A method and system for contaminant tracing based on fingerprinting

Abstract

The application relates to the technical field of environmental monitoring and discloses a pollution source tracing method and system based on a fingerprint spectrum, which comprises the following steps: step one, constructing a pollution fingerprint spectrum according to the types and emission modes of pollutants in a target area; step two, analyzing daily monitoring data transmitted by small monitoring stations to obtain an abnormal area with an abnormally high concentration of pollutants; step three, performing a first scan on the abnormal area by a Fourier infrared remote sensing device to obtain a transmission path and an emission area of the pollutants; and step four, planning a scanning path of a walk car according to the transmission path and the emission area of the pollutants, comprehensively performing a second scan on the abnormal area by the walk car, and combining a fingerprint spectrum directory to obtain enterprises with abnormally high values of the concentration of the pollutants. Through the construction of the fingerprint spectrum directory, a precise corresponding relationship between the pollutants and emission sources is established.

Description

Technical Field

[0001] This application relates to the field of environmental monitoring technology, specifically a pollutant source tracing method and system based on fingerprint spectrum. Background Technology

[0002] In the field of pollutant monitoring and source tracing in industrial parks, existing technologies mostly employ single monitoring methods, such as relying solely on fixed monitoring stations. This results in limited monitoring dimensions and coverage, failing to achieve comprehensive and three-dimensional monitoring of pollutants within the area. Simultaneously, existing source tracing technologies lack precise pollutant characteristic identification methods, making it difficult to quickly locate specific emission sources. Source tracing accuracy is limited to the enterprise level, unable to pinpoint specific emission points, leading to low efficiency and often requiring significant manpower and time for investigation, thus failing to meet the demands for rapid response and precise supervision.

[0003] In addition, the lack of a systematic method for constructing pollutant fingerprint spectra in existing technologies makes it difficult to establish an accurate correspondence between pollutants and emission sources, which can easily lead to misjudgments during the source tracing process and fail to provide a reliable basis for pollution control and regulatory enforcement.

[0004] Therefore, this application proposes a pollutant source tracing method and system based on fingerprint spectrum to address the shortcomings of the prior art. Summary of the Invention

[0005] The purpose of this application is to provide a pollutant source tracing method and system based on fingerprint spectrum to address the shortcomings mentioned in the background art.

[0006] The objective of this application can be achieved through the following technical solutions:

[0007] A pollutant source tracing method based on fingerprint spectrum includes the following steps:

[0008] Step 1: Construct a pollutant fingerprint spectrum based on the types and emission methods of pollutants within the target area;

[0009] Step two involves analyzing the daily monitoring data transmitted by small monitoring stations to identify abnormal areas where pollutant concentrations are abnormally high.

[0010] Step 3: Perform a first scan of the abnormal area using Fourier transform infrared telemetry equipment to obtain the transmission path and emission area of ​​the pollutants;

[0011] Step four: Based on the pollutant transmission path and emission area, plan the mobile scanning route, and conduct a comprehensive second scan of the abnormal area using the mobile scanning vehicle. Combined with the fingerprint spectrum database, identify enterprises with abnormally high pollutant concentrations.

[0012] Preferably, the pollutant fingerprint spectrum construction process is as follows: based on the raw materials and production processes of enterprises in the target area, combined with the total VOCs emissions of enterprises, the annual report on the implementation of the pollution discharge permit and the actual test results, characteristic pollutant factors are measured for each air-related link using the actual measurement method, and the test results are corrected in combination with the raw material information to construct the pollutant fingerprint spectrum of the waste gas characteristics of enterprises in the target area.

[0013] Preferably, the daily monitoring data includes real-time pollutant concentrations, the proportion of characteristic pollutant components, and meteorological data. The method for obtaining the target area of ​​abnormally elevated pollutant concentrations is as follows:

[0014] The acquired monitoring data is preprocessed;

[0015] Based on the daily monitoring environment of the small monitoring station, match the historical monitoring data of the target area;

[0016] Based on historical monitoring data of the target area, the normal concentration baseline values ​​and fluctuation upper limit thresholds of various pollutants are calculated and obtained;

[0017] Compare real-time monitoring data with normal concentration benchmarks and upper limit thresholds for fluctuations of various pollutants;

[0018] When the concentration of a single type of pollutant exceeds the upper limit of fluctuation for multiple consecutive preset collection cycles, or when a preset number of pollutants exceeds the threshold at the same time, it is marked as a concentration anomaly point.

[0019] Anomaly zones with abnormally high pollutant concentrations were constructed based on the marked anomaly locations.

[0020] Preferably, the method for performing step three is as follows:

[0021] The proportion of the characteristic pollutant components is matched with the fingerprint spectrum to screen out pollutant types that have a greater than preset threshold of consistency with the pollutant components in the abnormal area, which are then used as target source tracing pollutants.

[0022] The terrain features of the abnormal area are obtained, and the abnormal area is divided into multiple scanning sectors according to the terrain features. A scanning mode is preset for each sector. The Fourier transform infrared telemetry device collects the real-time peak concentration of the target source pollutant and the change curve of the proportion of characteristic components in the scanning sector as each scanning sector is scanned.

