Public-oriented air quality standard implementation social benefit evaluation method

Abstract

The invention relates to a public-oriented air quality standard implementation social benefit evaluation method. The method comprises the following steps: S1, constructing a social benefit evaluation index system; s2, determining an index weight; s3, collecting data; s4, analyzing the data to obtain comprehensive scores of different collected data; and S5, result grading and evaluation output are carried out, and an index weight table and a social benefit score are formed. The scientific, comprehensive and practical air quality standard social benefit assessment method is constructed, the cognition, behavior and emotional response of the public to air quality changes is quantitatively assessed through multi-dimensional data collection and analysis, the method has innovativeness, scientificity and practical application value, and important support can be provided for environmental policy optimization.

Description

Technical Field

[0001] The present invention relates to a benefit evaluation method, and in particular to a technical method for evaluating the spillover benefits generated by the implementation of air quality standards at the public attitude level. Background Art

[0002] The Ambient Air Quality Standard (GB3095) (hereinafter referred to as the Standard) is a milestone in the process of air pollution prevention and control, which has led to significant changes in air pollution work and pollution characteristics. With more than 60% of cities meeting the air quality standards, the current standards no longer have the role of leading the continuous improvement of air quality in most cities that meet the standards. However, key issues such as when the air quality standards will be revised, at what level the standards will be set, what benefits the implementation of the new standards will bring, how much it will cost, and what economic impacts will be generated urgently need to be comprehensively and comprehensively studied. The benefit evaluation generated by the implementation of air quality standards has become a research hotspot. Current research mainly focuses on the impact of air pollution on human health benefit evaluation and the extent of the impact, while there are few reports on social benefit evaluation for the public. The quality of air quality directly affects the quality of life of the public, and then affects the public's emotions and mental health. Studying the impact of air pollution on the public can better evaluate the social cost of air pollution control.

[0003] Social benefits refer to the positive role or beneficial effects of people's social practice activities on social development. The definition of social benefits is relatively broad. The social effects of policies are not obvious. Qualitative or quantitative evaluation of the social benefits of policies can not only evaluate the policy effects, but also provide guiding experience for further work. The following are several common methods for evaluating the social benefits of policies from different perspectives:

[0004] (1) Cost-benefit analysis is a quantitative evaluation method used to compare the social costs and benefits of policy implementation. By evaluating the economic and social benefits of a policy, the policy's return on investment can be determined and decision makers can be helped to make rational choices between different policy options. The social cost of the policy can be monetized and the public's attitude towards it can be expressed by their willingness to pay.

[0005] (2) Social return analysis: Social return analysis is a comprehensive evaluation method used to measure the impact of policy implementation on society, economy and environment. Different from traditional economic return analysis, social return analysis focuses on measuring the impact of policies on social welfare, including economic benefits, social benefits and environmental benefits. The social benefits evaluated by this method are usually broad social benefits, and pay more attention to marginalized groups than other methods.

[0006] (3) Sustainability assessment: Sustainability assessment is a comprehensive assessment method used to evaluate the impact of policy implementation on sustainable development goals. By comprehensively considering key factors in social, economic and environmental aspects, sustainability assessment can help policymakers determine whether the social benefits generated by policies can be sustained in the long run.

[0007] (4) Multi-criteria decision analysis is an evaluation method that considers multiple factors and is used to evaluate the social benefits of policy options. Commonly used methods for implementing this analysis include analytic hierarchy process, data envelopment method, expert consultation method, etc. By incorporating the weights of different factors into the evaluation process, multi-criteria decision analysis can help decision makers understand the advantages and disadvantages of different policy options and make corresponding decisions.

[0008] For policies that are difficult to directly judge the social benefits through direct evidence, an indicator system can be constructed to determine the secondary indicators of the social benefit indicators. Through detailed decomposition, the breadth and depth of the evaluation can be compressed, and the systematic nature of the social benefit evaluation can be ensured, and the evaluation can be carried out on several major factors that affect the social benefits. After determining the indicator system, the weight of the indicator can be determined by consulting experts in different fields to form a judgment matrix, or by constructing a mathematical model for simulation analysis, such as principal component analysis (PCA). If the aggregation level is reduced, the variance explained by each component is also reduced, so as to judge the importance of the indicator.

