A Pollution Prevention Pathway Evaluation Methodology Based on Systematic Collaborative Control

Abstract

To improve the efficiency of air pollution control, in this research, a systematic air pollution collaborative governance pathway system was developed from a systemic perspective. The sequencing of air pollution control pathways in the system can significantly affect its efficiency, so the order of the sequence was optimized. To develop the system, first, two case studies on coordinated air pollution control in the U.S. and China were conducted to demonstrate the importance of systematic collaborative governance. Next, based on the analysis of these two cases and a review of the related literature, a systematic coordinated air pollution control mechanism was proposed. The priorities of collaborative governance pathways were evaluated using the Analytic Hierarchy Process (AHP) methodology. The input to the AHP was data from in-depth interviews with established scholars and practitioners in air pollution prevention and control. Several policy suggestions are put forward based on the expert ranking of the results of the priorities of the collaborative governance pathways. These policy suggestions include identifying the most critical pathways in the cooperative control of air pollution and their order of implementation as well as measures that can effectively reduce pollution. The theoretical contributions of this research include the establishment of a cooperative governance mechanism and the analysis of governance pathways to help develop an efficient air pollution pathway system. The practical contributions of this research include policy suggestions to improve the efficiency of collaborative air pollution treatment and lower its costs.

1. Introduction

The atmosphere is vital to all living things, including humans. Clean and pollution-free air can significantly reduce the incidence of diseases and provide healthy and safe food for human beings. Some countries, such as the United States, Britain, Australia, Japan, and Germany, have completed their industrial revolutions in the past 300 years; however, many other countries, such as China and India, are still undergoing industrialization. Yet, with the associated advancements in urbanization and industrialization, air pollution has gotten out of control, and this problem has become more and more severe. It has become the focus of the attention of all countries.

In [1], the author argues that many countries that achieved or completed industrialization in the 20th century have significantly improved their air pollution control through governance. However, with other countries’ economic and social development, air pollution control still requires continuous improvement. In this regard, various countries and regions have put forward measures and pathways to control air pollution in their own countries or regions, but the results have been unsatisfactory [2]. That is because regional autonomy in the traditional sense lacks unified action and coordination measures, meaning it has been shown to have disadvantages and cannot effectively solve the air pollution problem. According to the characteristics of the cross-regional transportation of air pollution, when compared with purely regional governance, collaborative governance can effectively reduce the mutual movement and influence of pollutants between cities and reduce the concentration of air pollutants in each region as a whole system [3]. Therefore, the United Nations Council has held several world-class climate governance conferences to discuss the global climate governance plan collectively. Under the unified command of the United Nations, many countries have jointly responded to global climate change and governance by forming alliances and mutual dialogue and cooperation. Many scholars have also been actively involved in research on air pollution prevention and control. Based on a review of the literature on coordinated prevention and the control of air pollution, the literature is categorized into the following three subsets.

First, there are only a small number of theoretical research results on the necessity of the coordinated treatment of air pollution. The authors of [4] summarized the present situation and challenges of a coordinated treatment of air pollution. They put forward a theoretical framework incorporating coordinated prevention and control objectives, core coordinated tasks, and critical support guarantees. The author of [5] extended the theory of collaborative governance to regional environmental governance through the construction of a new mechanism of collaborative governance involving multiple subjects of government, enterprises, and the public in the region and promoted a coordinated approach to regional economic development and ecological environment protection. The authors of [6] put forward a theoretical model of local environmental competition and regional collaborative governance under the supervision of the central government. This “trinity” model of atmospheric environmental governance not only allows the initiatives of both the central and local governments to improve the efficiency of atmospheric environmental governance but it also dynamically improves the air quality assessment index system and optimizes the regional collaborative governance mechanism thanks to the model being based on a top-level design perspective which closely follows the new requirements of the “double carbon” target. These select theoretical studies on the coordinated control of air pollution mainly focus on the application of coordinated theory to air pollution prevention. They do not consider the optimal implementation of the coordinated treatment of air pollution. The research presented in this paper provides a theoretical basis for establishing a coordinated control mechanism and pathway system for air pollution and practical insights on the joint prevention and control of air pollution. This study provides an in-depth analysis of priorities/relationships among the elements of the mechanism, which is a major contribution to the literature. The purpose of its analysis is to maximize the system’s efficiency. The coordinated control pathway system constructed in this study follows ideas proposed by the authors of [5,6] but is much more comprehensive.

Second, there are papers which have studied coordinated control mechanisms for air pollution. The authors of [7] employed an empirical orthogonal function, continuous wavelet transformation, and the concentration weighted trajectory method to study the joint regional control of air pollution. They advocated that regional cooperation should be strengthened to achieve the joint control of air pollution. Based on the “structure-process” model, the authors of [8] suggested the adoption of a cooperative governance model to control air pollution in the Yangtze River Delta of China. Moreover, they constructed a cooperative governance mechanism for air pollution control using an institutional logic. The authors of [9] adopted the CiteSpaceV method to conduct a quantitative visual analysis of the literature on air pollution prevention and control. They found that European and American countries paid more attention to the causes of air pollution and its influence on human health in the context of air pollution control than the rest of the world. Furthermore, European and American countries focused on adopting new technologies and advanced equipment but without much success. The author of [10] suggested that countries and regions strengthen their coordinated control of air pollution, establish a cross-regional cooperation mechanism, and achieve systematic prevention and control. The above studies focused only on the overall mechanism of the joint prevention and control of air pollution. They omitted the inter-system mechanism of how its various elements cooperate. Based on the literature review above, it can be seen that only by the use of cooperation and the establishment of the mechanism of collaborative prevention and governance can air pollution be effectively prevented and controlled. Therefore, in this paper, by taking a systemic view of the mechanism, a systematic cooperative prevention and control mechanism for air pollution with an emphasis on the relationships between/the order of priority of its various elements is proposed.

Third, there is research on the pathways of the coordinated prevention and control of air pollution. The authors of [11] used the ESDA method to analyze the spatial correlation between the reduction in regional carbon emissions and environmental governance levels. They argued that green technology innovation should be brought into play to combat air pollution and to achieve green and high-quality development. Based on spatial correlation analysis and the dynamic spatial autoregressive model, ref. [12] explored the agglomeration evolution characteristics and related synergistic factors of urban air pollution in Beijing, Tianjin, and Hebei and surrounding areas and argued that the coordinated promotion of air pollution control should promote the upgrading of industrial infrastructure, the development of new clean energy, and the improvement of green infrastructure. The authors of [13] built an interactive endogenous growth model of environmental pollution control and economic and social development and recommended increasing investment in public green facilities to improve the efficiency of collaborative governance. In the above studies, scholars put forward coordinated prevention and control measures for air pollution on multiple levels and from many perspectives, ensuring that such measures can effectively prevent and control air pollution to a certain extent. However, they did not consider the relationships between these measures. The coordinated control pathway system of air pollution developed in this study incorporates these multiple levels and perspectives. In addition, our study investigates the relationships between these levels and perspectives and determines how to coordinate these pathways to maximize the efficiency of the system.

