Ozone concentration generation curve construction method, system, medium and terminal

Abstract

The present application provides a method, system, medium and terminal for constructing an ozone concentration generation curve, including: running calculations on the target area based on an air quality model to obtain sensitivity coefficients and ozone concentration simulation values ​​corresponding to each precursor emission reduction scenario; the precursor emission reduction scenarios include: basic scenario, 50% emission reduction scenario and 75% emission reduction scenario; the sensitivity coefficients include: first-order sensitivity coefficients, second-order sensitivity coefficients and cross-sensitivity coefficients; based on the sensitivity coefficients corresponding to each emission reduction scenario and the ozone concentration simulation value, a third-order optimization method is used to calculate and obtain an ozone concentration estimation value; an EKMA curve is generated based on the ozone concentration estimation value. The present application can not only improve the accuracy of ozone concentration estimation, but also reduce the number of model runs compared to the traditional method of drawing EKMA curves by running multiple groups of experiments based on observation models, greatly saving memory resources and improving calculation efficiency.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, system, medium and terminal for constructing an ozone concentration generation curve. Background Art

[0002] The ozone generation concentration curve (Empirical Kinetics Modeling Approach, EKMA curve) can reflect the nonlinear relationship between ozone and its precursors VOCs (volatile organic compounds) and NOx (nitrogen oxides). It is the mainstream method for studying the sensitivity of urban ozone concentration generation and its control path. The traditional method of drawing EKMA curves based on observation models by running multiple groups of experiments is generally based on at least 5×5, i.e. 25 groups of precursor proportional reduction experiments. It requires dozens or hundreds of experiments, which consumes computing resources and takes a long time. In addition, if the precursor concentration range and isoconcentration gradient are considered, the number of experiments needs to be doubled. Although the traditional method of drawing EKMA curves based on air quality models only requires one set of experiments, studies have found that when predicting the response relationship between ozone concentration and NOx emissions, when the emission changes by more than 50% to 60%, a large prediction error will be generated. Therefore, when estimating ozone concentration, it is easy to have a large error in drawing EKMA curves when the reduction ratio of precursors VOCs and NOx is large. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention provides a method, system, medium and terminal for constructing an ozone concentration generation curve, which are used to solve the problems in the prior art that the traditional model runs many times, consumes computing resources, takes a long time, and has large errors in drawing the EKMA curve.

[0004] To achieve the above-mentioned purpose and other related purposes, the first aspect of the present application provides a method for constructing an ozone concentration generation curve, comprising: performing operation calculations on the target area based on an air quality model to obtain sensitivity coefficients and ozone concentration simulation values ​​corresponding to each precursor emission reduction scenario; the precursor emission reduction scenarios include: a basic scenario, a 50% emission reduction scenario, and a 75% emission reduction scenario; the sensitivity coefficients include: a first-order sensitivity coefficient, a second-order sensitivity coefficient, and a cross-sensitivity coefficient; based on the sensitivity coefficients corresponding to each emission reduction scenario and the ozone concentration simulation value, a third-order optimization method is used to calculate to obtain an ozone concentration estimate; and an EKMA curve is generated based on the ozone concentration estimate.

[0005] In some embodiments of the first aspect of the present application, the ozone concentration estimation value is calculated based on the sensitivity coefficient corresponding to each emission reduction scenario and the ozone concentration simulation value using a third-order optimization method, including: obtaining a first cutoff point and a second cutoff point to divide the emission reduction ratio into emission reduction sub-ratios; the emission reduction sub-ratios include: a first emission reduction sub-ratio, a second emission reduction sub-ratio and a third emission reduction sub-ratio; based on the sensitivity coefficient corresponding to each emission reduction scenario, the ozone concentration change corresponding to each emission reduction sub-ratio is calculated; based on the ozone concentration change under each emission reduction sub-ratio, the ozone concentration estimation value is calculated.

[0006] In some embodiments of the first aspect of the present application, calculating the ozone concentration change corresponding to each emission reduction sub-ratio based on the sensitivity coefficient corresponding to each emission reduction scenario includes: the calculation formula of the ozone concentration change under the first emission reduction sub-ratio is as follows: Where Δc1 is the change in ozone concentration under the first emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of the precursor NOx under the basic scenario, is the first-order sensitivity coefficient of precursor VOCs under the basic scenario, is the second-order sensitivity coefficient of the precursor NOx under the basic scenario, is the second-order sensitivity coefficient of precursor VOCs under the basic scenario, The cross-sensitivity coefficients of precursors NOx and VOCs under the basic scenario.

[0007] In some embodiments of the first aspect of the present application, calculating the ozone concentration change corresponding to each emission reduction sub-ratio based on the sensitivity coefficient corresponding to each emission reduction scenario includes: the calculation formula of the ozone concentration change under the second emission reduction sub-ratio is as follows: Where Δc2 is the change in ozone concentration under the second emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of precursor NOx under the scenario of 50% emission reduction, is the first-order sensitivity coefficient of precursor VOCs under the scenario of 50% emission reduction, is the second-order sensitivity coefficient of the precursor NOx under the 50% emission reduction scenario, is the second-order sensitivity coefficient of precursor VOCs under the 50% emission reduction scenario, is the cross-sensitivity coefficient of precursor NOx and VOCs under the scenario of 50% emission reduction, cadjust-50％ It is the ozone concentration adjustment under the scenario of 50% emission reduction.

