CN117147778A - Method and device for tracing and monitoring atmospheric pollutants, electronic equipment and storage medium - Google Patents
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Abstract
The invention provides a tracing monitoring method and device for atmospheric pollutants, electronic equipment and a storage medium, and relates to the technical field of pollutant monitoring, comprising the following steps: dividing a target area to be monitored into a plurality of sub-grid areas, and determining a pollutant data set corresponding to each sub-grid area; according to cloud amount data, carrying out data coupling on a pollutant concentration satellite remote sensing inversion result and pollutant concentration ground station observation data to obtain a pollutant concentration coupling result; and respectively carrying out threshold dividing processing and image convolution processing based on the pollutant concentration coupling result to determine hot spot grid data with regional pollution events, and determining sub-grid regions suspected to be abnormal by combining enterprise electricity abnormal data and enterprise position data, so as to carry out traceable analysis of atmospheric pollutants. The invention can realize the fine monitoring of air quality and pollution distribution in the area and the accurate positioning of the heavy pollution area in regional pollution event.
Description
Technical Field
The invention relates to the technical field of pollutant monitoring, in particular to a method and a device for tracing and monitoring atmospheric pollutants, electronic equipment and a storage medium.
Background
The air pollution tracing technology is an important means for realizing the accurate treatment of the air pollution, and has an important effect on pushing the joint prevention and the joint control of the pollution. In the related patent, only the pollutant concentration abnormality around the enterprise is considered when the enterprise pollution is identified, and the pollution source is generally identified and traced based on data such as site observation, satellite monitoring and the like, and although an algorithm is relatively visual and easy to understand, the data type is single, the precision is limited, the complex pollution process cannot be effectively distinguished, obvious limitations exist, and the air quality and the pollution distribution in the area cannot be finely monitored.
In addition, the air pollution hot spot grid technology can reflect the regional pollution distribution situation more comprehensively, and the emission reduction strategy is formulated in a targeted manner by locating the hot spot region, so that the treatment resources and the power are intensively used in the key region, early warning is carried out on the heavy pollution process in advance, and the emergency response is ensured. In the related patent, a main factor capable of intuitively reflecting the pollution condition of the area is mainly selected as a judging index by a hot spot grid algorithm, a threshold condition of a hot spot is determined according to pollution standards or normal background value settings of the judging factors, and observed values of all the judging factors in each sub-grid area are calculated on the basis of grid division. However, in large scale contamination events, a single concentration rating or thresholding may not accurately reveal the local gradient of contamination and the areas of critical interest, resulting in an inability to accurately locate heavily contaminated areas in regional contamination events.
Disclosure of Invention
In view of the above, the invention aims to provide a traceability monitoring method, a traceability monitoring device, electronic equipment and a storage medium for atmospheric pollutants, which can realize the fine monitoring of air quality and pollution distribution in an area and the accurate positioning of a heavy pollution area in a regional pollution event.
In a first aspect, an embodiment of the present invention provides a method for tracing and monitoring atmospheric pollutants, including:
dividing a target area to be monitored into a plurality of sub-grid areas, and determining a data set corresponding to each sub-grid area; the data set comprises thermal anomaly data, cloud amount data, a satellite remote sensing inversion result of the pollutant concentration and ground station observation data of the pollutant concentration;
according to the cloud amount data, carrying out data coupling on the satellite remote sensing inversion result of the pollutant concentration and the ground site observation data of the pollutant concentration to obtain a coupling result of the pollutant concentration;
performing threshold division processing and image convolution processing respectively based on the pollutant concentration coupling result to determine hot spot grid data with regional pollution events, and determining enterprise electricity utilization abnormal data and enterprise position data;
And determining a sub-grid region suspected to be abnormal based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise position data, so as to perform traceability analysis of atmospheric pollutants in a targeted manner.
In one embodiment, according to the cloud data, performing data coupling on the satellite remote sensing inversion result of the pollutant concentration and the ground site observation data of the pollutant concentration to obtain a coupling result of the pollutant concentration, including:
for each sub-grid region, determining cloud coverage corresponding to the sub-grid region according to the cloud amount data;
judging whether the cloud coverage rate is larger than a preset coverage rate threshold value or not;
if yes, the pollutant concentration ground station observation data are used as pollutant concentration coupling results corresponding to the sub-grid area;
and if not, carrying out data coupling on the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid region and the ground site observation data of the pollutant concentration to obtain a coupling result of the pollutant concentration corresponding to the sub-grid region.
In one embodiment, the step of performing data coupling on the satellite remote sensing inversion result of the contaminant concentration corresponding to the sub-grid area and the ground site observation data of the contaminant concentration to obtain a coupling result of the contaminant concentration corresponding to the sub-grid area includes:
If the sub-grid area is a cloud-free area, the satellite remote sensing inversion result of the pollutant concentration is used as a pollutant concentration coupling result corresponding to the sub-grid area; if the sub-grid area is a cloud area, the pollutant concentration ground station observation data is used as a pollutant concentration coupling result corresponding to the sub-grid area;
or if the satellite remote sensing inversion result of the pollutant concentration corresponding to the subgrid region is larger than the ground site observation data of the pollutant concentration, using the satellite remote sensing inversion result of the pollutant concentration as a coupling result of the pollutant concentration corresponding to the subgrid region; if the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid area is smaller than the ground station observation data of the pollutant concentration, the ground station observation data of the pollutant concentration is used as a coupling result of the pollutant concentration corresponding to the sub-grid area;
or weighting the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid region and the ground site observation data of the pollutant concentration according to a preset weight to obtain a coupling result of the pollutant concentration corresponding to the sub-grid region.
