CN116626233A

CN116626233A - Air pollution tracing method based on multi-source data fusion, terminal and storage medium

Info

Publication number: CN116626233A
Application number: CN202310512484.7A
Authority: CN
Inventors: 马景金; 潘本锋; 武蕾丹; 李铮; 李春露; 张雪; 张朝
Original assignee: Hebei Advanced Environmental Protection Industry Innovation Center Co ltd; Hebei Sailhero Environmental Protection High Tech Co ltd
Current assignee: Hebei Advanced Environmental Protection Industry Innovation Center Co ltd; Hebei Sailhero Environmental Protection High Tech Co ltd
Priority date: 2023-05-08
Filing date: 2023-05-08
Publication date: 2023-08-22

Abstract

The invention provides an atmosphere pollution tracing method, a terminal and a storage medium based on multi-source data fusion, which comprise the following steps: acquiring air quality monitoring data and pollution source monitoring data of a target city; for any monitoring station, judging whether a target pollution parameter exists according to the monitoring data of the monitoring station; if the target pollution parameter exists in the monitoring station, judging whether the area corresponding to the monitoring station is polluted independently according to the first monitoring value and the second monitoring value of the target pollution parameter; if the area corresponding to the monitoring station is singly polluted, determining at least one pollution type corresponding to the monitoring station; and determining monitoring data of all pollution source monitoring points in a tracing range corresponding to the monitoring point, and sequentially calculating contribution values of each target pollution source in the tracing range to each pollution type corresponding to the monitoring point to obtain a pollution source tracing result of the pollution type. The invention can improve the pollution tracing precision.

Description

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

Technical Field

The invention relates to the technical field of air quality monitoring, in particular to an air pollution tracing method, a terminal and a storage medium based on multi-source data fusion.

Background

At present, air quality monitoring enters a big data era, and besides conventional air quality monitoring stations such as national control points, province control points, village and town stations and the like, grid micro-station monitoring, online particulate matter source analysis, online VOCs (volatile organic compounds ) monitoring, site dust monitoring and other systems are also widely applied. Meanwhile, the air quality of China presents a good trend of overall improvement, the treatment of the atmospheric environment in various places enters a deeper level, and higher requirements are put on the tracing of the atmospheric pollution sources.

The pollution tracing mode adopted daily in the present stage is mainly combined with manual analysis and monitoring data and field investigation, and a great amount of time is required in the tracing process. And, partial type data analysis is difficult, and the requirement of analysts is high, for example, the analysis of source analysis data requires more basic working experience as support. The pollution tracing working speed is slower, the result is lagged, the influence of subjective factors of analysts is larger, and the environment management cannot be effectively supported.

Therefore, how to improve the efficiency and accuracy of air pollution tracing based on multi-source data fusion is an urgent problem to be solved in the prior art.

Disclosure of Invention

In view of the above, the invention provides an atmosphere pollution tracing method, an atmosphere pollution tracing device, an atmosphere pollution tracing terminal and a storage medium based on multi-source data fusion, which can solve the problem of low atmosphere pollution tracing efficiency based on multi-source data fusion.

In a first aspect, an embodiment of the present invention provides an atmospheric pollution tracing method based on multi-source data fusion, including:

acquiring air quality monitoring data and pollution source monitoring data of a target city, wherein the air quality monitoring data of the target city comprises monitoring data of a plurality of monitoring stations in the target city, and for any monitoring station, the monitoring data of the monitoring station comprise concentration information of a plurality of preset types of pollution parameters, the pollution source monitoring data comprise monitoring data of a plurality of pollution source monitoring points, and each pollution source monitoring point corresponds to at least one type of pollution source;

judging whether a target pollution parameter exists or not according to monitoring data of any monitoring station in the target city, wherein the target pollution parameter is used for representing a pollution parameter meeting a corresponding pollution parameter alarm preset condition in the pollution parameters of multiple preset types;

If the target pollution parameter exists in the monitoring station, judging whether the target pollution parameter is singly polluted in the area corresponding to the monitoring station according to a first monitoring value and a second monitoring value of the target pollution parameter, wherein the first monitoring value is a concentration value of the target pollution parameter monitored by the monitoring station, and the second monitoring value is a reference concentration value of the target pollution parameter in the target city;

if the area corresponding to the monitoring station is singly polluted, determining at least one pollution type corresponding to the monitoring station;

and determining monitoring data of all pollution source monitoring points in a tracing range corresponding to the monitoring point, and for each pollution type corresponding to the monitoring point, calculating contribution values of each target pollution source in the tracing range to the pollution type in sequence to obtain a pollution source tracing result of the pollution type, wherein the type of the target pollution source is related to the pollution type.

In one possible implementation manner, for any monitoring site in the target city, determining whether the target pollution parameter exists according to the monitoring data of the monitoring site includes:

For any type of pollution parameter in the plurality of preset types of pollution parameters, if the concentration value of the pollution parameter is greater than or equal to a 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, the pollution parameter is the target pollution parameter.

