Ambient air bearing capacity quantitative evaluation method

Abstract

The invention discloses an ambient air bearing capacity quantitative evaluation method, which fully considers the importance degree of different atmospheric pollutants on air quality evaluation and the seasonal characteristics of primary pollutants, determines the weights of different evaluation index factors, highlights the difference of the evaluation index factors, and constructs an ambient air bearing capacity index (ACCI). The environment air bearing capacity index can be used for daily, monthly, quarterly and annual environment air bearing capacity change trend evaluation and situation research and judgment work, in the air quality improvement condition evaluation process, the influence of subjective factors of evaluation personnel is avoided, the quality of environment meteorological conditions can be reflected in time, and the evaluation efficiency is improved. And a theoretical basis is provided for formulating effective pollution control measures and evaluating climate and weather influences. The problems that the change degree of the environmental meteorological condition cannot be rapidly and visually evaluated and the comprehensive influence of the change of the environmental meteorological condition on the environmental air bearing capacity cannot be visually reflected in the prior art are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of atmospheric environmental condition evaluation, and in particular relates to a method for quantitatively evaluating the carrying capacity of ambient air. Background Art

[0002] The carrying capacity of ambient air refers to the maximum capacity of the ambient air system to withstand the emission of atmospheric pollutants from human socio-economic activities within a certain area, that is, the maximum supporting capacity of ambient air for the emission of atmospheric pollutants from human socio-economic development. Changes in climate and meteorological conditions have many impacts on the carrying capacity of ambient air, both positive and negative. For example, rising temperatures will cause pollutants in the atmosphere to react more actively, accelerate atmospheric photochemical reactions, and thus reduce the carrying capacity of ambient air. High temperatures can promote the formation of ozone (O3). Under calm weather conditions, atmospheric pollutants tend to accumulate near the ground, leading to deterioration of air quality, while under strong wind conditions, atmospheric pollutants can be rapidly diluted and transported, which is conducive to improving air quality. Precipitation can effectively remove pollutants from the air, especially by reducing the concentration of particulate matter in the air through the wet deposition process. It can also improve air quality by lowering the temperature and inhibiting the generation of O3. However, when the precipitation intensity is low, the relative humidity of the atmosphere is high, accompanied by light winds, low pressure, inversion, and calm weather, which may promote the formation of fine particulate matter (PM 2.5 ) The formation of secondary components leads to PM 2.5 Increased concentration.

[0003] In addition, the assessment and improvement of ambient air quality has always been an important topic of environmental protection. Traditional air quality evaluation methods mainly rely on direct monitoring of atmospheric pollutant concentrations, but this method cannot fully consider the comprehensive impact of changes in ambient meteorological conditions, and it is difficult to quantify and dynamically reflect the specific impact of ambient meteorological conditions on air quality.

[0004] Therefore, scientifically assessing changes in environmental meteorological conditions and analyzing their possible impact on the air quality situation can provide scientific support for atmospheric environmental management. Summary of the invention

[0005] The purpose of the present invention is to provide a method for quantitatively evaluating the ambient air carrying capacity in response to the deficiencies of the prior art, so as to solve the problem that the prior art cannot quickly and intuitively evaluate the degree of change of ambient meteorological conditions, and cannot intuitively reflect the comprehensive impact of changes in ambient meteorological conditions on the ambient air carrying capacity, make up for the lack of an evaluation system for the degree of ambient meteorological impact in the prior art, and achieve accurate and rapid quantification of the comprehensive impact of environmental system changes (such as fluctuations in climate and meteorological conditions) on the ambient air carrying capacity during the study period, and quantitatively reflect the relative good or bad of the ambient meteorological conditions that cause improvement or deterioration of air quality.

[0006] The present invention fully considers the importance of different atmospheric pollutants to air quality evaluation and the seasonal characteristics of primary pollutants, determines the weights of different evaluation index factors, highlights the differences of various evaluation index factors, and constructs an ambient air carrying capacity index (ACCI). The ambient air carrying capacity index can be used for daily, monthly, quarterly and annual ambient air carrying capacity change trend evaluation and situation analysis, and in the process of air quality improvement evaluation, it avoids the influence of subjective factors of evaluators, can timely reflect the pros and cons of environmental meteorological conditions, intuitively reflect the good or bad meteorological conditions that cause air quality improvement or deterioration, and provide a theoretical basis for formulating effective pollution control measures and evaluating climate and meteorological impacts.