In one embodiment, the steps of performing thresholding and image convolution processing to determine hotspot grid data in the presence of a regional contamination event based on the contaminant concentration coupling result, respectively, include:
determining an air quality index corresponding to each sub-grid region by using the pollutant concentration coupling result, and performing threshold dividing processing on the air quality index to take the sub-grid region with the air quality index larger than a preset index threshold as a first candidate grid;
carrying out image convolution processing on the pollutant concentration coupling result to obtain a convolution result corresponding to each sub-grid region, and taking the sub-grid region with the convolution result being a positive number as a second candidate grid; wherein the convolution result is positive number, which indicates that the air quality index corresponding to the sub-grid area is larger than the air quality index corresponding to the adjacent sub-grid area;
and carrying out space matching on the first candidate grids and the second candidate grids to obtain hot spot grid data with regional pollution events.
In one embodiment, the step of performing image convolution processing on the pollutant concentration coupling result to obtain a convolution result corresponding to each sub-grid region includes:
Determining a convolution result corresponding to each sub-grid region according to the following formula;
；
wherein,for position->Convolution results corresponding to sub-grid areas at +.>As a result of the coupling of the concentration of the contaminant,for convolution kernel +.>And->Is an index into the convolution kernel.
In one embodiment, determining a sub-grid area suspected of being abnormal based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data, and the enterprise location data, and performing targeted traceability analysis of atmospheric pollutants includes:
constructing a multidimensional feature vector associated with each sub-grid region according to the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise location data;
and classifying each sub-grid region by utilizing the multidimensional feature vector to determine a sub-grid region suspected to be abnormal, and performing traceability analysis of atmospheric pollutants in a targeted manner.
In one embodiment, the step of classifying each of the sub-grid regions by using the multi-dimensional feature vector includes:
if the sub-grid area is associated with the thermal anomaly data and the hot spot grid data, determining that the sub-grid area belongs to a suspected enterprise thermal anomaly area;
Or if the sub-grid area is associated with the hot spot grid data and the enterprise electricity consumption abnormal data, determining that the sub-grid area belongs to a suspected enterprise high energy consumption area.
In a second aspect, an embodiment of the present invention further provides a tracing and monitoring device for atmospheric pollutants, including:
the data determining module is used for dividing a target area to be monitored into a plurality of sub-grid areas and determining a pollutant data set corresponding to each sub-grid area; the pollutant data set comprises thermal anomaly data, cloud cover data, a pollutant concentration satellite remote sensing inversion result and pollutant concentration ground station observation data;
the data coupling module is used for carrying out data coupling on the satellite remote sensing inversion result of the pollutant concentration and the ground site observation data of the pollutant concentration according to the cloud cover data to obtain a coupling result of the pollutant concentration;
the grid determining module is used for respectively carrying out threshold dividing processing and image convolution processing based on the pollutant concentration coupling result, and is used for determining hot spot grid data with regional pollution events, and determining enterprise electricity utilization abnormal data and enterprise position data;
And the pollutant tracing monitoring module is used for determining a sub-grid area suspected to be abnormal based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise position data, so as to perform tracing analysis of atmospheric pollutants in a targeted manner.
In a third aspect, an embodiment of the present invention further provides an electronic device comprising a processor and a memory storing computer-executable instructions executable by the processor to implement the method of any one of the first aspects.
In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions which, when invoked and executed by a processor, cause the processor to implement the method of any one of the first aspects.
The embodiment of the invention provides a tracing monitoring method, a tracing monitoring device, electronic equipment and a storage medium for atmospheric pollutants, wherein a target area to be monitored is divided into a plurality of sub-grid areas, a pollutant data set corresponding to each sub-grid area is determined, and the pollutant data set comprises heat anomaly data, cloud cover data, a pollutant concentration satellite remote sensing inversion result and pollutant concentration ground station observation data; then, according to cloud amount data, carrying out data coupling on a pollutant concentration satellite remote sensing inversion result and pollutant concentration ground station observation data to obtain a pollutant concentration coupling result; threshold dividing processing and image convolution processing are respectively carried out based on the pollutant concentration coupling result, so as to determine hot spot grid data with regional pollution events, and determine enterprise electricity utilization abnormal data and enterprise position data; and finally, determining a sub-grid area suspected to be abnormal based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise position data, and performing targeted traceability analysis on the atmospheric pollutants. The regional air quality assessment method combining the multi-source pollutant data set is provided, the multi-source data such as the thermal anomaly data, the pollutant concentration satellite remote sensing inversion result, the pollutant concentration ground station observation data, the enterprise electricity anomaly data and the enterprise position data are effectively fused, the enterprise thermal anomaly and the enterprise electricity anomaly are comprehensively considered on the basis of a hot spot grid technology, the automatic identification and tracing of different types of pollution sources are realized, key pollution region positioning information is provided for the tracing technology, the atmospheric pollution caused by the excessive discharge of the enterprise is more accurately identified, and the fine monitoring of the air quality and pollution distribution in the region is realized; in addition, in order to further subdivide and identify sub-grid regions with higher pollution concentrations relative to their surrounding environment, the method introduces image convolution processing based on thresholding, which can enable accurate positioning of heavily polluted regions in regional pollution events.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for tracing and monitoring atmospheric pollutants according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of another method for tracing and monitoring atmospheric pollutants according to an embodiment of the present invention;
Fig. 3 is a schematic structural diagram of a tracing and monitoring device for atmospheric pollutants according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described in conjunction with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, the related technology cannot finely monitor the air quality and pollution distribution in the area and cannot accurately position the heavy pollution area in the regional pollution event, and based on the method, the device, the electronic equipment and the storage medium for tracing the atmospheric pollutants, the method, the device, the electronic equipment and the storage medium can finely monitor the air quality and pollution distribution in the area and accurately position the heavy pollution area in the regional pollution event.
