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The paper assesses the chemical transformation of surface waters in the southeastern part of the Khibiny Mountainous Massif after launching the Oleniy Ruchey apatite–nepheline ore deposit in 2012. The influence of the Oleniy Ruchey Mine was reflected in an increase in water mineralization (by an order of magnitude) and in a change in the basic ion ratios in water objects receiving runoff from mines, rock, and tailing dumps compared to the watercourses unaffected by the mining enterprise's activities. Natural hydrocarbonate–sodium water with a mineralization of 10 mg/L was transformed into the nitrate–sodium or sulfate–calcium water. The content of nitrogen group compounds in the Lake Komarinoe water, which receives wastewater from the tailing dumps over the ten-year history of the mining and processing plant, has increased by two orders of magnitude, and the nitrate became basic ion. The concentrations of other basic ions and mineralization in this lake increased by an order of magnitude, as the content of trace elements (Sr, F, Mo), which belong to the main rock-forming minerals of apatite–nepheline deposits. Compared to the background water bodies, the mine wastewaters have the elevated mineralization (up to 260 mg/L), pH value (up to 10), and a modified chemical composition. They are characterized by a hydrocarbonate–sodium composition with a large proportion of nitrates and sulfates. Mine wastewaters have elevated contents of nutrient compounds, organic matter, and some trace elements (Al, Fe, Sr, Cu, Mn, Zn, and Cr). It has been established that the geochemical modifications in the quality of surface water are locally developed, being typical of water bodies receiving wastewater from a mining enterprise, in contrast to metallurgical plants, the atmospheric emissions of which caused pollution over tens and hundreds km. [ABSTRACT FROM AUTHOR]

The paper proposes an approach to the numerical stochastic modeling of the time series of the wind chill index and equivalent effective temperature at weather stations located in the Arctic zone of the Russian Federation. The approach is based on the use of a specially designed stochastic weather generator. It is shown that the approach allows developing the models of the time series of bioclimatic indices that very accurately reproduce various statistical properties of real processes related, in particular, to their daily variations and specific features of the study area. [ABSTRACT FROM AUTHOR]