[0023] The coordinates of the peak concentration of the target source pollutant in each scanning sector are obtained. Based on real-time wind speed and direction data, the attenuation rate of the target source pollutant concentration is calculated starting from the scanning sector with the highest concentration of the target source pollutant in the abnormal area, and the preliminary potential transmission path is obtained.

[0024] Based on the changing patterns of the proportions of characteristic pollutant components, preliminary potential transmission paths are screened to obtain final potential transmission paths.

[0025] Using the starting point of any potential final transmission path as the center, the pollutant diffusion radius is calculated based on the inversion layer height and wind speed data to obtain the initial emission area;

[0026] By comparing the proportion of characteristic pollutant components in the initial emission area with the fingerprint spectrum, areas with a component consistency greater than a preset threshold are screened out. At the same time, based on the historical monitoring data of the small monitoring station, the pollutant concentration in the area before the abnormal period is verified, the emission area of ​​pollutants is determined, and potential pollution source locations in the emission area are marked simultaneously.

[0027] Preferably, the method for obtaining the decay rate of the target source pollutant concentration is as follows:

[0028] Using the peak pollutant concentration point as the transmission starting point, and based on the real-time wind speed in the abnormal area... Atmospheric diffusion coefficient in anomalous regions And the initial pollutant concentration at the highest concentration point within the abnormal area. Construct the spatial concentration distribution function of pollutants;

[0029] The first derivative of the spatial concentration distribution function of pollutants is obtained to obtain the instantaneous concentration change rate at any point in space.

[0030] The total cumulative concentration change within the transmission path interval is obtained through definite integral calculation;

[0031] The pollutant concentration decay rate is obtained by combining the total cumulative concentration change with the total length of the transport path. .

[0032] Preferably, the method for obtaining the initial emission area is as follows:

[0033] Based on the source center point of the final potential transmission path, the pollutant concentration decay rate, and the atmospheric diffusion coefficient, the effective diffusion critical distance of the pollutants is calculated, and the horizontal diffusion benchmark boundary of the emission source is obtained.

[0034] Based on the inversion layer height and real-time wind speed data in the anomalous area, and according to the vertical diffusion law of the atmosphere, the upper and lower limits of the vertical diffusion of pollutants are constrained, and the spatial three-dimensional diffusion constraint surface is delineated.

[0035] Spatial domain coupling modeling is performed based on the horizontal diffusion reference boundary and the vertical diffusion constraint surface, and a ring-shaped diffusion coverage area is generated with the source center point as the center.

[0036] By eliminating invalid areas within the annular diffusion coverage area where pollutant concentrations are lower than the normal concentration benchmark, the regional boundaries are corrected to obtain the preliminary pollutant emission area.

[0037] Preferably, the method for performing step four is as follows:

[0038] Based on the obtained pollutant transport paths, preliminary emission areas, and marked potential pollution source locations, a mobile vehicle scanning path is planned;

[0039] The pollutant detection equipment on the mobile monitoring vehicle was activated, and a second comprehensive scan of the abnormal area was carried out according to the planned route, while simultaneously collecting data on the real-time concentration of the target source pollutants and the proportion of characteristic pollutant components at the scan points;

[0040] The pollutant concentration data and characteristic component ratio data obtained by the mobile monitoring vehicle are compared one by one with the fingerprint spectrum database to screen out enterprises whose component matching degree is greater than the preset threshold as suspected abnormal high value emission enterprises.

[0041] Analyze the scanning data around suspected enterprises with abnormally high emissions to confirm whether the pollutant concentrations at the surrounding locations are consistently at abnormally high levels and whether the concentration changes match the production period of the enterprise. At the same time, based on historical monitoring data, identify enterprises with abnormally high pollutant emissions.

[0042] Preferably, the process of planning the scanning path of the mobile vehicle is as follows:

[0043] Integrate the coordinates of the final potential transmission path, the initial emission area of ​​pollutants, the coordinates of potential pollution source locations, and the topography and road distribution of the abnormal area;

[0044] Based on the needs of pollution source tracing, preset scanning priorities and set the scanning frequency for each area according to the scanning priorities;

[0045] Scanning priority includes primary scan area, secondary scan area, and tertiary scan area;

[0046] With the primary scanning area as the core, the main scanning path is planned, and the secondary scanning area is extended to plan the branch scanning path. The tertiary scanning area adopts a grid-like wiring to avoid terrain obstacles and prohibited sections, ensuring that the mobile vehicle can travel smoothly.

[0047] Simulate the travel trajectory of the mobile monitoring vehicle, and adjust the path wiring based on the simulation results.

[0048] This application also provides a pollutant source tracing system based on fingerprint spectrum, including the following modules:

[0049] The fingerprint spectrum construction module is used to construct pollutant fingerprint spectra based on the types and emission methods of pollutants within the target area.

[0050] The data acquisition module is used to collect pollutant data from the target area through small monitoring stations, Fourier transform infrared telemetry equipment, and mobile monitoring vehicles.

[0051] The data analysis module analyzes the daily monitoring data transmitted by the small monitoring station to identify abnormal areas where pollutant concentrations are abnormally high. The module performs a first scan of the abnormal area using a Fourier transform infrared telemetry device to obtain the transmission path and emission area of ​​the pollutants.

