CN112381341B - Regional air quality control measure effect evaluation method - Google Patents
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Abstract
The invention provides a regional air quality control measure effect evaluation method, which comprises the following steps: determining a space-time range of the atmospheric pollution control effect evaluation; configuring mode parameters; performing space-time distribution on the pollutant emission source list data; operating an air quality numerical model to obtain a functional relation between the amount of the emission precursor emitted by each pollutant emission source and the grid point pollutant step-by-step reference simulated concentration; calculating the contribution of each surface source control measure and point source control measure to the reduction of the pollutant concentration; and respectively obtaining the contribution rate of each control measure to the pollutant concentration improvement effect, and realizing the evaluation of the pollutant concentration improvement effect of each control measure. According to the method, the influence of different control measures on the regional air quality can be rapidly calculated based on the contribution of the source analysis result, so that a large amount of calculation overhead and time consumption of mode scene simulation are saved, and the rapid optimization of the control measures can be further realized.
Description
Technical Field
The invention belongs to the technical field of environmental protection, and particularly relates to a regional air quality control measure effect evaluation method.
Background
The atmospheric heavy pollution emergency plan includes a series of pollution control measures. In order to gradually improve the effectiveness of measures and plans, quantitative evaluation and optimization of the implementation effect are very important links.
At present, the commonly used method for quantitatively evaluating the atmospheric pollution control measures comprises the following steps: an air quality numerical mode scenario simulation method and a Response Surface Model (RSM) method. For the air quality numerical mode scene simulation method, when a plurality of sets of different control measures need to be evaluated, an emission source list needs to be regenerated and an air quality mode needs to be operated for each control measure, and the operation process is complex and the calculation efficiency is low. Specifically, for a set of heavy pollution emergency plans, which include a series of pollution control measures, the scene simulation method for the air quality numerical value mode needs to perform individual scene simulation for each pollution control measure included in the plan, and the set of plans generally includes 5 to 10 pollution control measures, so that when the scene simulation method is used for evaluation, the air quality numerical value mode needs to be independently operated for 5 to 10 times, the efficiency is extremely low, multiple sets of heavy pollution emergency plans cannot be quickly evaluated, and quick screening of different sets of heavy pollution emergency plans cannot be realized.
For the response surface model method, a large number of scenario simulations need to be carried out, so that a functional relation between pollutant concentration and emission source emission under corresponding meteorological conditions is established, and finally the control effect of atmospheric pollution is evaluated based on the functional relation. The response function relationship between the pollutant concentration and the emission source emission amount is constructed by the method, tens of groups to hundreds of groups of mode scene simulation is usually required, and the function relationship is required to be re-simulated and constructed under different meteorological conditions. Therefore, the calculation amount is huge, a large amount of computer resources (500-.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method for evaluating the effect of regional air quality control measures, which can effectively solve the problems.
The technical scheme adopted by the invention is as follows:
the invention provides a regional air quality control measure effect evaluation method, which comprises the following steps:
configuring mode parameters; inputting and operating a mesoscale meteorological model for the assessed geographic area over an assessment time horizon [ t ]1,t2]Simulating the meteorological data in the area, and outputting the evaluation time range [ t ] of each grid point in the evaluation geographical area1,t2]Time-by-time meteorological simulation data;
Ea,d,kthe meaning is as follows: in a geographic position, a pollutant emission source belonging to the d industry class emits the k pollutant WkThe total annual emission;
evaluating each grid point in the geographic area for an evaluation time range [ t ]1,t2]Time-by-time weather simulation data within, and each grid point in the estimated geographic area at an estimated time horizon [ t ]1,t2]Internal time-by-time pollutant emission Qk,d(i, j) inputting and operating together an air quality number model coupled with an online pollution source analysis module, said air quality number model outputting a time-wise reference simulated concentration C of each pollutant without taking any control measures0,k(i,j)，C0,k(i, j) have the following specific meanings: the kth contaminant WkSimulating the concentration of the (i, j) th grid point time-by-time basis; subscript 0 represents a reference;
step 4, determining the kth pollutant WkDischarge precursor M ofk(ii) a The discharge precursor MkIs at least one;
operating an air quality numerical mode to obtain each pollutant emission source Ea,dDischarged discharge precursor MkThe amount of (i) and the k-th pollutant W of the (i, j) th grid pointkTime-by-time reference analog concentration C of0,k(i, j), i.e. the emission-concentration response relationship, i.e. obtaining the emission source E of each pollutanta,dDischarged discharge precursor MkFor the k-th pollutant W of the (i, j) th grid pointkTime-by-time reference analog concentration C of0,kContribution R of (i, j)a,d,k(i,j)；
