Fine particulate matter and ozone regulation and control method and system, storage medium and electronic equipment

Abstract

The invention relates to a fine particulate matter and ozone regulation and control method and system, a storage medium and electronic equipment. The fine particulate matter and ozone regulation and control method comprises the steps that precursor data, maximum emission reduction potential and emission reduction policies of different emission reduction regions and ozone concentration data and fine particulate matter concentration of a receptor region are collected; non-linear responses between the precursors of different emission reduction areas and the ozone concentration of the acceptor area are confirmed; non-linear responses between the precursors of different emission reduction areas and the fine particulate matter concentration of the acceptor area are confirmed; determining the minimum emission reduction of the precursors in different emission reduction areas; confirming constraint conditions of precursors of different emission reduction regions; confirming target constraints of fine particulate matter concentration and ozone concentration in different receptor regions; and calculating the emission reduction proportions of the precursors of all the emission reduction areas. According to the method, the optimal emission reduction scheme of the precursor of the emission reduction area is solved by introducing the joint response relation between PM2.5 and O3 and the precursor thereof and different constraint conditions of different emission reduction cities.

Description

Technical Field

[0001] The present application relates to the field of environmental control technology, and in particular to a method, system, storage medium and electronic device for controlling fine particulate matter and ozone. Background Art

[0002] At present, China has made phased progress in air pollution prevention and control. 2.5 ) concentrations continued to decline. However, many typical pollution areas have not yet achieved PM 2.5 The annual average target is 35μg / m3. At the same time, atmospheric ozone (O3) pollution is showing a rapid upward trend, especially in summer, when ozone pollution occurs frequently. PM 2.5 and O3 have become important control indicators for the continuous improvement of my country's air quality.

[0003] PM 2.5 Essentially the same source as O3, they are two manifestations of complex air pollution in different seasons. If properly planned and managed, coordinated emission reduction can achieve a double reduction. 2.5 and O3 pollution control into the national air pollution control system, but currently there is still no national level to determine PM 2.5 and ozone precursors synergistic control strategy, and can scientifically guide regional PM 2.5 There is also limited research on collaborative control and continuous improvement with O3. Summary of the invention

[0004] In view of the above problems, the present application provides a method, system, storage medium and electronic device for controlling fine particulate matter and ozone, which solves the problem that the related technology lacks scientific guidance for regional PM2.5. 2.5 Collaborative control and continuous improvement related technical issues with O3.

[0005] In a first aspect, the present application provides a method for regulating fine particulate matter and ozone, the method comprising:

[0006] Collect data on precursors, maximum reduction potential and reduction policies in different emission reduction regions, as well as ozone concentration data and fine particulate matter concentrations in recipient regions;

[0007] Confirmation of nonlinear responses between precursors in different abatement regions and ozone concentrations in receptor regions;

[0008] Identify the nonlinear response between precursors in different abatement regions and fine particulate matter concentrations in recipient regions;

[0009] Identify the minimum emission reductions for precursors in different emission reduction areas;

[0010] Identify constraints on precursors in different abatement areas;

[0011] Identify target constraints for particulate matter and ozone concentrations in different receptor areas;

[0012] The emission reduction ratio of precursors in all emission reduction areas is calculated based on the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the recipient areas, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the recipient areas, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and ozone concentration in the different recipient areas.

[0013] In some embodiments, the identifying the nonlinear response between the precursors in different emission reduction regions and the ozone concentration in the receptor region comprises:

[0014] According to the formula:

[0015]

[0016] Confirmation of nonlinear responses between precursors and ozone concentrations in recipient regions at different emission reduction sites In the formula, i is the receptor area, j is the emission reduction area, is the change of O3 concentration, SA_O 3i,j represents the contribution of emission reduction region j to the O3 concentration of receptor region i in source apportionment; and Δ VOC are the percentage changes in NOx and VOCs emissions, respectively; and S VOC 1 are the primary sensitivity coefficients of NOx and VOCs respectively; and S VoC 2 are the secondary sensitivity coefficients of NOx and VOCs respectively; is the cross sensitivity coefficient between NOx and VOCs.

[0017] In some embodiments, the identifying a nonlinear response between the precursors in different emission reduction areas and the fine particulate matter concentration in the recipient area comprises:

[0018] According to the formula:

[0019] ΔPM 2.5i =ΔPPM i +ΔSNA i +ΔSOA i

[0020]

[0021]

[0022] ΔSOA i =G i (ΔNOx i ,ΔVOCs i )

[0023]

[0024] ΔSNA i =ΔPSO 4i +ΔPNO 3i +ΔPNH 4i

[0025] Identify nonlinear responses between precursors and fine particulate matter concentrations in recipient regions at different emission reduction sites Where ΔPM 2.5i represents PM in receptor region i 2.5 Concentration change, ΔPPM i , ΔSNA i , ΔSOA i Represents PM 2.5 Primary component PPM, secondary inorganic aerosol SNA, secondary organic aerosol SOA concentration change value; ΔPPM 2.5j , ΔSO 2j , ΔNO xj ,ΔNH 3j , ΔVOC sj Respectively represent the emission reduction ratios of PPM, SO2, NOx, NH3 and VOCs precursors in emission reduction area j; SA_SOA i,j ,SA_PPM i,j ,SA_PSO 4i,j ,SA_PNO 3i,j ,SA_PNH 4i,j They represent the transport contribution of emission reduction region j to SOA, PPM, sulfate, nitrate and ammonium in receptor region i in source apportionment.