In air pollution prevention and control practice, the United Nations Council and many governments worldwide are calling for collaborative governance. Scholars have also put forward the strategy of the joint prevention and control of air pollution based on theoretical research. Systematic and coordinated control among countries and regions has become a critical approach in the context of controlling air pollution effectively. The coordinated control of air pollution by various countries and regions has transformed individual operations in various regions into systematic actions. By setting the same goals and formulating unified plans and standards among regions, governments can realize systematic joint prevention and control and reduce the emission of regional air pollutants as much as is possible.

Scholars have researched air pollution prevention and control from different angles and put forward methods and pathways of coordinated prevention and control for air pollution. However, a comparison of existing pathways is scarce in the existing literature. This may make it challenging for decision-makers to choose prevention and control pathways. Therefore, the main objectives of the research were to put forward a prioritized and effective pathway system for coordinated prevention and air pollution control and to help decision-makers with the coordinated prevention and control of air pollution with low costs and high efficiency. In other words, the research results of this paper are of theoretical and practical significance.

To achieve these goals, two real case studies were conducted to analyze the model of the systematic collaborative control of air pollution. A hierarchical analysis of in-depth interview data was carried out to determine the priority of air pollution collaborative control pathways. The system proposed in this study fully utilizes the priority relationships among these elements; thus, it is more comprehensive than the models proposed in the existing literature. Compared with existing mechanisms, the mechanism of the systematic and coordinated prevention and control of air pollution constructed in this paper has clearer prevention and control pathways, more effective coordinated prevention and control links, and better operating procedures. Furthermore, it forms a closed-loop dynamic adjustment ecosystem. In addition to its theoretical contributions, our study also has practical value. The suggestions on coordinated air pollution control put forward in this paper can help improve air pollution prevention and control in practice.

2. Materials and Methods

2.1. The Mechanism of the Systematic Collaborative Control of Air Pollution

The systematic collaborative governance of air pollution is related to the divide-and-conquer model of air pollution control, which faces many problems, such as overlapping and inconsistent policies and systems, conflicting emission reduction standards and measures, and high governance costs. In the face of these problems, systematic collaborative governance can better and more effectively control air pollution incidents [14].

2.1.1. A Case Study of Cross-Regional Coordinated Air Pollution Control in Southern California, USA

The well-known photochemical smog incident in Los Angeles, Southern California, USA, is one of the eight most famous environmental pollution incidents globally and had a far-reaching impact on the coordinated control of air pollution in the United States and the establishment of relevant laws and regulations [15]. Los Angeles is located in the southwest of California, USA. As the atmosphere drifts with the wind, photochemical smog pollution in the air increases and spreads. In the 1970s, the state government realized that relying on the strength of one region could not effectively solve the air pollution problem. Therefore, in 1976, with the authorization of the U.S. Congress and the governor, an air pollution collaborative governance organization was established. An air quality control zone on the south coast of the special governmental area spanning cities and counties was established to systematically coordinate the governance of air pollution so as to ensure that air pollution could be effectively controlled. As a result, the air quality of the area met the standards required to protect public health [16].

At the same time, the United States federal government strengthened the construction of a collaborative governance system by introducing laws. The Clean Air Act defines the primary system and framework of the air pollution joint prevention and control system of the United States. It stipulates the responsibilities and obligations of the United States federal government and states and counties in the process of collaborative air pollution prevention and control. The states and counties also stipulate local and regional management responsibilities through legislation, which constitutes the legal system of coordinated prevention and control with respect to regional air pollution in California, which aims to achieve the same goal [17,18]. The South Coast Air Quality Control Zone of the special governmental district, which spans cities and counties, is responsible for the overall management of air pollution sources and air pollution flows. By strengthening cross-regional cooperation, it implemented cross-regional cooperation plans with local governments and other government agencies in California. Finally, under the multi-regional systematic collaborative governance model, air pollution was effectively controlled, and air quality was improved significantly.

2.1.2. A Case Study of Coordinated Air Pollution Control in Beijing-Tianjin-Hebei Region of China

The Beijing-Tianjin-Hebei regional coordinated air pollution control model is a typical case of systematic, coordinated air pollution control practice under the concept of governance with Chinese characteristics [19]. The Beijing-Tianjin-Hebei region is not only the political center of China but also one of the core regions in terms of economic development. With the acceleration in urbanization and the rapid growth of the industrial economy, the issue of regional air pollution in the Beijing-Tianjin-Hebei region has become increasingly prominent and severe. In areas where heavy industry is concentrated, air pollution has become a particularly important topic that seriously affects people’s lives and health. The governments of Beijing, Tianjin, and Hebei attach great importance to this and have taken measures to strengthen the prevention of and control air pollution.

However, air pollution in Beijing-Tianjin-Hebei and its surrounding areas has given rise to the realizations that vertical cooperation is problematic and vertical supervision is scattered in the sub-regional governance. Because of this, a leading group for “Beijing-Tianjin-Hebei and its surrounding areas for air pollution prevention and control” was jointly established. Under centralized and unified management, personnel were assigned, responsibilities were divided, the joint control group for air pollution prevention and control was promoted, and vertical guidance and supervision were integrated into the horizontal collaborative governance platform, which effectively broke down the informational barriers between regions and ensured regional air governance [20,21].

The 2017 government document “Action Plan for Comprehensive Control of Air Pollution in Beijing-Tianjin-Hebei and Surrounding Areas in Autumn and Winter of 2017–2018” clearly states that “taking the people’s governments of Beijing, Tianjin, Hebei, Shandong, Shanxi, and Henan as the theme, actively promote systematic, coordinated control of air pollution prevention and control in Beijing-Tianjin-Hebei and surrounding areas” [13].

