INTRODUCTION

In Russia’s post-Soviet period, significant social, economic, political, institutional, and technological changes became the background for changes in anthropogenic impact (AI) on the natural resource complex and health of the population in certain areas of the country. New conditions arose for formation of the environmental situation, due to the transition from a planned to a market economy, Russia’s integration into the global economy, and increased dependence on global economic cycles. The role of technological factors gradually decreased, while the role of structural changes in industry increased, since the maximum reduction in production volumes occurred in relatively high-tech processing sectors. The increased specialization of the economy in raw materials has led to an increase in anthropogenic load in the extractive regions; in major cities, rapid growth in motorization has become an important factor in the anthropogenic load. Institutional mechanisms gradually began to influence the environmental situation of territories; environmental payments somewhat incentivized the greening of economic activity.

The economic–geographical approach to studying AI on the environment is based on a comprehensive analysis and assessment of not only the actual environmental problems of a territory, but also their causes, among which an important place is occupied by the dynamics and structural transformations in material production. This approach allows the comparative study of ecological and socioeconomic functional and territorial structures and to identify the role of geographical differentiation of economic activity in the formation of territorial differences in the nature and intensity of environmental impact. Together with differences in the tolerance of various types of natural landscapes to AI, this leads to the formation of territorially heterogeneous environmental situations. The study of these factors makes it possible to construct not only a determining, but also an explanatory model.

In addition to analyzing the impact of key factors, as well as trends in the environmental situation, a comprehensive assessment of the transformation of the environmental and economic situation due to changes in the sectoral and territorial structure of regional economies is required. This kind of comprehensive assessment can be used to improve the effectiveness of investment costs in environmental protection.

Cities play a particular role in forming a territorially differentiated environmental situation, because they are distinguished not only by a high concentration of population, economic functions, capital, infrastructure, but also sources of pollution of all natural components. Effective management of the environmental situation is facilitated by the search for and development of adequate indicators of the environmental situation in cities in order to develop environmental policy priorities and coordinated measures to address environmental and economic problems using a comprehensive approach.

STUDY OF THE PROBLEM

Environmental issues were gradually included in economic and geographical studies more than 50 years ago against the backdrop of an increase in the scale of AI and increased attention to habitat. The conceptual approaches founded in three main directions during this period continue to this day.

(1) Awareness of the environmental factor role in the development of territorial and economic systems formed the basis for subsequent methodological development in this area; ideas about the environmental situation as a consequence of economic development were elaborated; the environmental factor was introduced into zoning criteria. The ideas of the early 1970s that not only natural, but also environmental factors should be taken into account when identifying areas (Komar, 1975; Mints, 1972; Saushkin, 1973) have been significantly developed when the estimate of interaction between production, settlement, social, infrastructural, and natural components formed the basis for ecological and economic zoning (Chistobaev and Sharygin, 1990; Privalovskaya, 1983; Privalovskaya and Runova, 1994; Razumovsky, 1989). Then, based on the concept of direct and “reverse resource use” like environmental pollution, balance ecological and economic models of industrial hubs were developed (Baklanov, 2007).

In the transition period geoecological consequences of the change in type of natural resource use, including under the influence the increased resource orientation of the economy, primitivization of the agrarian complex, and the weighting of the structure of the processing industry were intensively studied at the country and regional levels (Klyuev, 2015); the increasing influence of oil and gas production on the ecological state of regions was analyzed (Bityukova and Chizhova, 2006; Solodovnikov and Chistobaev, 2011).

Consideration of the problem of the influence of economic dynamics on the environmental situation of countries, regions, and cities fits into the international context of research. The idea of economic growth as the most effective means of solving both social and environmental problems, which dominated scientific and public discourse of the 1970s, was gradually shoved aside by the concept of the optimal level of economic development, at which environmental damage would be minimal (Yandle et al., 2002). There was an understanding that minimizing the negative impact on nature was closely related to changing the structure of the economy, increasing energy efficiency (Gómez-Calvet et al., 2014), in the transition to conscious consideration of the environmental factor in the postindustrial economy (Lopatnikov, 2013). Both Russian and foreign studies emphasize that economic crises contribute to strengthening of AI and the least efficient scenario (Bobylev and Zakharov, 2009; Hollander, 2003).

In recent years, the discrepancy between the rates of economic growth and resource consumption or environmental pollution has been recognized as one of the most important criteria for the development of a green economy. It was estimated by calculating the decoupling effect (Dt), when emissions and sinks increased many times slower than industrial production (Nagvi and Zwickl, 2017).

$${{D}_{t}} = 1 - \frac{{{{E}_{t}}/{{Y}_{t}}}}{{{{E}_{0}}/{{Y}_{0}}}},$$

where E0 and Et are the indicators characterizing the negative impact on the environment in the base and current periods (emissions, wastewater, solid waste, and water consumption volumes); Y0 and Yt is GDP in comparable 2005 prices in the base and current periods, respectively. A positive value of Dt indicates that the increase in value added is accompanied by a decrease in the load on the natural environment, while a negative value indicates absence of the decoupling effect. The decoupling effect for individual pollution indicators was calculated for the regions of post-Soviet countries (Bityukova and Shimunova, 2021) and Russian regions (Pakina and Kirillov, 2017), but it has not yet been used to analyze the integral indicators of anthropogenic impact.

(2) In the field of assessing the territorial heterogeneity of AI, the most important impetus for formation of the concept of differences in the scale of influence was ecological and geographical position (Klyuev, 1996), which became the basis for further development of ideas about the territorial structure of pollution as a set of mutually located and interconnected elements of environmental impact in a certain way, with their inherent spatial coordination, inextricable relationship between themselves and other structures: industrial, natural environment, settlement pattern. After the collapse of the USSR, the mutual influence of territories, which was the basis of this concept, became even more relevant, since the single economic complex of a large country was divided by state borders and the environmental factor acquired a geopolitical connotation. In this area, attempts were made to integrally assess regional differences in AI levels based on statistical analysis, but with a different set of indicators (Bityukova, 2021; Tikunov and Belousov, 2021).