[0008] In some embodiments of the first aspect of the present application, calculating the ozone concentration change corresponding to each emission reduction sub-ratio based on the sensitivity coefficient corresponding to each emission reduction scenario includes: the calculation formula of the ozone concentration change under the third emission reduction sub-ratio is as follows: Where Δc3 is the change in ozone concentration under the third emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of precursor NOx under the 75% emission reduction scenario, is the first-order sensitivity coefficient of precursor VOCs under the 75% emission reduction scenario, is the second-order sensitivity coefficient of the precursor NOx under the 75% emission reduction scenario, is the second-order sensitivity coefficient of precursor VOCs under the 75% emission reduction scenario, is the cross-sensitivity coefficient of precursor NOx and VOCs under the 75% emission reduction scenario, c adjust-75％ This is the ozone concentration adjustment for a 75% reduction scenario.

[0009] In some embodiments of the first aspect of the present application, the method for obtaining the first cutoff point includes: calculating and obtaining the first cutoff point when the error between the ozone concentration change under the second emission reduction sub-ratio and the ozone concentration simulation value under the 50% emission reduction scenario is the smallest; the calculation formula of the first cutoff point is as follows:

[0010] Among them, ε1 is the error between the change of ozone concentration under the second emission reduction sub-ratio and the simulated value of ozone concentration under the 50% emission reduction scenario, X is the first cutoff point, ΔC 50％ This is the simulated value of ozone concentration under the scenario of 50% emission reduction.

[0011] In some embodiments of the first aspect of the present application, the method for obtaining the second truncation point includes: when the error between the change in ozone concentration under the third emission reduction sub-ratio and the ozone concentration simulation value under the 75% emission reduction scenario is the smallest, the second truncation point is calculated; the calculation formula of the second truncation point is as follows:

[0012] Wherein, ε2 is the error between the change in ozone concentration under the third emission reduction sub-ratio and the simulated value of ozone concentration under the 75% emission reduction scenario, X is the first cutoff point, Y is the second cutoff point, ΔC 75％This is the simulated value of ozone concentration under the scenario of 75% emission reduction.

[0013] To achieve the above-mentioned purpose and other related purposes, the second aspect of the present application provides an ozone concentration generation curve construction system, including: a calculation module, which is used to perform operation calculations on the target area based on the air quality model to obtain the sensitivity coefficients and ozone concentration simulation values ​​corresponding to each precursor emission reduction scenario; the precursor emission reduction scenarios include: a basic scenario, a 50% emission reduction scenario and a 75% emission reduction scenario; the sensitivity coefficients include: a first-order sensitivity coefficient, a second-order sensitivity coefficient and a cross-sensitivity coefficient; an estimation module, which is connected to the calculation module, and is used to calculate the ozone concentration estimation value based on the sensitivity coefficients corresponding to each emission reduction scenario and the ozone concentration simulation value using a third-order optimization method; a drawing module, which is connected to the estimation module, and is used to generate an EKMA curve based on the ozone concentration estimation value.

[0014] To achieve the above-mentioned purpose and other related purposes, the third aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the ozone concentration generation curve construction method is implemented.

[0015] To achieve the above-mentioned purpose and other related purposes, the fourth aspect of the present application provides an electronic terminal, including a memory, a processor and a computer program stored in the memory; the processor executes the computer program to implement the ozone concentration generation curve construction method.

[0016] As described above, the ozone concentration generation curve construction method, system, medium and terminal of the present application have the following beneficial effects:

[0017] The method of constructing an ozone generation concentration curve based on a sensitivity analysis tool based on third-order optimization proposed in this application can not only improve the accuracy of ozone concentration estimation, but also reduce the number of model runs compared to the traditional method of drawing EKMA curves by running multiple groups of experiments based on observation models, greatly save memory resources, and improve computing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Shown is a flow chart of a method for constructing an ozone concentration generation curve in one embodiment of the present application.

[0019] Figure 2 Shown is a schematic diagram of a flow chart of ozone concentration estimation value calculation in one embodiment of the present application.

[0020] Figure 3 Shown is a specific embodiment diagram of a method for constructing an ozone concentration generation curve in one embodiment of the present application.

[0021] Figure 4Shown is another specific embodiment of a method for constructing an ozone concentration generation curve in one embodiment of the present application.

[0022] Figure 5 Shown is a structural schematic diagram of an ozone concentration generation curve construction system in one embodiment of the present application.

[0023] Figure 6 Shown is a schematic diagram of the structure of an electronic terminal in one embodiment of the present application. DETAILED DESCRIPTION

[0024] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0025] The present invention provides a method, system, medium and terminal for constructing an ozone concentration generation curve. The present application uses a sensitivity analysis tool (HDDM) in an air quality numerical model (CAMx) to calculate the first-order sensitivity coefficient, second-order sensitivity coefficient and cross-sensitivity coefficient of the change in ozone concentration for precursors NOx and VOCs, respectively, and based on the third-order optimization concept, achieves improvements in computational efficiency and accuracy. On this basis, a method for obtaining two cutoff points in the third-order optimization method is established using the least squares method, so that the error in ozone concentration estimation is further reduced. At the same time, compared with the traditional method of drawing an EKMA curve by running multiple groups of experiments based on an observation model, the frequency of model operation is reduced, the number of operations is reduced, and computing time and memory resources can be saved.