[0052] The source tracing module plans the scanning path of the mobile vehicle based on the transmission path and emission area of ​​the pollutants, and performs a comprehensive second scan of the abnormal area through the mobile vehicle to trace the source of the pollutants.

[0053] The beneficial effects of this application are as follows: By constructing a fingerprint spectrum database, this application establishes a precise correspondence between pollutants and emission sources, improving the accuracy of source tracing. It can accurately locate specific emission points and, through distributed small monitoring stations, Fourier transform infrared telemetry equipment, and mobile monitoring vehicles, comprehensively monitor the target area with a wide coverage. This allows for a complete understanding of pollutant emissions within the park, avoiding the limitations of single monitoring methods. Furthermore, the collaborative monitoring and source tracing method, combined with the advantages of multiple devices, improves source tracing efficiency, reducing the tracing time from the traditional several days to several hours, and significantly enhancing the speed of regulatory response.

[0054] Of course, any product implementing this application does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0055] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 This is a system module diagram of a pollutant source tracing system based on fingerprint spectrum according to this application.

[0057] Figure 2 This is a schematic diagram of the construction of the pollutant fingerprint spectrum in this application.

[0058] Figure 3 This is a flowchart illustrating the steps of a pollutant source tracing method based on fingerprint spectrum according to this application. Detailed Implementation

[0059] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0060] Please see Figure 1-2 As shown, this application is a pollutant source tracing system based on fingerprint spectrum, which includes a fingerprint spectrum construction module, a data acquisition module, a data analysis module, and a source tracing module;

[0061] The fingerprint spectrum construction module is used to construct pollutant fingerprint spectra based on the types and emission methods of pollutants in the target area. Specifically, by sorting out the raw materials, production processes and other information of enterprises in the park, combined with the total VOCs emissions of enterprises, the annual report on the implementation of the pollution discharge permit, and the actual test results, characteristic pollutant factors are determined by actual measurement method for each air-related link. The test results are corrected by combining the raw material information to construct a list of characteristic pollutant fingerprint spectra of enterprises in the park. Please refer to the fingerprint spectrum list table, which includes enterprise name, characteristic factors and emissions, proportional relationship, enterprise location, and fingerprint identification features.

[0062] Fingerprint Spectrum List

[0063] Company A N,N-Dimethylacetamide (683.33 kg), ethyl acetate (511.10 kg), n-butyl acetate (135.55 kg), toluene (69.89 kg), and m-xylene (27.65 kg) 25:18:5:3:1 South, southeast; 2.3km Corresponding wind direction, similar proportions or N,N-dimethylacetamide and ester compounds were detected. Company B Acetone (337.27 kg), trimethylsilanol (172.81 kg), ethyl acetate (241.91 kg) 2:1:1 North; 0.5km Corresponding to the wind direction, similar proportions or siloxane compounds such as trimethylsilanol were detected. Company C Ethyl acetate (385.67 kg), 2-ethylhexanol (127.15 kg), acetone (232.16 kg), isopentane (39.62 kg), n-butyl acetate (24.28 kg), isopropanol (20.23 kg) 19:6:11:2:1:1 South, southwest; 0.5km Corresponding wind direction, similar proportions or indicator pollutants such as 2-ethylhexanol and isopentane were detected. Company D Propylene (200.34 kg), acetone (193.11 kg), toluene (84.83 kg) 2:2:1 North, northwest; 2.9km Corresponding to the wind direction, similar proportional relationships or combinations of small molecule compounds such as propylene and acetic acid were detected. Enterprise E Ethyl acetate (582.36 kg), chloroform (118.74 kg), phenylacetylene (111.15 kg) 5:1:1 South, Southeast; 2.3km Under the corresponding wind direction, similar proportions or combinations of halogenated hydrocarbons (chloroform, trichloroethylene) and phenylacetylene were detected. Company F Acetone (195.27 kg), cis-2-butene (99.67 kg), ethanol (39.59 kg), m-p-xylene (10.00 kg) 20:10:4:1 South, Southeast; 0.3km Under the corresponding wind direction, a similar ratio was detected, or a combination of acetone + cis-2-butene + diethyl sulfide was detected.

[0064] The data acquisition module is used to collect pollutant data from the target area through small monitoring stations and Fourier transform infrared telemetry equipment. The small monitoring stations are mainly responsible for transmitting daily monitoring data, including real-time pollutant concentrations, the proportion of characteristic pollutant components, and meteorological data. By preprocessing the data, matching historical monitoring data of the target area, calculating the normal concentration benchmark value and the upper limit threshold of fluctuation, and comparing real-time data with the threshold, abnormal concentration points are marked and abnormal areas with abnormally high pollutant concentrations are constructed. For example, if a small monitoring station continuously collects VOCs concentration data of the target area, and matches the historical monitoring data of the area for the past 3 months to calculate the normal concentration benchmark value as 0.1 mg / m³ and the upper limit threshold of fluctuation as 0.3 mg / m³, and finds that the real-time VOCs concentration has reached 0.4 mg / m³ for 5 consecutive collection cycles, then this point is marked as an abnormal point, and an abnormal area is constructed by combining it with other abnormal points.