(3) Strengthening of the social orientation in assessing the environmental situation, the idea of a person as the main recipient of AI, the development of social ecology and human ecology (Prokhorov, 1991) became the scientific basis for including problems of sustainable development in economic and geographical research and the development of integral indices and risk assessment of sustainable development of regions (Volkova and Privalovskaya, 2010). A special place in this topic was occupied by urban sustainability assessments with the help of integral indicators that combine measurement of economic growth and ensuring social well-being, while minimizing environmental externalities. The response to requests to assess the quality of economic growth in cities in different periods was the developed indices of the quality of life, inclusive development, smart city, etc. (The Green …, 2012). In foreign ratings, indicators that assess the environmental friendliness of urban infrastructure as a whole play an important role: the convenience of public transport and how motivated residents are to use it or bicycles instead of cars, energy efficiency standards for buildings, the use of renewable energy sources for street lighting, the availability of a system for separate waste collection and recycling, as well as indicators that show the policy of authorities to promote green lifestyles and public participation (Arbab, 2017; Mori, 2014).Footnote 1

Generally, the ecological problems of cities and settlement systems became a priority in many economic and geographical studies and were carried out at different territorial levels. They can be divided into large-scale studies of intracity differences in the ecological state of the urban environment (not considered in this review, since it is a separate research area) and small-scale assessments of differences between cities. The latter often end with the compilation of city ratings based on an assessment of pollution from individual sources or integral indices.

Component assessments consider either individual types of AI, a certain type of impact sources, or the state of individual urban subsystems (air, soil, vegetation). For many countries, it has been revealed that the role of fuel energy production is decisive, in particular when coal is used. This is because when coal is used in the fuel balance of power plants and heating systems, more than a third of emissions are solid ash particles containing a complex of trace elements and nonferrous metals, including toxic ones (Pacyna et al., 2010; The World …, 2008). Emissions of this most hazardous component depend on the quality of the coal and the accepted standards for purifying flue gas in thermal power plants (Kumar and Jain, 2010; Tian et al., 2014). In general, the leading role of atmospheric emissions in the formation of increased atmospheric pollution levels has been proven for 80% of Russian cities (Bityukova and Kasimov, 2012) and for cities in nine US regions (McHale et al., 2021).

Comprehensive assessments of the environmental situation using integral indices in foreign studies are aimed primarily at assessing the attractiveness of studied objects and showing the main factors of their success. Differences in approaches to environmental indicators in Russian and foreign studies are due to their tasks and target audiences. Russian environmental ratings commonly use AI indicators, while foreign ratings use impact indicators (e.g., the concentration of substances in the environment) to show investors where the situation is more favorable. Russian ratings are aimed at identifying a problem and incentivizing the “lowest performers” to rectify it. Therefore, they are aimed more at those making administrative and economic decisions, and not at investors and city dwellers.

Among the shortcomings of international rankings noted by almost all compilers are poorly comparable statistical data for cities in different countries due to the lack of a unified methodology for collecting and processing them (Dobrolyubova, 2015). Foreign ratings mainly consider major cities; at the same time, there are almost no comparative estimates for cities of other ranks, in particular in global studies. In Russia, this direction is represented by ratings of the ecological state of all Russian cities (Bityukova, 2015) and the capitals of post-Soviet countries (Koldobskaya, 2014).

Thus the vector of ecological direction development in the economic and geographical research is directed from the general concepts of the balanced development of territorial socioeconomic systems to the development of specific methods that can fully assess the territorial differentiation of the environmental consequences of economic development, and from private indicators to the construction of integral indices, from the regional to city level.

METHODOLOGY FOR ASSESSING ANTHROPOGENIC IMPACT IN RUSSIAN REGIONS

The proposed comprehensive index of anthropogenic impact (IAI) is calculated with a methodology that uses only open statistical data published by federal structures. The use of official statistics makes it possible to avoid arguable indicators, the calculation of which requires special studies, and update the index without additional costs (Bityukova, 2021).

The indicators for assessing the level of impact in the regions, based on the principles of consistency, reliability, and statistical coverage, pronounced territorial differentiation and the presence of clearly interpretable dynamics, were chosen according to the types of impact:

— to the atmosphere (density of atmospheric emissions from all types of sources; emission toxicity coefficient)Footnote 2;

— on water resources (specific water consumption and wastewater per surface runoff resources; share of polluted wastewater)Footnote 3;

— on land resources (density of waste disposal; share of disturbed industrial lands)Footnote 4;

— of the agrarian complex (share of arable land; share of reclaimed land; livestock density; application of mineral and organic fertilizers and pesticides; livestock population)Footnote 5;

— on forest resources (volume of harvested wood in relation to stocks; cutting down of allowable felling area; share of forested area that died from fires and disease)Footnote 6;

— radiation impact resulting from global environmental pollution with technogenic radionuclides caused by nuclear weapons tests, accidents at nuclear facilities, and the impact of the modern nuclear fuel cycle (share of inhabitants in areas of radioactive contamination; density of radionuclide contamination of soil, forests, and localities, territories of Minatom enterprises; discharges of radionuclides with unbalanced waters at nuclear power plants; average daily gas and aerosol emissions of long-lived radionuclides at nuclear power plants).Footnote 7

Since only relative, mainly density, indicators of impact were used for the assessment, a federal city and surrounding region were considered together: Moscow with Moscow oblast; St. Petersburg with Leningrad oblast; Sevastopol with the Republic of Crimea. The need for such an association is due to two circumstances. From a substantive point of view, the AI of cities extends to adjacent territories (water consumption, wastewater disposal, solid waste disposal, and impact on forest resources, which is largely determined by the tourists’ flows). Meanwhile, there is no agrarian impact and load on forest resources on the territories of cities, which during calculation unreasonably reduces the minimum value when normalizing indicators by region; as a result, this significantly worsens the differentiating capabilities of the index. An important argument for such merging is the change in the borders of Moscow and St. Petersburg in the period under review, which worsens the comparability of time series.