[0026] Before further describing the present invention in detail, the nouns and terms involved in the embodiments of the present invention are explained. The nouns and terms involved in the embodiments of the present invention are applicable to the following interpretations:

[0027] <1> HDDM model: High-order direct decoupling direct method is a commonly used forward sensitivity analysis method for studying the dynamics of chemical substances and environmental impacts in ecosystems. HDDM has the characteristics of being more direct, effective and stable.

[0028] <2> Air quality model: This model is an important technical method that uses meteorological and mathematical knowledge to simulate air quality from different angles and on a large scale, so as to reproduce the various processes of pollutants in the atmosphere. At present, there are two types of air quality models in the world. One is called a statistical model, which is based on a large amount of existing data to establish a statistical forecast between atmospheric pollution concentration and meteorological parameters and a model for predicting atmospheric pollutant concentrations; the other is a numerical model, which is based on the theory of atmospheric dynamics and establishes a numerical model for the transport and diffusion of atmospheric pollution concentrations in the air, using computers to predict the dynamic distribution of atmospheric pollutant concentrations in the air.

[0029] <3> CAMx (Comprehensive Air Quality Model Extensions): The CAMx model is based on the framework of "One Atmosphere", adopts the atmospheric diffusion equation of mass conservation, and uses a finite difference three-dimensional grid as the framework to simulate the emission, diffusion, chemical reaction, and dry and wet deposition of gaseous and particulate pollutants and air toxics in the atmosphere. It is suitable for simulation and evaluation at the urban scale or even large-scale regions. CAMx simulates the emission, diffusion, chemical reaction, and removal of pollutants in the atmosphere by solving the physical and chemical change equations of each pollutant in each grid.

[0030] To facilitate understanding of the embodiments of the present application, first Figure 1 Detailed description. Figure 1 The following is a flow chart showing a method for constructing an ozone concentration curve in an embodiment of the present invention. The method for constructing an ozone concentration curve in this embodiment mainly includes the following steps:

[0031] Step S1: Based on the air quality model, the target area is operated and calculated to obtain the sensitivity coefficients and ozone concentration simulation values ​​corresponding to each precursor emission reduction scenario; the precursor emission reduction scenarios include: basic scenario, 50% emission reduction scenario and 75% emission reduction scenario; the sensitivity coefficients include: first-order sensitivity coefficient, second-order sensitivity coefficient and cross-sensitivity coefficient.

[0032] It should be noted that an air quality model is built. The air quality model is a mesoscale air quality model equipped with a sensitivity analysis module. The air quality model includes but is not limited to CAMx and CMAQ, and the sensitivity analysis module HDDM in the air quality model is turned on; the emission source data and meteorological data of the target area in the same period are input into the CAMx-HDDM model, and three sets of precursor emission reduction scenarios are run, namely, no reduction in precursor NOx and VOCs emissions (base scenario), 50% reduction in NOx and VOCs emissions (50% reduction scenario), and 75% reduction in NOx and VOCs emissions (75% reduction scenario); after the model runs the three sets of scenarios, the first-order sensitivity coefficients of ozone concentration to NOx and VOCs under the base scenario, 50% reduction scenario, and 75% reduction scenario are calculated respectively. and Second-order sensitivity coefficient and And the cross sensitivity coefficient

[0033] Specifically, the precursor refers to the substance in the previous stage of the product in a certain reaction process or the substance in the previous stage of a certain metabolic intermediate. In the process of ozone generation, volatile organic compounds and nitrogen oxides will generate ozone through photochemical reactions. The larger the sensitivity coefficient, the greater the impact on ozone generation. For example, the larger the sensitivity coefficient of the first precursor in a certain area, the more likely the volatile organic compounds emitted in this area will generate ozone, causing ozone pollution.

[0034] Furthermore, the meteorological fields required for the operation of the CAMx model are provided by meteorological models, such as the mesoscale meteorological model MM5 (Fifth-Generation NCAR / Penn State Mesoscale Model), WRF (Weather Research and Forecasting Model) and RAMS. The gas phase chemical reaction mechanisms used are CB05, SAPRC99 (now updated to SAPRC07), CB4 (now updated to CB6), and CBM-IV chemical mechanisms. The statistical species of CAMx emission source data generally include pollutants such as NOx, VOCs, CO, SO2, PM10, PM2.5 and NH3.

[0035] Step S2: Based on the sensitivity coefficients corresponding to each emission reduction scenario and the ozone concentration simulation value, a third-order optimization method is used to calculate and obtain an estimated ozone concentration value.

[0036] like Figure 2 As shown, step S2 includes:

[0037] Step S21: Obtain a first cutoff point and a second cutoff point to divide the emission reduction ratio into various emission reduction sub-ratios; the emission reduction sub-ratios include: a first emission reduction sub-ratio, a second emission reduction sub-ratio and a third emission reduction sub-ratio;

[0038] Step S22: Calculate the ozone concentration change corresponding to each emission reduction sub-ratio based on the sensitivity coefficient corresponding to each emission reduction scenario;

[0039] Step S23: Calculate the estimated ozone concentration based on the ozone concentration change under each emission reduction sub-ratio.

[0040] It should be noted that a first cutoff point X and a second cutoff point Y are set, wherein the range of the first cutoff point X is between 0 and 50, and the range of the second cutoff point Y is between 0 and 25; the emission reduction ratio of 0 to 100 is divided into three emission reduction sub-ratios by the two cutoff points, including: a first emission reduction sub-ratio (ranging between 0 and X), a second emission reduction sub-ratio (ranging between X and (X+Y)) and a third emission reduction sub-ratio (ranging between (X+Y) and 100).