Under the unified command of systematic collaborative governance, the government strengthened the process of governing air pollution control, realized the coordinated layout of the necessary elements, and comprehensively advocated for the coordinated development of Beijing-Tianjin-Hebei air pollution governance by relying on the resource advantages, economic infrastructure, technical expertise, the level of urban development, and the spatial linkage effect of each region. According to the overall responsibility and phased objectives with respect to collaborative air pollution control, the government coordinated tasks, the division of labor, and cooperation, promoted networked responsibility coordination, established and improved joint defense and cooperation mechanisms such as joint law enforcement, information sharing, and pollutant emission rights trading, and effectively reduced transaction costs in various regions, enhancing cooperation benefits through coordination mechanisms [22].

Based on this case, one can conclude that any performance appraisal of collaborative governance should be strengthened. The objectives of Beijing-Tianjin-Hebei atmospheric environmental quality monitoring, capacity structure adjustment, resource investment, rule of law construction, industrial infrastructure optimization, monitoring, and early warning should be included in the performance appraisal. Rewards and punishments should be given according to the assessment results. The set objectives should be adjusted to finally realize the effectiveness of joint collaborative prevention and air pollution control in the improvement of air quality.

2.1.3. A Systematic Collaborative Governance Mechanism for Air Pollution

We examined one case of cross-regional air pollution control in Southern California in the United States and one case of regional air pollution control in Beijing-Tianjin-Hebei, China. In this research, common features of the two cases were summarized and differences between them were analyzed. As a result, the systematic air pollution control mechanism, as shown in Figure 1, was established. Compared with existing mechanisms, the systematic, coordinated prevention and control mechanism for air pollution proposed in this paper has a clearer prevention and control pathway, more effective coordinated prevention and control links, and better mechanism of operation procedures. In addition, our mechanism forms a closed-loop dynamic adjustment ecosystem.

Figure 1 illustrates the main factors and links that should be included in the systematic collaborative control mechanism for air pollution, analyzes the mutual influence among the factors, and defines the interaction among the links. Figure 1 shows that the systematic collaborative governance of air pollution begins with the determination of the goal of collaborative governance and ends with the optimization of the pathway of the collaborative governance of air pollution, with feedback on the effect of this governance, forming a closed loop of systematic collaborative governance. That is to say, before the process of air pollution control begins, the goals of that control should be determined. The goal could be a reduction in the concentration levels of six critical air pollutants: sulfur dioxide (SO₂), nitrogen dioxide (NO₂), inhalable particulate matter (PM10), ozone (O₃), carbon monoxide (CO), and fine particulate matter (PM2.5), with the aim of meeting the requirements of Chinese Ambient air quality standards (GB3095—2012) [23]. After determining the goals, the government should set up a governing body for coordinated air pollution control, and through the governing body, the government should clarify the rights and responsibilities of the group members in the system, increase the investment of funds and resources for coordinated air pollution control, carry out coordinated air pollution prevention and control, strengthen the coordinated air pollution control process, and effectively improve the atmospheric environment by adjusting and optimizing energy and production infrastructures, advocating green and low-carbon travel, perfecting environmental protection regulations, and reducing the emissions of the six most significant air pollutants.

After a certain period of time in operation, it is necessary to evaluate the effect and to analyze the efficiency of coordinated air pollution treatment by measuring the input–output ratio in the treatment process and by determining whether the air quality has been improved or not and whether the extent of improvement has reached the expected goal. Such test results can reveal strengths and weaknesses of the current system, demonstrate efficient methods of operation, and expose existing problems and difficulties with regard to current practices. Rewards and punishments are then given in a timely manner according to the assessment results. The input cost is reduced and the efficiency of the coordinated control process is improved in the next cycle by overcoming the shortcomings according to the assessment results. The system is improved after each cycle, and a closed loop of coordinated prevention and air pollution control is formed.

2.2. Pathway and Hierarchy Analysis of Systematic Coordinated Air Pollution Prevention and Control

It is the interaction and integration of the factors described in Section 2.1 that can help identify the goal of the coordinated control of air pollution and ensures the effectiveness of the cooperative control mechanism. In this section, based on the in-depth interviews, these factors and their interactions will be analyzed. First, the AHP method will be explained. Then, the data, which was collected through in-depth interviews, will be presented. Finally, how the order of priority of these factors were determined through analyzing in-depth interview data will be explained.

2.2.1. Building a Pathway System for Coordinated Prevention and Air Pollution Control

Below is a literature review on the prevention and control elements in the coordinated control mechanism for air pollution as well as previous research on the pathway and measures for air pollution prevention and control and adopted ideas from the following studies. The authors of [24] found that environmental regulation can promote the optimization and upgrading of industrial infrastructure, reduce pollution, and improve the quality of the environment. The authors of [25] estimated the emission intensity of different transportation modes by using the factor method for quantitatively determining the emission of air pollutants in the transportation sector and proposed that clean energy should be developed to reduce air pollution or realize air pollution prevention and control. In [26], the author proposes restricting enterprises to reduce waste emissions by adjusting tax standards based on the airflow characteristics of pollution between regions. In [27,28,29,30], the authors established static and dynamic spatial panel models and used the L.M. test method to explore the influence of population density, the degree of economic and social development, the speed of scientific and technological progress, the traffic status, green construction, energy consumption, and other factors on air pollution and its prevention and control under different conditions. From these existing studies, the pathways that have been tested in practice were selected as the initial system for the analytic hierarchy process.

Then, a priority-based evaluation of the systematic, coordinated prevention, and control pathways for air pollution was performed based on the literature review. In this step, experts and scholars in ecological environment protection, air pollution prevention, and control as well as practitioners who had been engaged in environmental monitoring, environmental protection, and air pollution prevention for a long period of time were invited to fully discuss, delete the inappropriate pathway in the initial system, and supplement and improve the existing initial pathway, to finally form the pathway system of systematic collaborative air pollution control as shown in

Table 1. The pathway system for the coordinated prevention and control of atmospheric pollution.

Overall Evaluation Target (Target Level)	First-Class Index (Criterion Level)	Secondary Indicators (Scheme Level)
Improve the effectiveness of the systematic and coordinated control of air pollution (X)	Building a collaborative governance system (X1)	Develop a systematic collaborative governance scheme (X11)
		Explore the digital governance pathway (X12)
		Strengthen the publicity of air pollution hazards (X13)
		Promote the construction of an infrastructure to achieve pollution reduction and carbon reduction (X14)
		Optimize the performance appraisal mechanism for collaborative governance (X15)
	Promote the optimization and adjustment of the industrial infrastructure (X2)	Improve energy efficiency (X21)
		Develop green industries (X22)
		Incentivize enterprises to eliminate outdated modes of production (X23)
		Improve industrial total factor green productivity (X24)
	Promote the transformation and upgrading of the energy infrastructure (X3)	Increase the proportion of emerging energy sources such as wind energy, bioenergy, and photovoltaic energy (X31)
		Vigorously promote the development of renewable energy (X32)
		Builde a clean and low-carbon energy system (X33)
	Improve the construction of the legal system (X4)	Establish a sound system constraint mechanism (X41)
		Perfect regulatory agencies and strengthen supervision (X42)
		Establish a strict air pollution emission standard (X43)
		Improve the Ecological Environment Protection Act (X44)

.

