Air pollution source tracing method, terminal and storage medium based on multi-source data fusion

Abstract

The present invention provides an atmospheric pollution source tracing method, terminal, and storage medium based on multi-source data fusion, comprising: obtaining air quality monitoring data and pollution source monitoring data of a target city; for any monitoring station, determining whether a target pollution parameter exists based on the monitoring data of the monitoring station; if the target pollution parameter exists at the monitoring station, determining whether the area corresponding to the monitoring station is individually polluted based on the first and second monitoring values ​​of the target pollution parameter; if the monitoring station corresponds to individually polluted areas, determining at least one pollution type corresponding to the monitoring station; determining the monitoring data of all pollution source monitoring points within the tracing range corresponding to the monitoring station, and for each pollution type corresponding to the monitoring station, sequentially calculating the contribution value of each target pollution source within the tracing range to the pollution type, to obtain a pollution source tracing result for the pollution type. The present invention can improve the accuracy of pollution tracing.

Description

Technical Field

[0001] The present invention relates to the technical field of air quality monitoring, and in particular to an atmospheric pollution source tracing method, terminal, and storage medium based on multi-source data fusion. Background Art

[0002] Air quality monitoring has entered the era of big data. In addition to conventional air quality monitoring stations, such as national and provincial monitoring points and township stations, grid-based micro-station monitoring, online source analysis of particulate matter, online monitoring of volatile organic compounds (VOCs), and construction site dust monitoring systems are also widely used. At the same time, air quality is showing a positive momentum of overall improvement. Local governments are deepening their efforts in atmospheric environmental governance and raising the bar for tracing air pollution sources.

[0003] Currently, pollution source tracing is routinely conducted across the country, primarily through a combination of manual analysis of monitoring data and on-site inspections. This process is labor-intensive and time-consuming. Furthermore, some types of data analysis are challenging and require high-level analytical expertise. For example, source attribution data analysis requires extensive prior experience. This results in slow pollution source tracing, delayed results, and significant influence from analyst subjective factors, making it ineffective in supporting environmental management.

[0004] Therefore, how to improve the efficiency and accuracy of atmospheric pollution tracing based on multi-source data fusion is a problem that needs to be urgently solved by existing technologies. Summary of the Invention

[0005] In view of this, the present invention provides an air pollution source tracing method, device, terminal and storage medium based on multi-source data fusion, which can solve the problem of low efficiency of air pollution source tracing based on multi-source data fusion.

[0006] In a first aspect, an embodiment of the present invention provides an air pollution source tracing method based on multi-source data fusion, comprising:

[0007] Obtaining air quality monitoring data and pollution source monitoring data for a target city, wherein the air quality monitoring data for the target city includes monitoring data from multiple monitoring sites in the target city, and for any monitoring site, the monitoring data at the monitoring site includes concentration information of multiple preset types of pollution parameters; and the pollution source monitoring data includes monitoring data from multiple pollution source monitoring points, each pollution source monitoring point corresponding to at least one type of pollution source;

[0008] For any monitoring site in the target city, determining whether a target pollution parameter exists based on the monitoring data of the monitoring site, wherein the target pollution parameter is used to represent a pollution parameter that meets the corresponding pollution parameter alarm preset conditions among the multiple preset types of pollution parameters;

[0009] If the target pollution parameter exists at the monitoring site, determine whether the area corresponding to the monitoring site is individually polluted based on the first monitoring value and the second monitoring value of the target pollution parameter, wherein the first monitoring value is the concentration value of the target pollution parameter monitored by the monitoring site, and the second monitoring value is the reference concentration value of the target pollution parameter in the target city;

[0010] If the monitoring site corresponds to regional individual pollution, determining at least one pollution type corresponding to the monitoring site;

[0011] Determine the monitoring data of all pollution source monitoring points within the traceability range corresponding to the monitoring site. For each pollution type corresponding to the monitoring site, calculate the contribution value of each target pollution source within the traceability range to the pollution type in turn to obtain the pollution source tracing result of the pollution type, wherein the type of the target pollution source is related to the pollution type.

[0012] In a possible implementation, for any monitoring site in the target city, determining whether a target pollution parameter exists based on monitoring data of the monitoring site includes:

[0013] For any type of pollution parameter among the multiple preset types of pollution parameters, if the concentration value of the pollution parameter is greater than or equal to the preset threshold value corresponding to the pollution parameter, or the concentration value of the pollution parameter has an increasing trend, or the concentration value of the pollution parameter has a continuous high trend, then the pollution parameter is the target pollution parameter.

[0014] In a possible implementation, for any type of pollution parameter among the multiple preset types of pollution parameters, determining whether a concentration value of the pollution parameter has an increasing trend includes:

[0015] Calculating a first concentration increase percentage of the pollution parameter based on the concentration value of the pollution parameter at the current moment and the concentration value at the previous moment;

[0016] Determining, based on the concentration value of the pollution parameter at the current moment falling within a concentration interval in a first preset list, a percentage limit corresponding to the concentration value at the current moment, according to the first preset list, wherein, for any pollution parameter among the multiple preset types of pollution parameters, the first preset list includes multiple consecutive but non-overlapping concentration intervals corresponding to the pollution parameter and the percentage limit corresponding to each concentration interval, and the percentage limit corresponding to each concentration interval is a positive number;

[0017] If the first concentration increase percentage of the pollution parameter is greater than the percentage limit corresponding to the concentration value at the current moment, then the concentration value of the pollution parameter has an increasing trend.

[0018] In one possible implementation, for any type of pollution parameter among the multiple preset types of pollution parameters, determining whether a concentration value of the pollution parameter has a continuously high trend includes:

[0019] Calculating a second concentration increase percentage of the pollution parameter based on the concentration value of the pollution parameter at the current moment and the average concentration value of the pollution parameter at the previous m moments, where the previous m moments are m consecutive moments before the current moment;

[0020] If the first concentration percentage of the pollution parameter is greater than the first preset percentage and less than the percentage limit corresponding to the concentration value at the current moment, and the second concentration percentage of the pollution parameter is greater than the second preset percentage, then the concentration value of the pollution parameter has a trend of continuing to be high, wherein the first preset percentage is a negative number and the second preset percentage is a positive number.

[0021] In one possible implementation, before determining whether the area corresponding to the monitoring station is individually polluted, the method further includes:

[0022] Obtain the geographic location information of each monitoring site;

[0023] The determination of whether the area corresponding to the monitoring station is individually polluted includes:

[0024] Calculating an absolute value of a difference between the first monitoring value and the second monitoring value;

[0025] If the absolute value of the difference is less than or equal to the first preset value, the polluted area is the overall pollution of the target city;

[0026] If the absolute value of the difference is greater than the first preset value, the target local area is determined based on the geographical location information of the monitoring site, with the monitoring site as the center and the preset length as the radius, and the concentration value of the target pollution parameter monitored by other monitoring sites in the target local area is obtained. If the difference between the first monitoring value and the concentration value of the target pollution parameter monitored by other monitoring sites in the target local area is greater than the first preset value, the polluted area is the area corresponding to the monitoring site alone.