In one possible implementation manner, for any type of pollution parameter in the plurality of preset types of pollution parameters, determining whether there is an increasing trend in the concentration value of the pollution parameter includes:

calculating a first concentration rise percentage of the pollution parameter according to the concentration value of the pollution parameter at the current moment and the concentration value of the pollution parameter at the last moment;

determining a percentage limit value corresponding to the concentration value at the current moment according to the concentration value at the current moment of the pollution parameter in a first preset list and the concentration interval to which the first preset list belongs, wherein for any pollution parameter in the plurality of preset types of pollution parameters, the first preset list comprises a plurality of continuous but non-coincident concentration intervals corresponding to the pollution parameter, and a percentage limit value corresponding to each concentration interval, and the percentage limit value corresponding to each concentration interval is a positive number;

If the first concentration rising percentage of the pollution parameter is larger than the percentage limit value corresponding to the concentration value at the current moment, the concentration value of the pollution parameter has a rising trend.

In one possible implementation manner, for any type of pollution parameter in the plurality of preset types of pollution parameters, determining whether there is a continuous high-level trend in the concentration value of the pollution parameter includes:

calculating a second concentration rise percentage of the pollution parameter according to the concentration value of the pollution parameter at the current moment and the concentration average value of the previous m moments, wherein the previous m moments are m continuous moments before the current moment;

if the first concentration percentage of the pollution parameter is greater than a first preset percentage and less than a percentage limit value corresponding to the concentration value at the current moment, and the second concentration percentage of the pollution parameter is greater than a second preset percentage, 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.

In one possible implementation, before determining whether the area corresponding to the monitoring site is contaminated separately, the method further includes:

Obtaining geographic position information of each monitoring station;

the judging whether the area corresponding to the monitoring station is singly polluted comprises the following steps:

calculating the absolute value of the difference between the first monitoring value and the second monitoring value;

if the absolute value of the difference is smaller than or equal to a first preset value, the pollution area is the whole pollution of the target city;

and if the absolute value of the difference is larger than the first preset value, determining a target local area by taking the monitoring station as a circle center and taking a preset length as a radius according to the geographic position information of the monitoring station, acquiring concentration values of the target pollution parameters monitored by other monitoring stations in the target local area, and if the difference between the first monitoring value and the concentration values of the target pollution parameters monitored by other monitoring stations in the target local area is larger than the first preset value, independently polluting the pollution area corresponding to the monitoring station.

acquiring meteorological data of the target city, particulate matter monitoring data of the target city and air quality monitoring data of adjacent cities of the target city, wherein the meteorological data comprise humidity values, wind speeds and wind directions of the target city;

If the polluted area is the whole pollution of the target city, the method further comprises the following steps:

if the humidity value of the target city is larger than the first preset humidity, the wind speed is smaller than or equal to the first preset wind speed, and the wind direction changes at least once within the first preset time, judging that the type of the integral pollution of the target city is in a stable state, wherein the pollution cause is pollution accumulation caused by meteorological causes;

if the humidity value of the target city is smaller than the second preset humidity, the wind speed is larger than or equal to the second preset wind speed, and the wind direction is not changed within the second preset time, judging that the type of the integral pollution of the target city is in a non-stationary state, determining the upwind city of the target city according to the wind direction, comparing the change trend curve of the target pollution parameter in the upwind city with the change trend curve of the target city, and judging that the pollution source of the target city is urban pollution caused by the influence of the upwind city if the change trend curve is consistent or the concentration rising time of the target pollution parameter in the upwind city is earlier than that of the target city;

acquiring NO in the particulate matter monitoring data of the target city ₃ ^- And SO ₄ ^2- According to the ion concentration of NO ₃ ^- And SO ₄ ^2- Wherein, when SO ₄ ^2- Ion concentration of (2) is greater than NO ₃ ^- The pollution source is the combustion source of the target city and sulfide production enterprises, when SO ₄ ^2- Is less than NO ₃ ^- The pollution sources are the target urban traffic source, the combustion source and the industrial source.

In one possible implementation manner, for each pollution type corresponding to the monitoring station, calculating, in turn, a contribution value of each target pollution source in the traceability range to the pollution type includes:

determining all pollution sources related to the pollution type according to the pollution type and a second preset list, wherein for each pollution type, all the pollution sources related to the pollution type are included in the second preset list;

determining all target pollution sources within the traceable range according to all pollution sources related to the pollution type;

for any target pollution source, acquiring the emission intensity of the target pollution source through normalization treatment;

calculating the weight of each target pollution source through an inverse distance weight algorithm according to the distance between each target pollution source and the monitoring station;

For each target pollution source, calculating a contribution value of the target pollution source to the pollution type through emission intensity and weight of the target pollution source.

In one possible implementation manner, for any monitoring station, the method for determining the traceability range corresponding to the monitoring station includes:

acquiring a wind direction value of the monitoring station at the alarm time and a wind speed value in a preset time period, wherein the alarm time is the time when the target pollution parameter occurs at the monitoring station, and the preset time period comprises the alarm time;

according to the wind direction value of the alarm moment, determining the upwind direction of the monitoring station;

determining a tracing radius according to the wind speed value of the preset time period;

and determining a tracing range corresponding to the monitoring station according to the upwind direction and the tracing radius of the monitoring station.

In a second aspect, embodiments of the present invention provide a terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method as described above in the first aspect or any one of the possible implementations of the first aspect when the computer program is executed.

In a third aspect, embodiments of the present invention provide a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method as described above in the first aspect or any one of the possible implementations of the first aspect.