The overall goal of pathway evaluation is to improve the effectiveness of the systematic collaborative governance of air pollution. The first-level indicators are macro descriptions, which have four leading macro indicators: building a collaborative governance system, promoting the optimization and adjustment of the industrial infrastructure, promoting the transformation and upgrading of the energy infrastructure, and improving the construction of the legal system. The second-level index is the specific collaborative governance pathway for air pollution, in which the construction of a collaborative governance system includes five specific pathways: formulating a systematic collaborative governance scheme, exploring the digital governance pathway, strengthening the publicity of air pollution hazards, promoting the construction of pollution reduction and carbon reduction infrastructure, and optimizing the performance evaluation mechanism for collaborative governance. Promoting the improvement of the industrial infrastructure includes four specific pathways: improving the efficiency of energy utilization, developing green industries, prompting enterprises to eliminate outdated modes of production, and improving industrial total factor green productivity. Promoting the transformation and upgrading of energy infrastructure mainly includes three specific pathways: increasing the proportion of emerging sources of energy such as wind energy, bioenergy, and photovoltaic energy, vigorously promoting the development of renewable energy, and building a clean and low-carbon energy system. Improving the legal system mainly includes four specific pathways: establishing the institutional restraint mechanism, improving regulatory agencies, strengthening supervision, the tightening of air pollution emission standards, and improving the ecological environment.

In the process of evaluating the air pollution collaborative governance pathway in terms of priorities, the interrelation between each link and each element in the collaborative governance mechanism system was considered, and the specific governance pathways were included. Hence, the result is a relatively rigorous and comprehensive pathway system for the systematic collaborative governance of air pollution.

2.2.2. Analytic Hierarchy Process for Priority Evaluation for the Coordinated Prevention and Control of Air Pollution

The prioritization of the collaborative governance pathways was evaluated by employing the Analytic Hierarchy Process (AHP) method. This method is often used in the research of complex systems, and it is a systematic analysis method combining qualitative and quantitative analysis. The basic principle of AHP can be summarized as follows (as shown in Figure 2).

• According to the evaluation object, construct the structural relationship between elements and establish a hierarchical structure.
• According to the evaluation criteria, the degree of importance of each element relative to the upper element (target) is compared to form an evaluation matrix. According to this principle, it is possible to determine the ability of the systematic collaborative governance of air pollution to improve according to specific governmental pathways at the scheme level, which is convenient for experts when assigning scores and measurements.
• Judge the weight of the next level index relative to the previous level index, respectively, and then calculate the weight of each level element relative to the overall evaluation target and rank the importance of elements.

According to the analytical principle of the AHP method, when collecting data from the criterion level and the scheme level of the air pollution collaborative control pathway, we adopted the Likert scale method with five points. This transformed the pathway assignment into a survey question. A survey questionnaire was then designed, and data were collected by the questionnaire being distributed on WeChat, E-mail, and quiz star platforms.

(1)

Questionnaire design and revision

According to the calculation process of the analytic hierarchy process, one should first collect data for the criterion layer relative to the target layer and data for the scheme layer relative to the criterion layer in the pathway system for air pollution collaborative governance. According to this train of thought, the pathway description is transformed into the form of a problem. The main structure of the designed questionnaire was as follows: the first section consisted of basic information concerning the investigated object. The second section, the central part of the questionnaire, mainly included the construction of a collaborative governance system, the promotion of industrial infrastructure optimization and adjustment, the promotion of energy infrastructure transformation and upgrading, and the improvement of the construction of the legal system as well as the specific pathways contained in each subject, all of which were objective questions with five points. The third part was an open-ended questionnaire, the main purpose of which was to collect the respondents’ information about whether there are other ways to coordinate air pollution control.

(2)

Questionnaire distribution and recovery

In order to ensure the validity of the questionnaire and that it matched with the research pathway, after the design of the initial questionnaire was completed, a limited number of responses were investigated, mainly from other established experts and scholars in ecological environment protection, air pollution prevention, and monitoring at Xi’an University of Architecture and Technology, Northwest A&F University, La Trobe University, Wilfrid Laurier University, Northwest University, and the Academy of Environmental Sciences, Environmental Protection Bureau. The initial questionnaire was revised according to the investigation results.

The duration of the formal questionnaire distribution was four months. A total of 600 questionnaires were distributed mainly via the WeChat platform, e-mail, and the quiz star platform, and 538 questionnaires were responded to and returned. After eliminating any invalid questionnaires, 459 valid questionnaires were retained, with an effective response rate of 76.5%. They were then used as the sample data for the prioritization evaluation of the systematic collaborative governance pathway for air pollution.

(3)

Data collation and analysis

After the data were collected and collated, and the reliability and validity of the data were tested and analyzed using the social science statistical analysis software spss18.0 to ensure that the collected data could support the follow-up research.

①

Summary statistics

When statistically describing the data obtained through the survey questionnaire, the mean, variance, and standard deviation of the valid questionnaire data were analyzed via the factor analysis function in IBM SPSS 18.0. The specific analysis results are provided in

Table 2. Summary Statistics of the priority evaluation data of air pollution coordinated prevention and control pathway.

Serial Number	Secondary Indicators (Scheme Level)	Average Value	Variance	Standard Deviation
1	Develop systematic collaborative governance scheme (X11)	3.25	2.36	1.536
2	Explore the digital governance pathway (X12)	2.14	2.05	1.432
3	Strengthen the publicity of air pollution hazards (X13)	3.21	2.32	1.523
4	Promote the construction of an infrastructure to achieve pollution reduction and carbon reduction (X14)	1.48	1.96	1.40
5	Optimize the performance appraisal mechanism for collaborative governance (X15)	2.06	1.82	1.349
6	Improve energy efficiency (X21)	1.95	1.76	1.327
7	Develop green industry (X22)	3.54	3.43	1.852
8	Incentivize enterprises to eliminate outdated modes of production (X23)	2.13	1.98	1.407
9	Improve industrial total factor green productivity (X24)	4.01	3.69	1.921
10	Increase the proportion of emerging energy sources such as wind energy, bioenergy, and photovoltaic energy (X31)	2.36	2.31	1.519
11	Vigorously promote the development of renewable energy (X32)	1.58	1.21	1.10
12	Build a clean and low-carbon energy system (X33)	2.65	1.89	1.375
13	Establish a sound system constraint mechanism (X41)	3.52	2.36	1.536
14	Perfect regulatory agencies and strengthen supervision (X42)	3.94	2.89	1.70
15	Establihs a strict air pollution emission standard (X43)	2.56	2.09	1.446
16	Improve the Ecological Environment Protection Act (X44)	3.46	2.48	1.575

.