[0041] Furthermore, the ozone concentration change corresponding to each emission reduction sub-ratio is obtained by using different calculation formulas based on the sensitivity coefficients corresponding to each emission reduction scenario. The specific calculation formulas are as follows:

[0042] The calculation formula for the change in ozone concentration under the first emission reduction sub-ratio is as follows:

[0043]

[0044] Where Δc1 is the change in ozone concentration under the first emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of the precursor NOx under the basic scenario, is the first-order sensitivity coefficient of precursor VOCs under the basic scenario, is the second-order sensitivity coefficient of the precursor NOx under the basic scenario, is the second-order sensitivity coefficient of precursor VOCs under the basic scenario, The cross-sensitivity coefficients of precursors NOx and VOCs under the basic scenario.

[0045] It should be noted that λ in Formula 1 nox and λ voc The emission reduction change percentage represented ranges from 0 to X, and the ozone concentration change between the first emission reduction sub-ratio 0 and X is calculated in sequence.

[0046] The calculation formula for the change in ozone concentration under the second emission reduction sub-ratio is as follows:

[0047]

[0048] Where Δc2 is the change in ozone concentration under the second emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of precursor NOx under the scenario of 50% emission reduction, is the first-order sensitivity coefficient of precursor VOCs under the scenario of 50% emission reduction, is the second-order sensitivity coefficient of the precursor NOx under the 50% emission reduction scenario, is the second-order sensitivity coefficient of precursor VOCs under the 50% emission reduction scenario, is the cross-sensitivity coefficient of precursor NOx and VOCs under the scenario of 50% emission reduction, c adjust-50％ It is the ozone concentration adjustment under the scenario of 50% emission reduction.

[0049] It should be noted that λ in Formula 2 nox and λ voc The percentage range of emission reduction change represented is between X and (X+Y), and the ozone concentration change between the second emission reduction sub-ratio X and (X+Y) is calculated in turn.

[0050] Furthermore, c adjust-50％ is the concentration adjustment, i.e., the difference between Formula 1 and Formula 2 when the emission reduction ratio is at the intersection point of 50%. Specifically, the sensitivity coefficients of the precursors NOx and VOCs under the 50% emission reduction scenario are substituted into Formula 1 to obtain the value obtained by the calculation and the difference between the sensitivity coefficients of the precursors NOx and VOCs under the 50% emission reduction scenario and the value obtained when the second emission reduction ratio is 50% (i.e., λ nox and λ voc 2 to obtain the ozone concentration adjustment under the 50% emission reduction scenario.

[0051] The calculation formula for the change in ozone concentration under the third emission reduction sub-ratio is as follows:

[0052]

[0053] Where Δc3 is the change in ozone concentration under the third emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of precursor NOx under the 75% emission reduction scenario, is the first-order sensitivity coefficient of precursor VOCs under the 75% emission reduction scenario, is the second-order sensitivity coefficient of the precursor NOx under the 75% emission reduction scenario, is the second-order sensitivity coefficient of precursor VOCs under the 75% emission reduction scenario, is the cross-sensitivity coefficient of precursor NOx and VOCs under the 75% emission reduction scenario, c adjust-75％ This is the ozone concentration adjustment for a 75% reduction scenario.

[0054] It should be noted that λ in Formula 3 nox and λ voc The percentage range of emission reduction change represented is between (X+Y) and 100, and the ozone concentration change between the third emission reduction sub-ratio (X+Y) and 100 is calculated in turn.

[0055] Furthermore, c adjust-75％ is the concentration adjustment, i.e., the difference between the values ​​calculated by using Formula 1 and Formula 3 when the emission reduction ratio is 75% at the intersection point. Specifically, the sensitivity coefficients of the precursors NOx and VOCs under the 75% emission reduction scenario are substituted into Formula 1 to obtain the values ​​calculated when the third emission reduction ratio is 75% (i.e., λ nox and λ voc 3) to obtain the ozone concentration adjustment under the 75% emission reduction scenario.

[0056] It should be noted that the first truncation point X and the second truncation point Y are obtained in different ways.

[0057] The method for obtaining the first truncation point X includes:

[0058] When the error between the ozone concentration change under the second emission reduction sub-ratio and the ozone concentration simulation value under the 50% emission reduction scenario is the smallest, the first cutoff point X is calculated; that is, ε1 = Δc2-ΔC 50％ ; Substituting this formula into the calculation to obtain the specific calculation formula of the first truncation point X is as follows:

[0059]

[0060] Among them, ε1 is the error between the change of ozone concentration under the second emission reduction sub-ratio and the simulated value of ozone concentration under the 50% emission reduction scenario, X is the first cutoff point, ΔC 50％ is the simulated value of ozone concentration under the scenario of 50% emission reduction. Solving the cubic equation of formula 4 above about the first cutoff point X, the value of the first cutoff point X can be obtained.

