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Atmosphere
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Variations in Atmospheric Composition over Northern Eurasia Regions
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Variations in Atmospheric Composition over Northern Eurasia Regions

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Aerosols".

Deadline for manuscript submissions: closed (1 June 2021) | Viewed by 10098

Special Issue Editor

Prof. Dr. Georgy Golitsyn

E-Mail Website
Guest Editor
A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, 119991 Moscow, Russia
Interests: climate change; greenhouse effect; aerosol; atmospheric physics, turbulence

Special Issue Information

Dear Colleagues,

Twenty-five years ago, Prof. Paul Crutzen and I initiated the project TROICA aiming to examine atmospheric composition over the vast territory of Russia using a novel train-laboratory. The project included 15 large-scale campaigns which ended in 2010, and yielded unique information on spatial and temporal variations of concentrations of greenhouse gases, aerosols, ozone depleting and polluting substances, their sources, emissions, and transport. Since that time, new state-of-the-art technologies of ground-based and satellite monitoring have appeared, chemical and transport models have become more sophisticated, and researchers have revealed new findings about atmospheric composition over Northern Eurasia—the region faced with the most pronounced climatic changes. These changes provoke shifts in the atmospheric photochemical system, vary emissions and sinks of greenhouse gases because of permafrost melting, and modulate ecosystem shifts, wildfires, and floods. Traces of anthropogenic activity, like emissions from megacities and industrial clusters, agricultural lands, oil and gas fields, transport and domestic systems, have reached even the most remote areas and influence air quality and optical characteristics, secondary aerosol formation, atmosphere–biosphere exchange, and other processes which are crucial not only for Northern Eurasia, but for the entire Earth system.

I kindly invite researchers, both observers and modelers, to share their knowledge and data on atmospheric composition over Northern Eurasia regions and related topics by submitting papers to the Atmosphere Special Issue “Variations in Atmospheric Composition over Northern Eurasia Regions” in the hope that new connections will appear from complex analyses and new regional and global models constructed in order to explain past, present, and future changes.

Prof. Dr. Georgy Golitsyn
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • Atmospheric composition
  • Northern Eurasia
  • Trace gases
  • Aerosols
  • Atmospheric pollution
  • Atmospheric transport
  • Emissions and sinks
  • Wildfires
  • Biosphere–atmosphere exchange
  • Greenhouse gases
  • Carbon cycle
  • Ground-based and satellite observations
  • Atmospheric chemistry modelling

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Published Papers (3 papers)

