Effectiveness of the Federal ‘Clean Air’ Project to Improve Air Quality in the Most Polluted Russian Cities

Abstract

An unavoidable adverse consequence of industrial development is the contamination of urban atmospheres. Deterioration of air quality leads to a decrease in the quality of life of the population, creates a lot of risks of serious diseases, and threatens to increase life expectancy. This phenomenon is particularly evident in many large Russian cities, where historically a powerful industry has developed. In recent decades, the Russian government has acknowledged environmental remediation as a pivotal priority for the National Development Goals. The dedicated funding from the National ‘Ecology’ Project in 2018–2024 allowed for large-scale public and private investments to address the problem of improving the air quality of urban areas in Russia. What is the effectiveness of this spending? In this article, we answer this question by analyzing the effectiveness of the Federal ‘Clean Air’ Project, part of the National ‘Ecology’ Project, which aimed to improve air quality in 12 of the most polluted Russian cities. We show that the project’s key performance indicators (KPIs) underwent significant changes over the 2018–2024 period. The emissions reduction target was lowered from 22% to 20%, the methodology for measuring pollution was revised, and new targets were set. One of the main reasons for this was the suboptimal quality of the data on which the initial plan was based. As a result, the revised emissions estimates produced by the project were found to exceed not only the target benchmarks but also the baseline. The planned targets are largely on track, and it is likely that the target of a 20% reduction in emissions from the 2017 baseline will be met. However, the link between the KPIs and the improvement in urban air quality is questionable. The initial phase of the ‘Clean Air’ Project was a valuable first step, particularly in establishing an air quality monitoring network and conducting detailed pollution assessments in 12 cities. However, to further improve project performance, it is essential to base project KPIs on estimates of air pollution-related health damage and economic losses.

1. Introduction

High air quality has become an essential requirement for living in modern cities. According to the World Health Organization (WHO), 92% of the world’s population is exposed to hazardous concentrations of particulate matter smaller than 2.5 microns (PM_2.5) [1]. Meanwhile, 99% of the world’s population lives in places that do not meet WHO air quality standards [2]. The evidence of health damage from air pollution is overwhelming [3,4,5,6]. Inhalation of air pollutants can aggravate existing diseases or cause new ones [7,8,9]. In particular, air pollution is associated with respiratory [10,11,12] and cardiovascular [13,14] diseases, fertility problems [15,16,17], some kinds of cancer [18,19,20], and other health problems [21,22]. In 2021, air pollution contributed to 8.1 million deaths, accounting for more than 12% of overall value [23].

There is mounting evidence to suggest a correlation between air pollution and climate change [24,25]. The primary sources of air pollution, including industrial facilities, transportation, and stand-alone heating, are also significant emitters of greenhouse gases, contributing to global warming [26]. Thus, climate change mitigation measures can simultaneously improve air quality and have beneficial effects on health and mortality reduction [27,28].

Furthermore, both of these challenges have substantial economic implications [29]. One of these patterns of emission–income dependence is known as the environmental Kuznets curve [30,31,32]. To an even greater extent, air pollution affects the economy through excess morbidity and mortality. The case study from Hungary shows that air pollution can cause a loss of 4.1–9.4% of GDP per year due to a reduced labor force, as well as an additional increase in health care costs amounting to 0.1% of GDP [33]. On the contrary, air pollution control strategies might have positive economic consequences [34].

These factors collectively prompt policymakers to pursue enhanced air quality in urban areas. A study conducted by the United Nations Environment Programme (UNEP) indicates that most countries are implementing measures to improve ambient air quality standards (124 out of 195 respondents), clean production incentives (108), household energy (95), and vehicle emission standards (71), and the number of such countries is increasing over time. According to the survey in 2020, 54 countries had a national air quality management strategy, framework or plan of action and 57 had national ambient air quality monitoring networks [1].

In Beijing, China, the campaign against air pollution is part of a five-year environmental protection plan [35]. Until 2013, emission standards for the energy and industrial sectors were tightened. Between 2014 and 2017, coal-fired power plants were closed, and natural gas-fired plants were put into operation. In the public sector, small-capacity coal-fired boilers were closed, and a program was designed to replace coal-fired heating in private residences with electric or gas heating alternatives [36]. To support this public spending, Beijing increased funding for the program nearly 10-fold from 2009 to 2017. As a result, concentrations of SO₂, CO, NO₂, and particulates with a diameter less then 10 μm (PM₁₀) and less than 2.5 μm (PM_2.5) decreased by 70.4%, 38.2%, 17.9%, 35.6%, and 22.2%, respectively, from 2013 to 2017 [35].

In South Korea, the Air Quality Improvement Plan has been in place since 2005 and aimed to reduce overall emissions, especially dust emissions from diesel vehicles [37]. Since 2017, this plan has prioritized the reduction in particulate matter emissions. From 2020, it has also included measures to implement a carbon neutral strategy. After the completion of the first phase of the air quality improvement campaign, the annual PM₁₀ concentration decreased to 45 microgram per m³ (μg/m³) in Seoul (from 60 μg/m³ in 2004) and 51 μg/m³ in Incheon (from 61 μg/m³ in 2004) in 2013 [38].

The 2013 Clean Air Program for Europe aims to improve air quality by the year 2030 and reduce the number of premature deaths associated with air pollution by half of the figure recorded in 2005 [39]. The program encompasses three main areas: the establishment of air quality standards for significant pollutants across EU member states, the formulation of national emission reduction objectives, and the delineation of emission standards for all major sources of pollution. As a result, EU emissions decreased significantly for most contaminants between 2000 and 2017 [40], and the number of premature deaths associated with particulate matter emissions decreased by 41% between 2005 and 2021 [41]. At the same time, current levels of pollutants in urban air remain above EU and WHO standards [40]. One of the key financing mechanisms for environmental protection and climate change mitigation in the European Union since 1992 is the LIFE (L’Instrument Financier pour l’Environnement) program [42]. The budget for the LIFE program for the period of 2021–2027 is projected to be €5.4 billion. To illustrate, in Poland and Bulgaria, the LIFE program is providing financial support for the replacement of small-scale solid fuel heating systems and for initiatives aimed at raising awareness of the methods and technologies that can be employed to reduce emissions from chimneys. These include an assessment of the cost-effectiveness and environmental impact of such measures [43,44].