[0007] The method for evaluating the carrying capacity of ambient air of the present invention comprises the following steps: (1) The scenario analysis method is used, that is, the anthropogenic air pollutant emission inventory is fixedly used, and the meteorological fields of the baseline period and the target period (i.e., the period for comparative analysis with the baseline period) are used respectively. The natural source emission inventory of the corresponding period is generated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN) natural source emission model. The anthropogenic air pollutant emission inventory, the natural source emission inventory, and the meteorological field are input into the regional three-dimensional air quality model and run. The regional three-dimensional air quality model is used to simulate the air quality of the study area during the study period, and the hourly air quality simulation data of each grid point in the study area during the study period are output to obtain the daily simulated concentration of air pollutants in the corresponding period ( C ); (2) With reference to the calculation method of China's Air Quality Index and Air Quality Sub-Index (see the Technical Provisions of the People's Republic of China on Ambient Air Quality Index (AQI) (Trial) (HJ 633-2012), available at https: / / www.mee.gov.cn / ywgz / fgbz / bz / bzwb / jcffbz / 201203 / W020120410332725219541.pdf), the ambient air carrying capacity evaluation index factors corresponding to the daily pollutant simulation concentration values ​​were calculated respectively ( FAQI );

[0008] Where: FAQ p ——Ambient air carrying capacity evaluation index factor of pollutant item p; C p ——Simulated concentration value of pollutant item p; BPHi ——With C p The higher value of similar pollutant concentration limit; BP Lo ——With C p The lower value of similar pollutant concentration limits; IAQI Hi ——With BP Hi The corresponding air quality index; IAQI Lo ——With BP Lo The corresponding air quality index.

[0009] In the above formula, based on the simulated concentration value of atmospheric pollutants, the BP is obtained by querying the National Environmental Protection Standard of the People's Republic of China "Technical Provisions on Ambient Air Quality Index (AQI) (Trial)" (HJ 633-2012) (Table 1 "Air Quality Sub-Index and Corresponding Pollutant Item Concentration Limits" Hi and BP Lo ; and query the corresponding IAQI in Table 1 Hi and IAQI Lo .

[0010] Establishing the Ambient Air Carrying Capacity Index (ACCI): Introducing each ambient air carrying capacity evaluation index factor ( FAQI ) weight γ, and establish the following ambient air carrying capacity index calculation model;

[0011] Where: ACCI – ambient air carrying capacity index; FAQI p —— Pollutant Project p Evaluation index factors of ambient air carrying capacity; γ p —— Pollutant Project p The weight of the environmental air carrying capacity evaluation index factor (%); N——the number of pollutant items selected; e ——A constant of nature or Euler's number, an infinite non-repeating decimal, approximately 2.71828.

[0012] (4) Evaluation of ambient air carrying capacity: The calculated ACCI value of 50 is used as the dividing point (prosperity and decline line) of the ambient air carrying capacity. That is, when the ACCI value is greater than 50, it indicates that the ambient air carrying capacity is good; when the ACCI value is less than 50, it indicates that the ambient air carrying capacity is poor; when the ACCI value year-on-year change rate is greater than 0, it indicates that the ambient meteorological conditions are favorable year-on-year and the ambient air carrying capacity has improved. Among them, when 0<year-on-year change rate ≤ 10%, the ambient air carrying capacity is slightly better year-on-year; 10%<year-on-year change rate ≤ 20%, the ambient air carrying capacity is relatively good year-on-year; the year-on-year change rate > 20%, the ambient air carrying capacity is obviously favorable year-on-year. When the ACCI value year-on-year change rate is less than 0, it indicates that the ambient meteorological conditions are unfavorable year-on-year and the ambient air carrying capacity has deteriorated. Among them, when 0>year-on-year change rate ≥ -10%, the ambient air carrying capacity is slightly worse year-on-year; -10%>year-on-year change rate ≥ -20%, the ambient air carrying capacity is relatively worse year-on-year; the year-on-year change rate < -20%, the ambient air carrying capacity is obviously unfavorable year-on-year.

[0013] The formula for calculating the year-on-year change rate of ACCI value is as follows:

[0014] Where: ε——ACCI value year-on-year change rate (%); ACCI 0 ——ACCI value of the reference period; ACCI 1 ——ACCI value during the target period.