[0065] Fourier transform infrared (FTIR) telemetry equipment primarily performs the initial scan of anomaly areas identified by small monitoring stations. First, it matches the proportions of characteristic pollutant components with fingerprint spectra to screen out target pollutants. Then, it divides the anomaly area into scanning sectors based on the terrain and scans using a preset scanning mode. Simultaneously, it collects real-time peak concentrations of target pollutants and curves showing changes in the proportions of characteristic components in each sector. Combined with real-time wind speed and direction data, it calculates the concentration decay rate, obtains preliminary potential transmission paths, and screens out final potential transmission paths. Then, using the origin of the transmission path as the center, it calculates the diffusion radius based on inversion layer height and wind speed data to obtain the preliminary emission area. Finally, it compares the fingerprint spectra and verifies historical data. The emission area was determined and potential pollution source locations were marked. For example, the equipment matched the proportion of characteristic components collected with the fingerprint spectrum, and screened benzene series compounds with a consistency of ≥85% as target source pollutants. Industrial and residential sectors were divided and corresponding scanning modes were used. The peak concentration of benzene series compounds at a certain point in the industrial sector was 1.2 mg / m³. The attenuation rate was calculated by combining real-time wind speed, and two core transmission paths were fitted. After delineating the initial emission area, the fingerprint spectrum was compared to screen areas with a component consistency of ≥90%. Historical data was verified to confirm that the concentration in the area was normal before the abnormal period. Finally, the emission area was determined and a chemical plant's exhaust stack was marked as a potential pollution source.

[0066] Based on the emission area and potential pollution source locations, a scanning path is planned, and a second comprehensive scan of the abnormal area is carried out according to the planned path. Simultaneously, real-time concentrations and characteristic component ratios of the target source pollutants at the scan points are collected. The data is compared with the fingerprint spectrum database to screen out suspected enterprises with abnormally high emission values. The scan data around the suspected enterprises is analyzed and combined with historical monitoring data to determine the enterprises with abnormally high pollutant concentrations. For example, the mobile monitoring vehicle prioritizes scanning the emission area and the area around potential pollution source locations according to the planned path. It collects data showing that the concentration of benzene series compounds around a certain chemical enterprise is consistently above 0.8 mg / m³, and the concentration changes are completely matched with the production period of the enterprise. After eliminating interference by combining historical data, the enterprise is determined to be an enterprise with abnormally high emission values.

[0067] The data analysis module analyzes the daily monitoring data transmitted by the small monitoring stations to identify abnormal areas with abnormally high pollutant concentrations. It performs an initial scan of these abnormal areas using Fourier transform infrared telemetry to determine the pollutant transmission paths and emission areas. Specifically, the small monitoring stations are primarily used for daily monitoring, continuously transmitting daily monitoring data. Key daily monitoring data includes real-time pollutant concentrations, the proportion of characteristic pollutant components, and meteorological data. After acquiring and transmitting the daily monitoring data from the small monitoring stations, the module preprocesses the various types of data to remove abnormal data caused by equipment malfunctions or environmental interference, ensuring the authenticity and validity of the monitoring data. For example, it removes blank data caused by power outages and abnormal fluctuations under extreme weather conditions.

[0068] Subsequently, based on the daily monitoring environment of the small monitoring station, including the terrain of the monitoring point, the distribution of surrounding enterprises, and traffic conditions, historical monitoring data under the same monitoring environment in the target area are matched. Based on the real-time monitoring environment parameters of the current small monitoring station, including the terrain conditions of the monitoring point (such as flat areas, mountainous areas, and industrial areas), the layout of the surrounding environment (such as whether it is close to enterprise exhaust outlets, main roads, and residential areas), the real-time meteorological environment (such as wind speed, wind direction, and atmospheric stability), and the operating conditions of the monitoring equipment, historical monitoring data that are consistent with or highly consistent with the above-mentioned current monitoring environment parameters are selected from the historical monitoring database of the target area. Historical data with significant differences in environmental conditions due to changes in the surrounding environment, extreme weather, or equipment failure are eliminated. At the same time, it is ensured that the collection cycle and detection indicators of the selected historical data are consistent with those of the current real-time monitoring data. Finally, historical monitoring data that matches the current monitoring environment are obtained.

[0069] Based on the matched historical monitoring data, the normal concentration baseline value and fluctuation upper limit threshold of various pollutants are obtained. The normal concentration baseline value is the average value of historical monitoring data, and the fluctuation upper limit threshold is set in combination with the fluctuation range of historical data and industry emission standards. For example, if the historical average value of VOCs in a certain area is 0.15 mg / m³, the fluctuation upper limit threshold is set to 0.3 mg / m³ based on the fluctuation range. Then, the real-time monitoring data transmitted by the small monitoring station is compared with the normal concentration baseline value and fluctuation upper limit threshold of various pollutants one by one to determine whether there is a concentration anomaly. When the concentration of a single pollutant exceeds the fluctuation upper limit threshold for multiple consecutive preset collection cycles, such as 5 consecutive collection cycles, each cycle being 10 minutes, or a preset number, such as 3 or more pollutants exceeding the threshold at the same time, the monitoring point is marked as a concentration anomaly point.

[0070] Finally, based on all the marked abnormal concentration points, an abnormal area with abnormally high pollutant concentrations is constructed. For example, if multiple small monitoring stations in a certain area have marked abnormal concentration points, and these points are concentrated around the industrial area, then this concentrated area can be designated as an abnormal area.