[0061] The method for obtaining the second truncation point Y includes:

[0062] When the error between the change in ozone concentration under the third emission reduction sub-ratio and the simulated value of ozone concentration under the 75% emission reduction scenario is the smallest, the second cutoff point Y is calculated; that is, ε2 = Δc3-ΔC 75％ Substituting this formula into the calculation, the calculation formula for obtaining the second cutoff point Y is as follows:

[0063]

[0064] Wherein, ε2 is the error between the change in ozone concentration under the third emission reduction sub-ratio and the simulated value of ozone concentration under the 75% emission reduction scenario, X is the first cutoff point, Y is the second cutoff point, ΔC 75％ is the simulated value of ozone concentration under the scenario of 75% emission reduction. Solving the above cubic equation about the second cutoff point Y, we can get the value of the second cutoff point Y. At different locations and for different simulation periods, the values ​​of the first cutoff point X and the second cutoff point Y are slightly different.

[0065] It should be emphasized that after obtaining the values ​​of the first cutoff point X and the second cutoff point Y, the emission reduction ratio of 0 to 100 is divided into three emission reduction sub-ratios, and the ozone concentration change corresponding to each emission reduction sub-ratio is calculated according to the formulas corresponding to the three emission reduction sub-ratios, that is, the emission reduction ratios of the precursors NOx and VOCs are set to proportional gradient values ​​from 0% to 100%, and then the ozone concentration change corresponding to each ratio is obtained, and after integration, the estimated values ​​of ozone concentration under different NOx and VOCs emission reduction ratios are obtained.

[0066] Step S3: Generate an EKMA curve based on the estimated ozone concentration. The EKMA curve is generated by drawing the estimated ozone concentration at different NOx and VOCs emission reduction ratios, where the horizontal and vertical coordinates in the EKMA curve are different NOx and VOCs emission reduction ratios, and each broken line is the estimated ozone concentration at different NOx and VOCs emission reduction ratios.

[0067] It should be emphasized that the present invention uses the sensitivity analysis tool (HDDM) in the air quality numerical model (CAMx) to calculate the first-order sensitivity coefficient, second-order sensitivity coefficient and cross-sensitivity coefficient of the change in ozone concentration to the precursors NOx and VOCs, respectively, and based on the third-order optimization concept, it achieves improvements in computational efficiency and accuracy. On this basis, the least squares method is used to establish a method for obtaining two truncation points in the third-order optimization method, so that the error of ozone concentration estimation is further reduced. At the same time, compared with the traditional method of running multiple groups of experiments based on the observation model to draw the EKMA curve, the frequency of model operation is reduced, the number of operations is reduced, and computing time and memory resources can be saved.

[0068] In order to facilitate the demonstration of the specific method of constructing the ozone concentration generation curve of the present application, the following specific examples are provided for illustration.

[0069] Example 1: A method for constructing an ozone concentration curve; Figure 3 As shown, the method is as follows:

[0070] Step 1: Build the CAMx-HDDM air quality model;

[0071] Step 2: Run three sets of scenarios to calculate the first-order sensitivity coefficient, second-order sensitivity coefficient, cross-sensitivity coefficient and ozone concentration simulation value under the basic scenario, the first-order sensitivity coefficient, second-order sensitivity coefficient, cross-sensitivity coefficient and ozone concentration simulation value under the 50% emission reduction scenario, and the first-order sensitivity coefficient, second-order sensitivity coefficient, cross-sensitivity coefficient and ozone concentration simulation value under the 75% emission reduction scenario;

[0072] Step 3: Calculate and obtain the first truncation point X and the second truncation point Y;

[0073] Step 4: Divide the emission reduction ratio into a first emission reduction sub-ratio of 0 to X, a second emission reduction sub-ratio of X to (X+Y), and a third emission reduction sub-ratio of (X+Y) to 100 according to the first cutoff point X and the second cutoff point Y;

[0074] Step 5: Calculate the ozone concentration change Δc1 corresponding to the first emission reduction sub-ratio, the ozone concentration change Δc2 corresponding to the second emission reduction sub-ratio, and the ozone concentration change Δc3 corresponding to the third emission reduction sub-ratio respectively;

[0075] Step 6: Integrate the ozone concentration change Δc1 corresponding to the first emission reduction sub-ratio, the ozone concentration change Δc2 corresponding to the second emission reduction sub-ratio, and the ozone concentration change Δc3 corresponding to the third emission reduction sub-ratio to obtain an estimated ozone concentration value;

[0076] Step 7: Draw the EKMA curve based on the estimated ozone concentration.

[0077] Example 2: A specific example of constructing an ozone concentration generation curve; the specific process of the example is as follows:

[0078] This example uses an ozone concentration curve construction method to select a day of mild pollution with ozone as the primary pollutant in HZ City on September 27 for research. The main steps are as follows:

[0079] Step 1: CAMx-HDDM model construction. The model adopts two-layer nesting. The central longitude and latitude of the model area are 105° east longitude and 36° north latitude. The first area is East Asia, with a horizontal resolution of 27 kilometers and a horizontal grid point number of 240×200; the second area is the southeastern coastal area of ​​China, with a horizontal resolution of 9 kilometers and a horizontal grid point number of 238×223. The meteorological model WRF provides meteorological fields for CAMx. The initial and boundary conditions in the WRF model are taken from the FNL (Final Reanalysis Data) data set jointly produced by the National Center for Meteorological and Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). CAMx-HDDM uses the CB06 chemical mechanism and AERO5 aerosol modules;

[0080] Step 2: Run three sets of CAMx-HDDM experiments to obtain the first-order sensitivity coefficient, second-order sensitivity coefficient and cross-sensitivity coefficient data sets and ozone concentration simulation values ​​under the base case, 50% emission reduction case and 75% emission reduction case;

[0081] Step 3: Calculate the emission reduction ratio for all grid points in Hangzhou in all time periods, and use the third-order optimization algorithm to calculate the value of the first cutoff point X to be 48, the value of the second cutoff point Y to be 21, and divide the emission reduction ratio into the first emission reduction sub-ratio (0-48), the second emission reduction sub-ratio (48-69) and the third emission reduction sub-ratio (69-100);

[0082] Step 4: When the emission reduction ratios of the precursors NOx and VOCs are increased from 0% to 100% by 1% (i.e. 0%, 1%, 2%, ..., 100%), the estimated ozone concentration is calculated using the formula corresponding to each emission reduction sub-ratio to form a data set;

[0083] Step 5: Draw the EKMA curve based on the data set (such as Figure 4 shown).