Thus, we can conclude that the experience of different countries in implementing programs to improve urban air quality is generally similar in terms of the selected measures. Russia is not an exception in this case.

2. Russia’s State Policy on Urban Air Protection: National ‘Ecology’ Project

Since 2018, the Russian government has introduced a new mechanism for financing projects for the development of certain sectors, the so-called National Projects. One of these projects, ‘Ecology’, is dedicated to solving environmental problems and consists of ten structural blocks (so-called Federal Projects) by sector: waste utilization and recycling, elimination of landfills, preservation of forests and water bodies, reduction in atmospheric emissions, development of eco-tourism and environmental education, and preservation of biological diversity. The first cycle of the National Projects was designed for six years, until 2024, and is thus effectively coming to an end. Judging by the fact that the National Projects programs have been extended until 2030, the government recognizes their work as quite successful. For this reason, it is important to assess the results of the implementation of some National Projects and form recommendations for their further improvement.

The Federal ‘Clean Air’ Project, which is a component of the National ‘Ecology’ Project, commenced in 2019 in 12 Russian cities that were identified as being severely polluted (Figure 1). In fact, it is one of the first large-scale government programs dedicated specifically to air quality, making analysis of its effectiveness particularly relevant. The principal objective of the ‘Clean Air’ Project was to reduce the pollutant emissions across all participating cities by 2 million tons (Mt) by 2026, inclusive of a 1.6 Mt reduction in hazardous substances. The Russian Federal Service for the Oversight of Consumer Protection and Welfare (Rospotrebnadzor) recognizes 56 substances as hazardous pollutants whose emissions violate environmental protection standards and pose a threat to public health [45].

Table 1. The main pollutants by emission source in 12 cities.

Pollutant	Number of Cities Where the Concentration of the Substance Exceeded the Hygienic Thresholds Defined by Rospotrebnadzor [45]
	Transport	Industry	Social and Public Infrastructure	Total
Nitrogen dioxide	11	4	–	12
Carbon monoxide	–	2	4	6
Inorganic dust containing silicon dioxide	–	5	3	6
Abrasive dust	–	4	–	4
Hydrogen fluoride	–	3	–	3
Sulfur dioxide	–	2	1	3
Benzo[a]pyrene	–	2	–	2
Calcium oxide	–	2	–	2
Hydrogen sulfide	–	1	1	2
Carbon black	–	1	–	1
Ethanethiol	–	1	–	1
Gasoline (petroleum, low-sulfur) converted to carbon emissions	–	1	–	1
Lead and its inorganic compounds	–	1	–	1
Manganese and its compounds	–	1	–	1
Meat and bone meal dust	–	1	–	1
Methane	–	1	–	1
Methyl methacrylate	–	1	–	1
Naphthalene	–	1	–	1
Nitric oxide	–	1	–	1
Organic direct dyes	–	1	–	1
Heterogeneous suspended solid matter other than PM10 and PM2.5, contained in pollutant emissions	–	1	–	1
Selenium dioxide	–	1	–	1
White phosphorus	–	1	–	1

presents the list of hazardous air pollutants for which exceedances of the permissible concentration threshold were observed in 2023.

The baseline for the project is 2017, when total emissions in 12 cities were 3.8 Mt, including 2.6 Mt of hazardous air pollutants. The primary objectives of the project are the monitoring and control of air quality, the modernization of industrial enterprises and existing heating facilities, the conversion of residential heating from coal to more environmentally friendly fuel, and the introduction of public transport utilizing electricity and natural gas fuel.

In order to fulfill the project objectives, Federal Law No. 195, entitled “On Conducting an Experiment on Quoting Emissions of Pollutants and Amending Certain Legislative Acts of the Russian Federation to Reduce Air Pollution”, was adopted in 2019. To achieve the common goal of reducing air emissions, cooperation between regional authorities and federal services is organized as specified below.

In accordance with Federal Law No. 195, the regional authorities that govern the 12 cities implementing the project were obliged to develop a “Comprehensive emissions reduction plan” (Comprehensive Plan) [47]. Such Comprehensive Plans should include emission reduction targets, a list of measures to reduce emissions from industry, transportation, and social and municipal infrastructure, with an indication of deadlines, amounts, and sources of funding. The governors of the regions participating in the ‘Clean Air’ Project are held personally accountable for achieving the targets set forth in the Comprehensive Plan. A particularly crucial area of focus was the enhancement of the quality of initial data on atmospheric pollution. Federal Law No. 195 mandated the establishment and operation of a federal state information system for monitoring of atmospheric air quality in the 12 pilot cities. Furthermore, Consolidated Calculations were conducted for all 12 cities, comprising characteristics of the territory, a list of pollutants, pollution zones, and emission sources. To date, these calculations have been performed twice, in 2020 and 2023 [46].

Based on the Consolidated Calculations, Rospotrebnadzor, is tasked with conducting human health risk assessments and determining the list of priority pollutants for each city. Another Russian federal service, Rosprirodnadzor, the Federal Service for the Supervision of Natural Resources, which is responsible for ecological issues, establishes emission quotas that must not exceed permissible contributions to the atmosphere. The executive authorities of the Russian regions must ensure that quotas are not exceeded in transportation, utility, and social infrastructure facilities. Polluting companies are responsible for ensuring that industrial emission quotas are not exceeded or, alternatively, that compensatory measures are implemented.

Since 1 September 2023, 29 new cities have joined the Federal ‘Clean Air’ Project with the ambitious task of gradually halving harmful pollutant emissions by 2036 compared with baseline levels in 2020. This paper aims to evaluate the effectiveness of the activities carried out for the first 12 cities of the project and to discuss the prospects for the new participating cities.