Step 5, reading each non-point source control measure A to be evaluateda，AaThe meaning is as follows: a, a surface source control measure taken at a geographic position;
then, determining each non-point source control measure A according to the functional relation between the emission source emission amount and the pollutant concentration established by source analysisaThe affected source analysis industry u obtains each non-point source control measure AaTo pollutant emission source Ea,dDischarged discharge precursor MkArea source control measure reduction rate MAa,u(Aa,Mk) (ii) a Wherein u belongs to d;
calculating various surface source control measures A by adopting the following formulaaFor the k-th pollutant WkContribution of concentration reduction Pa,u,k：
Pa,u,k＝C0,k(i,j)·MAa,u(Aa,Mk)·Ra,d,k(i,j)
Wherein: u is an element of d;
when the k-th pollutant WkWhen a plurality of precursors are provided, the contribution of the surface source control measure to the concentration reduction of the precursors is calculated for each precursor, and finally, the sum is carried out, so that the contribution of the surface source control measure to the kth pollutant W is obtainedkThe total contribution of the concentration reduction, namely: the following formula is used for calculation:
wherein:
step 6, reading each point source control measure B to be evaluateda，BaThe meaning is as follows: point source control measure B taken at geographical position aa；
Then, determining each point source control measure B according to the functional relation between the emission source emission amount and the pollutant concentration established by source analysisaThe affected source analysis industry u obtains each point source control measure BaTo pollutant emission source Ea,dDischarged discharge precursor MkPoint source control measure reduction rate MP of discharge amounta,u(Ba,Mk) And obtaining: each emission precursor MkPoint source emission quantity EP performed by pollutant emission sources of u industry classes at corresponding pollutant emission source geographical position aa,u(Mk)；
Calculating the contribution of each point source control measure to the reduction amount of the pollutant concentration:
by the formulaCalculating each point source control measure BaFor the k-th pollutant WkDP contribution of concentration reductiona,u,k：
Wherein: u is an element of d;
when the k-th pollutant WkWith multiple precursors, point source control measure B is calculated for each precursoraThe contribution to the reduction of the precursor concentration is finally summed to obtain the point source control measure BaFor the k-th pollutant WkThe total contribution of the concentration reduction, namely: the following formula is used for calculation:
wherein:
and dividing the contribution of the point source or surface source control measures to the reduction amount of the concentration of the atmospheric pollutants by the total contribution to respectively obtain the contribution rate of each control measure to the improvement effect of the concentration of the pollutants, and further comparing the contribution of various control measures to the improvement effect of the concentration of the pollutants to evaluate the improvement effect of various control measures to the concentration of the pollutants.
Preferably, in step 1, the configured mode parameters include mode initial conditions, boundary conditions, grid number of the evaluation geographic area, and physical parameterization scheme configuration parameters.
The method for evaluating the effect of the regional air quality control measure provided by the invention has the following advantages:
according to the method, the influence of different control measures on the regional air quality can be rapidly calculated based on the contribution of the source analysis result, so that a large amount of calculation overhead and time consumption of mode scene simulation are saved, and the rapid optimization of the control measures can be further realized.
Drawings
FIG. 1 is a schematic flow chart illustrating a method for evaluating the effectiveness of regional air quality control measures according to the present invention;
FIG. 2 shows the control measures obtained by the present invention for a PM of a certain city2.5Contribution amount of concentration improvement effect;
FIG. 3 shows the control measures obtained by the present invention for a PM of a certain city2.5Concentration improvement effect contribution rate;
FIG. 4 shows a diagram of PM of a certain city according to control measures obtained by a conventional scenario simulation method2.5Contribution amount of concentration improvement effect;
FIG. 5 shows a diagram of PM of a certain city according to control measures obtained by a conventional scenario simulation method2.5The concentration-improving effect contribution rate.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In order to overcome the defects of the traditional air quality control measure effect evaluation method, the invention provides the regional air quality control measure effect evaluation method, which solves the problems of high calculation cost and low efficiency of traditional pollution control measure effect evaluation on the premise of not repeatedly operating an air quality numerical mode, thereby better supporting an environmental protection service department to dynamically evaluate and optimally adjust the effectiveness of control measures in an atmosphere heavy pollution emergency control scheme in real time. Specifically, under the condition of reasonable calculation resource overhead, the method can quickly and quantitatively evaluate the air quality improvement effect of a plurality of control measures in the air quality emergency plan before or after the atmospheric pollution occurs, support the comparison and optimization of the control effect of the control measures, and improve the effectiveness of the emergency plan.