Compared with the prior art, the embodiment of the invention has the beneficial effects that:

according to the method, abnormal pollution parameters are identified through air quality monitoring data and pollution source monitoring data of a target city, whether the pollution is single pollution or integral pollution of the city is judged according to the target pollution parameters, when the pollution is single at the monitoring site, the pollution type is identified, the tracing range is determined, the pollution source type related to the pollution type is determined in the tracing range, the pollution source of the related pollution source type is obtained as the target pollution source, the contribution value of each target pollution source to the pollution type is calculated, the tracing result corresponding to the pollution type is obtained, and the monitoring data used in the embodiment of the invention are all existing real-time data.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of an implementation of an air pollution tracing method based on multi-source data fusion provided by an embodiment of the invention;

fig. 2 is a schematic structural diagram of an air pollution tracing device based on multi-source data fusion according to an embodiment of the present invention;

fig. 3 is a schematic diagram of a terminal according to an embodiment of the present invention.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, 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.

For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the following description will be made by way of specific embodiments with reference to the accompanying drawings.

Conventional research pollution tracing technical methods comprise pollution source emission lists, diffusion models, receptor models and the like, but the methods have higher demands on basic data such as urban various pollution source emission amounts, receptor point component types and the like. The research methods are easy to use and limited, have poor timeliness, and have insufficient data application to urban air quality monitoring systems and pollution source real-time monitoring systems, and the mining of the data relations is insufficient.

Therefore, a method for efficiently and rapidly performing comprehensive tracing of the air pollution based on multi-source data fusion is needed. The invention provides one such method, referring to fig. 1, which shows a flowchart for implementing the air pollution tracing method based on multi-source data fusion according to the embodiment of the invention, and the detailed description is as follows:

in step 101, air quality monitoring data and pollution source monitoring data of a target city are acquired.

The air quality monitoring data of the target city comprise monitoring data of a plurality of monitoring stations in the target city, for any monitoring station, the monitoring data of the monitoring station comprise concentration information of pollution parameters of various preset types, the pollution source monitoring data comprise monitoring data of a plurality of pollution source monitoring points, and each pollution source monitoring point corresponds to at least one type of pollution source.

In an embodiment of the invention, the monitoring stations include, but are not limited to, national control automatic monitoring stations, provincial control automatic monitoring stations, municipal control automatic monitoring stations and village and town monitoring stations. Types of contamination parameters include, but are not limited to, PM ₁₀ 、PM _2.5 、SO ₂ 、NO ₂ CO and O ₃ Six contamination parameters, eachThe monitoring station can obtain real-time concentration information for each type of contamination parameter.

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

In the embodiment of the invention, the pollution source monitoring points comprise various types of monitoring points, for example, the pollution source monitoring points can be monitoring points for monitoring dust data of the urban construction site, monitoring points for acquiring emission monitoring data of industrial enterprises, monitoring points for monitoring boiler emission, navigation monitoring points and the like.

In an alternative implementation manner of the embodiment of the present invention, the method is further suitable for deployment of cities or areas of gridding micro-stations, in such cities or areas, grids are set according to preset step sizes, for example, grids are divided into a plurality of grids according to 3km by 3km, each grid is provided with one micro-station, and one micro-station is a pollution source monitoring point in the step.

Based on this, in one possible implementation, the pollution sources are categorized for each pollution source monitoring point according to the type of monitoring data and the location distribution of the pollution source monitoring points, each pollution source monitoring point corresponding to at least one type of pollution source. For example, the pollution source type corresponding to the pollution source monitoring point for realizing the on-line monitoring of the industrial enterprise is the industrial enterprise, the pollution source type corresponding to the site dust pollution source monitoring point is the construction site, the pollution source for the on-line monitoring of catering is the catering, and the pollution source corresponding to the gridding micro station positioned on the traffic main road is the road.

In an example of a distance, the pollution source used for monitoring by the pollution source monitoring point 1 is an industrial enterprise 1, the corresponding pollution source type is an industrial enterprise, the pollution source monitoring point 2 is used for monitoring a catering enterprise 1, the corresponding pollution source type is a catering, the pollution source monitoring point 3 is used for monitoring a construction site 1, and the corresponding pollution source type is a construction site … …

In the embodiment of the invention, various pollution source monitoring points are described in a classified introduction mode.

First kind, urban gridding microAnd the model station acquires the geographic position information of each micro station in advance, including but not limited to longitude and latitude information of each micro station. Real-time PM monitoring per micro station ₁₀ 、PM _2.5 、SO ₂ 、NO ₂ CO and O ₃ Hourly data for six contamination parameters. Meanwhile, according to the type of the pollution source around the meshed micro station, corresponding labels are allocated to each micro station, each micro station can correspond to one or more labels according to actual conditions, and each label corresponds to one type of the pollution source. For example, a road is marked near a main road, a restaurant is marked near a restaurant gathering area, an industrial enterprise is marked near an industrial enterprise, and a residential area is marked near a rural residential area.

The second category is that the dust-raising monitoring points of the urban construction site are also one pollution source monitoring point in the step, and the geographic position information of each monitoring point is obtained in advance, including but not limited to longitude and latitude information of each monitoring point. For obtaining dust monitoring data, including but not limited to PM, at a municipal worksite ₁₀ And PM _2.5 Hour by hour data. The corresponding pollution source type is a construction site.

Third, industrial enterprises discharge monitoring points, each monitoring point also belongs to one pollution source monitoring point in the step, and geographic position information of each monitoring point is obtained in advance, including but not limited to longitude and latitude information of each monitoring point, geographic position information of corresponding industries or enterprises and discharge port name information. The corresponding pollution source type is an industrial source and is used for acquiring emission monitoring data of industrial enterprises, including but not limited to monitoring parameters such as exhaust emission of an exhaust port, average flow rate, measured concentration of pollutants, emission of pollutants and the like.