For the convenience of understanding the present embodiment, first, a detailed description will be given of a method for tracing and monitoring an atmospheric contaminant disclosed in the present embodiment, referring to a schematic flow chart of a method for tracing and monitoring an atmospheric contaminant shown in fig. 1, the method mainly includes the following steps S102 to S108:
step S102, dividing the target area to be monitored into a plurality of sub-grid areas, and determining a data set corresponding to each sub-grid area.
The data set comprises thermal anomaly data, cloud amount data, a satellite remote sensing inversion result of the pollutant concentration and ground station observation data of the pollutant concentration. In one embodiment, the target area is divided into a plurality of sub-grid areas according to an equidistant method after being selected, and then thermal anomaly data, cloud cover data, a pollutant concentration satellite remote sensing inversion result and pollutant concentration ground station observation data corresponding to each sub-grid area are determined. The method comprises the steps of obtaining sunflower No. 9-AHI integral point remote sensing image data, performing fire point identification processing on the sunflower No. 9-AHI integral point remote sensing image data to obtain thermal anomaly data, performing cloud detection processing on the thermal anomaly data to obtain cloud quantity data, and converting the cloud quantity data into a pollutant concentration satellite remote sensing inversion result by using a satellite inversion model; in addition, air quality environmental site data are acquired, and are processed by a radial basis interpolation method to obtain pollutant concentration ground site observation data.
And step S104, carrying out data coupling on the satellite remote sensing inversion result of the pollutant concentration and the ground site observation data of the pollutant concentration according to cloud cover data to obtain a coupling result of the pollutant concentration.
For each sub-grid region, the cloud coverage corresponding to the sub-grid region can be determined according to cloud cover data. Further, under the condition that the cloud coverage exceeds a preset coverage threshold, only adopting the pollutant concentration ground station observation data, namely taking the pollutant concentration ground station observation data as a pollutant concentration coupling result corresponding to the sub-grid region; under the condition that the cloud coverage rate does not exceed a preset coverage rate threshold value, a pollutant concentration satellite remote sensing inversion result or pollutant concentration ground site observation data can be selected to serve as a pollutant concentration coupling result corresponding to the subgrid region, and the pollutant concentration satellite remote sensing inversion result and the pollutant concentration ground site observation data can be fused to obtain the pollutant concentration coupling result corresponding to the subgrid region, so that data coupling is achieved.
And step S106, respectively carrying out threshold division processing and image convolution processing based on the pollutant concentration coupling result to determine hot spot grid data with regional pollution events, and determining enterprise electricity utilization abnormal data and enterprise position data.
In one embodiment, firstly, determining an air quality index corresponding to each sub-grid region based on a pollutant concentration coupling result, then determining a first candidate grid with the air quality index exceeding a preset index threshold value from the sub-grid regions by utilizing threshold dividing processing, determining a second candidate grid with the convolution result being an integer from the sub-grid regions by utilizing image convolution processing, wherein the convolution result being a positive number indicates that the air quality index corresponding to the sub-grid region is greater than the air quality index corresponding to an adjacent sub-grid region, and finally performing space matching on the first candidate grid and the second candidate grid to determine hot spot grid data with regional pollution events.
Further, based on the hot spot grid data, enterprise information in the corresponding grid area is counted, wherein the enterprise information comprises power consumption time series data of enterprises in the area, and a Z-Score algorithm is adopted to judge whether the enterprises have abnormal power consumption in a research period, so that abnormal power consumption data of the enterprises are obtained; in addition, the collected business information also includes business location data.
Step S108, determining a sub-grid area suspected to be abnormal based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise position data, and performing targeted traceability analysis on the atmospheric pollutants.
In one embodiment, a multidimensional feature vector corresponding to each sub-grid region can be constructed based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise position data, so that the sub-grid regions are divided into region categories according to the multidimensional feature vector and preset conditions, suspected enterprise thermal anomaly regions and suspected enterprise high energy consumption regions are identified from the sub-grid regions, and the target region is subjected to traceable monitoring of atmospheric pollutants on the basis.
According to the method for tracing and monitoring the atmospheric pollutants, provided by the embodiment of the invention, the regional air quality assessment method combined with a multi-source pollutant data set is provided, multi-source data such as thermal anomaly data, pollutant concentration satellite remote sensing inversion results, pollutant concentration ground site observation data, enterprise electricity utilization anomaly data and enterprise position data are effectively fused, the enterprise thermal anomaly and the enterprise electricity utilization anomaly are comprehensively considered on the basis of a hot spot grid technology, the automatic identification and tracing of different types of pollution sources are realized, key pollution region positioning information is provided for the tracing technology, the atmospheric pollution caused by excessive discharge of enterprises is more accurately identified, and the fine monitoring of the air quality and pollution distribution in a region is realized; in addition, in order to further subdivide and identify sub-grid areas with higher pollution concentration relative to the surrounding environment, the tracing and monitoring method for the atmospheric pollutants, provided by the embodiment of the invention, introduces image convolution processing on the basis of threshold division, and can realize accurate positioning of heavy pollution areas in regional pollution events.