The method specifically comprises the following advantages:
(1) according to the invention, the emission-concentration response relation is established based on the air quality mode source analysis result, so that the phenomenon that the air quality numerical value mode is re-operated when different emission reduction measures are evaluated is avoided, and the evaluation speed is increased;
in particular, the contribution R calculated in step 4 of the present inventiona,d,k(i, j) is applicable to different control measures, so that R is obtained by running the air quality numerical mode oncea,d,kAfter (i, j), the air quality number mode is not operated again.
(2) Based on the air quality mode source analysis result, the method can quantitatively evaluate the contribution of each control measure to the air quality improvement effect through one-time calculation, and realizes the quick optimization of the control measure.
Specifically, the conventional scenario simulation method needs to perform multiple sets of scenario simulations on different control measures to obtain the influence of the different control measures on the air quality, for example, if 50 control measures need to be evaluated, 50 times of scenario simulations are required, which consumes a large amount of computing resources and time. Contribution R of source analysis result based on the inventiona,d,k(i, j) the influence of different management and control measures on the regional air quality can be rapidly calculated, calculation overhead and time consumption of a large amount of mode scene simulation are saved, and rapid optimization of the management and control measures can be further achieved.
Referring to fig. 1, the present invention provides a method for evaluating the effect of regional air quality control measures, including the following steps:
configuring mode parameters; the configured mode parameters include mode initial conditions, boundary conditions, grid number of the evaluation geographical area, and physical parameterization scheme configuration parameters. Inputting and operating a mesoscale meteorological model for the assessed geographic area over an assessment time horizon [ t ]1,t2]Simulating the meteorological data in the area, and outputting the evaluation time range [ t ] of each grid point in the evaluation geographical area1,t2]Time-by-time meteorological simulation data;
Ea,d,kthe meaning is as follows: in a geographic position, a pollutant emission source belonging to the d industry class emits the k pollutant WkThe total annual emission;
specifically, the pollutant emission source inventory data is an important basis for air quality monitoring data analysis, pollutant emission trend analysis, model research and relevant control strategy formulation.
Pollutant emission source inventory data records major pollutants (including SO) in different regions and industries2、NOxCO, Primary PM2.5Primary PM10、NH3VOCs).
evaluating each grid point in the geographic area for an evaluation time range [ t ]1,t2]Time-by-time weather simulation data within, and each grid point in the estimated geographic area at an estimated time horizon [ t ]1,t2]Internal time-by-time pollutant emission Qk,d(i, j) inputting and operating together an air quality number model coupled with an online pollution source analysis module, said air quality number model outputting a time-wise reference simulated concentration C of each pollutant without taking any control measures0,k(i,j)，C0,k(i, j) have the following specific meanings: the kth contaminant WkSimulating the concentration of the (i, j) th grid point time-by-time basis; subscript 0 represents a reference;
the online pollution source analysis module comprises, but is not limited to, NAQPMS-OSAM, CAMx-PSAT, CAMx-OSAT and the like.
Step 4, determining the kth pollutant WkDischarge precursor M ofk(ii) a The discharge precursor MkIs at least one;
operating an air quality numerical mode to obtain each pollutant emission source Ea,dDischarged discharge precursor MkThe amount of (i) and the k-th pollutant W of the (i, j) th grid pointkTime-by-time reference analog concentration C of0,k(i, j), i.e. the emission-concentration response relationship, i.e. obtaining the emission source E of each pollutanta,dDischarged discharge precursor MkFor the k-th pollutant W of the (i, j) th grid pointkTime-by-time reference analog concentration C of0,kContribution R of (i, j)a,d,k(i,j)；
For example, as shown in table 1, the relationship between each atmospheric pollutant and its emission precursor is shown.