From the statistical description results in Table 2, it can be seen that the data obtained from the systematic collaborative control of air pollution have good consistency and can support the follow-up research work of this paper.

②

Reliability and validity of the data

The Cronbach method was used to test the reliability of the data collected from the questionnaire. The Cronbach coefficient was tested in the social science statistical analysis software SPSS 18.0, as shown in

Table 3. The Cronbach Coefficient of Priority Evaluation for the Air Pollution Collaborative Prevention Pathway.

Cronbach’s Alpha	Number of Terms	Significance (F test)
0.862	16	0.000

.

Secondly, the structural validity of the questionnaire was analyzed by exploratory factor analysis. The KMO value was 0.784, and Bartlett spherical test value was 624.056 (as shown in

Table 4. The KMO and Bartlett Spherical Test Values for the Priority Evaluation Questionnaire for the Air Pollution Collaborative Prevention and Control Pathway.

Kaiser-Meyer-Olkin measure of sampling degree		0.784
Bartlett’s sphericity test	Approximate chi-square	624.056
	Df	94
	Sig.	0.000

). Therefore, factor analysis could be carried out. It can be concluded that the questionnaire designed in this study has good structural validity.

In summary, the data collected by the questionnaire passed the reliability and validity test. The data could therefore effectively support the subsequent performance evaluation and analysis.

2.2.3. Priority Evaluation Weighting for the Air Pollution Collaborative Prevention and Control Pathway

a.

Determine the number of evaluation experts

In the specific implementation process of the priority evaluation of the air pollution collaborative governance pathway, considering the research needs and the calculation principle of the analytic hierarchy process, ten experts and scholars who had been engaged in air pollution prevention and control for a long period of time and workers who had been engaged in ecological environment protection, air pollution prevention, and monitoring for an extended period were selected to form an expert team.

b.

Determine the subject areas of evaluation experts.

To calculate the priority weightings of the air pollution collaborative governance pathways according to the principle of systematic collaborative governance with regards to air pollution, evaluation experts were selected mainly from universities and practical fields: ① Six experts and scholars from universities and research institutes who had engaged in air pollution prevention and control for an extended period, accounting for 60% of the team, and ② four practitioners from the front line of air pollution prevention and control who had been engaged in ecological environment protection, air pollution prevention, and monitoring for a long period of time, who accounting for the remaining 40%. To determine the influence of the specific priority evaluation subject on the objectivity of the evaluation results, the personnel from different fields mentioned above formed a nominal group

c.

Invite evaluation experts to score

Experts were invited to rate the importance of the criterion layers in the target layer and the importance of the scheme layers in each of the criterion layers. For the calculation, the simple average of the scores of each expert was used as the evaluation value of the relative importance of the index. The scoring criteria, according to Saaty’s 1–9 scale of basic comparison for the analytic hierarchy process, are provided in

Table 5. Scale of importance judgment.

Scale	Importance Judgment
1	Comparing the two indexes, they have the same importance.
3	Comparing the two indicators, the former is slightly more important than the latter.
5	Comparing the two indexes, the former index is obviously more important than the latter index.
7	Comparing the two indicators, the former is more important than the latter.
9	Comparing the two indicators, the former is extremely important than the latter.
2, 4, 6, 8	The median value of former adjacent importance degree.
Reciprocal	Comparing the two indicators, the latter is more important than the former.

.

d.

Construction and calculation of index weight judgment matrix in criterion layer

Firstly, with the help of experts’ scores, the importance matrix for the criterion (standard) layers of the target layer was constructed, with purpose of the target layer index (X) being to improve the effectiveness of systematic collaborative control with respect to air pollution. Level indicators were included to build a collaborative governance system (X₁), promote the optimization and adjustment of the industrial infrastructure (X₂), promote the transformation and upgrading of the energy infrastructure (X₃), and improve the construction of the legal system (X₄). Index X₁ is important relative to X₂, with a weight of 3, most important relative to X₃, with a weight of 4, and also important relative to X₄, with a weight of 2; X₂ is important relative to X₃, with a weight of 2; the index X₄ is important relative to X₂, with a weight of 2, and more important relative to X₃, with a weight of 3. The importance matrix is provided in

Table 6. Importance judgment matrix of the criterion layers (B) in the target layer (A).

Index	X1	X2	X3	X4	Wi	Wi′	BWi	${\mathit{\lambda }}_{\mathit{M}\mathit{A}\mathit{X}}$
X1	1	3	4	2	1.864	0.466	1.887	4.031
X2	1/3	1	2	1/2	0.644	0.161	0.647
X3	1/4	1/2	1	1/3	0.384	0.096	0.386
X4	1/2	2	3	1	1.109	0.277	1.12

.

In Table 5, λ is the vector characteristic heel, and W_i is the index importance vector after normalization. It is normalized as:

$$W_i={(\prod a_{ij})}^{\frac{1}{n}}$$

(1)

In order to ensure the consistency of the evaluation, it is necessary to check the consistency after the weight calculation. The consistency test needs to measure the maximum eigenvalues of the vector matrix. The square root method was used to calculate the eigenvalues, λ_i, and the maximum characteristic root, ${\lambda }_{MAX}$ =$\frac{1}{n}{\displaystyle \sum }_{i=1}^n{\lambda }_i$.

The following can be used to check the consistency of the matrix in Table 5.

$$C.I.=\frac{{\lambda }_{MAX}-N}{N-1}$$

(2)

In (2), N = 4 and ${\lambda }_{MAX}$= 4.031. According to the reference scale of the consistency test, the matrix passed the consistency test, which showed that the expert’s judgments on the importance of the criterion layer relative to the target layer had good consistency. The priority evaluation of the air pollution collaborative governance pathway can be sorted according to its weighted score, which is as follows.