3. Literature Review on Air Pollution in Russia

The highest levels of pollution are predominantly observed in the Siberian (Irkutsk Oblast, Krasnoyarsk Krai) and the Ural (Sverdlovsk Oblast, Chelyabinsk Oblast) regions of Russia [48,49]. The causes of poor air quality in Russian cities from 1991 to 2016 can be attributed to a number of factors, including large-scale industrial emissions (Norilsk, Novokuznetsk), transportation emissions (Moscow, Yekaterinburg), a high natural potential for atmospheric pollution (Chita, Neryungri), and transboundary effects from geographically proximate external sources (Minusinsk) [50]. Studies analyzing satellite data are a valuable contribution to ground-based inventories [51]. For instance, the article [52] studies data from the TROPOspheric Monitoring Instrument of the Sentinel-5P Earth observation satellite and concludes that air pollution in cities is caused by both natural and anthropogenic factors. The authors considered the 20 largest cities of Russia with a population of more than 600 thousand people. The obvious hypothesis of the connection between urbanization and the growth of pollution levels is confirmed. Among the environmental factors, dust storms are influential in the cities of southern Russia, while natural fires contribute greatly to the increase in aerosol concentrations in the European part of Russia and Siberia [52]. Another study using data from the satellite found that for the period of 1996–2009, there was a linear growth of NO₂ concentrations over St. Petersburg of about 4% per year [53]. Similar studies were also conducted for Norilsk [54], Moscow, and Moscow Oblast [55]. Furthermore, on the example of 78 Russian cities, it was shown that the restriction of economic activity due to the COVID-19 pandemic had a great impact on NO₂ concentrations due to the reduced use of public and private transport and practically no impact on formaldehyde and carbon monoxide emissions [56].

However, most of the literature on the ‘Clean Air’ Project focuses on the 12 cities participating in the program. Irrespective of the underlying cause, air pollution has the potential to act as a trigger for disease or exacerbate pre-existing pathologies. In [57], the dynamics of atmospheric emissions and population morbidity for the period of 2012–2021 were analyzed. The results demonstrated a 1.7-fold reduction in the proportion of ambient air samples that did not meet hygienic standards, which led to a 2.8-fold decrease in the incidence of additional disease cases. Furthermore, it is essential to consider the limitations of the statistical data on air pollution and morbidity, as well as the frequent amendments to hygienic standards over the specified period. The lack of reliable quantitative data on pollutant emissions into the atmosphere across the majority of Russia’s territory is a significant obstacle to analyzing emission dynamics and assessing public health risk [58]. Concurrently, assessments of carcinogenic and non-carcinogenic health risks indicate that up to 78% of the population in the 12 cities participating in the ‘Clean Air’ project is at significant risk for some substances [59].

A considerable amount of research is devoted to the assessment of emissions from stand-alone heating sources and their associated impacts on human health. Approximately 75,000 stand-alone heating facilities are currently in operation in Russia [60]. The majority of these plants are coal-fired, located in close proximity to residential buildings, with low stack heights and a long heating season. This configuration results in significant air pollution, particularly in the surface layers [61,62]. The pollutants emitted by stand-alone heating sources can have adverse effects on public health, including respiratory organs, the blood system, developmental processes, the immune system, the cardiovascular system, the central nervous, and reproductive systems [63]. Kuznetsov and Bobylev demonstrated that the transition from coal-fired power generation to gasification in the Zabaikalsky Krai of Russia may yield a cumulative economic effect ten times greater than the initial investment, including an increase in life expectancy and human capital [64]. To reduce socio-economic consequences for the population from air pollution, it is essential to introduce a system of identification of sources of atmospheric pollution, long-term assessment of health risk to the population, and targeted compensation for the financial losses incurred by citizens as a result of diseases caused by air pollution [48].

Studies providing estimates of the pollution level, descriptions of the main pollutant substances, and statistics of morbidity associated with air contamination have been carried out in most of the cities participating in the project. These include Bratsk [65,66], Krasnoyarsk [63,67], Nizhny Tagil [68,69], Norilsk [70,71], Chita [72,73], Omsk [74,75,76], and others [59,77]. Furthermore, studies have been conducted in the cities that became participants of the second stage of the project since 2023 [78]. Few studies were carried out by research organizations of Rospotrebnadzor and were devoted to the development of air pollution monitoring programs and testing them in the context of individual cities or sources of pollution (see, for example, [65,68,73,79,80]).

A specific promising area of research is the study of subjective satisfaction of the citizens with the quality of atmospheric air [81,82,83,84]. In recent years there has been a notable increase in the demand from the younger population in Russia for improvements to be made to the quality of the environment [85]. A survey conducted in one of the Siberian cities participating in the ‘Clean Air’ Project in December 2021 revealed that 52% of the population expressed complete dissatisfaction with air quality, while 35% indicated mostly dissatisfaction [86]. At the same time, 40% of respondents believed that air quality had significantly deteriorated over the past year. The authors also note that subjective perception of air quality is frequently associated with organoleptic sensations, rather than specific chemical compounds.

In general, despite the valuable research on the assessment of the effectiveness of the ‘Clean Air’ project in terms of the dynamics of human health risks [77,87], it can be concluded that a comprehensive assessment of the progress in achieving the project targets, its environmental and economic effectiveness, has not yet been conducted. This paper aims to contribute to filling this gap.

4. Materials and Methods

The principal document delineating the target indicators, sources, and volumes of financing is the passport of the National ‘Ecology’ Project, comprising several Federal Projects including ‘Clean Air’ [88]. Since the project’s inception in 2018, the targets and activities outlined in the passport have undergone periodic revision, thereby facilitating an assessment of the project’s evolving trajectory. In addition, the Comprehensive Plan and the Consolidated Calculations are available for each city, containing data on air pollution and the progress of the ‘Clean Air’ project [89]. In this paper, we utilize these documents as the primary data sources to analyze the efficacy of the ‘Clean Air’ project in 12 Russian cities. Given the inherent limitations in the number of observations, we refrain from employing sophisticated data analysis techniques, except for the correlation analysis and distribution analysis. To visualize the results, we employ the ggplot2 package version 3.5.1 [90] in the open-source R Core Team software environment version 4.3.2 [91].