In order to assess the real increase/decrease in AI for each indicator, it is also necessary to normalize the indicators, relying on stable reference points. In terms of provision share, the range from 0 to 100% is used, but for indicators without limits, the only way to determine the reference points is by expert assessment (Ul Haq, 1995). Taking into account the fact that most indicators of the AI level decreased compared to the previous period, the maximum values for the previous period (1990–2000) were taken as reference points, which makes it possible to distribute the regions with respect to the level of the previous period.

For cities, the proposed structure of the comprehensive index is similar to the system of indicators for regions, but the impacts of the agrarian and forest complexes were excluded. Conversely, taking into account the specifics of the formation of AI in an urban environment, the following indicators were included: the population, road network, and building up densities. The impact of population on the environment is manifested both directly (without the mediation of technological processes, such as recreational load) and indirectly (through economic activity). At the same time, population density indicators largely characterize the degree of risk of exposure, because they show in specific conditions what part of the population experiences these loads. For a city, the building up density and the transport network density are also indicative, which determine both the direct impact on soils and the geological environment, and the conditions for air-clearing of a territory, i.e., partial self-cleaning potential.

The intensity of thermal exposure determines the presence in a city of high- and medium-contrast thermal anomalies with a temperature increase of more than 10°C above the background, associated mainly with industrial facilities and intense heat leaks from underground water-bearing utilities. It is characterized by the density of thermal and steam networks, the specific supply of thermal energy to consumers per year (Gcal/person), as well as the number of people per one heat supply source.Footnote 8

The comprehensive index of anthropogenic impact was calculated as the sum of the average values of indicators normalized by linear scaling over blocks (types of impact). For extremely high differences that distort the final index, the logarithm was taken.

RESULTS

Statistical analysis showed that, despite the fact that the main decrease in most private indicators of the ecological state and IAI occurred in the previous period of the systemic crisis of the 1990s, the decrease in level of impact continued in 55 regions, but the rate of decrease slowed significantly. In general, for the country, the main factors of change were electricity consumption, fuel resource consumption (IAI correlation coefficient 0.66), and industrial output and GDP dynamics (0.4–0.42). Conversely, a negative correlation coefficient was observed with the energy output of GDP, the volume of nonfinancial investment, and the volume of investment aimed at protecting the environment. In terms of regions, there was a certain degree of dependence of the change in the IAI on the production volumes of the three leading types of economic activity, which account for over 80% of emissions, water consumption, and wastewater; over 90% of waste—the extraction of fuel and energy minerals, electricity generation, and metallurgy.

Typology of Regions According to the Comprehensive Index of Anthropogenic Impact

The differences between the regions in the comprehensive IAI are 5.5- to 6-fold. The regions in the top of the ranking are characterized by increased energy output of GRP, and their contribution to GRP and industrial production exceeds their share in the country’s population (Table 1).

Table 1.   Groups of regions by IAI level
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According to the IAI, 5 groups of regions are distinguished, which changed slightly in different years. The cores of ecological tension, unevenly distributed over the territory of Russia, persist throughout the period under review. These are Chelyabinsk, Sverdlovsk, Kemerovo, Moscow, and Leningrad oblasts. In all federal districts of Russia there are areas with a high degree of AI that stand out in comparison with others. In impact density, the load is more evenly distributed in old-developed regions; it is localized beyond the Urals; in general, regional differences are smoothed out (Fig. 1).

Fig. 1.
figure 1

Comprehensive index of anthropogenic impact in Russian regions, 2000–2020.

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The group with a very high IAI level consistently includes five regions with developed heavy industry: Chelyabinsk, Lipetsk, Belgorod, and Kemerovo oblasts and Krasnoyarsk krai. In recent years, this group also includes the Moscow capital region (Moscow and Moscow oblast). Moscow, St. Petersburg, Moscow and Leningrad oblasts have significantly reduced emissions from vehicles as a result of both objective positive processes and changes in the methodology for taking into account emissions from mobile sources. The regions of this group produce 25% of industrial output and about 40% of the country’s total GRP, where the highest level of GRP energy output is produced.

The leading impact factors in them are air pollution (in all regions, from industry; in Moscow, from motor transport), water pollution, and waste generation. The level of impact on the atmosphere exceeds the Russian average by 2–4.5 times: the maximum in Krasnoyarsk krai, the minimum in Chelyabinsk oblast, this is the only one among the leading regions that reduced emissions in 2000–2020 by two times. It is likely that a significant reduction in air pollution allowed Chelyabinsk oblast to improve its position in the ranking, since for many years the region led in the IAI. In Krasnoyarsk krai and Lipetsk oblast, atmospheric pollution was stable, while in Moscow oblast and Kemerovo oblast, it increased.

The subindices of impact on water resources and agricultural impact are above the national average in regions with developed heavy industry (except for Krasnoyarsk krai), and on land resources, in all above mentioned regions except for Moscow capital region and Lipetsk oblast. Radiation contamination of Chelyabinsk oblast and Krasnoyarsk krai stands out.

The group of regions with a high IAI level is only 40% stable. This group in different years includes 15–19 Russian regions, where 20–32% of the population lives and produces 15–35% of industrial output and total GRP and consumes 35% of electricity. It is this group that significantly expands during years of crises; its contribution to the total GRP increases by about 6%. The stable core of this group is regions with balanced impact of industry and the agrarian complex: Krasnodar krai; Tula, Kursk, Voronezh, and Orenburg oblasts; and the Republic of Bashkortostan. They are territorially adjoined by the agroindustrial regions of the Ural-Volga area, the Chernozem Zone, and southern Russia, which reduce the level of impact in crisis years, e.g., Stavropol krai, Republic of Tatarstan, and Samara oblast, or increase it during periods of growth, like Sverdlovsk oblast. In this group, most indicators exceed the average Russian level by 1.5–2 times, with the exception of the load on forest resources in regions where the forestry, woodworking, and pulp and paper industries are specialization industries (Republic of Karelia, Vologda oblast, Perm krai).