[0009] The evaluation of social benefits involves various factors related to human social activities, and is complex, diverse, and difficult to quantify. In addition, there are no reports on the evaluation of social benefits of the implementation of ambient air quality standards at home and abroad, and the evaluation indicators, models, and methods have not yet formed a specific paradigm. Therefore, it is particularly important to propose a method for evaluating the social benefits of the implementation of air quality standards for the public, which can accurately and quantitatively evaluate the social benefits of the implementation of air quality standards. Summary of the invention

[0010] The purpose of this invention is to evaluate the social spillover benefits of air pollution control driven by the Ambient Air Quality Standard (GB3095) by constructing an indicator system, that is, the spillover benefits of air quality improvement brought about by the implementation of the standard at the level of public attitude, and propose a social benefit evaluation method for the implementation of air quality standards for the public, so as to conduct an accurate quantitative technical evaluation of the social benefits of the implementation of air quality standards.

[0011] To achieve the above object, the present invention provides a method for evaluating the social benefits of implementing air quality standards for the public, comprising the following steps:

[0012] Step S1, construct a social benefit evaluation index system, including three dimensions: cognition, satisfaction, and behavior, and design a questionnaire to quantify the indicators through the Likert five-level scoring method. The indicators, data sources, and quantification methods are as follows:

[0013]

[0014] Step S2, determine the indicator weights, use expert consultation method combined with analytic hierarchy process to obtain a judgment matrix with a 1-9 scale to determine the indicator weights, including:

[0015] Step S201, obtaining a judgment matrix, including organizing no less than 15 experts to conduct multiple rounds of anonymous questionnaire surveys, and using the 1-9 scaling method to construct a judgment matrix, comparing each pair of indicators, and each expert independently completing the comparison of the importance of indicators to construct a pairwise comparison judgment matrix, summarizing the matrices of all experts, calculating the mean of each pair of indicators, returning the summary results to the expert group, anonymously feedbacking the group's opinions, and requiring the adjustment of the scores until consensus is reached;

[0016] Step S202, weight calculation, including calculating the maximum eigenvalue λ of the judgment matrix max The eigenvector W = [w 1 ,w 2 ,…,w n ], and use the standardization method to normalize the feature vector:

[0017]

[0018] Calculate the consistency index CI:

[0019] CR=CI / RI

[0020] Among them, RI is the random consistency index, which is determined according to the matrix dimension n in combination with the following table. If CR<0.1, the matrix consistency is good, otherwise it needs to be corrected;

[0021] n 1 2 3 4 5 6 7 8 9 10 RI 0.0 0.0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49

[0022] The verified feature vector is the final weight;

[0023] Step S3, collecting data, obtaining data on the three dimensions of cognition, satisfaction, and behavior through questionnaire surveys to assess public cognition, or obtaining data through real-time monitoring, performing Poisson regression analysis to exclude other influencing factors, and quantifying the impact of air pollution changes on public cognition or behavior;

[0024] Step S4, analyzing the data, describing the statistical analysis, by calculating the mean, standard deviation and distribution, analyzing the correlation between different indicators through the Pearson correlation coefficient or the Spearman rank correlation coefficient, establishing a multiple linear regression model or a structural equation model, describing the comprehensive impact of each indicator on the public attitude, including weighted calculation of each indicator of each data collected in step S3 based on the determined indicator weights, and obtaining the comprehensive score of different collected data, wherein data annotation and comprehensive scoring include:

[0025] The scores of each indicator are standardized to the interval [0,1]:

[0026] X j =(X-min(X)) / (max(X)-min(X))

[0027] Calculate the comprehensive index for each region:

[0028]

[0029] Among them, EI is the comprehensive evaluation index, W j is the weight of the jth indicator, X j is the standardized score of the jth indicator;

[0030] Step S5, result grading, evaluation output, forming an indicator weight table and social benefit score, and dividing the social benefit into five levels according to the comprehensive index: excellent: EI ≥ 0.8; good: 0.6 ≤ EI < 0.8; medium: 0.4 ≤ EI < 0.6; poor: 0.2 ≤ EI < 0.4; extremely poor: EI < 0.2.