In a fourth class, other types of monitoring points, each monitoring point also belongs to one pollution source monitoring point in the step, and geographic position information of each monitoring point is obtained in advance, including but not limited to longitude and latitude information of each monitoring point, for example, a monitoring point used for obtaining boiler monitoring data, hour-by-hour data used for obtaining various pollution parameters emitted by a boiler, a corresponding pollution source type is a heat supply source, and a conventional parameter navigation monitoring data, satellite remote sensing data and navigation monitoring points of various pollution parameters hour-by-hour monitoring data are obtained. The pollution source type corresponding to each navigation monitoring point can be determined according to the position of the navigation monitoring point, for example, the pollution source type is catering when the pollution source type is near a catering enterprise.

In step 102, for any monitoring site in the target city, it is determined whether the target pollution parameter exists according to the monitoring data of the monitoring site.

The target pollution parameter is used for representing pollution parameters meeting the alarm preset conditions of the corresponding pollution parameters in various preset types of pollution parameters.

In the embodiment of the invention, for any type of pollution parameter in a plurality of preset types of pollution parameters, according to the concentration value of the pollution parameter at the current moment and the concentration value of the pollution parameter at the last 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, the pollution parameter is a target pollution parameter.

Alternatively, for any type of contamination parameter, e.g. PM ₁₀ The predetermined threshold value for the pollution parameter may be determined by eighty percent of the annual hour data of the parameter. The method for setting the preset threshold corresponding to each type of pollution parameter is not limited in the embodiment of the invention.

In an alternative implementation, for any one of a plurality of preset types of pollution parameters, determining whether there is an increasing trend in the concentration value of the pollution parameter includes: calculating a first concentration rise percentage of the pollution parameter according to the concentration value of the pollution parameter at the current moment and the concentration value of the pollution parameter at the last moment; determining a percentage limit value corresponding to the concentration value at the current moment according to the concentration value at the current moment of the pollution parameter in a first preset list and the concentration interval to which the first preset list belongs, wherein for any pollution parameter in a plurality of preset types of pollution parameters, the first preset list comprises a plurality of continuous but non-coincident concentration intervals corresponding to the pollution parameter and a percentage limit value corresponding to each concentration interval, and the percentage limit value corresponding to each concentration interval is a positive number; if the first concentration rising percentage of the pollution parameter is larger than the percentage limit value corresponding to the concentration value at the current moment, the concentration value of the pollution parameter has a rising trend.

The following describes a specific example. The current time is t time, and the concentration of a certain pollution parameter is X _t The concentration value of the pollution parameter at the time (t-1) is X _t-1 The first concentration increase percentage is calculated by a first formula, the first formula being

Wherein is a first concentration percentage of the contamination parameter.

The first preset list can be represented by the following table 1, table 1 being

According to X _t Determining corresponding percentage limit value in the concentration range of the first preset list SO that the pollution parameter is SO ₂ For example, at time t SO ₂ The corresponding percentage limit value obtained by looking up Table 1 above is 30% if the concentration parameter of (2) is 15%, and the SO is specified if n > 30% ₂ There is a tendency for the concentration to rise.

In table 1, when the concentration corresponding to the concentration range is low, it is indicated that the current concentration of the pollution parameter is low, and the percentage limit corresponding to the concentration range may not be set, or the percentage limit may be understood as infinity at this time.

In an alternative implementation, for any one of a plurality of preset types of pollution parameters, determining whether there is a continuous high trend in a concentration value of the pollution parameter includes: calculating a second concentration rise percentage of the pollution parameter according to the concentration value of the pollution parameter at the current moment and the concentration average value of the first m moments, wherein the first m moments are m continuous moments before the current moment; if the first concentration percentage of the pollution parameter is greater than a first preset percentage and less than a percentage limit value corresponding to the concentration value at the current moment, and the second concentration percentage of the pollution parameter is greater than a second preset percentage, 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.

The purpose of this step is to calculate the percentage increase in concentration based on a running average of several hours before t-hour, above which an alarm is activated, for a pollution process that increases continuously but is below a percentage limit, or continues at a high concentration and decreases less in amplitude. That is, a percentage exceeding this indicates a continuing trend in the contamination parameter.

For ease of understanding, the description continues with reference to the examples above.

Assuming m=4, for a certain contamination parameter, the concentration values at 4 times before the current time are each represented by X _t-4 、X _t-3 、X _t-2 、X _t-1 The second percent increase in concentration can be calculated by a second formula, the second formula being

Where n' is used to represent the second percent concentration increase.

For example, a first predetermined percentage = -10% and a second predetermined percentage = 20% are set, if n' > 20% and n > -10%, indicating that the concentration value of the contamination parameter has a tendency to stay high.

In step 103, if the target pollution parameter exists in the monitoring station, whether the area corresponding to the monitoring station is polluted independently is judged according to the first monitoring value and the second monitoring value of the target pollution parameter.

The first monitoring value is the concentration value of the target pollution parameter monitored by the monitoring station, and the second monitoring value is the reference concentration value of the target pollution parameter in the target city. Optionally, the second monitoring value is a concentration value of the pollution parameter monitored by the national control station.