TABLE 1 correspondence of emission precursor to atmospheric pollutants
Therefore, when the atmospheric pollutant to be studied is SO2Then the obtained emission precursor is SO2And at the moment, the SO discharged by each region and industry within the range of the simulated space region is obtained by operating the air quality numerical mode2SO for each pattern grid2The time-wise reference simulates the contribution of the concentration. For example, for a certain pattern grid, when the concentration is simulated on a time-by-time basis, the contribution of the steel industry in area a is 10%; the contribution of the chemical industry in the B area is 70 percent and the like.
For PM2.5And PM10For example, because it has a plurality of emission precursors, the following is used: by PM2.5For example, there are five emission precursors, respectively: primary PM2.5、SO2、NOx、NH3And VOCs; first, PM is obtained once for each pattern mesh2.5Time-wise reference analog concentrations of sulfate, nitrate, ammonium salt and secondary organic aerosol; then, primary PM discharged by each region and industry within the range of the simulated space region is obtained2.5Primary PM to pattern grid2.5Time-wise reference modeling the contribution of concentration; likewise, SO discharged from various regions and industries is obtained2Contribution to the time-wise reference simulated concentration of sulfate for the pattern grid; obtaining NO emitted by various regions and industriesxContribution to the time-wise reference simulated concentration of nitrates of the pattern grid; ammonium salts and secondary organic aerosols also receive corresponding contributions.
Step 5, reading each non-point source control measure A to be evaluateda，AaThe meaning is as follows: a, a surface source control measure taken at a geographic position;
then, according to the functional relation between the emission source emission amount and the pollutant concentration established by source analysis, each non-point source control measure is determinedApplication to AaThe affected source analysis industry u obtains each non-point source control measure AaTo pollutant emission source Ea,dDischarged discharge precursor MkArea source control measure reduction rate MAa,u(Aa,Mk) (ii) a Wherein u belongs to d;
calculating various surface source control measures A by adopting the following formulaaFor the k-th pollutant WkContribution of concentration reduction Pa,u,k：
Pa,u,k＝C0,k(i,j)·MAa,u(Aa,Mk)·Ra,d,k(i,j)
Wherein: u is an element of d;
when the k-th pollutant WkWhen a plurality of precursors are provided, the contribution of the surface source control measure to the concentration reduction of the precursors is calculated for each precursor, and finally, the sum is carried out, so that the contribution of the surface source control measure to the kth pollutant W is obtainedkThe total contribution of the concentration reduction, namely: the following formula is used for calculation:
wherein:
for example, suppose the atmospheric pollutant to be studied is SO2The current non-point source control measure to be evaluated is a non-point source control measure B1, and the SO of the non-point source control measure B1 on a certain pattern grid is obtained2Emission reduction rate MA1,uUsing reduction ratio MA1,u、SO2Time-by-time reference analog concentration C of contaminants0,k(i, j) and SO2SO discharged from discharge source2Time-by-time reference analog concentration C of lattice points0,kContribution R of (i, j)a,d,k(i, j), obtaining the surface source control measures B1 to SO2Contribution of reduced concentration.
Step 6, reading each point source control measure B to be evaluateda，BaThe meaning is as follows: point source control measure B taken at geographical position aa；
Then, determining each point source control measure B according to the functional relation between the emission source emission amount and the pollutant concentration established by source analysisaThe affected source analysis industry u obtains each point source control measure BaTo pollutant emission source Ea,dDischarged discharge precursor MkPoint source control measure reduction rate MP of discharge amounta,u(Ba,Mk) And obtaining: each emission precursor MkPoint source emission quantity EP performed by pollutant emission sources of u industry classes at corresponding pollutant emission source geographical position aa,u(Mk)；
Calculating the contribution of each point source control measure to the reduction amount of the pollutant concentration:
calculating each point source control measure B by adopting the following formulaaFor the k-th pollutant WkDP contribution of concentration reductiona,u,k：
Wherein: u is an element of d;
when the k-th pollutant WkWith multiple precursors, point source control measure B is calculated for each precursoraThe contribution to the reduction of the precursor concentration is finally summed to obtain the point source control measure BaFor the k-th pollutant WkThe total contribution of the concentration reduction, namely: the following formula is used for calculation:
wherein:
and dividing the contribution of the point source or surface source control measures to the reduction amount of the concentration of the atmospheric pollutants by the total contribution to respectively obtain the contribution rate of each control measure to the improvement effect of the concentration of the pollutants, and further comparing the contribution of various control measures to the improvement effect of the concentration of the pollutants to evaluate the improvement effect of various control measures to the concentration of the pollutants.
