Air Pollution Governance Research Articles

Study on the Precise Evaluation of Environmental Impacts of Air Pollution in Cold Regions Using the Cost Control Method

Objective: With the acceleration of industrialization, air pollution has become a global environmental issue, particularly in cold regions where the unique climatic and geographical conditions give rise to distinctive types of air pollution and impacts. Considering the economic evaluation of environmental damage is crucial for effective pollution control policies, this study aims to provide a more precise environmental damage assessment method through the Improved Virtual Control Cost Method (IVCCM) to optimize air pollution governance strategies in cold regions. Method: This study utilizes a case study of a major company producing methanol and coal-based natural gas, where the emissions from the boiler exhaust exceeded the prescribed standards for particulate matter, sulfur dioxide, and nitrogen oxides during a specific period. By employing a segmented counting approach that accounts for downtime, precise calculations were conducted for the actual periods of excess emissions. Adjustments were made to the calculation coefficients within the Virtual Control Cost Method to more accurately reflect the ecological damage caused by air pollution. Results: The IVCCM calculations revealed that the total environmental loss caused by the company’s excessive air pollution emissions amounted to USD 1.6844 million, significantly lower than the original calculation method (USD 2.1885 million). Specifically, the environmental losses due to particulate matter, sulfur dioxide, and nitrogen oxides were USD 0.0032 million, USD 0.3600 million, and USD 1.3212 million, respectively. Conclusions: The IVCCM enables a more precise assessment and prediction of ecological environmental damage caused by air pollution in cold regions. Compared to traditional methods, it effectively reduces assessment costs, mitigates disputes arising from unclear parameter values and calculation methods, and facilitates the development of more rational environmental protection policies and measures.

Environmental forcing and policy synergy: A multidimensional approach in the governance of air pollution and carbon emission

Policy synergies effectively contribute to the integrated management of air pollution and carbon emissions, which is crucial for safeguarding ecosystem stability and public health. This study uses the causal network model of Gaussian process regression to analyze the combined impacts of dynamic and static carbon emission reduction and air quality policies on carbon emissions and air quality. The causal effects of policy measures and their synergistic effects are also examined. The study results indicate: (1) There is significant geographical heterogeneity in the implementation of environmental policies and regional economic development, with the economically developed eastern coastal regions adopting more stringent carbon emission and air pollution control measures, while the western provinces adopt relatively lax environmental policies. (2) The synergistic effect of carbon emission reduction policies and air quality policies exists, and the two types of static policies are substitutable for managing carbon dioxide emissions and air pollution. (3) Policies' forced effect exists, where the exacerbation of environmental problems leads to the formation and implementation of policies. (4) The value added by the secondary industry is a key motivation for forming carbon emission reduction policies and air quality control policies. Additionally, the value added by the secondary industry directly impacts the incidence of respiratory diseases (e.g., tuberculosis). Finally, dynamic and synergistic policy recommendations are proposed based on the study's findings.

Assessing the role of public, media, and government attention on air pollution governance in China

Attention from social subjects, such as the government, public, and media, serves as a vital diver for urban environmental improvement. While most empirical studies about environmental attention have discussed only one or two of these subjects so far, the literature overlooks the potential collective influence. Drawing on the concept of attention and stakeholder theory, this paper integrates government, public, and media into a unified framework. Utilizing data from Chinese prefecture-level cities spanning from 2012 to 2020, this paper reveals how multi-subject attention influences air quality, including its spatial spillover effects and specific mechanisms. This study finds that 1) multi-subject attention could effectively inhibit air pollution, the direct effects of government, public, and media attention are -7.278, -0.077, and -0.502, respectively. 2) Only the public and media attention have significant cross-city suppressing effects on air pollution. Specifically, the spillover effects of the public and media attention's proxy variables are -4.003 and -1.850. 3) Overall, multi-subject attention can effectively reduce air pollution by establishing environmental laws and regulations, strengthening environmental enforcement, and increasing environmental protection investment. However, there are significant differences in the ways government, public, and media attention improve air quality in local and surrounding cities through these three mechanisms.