[0026] In some embodiments, determining the minimum emission reduction of precursors in different emission reduction areas includes:

[0027] According to the formula:

[0028]

[0029] Confirm the minimum emission reduction of five types of precursors SO2, NOx, VOCs, PPM, and NH3 in different emission reduction areas. In the formula, EM PPMj , EM So2j , EM NOxj , EM VOCsj , EM NH3jRespectively represent the PPM, SO2, NOx, NH3 and VOCs emissions of emission reduction area j; ΔPPM 2.5j , ΔSO 2j , ΔNO xj ,ΔNH 3j , ΔVOC sj They represent the emission reduction proportions of PPM, SO2, NOx, NH3 and VOCs precursors in emission reduction area j respectively.

[0030] In some embodiments, the identifying the constraints of precursors in different emission reduction regions includes:

[0031] According to the relationship:

[0032] 0<ΔPPM 2.5j(policy) <ΔPPM 2.5j <ΔPPM 2.5j(max) <1

[0033] 0<ΔSO 2j(policy) <ΔSO 2j <ΔSO 2j(max) <1

[0034] 0<ΔNO xj(policy) <ΔNO xj <ΔNO xj(max) <1

[0035] 0<ΔVOC sj(policy) <ΔVOC sj <ΔVOC sj(max) <1

[0036] 0<ΔNH 3j(policy) <ΔNH 3j <ΔNH 3j(max) <1

[0037] Identify the constraints of precursors in different emission reduction areas. In the formula, the max and policy subscripts represent the maximum emission reduction potential and the minimum emission reduction ratio of future development plans and policies, respectively.

[0038] In some embodiments, determining target constraints for fine particulate matter concentration and ozone concentration in different receptor areas includes:

[0039] According to the relationship:

[0040] PM 2.5i -ΔPM 2.5i ≤goalPM 2.5i (i∈{1,2,…,10})

[0041] Identify target constraints for fine particulate matter concentrations in different receptor areas;

[0042] According to the relationship:

[0043] O 3i -ΔO 3i ≤goalO 3i (i∈{1,2,…,10})

[0044] Identify target constraints for ozone concentrations in different receptor regions;

[0045] In the formula, PM 2.5i ,O 3i is the PM of receptor region i in the base year 2.5 and current status of O3 concentration; goalPM 2.5i ,goalO 3i Respectively represent the improvement of PM in the receptor area i 2.5 and target concentration of O3; ΔPM 2.5i and ΔO 3i are PM in receptor area i 2.5 and O3 concentration changes.

[0046] In some embodiments, the calculation of the emission reduction ratio of the precursors in all emission reduction areas according to the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas, and the target constraints of the fine particulate matter concentration and the ozone concentration in the different receptor areas includes:

[0047] The emission reduction ratio of precursors in all emission reduction areas is calculated through machine learning or genetic algorithms according to the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and ozone concentration in the different receptor areas.

[0048] In a second aspect, a fine particulate matter and ozone control system is provided, the system comprising:

[0049] A collection unit for collecting precursor data, maximum emission reduction potential and emission reduction policies in different emission reduction areas, as well as ozone concentration data and fine particulate matter concentration in the receptor area;

[0050] The first confirmation unit is used to confirm the nonlinear response between the precursors in different emission reduction areas and the ozone concentration in the receptor area;

[0051] The second confirmation unit is used to confirm the nonlinear response between the precursors in different emission reduction areas and the fine particulate matter concentrations in the receptor area;

[0052] The third confirmation unit is used to confirm the minimum emission reduction of precursors in different emission reduction areas;

[0053] The fourth confirmation unit is used to confirm the constraints of precursors in different emission reduction areas;

[0054] The fifth confirmation unit is used to confirm the target constraints of fine particulate matter concentration and ozone concentration in different receptor areas;

[0055] A calculation unit is used to calculate the emission reduction ratio of the precursors in all emission reduction areas according to the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and the ozone concentration in the different receptor areas.

[0056] In a third aspect, a storage medium stores a computer program that can be executed by one or more processors and can be used to implement the method for controlling fine particulate matter and ozone as described in the first aspect above.

[0057] In a fourth aspect, an electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the memory and the processor are communicatively connected to each other, and when the computer program is executed by the processor, the method for controlling fine particulate matter and ozone as described in the first aspect above is executed.