[0031] Preferably, the experts consulted by the expert consultation method should include experts in the fields of environment, social psychology, social behavior, and public health.

[0032] Preferably, the meaning of the scale in the 1-9 scale is defined as follows:

[0033] 1: The two indicators are equally important;

[0034] 3: One side is slightly more important;

[0035] 5: One side is important;

[0036] 7: One party is extremely important;

[0037] 9: One party is absolutely important;

[0038] 2, 4, 6, and 8 are intermediate values ​​between the two;

[0039] If the importance of indicator i to j is a ij ,but

[0040] Preferably, in step S201, 2 to 3 rounds are usually performed until the judgment matrix converges, and the mean values ​​of all expert scores are summarized to form a final judgment matrix.

[0041] Preferably, in step S4, the data is cleaned during data analysis, and the cleaning rules include:

[0042] If a small amount of data is missing (<5%), use the mean or median to fill in the missing data; if the proportion of missing values ​​is high (>20%), delete the questionnaire; check whether individual respondents have logical errors, and convert the text options in the questionnaire into numerical scores.

[0043] Preferably, in step S3, the step of obtaining data in three dimensions of cognition, satisfaction and behavior through a questionnaire survey to evaluate public cognition includes:

[0044] Design questions based on the three dimensions of public cognition, behavior and emotion;

[0045] The sample selection adopted stratified random sampling method to cover different age, income, regional and occupational groups, and the sample size was greater than 500 people.

[0046] Preferably, in step S3, the steps of acquiring data by real-time monitoring, performing Poisson regression analysis to exclude other influencing factors, and quantifying the impact of air pollution changes on public cognition or behavior include:

[0047] The polynomial formula for air quality and public perception or behavior is fitted, and the Poisson regression is as follows:

[0048]

[0049] Among them, λ k is the average rate of events occurring per unit time or per unit space, and k is the number of events occurring.

[0050] Based on the above technical solution, the advantages of the present invention are:

[0051] This paper constructs a scientific, comprehensive and practical method for evaluating the social benefits of air quality standards. Through multi-dimensional data collection and analysis, it quantitatively evaluates the public's cognitive, behavioral and emotional responses to air quality changes. It is innovative, scientific and has practical application value, and can provide important support for the optimization of environmental policies. For the first time, the public is taken as the core research object. By building a scientific evaluation system, the social spillover benefits generated after the implementation of air quality standards are deeply explored, filling the gap in the quantitative technical evaluation methods at the social level in existing research. It is suitable for different regions and groups and has good universality and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0053] Figure 1 Flowchart of social benefit assessment methodology for implementing air quality standards;

[0054] Figure 2 It is a schematic diagram of the indicator system;

[0055] Figure 3 An example of a survey questionnaire. DETAILED DESCRIPTION

[0056] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments.

[0057] The present invention provides a method for evaluating the social benefits of implementing air quality standards for the public, comprising the following steps:

[0058] Step S1, construct a social benefit evaluation index system, including three dimensions: cognition, satisfaction, and behavior, and design a questionnaire to quantify the indicators through the Likert five-level scoring method. The indicators, data sources, and quantification methods are as follows:

[0059] Building a social benefit evaluation index system is the key to qualitatively or quantitatively evaluating the social spillover benefits of air quality changes at the public level. We can conduct qualitative and quantitative explorations from the perspectives of public awareness, behavior, and emotions and their influencing factors, and we can also evaluate the social benefits of air pollution throughout the process through the interrelationships between these three dimensions.

[0060] 1) Determine the evaluation dimensions:

[0061] Public awareness: includes the public's level of awareness of the implementation of air quality standards (such as the degree of understanding of the policy and the perceived improvement in air quality after implementation). Public behavior: assesses changes in public behavior, such as the proportion of green travel and environmentally conscious behavior (energy-saving electricity, garbage sorting, etc.). Public sentiment: quantifies the public's satisfaction with changes in air quality and their subjective feelings about health and quality of life.

[0062] 2) Define specific indicators:

[0063] Several specific indicators are detailed under each dimension.

