Abstract
Snow cover is an effective accumulator of dust fallout and provides objective information on the level of pollution, but its sampling in large areas takes a long time. The use of remote sensing data (RSD) makes it possible to significantly simplify the assessment of the dust load in the atmosphere. Based on RSD from the town of Tobolsk, we evaluated the information value of various indices used to assess the distribution and properties of snow cover (NDSI, normalized S3 index, and SCI). Data on dust load and physicochemical properties of the snow obtained during sampling and subsequent analysis were compared with the spectral properties of the snow cover. It was determined that the dust load in the town averaged 32,1 mg/m2 per day, which is approximately 8 times higher than the background values. The degree of alkalinization is moderate, an increase in pH and salinity of snowmelt waters is observed. In comparison with other functional zones of the town, no increase in dust fallout was detected in the industrial zone (Tobolsk Petrochemical Plant). The level of dustiness is maximum in the zone of multistory buildings and on the streets with the highest traffic intensity. It was established that spectral indices indicate the amount of solid impurities in snow and the level of alkalinization. A statistically significant correlation was found between the amount of insoluble particles in snow and the S3 index as well as between pH and the SCI index. The paper concludes that these indices can be used to assess the environmental situation in urbanized areas.
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