[0071] After identifying the abnormal area, the characteristic pollutant component proportion data are matched with the pollutant fingerprint spectrum. A preset matching threshold is set (the component matching threshold is 85% in this application). Pollutant types with a matching degree greater than the threshold are selected and identified as target source pollutants. For example, if the characteristic component proportion detected in the abnormal area matches the benzene series in the fingerprint spectrum with a matching degree of 90%, then the benzene series is identified as the target source pollutant, thus clarifying the core pollutant type for source tracing.

[0072] Subsequently, the topographic features of the abnormal area are acquired, including topographic relief and regional functional division. Based on these topographic features, the abnormal area is divided into multiple scanning sectors. At the same time, two scanning modes, low-altitude scanning and high-altitude scanning, are preset for each sector. The Fourier transform infrared telemetry equipment is activated to scan each scanning sector one by one. During the scanning process, the real-time peak concentration of the target source pollutants and the characteristic component ratio change curves of each sector are collected simultaneously to obtain the pollutant concentration distribution of each sector. For example, when scanning the industrial area sector, the peak concentration of benzene series compounds at a certain point is collected as 1.2 mg / m³, and the coordinates of the point and the component ratio change curve are recorded at the same time.

[0073] After data collection, the coordinates of the peak concentration points of the target pollutants in each scanned sector are obtained. Based on the acquired real-time wind speed and direction data, the decay rate of the target pollutant concentration is calculated, starting from the scanned sector with the highest concentration of target pollutants in the abnormal area, using the formula:

[0074]

[0075] in, To target the rate of decay of pollutant concentrations at their source, This represents the initial pollutant concentration at the point with the highest concentration within the abnormal area. The spatial distance in the direction of pollutant transport. The coordinates of the starting point of the transmission path. This represents the endpoint coordinates corresponding to the pollutant concentration returning to the normal baseline value. This represents the atmospheric diffusion coefficient in the anomalous region. Real-time wind speed in abnormal areas;

[0076] Using the peak pollutant concentration point as the transmission starting point, and based on the real-time wind speed in the abnormal area... Atmospheric diffusion coefficient in anomalous regions And the initial pollutant concentration at the highest concentration point within the abnormal area. Construct the spatial concentration distribution function of pollutants Find the first derivative of the spatial concentration distribution function of pollutants. The instantaneous concentration change rate at any point in space is obtained, and the cumulative concentration change within the transmission path interval is obtained through definite integral calculation. Based on the total cumulative concentration change and the total length of the transmission path... Obtain the pollutant concentration decay rate .

[0077] For example, real-time wind speed in an abnormal area m / s, regional atmospheric diffusion coefficient Initial concentration of peak concentration mg / m 3 Distance from transmission starting point m, the distance corresponding to the pollutants returning to the normal baseline value m;

[0078] but,

[0079]

[0080] Under this operating condition, the average concentration decay rate of the target pollutant along the transport direction is approximately mg / (m 3 ⋅m), representing that for every 1 meter of outward transport of pollutants, the average concentration in the space decreases by 0.0346 mg / m³. This rate is then directly used to fit the initial potential transport path of pollutants.

[0081] In obtaining the pollutant concentration decay rate After identifying the initial potential transmission paths, the peak pollutant concentration points within the abnormal area are used as the starting points of the transmission paths. The main diffusion direction of pollutants is determined based on real-time wind speed and direction. Subsequently, the calculated concentration decay rate is used as the spatial diffusion constraint parameter. Along the atmospheric diffusion direction, the coordinates of the peak pollutant concentration points collected in each scanning sector are sequentially associated. The spatial distance and concentration difference between adjacent points are checked to verify whether they match the corresponding decay change pattern. Then, the point trajectories are continuously fitted based on the spatial distribution function of concentration to generate multiple initial potential transmission paths that conform to the atmospheric diffusion decay characteristics.

[0082] To illustrate this using the aforementioned pollutant concentration decay rate calculation results: In this source tracing scenario, the prevailing wind direction in the abnormal area is easterly, and the real-time wind speed is... m / s, the average concentration decay rate of the target source pollutant has been obtained by solving. 0.0346 mg / (m³⋅m), the peak point with the highest pollutant concentration in the region is set as the transmission starting point A(0,0), and the initial pollutant concentration at this point is... mg / m 3 Based on the real-time wind direction, it was determined that the pollutants diffused generally downwind (i.e., westward). Combined with the obtained concentration decay rate constraint, the peak concentration points in each scanning sector of the Fourier transform infrared telemetry were extracted sequentially, namely point B 50m from the starting point, point C 120m from the starting point, and point D 200m from the starting point. The pollutant concentration values ​​at each point were verified to conform to the decay change law calculated in this study. Then, the starting point A, point B, point C, and point D were continuously fitted and connected according to the spatial coordinate direction to form a continuous diffusion trajectory extending along the westerly wind. This spatial trajectory that satisfies the concentration decay law is the preliminary potential transmission path.