[0064] Public awareness: awareness of standards and knowledge of air pollution.

[0065] Perception level: The public's perception of air quality changes, which can be scored directly through a questionnaire. Environmental knowledge level: The degree of knowledge about air quality improvement, based on the scores of a standardized test questionnaire.

[0066] Public behavior: green behavior participation rate, frequency of participation in environmental protection activities.

[0067] Environmentally friendly behavior: The public actively intends to reduce environmental pollution or takes actual actions. Risk avoidance behavior: Actively taking actions to isolate or reduce the harm of air pollution, such as wearing masks.

[0068] Public sentiment: satisfaction ratings of improvements, subjective health improvement ratings.

[0069] Satisfaction with health impact: The public's satisfaction with the health benefits of improved air quality. Satisfaction with improved quality of life: The public's overall evaluation of the improved quality of life.

[0070] 3) Quantification of indicators:

[0071] Design a questionnaire and quantify the indicators using the Likert five-level rating method. For example, public satisfaction can be expressed by rating from "very dissatisfied" to "very satisfied", as shown in the following table:

[0072]

[0073]

[0074] Step S2, determine the indicator weights, use the expert consultation method combined with the hierarchical analysis method to obtain the judgment matrix with a 1-9 scale to determine the indicator weights, and combine the weights of the two to obtain the weighted comprehensive weights. The combination of the two avoids the artificiality and arbitrariness of indicator selection caused by only using the data envelopment method and the subjectivity of only using the hierarchical analysis method. Specifically, it includes:

[0075] Step S201, obtaining a judgment matrix, including organizing no less than 15 experts to conduct multiple rounds of anonymous questionnaires, and using the 1-9 scaling method to construct a judgment matrix, each pair of indicators is compared in pairs, each expert independently completes the comparison of the importance of indicators, constructs a pairwise comparison judgment matrix, summarizes the matrices of all experts, calculates the mean of each pair of indicators, returns the summary results to the expert group, anonymously feedbacks the group's opinions, and requires adjustment of the score until a consensus is reached. Usually 2-3 rounds are carried out until the judgment matrix converges (the score fluctuation range of each pair of indicators is small, or the consistency is passed). The mean of all expert scores is summarized to form the final judgment matrix.

[0076] Preferably, the experts consulted by the expert consultation method should include experts in the fields of environment, social psychology, social behavior, and public health.

[0077] Preferably, the meaning of the scale in the 1-9 scale is defined as follows:

[0078] 1: The two indicators are equally important;

[0079] 3: One side is slightly more important;

[0080] 5: One side is important;

[0081] 7: One party is extremely important;

[0082] 9: One party is absolutely important;

[0083] 2, 4, 6, and 8 are intermediate values ​​between the two;

[0084] If the importance of indicator i to j is a ij ,but

[0085] Step S202, weight calculation, including calculating the maximum eigenvalue λ of the judgment matrix max The eigenvector W = [w 1 ,w 2 ,…,w n ], and use the standardization method to normalize the feature vector:

[0086]

[0087] Calculate the consistency index CI:

[0088] CR=CI / RI

[0089] Among them, RI is the random consistency index, which is determined according to the matrix dimension n in combination with the following table. If CR<0.1, the matrix consistency is good, otherwise it needs to be corrected;

[0090] n 1 2 3 4 5 6 7 8 9 10 RI 0.0 0.0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49

[0091] The feature vector that passes the verification is the final weight.

[0092] Step S3, collect data, obtain data on the three dimensions of cognition, satisfaction, and behavior through questionnaire surveys to evaluate public cognition, or use real-time monitoring to obtain data, perform Poisson regression analysis to exclude other influencing factors, and quantify the impact of air pollution changes on public cognition or behavior.

