Source analysis method and emergency response system based on weather typing and meteorological forecast

Abstract

The application provides a source analysis method and an emergency response system based on weather classification and meteorological forecast. The application obtains data information required for atmospheric pollution source analysis and air quality fine management and control, stores the data information as a basic database after standardization and gridization processing, uses a weather classification tool to screen the best weather classification method suitable for the local area, combines a source analysis model to construct a source analysis case library under different weather classifications, classifies the weather according to the meteorological element forecast result obtained from the government weather forecast, calls the corresponding case in the source analysis case library, selects the emergency emission reduction measures of the corresponding grid atmospheric pollution source and constructs an emergency emission reduction scheme according to the pollution source contribution ratio and the wind speed and direction distribution in the case, the pollutant emission reduction ratio corresponding to the measures and the cost ranking, calculates the atmospheric pollutant emission reduction amount of the emission reduction scheme, calculates the air quality target accessibility by using a response function set of the atmospheric pollutant and the precursor, and optimizes the emergency emission reduction scheme based on the air quality target accessibility.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of environmental monitoring and emergency prevention and control, in particular, especially relates to a source analysis method based on weather typing and meteorological forecast and an emergency response system. BACKGROUND

[0002] Fine management of air quality is the future development trend of air pollution prevention and control, and the meteorology and source analysis as important influencing factors are included in the prevention and control system, which is an important step of fine management. The invention of constructing a rapid emergency prevention and control system by combining weather typing and source analysis has not been reported.

[0003] The present application allocates source emission contribution to high-resolution geographic information grid under the background of weather typing, determines the demand for prevention and control measures according to the air quality prediction results, and constructs a dynamic measure set to solve the problems of regional air quality fine management and rapid emergency prevention and control, which has the significance of reducing waste of social resources, reducing economic losses of enterprises and precise prevention and control according to local conditions. SUMMARY

[0004] In view of the technical limitations of fine management of air quality in the field of air pollution prevention and control, the present application provides a source analysis method based on weather typing and meteorological forecast, an emergency response method and system. The present application can realize the purposes of localizing weather typing method optimization, grid allocation of pollution source contribution and rapid reaction to formulate emergency scheme plan.

[0005] The technical means adopted by the present application are as follows:

[0006] A source analysis method based on weather typing and meteorological forecast, comprising the following steps:

[0007] Obtaining localized basic information data, the obtained basic information data includes geographic information data, emission source information, social and economic data, historical meteorological data and air quality data, and the above information is standardized and grid processed and stored, thereby constructing a basic database;

[0008] The applicable area is standardized and grid processed based on the geographic information data, the basic information of the corresponding grid unit is imported and updated to the basic information;

[0009] The weather typing method is screened based on the Euclidean distance method, and the most optimal local typing method is determined to build a weather typing module;

[0010] The historical meteorological data is imported into the weather typing module for weather typing, the spatiotemporal distribution rule of pollutants under each weather type is analyzed, and the main pollution parameters are determined;

[0011] The pollution emission information based on the grid unit is associated with the weather type to perform source analysis, a localized source classification system is constructed, the contribution proportion of the pollution source under the weather type is quantified, and thus a source analysis case library under each weather type is constructed.

[0012] Further, the weather typing method is screened based on the Euclidean distance method, including: taking the difference between groups after typing as the basis, and using a weather typing tool to complete; the typing tool includes the European Union COST 733, and the algorithm in the typing tool includes a neural network method, a K value method and a naive Bayes method.

[0013] Further, the source analysis is used to actually reflect the local source contribution, and the source analysis method includes online source analysis or PMF;

[0014] The historical source analysis case needs to be classified according to meteorological elements under different weather types, and the source contribution category is consistent with the local pollution source emission inventory classification system;

[0015] The transmission area grading of the source analysis case library and the pollution source contribution ratio can be dynamically updated, the method for performing the transmission area grading includes a backward trajectory model method or a meteorological model method, the grid through which the air mass is transported during the pollution period of a specific weather type is identified by using the backward trajectory model method or the meteorological model method, the transmission area grid is graded according to the wind direction and wind speed distribution, and the pollution source contribution ratio under different weather types under the main wind direction and wind speed is calculated by combining the source analysis method.