For ease of understanding, embodiments of the present invention provide a method for traceable monitoring of atmospheric contaminants.
For the foregoing step S102, the steps of dividing the target area to be monitored into a plurality of sub-grid areas and determining a contaminant data set corresponding to each sub-grid area may be performed as follows in steps 1A to 1D:
step 1A, selecting a target area, determining proper spatial resolution, and dividing the target area into a plurality of sub-grid areas according to an equidistant method.
Step 1B, obtaining atmospheric layer optical thickness (AOD) data through sunflower No. 9-AHI whole-point remote sensing image data, converting the data into near-ground atmospheric pollutant concentration distribution based on a satellite inversion model, and obtaining atmospheric pollutant concentration level distribution data (namely, pollutant concentration satellite remote sensing inversion results) of a target area in a research period;
step 1C, obtaining H9-AHI visible light and infrared band data of a target area through preprocessing operations such as geometric correction and angle correction, obtaining thermal anomaly data of the target area based on a fire point identification technology, and obtaining cloud quantity data of the target area based on a cloud detection technology;
and 1D, carrying out area screening and invalid value elimination on the air quality environment site data in the research period, and interpolating the site observation data into a target grid area by utilizing a Radial Basis Function (RBF) to obtain the pollutant concentration ground site observation data. The interpolation theory is as follows:
；
Wherein,is the interpolation function at the point->Value of->Is a generic form of radial basis function,is the Euclidean distance of the two position vectors, < >>Is->Control point positions of radial basis functions, +.>Is->Weight coefficient corresponding to radial basis function, < ->Is the total number of radial basis functions used for interpolation. Radial basis function->There are various options such as gaussian surface functions, polynomial functions, linear functions, cube surface functions, sheet surface functions, etc.
For the step S104, the step of performing data coupling on the satellite remote sensing inversion result of the contaminant concentration and the ground site observation data of the contaminant concentration according to the cloud cover data to obtain a coupling result of the contaminant concentration according to the following steps 2A to 2D may be performed:
and 2A, for each sub-grid area, determining the cloud coverage rate corresponding to the sub-grid area according to cloud quantity data. In one embodiment, knowing the resolution of each sub-grid region, calculating the ratio of cloud cover data to resolution to obtain cloud coverage, where the cloud coverage is used to determine the cloud coverage of each sub-grid region.
And 2B, judging whether the cloud coverage rate is larger than a preset coverage rate threshold value. If yes, executing the step 2C; if not, step 2D is performed.
And 2C, taking the pollutant concentration ground station observation data as a pollutant concentration coupling result corresponding to the sub-grid area. In one embodiment, if the cloud coverage exceeds a preset coverage threshold, only using the pollutant concentration ground site observation data and discarding the pollutant concentration satellite remote sensing inversion result.
And 2D, performing data coupling on the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid region and the ground site observation data of the pollutant concentration to obtain a coupling result of the pollutant concentration corresponding to the sub-grid region. In one embodiment, if the cloud coverage is lower than a preset coverage threshold, data coupling is considered, namely, whether the sub-grid area is cloud-free or partial cloud coverage is judged, and a coupling result of a pollutant concentration satellite remote sensing inversion result and pollutant concentration ground station observation data is adopted. In specific implementation, the data coupling may be performed in any one of the following manners one to three:
mode one: if the sub-grid area is a cloud-free area, the satellite remote sensing inversion result of the pollutant concentration is used as a pollutant concentration coupling result corresponding to the sub-grid area; or if the sub-grid area is a cloud area, the pollutant concentration ground station observation data is used as the pollutant concentration coupling result corresponding to the sub-grid area. In practical application, the satellite remote sensing inversion result of the pollutant concentration is used in a cloud-free area, and the ground station observation data of the pollutant concentration is used in a cloud-free area.
Mode two: if the satellite remote sensing inversion result of the pollutant concentration corresponding to the subgrid region is larger than the ground site observation data of the pollutant concentration, the satellite remote sensing inversion result of the pollutant concentration is used as the coupling result of the pollutant concentration corresponding to the subgrid region; or if the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid area is smaller than the ground site observation data of the pollutant concentration, the ground site observation data of the pollutant concentration is used as the coupling result of the pollutant concentration corresponding to the sub-grid area. In practical application, the satellite remote sensing inversion result of the pollutant concentration in each sub-grid area and a larger value of the ground site observation data of the pollutant concentration are taken as the coupling result of the pollutant concentration.
Mode three: and weighting the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid region and the ground site observation data of the pollutant concentration according to a preset weight to obtain a coupling result of the pollutant concentration corresponding to the sub-grid region. In practical application, the pollutant concentration ground station observation data and the pollutant concentration satellite remote sensing inversion result can be fused according to a specific proportion (namely, preset weight) to obtain the pollutant concentration coupling result corresponding to the sub-grid region.
For the foregoing step S106, the steps of performing the thresholding process and the image convolution process based on the coupling result of the contaminant concentration to determine the hotspot grid data where the regional contamination event exists, and determining the enterprise electricity anomaly data and the enterprise location data may be performed as follows in steps 3A to 3D:
and 3A, determining an Air Quality Index (AQI) corresponding to each sub-grid region by using a pollutant concentration coupling result, and performing threshold division processing on the air quality index to take the sub-grid region with the air quality index larger than a preset index threshold as a first candidate grid. In one embodiment, the AQI value of each sub-grid region is calculated using the result of the coupling of the contaminant concentration, and sub-grid regions having contaminant concentrations at or above a light contaminant level are screened out as first candidate grids.