[0015] Table 1 Classification of ambient air carrying capacity index

[0016] In the above method, due to the high annual average concentration of O3 in urban areas in China and the trend of fluctuation and increase, the background value of atmospheric O3 concentration is generally far more than 100 μg / m 3 Therefore, in order to more reasonably and accurately reflect the dynamic changes in the urban ambient air quality carrying capacity, the air quality sub-index (IAQI) corresponding to the maximum 8-hour sliding average concentration of O3 was adjusted based on the data in Table 1 of the National Environmental Protection Standard of the People's Republic of China "Technical Provisions on Ambient Air Quality Index (AQI) (Trial)" (HJ 633-2012), and the maximum 8-hour sliding average concentration of O3 was set at 160 μg / m 3 , 215 μg / m 3 , 265 μg / m 3 , 800 μg / m 3 , the corresponding IAQI Hi 50, 100, 150, 200, corresponding to IAQILo It is 0, 50, 100, 150.

[0017] In the above method, further, the pollutant item p Including PM 2.5 、O3、PM 10 , NO2, SO2 and CO, etc.

[0018] In the above method, further, considering the recent years, the national PM 10 , NO2, SO2 and CO have basically achieved stable compliance; PM 2.5 It is a binding indicator in ecological environment protection. Some cities are still far from reaching the standard. O3 pollution has gradually become the primary pollutant causing air quality to exceed the standard (especially in spring, summer and autumn), which has an impact on the number of good days. Therefore, PM 2.5 and O3, and other pollutants (such as PM 10 , SO2, NO2, CO), and the weight of the evaluation index factor is determined according to the impact of the pollutant on air quality. 2.5 The weights of differentiation from O3 are 50%~90% and 10%~50% respectively, and it is ensured that in each air quality improvement evaluation, the sum of the weights of the above evaluation factors used meets 100%.

[0019] In the above method, further, when other pollutants meet the standards, PM 2.5 The weights of differentiation from O3 are as follows γ PM2.5 = 90%, γ O3 = 10% Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention aims to solve the problem that the existing technology cannot quickly and intuitively evaluate the degree of change of environmental meteorological conditions and their comprehensive impact on the environmental air carrying capacity. Through a scenario analysis method based on a regional three-dimensional air quality model, the simulated concentration of atmospheric pollutants is calculated using the regional three-dimensional air quality model, and the environmental air carrying capacity index is calculated to quantitatively evaluate the impact of environmental system changes (such as fluctuations in climate and meteorological conditions) on the environmental air carrying capacity, which makes up for the lack of the existing technology in the environmental meteorological impact assessment system.

[0020] 2. The method of the present invention takes into account the importance and seasonal characteristics of different atmospheric pollutants to air quality, determines the weights of evaluation indicators, and constructs the ambient air carrying capacity index ACCI. ACCI can be used to evaluate the trend of ambient air carrying capacity changes on a daily, monthly, quarterly and annual basis, avoid the influence of subjective factors, and promptly reflect the impact of ambient meteorological conditions on air quality, providing a theoretical basis for formulating atmospheric pollution control measures and evaluating climate and meteorological impacts. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Ambient air carrying capacity index of a province from January to June 2024; Figure 2 Ambient air carrying capacity index of a province from 2020 to 2023. DETAILED DESCRIPTION

[0022] The present invention is further described in detail and completely by specific examples. It is necessary to point out that the following examples are only used to further illustrate the present invention and cannot be understood as limiting the scope of protection of the present invention. Those skilled in the art can make some non-essential improvements and adjustments to the present invention according to the above invention content and implement them specifically, which still falls within the scope of protection of the invention.

[0023] Example 1 In this embodiment, the changes in the ambient air carrying capacity of a province from January to June 2024 and from January to June 2023 are selected as the embodiment data, and the method is as follows: (1) The scenario analysis method is used, that is, the anthropogenic air pollutant emission inventory is used fixedly, and the mesoscale meteorological model is run to simulate the meteorological field data of the study area during the study period, and the hourly meteorological field simulation data of the baseline period and the target period (i.e., the period for comparative analysis with the baseline period) of the study area are output. The natural source emission inventory of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) natural source emission model is used to generate the natural source emission inventory of the corresponding period. The anthropogenic air pollutant emission inventory, the natural source emission inventory, and the meteorological field are input and run into the regional three-dimensional air quality model. The regional three-dimensional air quality model is used to simulate the air quality of the study area during the study period, and the hourly air quality simulation data of each grid point in the study area during the study period are output to obtain the PM2.5 in a certain province from January to June 2024 and from January to June 2023. 2.5 and O3 simulated concentration values, as shown in Table 2.