One embodiment is described below:
this section specifically illustrates the advantages of the present invention over conventional scene simulation methods by one embodiment.
Respectively adopting the method and the traditional scene simulation method to predict and evaluate PM in a certain area from 2016, 12 and 13 months to 2016, 12 and 23 months2.5And comparing the control effect of each level of emergency plan in the pollution process with the result and the calculation efficiency of the emergency plan.
The results of the red early warning scheme adopted in a certain area evaluated by the method of the invention are shown in fig. 2 and fig. 3. Wherein, FIG. 2 shows the PM of a certain city according to the control measures calculated by the present invention2.5Contribution amount of concentration improving effect. FIG. 3 shows the calculated control measures for a PM of a certain city2.5The concentration-improving effect contribution rate.
As can be seen from the figures 2 and 3, the three most effective treatment measures of controlling pollution of a certain city are iron and steel smelting reduction, cement and building material industry peak load shifting reduction and construction dust control, and PM in a heavy pollution period of a certain city is respectively controlled2.5The concentration was reduced by 19.4. mu.g m-3、12.2μg*m-3And 2.8. mu.g m-3For a certain city PM2.5The contributions of the concentration-improving effect were 52.3%, 32.9% and 7.7%, respectively.
After a red early warning scheme is adopted in a certain area of the traditional scene simulation evaluation, the result is shown in fig. 4 and fig. 5. Wherein, fig. 4 shows the control measures calculated by the traditional scene simulation method for the PM in a certain city2.5Contribution amount of concentration improving effect. FIG. 5 shows a PM of a certain city calculated by each control measure in the conventional scenario simulation method2.5The concentration-improving effect contribution rate.
The evaluation result shows that in the heavy pollution period of a certain area, compared with the traditional scene simulation method, the effect of the management and control measures evaluated by the method is similar to that obtained by the traditional scene simulation method, and the error range is within the calculation error range of the mode and belongs to an acceptable range. For computational efficiency, the contribution of 7 management and control measures to the improvement of air quality was evaluated using 64 computational cores, and the present invention took 53 minutes (including pollution source prediction and baseline simulation prediction time). And the traditional scene simulation method is applied, the same computing resources are adopted, the same region and the same control measures are evaluated, and 268 minutes is consumed. Therefore, the invention can obviously improve the evaluation efficiency on the premise of reliable evaluation results.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements should also be considered within the scope of the present invention.
Claims (2)
1. A regional air quality control measure effect evaluation method is characterized by comprising the following steps:
step 1, determining a space-time range for evaluating an atmospheric pollution control effect; wherein the spatiotemporal range includes an evaluation geographic region and an evaluation time range [ t1,t2](ii) a Wherein, t1To evaluate the starting time of the time range; t is t2To evaluate the end time of the time range;
configuring mode parameters; inputting and operating a mesoscale meteorological model for the assessed geographic area over an assessment time horizon [ t ]1,t2]Simulating the meteorological data in the area, and outputting the evaluation time range [ t ] of each grid point in the evaluation geographical area1,t2]Time-by-time meteorological simulation data;
step 2, reading a pre-stored pollutant emission source list of main pollutants in different areas and industries; wherein the pollutant emission source list comprises a plurality of pieces of pollutant emission source data, each piece of pollutant emission source data is represented as Ea,d,kWherein k represents the kth contaminant Wk(ii) a a represents the geographical position of a pollutant emission source; a belongs to A, and A represents a set of all geographical position marks divided during mode simulation; d represents the industry category corresponding to the pollutant emission source; d belongs to D, and D represents all industry classes in the pollutant emission source list;
Ea,d,kthe meaning is as follows: in geographic location a, pollutant emissions belonging to the category of industry dSource, discharge of kth pollutant WkThe total annual emission;
step 3, performing space-time distribution on pollutant emission source data of the pollutant emission source list to obtain an evaluation time range [ t ] of each grid point in the evaluation geographical area1,t2]Time-by-time pollutant emission data Qk,d(i,j)；
Qk,d(i, j) have the following specific meanings: kth pollutant W of the d-th industryk(ii) time-wise pollutant emissions at the (i, j) th grid point;