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Research

23 pages, 8045 KiB  
Article
Analysis of Mineral Aerosol in the Surface Layer over the Caspian Lowland Desert by the Data of 12 Summer Field Campaigns in 2002–2020
by Otto G. Chkhetiani, Natalia V. Vazaeva, Alexander V. Chernokulsky, Karim A. Shukurov, Dina P. Gubanova, Maria S. Artamonova, Leonid O. Maksimenkov, Fedor A. Kozlov and Tatyana M. Kuderina
Atmosphere 2021, 12(8), 985; https://doi.org/10.3390/atmos12080985 - 30 Jul 2021
Cited by 6 | Viewed by 2350
Abstract
In-situ knowledge on characteristics of mineral aerosols is important for weather and climate prediction models, particularly for modeling such processes as the entrainment, transport and deposition of aerosols. However, field measurements of the dust emission flux, dust size distribution and its chemical composition [...] Read more.
In-situ knowledge on characteristics of mineral aerosols is important for weather and climate prediction models, particularly for modeling such processes as the entrainment, transport and deposition of aerosols. However, field measurements of the dust emission flux, dust size distribution and its chemical composition under realistic wind conditions remain rare. In this study, we present experimental data over annual expeditions in the arid and semi-arid zones of the Caspian Lowland Desert (Kalmykia, south of Russia); we evaluate characteristics of mineral aerosol concentration and fluxes, estimate its chemical composition and calculate its long-distance transport characteristics. The mass concentration in different years ranges from several tens to several hundred of μg m−3. The significant influence of wind velocity on the value of mass and counting concentration and on the proposed entrainment mechanisms is confirmed. An increased content of anthropogenic elements (S, Sn, Pb, Bi, Mo, Ag, Cd, Hg, etc.), which is characteristic for all observation points in the south of the European Russia, is found. The trajectory analysis show that long-range air particles transport from the Caspian Lowland Desert to the central regions of European Russia tends to increase in the recent decades. Full article
(This article belongs to the Special Issue Variations in Atmospheric Composition over Northern Eurasia Regions)
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24 pages, 5734 KiB  
Article
Validation of WRF-Chem Model and CAMS Performance in Estimating Near-Surface Atmospheric CO2 Mixing Ratio in the Area of Saint Petersburg (Russia)
by Georgy Nerobelov, Yuri Timofeyev, Sergei Smyshlyaev, Stefani Foka, Ivan Mammarella and Yana Virolainen
Atmosphere 2021, 12(3), 387; https://doi.org/10.3390/atmos12030387 - 17 Mar 2021
Cited by 7 | Viewed by 4478
Abstract
Nowadays, different approaches for CO2 anthropogenic emission estimation are applied to control agreements on greenhouse gas reduction. Some methods are based on the inverse modelling of emissions using various measurements and the results of numerical chemistry transport models (CTMs). Since the accuracy [...] Read more.
Nowadays, different approaches for CO2 anthropogenic emission estimation are applied to control agreements on greenhouse gas reduction. Some methods are based on the inverse modelling of emissions using various measurements and the results of numerical chemistry transport models (CTMs). Since the accuracy and precision of CTMs largely determine errors in the approaches for emission estimation, it is crucial to validate the performance of such models through observations. In the current study, the near-surface CO2 mixing ratio simulated by the CTM Weather Research and Forecasting—Chemistry (WRF-Chem) at a high spatial resolution (3 km) using three different sets of CO2 fluxes (anthropogenic + biogenic fluxes, time-varying and constant anthropogenic emissions) and from Copernicus Atmosphere Monitoring Service (CAMS) datasets have been validated using in situ observations near the Saint Petersburg megacity (Russia) in March and April 2019. It was found that CAMS reanalysis data with a low spatial resolution (1.9° × 3.8°) can match the observations better than CAMS analysis data with a high resolution (0.15° × 0.15°). The CAMS analysis significantly overestimates the observed near-surface CO2 mixing ratio in Peterhof in March and April 2019 (by more than 10 ppm). The best match for the CAMS reanalysis and observations was observed in March, when the wind was predominantly opposite to the Saint Petersburg urbanized area. In contrast, the CAMS analysis fits the observed trend of the mixing ratio variation in April better than the reanalysis with the wind directions from the Saint Petersburg urban zone. Generally, the WRF-Chem predicts the observed temporal variations in the near-surface CO2 reasonably well (mean bias ≈ (−0.3) − (−0.9) ppm, RMSD ≈ 8.7 ppm, correlation coefficient ≈ 0.61 ± 0.04). The WRF-Chem data where anthropogenic and biogenic fluxes were used match the observations a bit better than the WRF-Chem data without biogenic fluxes. The diurnal time variation in the anthropogenic emissions influenced the WRF-Chem data insignificantly. However, in general, the data of all three WRF-Chem model runs give almost the same CO2 temporal variation in Peterhof in March and April 2019. This could be related to the late start of the growing season, which influences biogenic CO2 fluxes, inaccuracies in the estimation of the biogenic fluxes, and the simplified time variation pattern of the CO2 anthropogenic emissions. Full article
(This article belongs to the Special Issue Variations in Atmospheric Composition over Northern Eurasia Regions)
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19 pages, 7136 KiB  
Article
Air Pollution in Moscow Megacity: Data Fusion of the Chemical Transport Model and Observational Network
by Nikolai Ponomarev, Vladislav Yushkov and Nikolai Elansky
Atmosphere 2021, 12(3), 374; https://doi.org/10.3390/atmos12030374 - 13 Mar 2021
Cited by 6 | Viewed by 2563
Abstract
Comparisons of observational data obtained at the Moscow Ecological Monitoring network (MEM) with numerical simulations using a chemical transformation and transport model (SILAM—System for Integrated modeLling of Atmospheric coMposition) showed that the errors in determining the gaseous pollutant concentrations in the urban atmosphere [...] Read more.
Comparisons of observational data obtained at the Moscow Ecological Monitoring network (MEM) with numerical simulations using a chemical transformation and transport model (SILAM—System for Integrated modeLling of Atmospheric coMposition) showed that the errors in determining the gaseous pollutant concentrations in the urban atmosphere have a more complex structure than those assumed under the conventional algorithms of data assimilation. These errors are statistically nonstationary; they show a pronounced diurnal cycle and a significant lifetime. The statistical features of errors in numerical calculations also depend upon the type of pollutants, i.e., the chemical reactions in which they participate. Our analysis showed that the simulation errors are not small: the ratios of calculated and measured concentrations (even for daily averages at all measuring stations) may vary in a wide range. For the chemically active pollutants, the intradiurnal error variations may reach 100%. The diurnal cycle of such errors was found to vary according to seasons (in our case, summer and winter). The analysis of statistical properties of the errors, including their temporal and spatial variability, allows one to correct and adequately forecast the air pollution in the metropolis area at lead times up to three days in advance. Full article
(This article belongs to the Special Issue Variations in Atmospheric Composition over Northern Eurasia Regions)
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