In an alternative implementation, geographical location information of each monitoring station is obtained; calculating the absolute value of the difference between the first monitoring value and the second monitoring value; if the absolute value of the difference is smaller than or equal to a first preset value, the pollution area is the whole pollution of the target city; if the absolute value of the difference is larger than a first preset value, determining a target local area by taking the monitoring station as a circle center and taking a preset length as a radius according to the geographic position information of the monitoring station, acquiring concentration values of target pollution parameters monitored by other monitoring stations in the target local area, and if the difference between the first monitoring value and the concentration values of the target pollution parameters monitored by other monitoring stations in the target local area is larger than the first preset value, independently polluting the pollution area corresponding to the monitoring station.

In the embodiment of the invention, when one monitoring station monitors that the target pollution parameter exists, an alarm message is sent. Therefore, in the embodiment of the present invention, for convenience of explanation, a monitoring site where the target pollution parameter exists will be referred to as an alarm site. For the target pollution parameter, comparing the concentration value of the pollution parameter monitored by the alarm station with the concentration value of the pollution parameter monitored by the target city, for example, setting a first preset value=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%, namely, the absolute value of the difference is smaller than 10%, the whole pollution of the city is indicated. If the difference is greater than 10%, the alarm station is used as a center of a circle, the preset radius length, such as 5km, is used as a radius, the concentration value of the pollution parameter monitored by other monitoring stations in the range is determined, if the difference is greater than 10% with the concentration value monitored by other monitoring stations, the alarm station is singly polluted, and otherwise, the local area pollution is caused.

In an alternative implementation, weather data of a target city, including humidity values, wind speeds, and wind directions of the target city, particulate matter monitoring data of the target city, and air quality monitoring data of neighboring cities of the target city are obtained.

Optionally, weather data of the target city include time-by-time weather data of the target city including, but not limited to, temperature, humidity, wind direction, wind speed; the city air quality monitoring point comprises time-by-time meteorological data including temperature, humidity, wind direction, wind speed and atmospheric pressure.

Alternatively, the particulate matter monitoring data of the target city may be city particulate matter online source analytical monitoring data including, but not limited to, geographic location information and latitude and longitude of the enterprise, and NO in online ion chromatography ₃ ^- 、SO ₄ ^2- 、NH ₄ ⁺ And Ca ²⁺ And the like on an hour-by-hour concentration data.

Optionally, the air quality monitoring data of the neighboring cities of the target city includes, but is not limited to, the geographic location of the target city neighboring city national control station, the latitude and longitude, and the PM ₁₀ 、PM _2.5 、SO ₂ 、NO ₂ CO and O ₃ Concentration monitoring data.

If the contaminated area is the whole city pollution, the method further comprises the following steps: if the humidity value of the target city is larger than the first preset humidity, the wind speed is smaller than or equal to the first preset wind speed, and the wind direction changes at least once within the first preset time, judging that the type of the integral pollution of the target city is in a steady state, wherein the pollution cause is pollution accumulation caused by meteorological causes; if the humidity value of the target city is smaller than the second preset humidity, the wind speed is larger than or equal to the second preset wind speed, and the wind direction is not changed within the second preset time, judging that the type of the integral pollution of the target city is in an unstable state, determining the upwind city of the target city according to the wind direction, comparing the change trend curve of the target pollution parameter in the upwind city with the change trend curve of the target city, and judging that the pollution source of the target city is urban pollution caused by the influence of the upwind city if the change trend curve is consistent or the concentration rising time of the target pollution parameter in the upwind city is earlier than that of the target city; obtaining NO in particulate matter monitoring data of target city ₃ ^- And SO ₄ ^2- According to the ion concentration of NO ₃ ^- And SO ₄ ^2- Wherein, when SO ₄ ^2- Ion concentration of (2) is greater than NO ₃ ^- The pollution source is the combustion source of the target city and sulfide production enterprises when SO ₄ ^2- Is less than NO ₃ ^- The pollution sources are the target urban traffic sources, combustion sources and industrial sources.

For example, if the humidity is 70% to 99%, the wind level is 0 to 2, and the wind direction is varied, it is considered that the static state is present at this time, and the diffusion condition is unfavorable.

For another example, if the humidity is lower than 50%, the wind speed is 3 stages and above, and the wind direction is stable in the same direction for 3 hours and above, it is considered that the state is not stationary. And comparing the change trend of the same parameter with that of the upwind city, and judging that the city is polluted by the upwind direction if the change trend is basically consistent or the upwind city rises 1 to 3 hours before the city.

Resolving NO in online ion chromatography based on urban particulate matter online source ₃ ^- 、SO ₄ ^2- And NH ₄ ⁺ And (3) judging the local key control direction under the stationary weather condition. When SO ₄ ^2- /NO ₃ ^- When less than 1, NO ₃ ^- If the contribution of the fuel is higher, the management and control of a local traffic source, a combustion source or an industrial source and the like are required to be enhanced; when SO42-/NO 3-is greater than 1, the contribution of SO 42-is higher, and the control of local combustion sources and sulfide production enterprises needs to be enhanced.

Urban pollution results include pollution type and local pollution focus control direction. Listing the urban pollution type according to the urban pollution type judgment result, and listing the local key control direction according to the urban particulate matter on-line source analysis on-line ion chromatography judgment result.

In step 104, if the monitoring site corresponds to an individual contamination of the area, then at least one type of contamination corresponding to the monitoring site is determined.