[0016] The application further discloses an emergency response system, comprising:

[0017] A model construction unit is configured to construct a source analysis empirical model, and the source analysis empirical model is configured to implement the source analysis method of any one of the above.

[0018] A calculation unit is configured to obtain air quality forecast data, compare the air quality forecast data with a regional target limit value, and calculate a target emission reduction amount of a precursor according to a relationship response function set of atmospheric pollutants and precursors.

[0019] A cost-effectiveness analysis basic data set construction unit is configured to obtain emission reduction measures and emission reduction proportions and implementation costs of the emission reduction measures under different implementation intensity gradings, so as to construct a cost-effectiveness analysis basic data set.

[0020] An emergency emission reduction measure scheme construction unit is configured to associate a dynamic source analysis case library under a corresponding weather type and meteorological element according to the weather type and the meteorological forecast result, take the expected emission reduction amount as a target, take the emission reduction proportion and the implementation cost of each measure as a basis, call corresponding emission reduction measures in a measure library according to the emission reduction object and the target emission reduction amount of the transmission area grid, and construct an emergency emission reduction measure scheme.

[0021] The cost-benefit analysis unit is used to call the abatement ratio and unit cost in the cost-benefit analysis basic data set to account for the scheme, carry out the cost-benefit analysis of the abatement measure scheme, calculate the total expected abatement amount and total cost of the scheme, based on this, according to the response function set of the atmospheric pollutants and precursors, calculate the expected value of air quality improvement of the abatement scheme, compare the air quality target value, give the optimization suggestion of the measure, and the optimized emergency abatement scheme can be stored in the project case library.

[0022] Further, according to the weather type and the meteorological forecast result, the dynamic source analysis case library under the corresponding weather type and meteorological element is associated, the expected abatement amount is taken as the target, the abatement ratio and the implementation cost of each measure are sorted as the basis, the corresponding abatement measures in the measure library are called by combining the abatement object and the target abatement amount of the transmission area grid, and the emergency abatement measure scheme is constructed, including:

[0023] According to the transmission area grid grouping and the pollution source contribution ratio, the sorting of the control measures under different groupings is automatically matched for the user to select, and according to the selection of the control measures by the user, the expected abatement amount and the total cost under the current measure set are calculated, and the difference value with the target abatement amount is calculated.

[0024] Further, the construction method of the response function set of the atmospheric pollutants and precursors includes an air quality model method, and the system will give the default value of the response function set under different seasonal classifications of the user area, and the user can also customize the related parameters of the response function set under more detailed meteorological condition classifications.

[0025] Further, the cost-benefit analysis method includes the air quality improvement effect evaluation and the cost accounting of the abatement scheme, wherein the air quality improvement effect is quickly identified through the response function set, the abatement cost is calculated from the abatement object and the unit cost of the abatement measure, and the unit cost of the abatement measure refers to the social and economic cost consumed by the implementation of the unit abatement measure.

[0026] Further, the project case library includes a plurality of projects, each project includes the measure scheme in the preferred process, the scheme expected effect, the scheme actual effect and the scheme improvement suggestion, and the brief information of the finally executed scheme is placed on top.

[0027] Compared with the prior art, the present application has the following advantages:

[0028] The present application obtains data information required for atmospheric pollution source analysis and air quality fine management and control, stores the data information as a basic database after standardization and gridization processing, uses a weather typing tool to screen the best weather typing method suitable for the local area, combines a source analysis model to construct a source analysis case library under different weather typing, performs weather typing according to the meteorological element prediction results obtained from the government weather forecast, calls the corresponding case in the source analysis case library, selects the corresponding grid atmospheric pollution source emergency reduction measures and constructs an emergency reduction scheme according to the pollution source contribution ratio and the wind speed and direction distribution in the case, the pollutant reduction proportion corresponding to the measures and the cost ranking, calculates the atmospheric pollutant reduction amount of the reduction scheme, calculates the air quality target accessibility by using the atmospheric pollutant and precursor response function, and optimizes the emergency reduction scheme based on the air quality target accessibility. The source analysis method based on the weather type and the meteorological forecast can realize the grid emergency measure landing scheme optimization, and provide support for the air quality continuous improvement and standard reaching emergency. BRIEF DESCRIPTION OF DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0030] Figure 1 The flow chart of the source analysis method based on weather typing and meteorological forecast of the present application.