[0083] Subsequently, based on the changing patterns of the proportions of characteristic pollutant components, the preliminary potential transmission paths obtained based on attenuation rate fitting were screened. Paths with component proportion deviations greater than 10% were eliminated, and the final potential transmission paths with stable component proportions and concentration attenuation conforming to atmospheric diffusion patterns were retained. The transmission direction, transmission distance, and concentration distribution characteristics along the route of pollutants were clarified. The changing patterns of the proportions of characteristic pollutant components are as follows: exhaust gas emitted from the same pollution source has a fixed original component ratio. When pollutants diffuse with the wind in the atmosphere and their concentrations continuously decrease with distance, the relative proportions of various characteristic pollutants remain basically constant, with only the overall total concentration decreasing and the component ratio fluctuations being minimal. If exhaust gas from other enterprises, stray gases from the environment, or emissions from non-same-source pollution sources are mixed into the transmission path, the original ratio will be directly disrupted, resulting in significant deviations in component proportions, disordered proportions, and excessive fluctuations.

[0084] The process of screening preliminary potential transmission paths and obtaining final potential transmission paths is as follows: along each preliminary potential transmission path, the characteristic pollutant component proportion data at different distance points are extracted sequentially. Then, the real-time component proportion at each point is compared with the standard component proportion of the original pollutant source in the pollutant fingerprint spectrum point by point to obtain the component deviation value at each point. If the component proportion of all points on the entire path is stably consistent with the original proportion and the deviation value is always within the preset allowable range without obvious deviation or disorder, then the path is determined to be a true diffusion path from the same source and is retained. If there are points along a preliminary potential transmission path where the component proportion deviates significantly, the proportion is disordered, or the deviation value exceeds the threshold, it indicates that the path is mixed with external stray exhaust gas or other pollutant sources and is not the true transmission trajectory of the target pollutant, so the path is directly eliminated.

[0085] Subsequently, taking the starting point of any potential final transmission path as the center, and combining the inversion layer height and real-time wind speed data, the effective diffusion critical distance of pollutants is calculated based on the source center point of the potential final transmission path, the pollutant concentration decay rate, and the atmospheric diffusion coefficient, and the horizontal diffusion benchmark boundary of the emission source is determined.

[0086] The effective diffusion critical distance of pollutants is based on the spatial concentration distribution function of pollutants. By performing a reverse calculation, when the pollutant concentration along the route decreases to the normal pollutant concentration benchmark value, the spatial transmission distance between the emission source and the concentration point is the effective diffusion critical distance of the pollutant. This distance represents the limit of the diffusion distance of the target source pollutant from the emission source to the normal environmental background value.

[0087] The horizontal diffusion reference boundary uses the center point of the source of the final potential transmission path as the spatial reference circle, and the calculated effective diffusion critical distance of pollutants as the horizontal diffusion radius. The diffusion range is corrected according to the real-time wind direction of the abnormal area to weaken the offset error caused by crosswind airflow. A ring range is drawn in the horizontal plane of the ground according to this radius. The closed outer boundary formed by this is the horizontal diffusion reference boundary corresponding to the emission source, thereby limiting the maximum diffusion coverage of pollutants in the horizontal direction of the ground surface.

[0088] Based on the inversion layer height and real-time wind speed data, combined with the atmospheric vertical diffusion law, the upper and lower limits of vertical diffusion of pollutants are constrained, and a spatial three-dimensional diffusion constraint surface is delineated. Then, based on the horizontal diffusion benchmark boundary and the vertical diffusion constraint surface, a ring-shaped diffusion coverage area is generated with the source center point as the center. Finally, invalid areas with pollutant concentrations lower than the normal concentration benchmark value within the ring-shaped diffusion coverage area are eliminated, and the area boundary is corrected to obtain the preliminary pollutant emission area.

[0089] By comparing the proportion of characteristic pollutant components in the initial emission area with the fingerprint spectrum, areas with a component consistency greater than a preset threshold are screened out. At the same time, based on the historical monitoring data of the small monitoring station, the pollutant concentration in the area before the abnormal period is verified, the emission area of ​​pollutants is determined, and potential pollution source locations in the emission area are marked simultaneously.

[0090] The source tracing module is used to plan the mobile vehicle scanning path based on the pollutant's transmission path and emission area. The mobile vehicle performs a comprehensive second scan of the abnormal area to trace the pollutant's source. Specifically, based on the pollutant's final potential transmission path, the initial emission area of ​​the pollutant, and the marked potential pollution source locations within the emission area, it integrates the terrain and on-site road distribution information of the abnormal area, divides the scanning priority according to the source tracing requirements, and configures the corresponding scanning frequency. It sequentially plans the core main line, extended branch lines, and full-area grid scanning route, avoids terrain obstacles and restricted road sections, and completes path simulation verification and optimization to determine the final mobile vehicle scanning path.

[0091] The scanning priority division process is as follows: the area where pollutants are initially emitted and the surrounding area of ​​all marked potential pollution sources are designated as the first-level scanning area. This area is the core area of ​​suspected pollution sources and has the strongest pollution correlation. Therefore, it is set as the highest scanning priority and configured with the highest monitoring sampling frequency and point-to-point intensified scanning requirements.

[0092] The surrounding areas along all potential final transmission paths are designated as secondary scanning areas, which are areas through which pollutants diffuse. The pollution correlation is secondary, so they are set as medium scanning priority and use a conventional uniform scanning frequency to ensure complete collection of pollutant data along the transmission path.

