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Research shows how socio-economic development correlates with emissions in northern oil regions, suggesting key factors influence pollution levels.
Subject of research: the impact of socio-economic development of some northern oil and gas producing regions of Russia on air pollutant emissions. Purpose of research: to assess the impact of the main indicators of socio-economic development of oil and gas producing regions of the north of Russia on air pollutant emissions from stationary sources in the period from 2013 to 2022. The following regions were considered: the Komi Republic, the Nenets Autonomous Okrug, the Khanty-Mansi Autonomous Okrug – Yugra and the Yamalo-Nenets Autonomous Okrug. Research methods: a combination of the IPAT Kaya model and the LDMI method is used to determine the impact of the development of the production system technology of the region "T", welfare "A" and the size "P" of its population on the volume of pollutant emissions. Objects of research: emissions of pollutants into the atmosphere in the Komi Republic, the Nenets Autonomous Okrug, the Khanty-Mansi Autonomous Okrug – Yugra and the Yamalo-Nenets Autonomous Okrug. Research findings: the main influence on pollutant emissions in all regions is provided by the level of development of technology and economic systems, i.e. the energy intensity of emissions and the gross regional product. The second factor in terms of influence on emissions for half of the regions was the welfare of their population. The least influence is exerted by the population size of the regions, despite the significant difference in this indicator between the regions. The use of the specified analytical tools allows us to present the impact on the ecology of the region as a multiplicative function of the impact of key factors of anthropogenic activity, while ensuring the possibility of conducting a more detailed analysis of the impact of these factors through the decomposition of this function with zero residual errors on the indicators recorded by the current system of state statistics.
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Kutyshkin et al. (2025) studied this question.
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