The joint impact of PM2.5, O3, and CO2 on the East Asian Summer Monsoon in 2013 and 2018 due to contrasting emission reduction

With the rapid urbanization and the implementation of a series of air pollution control measures, significant changes have occurred in the emission of fine particulate matter (PM2.5), ozone (O3) precursors, and CO2 in China. In this study, we comprehensively assess the impact of emission variations on the East Asian Summer Monsoon (EASM) climate from 2008 to 2018 using a regional-chemistry-ecology model RegCM-Chem-YIBs. The investigations indicated a strengthening of the EASM from 2008 to 2018, with all four EASM Indices exhibiting an increase trend ranging from 0.08 to 1.09 per year based on the simulations. Since 2008, alterations in the emissions of PM2.5 and O3 precursors in 2013 and 2018 led to a rise in near-surface temperatures in China by 0.5–1.5 K, thereby enhancing the EASM. Conversely, the changed CO2 emissions, through its influence on radiative balance and altering BVOCs (Biogenic Volatile Organic Compounds) emissions via its effect on vegetation growth, decreased temperatures by 0.5–1.5 K, thus weakening the EASM. However, when considering the combined effects of total emissions changes in PM2.5, O3 precursors, and CO2, surface temperatures increased by 0.5–2 K, ultimately strengthening the EASM. In addition, compared to 2013, EASM was strongly enhanced in 2018 due to the notable increase in CO2 and significant reduction of PM2.5 and O3 precursors. Our study underscores the significant influence of variations in PM2.5, O3 precursors, and CO2 emissions on EASM climate and emphasizes the importance of coordinated governance of air pollution and climate change.

Interstate Air Pollution Governance in the United States: Exploring Clean Air Act Section 126

Air pollution is arguably the most pressing human health concern today, accounting for approximately 7–9 million premature deaths worldwide. In the United States, more than 40% of early deaths caused by air pollution are assessed to be caused by emissions produced by neighboring states. This article examines one of the governance mechanisms used by the U.S. to address this issue: section 126 of the Clean Air Act. Critical factors including case length, evidence used, and case outcome are compiled for the population of section 126 petitions submitted from 2000–2022. This evidence is assessed using comparative case analysis. The findings reinforce two issues with the petition process already identified in the literature–the use of cost as a proxy for significance and the excessive and unclear burden of proof placed on downwind states–adding texture to the latter issue by examining the modeling techniques used by downwind states. This analysis identifies lengthy response timelines as an additional issue and calls to attention the infrequency with which the EPA has formally accepted petitions. Collectively, these issues increase the cost, complexity, and unpredictability of filing a section 126 petition.

Evaluation the impact of electricity consumption on China's air pollution at the provincial level.

As the world's largest electricity-consuming country, China faces the challenge of energy conservation and environmental pollution. Therefore, it is imperative that China takes decisive action to address these issues. Based on the panel data of 30 provinces (cities, districts) in China from 2011 to 2020, we use the entropy method to measure the air pollution index in different provinces, construct two fixed effects models, panel quantile model, and spatial Durbin model to empirically analyze the impact of electricity consumption on air pollution in China's provincial regions. The experimental results show that: (1) Electricity consumption has a significant positive impact on the provincial air pollution index in China and the higher the index is, the more serious the air pollution is. When the electricity consumption increases 1%, the air pollution index will increase of by 0.0649% as accompanied. (2) Through comparison of different times, we found that the degree of increase in air pollution index caused by electricity consumption would be reduced due to the improvement of environmental protection efforts. From the perspective of different geographical locations, the electricity consumption in the southeast side of the "Hu Line" has exacerbated the impact on air pollution index. (3) According to the panel quantile regression results, the marginal effect of electricity consumption on air pollution is positive. With the increase of quantiles, the impact of electricity consumption on air pollution is increasing. (4) Spatial effect analysis shows that electricity consumption has a significant positive spatial spillover effect on air pollution index. The increase in electricity consumption not only increases the air pollution index in the local region, but also leads to an increase in the air pollution index in surrounding areas. These findings contribute to the governance of air pollution and the promotion of sustainable economic, environmental and energy development.

Ecological governance of Hainan coastline from the perspective of one health: A case study of the sustainable development of people’s livelihood after the coastline of Qionghai city was repopulated

Purposes It aims to discuss how to effectively carry out the ecological governance of the coastline of Qionghai City, Hainan Province under the concept of One Health [1] to promote the sustainable development of residents’ income and provide practical cases and theoretical references for the ecological governance of the Hainan Coastline. Methods Use field research and random interview methods to obtain relevant data and conduct quantitative analysis. Results and shortcomings Residents’ income has stable growth, water pollution control effects are outstanding, and the governance of air pollution is obvious. However, there are still problems such as serious degradation of coral reef ecosystems and lack of effective funding for ecological compensation, mainly due to the threat of insufficient capital investment and human activities. Conclusions It is recommended to improve the sustainable development capacity of the township governments, build a reasonable ecological compensation mechanism, accelerate the transformation of the township governments to the ecological government, increase the implementation of green GDP, form a virtuous circle of compared to achieve ecological environmental protection and economic development. Department decision -making provides a scientific basis.