In the embodiment of the invention, at least one pollution type corresponding to the monitoring station can be determined through the prior art. Alternatively, the pollution type of the monitoring station can be judged by a technical method provided in patent application number CN202010846058.3, and the patent name is a pollution source type automatic identification method based on machine learning.

The pollution type may be identified by other existing algorithms, such as determining the pollution type by an empirical value, or by an expert, which the embodiments of the present invention are not limited to.

In step 105, monitoring data of all pollution source monitoring points in a tracing range corresponding to the monitoring point are determined, and for each pollution type corresponding to the monitoring point, contribution values of each target pollution source in the tracing range to the pollution type are calculated in sequence, so that a pollution source tracing result of the pollution type is obtained, wherein the type of the target pollution source is related to the pollution type.

In the embodiment of the present invention, if it is determined in step 103 that the urban overall pollution or the urban local area pollution is detected, NO pollution tracing is performed, and NO in the particulate matter monitoring data of the target city is directly detected ₃ ^- And SO ₄ ^2- The ion concentration of (2) determines the source of the contamination.

If the monitoring station is determined to be polluted independently in the step 103, after the pollution type is determined in the step 104, the pollution source corresponding to the pollution type is analyzed through the step, so that the accurate identification of the pollution source is realized, the corresponding pollution source is managed and controlled, and the purpose of continuously increasing the pollution degree is achieved by fast and accurate control.

In an optional implementation manner, for any monitoring station, the method for determining the traceability range corresponding to the monitoring station includes: acquiring a wind direction value of the monitoring station point at the alarm time and a wind speed value in a preset time period, wherein the alarm time is the time when the target pollution parameter of the monitoring station point appears, and the preset time period comprises the alarm time; according to the wind direction value at the alarming moment, determining the upwind direction of the monitoring station; determining a tracing radius according to the wind speed value in a preset time period; and determining the tracing range corresponding to the monitoring station according to the upwind direction and the tracing radius of the monitoring station.

Optionally, wind direction angles are divided according to the traditional eight basic directions, the upwind direction of a pollution source is obtained according to the actual wind direction degrees, then the position is judged according to the wind speed, the tracing radius is defined according to the highest wind speed of an hour, further, considering the influence of long-distance pollution continuous transmission, the tracing radius range can be defined according to the highest wind speed transmission distance of 2 to 4 hours, and finally, the pollution source tracing range of the monitoring station is determined according to the upwind direction and the tracing radius range. The pollution sources corresponding to all pollution source monitoring points in the pollution source tracing range of the monitoring station are objects to be analyzed.

In an alternative implementation, according to the pollution type, determining all pollution sources related to the pollution type according to a second preset list, wherein for each pollution type, the second preset list comprises all pollution sources related to the pollution type; determining all target pollution sources in a traceable range according to all pollution sources related to the pollution type; for any target pollution source, acquiring the emission intensity of the target pollution source through normalization treatment; calculating the weight of each target pollution source through an inverse distance weight algorithm according to the distance between each target pollution source and the monitoring station; for each target pollution source, calculating a contribution value of the target pollution source to the pollution type through emission intensity and weight of the target pollution source.

For example, the pollution types include 5 types of dust sources, mobile sources, coal sources, catering lampblack sources and industrial sources, and the pollution types include eight types of industrial enterprises, boilers, catering, construction sites, roads, residential areas, fire points and motor vehicle tail gases.

Setting through experience values, wherein in a second preset list, pollution source types related to dust raising sources are industrial enterprises, construction sites, roads, residential areas and fire points; the pollution source types related to the mobile source are industrial enterprises, construction sites, roads, fire points and motor vehicle tail gases, the pollution source types related to the coal-fired source are industrial enterprises, boilers, catering, residential areas, fire points and motor vehicle tail gases, the pollution source types related to the catering oil smoke source are catering, residential areas and fire points, and the pollution source types related to the industrial source are industrial sources, boilers, residential areas, fire points and motor vehicle tail gases.

When the pollution type is determined in step 104, if the pollution type is a dust source, it is known from the second preset list that the pollution source type related to the dust source is an industrial enterprise, a construction site, a road, a residential area, and a fire point, and the pollution source corresponding to the pollution source monitoring point of the industrial enterprise, the construction site, the road, the residential area, and the fire point is obtained in the traceability range as the target pollution source.

Specifically, the implementation process of this step may be:

first, pollution source data is determined.

The emission intensity q of different pollution sources adopts different basic data.

The pollution sources with air quality monitoring such as construction sites, road traffic and the like adopt real-time monitoring concentration as emission intensity. And in the traceability range, if the monitoring data of the conventional parameter navigation monitoring points exist, classifying pollution sources according to the navigation positions, and taking the real-time monitoring concentration of the navigation monitoring points as the emission intensity.

The method combines two data of pollution source emission monitoring and air quality monitoring, wherein the emission in pollution source emission monitoring is preferentially adopted, and the real-time concentration monitoring of air quality monitoring is selected as one of the two data.

Second, normalizing pollution source data

The partial pollution sources adopt a mode of combining two kinds of data, different basic data of each pollution source are required to be normalized respectively, and the data are mapped into a range of 0-1, so that the data are dimensionless, and comparability is established. The normalized calculation formula is as follows:

wherein q _i For pollution source i emission intensity, q _min For the minimum emission intensity of the pollution source, q _max Maximum emission intensity of the pollution source, q _i ' is the result of normalization treatment of the pollution source.