[0024] Table 2 PM in a province from January to June 2024 and from January to June 2023 2.5 and O3 simulated concentration values

[0025] (2) Look up Table 1 "Air quality sub-index and corresponding pollutant concentration limits" in the National Environmental Protection Standard of the People's Republic of China "Technical Provisions for Ambient Air Quality Index (AQI) (Trial)" (HJ 633-2012), and use the given air quality sub-index and corresponding pollutant concentration limits (as shown in Table 3) to calculate the PM2.5 levels for January to June 2024 and January to June 2023. 2.5 The ambient air carrying capacity evaluation index factor corresponding to the O3 simulation concentration value ( FAQI ), as shown in Table 4.

[0026]

[0027] Where: FAQ p ——Ambient air carrying capacity evaluation index factor of pollutant item p; C p ——Simulated concentration value of pollutant item p; BP Hi ——With C p The higher value of similar pollutant concentration limit; BP Lo ——With C p The lower value of similar pollutant concentration limits; IAQI Hi ——With BP Hi The corresponding air quality index; IAQI Lo ——With BP Lo The corresponding air quality index.

[0028] The method for determining each quantity in the formula is, for example, PM in January 2024 2.5 The simulated concentration value of BP is 51.3. According to Table 3 below, Hi 75, BP Lo IAQI is 35 Hi IAQI is 100 Lo is 50; the simulated concentration of O3 in May 2024 is 152.4, then according to Table 3 below, BP Hi 160 BP Lo IAQI Hi IAQI is 50 Lo is 0.

[0029] Table 3 Air quality sub-indexes used and corresponding pollutant concentration limits

[0030] In order to more reasonably and accurately reflect the dynamic changes in the ambient air quality carrying capacity, the air quality sub-index (IAQI) corresponding to the maximum 8-hour sliding average concentration of O3 was adjusted based on the data in Table 1 of the National Environmental Protection Standard of the People's Republic of China "Technical Provisions on Ambient Air Quality Index (AQI) (Trial)" (HJ 633-2012). Table 3 shows the adjusted data.

[0031] Table 4 Evaluation index factors of ambient air carrying capacity of a province from January to June 2024 and from January to June 2023

[0032] Based on the ambient air carrying capacity index calculation model, the ambient air carrying capacity index (ACCI) is calculated, as shown in Table 5.

[0033] Table 5 Ambient Air Carrying Capacity Index (ACCI) of a province from January to June 2024 and from January to June 2023

[0034] Evaluation of ambient air carrying capacity: From January to June 2024, the average ACCI value of a certain province was 52.6, which was 2.6 higher than the prosperity line, and the ambient air carrying capacity was good; ACCI increased by 20.9% year-on-year, indicating that the ambient air carrying capacity was relatively good compared with the same period last year. In the first quarter (January to March), the ACCI value was 43.9, which was 6.1 lower than the prosperity line, and the ambient air carrying capacity was low; but ACCI increased by 38.1% year-on-year, indicating that the ambient air carrying capacity was significantly more favorable than the same period last year. In the second quarter (April to June), the ACCI value was 61.1, which was 11.1 higher than the prosperity line, and the ambient air carrying capacity was relatively high; ACCI increased by 8.5% year-on-year, indicating that the ambient air carrying capacity was more favorable than the same period last year.

[0035] According to the environmental meteorological observation results of the province from January to June 2024, the number of high temperature days in the first half of the year is relatively small, the rainfall increases (January and April are 51% and 80% higher than the same period of previous years, the average number of precipitation days from May to June is higher, the number of rainstorm stations is higher, and the convective weather in June has increased significantly), and the solar radiation decreases (the average sunshine hours in June are 39% less, the least in the same period since 1961). The environmental meteorological conditions are generally conducive to improving air quality. The environmental air carrying capacity index of the province is 19.8% better than the same period in 2023. The PM 2.5 The concentration dropped by 6% compared with the same period in 2023.