[0027] In one possible implementation, before determining whether the area corresponding to the monitoring station is individually polluted, the method further includes:

[0028] Acquire meteorological data of the target city, particulate matter monitoring data of the target city, and air quality monitoring data of cities adjacent to the target city, wherein the meteorological data includes humidity, wind speed, and wind direction of the target city;

[0029] If the polluted area is the entire target city, the method further includes:

[0030] If the humidity value of the target city is greater than a first preset humidity, the wind speed is less than or equal to the first preset wind speed, and the wind direction changes at least once within a first preset time period, then it is determined that the overall pollution type of the target city is a static and stable state, and the cause of the pollution is pollution accumulation due to meteorological reasons;

[0031] If the humidity value of the target city is less than a second preset humidity, the wind speed is greater than or equal to the second preset wind speed, and the wind direction does not change within a second preset time period, then the type of overall pollution in the target city is determined to be a non-stationary state. The upwind city of the target city is determined based on the wind direction, and a change trend curve of the target pollution parameter in the upwind city is compared with a change trend curve in the target city. If the change trend curves are consistent, or the concentration of the target pollution parameter in the upwind city increases earlier than that in the target city, then it is determined that the cause of pollution in the target city is urban pollution caused by the influence of the upwind city.

[0032] Obtain NO3 in the particulate matter monitoring data of the target city - and SO4 2- The ion concentration of NO3 - and SO4 2- The ion concentration determines the pollution source, among which, when SO4 2- The ion concentration is greater than NO3 - When the ion concentration is 2.5, the pollution sources are the combustion sources and sulfide production enterprises in the target city. When SO4 2- The ion concentration is less than NO3 -When the ion concentration is greater than 1%, the pollution sources are traffic sources, combustion sources and industrial sources in the target city.

[0033] In a possible implementation, for each pollution type corresponding to the monitoring site, sequentially calculating the contribution value of each target pollution source within the traceability range to the pollution type includes:

[0034] According to the pollution type, determining all types of pollution sources related to the pollution type according to a second preset list, wherein for each pollution type, the second preset list includes all types of pollution sources related to the pollution type;

[0035] Determine all target pollution sources within the traceability scope based on all types of pollution sources related to the pollution type;

[0036] For any target pollution source, the emission intensity of the target pollution source is obtained through normalization processing;

[0037] According to the distance between each target pollution source and the monitoring site, the weight of each target pollution source is calculated by the inverse distance weighting algorithm;

[0038] For each target pollution source, the contribution value of the target pollution source to the pollution type is calculated based on the emission intensity and weight of the target pollution source.

[0039] In one possible implementation, for any monitoring site, a method for determining the traceability scope corresponding to the monitoring site includes:

[0040] Obtaining the wind direction value of the monitoring site at the alarm moment and the wind speed value in a preset time period, wherein the alarm moment is the moment when the target pollution parameter appears at the monitoring site, and the preset time period includes the alarm moment;

[0041] Determining the upwind direction of the monitoring site according to the wind direction value at the alarm moment;

[0042] Determining a tracing radius based on the wind speed value during the preset time period;

[0043] The tracing range corresponding to the monitoring site is determined according to the upwind direction of the monitoring site and the tracing radius.

[0044] In a second aspect, an embodiment of the present invention provides a terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method described in the first aspect or any possible implementation of the first aspect are implemented.

[0045] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the method described in the first aspect or any possible implementation of the first aspect.

[0046] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0047] The present invention identifies abnormal pollution parameters through the air quality monitoring data and pollution source monitoring data of the target city, and judges whether it is the pollution of the monitoring site alone or the pollution of the city as a whole based on the target pollution parameters. When the monitoring site is polluted alone, the pollution type is identified and the tracing range is determined. The pollution source type related to the pollution type is determined within the tracing range, and the pollution source of the related pollution source type is obtained as the target pollution source. By calculating the contribution value of each target pollution source to the pollution type, the tracing result corresponding to the pollution type is obtained. The monitoring data used in the embodiment of the present invention are all existing real-time data. The method provided by the embodiment of the present invention can effectively improve the accuracy of pollution source tracing after pollution occurs, and provide real-time and accurate basis for pollution control. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 This is a flowchart of an implementation method for tracing the source of air pollution based on multi-source data fusion provided by an embodiment of the present invention;

[0050] Figure 2 This is a schematic structural diagram of an atmospheric pollution source tracing device based on multi-source data fusion provided by an embodiment of the present invention;

[0051] Figure 3 is a schematic diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In the following description, specific details such as particular system structures and techniques are provided for purposes of illustration, not limitation, to facilitate a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0053] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below with reference to the accompanying drawings.

[0054] Conventional research-based pollution source tracing methods include pollution source emission inventories, diffusion models, and receptor models. However, these methods require a high level of basic data, such as the emissions of various types of urban pollution sources and the types of receptor site components. These research methods are easily restricted and have poor timeliness. They also do not fully utilize data from urban air quality monitoring systems and real-time pollution source monitoring systems, and they also lack the ability to explore these data relationships.

[0055] Therefore, a method based on multi-source data fusion that can efficiently and quickly conduct comprehensive tracing of air pollution sources is needed. The present invention provides such a method. Figure 1 , which shows a flowchart of an implementation method of an air pollution source tracing method based on multi-source data fusion provided by an embodiment of the present invention, and is described in detail as follows:

[0056] In step 101, air quality monitoring data and pollution source monitoring data of a target city are obtained.

[0057] Among them, the air quality monitoring data of the target city includes the monitoring data of multiple monitoring stations in the target city. For any monitoring station, the monitoring data of the monitoring station includes the concentration information of multiple preset types of pollution parameters. The pollution source monitoring data includes the monitoring data of multiple pollution source monitoring points, and each pollution source monitoring point corresponds to at least one type of pollution source.

[0058] In the embodiment of the present invention, the monitoring stations include but are not limited to national automatic monitoring stations, provincial automatic monitoring stations, municipal automatic monitoring stations and township monitoring stations. The types of pollution parameters include but are not limited to PM 10 、PM 2.5 , SO2, NO2, CO and O3 pollution parameters. Each monitoring station can obtain real-time concentration information of each type of pollution parameter.

[0059] Furthermore, the geographical location information of each monitoring site may be obtained according to actual needs, including but not limited to the specific latitude and longitude information of the monitoring site.

[0060] In an embodiment of the present invention, the pollution source monitoring points include various types of monitoring points. For example, they can be monitoring points for monitoring dust data at urban construction sites, monitoring points for obtaining emission monitoring data from industrial enterprises, monitoring points for monitoring boiler emissions, and cruise monitoring points.

