Formation of gases and aerosol composition in background and urban areas of Western Siberia: a case study for the record-breaking hot April of 2020

This paper presents results of a comprehensive analysis of the formation of gases and aerosol composition during the anomalously hot April 2020 in Western Siberia. The analysis of the observed change in atmospheric composition and a modeling study with the WRF-Chem is carried out for suburban (TOR-station) and background (FON-station) areas. Two episodes of increased gases and aerosols were detected:13-15 April with a peak on 14 (in most part for the TOR station: increased NO, NO2, CO, CO2, aerosols) and 17-24 April with a peak on 23 (for both stations O3, aerosol, in most part for the FON station: NO2, SO2, CO, and CO2). Atmospheric circulation in the first episode was characterized by mesoscale differences between the two studied locations (surface temperature delta, although both stations are in the same region of large-scale transfers). For the second episode, a large scale atmospheric ridge was observed, which caused a transboundary transfer from Northern Kazakhstan and early wildfires. The simulation with WRF has demonstrated in most cases only the role of wildfires and, in general, has not demonstrated any observed differences between the two episodes. It shows that there is a need to search for more sensitive methods of discovering sources of pollution.


Introduction
The study of changes in the gases and aerosol composition during the period of observed climatic changes is necessary. There are many feedbacks associated with the chemical composition of the atmosphere and climate system. One of the exciting aspects of this matter is the study of the influence of extreme episodes associated with atmospheric circulation and changes in surface temperature. April 2020 was the second abnormally hot (the first one was in 2016) for our planet. The global temperature anomaly was 1.06°С (April 2020: another month that was the second warmest on record, https://bit.ly/3hWwibW). The most pronounced temperature anomalies were characteristic of Western Siberia, where the average monthly temperature exceeded the norm by an average of 5°C, and in the northern regions of Western Siberia by 10-12°C. According to the Russian weather services departments for Western Siberia, April 2020 was the first hottest April (https://ria.ru/20200420/1570277368.html, https://bit.ly/2Z6Cabk).
In the present paper, first we discuss the changes observed in the gas and aerosol composition during an abnormally warm April, analyze the circulation patterns associated with the transfer of air 2 masses, as well as the formation of atmospheric blocking conditions. The relevance of this study is connected both with the unusual weather conditions of April 2020 and with the fact that mainly the influence of circulation on the formation of the gas and aerosol composition of the atmosphere was considered for the winter and summer periods [1,2], and to a lesser extent during the transitional seasons. In the second part of the paper, we compare the modeled with WRF-Chem data with the changes observed in the gas (CO, NO, NO 2 , SO 2 , O 3 ) and aerosol composition during the abnormally warm April. This allows us to make some conclusions about the quality of simulation for extremal conditions of background and suburban areas.
To clarify the period and position of blocking processes, we use a GHGS (geopotential heightgradient south) criterion developed in [8][9][10] (equation 1). We use the GHGS with the fix blocking latitude (φ fix ) and flexible blocking latitude (φ flex ) based on [11], where Z is the 500 hPa geopotential height, for φ fix : Unlike [8,9], we took the following values for Δ: -5°, -2.5°, 0°, 2.5°, or 5°, which were first offered in [10]. To clarify the blocking dates, we also used the potential temperature on the dynamic tropopause (PV-θ). According to [12], PV-θ is a perfect candidate for studying the development of blocking since it is materially conserved in time, providing an excellent tracer for the air masses contributing to blocking formation, and can be inverted to give a balanced component of the flow. Also, the reversal of the meridional gradient PV-θ is associated with Rossby wave-breaking [12].
The simulation was carried out by WRF-Chem v 4.12 [14]. For the numerical simulation, the domain in the Lambert projection was used, limited horizontally by -45-74°N and 40-105°E and with the height from the ground to 50 hPa. The number of nodes in the computational domain was 99x104x21 in longitude, latitude, and height, respectively. The horizontal grid spacing was 4 km, a variable time modeling step was used in the range from 30 to 300 s for the meteorological parameters and 6 s for the chemical reactions, the grid step-in height was given by the ETA coordinate taking into account the orographic surface, and increased with increasing height. The height of the lower level was 50 m, and the relief data was set with a resolution of 30".
As the initial meteorological values we used the data of the FNL (NCEP) model [15] with a 6-hour time resolution. Fields of the initial FNL meteorological data were obtained based on GFS data using an increased volume of observational data. The source of anthropogenic emissions HTAP-2 [16] was used to specify the emission sources; methane emissions were supplemented from the EDGAR V.  [17] with a spatial resolution of 0.1x0.1° and a time resolution of 1 month. The power of the sources was set constant without taking into account the intraday and weekly dynamics of the emissions. The emission sources were specified in the surface layer.
Biogenic emissions were set using the MEGAN2.04 model [18], and emissions from fires were FINN v1.5 [19]. Emissions from swamps were set with constant values using the results of MACC II inverse modeling for 2012 [20]. The initial and boundary conditions for the chemicals were set using the global Mozart4 model for 2013 and the WACCM model for 2020. The parameterizations used in the Wrf-Chem model are: microphysics -Morrison; long-wave radiation -RRTM; shortwave radiation -Dudhia; surface layer -Rev. MM5; surface model -Noah; boundary planetary layer -Yonsei Univ.; cloud parameterization -Grell 3D. The WRF-Chem emission module code has been upgraded to allow methane emissions from fires and bioemissions to be read. In the calculations, the chemical mechanism MOZART-4 [22] was used together with the aerosol mechanism MOZAIC [21]. The chemical block of the model uses 85 substances, 157 reactions, and 39 photochemical ones. The aerosol block allows calculations for 4 size ranges, with median diameters of 0.078125, 0.3125, 1.25, and 5 . Figure 1 shows the gas and aerosol concentration in April 2020, the surface temperature measured at the TOR station, and the GHGS blocking conditions. According to Figure 1, two episodes of an increase in the concentration of gases and aerosols for the stations can be distinguished (shown by gray bars in the figure). Let us consider both episodes in detail. . The studied areas were in a baric saddle according to the maps of the 500 hPa geopotential. However, an extremely curious fact is that the temperature difference for the regions in the single circulation zone was 3.4 °C. For the suburban area, the daily average temperature was significantly higher. In this period there were no wildfire areas around both stations. The likely cause of the differences in the gas and aerosol composition may be the mesoscale circulation conditions, as well as the influence of the urban area for the TOR-station or/and the Ob River for the FON-station.