A medium IAI level in the 2000s was typical of 42% of very different regions, the contributions of which to the population, industrial output, and total GRP are almost two times lower than the share in the total number of regions. The stable core of this group is made up of only one-third of regions with a diverse manufacturing (mainly machinery industry specialization; in the Central and Volga-Vyatka economic areas), agroindustrial complex, and export-oriented oil producers. The main difference between this and the previous two groups is that two, rarely three, factors are leading, one of which is the impact on water resources combined with increased influence of the agricultural complex (Altai krai, Republic of Mordovia, and Kaliningrad, Oryol, Kurgan, Tambov, and Penza oblasts). The impact on the air, which is formed as a result of emissions from associated gas flaring, and on water resources forms the environmental situation in the Khanty-Mansi Autonomous Okrug and Komi Republic. In most regions of this group, separate areas of high emission density are formed. The intensity of impact on forests is higher than the national average in Arkhangelsk and Tyumen oblasts, Khabarovsk and Altai krais, and the republics of Mari El and Chuvashia.

A moderate IAI level is typical in different years for 14–21 regions of the country, in which 10–17% of the population lives; their contribution to industrial production, the amount of GRP, and energy consumption is 1.5 times less and does not exceed 11%. The stable core of this group consists of regions in which most indicators are below the national average. Anthropogenic load is formed almost equally by all factors at a low level. The exception is the high load on forest resources in republics of Buryatia and Yakutia, Jewish Autonomous Oblast and Zabaykalsky krai, sometimes combined with radiation exposure from nuclear fuel cycle enterprises. This group is maximally reduced in crisis years owing to regions with a high impact of the agrarian complex, e.g., in Volgograd and Astrakhan oblasts and the republics of Dagestan, Karachay-Cherkessia, Kabardino-Balkaria, and Ingushetia.

The group of regions with a low IAI level is the most stable; it has only six regions, in which 4.5% of the population lives, 5.8% of industrial production and 4.2% of total GRP are produced, and 3.5% of electricity is consumed. The level of energy output of the GRP in them is higher than in regions with moderate and medium IAI levels. These are sparsely populated and relatively underdeveloped regions in which environmental problems are localized in individual areas, and in structure, one type of impact is slightly distinguished, which is 5–40% higher than the average Russian level, e.g., on the atmosphere due to the influence of the gas industry in Yamalo-Nenets Autonomous Okrug; on water resources, in the Republic of Altai; and agrarian impact, in the Republic of Kalmykia.

Structure of the Integral Index

It reflects the nature of territorial heterogeneity of the ecological state of regions. The distribution of regions according to the dominant impact factor can become the basis for developing priorities for improving the environmental situation and analyzing the effectiveness of investment in environmental protection. For 2000–2020 for most regions of Russia, the pollution structure has become simpler, and the number of leading pollution factors has decreased. In the vast majority of regions, an excess of the average Russian values is typical of one to two subindices, while 10 years ago, it was three to four. The impact on water resources and the atmosphere, as well as radiation impact, were significantly reduced.

To a large extent, this structure is determined by three factors inherited from the previous period:

— The energy output of the leading industries, combined with the structure of the fuel balance of energy and district heating systems in the eastern part of the country. The highest energy output remains both in large industrial regions with a very high degree of environmental stress, and in regions with the lowest degree of environmental hazard, mainly due to increased consumption of coal in public utilities.

— Industrial specialization, age, and quality of assets. The institutional environment and policies of companies determine the degree of modernization of assets, this process proceeds at different speeds, and sometimes in different directions. The degree of industrial influence is declining, particularly intensively in the oil industry, but industry remains one of the leading and most dynamic factors of the ecological state.

— Accumulated radiation pollution is also one of the specific factors in some regions, but its role is gradually decreasing.

Impact of Economic Dynamics on the Change in AI Level in Regions

The high degree of interdependence of economic and ecological processes indicates the leading role of anthropogenic impact in shaping the environmental situation in Russia. During periods of economic crises, the reaction of both territorial and sectoral structures to economic downturn is much higher than at the economic growth stage.

Each stage of economic development of post-Soviet Russia had its own ecological projection. During 1990–1998, the AI level decreased significantly in most regions of the country, but much slower than the rate of decline in production, since sectors with the highest specific pollution (oil production, energy, and metallurgy) were characterized by relative economic stability. The structural shifts that have taken place in industry have only intensified the deformation of the sectoral structure of gross pollution, since they have led to an even greater “aggravation” of the economy, an increase in the share of the most natural-resource- and energy-intensive industries. As a result, the index of pollutant emissions on average for the country amounted to 58.3% (1999/1990), which exceeds the similar index for GDP and industrial production by 7 percentage points. At the same time, during the protracted crisis, environmental assets were reduced and technological degradation began, which led to additional loss of resources. Unused equipment was aging physically and technologically, the reduction in the number of employees, decrease in qualifications of personnel, and lack of proper pollution monitoring exacerbated the situation. During the transition period, the least favorable, in terms of environmental performance, structure of industrial production was formed.

Economic growth after 1998 led to an increase in air pollution, but at low rates. Already in 1999, the growth in industrial production amounted to 108.9%, while the growth in atmospheric pollution began only in 2000 and at a significantly lower rate than the growth in production (by 3.5 percentage points). This is because the compensatory rise in industry affected import-substituting industries (food, etc.) more rapidly with minimal specific pollution. In addition, in crisis conditions, enterprises liquidated the oldest and “dirty” part of the assets with the highest specific pollution, and relatively successful metallurgical, pulp and paper, and oil enterprises underwent reconstruction, which led to a decrease in specific and gross pollution. However, the technological modernization process began to slow in the face of growing investment risks.

