This article discusses the efficiency of transport infrastructure and cooperation of neighboring regions located in Asian Russia, China, Mongolia, and Kazakhstan in the context of creating new international economic corridors from the Silk Road and trans-Eurasian transport corridors. This study aims to highlight the possible ways of strengthening cross-border cooperation in the field of transport infrastructure. We evaluated the current state of the transport infrastructure, the dynamics of its development, and its influence on the territorial–production complex. Using quantitative data and the unified indicator for the efficiency of transport infrastructure, we also characterized the territorial differentiation, its causes, and prerequisites for further economic and trade cooperation between these countries. The main results are as follows: (1) The lowest levels of the efficiency of transport infrastructure are typical for the northeast of Asian Russia, as well as for the border regions of China, Mongolia, and Kazakhstan. (2) For Asian Russia, Kazakhstan, and Mongolia, the highest levels of the unified indicator are typical for regions located along the main transport routes and for regions with a developed mining industry. This is due to the strong unevenness of the socio-economic development of the territories. (3) The largest industrial and economic centers have been developing along the main transport corridors primarily due to the accumulated potential of equivalent freight turnover and export potential. This study can be useful for authorities and business, as well as for other users of transport infrastructure to improve its regulation and efficiency.

For the first time in the territory of the Russian Far East, a study related to the establishment of correlations between air quality and public health in Ulan-Ude (Buryatia, Russia) was carried out. This study is based on the analysis of official medical statistics on morbidity over several years, the data on the composition and volume of emissions of harmful substances into the air from various stationary sources, and laboratory measurements of air pollutants in different locations in Ulan-Ude. This study confirmed that the morbidity of the population in Ulan-Ude has been increasing every year and it is largely influenced by air pollutants, the main of which are benzo(a)pyrene, suspended solids, PM_2.5, PM₁₀, and nitrogen dioxide. It was found that the greatest contribution to the unfavorable environmental situation is made by three types of stationary sources: large heating networks, autonomous sources (enterprises and small businesses), and individual households. The main air pollutants whose concentrations exceed the limits are benzo(a)pyrene, formaldehyde, suspended particles PM_2.5, PM₁₀, and nitrogen dioxide. A comprehensive assessment of the content of various pollutants in the atmospheric air showed that levels of carcinogenic and non-carcinogenic risks to public health exceeded allowable levels. Priority pollutants in the atmosphere of Ulan-Ude whose concentrations create unacceptable levels of risk to public health are benzo(a)pyrene, suspended solids, nitrogen dioxide, PM_2.5, PM₁₀, formaldehyde, and black carbon. The levels of morbidity in Ulan-Ude were higher than the average for Buryatia by the main disease classes: respiratory organs—by 1.19 times, endocrine system—by 1.25 times, circulatory system—by 1.11 times, eye diseases—by 1.06 times, neoplasms—by 1.47 times, congenital anomalies, and deformations and chromosomal aberrations—by 1.63 times. There is an increase in the incidence of risk-related diseases of respiratory organs and the circulatory system. A strong correlation was found between this growth of morbidity and atmospheric air pollution in Ulan-Ude.

Presented are the results from studying the current state, modeling and forecasting of the transboundary transport of pollutants with the flow of the rivers within the Selenga river basin. The method for calculating the pollution coefficient was used to assess the degree of pollution of the Selenga river basin on the territories of Mongolia and the Republic of Buryatia (RF) on the linear sections of the river and its tributaries within the boundaries of the adjacent river sections according to data of state monitoring observation in both countries. Results from assessing the impact of economic entities located within the transboundary Selenga river basin on the streams according to the α-indicator of the pollution coefficient and subsequent ranking by four levels of pollution indicate that the catchment and Lake Baikal itself continue to be polluted by insufficiently treated wastewater from industrial enterprises and housing and communal services. Calculations showed that the aquatic ecosystems of the Kyakhtinka (Khiagt), Modonkul’ Selenga rivers in the border zone along the border of Russia and Mongolia in the area of Naushki – Sükhbaatar and Kyakhta ‒ Altanbulag, and in the area of the settlement of Novoselenginsk are most disturbed. On the territory of the Russian part of the basin, the Selenga river downstream, the degree of water pollution is increasing in the areas of industrial centers, such as Gusinoozersk and Ulan-Ude. The average indicator of the pollution coefficient as calculate for the Russian part of the Selenga river basin was higher than that for the Mongolian part, which suggests the conclusion that the degree of pollution by the pollutants under consideration is higher on the Mongolian territory than on the Russian territory.