[0061] In an embodiment of the present invention, an optional implementation method is also applicable to cities or regions where gridded micro stations are deployed. In such cities or regions, the city or region is gridded according to a preset step size, such as divided into several grids of 3km*3km, and a micro station is set in each grid. A micro station is a pollution source monitoring point in this step.

[0062] Based on this, in one possible implementation, each pollution source monitoring point is classified as a pollution source based on the type of monitoring data and the location distribution of the pollution source monitoring point. Each pollution source monitoring point corresponds to at least one type of pollution source. For example, a pollution source monitoring point used for online monitoring of industrial enterprises corresponds to the pollution source type of industrial enterprises, a construction site dust pollution source monitoring point corresponds to the pollution source type of construction sites, a pollution source used for online monitoring of restaurants corresponds to the pollution source type of restaurants, and a grid-based micro-station located on a major traffic artery corresponds to the pollution source type of roads.

[0063] In a distance example, pollution source monitoring point 1 is used to monitor the pollution source of industrial enterprise 1, and the corresponding pollution source type is industrial enterprise. Pollution source monitoring point 2 is used to monitor catering enterprise 1, and the corresponding pollution source type is catering. Pollution source monitoring point 3 is used to monitor construction site 1, and the corresponding pollution source type is construction site.

[0064] In the embodiment of the present invention, various types of pollution source monitoring points are described in a classified manner.

[0065] The first type is urban grid micro-stations, which pre-acquire the geographical location information of each micro-station, including but not limited to the latitude and longitude information of each micro-station. Each micro-station monitors PM in real time. 10 、PM 2.5 Hourly data on six pollution parameters: SO2, NO2, CO, and O3. Each microstation is assigned a label based on the type of pollution source surrounding the gridded microstation. Each microstation can have one or more labels, each corresponding to a pollution source type. For example, a microstation near a main road would be labeled "road," a microstation near a restaurant cluster would be labeled "restaurant," a microstation near an industrial enterprise would be labeled "industrial enterprise," and a microstation near a rural residential area would be labeled "residential area."

[0066] The second category is urban construction site dust monitoring points. Each monitoring point is also a pollution source monitoring point in this step. The geographical location information of each monitoring point is obtained in advance, including but not limited to the latitude and longitude information of each monitoring point. It is used to obtain urban construction site dust monitoring data, including but not limited to PM 10 and PM 2.5 Hourly data. The corresponding pollution source type is construction site.

[0067] The third category is industrial enterprise emission monitoring points. Each monitoring point also counts as a pollution source monitoring point in this step. The geographic location information of each monitoring point is pre-acquired, including but not limited to the latitude and longitude of each monitoring point, as well as the geographic location information of the corresponding industry or enterprise and the name of the emission outlet. The corresponding pollution source type is industrial source, which is used to obtain industrial enterprise emission monitoring data, including but not limited to monitoring parameters such as exhaust gas emissions, average flow rate, measured pollutant concentration, and pollutant emissions at the emission outlet.

[0068] The fourth category is other types of monitoring points. Each monitoring point is also a pollution source monitoring point in this step. The geographical location information of each monitoring point is obtained in advance, including but not limited to the latitude and longitude information of each monitoring point. For example, the monitoring point used to obtain boiler monitoring data is used to obtain hourly data on various pollution parameters emitted by boilers. The corresponding pollution source type is a heating source. There are also cruise monitoring points that obtain conventional parameter cruise monitoring data, satellite remote sensing data, and hourly monitoring data of various pollution parameters. The pollution source type corresponding to each cruise monitoring point can be determined based on the location of the cruise monitoring point. For example, if it is near a catering business, the pollution source type is catering.

[0069] In step 102, for any monitoring site in the target city, it is determined whether the target pollution parameter exists based on the monitoring data of the monitoring site.

[0070] The target pollution parameter is used to represent the pollution parameter that meets the corresponding pollution parameter alarm preset conditions among multiple preset types of pollution parameters.

[0071] In an embodiment of the present invention, for any type of pollution parameter among multiple preset types of pollution parameters, based on the concentration value of the pollution parameter at the current moment and the concentration value at the previous moment, or the concentration value of the pollution parameter has an increasing trend, or the concentration value of the pollution parameter has a continuous high trend, then the pollution parameter is the target pollution parameter.

[0072] Optional, for any type of pollution parameter, such as PM 10 The preset threshold corresponding to the pollution parameter can be determined by the eightieth percentile of the annual hourly data for that parameter. Alternatively, it can be determined based on empirical values ​​or expert recommendations. The present invention does not limit the method for setting the preset threshold corresponding to each type of pollution parameter.

[0073] In an optional implementation, for any type of pollution parameter among multiple preset types of pollution parameters, determining whether the concentration value of the pollution parameter has an increasing trend includes: calculating the first concentration increase percentage of the pollution parameter based on the concentration value of the pollution parameter at the current moment and the concentration value at the previous moment; determining the percentage limit corresponding to the concentration value at the current moment according to the concentration interval to which the concentration value of the pollution parameter at the current moment belongs in the first preset list, wherein, for any pollution parameter among the multiple preset types of pollution parameters, the first preset list includes multiple continuous but non-overlapping concentration intervals corresponding to the pollution parameter, and the percentage limit corresponding to each concentration interval, and the percentage limit corresponding to each concentration interval is a positive number; if the first concentration increase percentage of the pollution parameter is greater than the percentage limit corresponding to the concentration value at the current moment, then the concentration value of the pollution parameter has an increasing trend.

[0074] The following is a specific example. The current moment is t, and the concentration of a pollution parameter is X t , the concentration value of the pollution parameter at (t-1) is X t-1 , then the first concentration increase percentage is calculated by the first formula, which is:

[0075]

[0076] Wherein, is the first concentration percentage of the pollution parameter.

[0077] The first preset list can be represented by the following Table 1:

[0078]

[0079] According to X t In the concentration range belonging to the first preset list, determine the corresponding percentage limit. Taking the pollution parameter as SO2 as an example, the SO2 concentration parameter at time t is 15%. By looking up Table 1 above, the corresponding percentage limit is 30%. If n>30%, it means that the SO2 concentration has an increasing trend.

[0080] It should be noted that in Table 1 above, when the concentration corresponding to the concentration interval is low, it means that the current concentration of the pollution parameter is low, and the percentage limit corresponding to the concentration interval may not be set, and it can also be understood that the percentage limit at this time is infinite.

[0081] In an optional implementation, for any type of pollution parameter among multiple preset types of pollution parameters, determining whether the concentration value of the pollution parameter has a continuous high trend includes: calculating the second concentration increase percentage of the pollution parameter based on the concentration value of the pollution parameter at the current moment and the average concentration value of the previous m moments, where the previous m moments are m consecutive moments before the current moment; if the first concentration percentage of the pollution parameter is greater than the first preset percentage and less than the percentage limit corresponding to the concentration value at the current moment, and the second concentration percentage of the pollution parameter is greater than the second preset percentage, then the concentration value of the pollution parameter has a continuous high trend, wherein the first preset percentage is a negative number and the second preset percentage is a positive number.