[0084] In the embodiments of the present application, words such as "first" and "second" are used to distinguish the same items or similar items with substantially the same functions and effects. For example, the first truncation point and the second truncation point are only used to distinguish different truncation points, and do not limit their order. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit them to be different.

[0085] It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" represent examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0086] In the embodiments of the present application, "at least one" refers to one or more, and "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can represent: a, b, c, ab, ac, bc or abc, where a, b, c can be single or multiple.

[0087] Figure 5 is a schematic block diagram of an ozone concentration generation curve construction system 500 provided in an embodiment of the present application. Figure 5 As shown, the ozone concentration generation curve construction system 500 includes a calculation module 501, an estimation module 502 and a drawing module 503.

[0088] The calculation module 501 is used to perform operation calculations on the target area based on the air quality model to obtain the sensitivity coefficients and ozone concentration simulation values ​​corresponding to the precursor emission reduction scenarios; the precursor emission reduction scenarios include: basic scenario, 50% emission reduction scenario and 75% emission reduction scenario; the sensitivity coefficients include: first-order sensitivity coefficient, second-order sensitivity coefficient and cross-sensitivity coefficient;

[0089] An estimation module 502, connected to the calculation module 501, is used to calculate and obtain an estimated value of ozone concentration by using a third-order optimization method based on the sensitivity coefficient corresponding to each emission reduction scenario and the ozone concentration simulation value;

[0090] The drawing module 503 is connected to the estimation module 502 and is used to generate an EKMA curve based on the ozone concentration estimation value.

[0091] It should be understood that the specific process of each module executing the above corresponding steps has been described in detail in the above method embodiment, and for the sake of brevity, it will not be repeated here.

[0092] It should also be understood that the division of modules in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present application may be integrated into a processor, or may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0093] For example, the above modules or units may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs). For another example, when a module is implemented in the form of a processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0094] Figure 6 is an electronic terminal provided in the embodiment of the present application. Figure 6 As shown, the electronic terminal 600 includes: at least one processor 601, a memory 602, at least one network interface 603 and a user interface 605. The various components in the device are coupled together through a bus system 604. It can be understood that the bus system 604 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 604 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, Figure 6 In the specification, various buses are labeled as bus systems.

[0095] The user interface 605 may include a display, a keyboard, a mouse, a trackball, a click gun, keys, buttons, a touch pad or a touch screen.

[0096] It is understood that the memory 602 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM). The memory described in the embodiments of the present invention is intended to include but is not limited to these and any other suitable categories of memory.

[0097] The memory 602 in the embodiment of the present invention is used to store various categories of data to support the operation of the electronic terminal 600. Examples of these data include: any executable program for operating on the electronic terminal 600, such as an operating system 6021 and an application 6022; the operating system 6021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application 6022 may include various applications, such as a media player (Media Player), a browser (Browser), etc., for implementing various application services. The ozone concentration generation curve construction method provided in the embodiment of the present invention may be included in the application 6022.

[0098] The method disclosed in the above embodiment of the present invention can be applied to the processor 601, or implemented by the processor 601. The processor 601 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 601 or the instruction in the form of software. The above processor 601 may be a general processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 601 can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiment of the present invention. The general processor 601 may be a microprocessor or any conventional processor, etc. In combination with the steps of the accessory optimization method provided in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0099] In an exemplary embodiment, the electronic terminal 600 may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD) to execute the aforementioned method.

[0100] According to the method provided in the embodiment of the present application, the present application also provides a computer-readable storage medium, which stores a program code, and when the program code is run on a computer, the computer executes Figure 1 to Figure 2 A method according to any one of the embodiments shown.

[0101] The terms "component", "module", "system", etc. used in this specification are used to represent computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program and / or a computer. By way of illustration, both applications running on a computing device and a computing device can be components. One or more components may reside in a process and / or an execution thread, and a component may be located on a computer and / or distributed between two or more computers. In addition, these components may be executed from various computer-readable media having various data structures stored thereon. Components may, for example, communicate through local and / or remote processes according to signals having one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system and / or a network, such as the Internet interacting with other systems through signals).

[0102] Those of ordinary skill in the art will appreciate that the various illustrative logical blocks and steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0103] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0104] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0105] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0106] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0107] In the above embodiments, the functions of each functional unit can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions (programs). When loading and executing computer program instructions (programs) on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media integrations. Available media may be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., high-density digital video discs (DVDs), or semiconductor media (e.g., solid state disks (SSDs), etc.).

