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China and Russia have different interests in the Arctic but are forced to look for possible ways of cooperation in energy projects in the current external conditions. This changes the priorities of both countries and, accordingly, transforms the risks. Objectives of the research: to build an algorithm for identifying anthropogenic environmental risks in the context of two major players economic activities in the Arctic region: the Russian Federation and China. In the paper, we formulated an algorithm of environmental risk identification. We identified environmental hazards from the main parameter—the type of economic activity for the extraction of energy resources, premises, and factors for the occurrence of environmental hazards and compiled criteria for risk selection. Methods used: complex analysis (mixed method research): empirical and comparative methods, methods of expert assessments, the method of inductive statistics (inferential statistics) to compare the perception of risk at the level of different groups. Results: the algorithm has been formed for determining risks in the changed external conditions. Major anthropogenic environmental risks are identified from the perspective of the main players in the Arctic—Russia and China, which can help to make the necessary decisions on time and partially prevent environmental degradation. This makes it possible to identify the risks associated with conducting economic activities for the extraction of energy resources in the Arctic region. Therefore, this study contributes to a more accurate identification of anthropogenic environmental risks in the Arctic region. [ABSTRACT FROM AUTHOR]

Different radiometer sensors have different frequencies, spatial resolutions, and time resolutions, which lead to inconsistencies in ice drift products retrieved by radiometer sensors. Based on the continuous maximum cross-correlation method, in this paper, we used China's FY-3 and HY-2 satellite radiometer data to generate sea ice drift products; we further evaluated the consistency between them and sea ice drift products retrieved from AMSR2 and SSMIS satellite radiometer data, which could help in future retrieval accuracies of more radiometer sea ice drift products. The results show that ice drift products with good reliability can be obtained by retrievals using 37 and 89 GHz channels of FY-3 and HY-2 radiometer bright temperature data. Compared with the buoy data, the root mean square errors (RMSEs) of the 37 GHz HY-2 sea ice drift product (at an interval of 6 days) were 1.40 cm/s and 7.31° for speed and direction, respectively, and the relative errors (REs) were 5.78% and 6.44%, respectively. The RMSEs of the 37 GHz FY-3 sea ice drift product were 0.77 cm/s and 6.49° for speed and direction, respectively, and the REs were 4.38% and 9.23%, respectively. Moreover, comparisons between sea ice drift vectors derived from AMSR2 and SSMIS satellites showed good quantitative agreement. [ABSTRACT FROM AUTHOR]