When the pollution source adopts single data to represent the emission intensity, the data is normalized; when the pollution source adopts two or more data to represent emission intensity, such as organized emission monitoring and unorganized emission monitoring, different types of data are respectively normalized.

Third, calculating the weight of each target pollution source

Calculating the distance d from the target pollution source 1, the target pollution source 2 … … and the target pollution source n in the pollution source tracing area to the monitoring point according to the longitude and latitude information ₁ 、d ₂ ……d _n Weights for each target pollution source are then calculated based on the distances.

Wherein lambda is _i The weight of the target pollution source i. In consideration of large discharge volume of gaseous pollutants of industrial enterprises, when industrial pollution sources are traced, abnormal discharge enterprises can be identified according to the online monitoring data change condition of the enterprises, and a certain weight is added on the basis of the original weight, such as 0.5.

Fourth, calculating the contribution degree of the target pollution source:

wherein z is _i The contribution proportion of the target pollution source i is the contribution degree of the target pollution source i.

Fifthly, pollution tracing results:

The top 10 sources contributing the highest are listed according to the different pollution types, and the contribution ratio is noted. As shown in table 2 below, table 2 is:

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 source 1-2 (xx%)	Pollution source 2-2 (xx%)	Pollution source 3-2 (xx%)
				…	…	…	…
10	Pollution source 1-10 (xx%)	Pollution source 2-10 (xx%)	Pollution source 3-10 (xx%)

It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.

The following are device embodiments of the invention, for details not described in detail therein, reference may be made to the corresponding method embodiments described above.

Fig. 2 shows a schematic structural diagram of an air pollution tracing device based on multi-source data fusion according to an embodiment of the present invention, and for convenience of explanation, only the relevant parts of the embodiment of the present invention are shown, which is described in detail below:

as shown in fig. 2, the air pollution tracing device 2 based on multi-source data fusion includes: the device comprises a data acquisition module 21, a first judging module 22, a second judging module 23, a pollution type determining module 24 and a tracing module 25.

The data acquisition module 21 is configured to acquire air quality monitoring data and pollution source monitoring data of a target city, where the air quality monitoring data of the target city includes monitoring data of a plurality of monitoring sites in the target city, and for any monitoring site, the monitoring data of the monitoring site includes concentration information of a plurality of preset types of pollution parameters, the pollution source monitoring data includes monitoring data of a plurality of pollution source monitoring points, and each pollution source monitoring point corresponds to at least one type of pollution source;

A first judging module 22, configured to judge, for any monitoring site in the target city, whether a target pollution parameter exists according to monitoring data of the monitoring site, where the target pollution parameter is used to represent a pollution parameter that meets a corresponding pollution parameter alarm preset condition in a plurality of preset types of pollution parameters;

a second judging module 23, configured to judge whether the area corresponding to the monitoring station is polluted independently according to a first monitoring value and a second monitoring value of the target pollution parameter if the target pollution parameter exists in the monitoring station, where the first monitoring value is a concentration value of the target pollution parameter monitored by the monitoring station, and the second monitoring value is a reference concentration value of the target pollution parameter in the target city;

a pollution type determining module 24, configured to determine at least one pollution type corresponding to the monitoring station if the monitoring station corresponds to an individual pollution of an area;

the tracing module 25 is configured to determine monitoring data of all pollution source monitoring points in a tracing range corresponding to the monitoring point, and sequentially calculate, for each pollution type corresponding to the monitoring point, a contribution value of each target pollution source in the tracing range to the pollution type, to obtain a pollution source tracing result of the pollution type, where the type of the target pollution source is related to the pollution type.

In one possible implementation, the first determining module 22 is configured to:

for any type of pollution parameter in the plurality of 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, the pollution parameter is a target pollution parameter.

determining a percentage limit value corresponding to the concentration value at the current moment according to the concentration value at the current moment of the pollution parameter in a first preset list and the concentration interval to which the first preset list belongs, wherein for any pollution parameter in a plurality of preset types of pollution parameters, the first preset list comprises a plurality of continuous but non-coincident concentration intervals corresponding to the pollution parameter and a percentage limit value corresponding to each concentration interval, and the percentage limit value corresponding to each concentration interval is a positive number;

calculating a second concentration rise percentage of the pollution parameter according to the concentration value of the pollution parameter at the current moment and the concentration average value of the first m moments, wherein the first m moments are m continuous moments before the current moment;

In one possible implementation, the second determining module 23 is configured to:

obtaining geographic position information of each monitoring station;

if the absolute value of the difference is larger than a first preset value, determining a target local area by taking the monitoring station as a circle center and taking a preset length as a radius according to the geographic position information of the monitoring station, acquiring concentration values of target pollution parameters monitored by other monitoring stations in the target local area, and if the difference between the first monitoring value and the concentration values of the target pollution parameters monitored by other monitoring stations in the target local area is larger than the first preset value, independently polluting the pollution area corresponding to the monitoring station.