[0108] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0109] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0110] In summary, the present application provides a method, system, medium and terminal for constructing an ozone concentration generation curve, including: based on an air quality model, running calculations on the target area to obtain sensitivity coefficients and ozone concentration simulation values ​​corresponding to each precursor emission reduction scenario; the precursor emission reduction scenarios include: basic scenario, 50% emission reduction scenario and 75% emission reduction scenario; the sensitivity coefficients include: first-order sensitivity coefficients, second-order sensitivity coefficients and cross-sensitivity coefficients; based on the sensitivity coefficients corresponding to each emission reduction scenario and the ozone concentration simulation value, a third-order optimization method is used to calculate and obtain an estimated ozone concentration value; and an EKMA curve is generated based on the ozone concentration estimate. The method for constructing an ozone generation concentration curve based on a sensitivity analysis tool based on third-order optimization proposed in the present application can not only improve the accuracy of ozone concentration estimation, but also reduce the number of model runs compared to the traditional method of drawing EKMA curves by running multiple groups of experiments based on an observation model, greatly saving memory resources and improving computational efficiency.

[0111] This application uses the sensitivity analysis tool (HDDM) in the air quality numerical model (CAMx) to calculate the first-order sensitivity coefficient, second-order sensitivity coefficient and cross-sensitivity coefficient of the change in ozone concentration to the precursors NOx and VOCs, respectively. Based on the third-order optimization concept, it achieves improvements in computational efficiency and accuracy. On this basis, the least squares method is used to establish a method for obtaining two cutoff points in the third-order optimization method, so that the error of ozone concentration estimation is further reduced. At the same time, compared with the traditional method of running multiple groups of experiments based on the observation model to draw the EKMA curve, the frequency of model operation is reduced, the number of operations is reduced, and computing time and memory resources can be saved. Therefore, this application effectively overcomes the various shortcomings in the prior art and has a high industrial utilization value.

[0112] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A method for constructing an ozone concentration generation curve, characterized in that: include: Based on the air quality model, the target area is run and calculated to obtain the sensitivity coefficients and ozone concentration simulation values ​​corresponding to each precursor emission reduction scenario; The precursor emission reduction scenarios include: basic scenario, 50% emission reduction scenario and 75% emission reduction scenario; the sensitivity coefficients include: first-order sensitivity coefficient, second-order sensitivity coefficient and cross-sensitivity coefficient; Based on the sensitivity coefficients corresponding to each emission reduction scenario and the ozone concentration simulation value, a third-order optimization method is used to calculate and obtain an estimated ozone concentration value; specifically, the method includes: obtaining a first cutoff point and a second cutoff point to divide the emission reduction ratio into various emission reduction sub-ratios; the emission reduction sub-ratios include: a first emission reduction sub-ratio, a second emission reduction sub-ratio and a third emission reduction sub-ratio; based on the sensitivity coefficients corresponding to each emission reduction scenario, the ozone concentration change corresponding to each emission reduction sub-ratio is calculated; based on the ozone concentration change under each emission reduction sub-ratio, the ozone concentration estimate is calculated; The method for obtaining the first truncation point includes: When the error between the change in ozone concentration under the second emission reduction sub-ratio and the simulated value of ozone concentration under the 50% emission reduction scenario is the smallest, the first truncation point is calculated; the calculation formula of the first truncation point is as follows: Among them, ε1 is the error between the change of ozone concentration under the second emission reduction sub-ratio and the simulated value of ozone concentration under the 50% emission reduction scenario, X is the first cutoff point, ΔC 50％ It is the simulated value of ozone concentration under the scenario of 50% emission reduction; The method for obtaining the second truncation point includes: When the error between the change in ozone concentration under the third emission reduction sub-ratio and the simulated value of ozone concentration under the 75% emission reduction scenario is the smallest, the second truncation point is calculated; the calculation formula of the second truncation point is as follows: Wherein, ε2 is the error between the change in ozone concentration under the third emission reduction sub-ratio and the simulated value of ozone concentration under the 75% emission reduction scenario, X is the first cutoff point, Y is the second cutoff point, ΔC 75％ This is the simulated value of ozone concentration under the scenario of 75% emission reduction; Dividing the emission reduction ratio into a first emission reduction sub-ratio, a second emission reduction sub-ratio and a third emission reduction sub-ratio according to a first cutoff point and a second cutoff point; The calculation formula for the change in ozone concentration under the first emission reduction sub-ratio is as follows: Where Δc1 is the change in ozone concentration under the first emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of the precursor NOx under the basic scenario, is the first-order sensitivity coefficient of precursor VOCs under the basic scenario, is the second-order sensitivity coefficient of the precursor NOx under the basic scenario, is the second-order sensitivity coefficient of precursor VOCs under the basic scenario, The cross-sensitivity coefficients of precursors NOx and VOCs under the basic scenario; The calculation formula for the change in ozone concentration under the second emission reduction sub-ratio is as follows: Where Δc2 is the change in ozone concentration under the second emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of precursor NOx under the scenario of 50% emission reduction, is the first-order sensitivity coefficient of precursor VOCs under the scenario of 50% emission reduction, is the second-order sensitivity coefficient of the precursor NOx under the 50% emission reduction scenario, is the second-order sensitivity coefficient of precursor VOCs under the 50% emission reduction scenario, is the cross-sensitivity coefficient of precursor NOx and VOCs under the scenario of 50% emission reduction, c adjust-50％ The ozone concentration adjustment for a 50% reduction scenario; The calculation formula for the change in ozone concentration under the third emission reduction sub-ratio is as follows: Where Δc3 is the change in ozone concentration under the third emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of precursor NOx under the 75% emission reduction scenario, is the first-order sensitivity coefficient of precursor VOCs under the 75% emission reduction scenario, is the second-order sensitivity coefficient of the precursor NOx under the 75% emission reduction scenario, is the second-order sensitivity coefficient of precursor VOCs under the 75% emission reduction scenario, is the cross-sensitivity coefficient of precursor NOx and VOCs under the 75% emission reduction scenario, c adjust-75％ The ozone concentration adjustment for a 75% reduction scenario; An EKMA curve is generated based on the ozone concentration estimate.