Investigation of the spatial effects on PM2.5 in relation to land use and ecological restoration in urban agglomerations

Heavy pollution of particulate matter with an aerodynamic diameter of <2.5 μm (PM2.5) poses increasing threats to the living environment worldwide. Urban agglomerations often lead to regional rather than local air pollution problems. This study explored the underlying global and local spatial driving mechanisms of PM2.5 variations of the 195 county-level administrative units in the urban agglomeration in the middle reaches of the Yangtze River, China, in 2020, using the global spatial regression and geographically weighted regression methods. Results showed that (1) at the county level, there were spatial variations of PM2.5, fluctuating from 20.1263 μg/m3 to 44.8416 μg/m3. (2) The concentrations of PM2.5 presented a positive spatial autocorrelation with a remarkable direct spatial spillover effect. (3) Forestland, grassland, elevation and ecological restoration were negatively correlated with PM2.5 concentrations, the indirect spatial spillover effect of elevation was noticeable. (4) The indirect reduction effects of ecological restoration on PM2.5 concentrations were substantial in the Wuhan urban agglomeration. (5) The reduction effect of forestland, grassland, ecological restoration and elevation on PM2.5 showed a noticeable spatial heterogeneity. In the future, it is suggested regional variability and the spatial spillover effect of air pollution be taken into account in environmental governance. Simultaneously, utilization of the mitigation effect of ecological restoration on PM2.5 is anticipated for the concerted effort in air pollution governance.

Can factor substitution reduce the shadow price of air pollution embodied in international trade? A worldwide perspective.

The calculation of trade-embodied air pollution (TEAP) and its economic losses can be reasonably used to assess the impact of transboundary air pollution. However, these air pollutants, which are associated with international trade, can be easily ignored due to their concealment. Based on this, the global multiregional input‒output model (MRIO) is used to quantify the volume of five air pollutants that are embodied in the trade of 20 countries from 2000 to 2016. Then, the shadow price of trade-embodied air pollution (SPTEAP) and the elasticity of factor substitution (EFS) are both calculated by applying the translog production function. Finally, impulse response analysis is used to study the dynamic impact of EFS on the SPTEAP. The main conclusions are as follows: (1) All countries experienced a mass transfer of TEAP, among which China and the USA are the developing and developed countries with the largest amount of TEAP transfers, respectively. (2) The SPTEAP and EFS vary greatly among countries, and these values are generally higher in developed countries than in developing countries. The relationship between the three EFSs can be expressed as [Formula: see text] in all countries, thus indicating that improving the technological level of a country is the best solution for reducing the TEAP in that country while incurring the lowest cost and the least difficulty. (3) Over the long run, the increase in [Formula: see text] and [Formula: see text] reduces the SPTEAP. Conversely, an increase in [Formula: see text] increases the SPTEAP. Therefore, policymakers should weigh these three factors according to the fluctuation of the SPTEAP and constantly adjust the allocation structure and ratio of these factors to maximize the benefits of transboundary air pollution governance.

Air Pollution Governance and Residents’ Happiness: Evidence of Blue Sky Defense in China

Enhancing people’s happiness should be the standard of public policies. With the growing prominence of air pollution issues, governments and scholars have started to pay attention to happiness as it relates to air pollution. However, the relevant research has been limited in China, and the results are not clear, with little attention given to subjective perception related to air pollution. In recent years, China has strengthened its efforts in containing air pollution, striving to fulfill the people’s longing for a blue sky. In this study, we aimed to investigate the impact of pollution governance on residents’ happiness, considering both objective and subjective aspects. Using the Chinese General Social Survey and data on PM10, our study was diachronic in nature, analyzing residents’ happiness and the improvement in air quality as well as people’s evaluation of governance concerning pollution. The statistical methods used primarily included t-tests and multiple linear regression. The results showed the following: (1) Residents’ happiness showed a significant improvement from 2013 to 2021, accompanied by enhancements in both an objective improvement in air quality and subjective evaluation of pollution governance. (2) Both an objective improvement in air quality and the subjective evaluation of pollution governance showed positive effects on residents’ happiness. This study not only enriches the theoretical understanding of the relationship between air pollution and happiness but also provides valuable insights for formulating policies that are more conducive to pollution governance and public happiness. To enhance happiness, the government needs to continue improving the air quality and guide residents in appropriately evaluating pollution governance.