[0082] This step aims to calculate the percentage increase in concentration based on the sliding average of the hours preceding time t for pollution processes that continue to rise but fall below the percentage limit, or for pollution processes that remain high with little decrease. If the percentage exceeds this, an alarm is triggered. In other words, exceeding this percentage indicates a trend of persistently high levels for the pollution parameter.

[0083] To facilitate understanding, the above example is used for further explanation.

[0084] Assume that m = 4, for a certain pollution parameter, the concentration values ​​at the four moments before the current moment are represented by X t-4 、X t-3 、X t-2 、X t-1 The second concentration increase percentage can be calculated by the second formula, which is:

[0085]

[0086] Here, n′ is used to represent the second concentration increase percentage.

[0087] For example, if the first preset percentage is set to -10% and the second preset percentage is set to 20%, if n'>20% and n>-10%, it indicates that the concentration value of the pollution parameter has a trend of being continuously high.

[0088] In step 103, if the target pollution parameter exists at the monitoring site, it is determined whether the area corresponding to the monitoring site is individually polluted based on the first monitoring value and the second monitoring value of the target pollution parameter.

[0089] The first monitoring value is the concentration of the target pollution parameter monitored by the monitoring site, and the second monitoring value is the reference concentration of the target pollution parameter in the target city. Optionally, the second monitoring value is the concentration of the pollution parameter monitored by the national monitoring station.

[0090] In an optional implementation, the geographic location information of each monitoring site is obtained; the absolute value of the difference between the first monitoring value and the second monitoring value is calculated; if the absolute value of the difference is less than or equal to a first preset value, the polluted area is the overall pollution of the target city; if the absolute value of the difference is greater than the first preset value, the target local area is determined based on the geographic location information of the monitoring site, with the monitoring site as the center and a preset length as the radius, and the concentration values ​​of the target pollution parameters monitored by other monitoring sites in the target local area are obtained. If the difference between the first monitoring value and the concentration values ​​of the target pollution parameters monitored by other monitoring sites in the target local area is greater than the first preset value, the polluted area is the individual pollution of the area corresponding to the monitoring site.

[0091] In an embodiment of the present invention, when a monitoring station detects the presence of a target pollution parameter, an alarm message will be sent. Therefore, in an embodiment of the present invention, for ease of explanation, a monitoring station with a target pollution parameter is referred to as an alarm station. For the target pollution parameter, the concentration value of the pollution parameter monitored by the alarm station is compared with the concentration value of the pollution parameter monitored by the target city. For example, a first preset value is set to 10%. If the concentration value of the pollution parameter monitored by the alarm station is different from the reference concentration value of the city, if the difference is within ±10%, that is, the absolute value of the difference is less than 10%, then it indicates that the entire city is polluted. If it is greater than 10%, the concentration value of the pollution parameter monitored by other monitoring stations within the range is determined with the alarm station as the center and a preset radius length, such as 5km as the radius. If the difference is greater than 10% with the concentration value monitored by other monitoring stations, then it indicates that the alarm station is polluted alone, otherwise it is a local area of ​​the city.

[0092] In an optional implementation, meteorological data of the target city, particulate matter monitoring data of the target city, and air quality monitoring data of cities adjacent to the target city are obtained, where the meteorological data includes humidity, wind speed, and wind direction of the target city.

[0093] Optionally, the target city's meteorological data includes hourly meteorological data of the city, including but not limited to temperature, humidity, wind direction, and wind speed; the hourly meteorological data of the city's air quality monitoring points includes temperature, humidity, wind direction, wind speed, and atmospheric pressure.

[0094] Optionally, the particulate matter monitoring data of the target city can be the city's particulate matter online source analysis monitoring data, including but not limited to the geographical location information and longitude and latitude of the enterprise, and NO3 in the online ion chromatography - 、SO4 2- NH4 + and Ca 2+ Hourly concentration data.

[0095] Optionally, the air quality monitoring data of the target city's neighboring cities include but are not limited to the geographical location, longitude and latitude of the national monitoring stations in the target city's neighboring cities, and PM 10 、PM 2.5 , SO2, NO2, CO and O3 concentration monitoring data.

[0096] If the pollution area is the overall pollution of the target city, the method further includes: if the humidity value of the target city is greater than a first preset humidity, the wind speed is less than or equal to the first preset wind speed, and the wind direction changes at least once within a first preset time period, then the type of overall pollution in the target city is judged to be a stable state, and the cause of pollution is pollution accumulation due to meteorological reasons; if the humidity value of the target city is less than a second preset humidity, the wind speed is greater than or equal to the second preset wind speed, and the wind direction does not change within a second preset time period, then the type of overall pollution in the target city is judged to be a non-steady state, the upwind city of the target city is determined according to the wind direction, and the change trend curve of the target pollution parameter in the upwind city is compared with the change trend curve in the target city. If the change trend curves are consistent, or the concentration of the target pollution parameter in the upwind city increases earlier than that in the target city, then the cause of pollution in the target city is judged to be urban pollution caused by the influence of the upwind city; obtain NO3 in the particulate matter monitoring data of the target city. - and SO4 2- The ion concentration of NO3 - and SO4 2- The ion concentration determines the pollution source, among which, when SO4 2- The ion concentration is greater than NO3 - When the ion concentration is 2.5, the pollution source is the combustion source and sulfide production enterprise in the target city. When SO4 2- The ion concentration is less than NO3 - When the ion concentration is above , the pollution sources are traffic sources, combustion sources and industrial sources in the target city.

[0097] For example, if the humidity is between 70% and 99%, the wind level is between 0 and 2, and the wind direction is changeable, it can be considered that the environment is in a stable state and the diffusion conditions are unfavorable.

[0098] For example, if the humidity is below 50%, the wind speed is level 3 or above, and the wind direction remains stable for three hours or more, the state is considered unstable. This is compared with the trend of the same parameter in upwind cities. If the trend is basically the same, or if the upwind city's temperature rises one to three hours earlier than the city's, the city is considered to be affected by pollution in the upwind direction.

[0099] NO3 in online ion chromatography based on online source analysis of urban particulate matter - 、SO4 2- and NH4 +The ion concentration can be used to determine the key control direction of the local area under stable weather conditions. 2- / NO3 - When it is less than 1, NO3 - If the contribution of SO42- is too high, it is necessary to strengthen the control of local transportation sources, combustion sources or industrial sources; when SO42- / NO3- is greater than 1, the contribution of SO42- is too high, it is necessary to strengthen the control of local combustion sources and sulfide production enterprises.