[0031] Figure 2 The execution flow chart of the source analysis method based on weather typing and meteorological forecast in the embodiment.

[0032] Figure 3 The flow chart of the emergency response method of the present application.

[0033] Figure 4 The execution flow chart of the emergency response method in the embodiment.

[0034] Figure 5 The architecture diagram of the emergency response system in the embodiment. DETAILED DESCRIPTION

[0035] In order to make the person skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the present application.

[0036] As Figures 1-2 , the embodiment of the present application provides a source analysis method based on weather classification and weather forecast, comprising the following steps.

[0037] S110, the basic information data, the obtained basic information data includes: geographic information data, emission source information, social economic data, historical meteorological data and air quality data, the above information is stored after standardization and grid processing, thereby constructing a basic database; based on the geographic information data, the standardization and grid processing are carried out on the applicable area, and the high-resolution grid will automatically import the corresponding basic information from the database, and continuously update the data information.

[0038] In this embodiment, the obtained historical meteorological data includes but is not limited to temperature, humidity, wind speed, wind direction, light radiation intensity and the like with corresponding time resolution, and these meteorological elements are arranged in a predetermined time sequence; through a big data information collection method, the air quality data corresponding to the time sequence is obtained, including AQI, CO, SO2, NO, PM 2.5 , PM 10 , O3 and other atmospheric pollutant indexes and precursors, and can achieve the effects of automatic acquisition and automatic update, and is stored in the database storage after data standardization.

[0039] According to the grid processing of geographic information in the applicable area, the applicable area is divided into high-resolution grids and loaded with grid information, and the grid information includes but is not limited to: longitude and latitude, source activity level data, source emission data, existing end treatment measure information, emission source control information log, land use property data, social economic data and the like. The grid information can be stored through a linked database storage module, and the dynamic adjustment and update can be realized by exporting the standardized data of the database.

[0040] S120, the weather classification method is screened based on the Euclidean distance method, and the most optimal local classification method is determined to build a weather classification module. The method with the largest gap between the groups of weather classification results determined by the Euclidean distance method is the optimal weather classification method.

[0041] Specifically, weather typing is completed based on a weather typing tool, the typing tool includes but is not limited to European Cooperation in Science and Technology (COST) 733, wherein the typing algorithm includes but is not limited to a neural network method, a K value method, a naive Bayes method, etc.; based on the Euclidean distance method, the weather typing method is screened according to the difference between groups after typing, and the typing method with larger difference between groups is determined as the local weather typing algorithm, and a weather typing module is built. In this embodiment, the corresponding weather typing algorithm is preset for the applicable area, but it can also be customized according to user needs, and the weather typing effect of different algorithms is provided for comparison.

[0042] Based on the weather typing case, reliability verification and evaluation are carried out. The weather type of the historical data is divided by using the weather typing tool, and the main characteristics of each weather type are counted, including but not limited to the appearance frequency, the appearance season, the main weather system, the average vertical wind, the strength of the persistent influence, etc.; secondly, a single case is extracted to verify and evaluate the reliability of the weather typing result, and if the effect is poor, the typing algorithm is reselected.

[0043] S130, the historical meteorological data is imported into the weather typing module for weather typing, the spatiotemporal distribution rule of the pollutants under each weather type is analyzed, and the pollution day case under the historical weather type is formed.

[0044] Specifically, the air quality data and the meteorological data obtained from the basic information database are linked, the pollution characteristics under the weather type are studied from the time scale and the space scale, the main pollutants under each weather type are qualitatively analyzed, the main control factors of the meteorological elements under the weather typing are identified, the pollution day situation under each historical weather type is classified and counted for reference when selecting the emission reduction measures. The present application can also use a visualization tool to display the spatiotemporal evolution rule of various pollutants under the weather typing, call the historical or predicted air quality data and meteorological data, and display the pollution process under the influence of the weather type and the meteorological elements, provide intuitive visualization analysis data for the user, and finally generate a statistical analysis report for storage.