The success of the implementation of the project will be evaluated by comparing the predetermined objectives with the actual outcomes and by examining the most effective practices. This will enable the determination of the extent to which the circumstances in the 12 cities have evolved between 2019 and 2024, as well as the establishment of strategies to enhance the budgetary and environmental efficiency of the 29 cities that have joined the second phase of the project.

5. Results

5.1. Evolution of Goals of the ‘Clean Air’ Project

The first iteration of the Passport of the National ‘Ecology’ Project, approved on 24 December 2018 [88], identified the principal objective of the ‘Clean Air’ Project as the reduction in atmospheric air pollution in major industrial urban centers, including a minimum 20% reduction in the total emissions of pollutants into the atmospheric air in the most polluted cities. As of the baseline year, 2017, air pollution levels were deemed to be high or very high in 8 out of 12 cities engaged in the project. There was considerable variation in the mass of emissions across the cities, but in almost all cases, the proportion of pollution from stationary sources exceeded 90%, which is consistent with their status as industrial centers (

Table 2. Pollution characteristics of the ‘Clean Air’ Project’s participants, as of 2017.

Cities	Abbreviation	Air Pollution Level	Emissions, 1000 Tons			Emission Structure, %
			Industry	Transport	Stand-Alone Heating	Industry	Transport	Stand-Alone Heating
Bratsk	Br	Very high	111.2	0.6	1.0	98.6	0.5	0.9
Krasnoyarsk	Kr	Very high	117.6	2.9	5.3	93.5	2.3	4.2
Lipetsk	Li	Elevated	286.0	0.7	0.9	99.4	0.3	0.3
Magnitogorsk	Mag	Very high	226.9	1.4	1.9	98.6	0.6	0.8
Mednogorsk	Med	Elevated	7.3	0.01	0.3	96.0	0.2	3.9
Nizhniy Tagil	NT	High	138.8	1.5	5.4	95.2	1.0	3.7
Novokuznetsk	Nov	Very high	313.3	1.6	18.8	93.9	0.5	5.6
Norilsk	Nor	Very high	1720.2	0.8	0.0	100.0	0.0	0.0
Omsk	Om	Low	178.2	1.1	37.6	82.1	0.5	17.3
Chelyabinsk	Chel	High	207.0	1.4	2.5	98.2	0.6	1.2
Cherepovets	Cher	Elevated	318.4	0.7	0.1	99.8	0.2	0.0
Chita	Chi	Very high	39.2	1.0	34.3	52.6	1.3	46.1

Note: Since 2022, the level of pollution in a given urban area is calculated using a procedure [92] that includes a number of indicators that take into account both maximum short-term and long-term concentrations of harmful substances in the atmosphere.

).

In comparison to the initial 2018 iteration (

Table 3. Key performance indicators of the ‘Clean Air’ Project as of 2018 [88].

KPI of ‘Clean Air’ Project, 2018	Baseline	2019	2020	2021	2022	2023	2024
Number of cities with high and very high levels of air pollution, units	8	8	6	5	3	2	0
Decrease in total emissions (share of remaining emissions from the baseline assumed to be 100%), %	100	100	97	95	93	81	78
Number of Comprehensive Ecological Permissions (CEPs) issued to enterprises, units	0	15	80	150	300	4000	6900
Decreased import share of basic technological equipment operated in case of application of the Best Available Technologies (BAT), %	50	50	47	44	40	38	36

), the project target indicators have undergone modification in the revised version of the National ‘Ecology’ Project’s passport of 2024 (

Table 4. Key performance indicators of the ‘Clean Air’ project as of 2024 [93].

KPIs of the ‘Clean Air’ Project, 2024	Baseline	2020	2021	2022	2023	2024	2025	2026
Number of cities with high and very high levels of air pollution among 12 pilot cities, units	8	6	5	11	11	7	6	0
Decrease in total emissions (share of remaining emissions from the baseline assumed to be 100%), %	100	–	96	92	88.4	85	85	80
Decrease in emissions of harmful pollutants (share of remaining hazardous emissions from the baseline assumed to be 100%), %	100	–	96	92	88.2	85	85	80
Population that will have improved quality of life due to reduced emissions, 1000 people	1601.2	–	1945.9	2599.6	2599.6	4272.9	4623.0	6292.4
Number of Comprehensive Ecological Permissions (CEPs) given to all facilities that have a significant negative impact on atmospheric air and implement programs to improve environmental efficiency using the Best Available Technologies (BATs) to reduce emissions, units	2	2	2	3	3	7	7	–
Number of facilities with a negative impact on atmospheric air that have been modernized, including with the use of the BATs and/or with the use of green finance instruments, units	–	–	–	–	–	5	10	–

) [93]. In addition, the initial deadlines for achieving the key performance indicators by the conclusion of 2024 have been extended by a period of two years, until 31 December 2026.

The following section will examine the alterations that have been made to the project goals in the revised 2024 version in comparison to the original version. The number of indicators has increased from 4 to 6, and the target values and methodologies for defining indicators have also undergone modification.

In the first iteration of the National ‘Ecology’ Project passport, introduced in 2018, 8 out of 12 cities showed air pollution levels classified as high or very high. In accordance with the objective, it was anticipated that all of them would be removed from this category by 2024. However, a new procedure for determining air pollution levels was adopted in 2022 [92], resulting in a change to the baseline from 8 in 2017 to 11 in 2022. The new target also assumes that all these cities will cease to be classified as highly polluted by 2026. The most contradictory point appears to be that Novokuznetsk was initially included in the list of highly polluted cities but subsequently removed from this list in the revised procedure [94]. According to official Russian statistics from the Unified Interagency Information and Statistical System (EMISS), only Novokuznetsk, Cherepovets, and Chelyabinsk are currently not considered as cities with high or very high levels of air pollution [94].