[0100] Urban pollution results include pollution type and key local pollution control areas. Based on the results of the urban pollution type determination, the pollution type of the city is listed, and based on the results of the online source analysis and online ion chromatography determination of the urban particulate matter, the key local pollution control areas are listed.

[0101] In step 104, if the monitoring site corresponds to regional individual pollution, at least one pollution type corresponding to the monitoring site is determined.

[0102] In an embodiment of the present invention, at least one pollution type corresponding to the monitoring site can be determined using existing technologies. Alternatively, the pollution type at the monitoring site can be determined using the technical method provided in patent application number CN202010846058.3, entitled "A Method for Automatically Identifying Pollution Source Types Based on Machine Learning." This method uses a machine learning algorithm combined with environmental monitoring data to identify the occurrence of pollution problems and determine the pollution type.

[0103] At least one pollution type corresponding to the monitoring site may also be identified by other existing algorithms, such as determining the pollution type by empirical values ​​or by experts, which is not limited in this embodiment of the present invention.

[0104] In step 105, the monitoring data of all pollution source monitoring points within the traceability range corresponding to the monitoring station are determined. For each pollution type corresponding to the monitoring station, the contribution value of each target pollution source within the traceability range to the pollution type is calculated in turn to obtain the pollution source tracing result of the pollution type, wherein the type of the target pollution source is related to the pollution type.

[0105] In the embodiment of the present invention, if it is determined in step 103 that the pollution is urban pollution or local urban pollution, the pollution source is no longer traced, and the NO3 - and SO4 2- The ion concentration determines the source of contamination.

[0106] If it is determined in step 103 that the monitoring site is polluted individually, then after the pollution type is determined in step 104, the pollution source corresponding to the pollution type is analyzed in this step to achieve accurate identification of the pollution source, and then the corresponding pollution source is controlled to achieve the purpose of quickly and accurately controlling the continued increase in the pollution level.

[0107] In an optional implementation, for any monitoring site, a method for determining the tracing range corresponding to the monitoring site includes: obtaining the wind direction value at the alarm moment of the monitoring site and the wind speed value in a preset time period, wherein the alarm moment is the moment when the target pollution parameter appears at the monitoring site, and the preset time period includes the alarm moment; determining the upwind direction of the monitoring site according to the wind direction value at the alarm moment; determining the tracing radius according to the wind speed value in the preset time period; and determining the tracing range corresponding to the monitoring site according to the upwind direction and tracing radius of the monitoring site.

[0108] Alternatively, the wind direction angle can be divided according to the traditional eight cardinal directions, and the upwind position of the pollution source can be obtained based on the actual wind direction. The location can then be determined based on the wind speed, and the tracing radius can be determined based on the hourly maximum wind speed. Furthermore, considering the impact of continuous long-distance pollution transmission, the tracing radius can be determined based on the 2-4 hour maximum wind speed transmission distance. Finally, the pollution source tracing range of the monitoring station can be determined based on the upwind position and tracing radius. All pollution sources corresponding to the pollution source monitoring points within the pollution source tracing range of the monitoring station are the objects that need to be analyzed.

[0109] In an optional implementation, based on the pollution type, all types of pollution sources related to the pollution type are determined according to a second preset list, and for each pollution type, the second preset list includes all types of pollution sources related to the pollution type; based on all types of pollution sources related to the pollution type, all target pollution sources within the traceability range are determined; for any target pollution source, the emission intensity of the target pollution source is obtained through normalization processing; based on the distance between each target pollution source and the monitoring site, the weight of each target pollution source is calculated through an inverse distance weighted algorithm; for each target pollution source, the contribution value of the target pollution source to the pollution type is calculated through the emission intensity and weight of the target pollution source.

[0110] For example, the pollution types include dust sources, mobile sources, coal burning sources, catering fume sources, and industrial sources. The pollution source types include industrial enterprises, boilers, catering, construction sites, roads, residential areas, fire points, and motor vehicle exhaust.

[0111] Through experience value setting, in the second preset list, the pollution source types related to dust sources include industrial enterprises, construction sites, roads, residential areas, and fire points; the pollution source types related to mobile sources include industrial enterprises, construction sites, roads, fire points, and motor vehicle exhaust; the pollution source types related to coal-fired sources include industrial enterprises, boilers, catering, residential areas, fire points, and motor vehicle exhaust; the pollution source types related to catering oil fume sources include catering, residential areas, and fire points; the pollution source types related to industrial sources include industrial sources, boilers, residential areas, fire points, and motor vehicle exhaust.

[0112] After step 104 determines the pollution type, if the pollution type is a dust source, it can be seen from the second preset list that the pollution source types related to the dust source include industrial enterprises, construction sites, roads, residential areas, and fire points. The pollution source corresponding to the pollution source monitoring point with labels including industrial enterprises, construction sites, roads, residential areas, and fire points within the traceability range is the target pollution source.

[0113] Specifically, the implementation process of this step can be:

[0114] The first step is to determine the pollution source data.

[0115] The emission intensity q of different pollution sources uses different basic data.

[0116] For pollution sources with air quality monitoring, such as construction sites and road traffic, real-time monitoring concentrations are used as emission intensity. Within the traceability range, if monitoring data from regular parameter cruise monitoring points is available, the pollution source will be categorized according to its cruise location, and the real-time monitoring concentrations at the cruise monitoring points will be used as emission intensity.

[0117] Industrial enterprises, restaurants, boilers, etc. adopt a method that combines pollution source emission monitoring and air quality monitoring data. Among them, the emission amount in pollution source emission monitoring is given priority, and the real-time concentration monitoring of air quality monitoring is used secondly, either of the two.

[0118] The second step is to normalize the pollution source data

[0119] Some pollution sources use a combination of two data methods. It is necessary to normalize the different basic data of each pollution source separately, map the data to the range of 0 to 1, make it dimensionless, and establish comparability. The normalization calculation formula is as follows:

[0120]

[0121] Among them, q i is the emission intensity of pollution source i, q min is the minimum emission intensity of the pollution source, q max The maximum emission intensity of this pollution source, q i ′ is the result after normalization of the pollution source.

[0122] When a pollution source uses a single data to represent emission intensity, it is sufficient to normalize the data; when a pollution source uses two or more data to represent emission intensity, such as using organized emission monitoring and unorganized emission monitoring, different types of data need to be normalized separately.

[0123] The third step is to calculate the weight of each target pollution source

[0124] According to the longitude and latitude information, the distances d1, d2, ...d from the target pollution source 1, target pollution source 2, ..., target pollution source n in the pollution source tracing area to the monitoring point are calculated. n , and then calculate the weight of each target pollution source according to the distance.

