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Estimation of Dust Depositions in Snow Cover Using Earth’s Remote Sensing Data: Example of Nizhnevartovsk

  • OPTICS OF CLUSTERS, AEROSOLS, AND HYDROSOLES
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Abstract

We estimated the dust aerosol influx into the snow cover in the region of Nizhnevartovsk. The average content of solid insoluble particles in snowmelt waters for conventionally background area is 12.0 mg/L, four times larger than for the reference uncontaminated territories. The high local background is typical for the Middle Ob River area and is due to the effect of remote oil production plants. Under urban conditions, the aerosol dust influx increases by a factor of 7.5 relative to conventionally background area. The dust particle influx leads an intense alkalization of snow cover. Results obtained during field tests are compared with spectral properties of snow. Landsat-8 (OLI sensor) data are used to calculate snow indices (normalized difference index, normalized index, and contamination index), which agree with ground-based observations and can be used to estimate the technogenic contamination level. The normalized snow index is optimal to estimate the amount of dust sediments, and snow contamination index is optimal to estimate acid–base (pH) conditions.

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Funding

This work was carried out under the support of the Russian Foundation for Basic Research (grant no. 19-05-50062\19) and in the framework of fundamental research of the Siberian Branch, Russian Academy of Sciences (project no. AAAA-A17-117050400146-1).

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Authors and Affiliations

  1. Tyumen Scientific Center, Siberian Branch, Russian Academy of Sciences, Institute of Problems of Northern Development, 625026, Tyumen, Russia

    R. Yu. Pozhitkov, A. A. Tigeev & D. V. Moskovchenko

  2. Tyumen State University, 625003, Tyumen, Russia

    D. V. Moskovchenko

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  1. R. Yu. Pozhitkov
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  2. A. A. Tigeev
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  3. D. V. Moskovchenko
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Correspondence to R. Yu. Pozhitkov.

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Translated by O. Bazhenov

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Pozhitkov, R.Y., Tigeev, A.A. & Moskovchenko, D.V. Estimation of Dust Depositions in Snow Cover Using Earth’s Remote Sensing Data: Example of Nizhnevartovsk. Atmos Ocean Opt 34, 19–25 (2021). https://doi.org/10.1134/S1024856021010103

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