[0036] It can be seen that the results of the method of the present invention can reflect the changes in environmental meteorological conditions in the first half of the year, timely reflect the pros and cons of environmental meteorological conditions, intuitively reflect the good or bad meteorological conditions that cause air quality improvement or deterioration, and indicate the possible impact of climate and meteorological conditions on changes in environmental air quality, with certain accuracy and rationality.

[0037] Example 2 In this embodiment, the changes in the ambient air carrying capacity of a province from 2020 to 2023 are selected as the embodiment data, and the method is as follows: (1) Using a fixed anthropogenic air pollutant emission inventory, the meteorological fields of the baseline period and the target period are used to generate the natural source emission inventory for the corresponding period, and then drive the regional three-dimensional air quality model to obtain the PM2.5 emission of a province from 2020 to 2023. 2.5 and O3 simulated concentration values, as shown in Table 6.

[0038] Table 6 PM in a province from 2020 to 2023 2.5 and O3 simulated concentration values

[0039] (2) Look up Table 1 "Air quality sub-index and corresponding pollutant concentration limits" in the National Environmental Protection Standard of the People's Republic of China "Technical Provisions for Ambient Air Quality Index (AQI) (Trial)" (HJ 633-2012), and use the given air quality sub-index and corresponding pollutant concentration limits (as shown in Table 7) to calculate the PM2.5 levels from 2020 to 2023. 2.5 The ambient air carrying capacity evaluation index factor corresponding to the O3 simulation concentration value ( FAQI ), as shown in Table 8.

[0040] Table 7 The air quality sub-indexes used and the corresponding pollutant concentration limits

[0041] Table 8 Evaluation index factors of ambient air carrying capacity of a province from 2020 to 2023

[0042] Based on the ambient air carrying capacity index calculation model, the ambient air carrying capacity index (ACCI) is calculated, as shown in Table 9.

[0043] Table 9 Ambient Air Carrying Capacity Index (ACCI) of a province from 2020 to 2023

[0044] Evaluation of ambient air carrying capacity: From 2020 to 2023, the ACCI value of a certain province fluctuated, and the annual average value was higher than the boom-bust line, indicating that the ambient air carrying capacity was good; 2020 was the year with the best ambient air carrying capacity in these four years, 2022 was slightly worse than 2020, and 2023 was the worst. In addition, in 2021, ACCI decreased by 2.4% year-on-year, indicating that the ambient air carrying capacity was relatively worse than the same period last year; in 2022, ACCI increased by 2.3% year-on-year, indicating that the ambient air carrying capacity was relatively better than the same period last year; in 2023, ACCI decreased by 4.1% year-on-year, indicating that the ambient air carrying capacity was relatively worse than the same period last year.

[0045] According to the province's environmental meteorological observations from 2020 to 2023, the average temperature has been rising year by year, the average precipitation in the province has not changed significantly, and the annual average relative humidity and annual average wind speed have been decreasing, causing the province's environmental air carrying capacity index to fluctuate downward; in addition, 2023 was 0.9℃ higher than normal, setting a new record since 1961, breaking the 2022 historical record, and the average precipitation was 12% lower, ranking sixth lowest in history. The overall environmental meteorological conditions are not conducive to improving air quality. The province's environmental air carrying capacity index has decreased by 4.1% year-on-year, and the province's PM 2.5 The concentration increased by about 5% compared with the same period in 2022.

[0046] It can be seen that the results of the method of the present invention can reflect the changes in environmental meteorological conditions from 2020 to 2023, indicating the possible impact of climate and meteorological conditions on changes in ambient air quality, and have certain accuracy and rationality.

