Abstract
The study aims to estimate the applicability and precision of a methodology for identifying the background concentration of ozone. These values are necessary to estimate a maximum permissible emission value, understand the population’s health risk level, and evaluate the activity of ozone sources (first of all man-made). Currently applied state-approved methods have some limitations; thus, applying a new methodology based on the time variations of impurity concentration is of research and practical interest. Research objects are concentrations of tropospheric ozone in Moscow (anthropogenic polluted atmospheric air, mostly because of the transport activity) and in the settlement with relatively low pollution levels. Initial data are the results of the continuous records of concentrations of ozone, its precursors, and meteorological parameters from the ozone monitoring network. The methodology tested in this study to identify a background ozone concentration is the dynamic phase portrait method, considering variations of changes in concentration during the time. The value obtained presents the concentration of tropospheric ozone most characteristic of the studied location. The background concentration value obtained using the tested methodology is more consistent with the values calculated using the state-approved methodology the longer the observation period is. Furthermore, the values identified make it possible to consider the peculiarities of the distribution of pollutants and the complex meteorological factors in a particular territory and to abandon the standard values assigned.
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Khaustov, A., Redina, M. (2023). Evaluation of Background Concentrations of Tropospheric Ozone Using Dynamic Phase Portrait Methodology. In: Çiner, A., et al. Recent Research on Environmental Earth Sciences, Geomorphology, Soil Science, Paleoclimate, and Karst. MedGU 2021. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-42917-0_17
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DOI: https://doi.org/10.1007/978-3-031-42917-0_17
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