[0058] The present application provides a method, system, storage medium and electronic device for regulating fine particulate matter and ozone, including: collecting precursor data, maximum emission reduction potential and emission reduction policies of different emission reduction areas, as well as ozone concentration data and fine particulate matter concentration of recipient areas; confirming the nonlinear response between precursors in different emission reduction areas and ozone concentration in recipient areas; confirming the nonlinear response between precursors in different emission reduction areas and fine particulate matter concentration in recipient areas; confirming the minimum emission reduction amount of precursors in different emission reduction areas; confirming the constraints of precursors in different emission reduction areas; confirming the target constraints of fine particulate matter concentration and ozone concentration in different recipient areas; calculating the emission reduction ratio of precursors in all emission reduction areas according to the nonlinear response between precursors in different emission reduction areas and ozone concentration in recipient areas, the nonlinear response between precursors in different emission reduction areas and fine particulate matter concentration in recipient areas, the minimum emission reduction amount of precursors in different emission reduction areas, the constraints of precursors in different emission reduction areas and the target constraints of fine particulate matter concentration and ozone concentration in different recipient areas. The present application introduces PM 2.5The joint response relationship between O3 and its precursors, as well as the different constraints of different emission reduction cities, are used to solve the optimal emission reduction plan for precursors in the emission reduction area. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0060] Figure 1 A schematic diagram of a process for controlling fine particulate matter and ozone provided in an embodiment of the present application;

[0061] Figure 2 A schematic diagram of the concentration comparison of the optimized emission reduction scheme for five types of precursors with 2022 as the base year and the optimization algorithm and scenario simulation provided in the embodiments of the present application;

[0062] Figure 3 A schematic diagram of the structure of a fine particulate matter and ozone control system provided in an embodiment of the present application;

[0063] Figure 4 A connection block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] The following will describe the implementation methods of the present application in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present application applies technical means to solve technical problems and achieve corresponding technical effects can be fully understood and implemented accordingly. The embodiments of the present application and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present application.

[0065] From the background technology, we know that although my country has already 2.5 and O3 pollution control into the national air pollution control system, but currently there is still no national level to determine PM 2.5 and ozone precursors synergistic control strategy, and can scientifically guide regional PM 2.5 There is also limited research on collaborative control and continuous improvement with O3.

[0066] In view of this, the present application provides a method, system, storage medium and electronic device for controlling fine particulate matter and ozone, which solves the problem that the related technology lacks the ability to scientifically guide regional PM 2.5 Collaborative control and continuous improvement related technical issues with O3.

[0067] Embodiment 1

[0068] Figure 1 A schematic diagram of a process for controlling fine particulate matter and ozone provided in an embodiment of the present application, such as Figure 1 As shown, the method includes:

[0069] S101. Collect precursor data, maximum emission reduction potential and emission reduction policies in different emission reduction areas, as well as ozone concentration data and fine particulate matter concentration in the recipient areas;

[0070] S102. Confirm the nonlinear response between precursors in different emission reduction areas and ozone concentrations in the receptor area;

[0071] S103. Confirm the nonlinear response between the concentration of fine particulate matter in the precursor and receptor areas in different emission reduction areas;

[0072] S104. Confirm the minimum emission reduction of precursors in different emission reduction areas;

[0073] S105. Confirm the constraints on precursors in different emission reduction areas;

[0074] S106. Confirm the target constraints for fine particulate matter concentration and ozone concentration in different receptor areas;

[0075] S107. Calculate the emission reduction ratio of precursors in all emission reduction areas based on the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and ozone concentration in the different receptor areas.

[0076] It should be noted that this method is based on PM 2.5 With O3 coordinated control as the core goal, comprehensive consideration of regional transmission contribution, emissions, response relationship and other factors, with the maximum allowable emissions as the objective function, PM 2.5 and O3 concentration targets as constraints, and establish a policy suitable for precursor reduction and PM 2.5 , O3 concentration surface response relationship to solve the optimal precursor reduction plan. This method uses source analysis and scenario simulation to establish a surface response relationship between precursor reduction in different regions and urban air quality. Based on the Taylor formula, the quadratic equation expression is fitted to quantify the nonlinear response relationship between NOx and VOCs and ozone concentrations; based on linear programming, the SO2, NOx, VOCs, PPM, NH3 emission reduction and precursor PM are established. 2.5 The linear response relationship between them.

[0077] The optimized emission reduction plan calculated by this technical method can provide strong technical support for the scientific and optimized emission reduction of urban particulate matter and ozone coordinated control, and can provide scientific decision-making support for the deep governance of the regional atmospheric environment and the continuous improvement of air quality. It is of great significance for addressing the current hot environmental issues of particulate matter and ozone pollution prevention and control in my country.