[0045] S140, the pollution emission information of the grid unit is associated with the weather type for source analysis, a local source classification system is constructed, the contribution proportion of the pollution source under the weather type is quantified, and thus a source analysis case library under each weather type is constructed. The emission source information refers to the information of the emission source stored in the grid information, such as the attributes of the emission source location, height, name, etc.; and the pollution emission information includes the emission source information and the concentration of each pollutant.

[0046] Specifically, a localized source resolution method under the weather type is selected. On the basis of the above-mentioned local weather classification results, further classification is performed again according to meteorological factors such as wind speed and wind direction that have greater influences. The more the categories, the more the source resolution cases under the weather type, the source resolution experience model can better reflect the actual situation, and the faster the effect of emergency response and prevention and control. The localized source resolution method is matched under different classification conditions, and the source resolution method is selected according to the criterion of actually reflecting the source contribution of the local area, including but not limited to online source resolution, PMF (Positive Matrix Factorization) and the like.

[0047] The case is classified by a transmission area, and the contribution ratio of the case to the pollution source is calculated. The transmission area classification method includes but is not limited to a backward trajectory model, a meteorological model and the like. The grid through which the air mass is transported during the pollution period of a specific weather type is identified by using the above-mentioned model, the transmission area grid is classified according to the wind direction and wind speed distribution, the source contribution category is determined in combination with the selected source resolution method, and the pollution source contribution ratio under the main wind direction and wind speed of different weather types is calculated. After the characteristics and rules of the source contribution ratio of the main pollutants under the weather type are counted and summarized, the historical source resolution case under the weather type is formed, the format is unified, and the storage is standardized, and the historical source resolution case library under the weather type is constructed. The source contribution category identified above is consistent with the local pollution source emission inventory classification system, and the transmission area classification of the source resolution case library under the weather type and the contribution ratio of the pollution source can be dynamically updated.

[0048] The transmission area classification is performed according to the backward trajectory model or the meteorological model method, the pollution concentration of a certain pollutant under a certain weather type in the grid is calculated, the transmission area grade of the grid is determined according to the pollution concentration, and the grid information is stored. According to the source resolution result, the pollution source of a certain pollutant is determined, and the source contribution ratio of the pollutant under the main wind direction and wind speed of different weather types is calculated.

[0049] The historical source resolution case needs to be classified according to the meteorological elements under different weather types, and the source contribution category is consistent with the local pollution source emission inventory classification system. The transmission area classification of the source resolution case library and the contribution ratio of the pollution source can be dynamically updated. The method for performing the transmission area classification includes a backward trajectory model method or a meteorological model method. The grid through which the air mass is transported during the pollution period of a specific weather type is identified by using the backward trajectory model method or the meteorological model method, the transmission area grid is classified according to the wind direction and wind speed distribution, and the source resolution method is combined to calculate the pollution source contribution ratio under the main wind direction and wind speed of different weather types.

[0050] As shown in Figures 3-4 The embodiment of the present application also provides an emergency response system, which comprises a model construction unit, a calculation unit, a cost-effectiveness analysis basic data set construction unit, an emergency emission reduction measure scheme construction unit and a cost-effectiveness analysis unit.

[0051] A model construction unit is configured to construct a source analysis empirical model for implementing the source analysis method according to any one of the preceding embodiments.

[0052] Specifically, the emergency emission reduction measures are obtained, classified according to different emission sources, and the emission reduction intensity is set according to the emission reduction scenario, and different emergency emission reduction measures are selected to correspond under different emission reduction intensities; in conjunction therewith, the emission reduction proportion of the measures is obtained, which corresponds to the emergency emission reduction measures one by one; as one of the preferred conditions, the unit cost of the emergency emission reduction measures is obtained, which is matched with the emission reduction measures and the emission reduction proportion and stored together, to construct a cost-effectiveness analysis basic data set. The cost-effectiveness analysis basic data set and the emission reduction proportion and implementation cost thereof can be customized and modified according to the actual situation of the user on the basis of the conventional basic data.