Despite the relatively low growth rates of atmospheric pollution, the negative trends of the transition period could not be overcome; on the contrary, they even increased to a certain extent due to the peculiarities of the investment process and outstripping growth of the dirtiest industries. The initial stage of investment in conditions of economic growth was characterized by low capital intensity—an increase in the utilization of old facilities; the cost of overhaul was 2.7 times that of 1999. Only in 2006–2008 did environmental investment by large companies begin to play a role.

During the 2009–2010 crisis, air pollution again fell, then rose; dependence on production dynamics was manifested, but to a lesser extent than in the years of the previous crisis.

The influence of crises on the change in regional structure of pollution is much greater than that of economic growth: during the crisis of the 1990s, almost all regions reduced their pollution. However, the crisis did not liquidate the oldest assets of the most environmentally problematic sectors, coal energy and mining, and partly metallurgy, where assets were preserved in the production of pig iron, but the dirtiest open furnaces in steelmaking were liquidated everywhere. As a result, the sanitizing role of the systemic crisis ceased to manifest itself by 2003, and the growth of emissions and sinks became almost universal (although in 1999–2003, an increase in pollution was observed only in half the country’s regions). Since modernization was clearly insufficient, each subsequent stage of growth was accompanied by an increase in pollution, but very unevenly; territorial differentiation of AI increased in proportion to the growth rate of production.

In 2010–2020, the dependence of pollution volumes on production volumes was already minimal, but 85% of the pollution dynamics is still determined by three industries, the share of each of which in emission volumes is 1.5–2.5 times higher than in the industrial production volumes:

— extraction of fuel and energy minerals (the industry’s emissions are declining faster than the national average with respect to growth in production, so specific emissions are also declining but remain high);

— the metallurgical complex (characterized by a steady reduction in emissions with a slight decrease in production, but specific emissions continue to be some of the highest in the industry);

— production and distribution of electricity, industries with the highest specific atmospheric emissions, and the highest degree of dependence of pollution on production volumes (correlation coefficient 0.65), which indicates a low level of asset modernization.

By 2020, all three industries had reduced emissions by 10–15% versus 2010, but the most positive trends are typical of pulp and paper, chemical, coke and petroleum production, when, with a significant increase in production, a significant reduction in atmospheric pollution is observed.

The comprehensive IAI is less dependent on production dynamics than individual impact indicators. The comprehensive index contains indicators that to a greater (air and water pollution) or lesser (load on the forest complex, waste generation) extent depend on economic dynamics. The latter are determined by “genetic” factors of development. The interaction of genetic and transformational factors governs the nature of the spatial mosaic of AI in regions.

The highest level of discrepancy between economic development trends and the integral load index is typical of the most problematic regions: Krasnoyarsk krai and Chelyabinsk and Sverdlovsk oblasts (Fig. 2). The IAI in these regions is quite stable, and the growth of waste generation is offset by a decrease in radioactive and water load and relatively stable emissions. A negative correlation coefficient for IAI and GRP is also characteristic of other industrial regions (Perm krai; Nizhny Novgorod, Saratov, Samara, Sakhalin, and Vologda oblasts; the republics of Karelia, Tatarstan, and Bashkortostan; and the Yamal-Nenets Autonomous Okrug). Therefore, economic growth in industrial regions in the last decade is not directly related to an increase in AI. Meanwhile, it is in these regions that during crisis years, against a decrease in production, an increase (or at least stabilization) in anthropogenic load is observed.

Fig. 2.
figure 2

The level of dependence between the change in GRP and comprehensive index of anthropogenic impact (IAI) in Russian regions, 2000–2020. 1, Murmansk oblast; 2, Republic of Karelia; 3, Nenets Autonomous Okrug; 4, Chukotka Autonomous Okrug; 5, Kaliningrad oblast; 6, St. Petersburg and Leningrad oblast; 7, Novgorod oblast; 8, Vologda oblast; 9, Arkhangelsk oblast; 10, Komi Republic; 11, Yamalo-Nenets Autonomous Okrug; 12, Krasnoyarsk krai; 13, Sakha Republic (Yakutia); 14, Magadan oblast; 15, Kamchatka krai; 16, Pskov oblast; 17, Tver oblast; 18, Yaroslavl oblast; 19, Ivanovo oblast; 20, Kostroma oblast; 21, Republic of Mari El; 22, Kirov oblast; 23, Perm krai; 24, Khanty-Mansi Autonomous Okrug; 25, Tyumen oblast; 26, Tomsk oblast; 27, Kemerovo oblast; 28, Irkutsk oblast; 29, Amur oblast; 30, Khabarovsk krai; 31, Smolensk oblast; 32, Kaluga oblast; 33, Moscow and Moscow oblast; 34, Vladimir oblast; 35, Nizhny Novgorod oblast; 36, Chuvash Republic; 37, Republic of Tatarstan; 38, Republic of Udmurtia; 39, Sverdlovsk oblast; 40, Kurgan oblast; 41, Novosibirsk oblast; 42, Republic of Khakassia; 43, Republic of Buryatia; 44, Jewish Autonomous Oblast; 45, Primorsky krai; 46, Bryansk oblast; 47, Oryol oblast; 48, Tula oblast; 49, Ryazan oblast; 50, Republic of Mordovia; 51, Ulyanovsk oblast; 52, Samara oblast; 53, Republic of Bashkortostan; 54, Chelyabinsk oblast; 55, Omsk oblast; 56, Altai krai; 57, Tyva Republic; 58, Zabaykalsky krai; 59, Kursk oblast; 60, Lipetsk oblast; 61, Tambov oblast; 62, Penza oblast; 63, Saratov oblast; 64, Orenburg oblast; 65, Altai Republic; 66, Sakhalin oblast; 67, Belgorod oblast; 68, Voronezh oblast; 60, Volgograd oblast; 70, Republic of Crimea and Sevastopol; 71, Republic of Adygea; 72, Krasnodar krai; 73, Rostov oblast; 74, Republic of Kalmykia; 75, Astrakhan oblast; 76, Karachay-Cherkess Republic; 77, Stavropol krai; 78, Chechen Republic; 79, Republic of Dagestan; 80, Republic of Kabardino-Balkaria; 81, Republic of North Ossetia – Alania; 82, Republic of Ingushetia.