In one possible implementation, the second determining module 23 is further configured to:

acquiring meteorological data of a target city, particulate matter monitoring data of the target city and air quality monitoring data of adjacent cities of the target city, wherein the meteorological data comprise humidity values, wind speeds and wind directions of the target city;

if the contaminated area is the whole city pollution, the method further comprises the following steps:

if the humidity value of the target city is larger than the first preset humidity, the wind speed is smaller than or equal to the first preset wind speed, and the wind direction changes at least once within the first preset time, judging that the type of the integral pollution of the target city is in a steady state, wherein the pollution cause is pollution accumulation caused by meteorological causes;

if the humidity value of the target city is smaller than the second preset humidity, the wind speed is larger than or equal to the second preset wind speed, and the wind direction is not changed within the second preset time, judging that the type of the integral pollution of the target city is in an unstable state, determining the upwind city of the target city according to the wind direction, comparing the change trend curve of the target pollution parameter in the upwind city with the change trend curve of the target city, and judging that the pollution source of the target city is urban pollution caused by the influence of the upwind city if the change trend curve is consistent or the concentration rising time of the target pollution parameter in the upwind city is earlier than that of the target city;

Obtaining NO in particulate matter monitoring data of target city ₃ ^- And SO ₄ ^2- According to the ion concentration of NO ₃ ^- And SO ₄ ^2- Wherein, when SO ₄ ^2- Ion concentration of (2) is greater than NO ₃ ^- The pollution source is the combustion source of the target city and sulfide production enterprises when SO ₄ ^2- Is less than NO ₃ ^- The pollution sources are the target urban traffic sources, combustion sources and industrial sources.

In one possible implementation, the tracing module 25 is configured to:

determining all pollution sources related to the pollution type according to the pollution type and a second preset list, wherein for each pollution type, the second preset list comprises all pollution sources related to the pollution type;

determining all target pollution sources in a traceable range according to all pollution sources related to the pollution type;

In one possible implementation, the tracing module 25 is configured to:

acquiring a wind direction value of the monitoring station point at the alarm time and a wind speed value in a preset time period, wherein the alarm time is the time when the target pollution parameter of the monitoring station point appears, and the preset time period comprises the alarm time;

according to the wind direction value at the alarming moment, determining the upwind direction of the monitoring station;

determining a tracing radius according to the wind speed value in a preset time period;

and determining the tracing range corresponding to the monitoring station according to the upwind direction and the tracing radius of the monitoring station.

The air pollution tracing device based on multi-source data fusion provided in this embodiment may be used to execute the air pollution tracing method embodiment based on multi-source data fusion, and its implementation principle and technical effect are similar, and this embodiment is not described here again.

Fig. 3 is a schematic diagram of a terminal according to an embodiment of the present invention. As shown in fig. 3, the terminal 3 of this embodiment includes: a processor 30, a memory 31 and a computer program 32 stored in said memory 31 and executable on said processor 30. The processor 30 implements the steps of the embodiments of the air pollution tracing method based on multi-source data fusion, such as steps 101 to 105 shown in fig. 1, when executing the computer program 32. Alternatively, the processor 30 may perform the functions of the modules/units of the apparatus embodiments described above, such as the functions of the modules 21 to 25 shown in fig. 2, when executing the computer program 32.

Illustratively, the computer program 32 may be partitioned into one or more modules/units that are stored in the memory 31 and executed by the processor 30 to complete the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 32 in the terminal 3.

The terminal 3 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The terminal 3 may include, but is not limited to, a processor 30, a memory 31. It will be appreciated by those skilled in the art that fig. 3 is merely an example of the terminal 3 and does not constitute a limitation of the terminal 3, and may include more or less components than illustrated, or may combine certain components, or different components, e.g., the terminal may further include an input-output device, a network access device, a bus, etc.

The processor 30 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 31 may be an internal storage unit of the terminal 3, such as a hard disk or a memory of the terminal 3. The memory 31 may 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 (Flash Card) or the like, which are provided on the terminal 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the terminal 3. The memory 31 is used for storing the computer program as well as other programs and data required by the terminal. The memory 31 may also be used for temporarily storing data that has been output or is to be output.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other manners. For example, the apparatus/terminal embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present invention may implement all or part of the flow of the method of the foregoing embodiment, or may be implemented by instructing related hardware by a computer program, where the computer program may be stored in a computer readable storage medium, and the computer program may implement the steps of each embodiment of the air pollution tracing method based on multi-source data fusion when executed by a processor. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium may include content that is subject to appropriate increases and decreases as required by jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is not included as electrical carrier signals and telecommunication signals.

The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.

Claims

1. The atmosphere pollution tracing method based on multi-source data fusion is characterized by comprising the following steps of:

2. The method of claim 1, wherein for any monitoring site in the target city, determining whether the target pollution parameter exists according to the monitoring data of the monitoring site comprises:

3. The method according to claim 2, wherein, for any one of the plurality of preset types of pollution parameters, determining whether there is an increasing trend in the concentration value of the pollution parameter comprises:

4. A method according to claim 3, wherein, for any one of the plurality of predetermined types of pollution parameters, determining whether there is a continuous high-level trend in the concentration value of the pollution parameter comprises:

5. The method according to any one of claims 1 to 4, wherein before determining whether the area corresponding to the monitoring site is contaminated alone, the method further comprises:

Obtaining geographic position information of each monitoring station;

6. The method of claim 5, wherein prior to determining whether the area corresponding to the monitored site is contaminated alone, the method further comprises:

7. The method according to any one of claims 1 to 4, wherein, for each pollution type corresponding to the monitoring station, calculating the contribution value of each target pollution source in the traceable range to the pollution type sequentially includes:

8. The method according to any one of claims 1 to 4, wherein for any one of the monitoring stations, the method for determining the trace back range corresponding to the monitoring station includes:

9. A terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of the preceding claims 1 to 8 when the computer program is executed.

10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any of the preceding claims 1 to 8.