[0053] A calculation unit is configured to obtain air quality forecast data, compare the data with the regional target limit value, and calculate the target emission reduction amount of the precursors according to the response function set of the atmospheric pollutants and the precursors.

[0054] Specifically, meteorological forecast data are obtained, the weather type is predicted by calling a weather typing module, the emergency emission reduction measures are selected in combination with the source analysis empirical model under the weather type, the emission reduction proportion and the emission reduction cost under the emergency measures are matched by linking the cost-effectiveness analysis basic database, the cost-effectiveness analysis is performed, and the rapid emergency emission reduction measure scheme with small social impact and low economic investment is optimized under the premise of meeting the emission standard.

[0055] Air quality prediction data and regional air quality limit values are obtained, the air quality prediction data include but are not limited to prediction time, PM 2.5 , PM 10 , O3, NO2, CO, SO2, and AQI, and the data format should be unified and standardized; the regional target limit value is set to a default value according to the order of national-local-industry air quality standards, and is automatically adjusted according to different requirements of the applicable region, and the value can also be freely modified according to the user's demand.

[0056] The specific steps of constructing the response relationship function of the atmospheric pollutants and the precursors by the air quality model method include: 1. Formulating orthogonal simulation cases of all precursors under different emission levels; 2. Simulating the atmospheric pollutant concentrations under the above cases by using the air quality model; and 3. Constructing the response function based on the simulated concentrations of the target pollutants and the emission levels. The mode is selected by selecting different parameters in the air quality model or embedding related programs.

[0057] The response function set is a calculation function of the relationship between atmospheric pollutants and precursors, which can calculate the emission reduction amount of atmospheric pollutants after reducing the emission of precursors (air quality improvement), and determine the emission reduction amount of each pollutant. The response function is affected by the regional location and season, and all response functions should be constructed according to the region and season. The construction of the relationship response function set requires setting different regional and seasonal scenarios, and the initial value of the relationship response function set construction can be set by the user.

[0058] The cost-effectiveness analysis basic data set construction unit is used for obtaining the emission reduction measures and the emission reduction proportion and implementation cost of the emission reduction measures under different implementation intensity grades, and constructing a cost-effectiveness analysis basic data set storage.

[0059] The emergency emission reduction measure scheme construction unit is used for associating the dynamic source analysis case library under the corresponding weather type and meteorological element according to the weather type and meteorological forecast result, taking the expected emission reduction amount as a target, taking the emission reduction proportion and implementation cost sorting of each measure as a basis, combining the emission reduction object and target emission reduction amount of the transmission regional grid, calling the corresponding emission reduction measures in the measure library, and constructing an emergency emission reduction measure scheme.

[0060] The cost-effectiveness analysis unit is used for calling the emission reduction proportion and unit cost in the cost-effectiveness analysis basic data set to account the scheme, carrying out cost-effectiveness analysis of the emission reduction measure scheme, calculating the total expected emission reduction amount and total cost of the scheme, based on this, calculating the expected value of air quality improvement of the emission reduction scheme according to the relationship response function set of atmospheric pollutants and precursors, comparing the target value of air quality, giving a measure optimization suggestion, and the optimized emergency emission reduction scheme can be stored in the project case library.

[0061] In the embodiment of the application, the source analysis empirical model under the weather type is used to achieve the function of rapid emergency prevention and control, and specifically includes the following contents.

[0062] Based on the obtained emergency emission reduction measures, the measures are classified according to the types of emission sources; an emission reduction scenario is constructed, different emission reduction intensities are determined according to different emission reduction demands, different emission reduction measures are set under different emission reduction intensities, and multiple emission reduction measures can be used instead of each other under the same emission reduction intensity. Correspondingly, the cost-effectiveness analysis basic data set is constructed based on the obtained emission reduction measure cost and emission reduction proportion and the corresponding matching of the emission reduction measures, so as to be called for subsequent cost-effectiveness analysis.