This article examines the territorial production and resource structures in the territory of Asian Russia, which include natural, economic, and social elements. The objective of this study is to assess, typologize, and zone the territorial production–resource structures. The methodological framework of this study is based on calculating an integral development indicator for the regions of Asian Russia, represented by an Adjusted Net Savings index. This index reflects regional wealth according to the World Bank’s expanded concept of national wealth, which includes three types of capital: “reproducible”, “natural”, and “human”. The study also involves a larger typology of the regions, classifying them based on the predominance of these capital forms through the Analytic Hierarchy Process and the triangular illustration method. Regional clustering within the study area was also conducted through the k-means method using Statistica 12 software. Accordingly, adjusted net savings and sectoral contributions to gross regional product were calculated for the regions in this area. A relationship between regional specialization and the level of genuine savings was identified, forming the basis for the grouping of regions. A total of three groups were distinguished: regions with negative, moderate, and the highest levels of genuine savings within the macroregion. A larger typology using dominant, predominant, and complex functions was also developed. Using data on natural, physical, and human capital in Asian Russia, its regions were clustered, resulting in the identification of five clusters. The territory was then zoned based on the clustering results. A total of eight zones were identified, reflecting the size and balance of the three types of capital (human, physical capital, and productive natural), with regions grouped according to their cluster membership and territorial proximity. The findings can help identify pathways for more sustainable development of this territory amidst evolving natural, economic, social, and geopolitical conditions.

The dynamics of indicators of a number of natural factors from 1970 to 2022 in the subjects of the Baikal region: air temperature, annual precipitation, water resources, and forest area affected by fires are considered in the article. A correlation analysis was carried out between the presented components in the territory under consideration, which revealed the strength of dependence from medium negative to highly positive. The results of the work carried out can be one of the bases for natural and economic regulation in the territory under consideration, predictive assessments of the dynamics of natural processes for their consideration in the complex of natural and socio-economic processes, as well as in planning and forecasting socio-economic activities in the territory of the subjects of the Baikal region.

This paper proposes an innovative research algorithm “measurement—pattern—driving force—synergy” that determines the eco-efficiency of 83 Russian federal subjects (2000–2019) using the Slacks-Based Measure (SBM) model with non-desired outputs (incorporating comprehensive input indicators such as water resources and electricity input, and dual non-desired outputs of waste gas and wastewater). Combined with hot spot analysis, a gravity center model, and panel Tobit regression, we reveal the temporal-spatial evolution and driving mechanisms of eco-efficiency in resource-based economies. The research finds that the overall eco-efficiency of Russia is at a medium level and shows a dynamic correlation with the economic development stage. In the early stage of the period under review, there was a high degree of synergy, but the efficiency declined during the period of rapid economic growth. Later, it rebounded somewhat in tie with technological progress. Spatially, it presents a special pattern of low efficiency in the western European industrialized regions and high efficiency in the Arctic and Far East peripheral regions, reflecting the spatial heterogeneity of resource-dependent economies and the survival-constrained efficiency feature. The analysis of influencing factors indicates that per capita GDP has a significant positive driving effect on eco-efficiency, but the expansion of residents’ consumption, the improvement of education level and the dependence on foreign trade all have inhibitory effects, highlighting the path dependence of the current growth model on the structure of resource consumption. The research suggests that Russia should implement differentiated spatial governance in the future, promote the green transformation of consumption and trade structures, and strengthen the ecological orientation of the education and scientific research system to achieve a fundamental transformation of regional sustainable development from survival constraints to innovation-driven.