And 3B, performing image convolution processing on the pollutant concentration coupling result to obtain a convolution result corresponding to each sub-grid region, and taking the sub-grid region with the convolution result being a positive number as a second candidate grid. Wherein the convolution result is a positive number, which indicates that the air quality index corresponding to the sub-grid region is greater than the air quality index corresponding to the adjacent sub-grid region. In one embodiment, a second candidate grid of sub-grid regions having a higher contaminant concentration than the perimeter is screened out based on an image convolution technique. Specifically, the convolution result corresponding to each sub-grid region may be determined according to the following formula:
；
Wherein,for position->Convolution results corresponding to sub-grid areas at +.>As a result of the coupling of the concentration of the contaminant,for convolution kernel +.>And->Is the index in the convolution kernel.
Further, the method comprises the steps of,is->Convolution kernel: />；
The center point of the convolution kernel has a weight of 8 and the other 8 adjacent points have weights of-1, so that when the convolution kernel is used to perform convolution operation on an image, if the value of the center point is larger than that of the other 8 adjacent points, the convolution result will be a positive number, and otherwise a negative number or zero. On the basis of this, ifDescription location->AQI values of (2) are larger than the surrounding points, in which case the position +.>The sub-grid region at is used as the second candidate grid.
And 3C, performing space matching on the first candidate grids and the second candidate grids to obtain hot spot grid data with regional pollution events. In one embodiment, the first candidate grid determined in the step 3A and the second candidate grid determined in the step 3B are spatially matched, that is, a sub-grid region with light pollution and above with more serious pollution degree than surrounding in a regional pollution event can be effectively extracted, and a part of sub-grid regions (such as the first 50 sub-grid regions) with the front AQI rank are taken and defined as pollutant hot spot grids, so that hot spot grid data are obtained.
In a specific implementation, for each sub-grid region, if the AQI value corresponding to the sub-grid region is greater than a preset exponential threshold (i.e., belongs to the first candidate grid), and the convolution result corresponding to the sub-grid region is a positive number (i.e., belongs to the second candidate grid), the sub-grid region may be determined as a pollutant hot spot grid.
And 3D, determining enterprise electricity utilization abnormal data and enterprise location data corresponding to the hot spot grid data.
In one embodiment, based on the pollutant hotspot grid extracted in the step 3C, enterprise information in the corresponding sub-grid area is counted, power consumption time series data of the enterprise in the area are collected, and a Z-Score algorithm is adopted to judge whether the enterprise has abnormal power consumption in a research period. The Z-Score algorithm is formulated as follows:
；
wherein the method comprises the steps ofTime series of electricity consumption for each enterprise, +.>For its corresponding Z-Score, < >>Is->Average value of>Is->Standard deviation of (2).
For the foregoing step S108, the step of determining the sub-grid area suspected of being abnormal based on the thermal anomaly data, the hotspot grid data, the enterprise electricity anomaly data, and the enterprise location data may be performed according to the following steps 4A to 4C, so as to perform the traceability analysis of the atmospheric pollutants in a targeted manner:
And 4A, constructing a multidimensional feature vector associated with each sub-grid region according to the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise location data. In one embodiment, a multidimensional feature database is generated from the multi-dimensional feature vectors of each sub-grid region constructed from the thermal anomaly data, the hotspot grid data, the enterprise electricity anomaly data, and the enterprise location data.
And 4B, classifying each grid by utilizing the multidimensional feature vector, determining a sub-grid region suspected to be abnormal, and performing traceability analysis on the atmospheric pollutants in a targeted manner. In one embodiment, if the sub-grid region is associated with thermal anomaly data and hotspot grid data, determining that the sub-grid region belongs to a suspected enterprise thermal anomaly region; or if the sub-grid area is associated with hot spot grid data and enterprise electricity consumption abnormal data, determining that the sub-grid area belongs to a suspected enterprise high energy consumption area.
Specifically, whether the multidimensional feature vectors associated with each sub-grid region meet a certain condition can be judged, and region classification is carried out on the multidimensional feature vectors meeting the certain condition:
(a) Identifying the enterprise area which is simultaneously defined as a hot spot grid and a thermal anomaly point as a suspected enterprise thermal anomaly area;
(b) And identifying the enterprise area which is simultaneously defined as the hot spot grid and the abnormal electricity consumption as a suspected enterprise high-energy consumption area.
If the suspected enterprise high energy consumption area and the suspected enterprise thermal anomaly area do not exist in the pollution process of the target area in the research period, judging that the pollution process is possibly caused by external pollution transmission, and analyzing a pollution conveying path and a source outside the area by adopting a potential source area contribution method (PSCF), a concentration weight contribution method (CWT), a pollution tracing track model (HYSPLIT) and other methods; if a suspected enterprise high energy consumption area or a suspected enterprise thermal anomaly area exists in the pollution process of the target area in the research period, judging that the pollution process is possibly influenced by a local pollution source, and listing related enterprises as important investigation objects.
In summary, the embodiment of the present invention has at least the following features:
(1) In the prior art, the pollutant concentration abnormality around the enterprise is mainly considered when the enterprise pollution is identified, the enterprise operation abnormality, namely the enterprise thermal abnormality and the enterprise power consumption abnormality, is comprehensively considered on the basis of the hot spot grid technology, accurate tracing is performed, and the method and the device are favorable for more accurately identifying the atmospheric pollution caused by the excessive discharge of the enterprise.