The weighted score for formulating a systematic collaborative governance scheme (X₁₁) is 0.414, which means that the scheme is the most important and should be the first pathway to be implemented in the systematic collaborative governance of air pollution. The weighted score for the performance appraisal mechanism for optimized collaborative governance (X₁₅) is 0.345. That is, after the scheme is worked out, the performance appraisal for the collaborative governance of air pollution should be strengthened. Promoting the construction of pollution and carbon reduction infrastructure (X₁₄) has a weighted score of 0.152; the weighted score for the publicity on the hazards of air pollution (X₁₃) is 0.058. This means more people should know about the hazards of air pollution to human health and the ecological environment, and governments should enhance human awareness of environmental protection, discourage air pollution behaviors, and jointly protect healthy human homes. Finally, the weighted score for the exploring digital governance pathway (X₁₂) is 0.032. With the rapid development of the digital economy and technology, the digital governance pathway has become a more advanced measure and has influenced the direction of air pollution collaborative governance.

e.

Construction and calculation of index weight judgment matrix at scheme level

According to the above ideas concerning the index importance matrix of the criterion level, an index importance judgment matrix of the scheme level relative to the criterion level was also constructed, as shown in

Table 7. Importance judgment matrix of the scheme (C₁) in the criterion layer (B₁).

Index	X11	X12	X13	X14	X15	Wi	Wi′	BWi	${\mathit{\lambda }}_{\mathit{M}\mathit{A}\mathit{X}}$
X11	1	10	8	5	2	1.918	0.414	2.648	5.31
X12	1/10	1	1/3	1/6	1/9	0.149	0.032	0.155
X13	1/8	3	1	1/5	1/8	0.268	0.058	0.279
X14	1/5	6	5	1	1/4	0.703	0.152	0.803
X15	1/2	9	8	4	1	1.6	0.345	1.912

,

Table 8. Importance judgment matrix of the scheme (C₂) in the criterion layer (B₂).

Index	X21	X22	X23	X24	Wi	Wi′	BWi	${\mathit{\lambda }}_{\mathit{M}\mathit{A}\mathit{X}}$
X21	1	9	3	7	2.329	0.582	2.525	4.199
X22	1/9	1	1/6	1/4	0.178	0.044	0.18
X23	1/3	6	1	4	1.063	0.266	1.152
X24	1/7	4	1/4	1	0.429	0.107	0.433

,

Table 9. Importance judgment matrix of the scheme (C₃) in the criterion layer (B₃).

Index	X31	X32	X33	Wi	Wi′	BWi	${\mathit{\lambda }}_{\mathit{M}\mathit{A}\mathit{X}}$
X31	1	4	6	2.054	0.685	2.133	3.055
X32	1/4	1	3	0.663	0.221	0.674
X33	1/6	1/3	1	0.281	0.094	0.282

and

Table 10. Importance judgment matrix of the scheme (C₄) in the criterion (B₄).

Index	X41	X42	X43	X44	Wi	Wi′	BWi	${\mathit{\lambda }}_{\mathit{M}\mathit{A}\mathit{X}}$
X41	1	1/2	4	6	1.303	0.326	1.365	4.099
X42	2	1	5	7	2.024	0.506	2.113
X43	1/4	1/5	1	3	0.455	0.114	0.462
X44	1/6	1/7	1/3	1	0.219	0.055	0.219

.

In the importance matrix of C₁ of the standard layer B₁, the index of the standard layer B₁ is to build a collaborative governance system (X₁), and the indices of the plan layer C₁ are to formulate a systematic collaborative governance scheme (X₁₁), to explore a digital governance path (X₁₂), to strengthen the publicity of air pollution hazards (X₁₃), to promote the construction of infrastructure to achieve pollution reduction and carbon reduction (X₁₄), and to optimize the performance evaluation mechanism for collaborative governance (X₁₅). Index X₁₁ is the most important relative to X₁₂, with a weight of 10, followed by X₁₃, with a weight of 8, which is important relative to X₁₄, with a weight of 5, and important relative to X₁₅, with a weight of 2; index X₁₃ is important relative to X₁₂, with a weight of 3. Index X₁₄ is important relative to X₁₂, with a weight of 6; it is more important relative to X₁₃, with a weight of 5. Index X₁₅ is more important than X₁₂, X₁₃, and X₁₄ with a weight of 9, 8, and 4, respectively. The importance matrix is provided in Table 7.

We then checked the consistency of matrix C₁. The consistency test coefficient was $C.I.=\frac{{\lambda }_{MAX}-N}{N-1}=$ 0.078, N = 5, C.R. = 0.078/1.12 = 0.07 < 0.1. Therefore, the judgment matrix C₁ passed the consistency test.

In the importance matrix of C₂ in the standard layer B₂, the index of the standard layer B₂ is to promote the optimization and adjustment of the industrial infrastructure (X₂), and the indices of the plan layer C₂ are to improve energy utilization efficiency (X₂₁), to develop green industries (X₂₂), to urge enterprises to eliminate backward modes of production (X₂₃), and to improve the total factor green productivity of industry (X₂₄). The index X₂₁ is the most important relative to X₂₂, with a weight of 9, more important relative to X₂₃, with a weight of 3, and important relative to X₂₄, with a weight of 7. Index X₂₃ is important relative to X₂₂, with a weight of 6, and is more important relative to X₂₄, with a weight of 4. Index X₂₄ is important relative to X₂₂, with a weight of 4. The importance matrix is provided in Table 8.

The consistency of matrix C₂ was checked by the consistency test. The coefficient from the test was $C.I.=\frac{{\lambda }_{MAX}-N}{N-1}=$ 0.066, N = 4, C.R. = 0.066/0.9 = 0.07 < 0.1. Hence, the judgment matrix C₂ passed the consistency test.

In the importance matrix of C₃ in the standard layer B₃, the index of the standard layer B₃ is to promote the transformation and upgrading of energy infrastructure (X₃), and the indices of the plan layer C₃ are to increase the proportion of emerging energy sources such as wind energy, bioenergy, and photovoltaic energy (X₃₁), to vigorously promote the development of renewable energy (X₃₂), and to build a clean and low-carbon energy system (X₃₃). The index X₃₁ is important relative to X₃₂, with a weight of 4; it is important relative to X₃₃, with a weight of 6; index X₃₂ is important relative to X₃₃, with a weight of 3. The importance matrix is provided in Table 9.

The consistency test coefficient obtained from checking the consistency of matrix C₃ was $C.I.=\frac{{\lambda }_{MAX}-N}{N-1}=$ 0.028, N = 3, and C.R. = 0.028/0.58 = 0.05 < 0.1. Hence, the judgment matrix passed the consistency test.