Collaborative governance of trade-driven transboundary air pollution in China: A responsibility-based fair compensation mechanism

Transboundary air pollution poses a significant challenge in China, and collaborative governance presents a promising approach to tackle this problem. However, such approach is rarely implemented due to the influence of inter-regional trade dynamics. To address this issue, a comprehensive, responsibility-based fair compensation mechanism was established in the present study. The aim of the mechanism is to bridge the existing gap through the integrated utilization of air pollutant emission inventories, multi-regional input-output analysis, emission responsibility allocation, and an ecological compensation model. In 2017, approximately 50% of China's air pollutant emissions were embedded in inter-provincial trade, primarily originating from wealthier provinces and directed towards less-developed regions with higher pollution intensity. There exists a significant imbalance between the inter-provincial transfers of air pollution and economic benefits, owing to which Inner Mongolia and Liaoning have suffered from serious environmental inequity brought about by trade. The allocation of responsibility for trade-related emissions between producers and consumers is determined by the economic surplus they gain from trade. Such approach results in an intermediate outcome that falls between production-based and consumption-based emissions for the majority of provinces. The scheme highlights the import-related share of responsibility for economically developed provinces and the export-related share for less-developed, pollution-intensive provinces, which can primarily be attributed due to their differences in value chain specialization. The inter-provincial compensation volumes for trade-related emissions are determined based on the economically equitable emission responsibility sharing scheme. More developed provinces, characterized by industrial structures focused on low-pollution, high-value-added products, primarily function as compensation providers. In contrast, less-developed provinces with higher pollution intensity seek compensation from these more affluent regions. The present findings can offer a quantitative basis for the ecological compensation and collaborative control mechanism of trade-driven transboundary air pollution in China.

Can low carbon policies achieve collaborative governance of air pollution? Evidence from China's carbon emissions trading scheme pilot policy

In the context of environmental and climate governance, the efficiency with which low-carbon policies reduce air pollution is vital for enhancing the effectiveness of environmental policy implementation. Using the emissions trading scheme (ETS), the most representative low-carbon policy in China, as an example, this study employs a panel data set of 250 Chinese cities for the period 2003–2016. Additionally, a spatial difference-in-differences (SDID) model is utilized to explore the ETS pilot policy's impact on sulfur dioxide (SO2) emissions and haze pollution (PM2.5 concentrations) and identify the mechanism underlying these effects. Our results show that the policy helps to reduce both types of air pollution, thereby having a significant collaborative-governance effect. Moreover, while the ETS pilot policy improves PM2.5 concentrations in neighboring cities significantly, it fails to curb SO2 emissions in these areas. The mechanism identification results point to a collaborative-governance effect of the policy via industrial structure upgrading, energy structure optimization, and green technology innovation. According to heterogeneity analysis, while the policy has a more evident impact on air pollution in central and western China, it does not exert a collaborative-governance effect on SO2 emissions in non-key environmental protection and energy-oriented cities.

Collaborative Governance of Air Pollution Caused by Energy Consumption in the Yangtze River Delta Urban Agglomeration Under Low-Carbon Constraints: Efficiency Measurement and Spatial Empirical Testing

Collaborative Governance of Air Pollution Caused by Energy Consumption in the Yangtze River Delta Urban Agglomeration Under Low-Carbon Constraints: Efficiency Measurement and Spatial Empirical Testing

Research on environmental monitoring and governance of air contamination in the Beijing‐Tianjin‐Hebei region stemmed from spatiotemporal data collection

AbstractFrom 2013 to now, Beijing‐Tianjin‐Hebei (Hereinafter referred to as “the region”) has carried out comprehensive air pollution governance, which has promoted the sustained and rapid development of the regional economy while significantly improving regional air quality. However, the spatial and seasonal differences in atmospheric quality are obvious, and the regional and structural problems are still prominent. There is a long way to go for new challenges of cooperate governance of PM2.5 and O3. Therefore, first, we should further deepen the joint prevention and control mechanism based on regional collaborative governance. Second, we should rely on technological innovation to impetus the upgrading of energy and industrial structure. Third, we should adjust the transportation structure and create a new pattern of transportation network. Fourth, we should improve the ecological compensation mechanism and give full play to the functions of ecological conservation areas. Fifth, we should think highly of the self‐purification capacity of the ecosystem and build urban forest parks. At last, we should Strengthen publicity and mobilization, and participate in joint governance through nationwide action.