[0078] In some embodiments, the identifying the nonlinear response between the precursors in different emission reduction regions and the ozone concentration in the receptor region comprises:

[0079] According to the formula:

[0080]

[0081] Confirmation of nonlinear responses between precursors and ozone concentrations in recipient regions at different emission reduction sites In the formula, i is the receptor area, j is the emission reduction area, is the change in O3 concentration (μg / m 3 ), SA_O 2i,j represents the contribution of emission reduction region j to the O3 concentration of receptor region i in source apportionment; and Δ VOC are the percentage changes in NOx and VOCs emissions, respectively; and S VOC 1 are the primary sensitivity coefficients of NOx and VOCs respectively; and S VOC 2 are the secondary sensitivity coefficients of NOx and VOCs respectively; is the cross sensitivity coefficient between NOx and VOCs.

[0082] In some embodiments, the identifying the nonlinear response between the precursors in different emission reduction areas and the fine particulate matter concentration in the recipient area comprises:

[0083] According to the formula:

[0084] ΔPM 2.5i =ΔPPM i +ΔSNA i +ΔSOA i

[0085]

[0086] ΔSOA i =G i (ΔNOx i ,ΔVOCs i )

[0087]

[0088] ΔSNA i =ΔPSO 4i +ΔPNO 3i +ΔPNH 4i

[0089] Confirm the nonlinear response G(Δ NOx ,Δ VOV ), where ΔPM 2.5i represents PM in receptor region i 2.5 Concentration change, ΔPPM i , ΔSNA i , ΔSOA i Represents PM 2.5 Concentration changes of primary component (PPM), secondary inorganic aerosol (SNA), and secondary organic aerosol (SOA); ΔPPM 2.5j , ΔSO 2j , ΔNO xj ,ΔNH 3j , ΔVOC sj Respectively represent the emission reduction ratios of PPM, SO2, NOx, NH3 and VOCs precursors in emission reduction area j; SA_SOA i,j ,SA_PPM i,j ,SA_PSO 4i,j ,SA_PNO 3i,j ,SA_PNH 4i,j They represent the transport contribution of emission reduction region j to SOA, PPM, sulfate, nitrate and ammonium in receptor region i in source apportionment.

[0090] In some embodiments, determining the minimum emission reduction of precursors in different emission reduction areas includes:

[0091] According to the formula:

[0092]

[0093] Confirm the minimum emission reduction of five types of precursors SO2, NOx, VOCs, PPM, and NH3 in different emission reduction areas. In the formula, EM PPMj , EM So2j , EM NOxj , EM VOCsj , EM NH3jRespectively represent the PPM, SO2, NOx, NH3 and VOCs emissions of emission reduction area j; ΔPPM 2.5j , ΔSO 2j , ΔNO xj ,ΔNH 3j , ΔVOC sj They represent the emission reduction proportions of PPM, SO2, NOx, NH3 and VOCs precursors in emission reduction area j respectively.

[0094] It should be noted that the above equation is for the minimum emission reduction (i.e., the maximum allowable emission) of the five types of precursors SO2, NOx, VOCs, PPM, and NH3.

[0095] In some embodiments, the identifying the constraints of precursors in different emission reduction regions includes:

[0096] According to the relationship:

[0097] 0<ΔPPM 2.5j(policy) <ΔPPM 2.5j <ΔPPM 2.5j(max) <1

[0098] 0<ΔSO 2j(policy) <ΔSO 2j <ΔSO 2j(max) <1

[0099] 0<ΔNO xj(policy) <ΔNO xj <ΔNO xj(max) <1

[0100] 0<ΔVOC sj(policy) <ΔVOC sj <ΔVOC sj(max) <1

[0101] 0<ΔNH 3j(policy) <ΔNH 3j <ΔNH 3j(max) <1

[0102] Identify the constraints of precursors in different emission reduction areas. In the formula, the max and policy subscripts represent the maximum emission reduction potential and the minimum emission reduction ratio of future development plans and policies, respectively.

[0103] It should be noted that the constraints include not only non-negative constraints, but also maximum emission reduction potential constraints: the maximum emission reduction potential is the upper limit of the precursor emission reduction, which is calculated based on the precursor emission treatment process and emission reduction intensity.

[0104] It also includes policy constraints: the industry development planning policies of each city refer to the emission reduction policies that must be implemented in the future.

[0105] It should be noted that some variables in the optimization results may reach the upper limit, while the upper limit of the decision variable should be desirable and feasible.

[0106] In some embodiments, determining target constraints for fine particulate matter concentration and ozone concentration in different receptor areas includes:

[0107] According to the relationship:

[0108] PM 2.5i -ΔPM 2.5i ≤goalPM 2.5i (i∈{1,2,…,10})

[0109] Identify target constraints for fine particulate matter concentrations in different receptor areas;

[0110] According to the relationship:

[0111] O 3i -ΔO 3i ≤goalO 3i (i∈{1,2,…,10})

[0112] Identify target constraints for ozone concentrations in different receptor regions;

[0113] Where, PM 2.5i ,O 3i is the PM of receptor region i in the base year 2.5 and current status of O3 concentration; goalPM 2.5i ,goalO 3i Respectively represent the improvement of PM in the receptor area i 2.5 and target concentration of O3; ΔPM 2.5i and ΔO 3i are PM in receptor area i 2.5 and O3 concentration changes.