[0093] The entire area outside of the first and second-level areas within the abnormal region is designated as the third-level scanning area. This area is used only for comprehensive investigation and has the weakest pollution correlation. It is set as the lowest scanning priority and uses a sparse mesh format for low-frequency scanning. After the core area is scanned, a full-area coverage scan is performed to complete the hierarchical division based on the pollution source tracing weight.

[0094] Subsequently, the detection equipment on the mobile monitoring vehicle was activated, and a second comprehensive scan of the abnormal area was carried out according to the planned optimal path, while simultaneously collecting monitoring data such as the real-time concentration of target pollutants and the proportion of characteristic pollutant components at each point along the route.

[0095] Next, all the measured data collected by the mobile monitoring vehicle were compared with the previously constructed enterprise pollutant fingerprint database one by one to screen out suspected abnormal emission enterprises with a matching degree exceeding the preset threshold. Finally, the characteristics of pollutant concentration changes around the suspected abnormal emission enterprises, the matching relationship between concentration fluctuations and the enterprise's production period, and the historical monitoring data retained by the small monitoring station were combined to complete interference elimination and authenticity verification, and to identify the enterprises involved with abnormally high pollutant concentrations.

[0096] Please see Figure 3 This application also provides a pollutant source tracing method based on fingerprint spectrum, including the following steps:

[0097] Step 1: Construct a pollutant fingerprint spectrum based on the types and emission methods of pollutants within the target area;

[0098] Step two involves analyzing the daily monitoring data transmitted by small monitoring stations to identify abnormal areas where pollutant concentrations are abnormally high.

[0099] Step 3: Perform a first scan of the abnormal area using Fourier transform infrared telemetry equipment to obtain the transmission path and emission area of ​​the pollutants;

[0100] Step four: Based on the pollutant transmission path and emission area, plan the mobile scanning route, and conduct a comprehensive second scan of the abnormal area using the mobile scanning vehicle. Combined with the fingerprint spectrum database, identify enterprises with abnormally high pollutant concentrations.

[0101] The above description is merely an example and illustration of the concept of this application. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the inventive concept or exceed the scope defined in the claims, they should all fall within the protection scope of this application.

Claims

1. A pollutant source tracing method based on fingerprint spectrum, characterized in that, Includes the following steps: Step 1: Construct a pollutant fingerprint spectrum based on the types and emission methods of pollutants within the target area; Step two involves analyzing the daily monitoring data transmitted by small monitoring stations to identify abnormal areas where pollutant concentrations are abnormally high. Step 3: Perform a first scan of the abnormal area using Fourier transform infrared telemetry equipment to obtain the transmission path and emission area of ​​the pollutants; Step four: Based on the pollutant transmission path and emission area, plan the mobile scanning route, and conduct a comprehensive second scan of the abnormal area using the mobile scanning vehicle. Combined with the fingerprint spectrum database, identify enterprises with abnormally high pollutant concentrations.

2. The pollutant source tracing method based on fingerprint spectrum according to claim 1, characterized in that, The pollutant fingerprint spectrum construction process is as follows: based on the raw materials and production processes of enterprises in the target area, combined with the total VOCs emissions of enterprises, the annual report on the implementation of the pollution discharge permit and the actual test results, characteristic pollutant factors are measured for each air-related link using the actual measurement method, and the test results are corrected in combination with the raw material information to construct the pollutant fingerprint spectrum of the waste gas characteristics of enterprises in the target area.

3. The pollutant source tracing method based on fingerprint spectrum according to claim 1, characterized in that, The routine monitoring data includes real-time pollutant concentrations, the proportion of characteristic pollutant components, and meteorological data. The method for obtaining the target areas with abnormally high pollutant concentrations is as follows: The acquired monitoring data is preprocessed; Based on the daily monitoring environment of the small monitoring station, match the historical monitoring data of the target area; Based on historical monitoring data of the target area, the normal concentration baseline values ​​and fluctuation upper limit thresholds of various pollutants are calculated and obtained; Compare real-time monitoring data with normal concentration benchmarks and upper limit thresholds for fluctuations of various pollutants; When the concentration of a single type of pollutant exceeds the upper limit of fluctuation for multiple consecutive preset collection cycles, or when a preset number of pollutants exceeds the threshold at the same time, it is marked as a concentration anomaly point. Anomaly zones with abnormally high pollutant concentrations were constructed based on the marked anomaly locations.

4. The pollutant source tracing method based on fingerprint spectrum according to claim 1, characterized in that, The method for performing step three is as follows: The proportion of the characteristic pollutant components is matched with the fingerprint spectrum to screen out pollutant types that have a greater than preset threshold of consistency with the pollutant components in the abnormal area, which are then used as target source tracing pollutants. The terrain features of the abnormal area are obtained, and the abnormal area is divided into multiple scanning sectors according to the terrain features. A scanning mode is preset for each sector. The Fourier transform infrared telemetry device collects the real-time peak concentration of the target source pollutant and the change curve of the proportion of characteristic components in the scanning sector as each scanning sector is scanned. The coordinates of the peak concentration of the target source pollutant in each scanning sector are obtained. Based on real-time wind speed and direction data, the attenuation rate of the target source pollutant concentration is calculated starting from the scanning sector with the highest concentration of the target source pollutant in the abnormal area, and the preliminary potential transmission path is obtained. Based on the changing patterns of the proportions of characteristic pollutant components, preliminary potential transmission paths are screened to obtain final potential transmission paths. Using the starting point of any potential final transmission path as the center, the pollutant diffusion radius is calculated based on the inversion layer height and wind speed data to obtain the initial emission area; By comparing the proportion of characteristic pollutant components in the initial emission area with the fingerprint spectrum, areas with a component consistency greater than a preset threshold are screened out. At the same time, based on the historical monitoring data of the small monitoring station, the pollutant concentration in the area before the abnormal period is verified, the emission area of ​​pollutants is determined, and potential pollution source locations in the emission area are marked simultaneously.