(2) The single concentration rating or threshold division in the existing hot spot grid algorithm may not accurately reveal the local gradient and the important focus area of pollution, so that the embodiment of the invention introduces a convolution operation method in image processing, further subdivides and identifies sub-grids with higher pollution concentration relative to the surrounding environment on the basis of threshold judgment, and further realizes the accurate positioning of the heavy pollution area in regional pollution event.
(3) The embodiment of the invention effectively integrates the hot spot grid technology and the pollutant tracing technology, combines the advantages of the two technologies, can locate a key pollution area, dynamically trace a pollution source, improve tracing precision, share a monitoring data platform, reduce deployment cost and improve supervision efficiency.
For easy understanding, the embodiment of the present invention further provides another implementation of the method for tracing and monitoring atmospheric pollutants, referring to a schematic flow chart of another method for tracing and monitoring atmospheric pollutants shown in fig. 2, the method mainly includes the following steps S202 to S208:
in step S202, the target area is gridded and data is initialized. In particular, reference may be made to the foregoing steps 1A to 1D, and detailed descriptions of the embodiments of the present invention are omitted herein.
In step S204, the contaminant concentration multisource data is coupled. In particular, reference may be made to the foregoing steps 2A to 2D, and detailed descriptions of the embodiments of the present invention are omitted herein.
Step S206, extracting pollutant hot spot grids. In particular, reference may be made to the foregoing steps 3A to 3C, and detailed descriptions of the embodiments of the present invention are omitted herein.
Step S208, comprehensively judging the source of the pollutants. In particular, reference may be made to the foregoing steps 3D, 4A to 4C, and the embodiments of the present invention are not described herein again.
The embodiment of the invention provides a regional air quality assessment method combining multi-source observation data, which effectively fuses multi-source data such as satellite remote sensing inversion data, ground site observation data, enterprise power consumption data, heat abnormal point data, geographic information data and the like, comprehensively considers enterprise heat abnormality and enterprise power consumption abnormality on the basis of a hot spot grid technology, automatically identifies and traces different types of pollution sources, provides key pollution regional positioning information for the tracing technology, is favorable for more accurately identifying atmospheric pollution caused by excessive discharge of enterprises, and realizes fine monitoring of air quality and pollution distribution in a region; in addition, in order to further subdivide and identify sub-grid areas with higher pollution concentration relative to the surrounding environment, the embodiment of the invention introduces a convolution operation method in image processing on the basis of threshold judgment, and can realize accurate positioning of heavy pollution areas in regional pollution events.
On the basis of the foregoing embodiments, the embodiment of the present invention provides a tracing and monitoring device for atmospheric pollutants, referring to a schematic structural diagram of the tracing and monitoring device for atmospheric pollutants shown in fig. 3, the device mainly includes the following parts:
the data determining module 302 is configured to divide a target area to be monitored into a plurality of sub-grid areas, and determine a pollutant data set corresponding to each sub-grid area; the pollutant data set comprises thermal anomaly data, cloud amount data, a pollutant concentration satellite remote sensing inversion result and pollutant concentration ground station observation data;
the data coupling module 304 is configured to perform data coupling on the satellite remote sensing inversion result of the pollutant concentration and the ground site observation data of the pollutant concentration according to the cloud cover data, so as to obtain a coupling result of the pollutant concentration;
the grid determining module 306 is configured to perform thresholding processing and image convolution processing based on the pollutant concentration coupling result, to determine hot spot grid data with regional pollution events, and to determine enterprise electricity anomaly data and enterprise location data;
the pollutant tracing monitoring module 308 is configured to determine a sub-grid area suspected to be abnormal based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise location data, so as to perform tracing analysis of atmospheric pollutants in a targeted manner.
The embodiment of the invention provides a tracing monitoring device for atmospheric pollutants, which combines a multi-source pollutant data set to effectively fuse multi-source data such as thermal anomaly data, pollutant concentration satellite remote sensing inversion results, pollutant concentration ground site observation data, enterprise electricity anomaly data, enterprise position data and the like, comprehensively considers the enterprise thermal anomaly and the enterprise electricity anomaly on the basis of a hot spot grid technology, automatically identifies and traces different types of pollution sources, provides key pollution area positioning information for tracing technology, is favorable for more accurately identifying atmospheric pollution caused by excessive discharge of enterprises, and realizes the fine monitoring of air quality and pollution distribution in an area; in addition, in order to further subdivide and identify sub-grid areas with higher pollution concentration relative to the surrounding environment, the tracing and monitoring device for the atmospheric pollutants provided by the embodiment of the invention introduces image convolution processing on the basis of threshold division, and can realize the accurate positioning of heavy pollution areas in regional pollution events.
In one embodiment, based on the cloud data, the data coupling module 304 is further configured to:
For each sub-grid region, determining cloud coverage corresponding to the sub-grid region according to cloud quantity data;
judging whether the cloud coverage rate is larger than a preset coverage rate threshold value or not;
if yes, the pollutant concentration ground station observation data are used as pollutant concentration coupling results corresponding to the sub-grid area;
and if not, carrying out data coupling on the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid region and the ground site observation data of the pollutant concentration to obtain a coupling result of the pollutant concentration corresponding to the sub-grid region.