In a revised iteration of the National ‘Ecology’ Project, the objective for total emissions has been adjusted. Originally, they were to be reduced by 22% from the 2017 baseline by 2024. The new targets are 15% in 2024 and 20% in 2026. As of September 2024, Russia’s average emissions are 85.6% of the baseline value [94]. Meanwhile, the values vary significantly by city, with figures ranging from 76.4% in Cherepovets to 98.4% in Norilsk. Furthermore, a new indicator has been introduced to reflect the reduction in hazardous emissions, which must also be cut by 20% from 2017 levels by 2026. In this regard, emissions of substances from the special list of “priority pollutants” are considered to be harmful [95]. The specific list of pollutants differs depending on the city in question. The emission of such contaminants has an impact on the exceedance of hygienic standards for atmospheric air quality, thereby creating risks for human health. Given that not all pollutants have a detrimental impact on human health, accounting for reductions in emissions of harmful pollutants specific to each city seems reasonable. The current average level of harmful emissions is 84.8% of the baseline. The most favorable outcomes were observed in Novokuznetsk (67.6%), while the change in Norilsk was the least (98.4%) [94].

A new indicator was added to the performance indicators, reflecting the satisfaction of the population with the improvement of environmental quality. However, the methodology for measuring the indicator does not contain an approach to assessing the quality of life [96]. In fact, the indicator is calculated as the number of the city’s population that managed to achieve the goal of reducing harmful emissions by 20% in comparison to 2017. As of September 2024, more than 4 million people have improved their quality of life in the following cities: Cherepovets, Novokuznetsk, Lipetsk, Omsk, Mednogorsk, and Magnitogorsk, which is quite consistent with the plan [94]. Still, this indicator does not account for the fact that individuals residing at varying distances from a stationary source that has reduced emissions are likely to experience disparate improvements in their quality of life. For instance, studies show that implementation of measures laid down by the Federal ‘Clean Air’ Project in the city of Krasnoyarsk with regard to stand-alone heating sources will reduce acute risks only for 50,000 people and chronic risks for 35,000 citizens. In its current form, the indicator appears to be superfluous, as it depends primarily on the size of the urban population, rather than on the efficacy of emission reductions.

Two key indicators refer to air-polluting enterprises: the number of comprehensive ecological permissions obtained and the number of modernized facilities. Both indicators pertain to the implementation of the best available technologies (BATs) at polluting enterprises. Moreover, both have undergone notable alterations throughout the various iterations of the project passport. The Russian government has implemented policies that encourage enterprises to invest in modernization of production processes, utilizing the best available technologies to reduce environmental damage. One of the principal instruments employed to implement this policy is the issuance of a comprehensive ecological permit (CEP).

A comprehensive ecological permit is a special document that contains requirements for environmental protection and replaces multiple permitting documents for an enterprise that has a large negative impact on the environment. Obtaining CEP is mandatory for a special category of enterprises that have a significant negative impact on the environment and belong to the areas of application of the best available technologies. Such enterprises include oil and gas production facilities, metallurgy, chemical production, mining, and other facilities [63,97]. Russia has approximately 6000 such enterprises, with the top 300 largest accounting for two-thirds of all emissions.

To obtain a CEP, an enterprise must satisfy a considerable number of requirements, including an inventory of emission sources, calculation of permissible emission levels, development of an environmental efficiency improvement program, modernization program based on the best available technologies, and a program for monitoring the condition and pollution of the environment in the territories of waste disposal facilities. If an enterprise, as a consequence of modernization, becomes compliant with the best available technologies and obtains CEP, its payment for negative environmental impact will be rendered null. In addition to the evident advantages for the public and the state, companies may also gain competitive advantages. Implementing BAT and obtaining CEP actually verifies companies’ green projects and confirms their compliance with ESG criteria [98]. The National ‘Ecology’ Project anticipated that 300 of Russia’s largest polluters would obtain comprehensive environmental permits by the end of 2022.

Furthermore, as a consequence of international trade sanctions imposed on Russia, the deadline for obtaining CEPs was extended by a period of two years. The objective was to facilitate the procurement of analogous equipment needed for modernization, which had previously been imported from other countries [99]. The new deadline is 1 January 2025. Thereafter, the penalty for environmental damage caused by enterprises that have not obtained the CEP will be 100 times the current rate, while the penalty for waste disposal will be 25 times the current rate. In contrast, the 300 largest polluters have been granted a privileged status, with the deadline for obtaining a CEP set for the end of 2024.

Notwithstanding the potentially considerable penalties, the implementation of BAT is still progressing at a disappointingly slow pace. In the initial passport of the National ‘Ecology’ Project of 2018, it was assumed that 6900 enterprises in Russia should receive CEP by 2024, which would generally contribute to the reduction in air pollution. Subsequently, the list of enterprises was reduced and now includes about 5800 polluting enterprises. As of mid-2024, less than 900 of them have obtained CEPs [100]. At the same time, fines increased by 100 times can bring the companies to the edge of bankruptcy. In this regard, the Russian Union of Industrialists and Entrepreneurs (RSPP) is asking the Russian government for a new postponement [101]. In addition, about 1500 companies have changed the environmental hazard category of their production to a more lenient one, which also necessitates a government audit [102]. Another major concern is that receiving CEP only means having a BAT-based environmental modernization program. CEP is valid for seven years, which allows for the full implementation of BAT to be achieved only by the end of this period, i.e., by 2032.

For fuel and energy companies in 12 cities that are participating in the ‘Clean Air’ Project, preferential loans for the modernization of power generation and heat supply facilities are available from 2023. The interest rate on such loans for enterprises is 3%, with the discrepancy between this and the market rate subsidized by the government until the end of 2024 [103]. However, if the deadline for obtaining CEP is further extended, an extension of this support measure can also be expected. As of September 2024, 20 CEPs have been issued in the cities participating in the ‘Clean Air’ Project, and six of these have been issued to enterprises in Novokuznetsk [94]. This appears to be significantly higher than the target value of seven. At the same time, the completion of modernization using the BAT is noted only in two enterprises in Krasnoyarsk and one entity in Bratsk. Apparently, these results are ensured by United Company RUSAL, which has introduced at its aluminum plants in these cities electrolyzers of its own design, allowing the efficiency of fluoride and benzo[a]pyrene capture to exceed 99% [104].