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Conversely, the highest degree of dependence is typical of agrarian or agroindustrial regions (Krasnodar and Altai krais; Ulyanovsk, Astrakhan, Kursk, Rostov, and Tambov oblasts; the republics of Dagestan, Mari El, and Crimea), as well as for regions where one of the key sources of pollution is fuel energy production with coal predominant in the structure of the fuel balance (Novosibirsk, Magadan, and Irkutsk oblasts; Primorsky krai; Tyva Republic). However, decoupling, or mismatching of trends, is a positive characteristic of a region, mainly at the growth stage, since if pollution increases during a decrease in production, this is the most negative scenario for environmental degradation.

The basic trends in the change in the territorial structure of AI in Russia are a general decrease in AI level, gradual alignment of regional proportions against a general slowdown in economic growth, a gradual decrease in dependence on the economic situation, and simplification of the structure of types of impact within regions. The main changes occur, as a rule, in the most polar groups—regions with very high and very low AI levels: these groups prove more stable or even expand during crises, since the regions in them produce goods with obsolete assets.

Changes in AI Level in Cities

Russian cities differ sharply in AI level. The dynamics of individual AI indicators in cities is largely governed by their population size, structure of production and fuel balance, and size and structure of the vehicle fleet. Therefore, analysis for groups of cities with different populations makes it possible to identify certain features of the transformation of AI.

For the vast majority of cities, the specific emission value is inversely proportional to population size. Moreover, the impact of the economic situation on pollution in different types of cities also depends on the size of the city, since during the years of crises, air pollution decreased in almost all cities, and during periods of growth, an adequate increase in atmospheric emissions involved only small and medium-sized cities for a long time. Thus, during the crisis years of the 1990s, emissions of harmful substances from industrial enterprises decreased in 82% of cities. Economic growth 1999–2008 caused an increase in pollution in 44% of cities, including half of small and medium-sized ones, and only in every third million-plus city. The 2008 crisis led to a new reduction in air pollution in 61% of Russian cities. Weak modernization, investment inactivity, and high fuel production of industrial and domestic sources of pollution determined the direct dependence of the dynamics of emissions on economic dynamics. In subsequent periods, the situation stabilized, the decline period was short, and growth was insignificant, quickly turning into stagnation in recent years, so emissions increased in 40–45% of cities with populations of up to 500 000 people and in 24–29% of major cities (Fig. 3).

Fig. 3.
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Share of cities that increased their gross atmospheric emissions, from total number of cities of corresponding population class, 1990–2020.

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After 2010, when economic growth slowed, the situation with pollution dynamics largely stabilized, and by 2014, the shares of polar groups in which atmospheric pollution was rapidly increasing or decreasing, decreased; on the contrary, in almost half of Russian cities, the volume of emissions changed by no more than 20%. In 2014–2020 pollution volumes had already increased mainly in major cities with populations of 500 000–1 000 000 people. Among them, the main growth was observed not in metallurgical centers, but in cities previously characterized by a reduction (Saratov, Krasnodar, Barnaul, Ulyanovsk, Vladivostok, Irkutsk, Tyumen, Naberezhnye Chelny). The volume of emissions in most cities fluctuated slightly, but was maximum in medium-sized cities (by 12%), as a result of which their contribution to the country’s gross pollution increased again up to 16%. Medium-sized cities are characterized by inertial pollution dynamics; therefore, during periods of economic recession, they are closer to small cities in type of dynamics: against a crisis, they begin to mono-specialize the economy, and pollution from the energy and extractive industries comes to the fore. During periods of economic growth, they tend to maintain the same level of pollution, which to some extent brings them closer to large cities.

Thus, whereas during the ten-year growth of the economy the urban structure of pollution almost returned to the 1990 level, after 2010, when economic growth slowed, the situation with the pollution dynamics stabilized to a large extent; in almost half of Russian cities, the volume of emissions became almost stable. However, by 2020, the number of cities in groups with either the highest growth rates of emissions or, conversely, with the fastest reduction has again increased.

Road transport is gradually becoming an increasingly important factor determining the environmental situation in Russian cities, despite the reduction in the standard for calculating emissions by three times since 2019. The increase in emissions is facilitated by high traffic intensity, topography, planning structure and new housing construction, the presence of bridges, road width, low road network connectivity, increased role of transit functions, etc. The reduction in emissions is facilitated by renewal of the vehicle fleet, improvement in fuel quality, expansion of the road network, strengthening of its connectivity, and reduction in barriers, i.e., the ability to move at optimal speed. As a result of the combined action of these factors, despite continued growth of the vehicle fleet, the volume of emissions in the country increased by only 13% compared to the beginning of the 2000s, and in total, it is even decreasing in cities. The decline occurred in all types of cities, with the exception of cities with million-plus population and other regional centers, where the introduction of fuel standards did not compensate for the explosive growth of the vehicle fleet. Small cities showed the greatest decline. In the level of decline, medium-sized cities occupy an intermediate position between small and large.

The volume of water consumption is a significant factor in the water resources depletion, which changes under the influence of economic activity and is an important component of the ecological state of territories. The water consumption dynamics, considered together with production volumes, can be considered a leading indicator of sustainable urban development. According to statistical data, ~62–67% of water is consumed in Russia just in cities.