In one embodiment, the data coupling module 304 is further configured to:
if the sub-grid area is a cloud-free area, the satellite remote sensing inversion result of the pollutant concentration is used as a pollutant concentration coupling result corresponding to the sub-grid area; if the sub-grid area is a cloud area, the pollutant concentration ground station observation data is used as a pollutant concentration coupling result corresponding to the sub-grid area;
or if the satellite remote sensing inversion result of the pollutant concentration corresponding to the subgrid region is larger than the ground site observation data of the pollutant concentration, the satellite remote sensing inversion result of the pollutant concentration is used as the coupling result of the pollutant concentration corresponding to the subgrid region; if the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid area is smaller than the ground site observation data of the pollutant concentration, the ground site observation data of the pollutant concentration is used as the coupling result of the pollutant concentration corresponding to the sub-grid area;
Or weighting the satellite remote sensing inversion result of the pollutant concentration corresponding to the grid and the ground site observation data of the pollutant concentration according to preset weights to obtain a coupling result of the pollutant concentration corresponding to the sub-grid region.
In one embodiment, grid determination module 306 is further to:
determining an air quality index corresponding to each sub-grid region by using a pollutant concentration coupling result, and performing threshold dividing treatment on the air quality index to take the sub-grid region with the air quality index larger than a preset index threshold as a first candidate grid;
carrying out image convolution processing on the pollutant concentration coupling result to obtain a convolution result corresponding to each sub-grid region, and taking the sub-grid region with the convolution result being a positive number as a second candidate grid; wherein, the convolution result is positive number, which indicates that the air quality index corresponding to the sub-grid area is larger than the air quality index corresponding to the adjacent sub-grid area;
and performing space matching on the first candidate grids and the second candidate grids to obtain hot spot grid data with regional pollution events.
In one embodiment, grid determination module 306 is further to:
determining a convolution result corresponding to each sub-grid region according to the following formula;
；
Wherein,for position->Convolution results corresponding to sub-grid areas at +.>As a result of the coupling of the concentration of the contaminant,for convolution kernel +.>And->Is the index in the convolution kernel.
In one embodiment, the contaminant traceability monitoring module 308 is further configured to:
constructing a multidimensional feature vector associated with each sub-grid region according to the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise location data;
and classifying each sub-grid region by utilizing the multidimensional feature vector to determine a sub-grid region suspected to be abnormal, and performing traceability analysis of atmospheric pollutants in a targeted manner.
In one embodiment, the contaminant traceability monitoring module 308 is further configured to:
if the sub-grid area is associated with the thermal anomaly data and the hot spot grid data, determining that the sub-grid area belongs to a suspected enterprise thermal anomaly area;
or if the sub-grid area is associated with hot spot grid data and enterprise electricity consumption abnormal data, determining that the sub-grid area belongs to a suspected enterprise high energy consumption area.
The device provided by the embodiment of the present invention has the same implementation principle and technical effects as those of the foregoing method embodiment, and for the sake of brevity, reference may be made to the corresponding content in the foregoing method embodiment where the device embodiment is not mentioned.
The embodiment of the invention provides electronic equipment, which comprises a processor and a storage device; the storage means has stored thereon a computer program which, when executed by the processor, performs the method of any of the embodiments described above.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device 100 includes: a processor 40, a memory 41, a bus 42 and a communication interface 43, the processor 40, the communication interface 43 and the memory 41 being connected by the bus 42; the processor 40 is arranged to execute executable modules, such as computer programs, stored in the memory 41.
The memory 41 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and the at least one other network element is achieved via at least one communication interface 43 (which may be wired or wireless), which may use the internet, a wide area network, a local network, a metropolitan area network, etc.
Bus 42 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 4, but not only one bus or type of bus.
The memory 41 is configured to store a program, and the processor 40 executes the program after receiving an execution instruction, and the method executed by the apparatus for flow defining disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 40 or implemented by the processor 40.
The processor 40 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in processor 40. The processor 40 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a digital signal processor (Digital Signal Processing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 41 and the processor 40 reads the information in the memory 41 and in combination with its hardware performs the steps of the method described above.
The computer program product of the readable storage medium provided by the embodiment of the present invention includes a computer readable storage medium storing a program code, where the program code includes instructions for executing the method described in the foregoing method embodiment, and the specific implementation may refer to the foregoing method embodiment and will not be described herein.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or 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. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. The method for tracing and monitoring the atmospheric pollutants is characterized by comprising the following steps of:
dividing a target area to be monitored into a plurality of sub-grid areas, and determining a data set corresponding to each sub-grid area; the data set comprises thermal anomaly data, cloud amount data, a satellite remote sensing inversion result of the pollutant concentration and ground station observation data of the pollutant concentration;
According to the cloud amount data, carrying out data coupling on the satellite remote sensing inversion result of the pollutant concentration and the ground site observation data of the pollutant concentration to obtain a coupling result of the pollutant concentration;
performing threshold division processing and image convolution processing respectively based on the pollutant concentration coupling result to determine hot spot grid data with regional pollution events, and determining enterprise electricity utilization abnormal data and enterprise position data;
and determining a sub-grid region suspected to be abnormal based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise position data, so as to perform traceability analysis of atmospheric pollutants in a targeted manner.
2. The method for tracing and monitoring atmospheric pollutants according to claim 1, wherein the step of performing data coupling on the satellite remote sensing inversion result of the pollutant concentration and the ground site observation data of the pollutant concentration according to the cloud cover data to obtain a coupling result of the pollutant concentration comprises the following steps:
for each sub-grid region, determining cloud coverage corresponding to the sub-grid region according to the cloud amount data;
judging whether the cloud coverage rate is larger than a preset coverage rate threshold value or not;
If yes, the pollutant concentration ground station observation data are used as pollutant concentration coupling results corresponding to the sub-grid area;
and if not, carrying out data coupling on the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid region and the ground site observation data of the pollutant concentration to obtain a coupling result of the pollutant concentration corresponding to the sub-grid region.