[0125]

[0126] Among them, λ i is the weight of target pollution source i. Considering that industrial enterprises emit large amounts of gaseous pollutants, when tracing industrial pollution sources, we can identify enterprises with abnormal emissions based on changes in their online monitoring data and increase the weight of these enterprises by a certain amount, such as 0.5, based on their original weight.

[0127] The fourth step is to calculate the contribution of the target pollution source:

[0128]

[0129] Among them, z i is the contribution ratio of target pollution source i, that is, the contribution degree of target pollution source i.

[0130] Step 5: Pollution tracing results:

[0131] According to different pollution types, the top 10 pollution sources with the highest contribution are listed and the contribution ratio is marked. As shown in Table 2 below, Table 2 is:

[0132] Contribution Ranking Pollution Type 1 Pollution Type 2 Pollution Type 3 1 Pollution source 1-1 (xx%) Pollution source 2-1 (xx%) Pollution source 3-1 (xx%) 2 Pollution sources 1-2 (xx%) Pollution source 2-2 (xx%) Pollution source 3-2 (xx%) … … … … 10 Pollution sources 1-10 (xx%) Pollution sources 2-10 (xx%) Pollution sources 3-10 (xx%)

[0133] In the embodiment of the present invention, if it is determined in step 103 that the pollution is urban pollution or local urban pollution, the pollution source is no longer traced, and the NO3 - and SO4 2- The ion concentration determines the source of contamination.

[0134] If it is determined in step 103 that the monitoring site is polluted individually, then after the pollution type is determined in step 104, the pollution source corresponding to the pollution type is analyzed in this step to achieve accurate identification of the pollution source, and then the corresponding pollution source is controlled to achieve the purpose of quickly and accurately controlling the continued increase in the pollution level.

[0135] The present invention identifies abnormal pollution parameters through the air quality monitoring data and pollution source monitoring data of the target city, and judges whether it is the pollution of the monitoring site alone or the pollution of the city as a whole based on the target pollution parameters. When the monitoring site is polluted alone, the pollution type is identified and the tracing range is determined. The pollution source type related to the pollution type is determined within the tracing range, and the pollution source of the related pollution source type is obtained as the target pollution source. By calculating the contribution value of each target pollution source to the pollution type, the tracing result corresponding to the pollution type is obtained. The monitoring data used in the embodiment of the present invention are all existing real-time data. The method provided by the embodiment of the present invention can effectively improve the accuracy of pollution source tracing after pollution occurs, and provide real-time and accurate basis for pollution control.

[0136] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0137] The following are device embodiments of the present invention. For details not fully described therein, reference may be made to the corresponding method embodiments described above.

[0138] Figure 2 The following is a schematic diagram of the structure of an atmospheric pollution source tracing device based on multi-source data fusion provided by an embodiment of the present invention. For ease of explanation, only the parts related to the embodiment of the present invention are shown, which are detailed as follows:

[0139] like Figure 2 As shown, the atmospheric pollution source tracing device 2 based on multi-source data fusion includes: a data acquisition module 21, a first judgment module 22, a second judgment module 23, a pollution type determination module 24 and a source tracing module 25.

[0140] A data acquisition module 21 is configured to acquire air quality monitoring data and pollution source monitoring data for a target city. The air quality monitoring data for the target city includes monitoring data from multiple monitoring stations in the target city. For any monitoring station, the monitoring data includes concentration information of multiple preset types of pollution parameters. The pollution source monitoring data includes monitoring data from multiple pollution source monitoring points, each pollution source monitoring point corresponding to at least one type of pollution source.

[0141] A first judgment module 22 is configured to determine, for any monitoring station in the target city, whether a target pollution parameter exists based on the monitoring data of the monitoring station, wherein the target pollution parameter is used to represent a pollution parameter that meets a corresponding pollution parameter alarm preset condition among multiple preset types of pollution parameters;

[0142] A second judgment module 23 is configured to determine, if the target pollution parameter exists at the monitoring site, whether the area corresponding to the monitoring site is individually polluted based on a first monitoring value and a second monitoring value of the target pollution parameter, wherein the first monitoring value is the concentration value of the target pollution parameter monitored by the monitoring site, and the second monitoring value is the reference concentration value of the target pollution parameter in the target city;

[0143] The pollution type determination module 24 is configured to determine at least one pollution type corresponding to the monitoring site if the monitoring site corresponds to regional individual pollution;

[0144] The traceability module 25 is used to determine the monitoring data of all pollution source monitoring points within the traceability range corresponding to the monitoring site. For each pollution type corresponding to the monitoring site, the contribution value of each target pollution source within the traceability range to the pollution type is calculated in turn to obtain the pollution source tracing result of the pollution type, wherein the type of the target pollution source is related to the pollution type.

[0145] The present invention identifies abnormal pollution parameters through the air quality monitoring data and pollution source monitoring data of the target city, and judges whether it is the pollution of the monitoring site alone or the pollution of the city as a whole based on the target pollution parameters. When the monitoring site is polluted alone, the pollution type is identified and the tracing range is determined. The pollution source type related to the pollution type is determined within the tracing range, and the pollution source of the related pollution source type is obtained as the target pollution source. By calculating the contribution value of each target pollution source to the pollution type, the tracing result corresponding to the pollution type is obtained. The monitoring data used in the embodiment of the present invention are all existing real-time data. The method provided by the embodiment of the present invention can effectively improve the accuracy of pollution source tracing after pollution occurs, and provide real-time and accurate basis for pollution control.

[0146] In a possible implementation, the first determination module 22 is configured to:

[0147] For any type of pollution parameter among multiple preset types of pollution parameters, if the concentration value of the pollution parameter is greater than or equal to the preset threshold value corresponding to the pollution parameter, or the concentration value of the pollution parameter has an increasing trend, or the concentration value of the pollution parameter has a continuous high trend, then the pollution parameter is the target pollution parameter.

[0148] In a possible implementation, the first determination module 22 is configured to:

[0149] Calculating a first concentration increase percentage of the pollution parameter based on the concentration value of the pollution parameter at the current moment and the concentration value at the previous moment;

[0150] Determining, based on the concentration value of the pollution parameter at the current moment falling within the concentration interval of the first preset list, a percentage limit corresponding to the concentration value at the current moment, wherein, for any pollution parameter from the plurality of preset types of pollution parameters, the first preset list includes a plurality of consecutive but non-overlapping concentration intervals corresponding to the pollution parameter and a percentage limit corresponding to each concentration interval, and the percentage limit corresponding to each concentration interval is a positive number;

[0151] If the first concentration increase percentage of the pollution parameter is greater than the percentage limit corresponding to the concentration value at the current moment, then the concentration value of the pollution parameter has an increasing trend.