Influencing factors of PM2.5 concentration in the typical urban agglomerations in China based on wavelet perspective

PM2.5 is one of the most harmful air pollutants affecting sustainable economic and social development in China. The analysis of influencing factors affecting PM2.5 concentration is significant for the improvement of air quality. In this study, three typical urban agglomerations in China (Beijing‒Tianjin‒Hebei [BTH], the Yangtze River Delta [YRD], and the Pearl River Delta [PRD]) were studied using innovative trend analysis, a Bayesian statistical model, and partial wavelet and multiwavelet coherence to analyze PM2.5 concentration variations and multi-scale coupled oscillations between PM2.5 concentration and air pollutants/meteorological factors. The results showed that: (1) PM2.5 concentration time-series showed significant downward trends, which decreased as follows: BTH > YRD > PRD. The higher the pollution level, the greater the change trend. In BTH and the PRD, PM2.5 had obvious trends and seasonal change points; whereas, the PM2.5 time-series change point in the YRD was not obvious. (2) PM2.5 had significant intermittent resonance cycles with air pollutants and meteorological factors in different time domains. There were differences in the main controlling factors affecting PM2.5 among the three urban agglomerations. (3) The explanatory ability of air pollutant combinations for variations in PM2.5 was higher than that of meteorological factor combinations. However, the synergistic effect of air pollutants/meteorological factors could better explain the PM2.5 concentration variations on all time-frequency scales. The results of this study provide a reference for ecological improvement as well as collaborative governance of air pollution.

STCM: A spatio-temporal calibration model for low-cost air monitoring sensors

Air pollution is one of the most common health-threatening factors, potentially causing millions of deaths every year. Static stations typically collect air pollution data by utilizing a small number of costly and high-quality sensors and numerous low-cost micro stations. However, data collected from micro stations usually suffers from large noise and thus calibration would be necessary for operating good air pollution governance. Point-to-point models and sequence-to-point models have the potential limitations of either failing to mine latent patterns embedded in historical time series or ignoring spatial dependency within a certain region. To address these issues, we propose a novel method called Spatio-Temporal Calibration Model (STCM) based on dual encoders. STCM consists of long-term encoder, short-term encoder, and decoder modules. The long-term encoder encodes historical reference data via GRU and extracts the trend, periodicity, and adjacency of the target pollutant through a temporal attention mechanism. The short-term encoder then reflects real-time conditions through a spatial attention mechanism, quantifying dynamic station-wise correlations between micro stations and the static station. The decoder ultimately integrates outputs of dual encoders and generates calibration results of all micro stations. STCM has been experimentally justified by comparing against nine baseline methods based on two real-world datasets.

Study on the spatio-temporal patterns of urban air pollution and its spatial mismatch with air pollutant emissions in the Yellow River Basin, China

In order to promote the precise governance of air pollution in the Yellow River Basin(YRB), it is of great significance to reveal the spatio-temporal patterns of urban air pollution in the basin and its spatial mismatch characteristics with air pollutant emissions. Based on spatial autocorrelation model and spatial mismatch model, this paper selected air pollution-related monitoring data from 69 cities in YRB from 2015 to 2020 as samples, and used ArcGIS, Stata, GeoDa and other softwares to analyze the spatio-temporal patterns of urban air pollution and its spatial mismatch characteristics with air pollutant emissions in YRB. The results showed that: (1) Temporally, the average annual Air Quality Index (AQI) values of cities in YRB ranged from 78.22 to 97.08 in 2015–2020, among which, the average annual AQI values of cities in the upper, middle and lower reaches of the basin decreased from 79.86, 89.23 and 122.14 in 2015 to 66.87,82.98 and 98.43 in 2020. (2) Spatially, there were obvious spatial differences in urban air pollution in YRB, and the AQI was roughly distributed in a geographical gradient of upper reaches < middle reaches < lower reaches, and there were significant spatial correlations in urban air pollution, mainly showing ‘high-high’ and ‘low-low’ aggregating characteristics. Among them, the lower reaches of YRB had formed a concentrated ‘high pollution zone’. (3) There was an obvious spatial mismatch between urban air pollution and air pollutant emissions in YRB, among which the spatial mismatch was obvious in cities such as Wuhai, Zibo, Shizuishan, Yangquan, Taiyuan, Datong, Jiyuan, Kaifeng, Puyang and Xi’an. (4) To improve the overall situation of air pollution in the cities of YRB, this paper proposed that the geographical gradient difference of air pollution in the upper, middle and lower reaches of YRB needs to be fully considered, following the principle of ‘focused treatment, gradual progress, enhanced prevention’, and according to the spatial mismatch characteristics of urban air pollution and air pollutant emissions, it is necessary to build a ‘differentiated’ governance strategy system for urban air pollution in the basin, which is ‘tailored to local conditions and categorized measures’.