In the importance matrix of C₄ in the standard level B₄, the index of the standard level B₄ is to improve the legal system construction (X₄), and the indices of the plan level C₄ are to establish and improve the institutional restraint mechanism (X₄₁), to improve the supervision institutions and strengthen supervision (X₄₂), to strictly enforce air pollution emission standards (X₄₃), and to improve the Ecological Environment Protection Act (X₄₄). The index X₄₁ is more important than X₄₃, with a weight of 4, and more important than X₄₄, with a weight of 6. The index X₄₂ is important relative to X₄₁, X₄₃, and X₄₄, with a weight of 2, 5, and 7, respectively. The index X₄₃ is important relative to X₄₄, with a weight of 3. The importance matrix is provided in Table 10.

We also checked the consistency of matrix C₄. The consistency test coefficient was $C.I.=\frac{{\lambda }_{MAX}-N}{N-1}=$ 0.033, N = 4, C.R. = 0.033/0.9 = 0.037 < 0.1, so the judgment matrix C₄ passed the consistency test.

f.

Weight determination and ranking

To judge the weight of the performance evaluation index it was necessary to calculate the weight by combining the relative importance of each level index with that of the upper-level index. The weight matrix of the comprehensive index is provided in

Table 11. The comprehensive index weight matrix.

Index	X1 (0.466)	X2 (0.161)	X3 (0.096)	X4 (0.277)	Combination Weight
Develop a systematic collaborative governance scheme (X11)	0.414	0	0	0	0.193
Explore the digital governance pathway (X12)	0.032	0	0	0	0.015
Strengthen the publicity of air pollution hazards (X13)	0.058	0	0	0	0.027
Promote the construction of infrastructure to achieve pollution reduction and carbon reduction (X14)	0.152	0	0	0	0.071
Optimize the performance appraisal mechanism for collaborative governance (X15)	0.345	0	0	0	0.161
Improve energy efficiency (X21)	0	0.582	0	0	0.094
Develop green industry (X22)	0	0.044	0	0	0.007
Incentivize enterprises to eliminate outdated modes of production (X23)	0	0.266	0	0	0.043
Improve industrial total factor green productivity (X24)	0	0.107	0	0	0.017
Increase the proportion of emerging energy sources such as wind energy, bioenergy, and photovoltaic energy (X31)	0	0	0.685	0	0.066
Vigorously promote the development of renewable energy (X32)	0	0	0.221	0	0.021
Building a clean and low-carbon energy system (X33)	0	0	0.094	0	0.009
Establish a sound system constraint mechanism (X41)	0	0	0	0.326	0.091
Perfect regulatory agencies and strengthen supervision (X42)	0	0	0	0.506	0.14
Establish a strict air pollution emission standard (X43)	0	0	0	0.114	0.032
Improve the Ecological Environment Protection Act (X44)	0	0	0	0.055	0.015

.

According to Table 10, the index weight vector can be obtained by judging the comprehensive weight of the priority evaluation of the air pollution cooperative governance pathway: W = (0.193, 0.015, 0.027, 0.071, 0.161, 0.094, 0.007, 0.043, 0.017, 0.066, 0.021, 0.009, 0.091, 0.14, 0.032, 0.015).

3. Results

3.1. Research Summary

According to the index weight vector from the priority evaluation of the systematic collaborative governance pathways for air pollution, the major paths are listed in descending order of priority as follows: formulating a systematic and collaborative governance scheme, refining the collaborative governance performance appraisal mechanism, perfecting regulatory agencies and strengthening supervision, improving the efficiency of energy utilization, establishing and perfecting the institutional restraint mechanism, promoting the construction of infrastructure for reducing pollution and carbon, increasing the proportion of emerging energy such as wind energy, bioenergy, and photovoltaic energy, urging enterprises to eliminate backward modes of production, tightening air pollution emission standards, strengthening the publicity of air pollution hazards, vigorously promoting the development of renewable energy, improving the industrial total factor green productivity, improving the Ecological Environment Protection Act, exploring the digital governance pathway, building a clean and low-carbon energy system, and developing green industries.

3.2. Research Impact

Literature reviews and case studies have confirmed that air pollution can only be controlled in a systematic and coordinated way: in [31], the authors conclude that nowhere is immune to regional environmental problems and suggest that local governments adjacent to each other should bypass administrative barriers and coordinate environmental governance. The analysis in [32] shows that in the coordinated prevention and control of air pollution, the central government’s continuous coordination of the cooperative behavior of local governments from top to bottom, and the formation of a joint prevention and control mechanism for air pollution are helpful when encouraging local governments to move from “going their own way” towards “win-win cooperation”. China has proposed to build a community of common destiny for mankind and promised to achieve carbon neutrality by 2060. Countries such as the United States have also encouraged cooperative actions for air pollution prevention and control which have been jointly initiated by various departments of the federal government [33].

However, the coordinated control of air pollution is a step-by-step process. Among many measures, there should be a priority system. Otherwise, it will only achieve half of its aims with twice the effort or even waste many human, material, and financial resources. In this research, a hierarchical analysis of the order of priority order for the air pollution collaborative control pathways were conducted. The collaborative governance measures were ranked according to their contributions. The ranking result is the priority sequence of these governance measures for air pollution. Some managerial and policy insights on effective and systematic coordinated air pollution control are also put forward according to the pathway analysis.

The world health organization defines air pollution as the “contamination of the indoor or outdoor environment by any chemical, physical or biological agent that modifies the natural characteristics of the atmosphere” (https://www.who.int/health-topics/air-pollution, accessed on: 5 March 2022). One consequence of air pollution is climate change caused by increases in the atmospheric concentrations of greenhouse gases. Carbon dioxide (CO₂) is the primary greenhouse gas emitted through human activities. For example, the Chinese government promised to peak its carbon-dioxide emissions by 2030, achieve “carbon neutrality” by 2060, and establish a green, low carbon, and circular economic development system [34]. Pathways to these goals include the deep integration of emerging technologies such as the Internet, big data, artificial intelligence, and 5G technology with green low-carbon industries, the development of a green manufacturing and service system, an increase in the proportion of green low-carbon industries in the total economic output, the adjustment of industrial and energy infrastructures, and active participation in international negotiations on climate change [35]. These pathways are all included in our study; for further details, see the insights obtained from our research below. Overall, our study of the coordination of these pathways provides insights on achieving “carbon neutrality”.

