The paper presents the distribution of heavy metals in the roadside zone, using the example of sections of Russian railway lines with different intensity of train traffic. The research methodology involved constructing a mathematical model on the basis of experimental data, which makes it possible to estimate the distribution of pollutants over the zone. Mass transfer of dust particles during train passage is represented on the model of snow structures. The functional dependence for construction of the complete curve of contamination of the roadside zone depending on the coordinate of distance from the track axis was obtained. The model of mass transfer of dust particles makes it possible to estimate soil contamination in the roadside zone. It was established that on the basis of correlation of theoretical surface contamination with actual contamination, it is possible to draw a complete contamination curve by sampling points using the functional dependence of mass transfer obtained in the modeling. It was revealed that 70% of dust surface pollution accounts for the right-of-way, providing further maximum contamination with heavy metals of the upper layer of soils. Other 30% are distributed on a sanitary-protective zone and city soils. At the same time it is worth noting that the share of metals of the 1st class is insignificant in this distribution.


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    Titel :

    Assessment of Heavy Metal Pollution in the Roadside Area of Motorways


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Guda, Alexander (Herausgeber:in) / Zhuravleva, Margarita (Autor:in) / Efremova, Soniya (Autor:in) / Konovalov, Vladimir (Autor:in) / Zubrev, Nikolai (Autor:in) / Panfilova, Marina (Autor:in) / Goryacheva, Anna (Autor:in)

    Kongress:

    International School on Neural Networks, Initiated by IIASS and EMFCSC ; 2022 ; St.Petersburg, Russia February 08, 2022 - February 10, 2022



    Erscheinungsdatum :

    16.11.2022


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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