The ‘Clean Air’ Project accorded particular attention to the establishment of an environmental air quality monitoring network in all participating cities [78,105]. Additionally, the National ‘Ecology’ Project also includes the Federal ‘Ecomonitoring’ Project, which implies the creation of a comprehensive information system for environmental monitoring: FGIS Ecomonitoring [106]. Data from automatic environmental monitoring systems established in 12 cities participating in the ‘Clean Air’ Project should also be incorporated in this system [107]. Technically, monitoring data are currently available in all 12 cities, as well as for the 29 new project participants. Meanwhile, the amount of openly available data varies significantly between cities. For example, there are convenient interactive maps of Krasnoyarsk, Chelyabinsk, and Mednogorsk that allow us to see the locations of stationary stations and track the values of air pollution indicators in real time. In many other cities, only pollution levels (from low to high) are indicated without numerical values, specification of pollutants, and monitoring station location. The new decree of the Russian Government additionally requires enterprises in 12 cities participating in the ‘Clean Air’ Project to implement a system of automatic control of at least 70% of emissions for 14 main pollutants starting 1 September 2024 [108].

5.2. Patterns of the ‘Clean Air’ Project Implementation in 12 Russian Cities

The analysis of the environmental situation in a particular city is based on data from two key documents for each settlement: the Comprehensive Plan and the Consolidated Calculations, which contain pollution statistics, volumes and sources of funding, and a description of measures to achieve KPIs [89]. Depending on the source, emissions can be classified into three main categories: industrial, transportation-related, and emissions from municipal and social infrastructure facilities. It is important to note the discrepancies in accounting for emissions from municipal and social infrastructure facilities in these two documents. The Consolidated Calculations consider solely private and municipal independent heat supply sources. At the same time, Comprehensive Plans incorporate strategies for curbing emissions from landfills and sewerage systems. As Comprehensive Plans usually describe only emission reduction strategies, rather than initial emission volumes, henceforth we will refer to total emissions without considering other infrastructure facilities beyond stand-alone heat supply sources, in accordance with Consolidated Calculations.

In contrast to the passport of the National ‘Ecology’ Project, the cities’ Comprehensive Plans contain only 2 KPIs: a reduction in the total emissions and a reduction in harmful substances emissions. Among the cities included in the analysis, only Norilsk has additional targets set forth in its Comprehensive Plan that includes two key targets: firstly, a reduction in the level of air pollution from very high to elevated levels; and secondly, an improvement in the quality of life of a specified number of people due to the reduction in emissions. Another particular KPI for Norilsk is the objective to increase the volume of natural gas consumption as a motor fuel from 0 to 1.9 million cubic meters. In fact, this means that for most cities, KPIs have not been revised since the first version of the National ‘Ecology’ Project passport. In addition, the cities’ Comprehensive Plans did not initially include CEPs.

Figure 2 reflects the ratio of funding levels reported in Comprehensive Plans and emissions according to the 2023 Consolidated Calculations. Norilsk is the leader by a large margin in both respects.

The funding sources are classified into three categories: federal budgetary funds, funds from the consolidated budget of the region, and off-budget funds, which actually reflect private investments in modernization of the polluting companies themselves. Generally, the region’s own funds are small and are provided by transfers from the federal budget. In addition, in a number of cases, financing of measures to reduce emissions from transport, social, and municipal infrastructure can be financed by other federal and regional initiatives, such as ‘Safe and Quality Roads’, ‘Clean Country’, ‘Affordable and Quality Housing’, and so on. The structure of emissions and financing by sources is presented in Figure 3.

The cities differ significantly in the emissions levels, yet their structure is generally the same. With the exception of Chita, the overwhelming majority of emissions originate from enterprises situated within all of the aforementioned cities. This is also influences the structure of funding. In fact, in almost all cities, the largest share of the ‘Clean Air’ Project costs is borne by polluting enterprises. Figure 2 and Figure 3 illustrate that the amount of allocated funding is not always directly proportional to the level of pollution. For instance, the levels of emissions in Lipetsk and Cherepovets are comparable, yet the amount of private investment in these cities exhibits a threefold discrepancy. A similar pattern is observed in Omsk and Magnitogorsk.

It is difficult to compare cities because the number of air monitoring stations, the number of inhabitants, and the geographical landscape vary considerably. In almost all of them, the main polluters are industrial enterprises. Chita is the only exception, with thermal power plants and stand-alone heating being the largest contributors to atmospheric emissions. Outdated technologies of thermal power plants and boiler houses, together with the fact that the city is located in a basin, determine a high level of pollution in the surface layers of the atmosphere. A similar effect is observed in Krasnoyarsk, but the contribution of stand-alone heating to air pollution is incomparably less than industrial emissions. In contrast with Chita, in other cities the polluters are large industrial enterprises of ferrous and non-ferrous metallurgy, mining and processing plants, the chemical industry, and machine building. The specialization of these enterprises, as a rule, determines the set and mass of harmful substances polluting the atmospheric air in the city.

In addition, it can be argued that the relationship between the amount of financing and the expected plans of emission reduction is also not so clear. The correlation coefficients for the total amount of financing and emission reduction plans turned out to be insignificant (p-values > 0.1) for all subsamples by the emission source and the pooled sample of 11 cities, excluding Norilsk (Figure 4). The inclusion of Norilsk in the subsample makes the correlation coefficient for industrial emissions significant due to the extremely high pollution values in this city. In general, for all sectors, the correlation coefficient is only 0.24. The strongest correlation is demonstrated by the transport sector (0.42). However, it should be noted that this is the sector with the lowest expected effects and the lowest amount of investment. The sector of public utilities and social infrastructure shows a negative coefficient. This discrepancy may be attributed to the heterogeneity of the data, as the composition of this sector may vary across cities, encompassing elements such as individual heat supply to private residences, municipal boiler houses, and challenges associated with waste management.