[0152] In a possible implementation, the first determination module 22 is configured to:

[0153] Calculating a second concentration increase percentage of the pollution parameter based on the concentration value of the pollution parameter at the current moment and the average concentration value of the pollution parameter at the previous m moments, where the previous m moments are m consecutive moments before the current moment;

[0154] If the first concentration percentage of the pollution parameter is greater than the first preset percentage and less than the percentage limit corresponding to the concentration value at the current moment, and the second concentration percentage of the pollution parameter is greater than the second preset percentage, then the concentration value of the pollution parameter has a trend of continuing to be high, wherein the first preset percentage is a negative number and the second preset percentage is a positive number.

[0155] In a possible implementation, the second determination module 23 is configured to:

[0156] Obtain the geographic location information of each monitoring site;

[0157] Calculate the absolute value of the difference between the first monitoring value and the second monitoring value;

[0158] If the absolute value of the difference is less than or equal to the first preset value, the polluted area is the overall pollution of the target city;

[0159] If the absolute value of the difference is greater than a first preset value, the target local area is determined based on the geographical location information of the monitoring site, with the monitoring site as the center and the preset length as the radius, and the concentration value of the target pollution parameter monitored by other monitoring stations in the target local area is obtained. If the difference between the first monitoring value and the concentration value of the target pollution parameter monitored by other monitoring stations in the target local area is greater than the first preset value, the polluted area is the area corresponding to the monitoring site and is polluted alone.

[0160] In a possible implementation, the second determining module 23 is further configured to:

[0161] Obtain meteorological data for the target city, particulate matter monitoring data for the target city, and air quality monitoring data for cities adjacent to the target city. Meteorological data includes humidity, wind speed, and wind direction for the target city.

[0162] If the polluted area is the entire target city, the method further includes:

[0163] If the humidity value of the target city is greater than a first preset humidity, the wind speed is less than or equal to the first preset wind speed, and the wind direction changes at least once within a first preset time period, then it is determined that the overall pollution type in the target city is a static and stable state, and the cause of the pollution is pollution accumulation due to meteorological reasons;

[0164] If the humidity value of the target city is less than a second preset humidity, the wind speed is greater than or equal to the second preset wind speed, and the wind direction does not change within a second preset time period, then the type of overall pollution in the target city is determined to be a non-stationary state. The upwind city of the target city is determined based on the wind direction, and the change trend curve of the target pollution parameter in the upwind city is compared with the change trend curve in the target city. If the change trend curves are consistent, or the concentration of the target pollution parameter in the upwind city increases earlier than that in the target city, then it is determined that the cause of pollution in the target city is urban pollution caused by the influence of the upwind city.

[0165] Obtain NO3 from the particulate matter monitoring data of the target city - and SO4 2- The ion concentration of NO3 - and SO4 2- The ion concentration determines the pollution source, among which, when SO4 2- The ion concentration is greater than NO3 - When the ion concentration is 2.5, the pollution source is the combustion source and sulfide production enterprise in the target city. When SO4 2- The ion concentration is less than NO3 - When the ion concentration is above , the pollution sources are traffic sources, combustion sources and industrial sources in the target city.

[0166] In one possible implementation, the traceability module 25 is used to:

[0167] According to the pollution type, determining all types of pollution sources related to the pollution type according to a second preset list, wherein for each pollution type, the second preset list includes all types of pollution sources related to the pollution type;

[0168] Determine all target pollution sources within the scope of tracing based on all types of pollution sources related to the pollution type;

[0169] For any target pollution source, the emission intensity of the target pollution source is obtained through normalization processing;

[0170] According to the distance between each target pollution source and the monitoring site, the weight of each target pollution source is calculated by the inverse distance weighting algorithm;

[0171] For each target pollution source, the contribution value of the target pollution source to the pollution type is calculated based on the emission intensity and weight of the target pollution source.

[0172] In one possible implementation, the traceability module 25 is used to:

[0173] Obtain the wind direction value at the alarm time of the monitoring station and the wind speed value in a preset time period, wherein the alarm time is the time when the target pollution parameter appears at the monitoring station, and the preset time period includes the alarm time;

[0174] According to the wind direction value at the alarm time, determine the upwind direction of the monitoring station;

[0175] Determine the tracing radius based on the wind speed value in the preset time period;

[0176] According to the upwind direction and tracing radius of the monitoring site, the tracing range corresponding to the monitoring site is determined.

[0177] The air pollution source tracing device based on multi-source data fusion provided in this embodiment can be used to execute the above-mentioned air pollution source tracing method embodiment based on multi-source data fusion. Its implementation principle and technical effects are similar, and will not be repeated here in this embodiment.

[0178] Figure 3 FIG is a schematic diagram of a terminal provided by an embodiment of the present invention. Figure 3 As shown, the terminal 3 of this embodiment includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30. When the processor 30 executes the computer program 32, the steps in the above-mentioned embodiments of the atmospheric pollution source tracing method based on multi-source data fusion are implemented, for example Figure 1 Alternatively, when the processor 30 executes the computer program 32, the functions of the modules / units in the above-mentioned device embodiments are realized, for example, Figure 2 The functions of modules 21 to 25 are shown.

[0179] Exemplarily, the computer program 32 may be divided into one or more modules / units, which are stored in the memory 31 and executed by the processor 30 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 32 in the terminal 3.

[0180] The terminal 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal 3 may include, but is not limited to, a processor 30 and a memory 31. Those skilled in the art will understand that Figure 3 It is only an example of terminal 3 and does not constitute a limitation on terminal 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0181] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0182] The memory 31 may be an internal storage unit of the terminal 3, such as a hard disk or memory of the terminal 3. The memory 31 may also be an external storage device of the terminal 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash memory card, etc. equipped on the terminal 3. Furthermore, the memory 31 may include both an internal storage unit of the terminal 3 and an external storage device. The memory 31 is used to store the computer program and other programs and data required by the terminal. The memory 31 may also be used to temporarily store data that has been output or is about to be output.

[0183] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0184] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0185] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or 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. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0186] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, and can be electrical, mechanical, or other forms.

[0187] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0188] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0189] If the integrated module / unit 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 present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various embodiments of the atmospheric pollution source tracing method based on multi-source data fusion. Among them, the computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practices in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practices, computer-readable media does not include electrical carrier signals and telecommunication signals.