[0063] Based on the obtained air quality prediction data and regional air quality limit value, the target emission reduction amount is calculated by constructing a function. The function construction method includes but is not limited to an air quality model, and the system will give the default value of the response function set of the user region under different seasonal classification, and the user can also customize the response function set under more detailed meteorological condition classification. The difference between the pollutant concentration and the regional air quality limit value is calculated, and the target emission reduction amount of the precursor is calculated according to the relationship response function set of atmospheric pollutants and precursors.

[0064] Call weather typing tool, combined with meteorological prediction data for weather typing in the prediction period, its typing algorithm is consistent with the algorithm for building the local historical source analysis case library described in the foregoing of the present application, ensuring that the case library can match the predicted weather type scene when called.

[0065] According to the prediction results of weather typing, the corresponding typical weather type source analysis statistical case is associated, the key pollution parameters are analyzed, and the source analysis results of the predicted weather type are quickly derived after the main pollutants are determined, including but not limited to qualitative identification of pollution sources and quantification of pollution source contribution ratio; by matching the source analysis case library with the predicted weather type and the weather forecast, the transmission area grid and its pollution source contribution ratio under the weather type are quickly matched, the emergency management and control object grid is quickly identified and located, and its basic information is obtained; different source contribution ratios are classified and counted according to the source classification system, and the industry that needs to be reduced is determined according to the target emission reduction amount and the difficulty of emission reduction.

[0066] With grid unit as the minimum calculation unit, according to the transmission area grid grouping and its pollution source contribution ratio, the present application can realize automatic matching of control measures under different groupings for user selection; the user calls the corresponding emission reduction measures from the cost-effectiveness analysis basic data set to form a dynamic emergency emission reduction measure set through the pop-up options, and according to the user's check of the control measures, the expected emission reduction amount and the total cost under the current measure set are automatically calculated, and the target difference prompt and expert suggestion are given in combination with the target emission reduction amount, if the total emission reduction amount does not reach the target emission reduction amount, the control measures need to be rechecked or other emergency emission reduction scheme is selected; after the control measures are checked, an emergency emission reduction scheme is formed, which includes the measure set, the expected total emission reduction amount and the total emission reduction cost, etc.

[0067] The total emission reduction ratio of the emergency emission reduction measures is calculated by calling the emission reduction ratio of the cost-effectiveness analysis basic data set, and the air quality improvement effect is evaluated. With grid unit as the minimum calculation unit, the formula is as follows:

[0068]

[0069] In the formula, Q is the total emission reduction ratio of the grid unit, expressed in percentage; represents the number of the i-th emission reduction measure; is the unit emission reduction ratio of the i-th emission reduction measure, expressed in percentage; i represents the type of emission reduction measure; j represents the grid number.

[0070] The total emission reduction cost of the emergency emission reduction scheme is calculated by calling the cost-effectiveness analysis basic data set, and the emission reduction cost is calculated by the unit cost of the emission reduction object and the emission reduction measure. The social and economic cost consumed by the unit emission reduction measure is calculated with grid as the minimum calculation unit and matched with the measure set. The formula is as follows:

[0071]

[0072] is the total cost of emission reduction, is the cost of unit emission reduction measures, is the required amount of emission reduction measures, i represents a control technology, p represents a pollutant, r represents a region, and j represents a grid number.

[0073] Based on the above total amount of emission reduction and cost accounting, the emergency emission reduction measure scheme is optimized. The cost-effectiveness analysis of the emergency emission reduction scheme is carried out. First, the emission reduction proportion is arranged, and the emergency emission reduction measure scheme that meets the target emission reduction amount is selected according to the target emission reduction amount. Then, the total cost is compared and sorted from low to high, and the ten schemes with the lowest total cost are selected for display and output. The feasibility of the scheme is evaluated, and the implementation effect, social influence, economic effect, and effectiveness time of the scheme are judged. If necessary, expert opinions can be provided for interactive guidance, and finally the project case is stored in the fast emergency emission reduction project case library.