[0114] It should be noted that the above two relationships represent the target constraints of fine particulate matter concentration and ozone concentration in different receptor areas, also known as air quality target constraints, representing the PM concentration in each receptor area. 2.5 The concentration is constrained below the target concentration. The O3 concentration in each receptor area is constrained below the target concentration.

[0115] In some embodiments, the calculation of the emission reduction ratio of the precursors in all emission reduction areas according to the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas, and the target constraints of the fine particulate matter concentration and the ozone concentration in the different receptor areas includes:

[0116] The emission reduction ratio of precursors in all emission reduction areas is calculated through machine learning or genetic algorithms according to the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and ozone concentration in the different receptor areas.

[0117] It should be noted that the five types of precursors NOx, VOCs, and primary PM2.5 in all emission reduction cities are obtained through machine learning / genetic algorithms. 2.5 , SO2, NH3 emission reduction ratio.

[0118] In order to facilitate understanding of the above-mentioned fine particulate matter and ozone control method, specific examples are given below to illustrate:

[0119] Taking 2022 as the base year, PM in Beijing-Tianjin-Hebei region 2.5 and O3 composite pollution cities (exceeding the secondary standard of 35ug / m 3 and 160ug / m 3 ) including Beijing, Tianjin, Shijiazhuang, Handan, Xingtai, Baoding, Cangzhou, Langfang, and Hengshui. The target equation is PM 2.5 The annual average concentration and the 90% percentile of the maximum 8-hour O3 daily evaluation index were 35ug / m 3 、160ug / m 3 The emission reduction areas are set as the recipient cities and the surrounding provinces of Shanxi, Shandong and Henan, where transmission contributions are relatively significant.

[0120] According to the control method of fine particulate matter and ozone in this application, after collecting data, the estimated concentration of pollutants in the emission reduction scheme and optimization scheme scenario is solved as follows: Figure 2 The figure shows the optimized emission reduction scheme for five types of precursors and the concentration comparison diagram of the optimization algorithm and scenario simulation with 2022 as the base year. Among them, (a) is the optimized emission reduction scheme for five types of precursors in 2030, (b) is the optimized emission reduction scheme for five types of precursors in 2035, (c) is the concentration comparison of the optimization algorithm and scenario simulation in 2030, and (d) is the concentration comparison of the optimization algorithm and scenario simulation in 2035. It can be clearly seen that different cities have obvious emission reduction effects over time.

[0121] It can be seen that the control method of fine particulate matter and ozone in the present application establishes the EKMA curve of O3 and its precursors NOx and VOCs based on multiple sets of scenario simulation results. The first-order sensitivity and second-order sensitivity of the EKMA curve are fitted using the Taylor formula to quantify the disturbance of O3 concentration as the emission of precursors is reduced / increased. Based on the source analysis results, the contribution of O3 precursors in the receptor area is allocated according to the source-receptor transfer matrix, and finally the surface response relationship of the emission reduction of precursors NOx and VOCs in multiple divided emission reduction areas to the receptor O3 concentration is obtained. For PM 2.5 , based on the PPM and SNA component concentrations and their precursor PM 2.5 The linear response relationship between SO2, NOx, and NH3 emission reduction is established to establish a linear programming equation. In view of the nonlinear response of SOA components to NOx and VOCs, the scenario simulation method is also used to fit the binary quadratic equation quantitative expression. According to the source analysis results, the transmission matrix of the source receptor is allocated to obtain the PM direct emission of precursors in multiple emission reduction areas. 2.5 Linear / nonlinear response relationship of SO2, NOx, VOCs, and NH3 emission reduction to PPM, PSO4, PNO3, PNH4, and SOA in the receptor area. Comprehensive PM 2.5 and O3 sensitivity results, and establish PM 2.5 and O3 concentrations and their precursor PM 2.5 , the joint response relationship of SO2, NOx, VOCs and NH3 emissions.

[0122] Based on the optimization control technology theory, PM 2.5 The joint response relationship between O3 and its precursors was calculated by comprehensively considering the current baseline concentration, air quality improvement goals, policy planning, emission reduction potential, emission reduction costs and other factors. 2.5 The maximum allowable emissions of five types of precursors, SO2, NOx, VOCs, and NH3, are five objective functions. Different weight coefficients can be set as needed, and the constraints are set as non-negative constraints, policy constraints, maximum emission reduction potential constraints, O3 and PM 2.5 Based on the concentration target constraint, a nonlinear multi-objective optimization model for the coordinated control of particulate matter and ozone is established, and artificial intelligence / genetic algorithm is used to solve the optimization model to obtain the optimal emission reduction plan for pollutants in different regions.