In recent years, against a generally positive reduction in absolute and specific water consumption, the rate of reduction has significantly slowed down. The volume of water consumption in cities from surface sources has the same trend as water use for industrial needs: an increase in 2010–2011 and a gradual decline in recent years. Water consumption in 2010–2020 decreased by 20%, to the greatest extent in the largest (by 29%), million-plus, and medium-sized cities (by 25%).

The reduction in domestic and growth in industrial water consumption in the most water-intensive sectors largely explains the territorial differences between cities, which are much higher than interregional ones. The level of territorial concentration is also much higher: 1% of cities consume 40% of water taken from surface sources, and this share has been steadily increasing since 2009. Among the leading cities are mainly centers for the location of nuclear power plants, the largest fuel power plants, and Moscow and St. Petersburg.

The largest contribution to the volume of water consumption (40–43%) is made by small cities; their share is increasing, since the rate of reduction in their total water consumption is one of the lowest, only 2% for 2010–2020. Usually, due to the underdevelopment of water supply systems in small cities, their water consumption is much less than that of large ones. Such a high contribution of small cities is due to the placement in some of them of major state district power plants, nuclear power plants, and pulp and paper mills. Therefore, only 20 cities in which 0.4% of the population lives consume 72% of the volume of water used by this type of city.

Medium-sized and major cities differ from all others in the fastest rate of reduction in water consumption: 30% by 2020, mainly as a result of an increase in water circulation in the centers of state district power plants location (Nazarovo, Dzerzhinsky, Kirishi, Kstovo, and Neryungri). Water consumption by large cities has become fairly stable: it has decreased by only 7%, determined by a stable level in centers of chemistry, petrochemistry, oil refining, and the pulp and paper industry. The contribution of large cities to the volume of water consumption (7%) is two times less than the population size; they have the minimum per capita water consumption among all types, close to the level of million-plus cities (500–600 L per person per day), and it has decreased by 12% compared to 2010. The level of per capita water consumption has increased only in regional centers where there are large water-intensive industries, mainly metallurgical.

Million-plus cities have reduced the amount of water consumed by an average of 23%, with the maximum in Rostov-on-Don, Yekaterinburg, Nizhny Novgorod, Moscow, Voronezh, Kazan, and St. Pe-tersburg. Growth was observed only in Krasnoyarsk, by 17%. Per capita water consumption decreased even more and grew by 3% only in Krasnoyarsk.

The wastewater discharge volume decreased by 26% over the past 20 years, but continued to grow in every fourth city in the country. The dynamics of cities differ very significantly. Cities with populations of more than 500 000 are steadily reducing the volume of runoff. Compared to 2010, they have lost 24–37% of effluents. Stable runoff levels in small, medium-sized, and large cities. The dynamics of large cities is significantly different, which were characterized by a sharp growth in the period 2010–2013, mainly in centers of metallurgy and the pulp and paper industry, followed by a decrease. Among million-plus cities, an increase in runoff was observed in St. Petersburg, Nizhny Novgorod, and Novosibirsk; only Krasnoyarsk was stable throughout the entire period.

The comprehensive IAI in cities makes it possible not only to compare them with each other, but also to identify the features of the subregional structure of AI. Twenty-nine cities with populations of 18 mln people are characterized by the highest IAI values. The composition of this group is diverse: it includes three million-plus cities (Moscow, Novosibirsk, and Krasnoyarsk), four with populations of 500 000–1 000 000 people (Irkutsk, Khabarovsk, Kemerovo, Tula), seven large, three medium-sized, and 12 small cities, among which the city of Zapolyarny occupies first place.

The structure of the comprehensive index is very diverse even within the same group. For example, in the group of cities with the highest level of environmental stress—Zapolyarny, Moscow, and Norilsk, in centers of large coal-fired power plants location (Gusinoozersk), metallurgy (Tula)—the role of the air pollution subindex has increased. In Neryungri, Kemerovo, Kostomuksha, Bilibino, and Kovdor, the volume and structure of waste is the leading factor. In small cities of the East Ural, there are traces of radiation exposure from an accident at the Mayak Production Association.

The final value of the index was affected more strongly by the density of waste, emissions, and volume of load on water sources; significant deviations are also formed by radiation pollution. In small cities, indicators related to the level of improvement in the territory and radiation pollution have a stronger effect, since it is mainly small cities that have fallen into the zones of greatest radiation hazard. For cities with populations of over 500 000 people, the integral estimates are maximum and close in level; they have an increased share of atmospheric pollution, moreover, for million-plus cities, due to the influence of transport, and for major cities (more than 500 000), industrial influence.

Intraregional Distribution of Cities by IAI

Nearly 50 regions have centers with very high AI values, 47 of which are regional capitals. Such cities are distributed fairly evenly across the country; there is no disproportion between European and Asian Russia, although localization is more significant in regions of the Urals, the Volga region, and Southern Siberia. The maximum number of such cities (four) is in Irkutsk oblast, three each in Bashkiria and Sverdlovsk oblast, and two each in Republic of Tatarstan and Samara, Kemerovo, and Chelyabinsk oblasts.

The degree to which cities determine the environmental situation in their regions was revealed by the relation of IAI levels in a region and cities in its territory with respect to the average Russian level, which made it possible to identify the following territorial relations:

— In the regions of the Urals and Siberia, a high AI level, a diversified structure of pollution sources, and cities make an adequate contribution to the pollution of the territory as the largest regional centers, centers for the location of large enterprises of heavy industry. Among small and medium-sized cities, these are mining, aluminum industry, and energy centers, as well as cities of regional centers’ agglomerations. About 34 mln people live in such cities (Fig. 4).

Fig. 4.
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Distribution of population by cities according to level of index of anthropogenic impact (IAI).