[0074] The project case library includes multiple projects, each project includes but is not limited to the measure scheme in the optimization process, the expected effect of the scheme, the actual effect of the scheme, and the improvement suggestion of the scheme. Each project is stored according to its weather type and meteorological conditions. After the next weather forecast and weather type prediction, the project case with higher matching degree can be recommended for reference to optimize the speed of atmospheric pollution fast emergency response. After the application of the scheme, the application emission reduction effect is continuously collected, the influence on the society and economy is evaluated, and they are stored in the project case library to assist the decision and optimization of the next project scheme.

[0075] As shown in Figure 5 , it is the design architecture of the emergency response system in the embodiment, mainly based on the decision assistance demand to build a chart comparison and sorting visualization tool. It mainly includes a central processing control and visualization analysis unit, a source analysis experience model unit based on weather typing, a database storage unit, an external information acquisition unit, and an atmospheric pollution fast emergency response unit based on air quality forecast and source analysis experience model.

[0076] The visualization technology aims to display multi-dimensional information and optimize fast emergency schemes, calls the information of pollution process and emission reduction measures in the database, quickly simulates the implementation effect of the emergency emission reduction scheme, and provides reference basis for decision makers with intuitive data such as pictures, tables, dynamic animation process, etc. Visualization technology includes weather typing method screening, pollution spatio-temporal distribution, source analysis scenario analysis, fast emergency scheme optimization, and other data visualization display functions.

[0077] Among them, the weather typing method screening module is to compare the group difference of the typing results of each method, use the Euclidean distance method to display the typing effect in a chart, and realize quick judgment and sorting screening; the pollution emission space-time distribution module is to use a drawing tool to realize the characteristic display of the time evolution and spatial distribution of pollution, including the distribution of pollutant concentration and emission source intensity; the source analysis scenario analysis refers to the source analysis of the main pollutants under a specific weather type, and after determining the analyzed pollution components, the contribution ratio of each type of pollution source is output in a chart form; the quick emergency scheme optimization module is to sort the total emission reduction ratio and total cost of each scheme after constructing the emergency emission reduction measures scheme under quick source analysis, realize the cost-effectiveness analysis of different schemes, dynamically display the predicted pollution process, compare the pollution concentration difference before and after the emission reduction of the same scheme, and evaluate the feasibility of the emergency emission reduction scheme.

[0078] The visualization technology is an effective display of data results, which can directly affect the efficiency of data mining and the subjective judgment of expert decision-making. As a performance carrier for scheme optimization, different visualization forms can directly affect the understanding of the information hidden behind the data. The regional atmospheric historical pollution rule and the pollution source analysis result under the weather type in the embodiment can be directly displayed on a two-dimensional map through application software such as Arcgis; in addition, the programming method can be used to realize the dynamic simulation and prediction of the pollution process under the weather type and the emission reduction effect of the emergency emission reduction measures scheme; at the same time, the data analysis software and programming language can be used to realize the operations of category comparison, proportion composition, mutual contact, distribution characteristics, data enhancement and single value highlighting of data information. Through the automatic operation process of data statistical analysis, the above data is classified and counted, and is further processed into a statistical analysis report output. In addition, the data for visualization display is saved and exported for repeated use of the display data.

[0079] In the above embodiments of the present application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0080] In the embodiments provided in the present application, it should be understood that the disclosed technical content can be implemented by other ways. Among them, the device embodiments described above are only schematic, for example, the division of the units can be a logical function division, and in actual implementation, there can be another division way, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or modules shown or discussed can be indirect coupling or communication connection through some interfaces, units or modules, which can be electrical or other forms.

[0081] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, i.e. may be located in one place, or may be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0082] In addition, each functional unit in the embodiment of the application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0083] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical scheme of the application, essentially or the part that contributes to the prior art, or all or part of the technical scheme can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the application. The foregoing storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various program code storage media.

[0084] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the application, and not to limit them; although the application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical scheme recorded in the foregoing embodiments, or make equivalent replacement to part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical scheme deviate from the scope of the technical scheme of the embodiments of the application.