[0123] In summary, the embodiments of the present application provide a method for regulating fine particulate matter and ozone, including: collecting precursor data, maximum emission reduction potential and emission reduction policies of different emission reduction areas, as well as ozone concentration data and fine particulate matter concentration of recipient areas; confirming the nonlinear response between precursors in different emission reduction areas and ozone concentrations in recipient areas; confirming the nonlinear response between precursors in different emission reduction areas and fine particulate matter concentrations in recipient areas; confirming the minimum emission reduction amount of precursors in different emission reduction areas; confirming the constraints of precursors in different emission reduction areas; confirming the target constraints of fine particulate matter concentrations and ozone concentrations in different recipient areas; according to the nonlinear response between precursors in different emission reduction areas and ozone concentrations in recipient areas, the nonlinear response between precursors in different emission reduction areas and fine particulate matter concentrations in recipient areas, the minimum emission reduction amount of precursors in different emission reduction areas, the constraints of precursors in different emission reduction areas and the target constraints of fine particulate matter concentrations and ozone concentrations in different recipient areas, calculate the emission reduction ratio of precursors in all emission reduction areas. This application introduces PM 2.5 The joint response relationship between O3 and its precursors, as well as the different constraints of different emission reduction cities, are used to solve the optimal emission reduction plan for precursors in the emission reduction area.

[0124] Embodiment 2

[0125] Based on the method for controlling fine particulate matter and ozone disclosed in the above embodiment of the present invention, Figure 3 Specifically disclosed is a fine particle and ozone control system using the fine particle and ozone control method.

[0126] like Figure 3 As shown, an embodiment of the present invention discloses a control system for fine particulate matter and ozone, the system comprising:

[0127] A collection unit 301 is used to collect precursor data, maximum emission reduction potential and emission reduction policies in different emission reduction areas, as well as ozone concentration data and fine particulate matter concentration in the recipient area;

[0128] A first confirmation unit 302 is used to confirm the nonlinear response between the precursors in different emission reduction areas and the ozone concentration in the receptor area;

[0129] The second confirmation unit 303 is used to confirm the nonlinear response between the precursors in different emission reduction areas and the fine particulate matter concentration in the receptor area;

[0130] The third confirmation unit 304 is used to confirm the minimum emission reduction amount of the precursor in different emission reduction areas;

[0131] The fourth confirmation unit 305 is used to confirm the constraints of precursors in different emission reduction areas;

[0132] A fifth confirmation unit 306 is used to confirm the target constraints of fine particulate matter concentration and ozone concentration in different receptor areas;

[0133] The calculation unit 307 is used to calculate the emission reduction ratio of the precursors in all emission reduction areas according to the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and ozone concentration in the different receptor areas.

[0134] For the specific working process of the collection unit 301, the first confirmation unit 302, the second confirmation unit 303, the third confirmation unit 304, the fourth confirmation unit 305, the fifth confirmation unit 306 and the calculation unit 307 in the fine particulate matter and ozone control system disclosed in the above embodiment of the present invention, please refer to the corresponding content in the fine particulate matter and ozone control method disclosed in the above embodiment of the present invention, which will not be repeated here.

[0135] In summary, the embodiment of the present application provides a fine particulate matter and ozone control system, including: collecting precursor data, maximum emission reduction potential and emission reduction policies of different emission reduction areas, as well as ozone concentration data and fine particulate matter concentration of recipient areas; confirming the nonlinear response between precursors in different emission reduction areas and ozone concentrations in recipient areas; confirming the nonlinear response between precursors in different emission reduction areas and fine particulate matter concentrations in recipient areas; confirming the minimum emission reduction amount of precursors in different emission reduction areas; confirming the constraints of precursors in different emission reduction areas; confirming the target constraints of fine particulate matter concentrations and ozone concentrations in different recipient areas; calculating the emission reduction ratio of precursors in all emission reduction areas according to the nonlinear response between precursors in different emission reduction areas and ozone concentrations in recipient areas, the nonlinear response between precursors in different emission reduction areas and fine particulate matter concentrations in recipient areas, the minimum emission reduction amount of precursors in different emission reduction areas, the constraints of precursors in different emission reduction areas and the target constraints of fine particulate matter concentrations and ozone concentrations in different recipient areas. This application introduces PM 2.5 The joint response relationship between O3 and its precursors, as well as the different constraints of different emission reduction cities, are used to solve the optimal emission reduction plan for precursors in the emission reduction area.

[0136] Embodiment 3

[0137] This embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a disk, an optical disk, a server, an App application store, etc., on which a computer program is stored. When the computer program is executed by a processor, the method steps of the first embodiment can be implemented, and this embodiment will not be repeated here.

[0138] Embodiment 4

[0139] Figure 4 A connection block diagram of an electronic device 400 provided in an embodiment of the present application, such as Figure 4 As shown, the electronic device 400 may include: a processor 401 , a memory 402 , a multimedia component 403 , an input / output (I / O) interface 404 , and a communication component 405 .