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— In regions of European Russia with an average AI level, specializing in machinery industry, light and food industries, cities concentrating main pollution (52.7 mln people) are mainly the primary and secondary cities of relatively clean regions.

— In resource-producing regions, where a significant part of the impact is shifted outside the cities, the centers themselves are relatively clean (Tyumen oblast, Komi Republic). Small cities of regions where pollution is concentrated at the major heavy industry enterprises and localized in large cities are characterized by low AI levels in relatively more polluted territories; in total, 5.1% of the urban population lives in such cities.

— In the regions of the South, Center, and Volga region with moderate and low AI levels in cities specializing in the food and recreation industries, the level of impact is determined mainly by the agrarian complex; small and medium-sized cities are also characterized by a low AI level (5% of the urban population).

The comprehensive IAI does not have a statistically significant relationship with the population of a city, but its territorial differentiation within regions has a center–periphery character, although on the whole, with an increase in population, the probability of falling into the group with maximum values of individual indicators increases. Thus, in Moscow, almost all indicators are maximum, except for the share of contaminated wastewater and radiation exposure. Then, in descending order, follow St. Petersburg, Rostov-on-Don, Krasnoyarsk, Omsk, Tula, Khabarovsk, and Novosibirsk. Two hundred twenty-four cities have more than one indicator with a maximum value, and 603 more have at least one of the 21 indicators.

There is also no statistically significant relationship between the share in the structure of production of industries with high pollution levels and IAI. However, on average, for groups of single-industry cities with metallurgical specialization, the IAI is 16% higher than in cities with chemical production, 22% higher than in centers for production of electrical, electronic, and optical equipment; 25% higher in centers of pulp and paper production; and 46% higher than in food production centers.

CONCLUSIONS

The changes in the environmental situation in Russia that have taken place over the past 20 years are characterized by a general basic trend towards a reduction and a change in the structure of its determining factors; they manifest themselves differently at different levels.

For the country as a whole, the dependence of the pollution level on the level and dynamics of economic development is weakening due to modernization processes in industry, which was the leading source of anthropogenic impact in the Soviet period. However, the stark dynamics of the transition period gave way to weak fluctuations in the 2000s and often difficult to explain changes in the environmental situation, both on the whole and in its individual components, conditions, and factors.

At the regional level, there is a more complex relationship: a deep economic downturn tends to reduce pollution levels in all regions of the country, and economic growth is not always associated with growth in AI, in particular, if it starts in clean industries and with the use of new equipment. An insufficient level of terminating obsolete assets during periods of crisis and weak modernization lead to the fact that pollution increases with the onset of economic growth. However, the higher the economic growth rate, the more diverse the scenarios for changing anthropogenic impact.

The comprehensive index of anthropogenic impact (IAI) makes it possible to integrally assess the environmental situation in regions; the structure of the index reveals the leading factors of influence and can become the basis for developing regional environmental policy priorities, and the rating of regions based on IAI, for territorial development strategies. The IAI ranking of regions, like most Russian approaches in this area, is aimed at identifying the problem and encouraging “underachievers” to rectify this.

Trends in the environmental situation in cities and regions have both similarities and differences. The role of industrial pollution has decreased both for cities and regions, but for the latter, the role of industry is more pronounced due to the influence of extractive industries. A similarity is also manifested in the general basic trend in the reduction in anthropogenic impact, in the increasing role of such components as the load on water resources and waste generation, and in the increased contribution of pollution associated with vital activity of the population.

Even though the factors of formation of the environmental situation in cities and regions are similar in many respects, in cities they are more dynamic and more dependent on the level of improvement and development of housing and communal services. Road transport plays a special role in cities, the factors of which have changed rapidly in the last decade: the dependence of atmospheric pollution on the growth in the number of cars is decreasing and the role of such factors as engine and fuel quality, road network density, and traffic patterns is increasing.

In general, the trends in changes in the environmental situation in regions are smoother than in cities. The more diversified a region’s economy, the smaller the range of fluctuations in IAI, since economic and environmental indicators of development change at different rates in different sectors. The more developed the large urban settlement pattern in a region, the more complex and diverse the factors of the environmental situation. An exception is hydrocarbon production regions, where the main areas of pollution are shifted to nonurban areas.

The highest level of mismatch between economic development trends and the comprehensive load indicator is typical of regions with the highest IAI level. Conversely, agricultural or agroindustrial regions are characterized by the highest degree of dependence, as well as regions where one of the key sources of pollution is fuel energy with coal predominant in the fuel balance structure.

The dynamics of individual AI indicators are much more dependent on the dynamics of production and are often multidirectional. There is a discrepancy between trends in air pollution from industry and vehicles, water consumption from surface and underground sources, and wastewater volumes to the greatest extent for large and largest cities, and to the smallest extent for small and major cities. The worst-case scenarios are typical of small cities, whose environmental problems are complex, multifaceted; they are united by the inability to solve problems on their own.

Changing the territorial patterns of pollution makes it possible to identify the role of the main factors of the environmental situation in order to determine the directions for its improvement. The inherited territorial structure of the economy, the location of heavy industry with outdated assets, and the localization of the main extractive regions contribute to the conservation of the territorial structure of pollution. The interaction of genetic and transformational factors determines the nature of the spatial mosaic of AI both between regions, cities, and within them. For cities, institutional and consumer factors, the change in the role of the two leading actors of territorial and industrially isolated groups of the population and the state, are of particular importance. On the one hand, increasing state control has not yet incentivized producers to increase investment in environmental technologies. On the other hand, social groups with environmentally friendly consumption are gradually being formed in large cities. Among manufacturers, the emergence of a new actor—the management of large companies usually oriented towards Western markets and standards—has led to a specific manifestation of not only institutional factors, but also of economic and geographical location, since decisions can both depend on the location of an object and change this situation as a result of construction of new infrastructure.