[0093] Preferably, in step S3, data on the three dimensions of cognition, satisfaction and behavior are obtained through questionnaire surveys to evaluate public cognition. Data on perception, atmospheric science knowledge and behavioral intentions are obtained through questionnaire surveys to evaluate public cognition. The questionnaires need to be analyzed separately according to conditions such as age group, income and location, and the influencing factors of social benefits can be explored. The steps include:

[0094] Questions were designed based on the three dimensions of public cognition, behavior, and emotion; for example, do you understand the content of the implementation of air quality standards? (Options: very well understood, relatively well understood, generally understood, not understood much, not understood); Have you reduced your driving frequency in the past three months? (Options: reduced a lot, reduced some, no change, increased some, increased a lot); How satisfied are you with the current improvement in air quality? (Likert five-point rating) and other questions can be referred to the attached Figure 3 The questionnaire shown is:

[0095] The stratified random sampling method is mainly used to ensure coverage of different age, income, region and occupation groups. The recommended sample size is not less than 500 people. Use electronic questionnaires (such as Google Forms, Questionnaire Star) or paper questionnaires.

[0096] Preferably, in step S3, the steps of acquiring data by real-time monitoring, performing Poisson regression analysis to exclude other influencing factors, and quantifying the impact of air pollution changes on public cognition or behavior include:

[0097] The polynomial formula for air quality and public perception or behavior is fitted, and the Poisson regression is as follows:

[0098]

[0099] Among them, λ k is the average rate of events occurring per unit time or per unit space, and k is the number of events occurring.

[0100] We can also use platforms such as Weibo and WeChat to explore the public's emotions and satisfaction with air quality through semantic analysis of social media. We will conduct regression analysis on the data with continuous time series, exclude interference from economic and health factors, and use the public's response in the three dimensions of cognition, behavior and satisfaction to comprehensively represent the social benefits brought by the Standard.

[0101] Step S4, analyze the data, describe the statistical analysis by calculating the mean, standard deviation and distribution, analyze the correlation between different indicators through the Pearson correlation coefficient or the Spearman rank correlation coefficient, establish a multivariate linear regression model or a structural equation model, describe the comprehensive impact of each indicator on public attitudes, including weighted calculation of each indicator of each data collected in step S3 based on the determined indicator weights, and obtain the comprehensive score of different collected data. Data processing tools can use SPSS, R, Python, etc.

[0102] Among them, data annotation and comprehensive scoring include:

[0103] The scores of each indicator are standardized to the interval [0,1]:

[0104] X j =(X-min(X)) / (max(X)-min(X))

[0105] Calculate the comprehensive index for each region:

[0106]

[0107] Among them, EI is the comprehensive evaluation index, W j is the weight of the jth indicator, X j is the standardized score of the jth indicator.

[0108] Preferably, in step S4, the data is cleaned during data analysis, and the cleaning rules include: if a small amount of data is missing (<5%), use the mean or median to fill in, if the proportion of missing values ​​is high (>20%), delete the questionnaire. Check whether a single respondent has logical errors (such as age and income not matching). Convert text options in the questionnaire (such as "very satisfied") into numerical values ​​(1-5 points).

[0109] Step S5, the results are graded, the evaluation output is generated, and the index weight table and social benefit score are formed to provide a quantitative basis for the optimization of air quality policies in different regions. According to the comprehensive index, the social benefits are divided into five levels: excellent: EI ≥ 0.8; good: 0.6 ≤ EI < 0.8; medium: 0.4 ≤ EI < 0.6; poor: 0.2 ≤ EI < 0.4; extremely poor: EI < 0.2.

[0110] This paper constructs a scientific, comprehensive and practical method for evaluating the social benefits of air quality standards. Through multi-dimensional data collection and analysis, it quantitatively evaluates the public's cognitive, behavioral and emotional responses to air quality changes. It is innovative, scientific and has practical application value, and can provide important support for the optimization of environmental policies. For the first time, the public is taken as the core research object. By building a scientific evaluation system, the social spillover benefits generated after the implementation of air quality standards are deeply explored, filling the gap in the quantitative technical evaluation methods at the social level in existing research. It is suitable for different regions and groups and has good universality and promotion value.

[0111] Example 1

[0112] To further illustrate the social benefit assessment method for implementing air quality standards of the present invention, a certain area is taken as an example to describe in detail the process of the social benefit assessment method for implementing air quality standards for the public:

[0113] From cognition, emotion and behavior Figure 3The secondary indicators covering public cognition, public behavior and public satisfaction were designed at each level. (1) Public cognition: Based on sociology and psychology, the three-level indicators of downward perception, atmospheric science knowledge and behavioral intention were designed; (2) Public satisfaction: Relying on the three senses of blue sky, sense of gain is the foundation, sense of security is the guarantee, and sense of happiness is the core; (3) Public behavior: Public behavior is divided into two categories: risk avoidance behavior and environmentally friendly behavior, such as Figure 2 shown.