3. The method for tracing and monitoring atmospheric pollutants according to claim 2, wherein the step of performing data coupling on the satellite remote sensing inversion result of the pollutant concentration corresponding to the subgrid region and the ground site observation data of the pollutant concentration to obtain the coupling result of the pollutant concentration corresponding to the subgrid region comprises the following steps:
if the sub-grid area is a cloud-free area, the satellite remote sensing inversion result of the pollutant concentration is used as a pollutant concentration coupling result corresponding to the sub-grid area; if the sub-grid area is a cloud area, the pollutant concentration ground station observation data is used as a pollutant concentration coupling result corresponding to the sub-grid area;
or if the satellite remote sensing inversion result of the pollutant concentration corresponding to the subgrid region is larger than the ground site observation data of the pollutant concentration, using the satellite remote sensing inversion result of the pollutant concentration as a coupling result of the pollutant concentration corresponding to the subgrid region; if the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid area is smaller than the ground station observation data of the pollutant concentration, the ground station observation data of the pollutant concentration is used as a coupling result of the pollutant concentration corresponding to the sub-grid area;
Or weighting the satellite remote sensing inversion result of the pollutant concentration corresponding to the sub-grid region and the ground site observation data of the pollutant concentration according to a preset weight to obtain a coupling result of the pollutant concentration corresponding to the sub-grid region.
4. The method of claim 1, wherein the step of performing thresholding and image convolution processes, respectively, to determine hotspot grid data for the presence of regional contamination events based on the contaminant concentration coupling results comprises:
determining an air quality index corresponding to each sub-grid region by using the pollutant concentration coupling result, and performing threshold dividing processing on the air quality index to take the sub-grid region with the air quality index larger than a preset index threshold as a first candidate grid;
carrying out image convolution processing on the pollutant concentration coupling result to obtain a convolution result corresponding to each sub-grid region, and taking the sub-grid region with the convolution result being a positive number as a second candidate grid; wherein the convolution result is positive number, which indicates that the air quality index corresponding to the sub-grid area is larger than the air quality index corresponding to the adjacent sub-grid area;
And carrying out space matching on the first candidate grids and the second candidate grids to obtain hot spot grid data with regional pollution events.
5. The method for tracing atmospheric pollutants according to claim 4, wherein the step of performing image convolution processing on the pollutant concentration coupling result to obtain a convolution result corresponding to each sub-grid region comprises:
determining a convolution result corresponding to each sub-grid region according to the following formula;
；
wherein,for position->Convolution results corresponding to sub-grid areas at +.>For the coupling result of the contaminant concentration, +.>For convolution kernel +.>And->Is an index into the convolution kernel.
6. The method for traceable monitoring of atmospheric pollutants according to claim 1, wherein determining a sub-grid region suspected of being abnormal based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise location data, and performing traceable analysis of the atmospheric pollutants specifically comprises:
constructing a multidimensional feature vector associated with each sub-grid region according to the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise location data;
And classifying each sub-grid region by utilizing the multidimensional feature vector to determine a sub-grid region suspected to be abnormal, and performing traceability analysis of atmospheric pollutants in a targeted manner.
7. The method of claim 6, wherein classifying each of the sub-grid regions by using the multi-dimensional feature vector comprises:
if the sub-grid area is associated with the thermal anomaly data and the hot spot grid data, determining that the sub-grid area belongs to a suspected enterprise thermal anomaly area;
or if the sub-grid area is associated with the hot spot grid data and the enterprise electricity consumption abnormal data, determining that the sub-grid area belongs to a suspected enterprise high energy consumption area.
8. The utility model provides a monitoring devices that traces to source of atmospheric pollutants which characterized in that includes:
the data determining module is used for dividing a target area to be monitored into a plurality of sub-grid areas and determining a data set corresponding to each sub-grid area; the data set comprises thermal anomaly data, cloud amount data, a satellite remote sensing inversion result of the pollutant concentration and ground station observation data of the pollutant concentration;
The data coupling module is used for carrying out data coupling on the satellite remote sensing inversion result of the pollutant concentration and the ground site observation data of the pollutant concentration according to the cloud cover data to obtain a coupling result of the pollutant concentration;
the grid determining module is used for respectively carrying out threshold dividing processing and image convolution processing based on the pollutant concentration coupling result, and is used for determining hot spot grid data with regional pollution events, and determining enterprise electricity utilization abnormal data and enterprise position data;
and the pollutant tracing monitoring module is used for determining a sub-grid area suspected to be abnormal based on the thermal anomaly data, the hot spot grid data, the enterprise electricity anomaly data and the enterprise position data, so as to perform tracing analysis of atmospheric pollutants in a targeted manner.
9. An electronic device comprising a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the method of any one of claims 1 to 7.
10. A computer readable storage medium storing computer executable instructions which, when invoked and executed by a processor, cause the processor to implement the method of any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117408856A (en) * | 2023-12-13 | 2024-01-16 | 浙江省生态环境监测中心(浙江省生态环境信息中心) | Pollutant tracing method and device, storage medium and electronic equipment |
| CN117408856B (en) * | 2023-12-13 | 2024-03-26 | 浙江省生态环境监测中心(浙江省生态环境信息中心) | Pollutant tracing method and device, storage medium and electronic equipment |
| CN117973710A (en) * | 2024-04-02 | 2024-05-03 | 生态环境部卫星环境应用中心 | Atmospheric pollution tracing method for satellite high-value region |
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