Claims

1. An emergency response system, characterized in that, include: Model building unit, used for On the one hand, it acquires local basic information data, processes it into a standardized grid, and then stores it to build a basic database. On the one hand, the applicable area is standardized and gridded based on geographic information data, and the basic information of the corresponding grid units is imported and updated. On the one hand, weather classification methods are screened based on the Euclidean distance method to determine the most effective localized classification method for building a weather classification module. On the one hand, historical meteorological data is imported into the weather classification module to classify weather patterns and analyze the spatiotemporal distribution patterns of pollutants under each weather type. On the other hand, source apportionment is performed based on the pollution emission information of grid cells and the weather patterns. A localized source classification system is constructed. The backward trajectory model method or meteorological model method is used to identify the grid through which the air mass passes during the pollution period of a specific weather pattern. The grid of the transmission area is classified according to the wind direction and wind speed distribution. Combined with online source apportionment or PMF source apportionment method, the pollution source contribution ratio of different weather patterns under the main wind direction and wind speed is calculated, thereby constructing a source apportionment case library under each weather pattern. The calculation unit is used to acquire air quality forecast data, compare it with regional target limits, and calculate the target emission reduction of precursors based on the response function set of the relationship between air pollutants and precursors. The cost-effectiveness analysis basic dataset construction unit is used to obtain emission reduction measures and their emission reduction ratios and implementation costs under different implementation intensity levels, thereby constructing the cost-effectiveness analysis basic dataset; The emergency emission reduction measures scheme construction unit is used to construct an emergency emission reduction measures scheme based on weather type and meteorological forecast results, associate the dynamic source analysis case library under the corresponding weather type and meteorological elements, take the expected emission reduction amount as the target, sort the emission reduction ratio and implementation cost of each measure as the basis, combine the emission reduction objects and target emission reduction amount of the transmission area grid, call the corresponding emission reduction measures in the measure library, and construct the emergency emission reduction measures scheme. The cost-effectiveness analysis unit is used to call the emission reduction ratio and unit cost in the cost-effectiveness analysis basic dataset to calculate the cost-effectiveness of the scheme, carry out the cost-effectiveness analysis of the emission reduction measures, calculate the total expected emission reduction and total cost of the scheme, and based on this, calculate the expected air quality improvement value of the emission reduction scheme according to the response function set of the relationship between air pollutants and precursors, compare it with the air quality target value, give suggestions for optimizing the measures, and can optimize the emergency emission reduction scheme and store it in the project case library.

2. The emergency response system according to claim 1, characterized in that, Based on weather patterns and meteorological forecasts, and in conjunction with the dynamic source apportionment case library for corresponding weather patterns and meteorological elements, and using the expected emission reduction as the target, and ranking the emission reduction ratios and implementation costs of various measures, combined with the emission reduction targets and target emission reductions of the transmission area grid, the corresponding emission reduction measures in the measure library are invoked to construct an emergency emission reduction measure plan, including: Based on the grid grouping of the transmission area and the contribution ratio of its pollution sources, the system automatically matches the control measures under different groups for users to choose from. Based on the user's choice of control measures, the system calculates the expected emission reduction and total cost under the current set of measures, and calculates the difference between the current set of measures and the target emission reduction.

3. An emergency response system according to claim 1, characterized in that, The method for constructing the response function set of the relationship between atmospheric pollutants and precursors includes the air quality model method. The system provides default values ​​for the response function set under different seasonal classifications of the user's region, or allows the user to define relevant parameters for the response function set under more detailed meteorological condition classifications.

4. An emergency response system according to claim 1, characterized in that, The cost-effectiveness analysis method includes the evaluation of the air quality improvement effect of emission reduction schemes and cost accounting. The air quality improvement effect is quickly identified through a set of response functions. The emission reduction cost is calculated from the emission reduction target and the unit cost of emission reduction measures. The unit cost of emission reduction measures refers to the socio-economic cost consumed by implementing a unit of emission reduction measures.

5. An emergency response system according to claim 1, characterized in that, The project case library includes multiple projects, each of which includes multiple optimization processes, expected effects, actual effects, and improvement suggestions, with a brief overview of the final implementation plan at the top.

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