The observed change in gas and aerosol compositions, atmospheric circulation features
2nd event: April 17-24 with a maximum of April 23. First of all, attention is drawn to the change in the ozone concentration for both stations (The O 3 was almost two times higher than average for 2009-2018 April for the Fonovaya station). A synchronous change is also characteristic of the aerosol concentration. It can be seen that the CO/CO 2 ratio increased for both stations; however, for the episode under consideration it was more significant in the background. For the TOR station, the first episode was more pronounced in an increase in the concentration of CO and CO 2 . Besides, we noted that for the case of the second event only for the background conditions there was an increase in NO and NO 2 . Moreover, an increase in the SO 2 concentration was also noted. The predominance of the meridional form with the development of high-pressure ridges for the circulation in the middle atmosphere was characterized. The air masses from the southern regions (Kazakhstan) (Figure 2b) are transported throughout the south of Western Siberia. The transport of air masses from the industrial areas of Kazakhstan is confirmed by the calculated background trajectories (Figure 3a). The second important factor characterizing the second episode is a large number of natural fire sources ( Figure  3b). The TOR station territory is more subject to smoke from fires.   Figure 4 shows selective time series of the observed and simulated gas and aerosol composition. To estimate the contribution of emissions from fires to the composition of the atmosphere, two simulation runs were performed. The first run was performed using all emissions (in the figure it is denoted by "all"). For the second run, emissions from fires were turned off (in the figure it is denoted by "abw"). The model reproduces individual elements of changes in the gas and aerosol components (two episodes of increasing gases and aerosols), but it strongly depends on the block "natural fires". It can be seen that for most of the time series in Figure 4 there is no evident increase in the chemical atmospheric composition when the block counts wildfires were turned off. In most cases, the model demonstrated overestimated values or peaks which have not been observed.