2. A system for constructing an ozone concentration generation curve, characterized in that: include: A calculation module is used to perform operation calculations on the target area based on the air quality model to obtain the sensitivity coefficients and ozone concentration simulation values ​​corresponding to each precursor emission reduction scenario; The precursor emission reduction scenarios include: basic scenario, 50% emission reduction scenario and 75% emission reduction scenario; the sensitivity coefficients include: first-order sensitivity coefficient, second-order sensitivity coefficient and cross-sensitivity coefficient; An estimation module, connected to the calculation module, is used to calculate and obtain an estimated ozone concentration value by using a third-order optimization method based on the sensitivity coefficient corresponding to each emission reduction scenario and the ozone concentration simulation value; specifically comprising: obtaining a first cutoff point and a second cutoff point to divide the emission reduction ratio into various emission reduction sub-ratios; the emission reduction sub-ratios include: a first emission reduction sub-ratio, a second emission reduction sub-ratio and a third emission reduction sub-ratio; calculating and obtaining an ozone concentration change corresponding to each emission reduction sub-ratio based on the sensitivity coefficient corresponding to each emission reduction scenario; and calculating and obtaining an estimated ozone concentration value based on the ozone concentration change under each emission reduction sub-ratio; The method for obtaining the first truncation point includes: When the error between the change in ozone concentration under the second emission reduction sub-ratio and the simulated value of ozone concentration under the 50% emission reduction scenario is the smallest, the first truncation point is calculated; the calculation formula of the first truncation point is as follows: Among them, ε1 is the error between the change of ozone concentration under the second emission reduction sub-ratio and the simulated value of ozone concentration under the 50% emission reduction scenario, X is the first cutoff point, ΔC 50％ It is the simulated value of ozone concentration under the scenario of 50% emission reduction; The method for obtaining the second truncation point includes: When the error between the change in ozone concentration under the third emission reduction sub-ratio and the simulated value of ozone concentration under the 75% emission reduction scenario is the smallest, the second truncation point is calculated; the calculation formula of the second truncation point is as follows: Wherein, ε2 is the error between the change in ozone concentration under the third emission reduction sub-ratio and the simulated value of ozone concentration under the 75% emission reduction scenario, X is the first cutoff point, Y is the second cutoff point, ΔC 75％ This is the simulated value of ozone concentration under the scenario of 75% emission reduction; Dividing the emission reduction ratio into a first emission reduction sub-ratio, a second emission reduction sub-ratio and a third emission reduction sub-ratio according to a first cutoff point and a second cutoff point; The calculation formula for the change in ozone concentration under the first emission reduction sub-ratio is as follows: Where Δc1 is the change in ozone concentration under the first emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of the precursor NOx under the basic scenario, is the first-order sensitivity coefficient of precursor VOCs under the basic scenario, is the second-order sensitivity coefficient of the precursor NOx under the basic scenario, is the second-order sensitivity coefficient of precursor VOCs under the basic scenario, The cross-sensitivity coefficients of precursors NOx and VOCs under the basic scenario; The calculation formula for the change in ozone concentration under the second emission reduction sub-ratio is as follows: Where Δc2 is the change in ozone concentration under the second emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of precursor NOx under the scenario of 50% emission reduction, is the first-order sensitivity coefficient of precursor VOCs under the scenario of 50% emission reduction, is the second-order sensitivity coefficient of the precursor NOx under the 50% emission reduction scenario, is the second-order sensitivity coefficient of precursor VOCs under the 50% emission reduction scenario, is the cross-sensitivity coefficient of precursor NOx and VOCs under the scenario of 50% emission reduction, c adjust-50％ The ozone concentration adjustment for a 50% reduction scenario; The calculation formula for the change in ozone concentration under the third emission reduction sub-ratio is as follows: Where Δc3 is the change in ozone concentration under the third emission reduction sub-ratio, λ nox is the percentage change of NOx emission reduction of precursor, λ voc is the percentage change of precursor VOCs emission reduction, is the first-order sensitivity coefficient of precursor NOx under the 75% emission reduction scenario, is the first-order sensitivity coefficient of precursor VOCs under the 75% emission reduction scenario, To reduce The second-order sensitivity coefficient of the precursor NOx under the 75% emission scenario is: is the second-order sensitivity coefficient of precursor VOCs under the 75% emission reduction scenario, is the cross-sensitivity coefficient of precursor NOx and VOCs under the 75% emission reduction scenario, c adjust-75％ The ozone concentration adjustment for a 75% reduction scenario; A drawing module is connected to the estimation module and is used to generate an EKMA curve based on the ozone concentration estimation value.

3. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for constructing an ozone concentration generation curve according to claim 1 is implemented.

4. An electronic terminal comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the ozone concentration generation curve construction method according to claim 1.

Images