[0114] Determine the indicator weights. Use the expert consultation method (Delphi method) combined with the hierarchical analysis method to obtain a judgment matrix with a 1-9 scale to determine the indicator weights. The experts consulted should include experts in the fields of environment, social psychology, social behavior, public health, etc. Combining the weights of the two, a weighted comprehensive weight can be obtained. Table 1 below is the evaluation criteria, and Tables 2 and 3 below are the public cognition judgment matrix and the social benefit judgment matrix respectively.

[0115] Table 1. Evaluation criteria: (1-9 scale)

[0116]

[0117]

[0118] Table 2. Public perception judgment matrix

[0119]

[0120] Table 3. Social benefit judgment matrix

[0121] Public perception Public behavior Public satisfaction Public perception 1 Public behavior 1 Public satisfaction 1

[0122] According to the survey statistics, the results of the expert consultation judgment matrix are as follows:

[0123] Table 4. Results of expert consultation judgment matrix

[0124]

[0125] Calculate the maximum eigenvalue λ of the judgment matrix max And the corresponding eigenvector. After normalization, the weight vector is obtained:

[0126] W=[0.15,0.10,0.20,0.25,0.10,0.20]

[0127] The consistency index was calculated, CI = 0.04, CR = 0.035 < 0.1, and the judgment matrix passed the consistency test.

[0128] The data on perception level, atmospheric science knowledge and behavioral intentions are obtained through questionnaire surveys to assess public awareness. The questionnaire (using the questionnaire table above) needs to be analyzed separately according to conditions such as age group, income and region, and other distribution platforms such as WJX can be used.

[0129] Step 104: Data analysis. Use the 1-9 scale method and the analytic hierarchy process (AHP) to construct a judgment matrix, calculate the relative importance of each indicator, and generate a weight value. Based on the determined indicator weights, perform weighted calculations on each indicator of each questionnaire to obtain the comprehensive scores of different questionnaires. The average score of the perceived degree is 3.8, standard deviation: 0.7; the average score of the health impact satisfaction is 4.2, standard deviation: 0.5. Calculate the comprehensive index based on the weights:

[0130]

[0131] The index values ​​of the study area after standardization are X = [0.8, 0.7, 0.6, 0.9, 0.7, 0.8], and the comprehensive index is calculated as: EI = 0.15 × 0.8 + 0.10 × 0.7 + 0.20 × 0.6 + 0.25 × 0.9 + 0.10 × 0.7 + 0.20 × 0.8 = 0.78.

[0132] Result Grading

[0133] The scoring results of all questionnaires were combined to analyze the public's responses in the three dimensions of cognition, behavior and emotion, providing a quantitative basis for the evaluation of social benefits. According to the EI value, the social benefits of the region were evaluated as "good" (0.6≤EI<0.8).

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or some technical features can be replaced by equivalents without departing from the spirit of the technical solution of the present invention, which should be included in the scope of the technical solution for protection of the present invention.