The burning of fossil fuels is the primary human activity that leads to greenhouse gas emissions. In the “14th Five-Year Plan”, the Chinese government attaches great importance to energy conservation and emission reduction. To reach this goal, the Chinese government suggested the following pathways: improving the control of the dual factors of total energy consumption and intensity, implementing the system to control carbon intensity (as a first priority) and total carbon emissions (as a second), helping qualified localities, key industries, and enterprises to reach a peak in carbon emissions first, promoting clean, low-carbon, safe, and efficient use of energy, and further promoting low-carbon transformation, tightening the control of methane, hydrofluorocarbons, perfluorocarbons, and other greenhouse gas emissions, improving the carbon capture capacity of the ecosystem, constructively participating in and leading international cooperation on climate change, advocating the implementation of the United Nations Framework Convention on Climate Change and its Paris Agreement, and actively carrying out South–South cooperation on climate change [36]. All these pathways are also included in our study; for more details, see the insights obtained from our research below. Therefore, our study of the coordination of these pathways provides insights into achieving policies such as the “14th Five-Year Plan”.

The coordinated prevention and control of air pollution can effectively reduce the mutual movement and influence of pollutants among cities, reduce regional air pollutant emissions to the greatest extent, and minimize the deficiency of the divide-and-conquer model of air pollution control. There are risks associated with the divide-and-conquer model: for a long time, restricted by the traditional governance concept of “polluter pays”, there are risks and limitations in the coordinated prevention and control of air pollution, such as the pollution income being greater than the governance cost and the difficulty of incorporating other subjects. On the other hand, under the framework of a coordinated air pollution control mechanism, there remain unaccounted for participants, an unclear division of responsibilities among the subjects, and the risk of mutual prevarication and wrangling, making it challenging to form complementary advantages [37]. To reduce this risk, this research proposes a clear prescription of the rights and responsibilities of each region under the same governance goal in the construction of the coordinated prevention and control mechanism for air pollution, the periodical assessment of the performance of each region, the timely delivery of feedback, and the prompt adjustment of the joint prevention and control governance pathway according to the assessment results. These steps form a closed-loop system.

3.3. Policy Recommendations

In this paper, a systematic cooperative control mechanism for air pollution has been studied. Based on the main paths in the cooperative control mechanism for air pollution, the systematic cooperative control pathway system for air pollution was constructed. The analytic hierarchy process (AHP) was adopted to rank the constructed systematic cooperative control pathways for air pollution according to their contribution to the overall goal of air pollution control. Based on the analysis results, there are three major conclusions and insights.

Firstly, governments should attach great importance to the pathway of governance and the pathways related to the leadership of the organizational structure of the systematic collaborative governance of air pollution. According to the analytic hierarchy process (AHP) measurement results, the three paths, namely, making a systematic and collaborative governance scheme, optimizing the collaborative governance performance appraisal mechanism, improving regulations, and strengthening supervision, have contributed the most to improving collaborative governance capacity in terms of air pollution. Looking at these three pathways from a systematic perspective, one has no difficulty in finding that they are all achieved at the leadership level of the air pollution collaborative governance hierarchy, that is, the top level of the collaborative governance hierarchy.

When the air pollution joint prevention and control system is established, a government should first establish a collaborative control scheme and require all regions to determine the required tasks according to the scheme. Then, in the actual implementation process, it is necessary to strengthen the supervision mechanism to ensure that the tasks in the scheme are implemented. Finally, according to the effect of the implementation plan, the effectiveness of air pollution prevention and the control and air quality, the rewards and punishments should be clear-cut to ensure the further effective execution of the cooperative control of air pollution. In addition, according to the priority evaluation results of the collaborative governance pathway, governments should also progressively implement the systematic collaborative governance of air pollution. Most countries can follow this recommendation by integrating new technology into existing infrastructure and using policy instruments. Pathways related to this recommendation include establishing and perfecting the institutional mechanism to restrain activities that contribute to air pollution in various regions through laying foundations and ensuring compliance with respect to the joint prevention and control of air pollution.

Secondly, it is necessary to tightly control the emission standards for air pollution, set high standards satisfying the system’s constraints, and curb air pollution from all sources. It is also vital to increase public awareness of the dangers of air pollution. When the time is right and the system is running smoothly, the government should introduce bills to strengthen ecological environmental protection and ensure the long-term continuation of the collaborative governance system. As the first recommendation, this recommendation also includes pathways that can be implemented through the integration of technology or investment. Pathways related to this recommendation mainly include improving the efficiency of energy utilization, expanding the construction of pollution reduction and carbon reduction infrastructure, increasing the proportion of green energy such as wind energy, bioenergy, and photovoltaic energy in the total energy consumption, encouraging enterprises to eliminate outdated modes of production, fostering the development of renewable energy, and advocating an increase in the green total factor productivity. Theoretically, although these pathways have different priorities, they can be implemented in parallel or in any order under certain conditions.

Thirdly, with advancements in science and technology, economic growth, and social development in most countries, the model of the systematic collaborative control of air pollution should be gradually pushed to a higher level by exploring pathways including developing digital governments, building a clean and low-carbon energy system, and fostering green industries. Under the previous implementation of the joint prevention and control, air pollution has been dramatically reduced, and air quality has been improved. At this stage, the goals regarding the joint prevention and control of air pollution are mainly to maintain air quality, build a clean energy system, reduce major air pollution sources, develop green industries, and promote sustainable development under current economic, societal, cultural, and ecological conditions.

4. Conclusions and Future Research Plan

4.1. Highlights of the Research

In this research, the mechanism of the coordinated control of air pollution was investigated from a systemic perspective. The established coordinated prevention and control pathways for air pollution were ranked according to their contribution levels using the AHP methodology. In-depth interviews with practitioners and scholars in air pollution were conducted to evaluate the contributions of different paths. Accordingly, policy suggestions on coordinated air pollution were put forward.

4.2. Strengths and Limitations of the Research

4.2.1. Strengths of the Research

This research expands and enriches theoretical results and practical insights on the coordinated prevention and control of air pollution. The main contribution of this study is the development of a priority pathway system for collaborative air pollution prevention and control. This research is significant because in the joint prevention and control of air pollution in practice, one can apply our results to select the method that contributes most among all possible pathways. Thus, our results can help not only reduce the investments in resources and costs associated with air pollution prevention and control but also greatly improve its efficiency.

4.2.2. Limitations and Future Research

One limitation of the article is that in the process of constructing the systematic, coordinated pathway system for air pollution prevention and control, our literature review may not have been comprehensive enough. Thus, it is possible that some pathways for air pollution prevention and control have been omitted in this study. In addition, in the process of evaluating the prioritization of collaborative governance pathways by AHP, the number and subjectivity of experts may have had a specific impact on the research results. In the future, we plan to adopt a more objective methodology to research the coordinated prevention and control of air pollution.