Next, we examined the allocation of specific funding by sector, taking as efficiency the amount of investment per ton of emissions reduced under the 2026 target (Figure 5). In this case, the assumption is made that the investment resulted in the targeted emissions reductions in the target amount, although this is not explicitly stated.

The distribution of expenditures per 1 ton reduced emissions across sectors is unequal. The Kruskal—Wallis test confirms statistically significant differences with ${\chi }^2$ = 15.4 (p-value < 0.0005). Epsilon-squared effect size measure ${\epsilon }^2$ = 0.5 shows that the difference in funding volumes between pollution sources is strong [109,110,111]. The costs of transportation are disproportionately greater than the potential environmental benefits. This is particularly evident in Krasnoyarsk and Omsk. Obviously, such expenditures have valuable positive social effects and benefits to society. However, within the context of this Federal Project, they can present indicators for reporting in a favorable light but do not fundamentally improve the environmental situation. At the same time, it is important to consider that, in absolute terms, the costs of transportation and the expected environmental effects are significantly lower than the values for industry or social and communal infrastructure.

In Section 5.1, the efficacy of the Federal Project designated for the improvement of air quality is significantly impeded by alterations in the number and composition of its key performance indicators (KPIs). A further issue is the low reliability of contamination data at the time of project launch. The consolidated calculations carried out in 2020 and 2023 aimed to update the air pollution data and become the basis for the assessment of public health risk and emission quotas for polluting enterprises. Figure 6 presents a comparison between the emission reduction targets reflected in the Comprehensive Plans made for 12 cities and the Summary Calculations (results of updated statistics) conducted in 2020 and 2023.

Following the Consolidated Calculations conducted in 2020, it became evident that initial baselines and reduction goals are inadequate for almost all 12 cities. Despite that, their Comprehensive Plans were not adjusted even after the new results of Consolidated Calculations in 2023. In most cases, the 2020 and 2023 Consolidated Calculations data not only exceed the expected results of project implementation in 2026, but even the 2017 Comprehensive Plans baselines (Figure 6). At the same time, data of the Consolidated Calculations regarding emissions from municipal and social infrastructure contain only emissions from stand-alone heating sources but exclude municipal boiler houses and emissions from waste and sewerage. Meanwhile, the Comprehensive Plan for Chelyabinsk indicates that most of the total emissions reduction (62,800 tons) will be achieved through the reclamation of areas occupied by the city’s landfill. In addition, for some cities, such as Krasnoyarsk and Mednogorsk, the data of the Consolidated Calculations of 2023 even exceed the values in 2020, which also indicates the volatility of the calculation approach. The number of observed pollutant facilities has increased in many cities between 2020 and 2023.

The results of the comparison demonstrate that the quality of the statistics utilized to construct the original Comprehensive Plans is poor, which presents a significant challenge in accurately evaluating the efficacy of the implemented activities. Currently, the Consolidated Calculations for 29 new cities are ready. These will serve as the foundation for the new Comprehensive Plans, which should result in a twofold reduction in harmful emissions by 2036 compared to the new 2020 baseline. It can be concluded that the most important useful result of the first stage of the ‘Clean Air’ Project was the establishment of a monitoring system and the enhancement of statistical accounting for pollution. However, it is challenging to evaluate the efficacy of emission reduction measures in terms of budgetary and environmental efficiency.

6. Discussion

This paper seeks to assess the efficacy of the Russian government’s ‘Clean Air’ Project, which was implemented during 2019–2024 and was designed to reduce pollutant emissions by 20–22% from the 2017 baseline. In contrast to the large number of studies devoted to the evaluation of damage to public health in Russian cities [68,74,77,79,87], this study represents the first attempt to assess the fulfillment of the KPIs set out in the ‘Clean Air’ Project, as well as the relationship between the funding allocated to the project and the levels of pollution in 12 settlements.

We found that a comprehensive assessment of the efficiency of project activities is extremely difficult for a number of reasons. Among them are changes in the number and content of project KPIs, modifications to the methodologies employed for calculating indicators, poor quality of baseline calculation data, partial financing of program activities at the expense of other Federal Projects, and a lack of linkage between financing and pollution levels.

Moreover, one of the key challenges of ‘Clean Air’ Project implementation is the unobvious assumption that there is a relationship between achieving the KPIs set out in the project passport and improving the well-being of the population of the 12 cities. One of the project’s KPIs is technically formulated as the number of people whose quality of life has improved. Despite this, the actual calculation of this indicator is not based on an assessment of the potential health risks and potential economic damage.

Scientific institutions of Rospotrebnadzor prepared a methodological basis for the implementation of the Federal ‘Clean Air’ Project during 2019–2020, including guides for developing atmospheric air quality observation programs [112], public health risk analysis [113], and assessment of economic efficiency of measures to reduce air pollution levels [114]. The health risk assessment procedure is based on the Russian Guideline for Health Risk Assessment of Population Exposure to Chemicals Contaminating the Environment [115], which is consistent with the approach proposed by the U.S. Environmental Protection Agency [116]. Nevertheless, official estimates of public health risks and associated economic damage from Rospotrebnadzor are not publicly available. Concurrently, the literature contains a number of disparate estimates for specific years, conducted by scientific organizations within the Rospotrebnadzor institution [69,87].

The Federal Scientific Center for Medical and Preventive Health Risk Management Technologies is responsible for conducting the most comprehensive assessment of health risks in the cities participating in the ‘Clean Air’ project [77]. The total carcinogenic risk and chronic non-carcinogenic risk of respiratory disease development were estimated for all 12 cities during the period spanning from 2020 to 2022. The findings indicate that despite substantial declines in overall emissions between 2017 and 2022, public health risks remained elevated or even increased. The general reason for this is that the target of reducing emissions and emission quotas for polluters has a weak impact on public health. In this case, even if all project indicators are met by 2026, there will not be a proportional improvement in well-being, and the approach would be economically inefficient [77].