[0140] The processor 401 is used to execute all or part of the steps in the method for controlling fine particulate matter and ozone in Example 1. The memory 402 is used to store various types of data, which may include instructions of any application or method in the electronic device, and data related to the application.

[0141] The processor 401 can be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and is used to execute the method for controlling fine particulate matter and ozone in the above-mentioned embodiment 1.

[0142] The memory 402 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0143] The multimedia component 403 may include a screen and an audio component, the screen may be a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, and the microphone is used to receive external audio signals. The received audio signal may be further stored in a memory or sent via a communication component. The audio component also includes at least one speaker for outputting audio signals.

[0144] The I / O interface 404 provides an interface between the processor 401 and other interface modules, which may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons.

[0145] The communication component 405 is used for wired or wireless communication between the electronic device 400 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 405 can include: Wi-Fi module, Bluetooth module, NFC module.

[0146] In summary, the present application provides a method, system, storage medium and electronic device for regulating fine particulate matter and ozone, the method comprising: collecting precursor data, maximum emission reduction potential and emission reduction policies of different emission reduction areas, as well as ozone concentration data and fine particulate matter concentration of recipient areas; confirming the nonlinear response between precursors in different emission reduction areas and ozone concentration in recipient areas; confirming the nonlinear response between precursors in different emission reduction areas and fine particulate matter concentration in recipient areas; confirming the minimum emission reduction amount of precursors in different emission reduction areas; confirming the constraints of precursors in different emission reduction areas; confirming the target constraints of fine particulate matter concentration and ozone concentration in different recipient areas; calculating the emission reduction ratio of precursors in all emission reduction areas according to the nonlinear response between precursors in different emission reduction areas and ozone concentration in recipient areas, the nonlinear response between precursors in different emission reduction areas and fine particulate matter concentration in recipient areas, the minimum emission reduction amount of precursors in different emission reduction areas, the constraints of precursors in different emission reduction areas and the target constraints of fine particulate matter concentration and ozone concentration in different recipient areas. The present application introduces PM 2.5 The joint response relationship between O3 and its precursors, as well as the different constraints of different emission reduction cities, are used to solve the optimal emission reduction plan for precursors in the emission reduction area.

[0147] In the several embodiments provided in the present application, it should be understood that the disclosed method can also be implemented in other ways. The method embodiments described above are merely illustrative.

[0148] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0149] Although the implementation methods disclosed in this application are as above, the above contents are only the implementation methods adopted for facilitating the understanding of this application, and are not intended to limit this application. Any technician in the technical field to which this application belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in this application, but the scope of patent protection of this application shall still be based on the scope defined in the attached claims.

Claims

1. A method for regulating fine particulate matter and ozone, characterized in that: The method comprises: Collect data on precursors, maximum reduction potential and reduction policies in different emission reduction regions, as well as ozone concentration data and fine particulate matter concentrations in recipient regions; Confirmation of nonlinear responses between precursors in different abatement regions and ozone concentrations in receptor regions; Identify the nonlinear response between precursors in different abatement regions and fine particulate matter concentrations in recipient regions; Identify the minimum emission reductions for precursors in different emission reduction areas; Identify constraints on precursors in different abatement areas; Identify target constraints for particulate matter and ozone concentrations in different receptor areas; The emission reduction ratio of precursors in all emission reduction areas is calculated based on the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the recipient areas, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the recipient areas, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and ozone concentration in the different recipient areas.

2. The method according to claim 1, characterized in that The identification of nonlinear responses between precursors in different emission reduction regions and ozone concentrations in receptor regions includes: According to the formula: Confirmation of nonlinear responses between precursors and ozone concentrations in recipient regions at different emission reduction sites In the formula, i is the receptor area, j is the emission reduction area, is the change of O3 concentration, SA_O 3i,j represents the contribution of emission reduction region j to the O3 concentration of receptor region i in source apportionment; and Δ VOC are the percentage changes in NOx and VOCs emissions, respectively; and S VOC 1 are the primary sensitivity coefficients of NOx and VOCs respectively; and S VOC 2 are the secondary sensitivity coefficients of NOx and VOCs respectively; is the cross sensitivity coefficient between NOx and VOCs.

3. The method according to claim 1, characterized in that The identification of nonlinear responses between precursors in different emission reduction areas and fine particulate matter concentrations in recipient areas includes: According to the formula: ΔPM 2.5i =ΔPPM i +ΔSNA i +ΔSOA i ΔSOA i =G i (ΔNOx i ,ΔVOCs i ) ΔSNA i =ΔPSO 4i +ΔPNO 3i +ΔPNH 4i Identify nonlinear responses between precursors and fine particulate matter concentrations in recipient regions at different emission reduction sites Where ΔPM 2.5i represents PM in receptor region i 2.5 Concentration change, ΔPPM i , ΔSNA i , ΔSOA i Represents PM 2.5 Primary component PPM, secondary inorganic aerosol SNA, secondary organic aerosol SOA concentration change value; ΔPPM 2.5j , ΔSO 2j , ΔNO xj ,ΔNH 3j , ΔVOC sj Respectively represent the emission reduction ratios of PPM, SO2, NOx, NH3 and VOCs precursors in emission reduction area j; SA_SOA i,j ,SA_PPM i,j ,SA_PSO 4i,j ,SA_PNO 3i,j ,SA_PNH 4i,j They represent the transport contribution of emission reduction region j to SOA, PPM, sulfate, nitrate and ammonium in receptor region i in source apportionment.