Claims

1. A method for evaluating the carrying capacity of ambient air, characterized in that: The following steps are involved: (1) Using the scenario analysis method, the anthropogenic air pollutant emission inventory is fixed, the meteorological fields of the baseline period and the target period are used respectively, and the MEGAN natural source emission model is used to generate the natural source emission inventory of the corresponding period; The man-made source atmospheric pollutant emission inventory, natural source emission inventory, and meteorological field are input into the regional three-dimensional air quality model and run. The regional three-dimensional air quality model is used to simulate the air quality of the study area during the study period, and the hourly air quality simulation data of each grid point in the study area during the study period are output to obtain the daily simulated atmospheric pollutant concentrations for the corresponding period. C ; (2) According to the calculation method of China Air Quality Index and Air Quality Sub-Index, calculate the environmental air carrying capacity evaluation index factors corresponding to the daily atmospheric pollutant simulation concentration values. FAQI ; , Where: FAQ p ——Ambient air carrying capacity evaluation index factor of pollutant item p; C p ——Simulated concentration value of pollutant item p; BP Hi ——With C p The higher value of similar pollutant concentration limit; BP Lo ——With C p The lower value of similar pollutant concentration limits; IAQI Hi ——With BP Hi The corresponding air quality index; IAQI Lo ——With BP Lo The corresponding air quality index; In the formula, based on the simulated concentration value of atmospheric pollutants, the BP is obtained by querying the relevant air quality sub-index and the corresponding pollutant item concentration limit in the industry technical data. Hi and BP Lo , and the corresponding IAQI Hi and IAQI Lo; (3) Establishing the Ambient Air Carrying Capacity Index (ACCI): Introducing each ambient air carrying capacity evaluation index factor FAQI The weight γ is used to establish the following ambient air carrying capacity index calculation model: , Where: ACCI – ambient air carrying capacity index; FAQI p —— Pollutant Project p Evaluation index factors of ambient air carrying capacity; γ p —— Pollutant Project p The weight of the environmental air carrying capacity evaluation index factors; N——the number of pollutant items selected; e — constant of nature or Euler number; (4) Evaluation of ambient air carrying capacity: The calculated ACCI value of 50 is used as the dividing point between the ambient air carrying capacity and the ambient air carrying capacity. When the ACCI value is greater than 50, the ambient air carrying capacity is judged to be good. When the ACCI value is less than 50, it is judged that the ambient air carrying capacity is poor; When the year-on-year change rate of the ACCI value is greater than 0, it is determined that the environmental meteorological conditions are favorable year-on-year, and the environmental air carrying capacity has improved; among them, when 0<year-on-year change rate≤10%, the environmental air carrying capacity is slightly better year-on-year; 10%<year-on-year change rate≤20%, the environmental air carrying capacity is relatively good year-on-year; the year-on-year change rate>20%, the environmental air carrying capacity is obviously favorable year-on-year; when the year-on-year change rate of the ACCI value is less than 0, it is determined that the environmental meteorological conditions are unfavorable year-on-year, and the environmental air carrying capacity has deteriorated. Among them, when 0>year-on-year change rate≥-10%, the environmental air carrying capacity is slightly worse year-on-year; -10%>year-on-year change rate≥-20%, the environmental air carrying capacity is relatively worse year-on-year; the year-on-year change rate<-20%, the environmental air carrying capacity is obviously unfavorable year-on-year; The formula for calculating the year-on-year change rate of ACCI value is as follows: , Where: ε——ACCI value year-on-year change rate (%); ACCI 0 ——ACCI value of the reference period; ACCI 1 ——ACCI value during the target period.

2. The method according to claim 1, characterized in that: Step (2) Based on the relevant air quality sub-index and the corresponding pollutant item concentration limit values ​​queried, the air quality sub-index (IAQI) corresponding to the maximum 8-hour sliding average concentration of O3 is adjusted to set the maximum 8-hour sliding average concentration of O3 to 160 μg / m 3 , 215 μg / m 3 , 265 μg / m 3 , 800 μg / m 3 , the corresponding IAQI Hi 50, 100, 150, 200, corresponding to IAQI Lo It is 0, 50, 100, 150.

3. The method according to claim 1, characterized in that: The pollutant items p For PM 2.5 、O3、PM 10 , at least one of NO2, SO2 and CO.

4. The method according to claim 1, characterized in that: According to the impact of current atmospheric pollutants on air quality, PM 2.5 The weights of O2 and O3 are relatively high, and the weights of other pollutant evaluation index factors are determined according to the impact of the pollutant on air quality.

5. The method according to claim 4, characterized in that: Set PM 2.5 The weights of differentiation from O3 are 50%~90% and 10%~50% respectively, and it is ensured that in each air quality improvement evaluation, the sum of the weights of each evaluation factor used meets 100%.

6. The method according to claim 5, characterized in that: When other pollutants meet the standards, PM 2.5 The weights of differentiation from O3 are as follows: c PM2.5 = 90%, c O3 = 10%.

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