5. The pollutant source tracing method based on fingerprint spectrum according to claim 4, characterized in that, The method for obtaining the decay rate of the target source pollutant concentration is as follows: Using the peak pollutant concentration point as the transmission starting point, and based on the real-time wind speed in the abnormal area... Atmospheric diffusion coefficient in anomalous regions And the initial pollutant concentration at the highest concentration point within the abnormal area. Construct the spatial concentration distribution function of pollutants; The first derivative of the spatial concentration distribution function of pollutants is obtained to obtain the instantaneous concentration change rate at any point in space. The total cumulative concentration change within the transmission path interval is obtained through definite integral calculation; The pollutant concentration decay rate is obtained by combining the total cumulative concentration change with the total length of the transport path. .

6. The pollutant source tracing method based on fingerprint spectrum according to claim 5, characterized in that, The method for obtaining the preliminary emission area is as follows: Based on the source center point of the final potential transmission path, the pollutant concentration decay rate, and the atmospheric diffusion coefficient, the effective diffusion critical distance of the pollutants is calculated, and the horizontal diffusion benchmark boundary of the emission source is obtained. Based on the inversion layer height and real-time wind speed data in the anomalous area, and according to the vertical diffusion law of the atmosphere, the upper and lower limits of the vertical diffusion of pollutants are constrained, and the spatial three-dimensional diffusion constraint surface is delineated. Spatial domain coupling modeling is performed based on the horizontal diffusion reference boundary and the vertical diffusion constraint surface, and a ring-shaped diffusion coverage area is generated with the source center point as the center. By eliminating invalid areas within the annular diffusion coverage area where pollutant concentrations are lower than the normal concentration benchmark, the regional boundaries are corrected to obtain the preliminary pollutant emission area.

7. The pollutant source tracing method based on fingerprint spectrum according to claim 1, characterized in that, The method for performing step four is as follows: Based on the obtained pollutant transport paths, preliminary emission areas, and marked potential pollution source locations, a mobile vehicle scanning path is planned; The pollutant detection equipment on the mobile monitoring vehicle was activated, and a second comprehensive scan of the abnormal area was carried out according to the planned route, while simultaneously collecting data on the real-time concentration of the target source pollutants and the proportion of characteristic pollutant components at the scan points; The pollutant concentration data and characteristic component ratio data obtained by the mobile monitoring vehicle are compared one by one with the fingerprint spectrum database to screen out enterprises whose component matching degree is greater than the preset threshold as suspected abnormal high value emission enterprises. Analyze the scanning data around suspected enterprises with abnormally high emissions to confirm whether the pollutant concentrations at the surrounding locations are consistently at abnormally high levels and whether the concentration changes match the production period of the enterprise. At the same time, based on historical monitoring data, identify enterprises with abnormally high pollutant emissions.

8. The pollutant source tracing method based on fingerprint spectrum according to claim 7, characterized in that, The process of planning the scanning path of the mobile vehicle is as follows: Integrate the coordinates of the final potential transmission path, the initial emission area of ​​pollutants, the coordinates of potential pollution source locations, and the topography and road distribution of the abnormal area; Based on the needs of pollution source tracing, preset scanning priorities and set the scanning frequency for each area according to the scanning priorities; Scanning priority includes primary scan area, secondary scan area, and tertiary scan area; With the primary scanning area as the core, the main scanning path is planned, and the secondary scanning area is extended to plan the branch scanning path. The tertiary scanning area adopts a grid-like wiring to avoid terrain obstacles and prohibited sections, ensuring that the mobile vehicle can travel smoothly. Simulate the travel trajectory of the mobile monitoring vehicle, and adjust the path wiring based on the simulation results.

9. A pollutant source tracing system based on fingerprint spectrum, applicable to the pollutant source tracing method based on fingerprint spectrum according to claims 1-8, characterized in that, Includes the following modules: The fingerprint spectrum construction module is used to construct pollutant fingerprint spectra based on the types and emission methods of pollutants within the target area. The data acquisition module is used to collect pollutant data from the target area through small monitoring stations, Fourier transform infrared telemetry equipment, and mobile monitoring vehicles. The data analysis module analyzes the daily monitoring data transmitted by the small monitoring station to identify abnormal areas where pollutant concentrations are abnormally high. The module performs a first scan of the abnormal area using a Fourier transform infrared telemetry device to obtain the transmission path and emission area of ​​the pollutants. The source tracing module plans the scanning path of the mobile vehicle based on the transmission path and emission area of ​​the pollutants, and performs a comprehensive second scan of the abnormal area through the mobile vehicle to trace the source of the pollutants.

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