming increase in hypoxic and anoxic waters.

[1] In mires, which occupy large areas of the boreal region, net ecosystem CO 2 exchange (NEE) rates vary significantly over various timescales. In order to examine the effect of one of the most influencing variables, the water table depth, on NEE the general ecosystem model GUESS-ROMUL was modified to predict mire daily CO 2 exchange rates. A simulation was conducted for a lawn, the most common microtopographical feature of boreal oligotrophic minerotrophic mires. The results were validated against eddy covariance CO 2 flux measurements from Degerö Stormyr, northern Sweden, obtained during the period [2001][2002][2003]. Both measurements and model simulations revealed that CO 2 uptake was clearly controlled by interactions between water table depth and temperature. Maximum uptake occurred when the water table level was between 10 and 20 cm and the air temperature was above 15°C. When the water table was higher, the CO 2 uptake rate was lower, owing to reduced rates of photosynthetic carbon fixation. When the water table was lower, NEE decreased owing to the increased rate of decomposition of organic matter. When the water table level was between 10 and 20 cm, the NEE was quite stable and relatively insensitive to both changes within this range and any air temperature changes above +15°C. The optimal water table level range for NEE corresponds to that characteristic of mire lawn plant communities, indicating that the annual NEE will not change dramatically if climatic conditions remain within the optimal range for the current plant community.

Abstract. This study compares the CH 4