In this work, a numerical estimate of the average field of the mass concentration of PM2.5 aerosol particles for the European part of Russia was obtained using the numeric technology of fluid-location of the atmosphere (FLA). Atmospheric aerosol concentrations reconstructed based on satellite lidar measurements were used as input information for the first time. According to the modeling results, the areas of the increased PM2.5 mass concentrations were observed over Krasnoyarsk Krai in the summer period of 2021. The results were compared with the spatial distribution of the surface PM2.5 mass concentrations derived from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2).
The paper discusses the development of a new version of the back trajectory statistics method, where data obtained from moving measuring platforms are used as initial information on the content of atmospheric impurities. The measurements of the aerosol physicochemical characteristics obtained during two cruises of the research vessel “Professor Multanovskiy” (July 28 - September 7, 2019) and “Akademik Mstislav Keldysh” (July 31 - August 24, 2020) were used as initial information.
The long-term variability (2004-2021) of the aerosol parameters in the atmospheric column, were obtained at a location near the city of Yekaterinburg in the Middle Urals using solar photometer CIMEL CE-318 of the ground-based aerosol robotic network (AERONET). In this study, we present the results of analysis of trend of long-term changes of the aerosol optical depth (AOD) and the characteristics of the aerosol microstructure in the atmospheric column. The AERONET measurements show gradual decrease in annual values of AOT at a wavelength of 0.5 μm, fine and coarse components of atmospheric aerosol.
The article is concerned with statistical analysis of the relationship between the ground level fine aerosol concentrations and the aerosol optical depth of the atmosphere. The aerosol characteristics measurements at two monitoring sites in the Middle Urals (Yekaterinburg city and the background region) combined with meteorological parameters and vegetation indices were used. Several linear models to estimate fine particulate matter concentrations using aerosol optical depth measurements and meteorological parameters are presented.
A machine learning approach to solve a multiple regression problem is considered. Mass concentration of aerosol particles in the surface layer of the atmosphere was used as a dependent variable. The aerosol optical depth of the atmosphere and a number of meteorological parameters from the ECMWF ERA5 reanalysis database were chosen as predictors. The problem was solved using an ensemble machine learning algorithm - a random forest.
Estimation results of the 2016 and 2017 average fields of the atmospheric aerosol sink caused by the processes of wet and dry deposition of particles are discussed. The estimation was based on the simulation of the three-dimensional average effective fields of submicron aerosol volume concentration obtained by the method of fluid-location of the atmosphere using photometric measurements of the AERONET station located in the Middle Urals.
Based on data of 3-year (2016-2018) measurements in the Middle Urals, we investigated the diurnal variability in aerosol characteristics: atmospheric aerosol optical depth (τ0.5) and concentrations of fine aerosol (PM2.5) in the surface layer of the atmosphere at urban and background sites in the Middle Urals. Also, as a part of this study, we estimated the relation between τ0.5 and PM2.5. The linear regression functions of the hourly PM2.5 concentration and τ0.5 were PM2.5 = 2.83 × τ0.5 + 20.35 (R=0.46) and PM2.5 = 1.8 × τ0.5 + 15.87 (R=0.31) for urban and background sites, respectively. In addition, the results also demonstrated significant differences in correlation for different time window during the day.
A mathematical formulation of a new method of fluid location of the atmosphere (FLA) is proposed. On the basis of instrumental measurements at one or a few monitoring sites and information on atmospheric dynamics (back trajectories of the motion of air parcels) the FLA method makes it possible to estimate the spatial structure of fields of a measured quantity. Results of solution to a problem of estimating the spatial distribution of the volume concentration of a submicron aerosol are presented; these results were obtained during an analysis of photometric measurements in the period of 20132015 at eight AERONET monitoring sites on the territory of Far Eastern region.
Results of simulation of effective quasi-two-dimensional average fields of volume concentration of submicron aerosol, obtained by the method of fluid-location of atmosphere (FLA) are discussed. The input information are AERONET photometric measurement data and back trajectories of the air parcels calculated by the HYSPLIT software.
The paper presents some results of greenhouse gases in situ measurements in 2015-2017 summertime from a high Arctic Belyy Island (Russia). The atmospheric CO2 concentration has increased by 3.1 ppm per year, which is 1.5 times higher than the mean annual global rate during last 10 years. However, the absolute CO2 levels were significantly less than the global background, which exceeded 400 ppm in 2015. The CH4 content had not changed, but in summer periods tundra ecosystem of the island was shown to remain a local net CH4 source in comparison to marine ecosystem. Possible mechanisms of forming mean diurnal cycles of CO2 and CH4 concentration are discussed. The temperature dependences of the measured parameters are established, indicating a significant sensitivity of carbon balance in the arctic tundra to the air temperature variability.
Results of the complex aerosol experiment “city-background”, performed in the Middle Urals in 2014, are discussed. We analyze interrelations of the optical and microphysical characteristics of aerosol in the atmospheric column and in the near-ground layer in two regions: in Yekaterinburg on the roof of Institute of Industrial Ecology, Ural Branch, Russian Academy of Sciences (IIE UB RAS) and in the background region on the territory of Kourovka Astronomical Observatory (KAO), located in forested terrain about 65 km northwest of the city. Estimates of how meteorological conditions influence the aerosol characteristics are presented.
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