Claims

1. A method for evaluating the social benefits of implementing air quality standards for the public, characterized by: The steps include: Step S1, construct a social benefit evaluation index system, including three dimensions: cognition, satisfaction, and behavior, and design a questionnaire to quantify the indicators through the Likert five-level scoring method. The indicators, data sources, and quantification methods are as follows: Step S2, determine the indicator weights, use expert consultation method combined with analytic hierarchy process to obtain a judgment matrix with a 1-9 scale to determine the indicator weights, including: Step S201, obtaining a judgment matrix, including organizing no less than 15 experts to conduct multiple rounds of anonymous questionnaire surveys, and using the 1-9 scaling method to construct a judgment matrix, comparing each pair of indicators, and each expert independently completing the comparison of the importance of indicators to construct a pairwise comparison judgment matrix, summarizing the matrices of all experts, calculating the mean of each pair of indicators, returning the summary results to the expert group, anonymously feedbacking the group's opinions, and requiring the adjustment of the scores until consensus is reached; Step S202, weight calculation, including calculating the maximum eigenvalue λ of the judgment matrix max The eigenvector W = [w1,w2,…,w n ], and use the standardization method to normalize the feature vector: Calculate the consistency index CI: CR=CI / RI Among them, RI is the random consistency index, which is determined according to the matrix dimension n in combination with the following table. If CR<0.1, the matrix consistency is good, otherwise it needs to be corrected; The verified feature vector is the final weight; Step S3, collecting data, obtaining data on the three dimensions of cognition, satisfaction, and behavior through questionnaire surveys to assess public cognition, or obtaining data through real-time monitoring, performing Poisson regression analysis to exclude other influencing factors, and quantifying the impact of air pollution changes on public cognition or behavior; Step S4, analyzing the data, describing the statistical analysis, by calculating the mean, standard deviation and distribution, analyzing the correlation between different indicators through the Pearson correlation coefficient or the Spearman rank correlation coefficient, establishing a multiple linear regression model or a structural equation model, describing the comprehensive impact of each indicator on the public attitude, including weighted calculation of each indicator of each data collected in step S3 based on the determined indicator weights, and obtaining the comprehensive score of different collected data, wherein data annotation and comprehensive scoring include: The scores of each indicator are standardized to the interval [0,1]: X j =(X-min(X)) / (max(X)-min(X)) Calculate the comprehensive index for each region: Among them, EI is the comprehensive evaluation index, W j is the weight of the jth indicator, X j is the standardized score of the jth indicator; Step S5, result grading, evaluation output, forming an indicator weight table and social benefit score, and dividing the social benefit into five levels according to the comprehensive index: excellent: EI ≥ 0.8; good: 0.6 ≤ EI < 0.8; medium: 0.4 ≤ EI < 0.6; poor: 0.2 ≤ EI < 0.4; extremely poor: EI < 0.

2.

2. The method for evaluating the social benefits of implementing air quality standards according to claim 1, characterized in that: The experts consulted in the expert consultation method should include experts in the fields of environment, social psychology, social behavior, and public health.

3. The method for evaluating the social benefits of implementing air quality standards according to claim 1 is characterized in that: The meaning of the scale in the 1-9 scale is defined as follows: 1: The two indicators are equally important; 3: One side is slightly more important; 5: One side is important; 7: One party is extremely important; 9: One party is absolutely important; 2, 4, 6, and 8 are intermediate values ​​between the two; If the importance of indicator i to j is a ij ,but 4. The method for evaluating the social benefits of implementing air quality standards according to claim 1 is characterized in that: In step S201, 2 to 3 rounds are usually performed until the judgment matrix converges, and the mean values ​​of all expert scores are summarized to form a final judgment matrix.

5. The method for evaluating the social benefits of implementing air quality standards according to claim 1 is characterized by: In step S4, the data is cleaned during data analysis, and the cleaning rules include: If a small amount of data is missing (<5%), use the mean or median to fill in the missing data; if the proportion of missing values ​​is high (>20%), delete the questionnaire; check whether individual respondents have logical errors, and convert the text options in the questionnaire into numerical scores.

6. The method for evaluating the social benefits of implementing air quality standards according to claim 1, characterized in that: In step S3, the steps of obtaining data on the three dimensions of cognition, satisfaction, and behavior through questionnaire survey to evaluate public cognition include: Design questions based on the three dimensions of public cognition, behavior and emotion; The sample selection adopted stratified random sampling method to cover different age, income, regional and occupational groups, and the sample size was greater than 500 people.

7. The method for evaluating the social benefits of implementing air quality standards according to claim 1, characterized in that: In step S3, real-time monitoring is used to obtain data, and Poisson regression analysis is performed to exclude other influencing factors. The steps of quantifying the impact of air pollution changes on public cognition or behavior include: The polynomial formula for air quality and public perception or behavior is fitted, and the Poisson regression is as follows: Among them, λ k is the average rate of events occurring per unit time or per unit space, and k is the number of events occurring.

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