Spatiotemporal Variation Air Quality Index Characteristics in China's Major Cities During 2014-2020.

The temporal and spatial variation characteristics of air quality index (AQI) in major cities in China were explored in this paper using statistical analysis, hot spot analysis, spatial autocorrelation, mean center, and geographic detector based on the daily AQI data from 2014 to 2020. The results show that ① the annual AQI average value dropped from 94 to 67 from 2014 to 2020. The percentage of cities with daily AQI excellent rates between 0.8 and 1 is significantly increasing, reaching 77% in 2020. ② AQI is highest and lowest in winter and summer, respectively. The trend of the monthly AQI average value is roughly in a U shape. Moreover, the AQI in January and December is high, and the AQI in August and September is low. ③ The spatial distribution of the annual AQI average in China's major cities shows agglomeration effects. The hot spots are distributed in North China and Xinjiang, and the cold spots are mainly distributed in the northeast and southern regions of China. ④ The average center of the annual AQI average of major cities in China was distributed in Sanmenxia City and Luoyang City, Henan Province, from 2014 to 2020 with a relatively small mean center migration range. ⑤ Based on the geographical detector model, the impact of total precipitation, 10-m u component of wind, 10-m v component of wind, surface pressure, and 2-m temperature on AQI is analyzed, and it is concluded that 2-m temperature has the greatest impact on AQI. Meanwhile, it is explored that GDP and population density have a certain impact on air quality. Therefore, analyzing the temporal and spatial characteristics of air quality provides some scientific basis for the regional collaborative governance of air pollution and the in-depth fight against pollution in China.

Synergetic roadmap of carbon neutrality and clean air for China

It is well recognized that carbon dioxide and air pollutants share similar emission sources so that synergetic policies on climate change mitigation and air pollution control can lead to remarkable co-benefits on greenhouse gas reduction, air quality improvement, and improved health. In the context of carbon peak, carbon neutrality, and clean air policies, this perspective tracks and analyzes the process of the synergetic governance of air pollution and climate change in China by developing and monitoring 18 indicators. The 18 indicators cover the following five aspects: air pollution and associated weather-climate conditions, progress in structural transition, sources, inks, and mitigation pathway of atmospheric composition, health impacts and benefits of coordinated control, and synergetic governance system and practices. By tracking the progress in each indicator, this perspective presents the major accomplishment of coordinated control, identifies the emerging challenges toward the synergetic governance, and provides policy recommendations for designing a synergetic roadmap of Carbon Neutrality and Clean Air for China.

Structural Characteristics and Evolution Trend of Collaborative Governance of Air Pollution in “2 + 26” Cities from the Perspective of Social Network Analysis

The regional and complex air pollution problem has become a major bottleneck restricting the sustainable development of regional economies and societies. Constructing a regional collaborative governance network has become a key solution to solving the cross-regional air pollution problem. By performing a social network analysis, this paper analyzes the overall structure, internal characteristics, and evolution trend of the collaborative governance network of regional air pollution by selecting the data samples of the “2 + 26” cities from 2017 to 2021. The study found that the excellent results of air pollution control in Beijing–Tianjin–Hebei and its surrounding areas are due to precise and efficient collaboration among the “2 + 26” cities. The collaborative network formed by “2 + 26” cities based on the joint initiation of severe weather emergency responses is an important measure that can help to effectively control regional air pollution problems. There is a distinct difference in the collaborative pattern in the “2 + 26” cities air pollution collaborative governance model, showing a nested-difference network structure.