4. The method according to claim 1, characterized in that: The minimum emission reductions for precursors in different emission reduction areas include: According to the formula: Confirm the minimum emission reduction of five types of precursors SO2, NOx, VOCs, PPM, and NH3 in different emission reduction areas. In the formula, EM PPMj , EM SO2j , EM NOxj , EM VOCsj , EM NH3j Respectively represent the PPM, SO2, NOx, NH3 and VOCs emissions of emission reduction area j; ΔPPM 2.5j , ΔSO 2j , ΔNO xj ,ΔNH 3j , ΔVOC sj They represent the emission reduction proportions of PPM, SO2, NOx, NH3 and VOCs precursors in emission reduction area j respectively.

5. The method according to claim 1, characterized in that The constraints for identifying precursors in different emission reduction areas include: According to the relationship: 0<ΔPPM 2.5j(policy) <ΔPPM 2.5j <ΔPPM 2.5j(max) <1 0<ΔSO 2j(policy) <ΔSO 2j <ΔSO 2j(max) <1 0<ΔNO xj(policy) <ΔNO xj <ΔNO xj(max) <1 0<ΔVOC sj(policy) <ΔVOC sj <ΔVOC sj(max) <1 0<ΔNH 3j(policy) <ΔNH 3j <ΔNH 3j(max) <1 Identify the constraints of precursors in different emission reduction areas. In the formula, the max and policy subscripts represent the maximum emission reduction potential and the minimum emission reduction ratio of future development plans and policies, respectively.

6. The method according to claim 1, characterized in that The target constraints for particulate matter and ozone concentrations in different receptor areas are confirmed, including: According to the relationship: PM 2.5i -ΔPM 2.5i ≤goalPM 2.5i (i∈{1,2,…,10}) Identify target constraints for fine particulate matter concentrations in different receptor areas; According to the relationship: Oh 3i -ΔO 3i ≤goalO 3i (i∈{1,2,…,10}) Identify target constraints for ozone concentrations in different receptor regions; In the formula, PM 2.5i ,O 3i is the PM of receptor region i in the base year 2.5 and current status of O3 concentration; goalPM 2.5i ,goalO 3i Respectively represent the improvement of PM in the receptor area i 2.5 and target concentration of O3; ΔPM 2.5i and ΔO 3i are PM in receptor area i 2.5 and O3 concentration changes.

7. The method according to claim 1, characterized in that The calculation of the emission reduction ratio of the precursors in all emission reduction areas according to the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and the ozone concentration in the different receptor areas includes: The emission reduction ratio of precursors in all emission reduction areas is calculated through machine learning or genetic algorithms according to the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and ozone concentration in the different receptor areas.

8. A fine particulate matter and ozone control system, characterized in that: The system comprises: A collection unit for collecting precursor data, maximum emission reduction potential and emission reduction policies in different emission reduction areas, as well as ozone concentration data and fine particulate matter concentration in the receptor area; The first confirmation unit is used to confirm the nonlinear response between the precursors in different emission reduction areas and the ozone concentration in the receptor area; The second confirmation unit is used to confirm the nonlinear response between the precursors in different emission reduction areas and the fine particulate matter concentrations in the receptor area; The third confirmation unit is used to confirm the minimum emission reduction of precursors in different emission reduction areas; The fourth confirmation unit is used to confirm the constraints of precursors in different emission reduction areas; The fifth confirmation unit is used to confirm the target constraints of fine particulate matter concentration and ozone concentration in different receptor areas; A calculation unit is used to calculate the emission reduction ratio of the precursors in all emission reduction areas according to the nonlinear response between the precursors in the different emission reduction areas and the ozone concentration in the receptor area, the nonlinear response between the precursors in the different emission reduction areas and the fine particulate matter concentration in the receptor area, the minimum emission reduction amount of the precursors in the different emission reduction areas, the constraints of the precursors in the different emission reduction areas and the target constraints of the fine particulate matter concentration and the ozone concentration in the different receptor areas.

9. A storage medium, characterized in that: The computer program stored in the storage medium can be executed by one or more processors and can be used to implement the method for controlling fine particulate matter and ozone as described in any one of claims 1 to 7.

10. An electronic device, characterized in that: It comprises a memory and a processor, wherein a computer program is stored in the memory, and the memory and the processor are communicatively connected with each other, and when the computer program is executed by the processor, the method for controlling fine particulate matter and ozone as claimed in any one of claims 1 to 7 is executed.

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