In general, the design of Russia’s air quality improvement program is broadly similar to programs in other countries [35,39,42]. Tightening emission standards for industry and energy, reducing emissions from coal combustion in municipal infrastructure, and renewing the transportation fleet are measures common to all cities suffering from air pollution. Hence, we strongly believe that continuing the ‘Clean Air’ Project with the new 29 cities is essential. However, the KPIs need to be revised so that they reflect real improvements in the well-being of settlements. The inclusion in the KPIs of an emission reduction indicator that is different for each city is an important step in this direction. At the same time, further development of the ‘Clean Air’ Project requires open official estimates of public health risks and associated economic damage. These estimates should serve as the foundation for the development of new KPIs and the subsequent evaluation of the socio-ecological efficacy of emission reduction measures. Thus, the in-depth causal analysis of the relationship between project KPIs and air quality improvement indicators may be a promising area for further research.

7. Conclusions

We assessed the efficacy of the implementation of the Federal ‘Clean Air’ Project as a part of the National ‘Ecology’ Project in 12 participating cities and discussed the prospects for its continuation. The analysis was based on two versions of the National ‘Ecology’ Project passport and two key documents containing data on pollution, financing, and KPIs for each of the cities (Comprehensive Plans and Consolidated Calculations). The main results can be summarized as follows:

• The latest iteration of the passport of the National ‘Ecology’ Project as of 2024 differs significantly from the initial version, which was released in 2018. The KPIs set in the original version were not achieved by 2024 and have been substantially revised. In particular, for the indicator “Number of cities with high and very high levels of air pollution”, the baseline has been revised from 8 to 11 cities due to the refinement of the pollution measurement procedure. Furthermore, the target of an overall 22% reduction in emissions by 2024 appeared to be too high and was changed to 15% by 2024 and 20% by 2026.
• The mechanism of polluting enterprises’ modernization using the Best Available Technologies and obtaining Comprehensive Ecological Permissions was flawed. The incentives provided to companies were inadequate, and the procedure for obtaining CEP is quite complex. Therefore, the business focused on solving more important short-term challenges related to overcoming the crisis caused by COVID-19 and then adapting to international sanctions imposed on Russia. The failure of polluting companies to obtain a CEP has placed the government in a difficult position. On the one hand, it has had to consider the prospect of more than 5000 companies that are essential to the Russian economy being placed on the brink of bankruptcy due to a 100-fold increase in pollution fees. On the other hand, it has had to decide whether to repeatedly postpone the deadline for receiving a CEP. In addition, the CEP does not necessarily guarantee that modernization will be completed within the next 7 years.
• The quality of the pollution statistics utilized as the foundation for the KPIs in the 2018 National ‘Ecology’ Project passport was quite poor. The pollution reduction plans reflected in the Comprehensive Plan and emission estimates of the Consolidated Calculations exhibit notable discrepancies. Actual emissions in 2023 for several cities exceed both the target for that year and the 2017 baseline. Despite the emissions targets in the new version of the Comprehensive Plans being extended for two years until 2026, they were not adjusted in accordance with the Consolidated Calculations.
• Private companies are responsible for the majority of emissions and financing activities within the Federal ‘Clean Air’ Project. It is challenging to differentiate between modernization activities driven by the project and the natural process of reequipment, which is already a necessity due to the obsolescence of fixed assets. To address this, futher studies incorporating data on equipment at the polluting enterprises are essential.
• We found no correlation between the planned emission reductions and the allocations for any of the three sources of pollution: transportation, industry, and social and municipal infrastructure. This can be explained by a few reasons, including the poor quality of pollution statistics used in the Comprehensive Plans, the small sample size, the heterogeneity of emission reduction measures even within the same sector, pollutant substances, and prices in the participating cities.
• Our findings revealed statistically significant discrepancies between pollution sources in terms of funding per 1 ton of emissions. The median values of expenditures on measures to reduce emissions from transportation are significantly higher than those for industrial facilities and social infrastructure. The incorporation of measures to improve transportation infrastructure has a notable social impact and is perceived favorably by the population. Yet, their impact on improving the environmental situation and reducing health risks is generally insufficient. In addition, the list of completed emission reduction activities in several cities includes activities financed by other federal and regional projects.
• Official statistics indicate that the new KPIs have been achieved in a timely manner, but their relationship to improving the environmental situation in cities is ambiguous. The only indicator that directly determines the dynamics of the citizens’ quality of life actually reflects only the number of people in a city that has achieved a 20% reduction in emissions. Moreover, the key performance indicators measured in total mass of emissions are also imperfect because pollutants cause different health effects. To enhance the efficacy of the Federal Project, a formal assessment of public health risks and potential economic losses must be made. KPIs should be linked to these assessments, which will significantly improve the effectiveness of emission reduction measures and enhance public perception of the ‘Clean Air’ Project implementation. These recommendations align with the findings of other studies [69,77,87].
• One of the most valuable outcomes of the ‘Clean Air’ Project is the Consolidated Calculations. This effort updated the data on emissions, identified harmful substances for each city determined the main sources and pollution zones within the cities. In addition, 12 cities have established a permanent air quality monitoring system. Further efforts should be directed toward enhancing this system by increasing the number of observation points, improving the quality of data presentation, and developing a pollutant monitoring system at enterprises.

Basically, the reasons for the difference in the performance of cities in reducing air pollution are limited to the peculiarities of the polluting companies’ ecological strategies. The effectiveness of air quality improvement measures in different cities depended on the specialization of the largest polluting companies, their plans and capacity to upgrade their fixed assets, their commitment to ESG practices, their financial status, and the level of losses from the COVID-19 pandemic and international sanctions. Despite the fact that the ‘Clean Air’ Project is a state program, the achievement of most of the KPIs by 2024 was to be accomplished using off-budget funding. Regional and municipal authorities did not have enough authority and resources to influence enterprises or support them financially.

It is noteworthy that the initiation of the ‘Clean Air’ Project itself demonstrates the positive response of the Russian government to the growing demand for improved environmental quality from the urban population. Moreover, the decision to extend financial support for the project indicates that this response has not been sporadic and that Russia continues to move toward sustainable development even under difficult geopolitical circumstances. Achieving this goal, however, requires a careful review of the project objectives and their relationship to the quality of life of the population.