[0190] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for tracing the source of air pollution based on multi-source data fusion, characterized in that: include: Obtaining air quality monitoring data and pollution source monitoring data for a target city, wherein the air quality monitoring data for the target city includes monitoring data from multiple monitoring sites in the target city, and for any monitoring site, the monitoring data at the monitoring site includes concentration information of multiple preset types of pollution parameters; and the pollution source monitoring data includes monitoring data from multiple pollution source monitoring points, each pollution source monitoring point corresponding to at least one type of pollution source; For any monitoring site in the target city, determining whether a target pollution parameter exists based on the monitoring data of the monitoring site, wherein the target pollution parameter is used to represent a pollution parameter that meets the corresponding pollution parameter alarm preset conditions among the multiple preset types of pollution parameters; If the target pollution parameter exists at the monitoring site, determine whether the area corresponding to the monitoring site is individually polluted based on the first monitoring value and the second monitoring value of the target pollution parameter, wherein the first monitoring value is the concentration value of the target pollution parameter monitored by the monitoring site, and the second monitoring value is the reference concentration value of the target pollution parameter in the target city; If the monitoring site corresponds to regional individual pollution, determining at least one pollution type corresponding to the monitoring site; Determine the monitoring data of all pollution source monitoring points within the traceability range corresponding to the monitoring station. For each pollution type corresponding to the monitoring station, calculate the contribution value of each target pollution source within the traceability range to the pollution type in turn, and obtain the pollution source tracing result for the pollution type, wherein the type of the target pollution source is related to the pollution type. Before determining whether the area corresponding to the monitoring station is individually polluted, the method further includes: Obtain the geographic location information of each monitoring site; The determination of whether the area corresponding to the monitoring station is individually polluted includes: Calculating an absolute value of a difference between the first monitoring value and the second monitoring value; If the absolute value of the difference is less than or equal to the first preset value, the polluted area is the overall pollution of the target city; If the absolute value of the difference is greater than the first preset value, the target local area is determined based on the geographical location information of the monitoring site, with the monitoring site as the center and the preset length as the radius, and the concentration value of the target pollution parameter monitored by other monitoring sites in the target local area is obtained. If the difference between the first monitoring value and the concentration value of the target pollution parameter monitored by other monitoring sites in the target local area is greater than the first preset value, the polluted area is the area corresponding to the monitoring site, otherwise it is the pollution in the local area of ​​the city.

2. The method according to claim 1, characterized in that For any monitoring station in the target city, judging whether the target pollution parameter exists based on the monitoring data of the monitoring station includes: For any type of pollution parameter among the multiple preset types of pollution parameters, if the concentration value of the pollution parameter is greater than or equal to the preset threshold value corresponding to the pollution parameter, or the concentration value of the pollution parameter has an increasing trend, or the concentration value of the pollution parameter has a continuous high trend, then the pollution parameter is the target pollution parameter.

3. The method according to claim 2, characterized in that For any type of pollution parameter among the plurality of preset types of pollution parameters, determining whether a concentration value of the pollution parameter has an increasing trend includes: Calculating a first concentration increase percentage of the pollution parameter based on the concentration value of the pollution parameter at the current moment and the concentration value at the previous moment; Determining, based on the concentration value of the pollution parameter at the current moment falling within a concentration interval in a first preset list, a percentage limit corresponding to the concentration value at the current moment, according to the first preset list, wherein, for any pollution parameter among the multiple preset types of pollution parameters, the first preset list includes multiple consecutive but non-overlapping concentration intervals corresponding to the pollution parameter and the percentage limit corresponding to each concentration interval, and the percentage limit corresponding to each concentration interval is a positive number; If the first concentration increase percentage of the pollution parameter is greater than the percentage limit corresponding to the concentration value at the current moment, then the concentration value of the pollution parameter has an increasing trend.

4. The method according to claim 3, characterized in that For any type of pollution parameter among the plurality of preset types of pollution parameters, determining whether a concentration value of the pollution parameter has a continuously high trend includes: Calculating a second concentration increase percentage of the pollution parameter based on the concentration value of the pollution parameter at the current moment and the average concentration value of the pollution parameter at the previous m moments, where the previous m moments are m consecutive moments before the current moment; If the first concentration percentage of the pollution parameter is greater than the first preset percentage and less than the percentage limit corresponding to the concentration value at the current moment, and the second concentration percentage of the pollution parameter is greater than the second preset percentage, then the concentration value of the pollution parameter has a trend of continuing to be high, wherein the first preset percentage is a negative number and the second preset percentage is a positive number.

5. The method according to claim 1, wherein Before determining whether the area corresponding to the monitoring station is individually polluted, the method further includes: Acquire meteorological data of the target city, particulate matter monitoring data of the target city, and air quality monitoring data of cities adjacent to the target city, wherein the meteorological data includes humidity, wind speed, and wind direction of the target city; If the polluted area is the entire target city, the method further includes: If the humidity value of the target city is greater than a first preset humidity, the wind speed is less than or equal to the first preset wind speed, and the wind direction changes at least once within a first preset time period, then it is determined that the overall pollution type of the target city is a static and stable state, and the cause of the pollution is pollution accumulation due to meteorological reasons; If the humidity value of the target city is less than a second preset humidity, the wind speed is greater than or equal to the second preset wind speed, and the wind direction does not change within a second preset time period, then the type of overall pollution in the target city is determined to be a non-stationary state. The upwind city of the target city is determined based on the wind direction, and a change trend curve of the target pollution parameter in the upwind city is compared with a change trend curve in the target city. If the change trend curves are consistent, or the concentration of the target pollution parameter in the upwind city increases earlier than that in the target city, then it is determined that the cause of pollution in the target city is urban pollution caused by the influence of the upwind city. Obtain NO3 in the particulate matter monitoring data of the target city - and SO4 2- The ion concentration of NO3 - and SO4 2- The ion concentration determines the pollution source, among which, when SO4 2- The ion concentration is greater than NO3 - When the ion concentration is 2.5, the pollution sources are the combustion sources and sulfide production enterprises in the target city. When SO4 2- The ion concentration is less than NO3 - When the ion concentration is greater than 1%, the pollution sources are traffic sources, combustion sources and industrial sources in the target city.

6. The method according to any one of claims 1 to 4, characterized in that For each pollution type corresponding to the monitoring site, sequentially calculating the contribution value of each target pollution source within the traceability range to the pollution type includes: According to the pollution type, determining all types of pollution sources related to the pollution type according to a second preset list, wherein for each pollution type, the second preset list includes all types of pollution sources related to the pollution type; Determine all target pollution sources within the scope of the traceability based on all types of pollution sources related to the pollution type; For any target pollution source, the emission intensity of the target pollution source is obtained through normalization processing; According to the distance between each target pollution source and the monitoring site, the weight of each target pollution source is calculated by the inverse distance weighting algorithm; For each target pollution source, the contribution value of the target pollution source to the pollution type is calculated based on the emission intensity and weight of the target pollution source.

7. The method according to any one of claims 1 to 4, characterized in that For any monitoring site, the method for determining the traceability scope corresponding to the monitoring site includes: Obtaining the wind direction value of the monitoring site at the alarm moment and the wind speed value in a preset time period, wherein the alarm moment is the moment when the target pollution parameter appears at the monitoring site, and the preset time period includes the alarm moment; Determining the upwind direction of the monitoring site according to the wind direction value at the alarm moment; Determining a tracing radius based on the wind speed value during the preset time period; The tracing range corresponding to the monitoring site is determined according to the upwind direction of the monitoring site and the tracing radius.

8. A terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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