evaluating each grid point in the geographic area for an evaluation time range [ t ]1,t2]Time-by-time weather simulation data within, and each grid point in the estimated geographic area at an estimated time horizon [ t ]1,t2]Internal time-by-time pollutant emission Qk,d(i, j) inputting and operating together an air quality number model coupled with an online pollution source analysis module, said air quality number model outputting a time-wise reference simulated concentration C of each pollutant without taking any control measures0,k(i,j)，C0,k(i, j) have the following specific meanings: the kth contaminant WkSimulating the concentration of the (i, j) th grid point time-by-time basis; subscript 0 represents a reference;
step 4, determining the kth pollutant WkDischarge precursor M ofk(ii) a The discharge precursor MkIs at least one;
operating an air quality numerical mode to obtain each pollutant emission source Ea,dDischarged discharge precursor MkThe amount of (i) and the k-th pollutant W of the (i, j) th grid pointkTime-by-time reference analog concentration C of0,k(i, j), i.e. the emission source emission and pollutant concentration, i.e. obtaining the emission source E of each pollutanta,dDischarged discharge precursor MkFor the k-th pollutant W of the (i, j) th grid pointkTime-by-time reference analog concentration C of0,kContribution R of (i, j)a,d,k(i,j)；
Step 5, reading each non-point source control measure A to be evaluateda，AaThe meaning is as follows:a, a surface source control measure taken at a geographic position;
then, determining each non-point source control measure A according to the functional relation between the emission source emission amount and the pollutant concentration established by source analysisaThe affected source analysis industry u obtains each non-point source control measure AaTo pollutant emission source Ea,dDischarged discharge precursor MkArea source control measure reduction rate MAa,u(Aa,Mk) (ii) a Wherein u belongs to d;
calculating various surface source control measures A by adopting the following formulaaFor the k-th pollutant WkContribution of concentration reduction Pa,u,k：
Pa,u,k＝C0,k(i,j)·MAa,u(Aa,Mk)·Ra,d,k(i,j)
Wherein: u is an element of d;
when the k-th pollutant WkWhen a plurality of precursors are provided, the contribution of the surface source control measure to the concentration reduction of the precursors is calculated for each precursor, and finally, the sum is carried out, so that the contribution of the surface source control measure to the kth pollutant W is obtainedkThe total contribution of the concentration reduction, namely: the following formula is used for calculation:
wherein:
step 6, reading each point source control measure B to be evaluateda，BaThe meaning is as follows: point source control measure B taken at geographical position aa；
Then, determining each point source control measure B according to the functional relation between the emission source emission amount and the pollutant concentration established by source analysisaThe affected source analysis industry u obtains each point source control measure BaTo pollutant emission source Ea,dDischarged discharge precursor MkPoint source control measure reduction rate MP of discharge amounta,u(Ba,Mk) And obtaining: each emission precursor MkPoint source emission quantity EP performed by pollutant emission sources of u industry classes at corresponding pollutant emission source geographical position aa,u(Mk)；
Calculating the contribution of each point source control measure to the reduction amount of the pollutant concentration:
calculating each point source control measure B by adopting the following formulaaFor the k-th pollutant WkDP contribution of concentration reductiona,u,k：
Wherein: u is an element of d;
when the k-th pollutant WkWith multiple precursors, point source control measure B is calculated for each precursoraThe contribution to the reduction of the precursor concentration is finally summed up and further collectedPoint source control measure BaFor the k-th pollutant WkThe total contribution of the concentration reduction, namely: the following formula is used for calculation:
wherein:
cmp is equal to 1.. z, which is the identity of one of the z precursors of the atmospheric pollutant PM;
step 7, calculating the contribution DP of various point source control measures to the reduction of the concentration of the atmospheric pollutantsa,u,kAnd the contribution P of various non-point source control measures to the reduction of the concentration of the atmospheric pollutantsa,u,kSumming to obtain the total contribution of the control measures to the reduction of the concentration of the pollutants;
and dividing the contribution of the point source or surface source control measures to the reduction amount of the concentration of the atmospheric pollutants by the total contribution to respectively obtain the contribution rate of each control measure to the improvement effect of the concentration of the pollutants, and further comparing the contribution of various control measures to the improvement effect of the concentration of the pollutants to evaluate the improvement effect of various control measures to the concentration of the pollutants.
2. The method for evaluating the effect of a regional air quality control measure according to claim 1, wherein in step 1, the configured mode parameters comprise mode initial conditions, boundary conditions, grid number of the evaluation geographical region and physical parameterization scheme configuration parameters.
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