Method and device for determining heavy metal emission from unorganized sources and electronic equipment

Abstract

Embodiments of the present application provide a kind of unorganized source heavy metal emission determination method, device and electronic equipment, belong to atmospheric environment evaluation field.Therein method includes: setting the monitoring path of each unorganized source partition, according to monitoring path obtains particulate matter concentration matrix and wind vector matrix;According to particulate matter concentration matrix, obtain the boundary of flux monitoring section;The target heavy metal content of particulate matter in each unorganized source partition is acquired;Based on particulate matter concentration matrix, wind vector matrix and target heavy metal content, the heavy metal emission of all grids in the boundary of flux monitoring section is summed, and the heavy metal emission of each unorganized source partition is obtained;According to the heavy metal emission of each unorganized source partition, the total heavy metal emission of mine enterprise unorganized source area is acquired.The numerical value of all grids in the boundary of flux monitoring section is calculated to obtain the heavy metal emission of unorganized source area, and the accounting accuracy of heavy metal emission of unorganized source area is improved.

Description

Technical Field

[0001] This application relates to the field of atmospheric environmental assessment, and in particular to a method, apparatus and electronic equipment for determining the emission of heavy metals from fugitive sources. Background Technology

[0002] Fugitive emissions refer to exhaust gas emissions without a stack or with a stack height of less than 15 meters. Fugitive emissions from mining enterprises often contain heavy metals, posing a significant hazard. These emissions are characterized by multiple pollution-generating points, dispersed emission sources, irregular patterns, and the lack of definite emission outlets for monitoring, making accurate calculation of heavy metal emissions quite difficult. Summary of the Invention

[0003] To address the aforementioned technical problems, embodiments of this application provide a method, apparatus, and electronic device for determining the emission of heavy metals from fugitive sources.

[0004] In a first aspect, embodiments of this application provide a method for determining the amount of heavy metal emissions from fugitive sources, the method comprising:

[0005] The mining enterprises are divided into multiple unorganized source zones;

[0006] Set the monitoring path for each of the aforementioned unorganized source zones, obtain the flux monitoring section composed of particulate matter concentration and wind vector according to the monitoring path, grid the flux monitoring section to obtain the particulate matter concentration and wind vector of each grid, and establish the particulate matter concentration matrix and wind vector matrix corresponding to each grid respectively.

[0007] The boundary of the flux monitoring section is determined based on the particulate matter concentration matrix;

[0008] Obtain the target heavy metal content of particulate matter in each of the aforementioned unorganized source zones;

[0009] The heavy metal emissions of each of the unorganized source zones are obtained by summing the heavy metal emissions of all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix, and the target heavy metal content.

[0010] The total heavy metal emissions from the unorganized source areas of the mining enterprise are calculated based on the heavy metal emissions from each of the aforementioned unorganized source zones.

[0011] In one embodiment, setting the monitoring path for each of the unorganized source partitions includes:

[0012] The monitoring distance is determined based on the emission length of the unorganized source zone;

[0013] The scanning direction is determined based on the exhaust direction of the unorganized source partition;

[0014] The monitoring path is set according to the monitoring distance and the scanning direction.

[0015] In one embodiment, the flux monitoring section includes a concentration monitoring section and a wind vector monitoring section. The step of obtaining the flux monitoring section composed of particulate matter concentration and wind vector based on the monitoring path, and then gridding the flux monitoring section to obtain the particulate matter concentration and wind vector for each grid, includes:

[0016] By using a particulate matter lidar to monitor along the monitoring path at preset positioning accuracy intervals within the production cycle, multiple concentration monitoring sections composed of particulate matter concentrations are obtained. Each concentration monitoring section is then gridded to obtain multiple particulate matter concentrations corresponding to each grid.

[0017] By using a wind-measuring lidar to monitor along the monitoring path at preset positioning accuracy intervals within the production cycle, multiple wind vector monitoring sections composed of wind vectors are obtained. Each wind vector monitoring section is then gridded to obtain multiple wind vectors corresponding to each grid.

[0018] In one embodiment, the particulate matter lidar monitors the particulate matter along the monitoring path at preset positioning accuracy intervals within the production cycle to obtain multiple concentration monitoring sections composed of particulate matter concentration, including:

[0019] The extinction coefficient distribution and the response function of particulate matter concentration of the lidar are pre-established;

[0020] The current extinction coefficient of the particulate matter lidar on the monitoring path is obtained at preset positioning accuracy intervals;

[0021] The current particulate matter concentration is obtained through the response function and the current extinction coefficient. Based on the particulate matter concentration, a current concentration monitoring section is constructed, and finally, multiple current concentration monitoring sections are obtained within the production cycle.

[0022] In one embodiment, determining the boundary of the flux monitoring section based on the particulate matter concentration matrix includes:

[0023] The particulate matter concentration threshold of the boundary is set according to the particulate matter concentration of the background point upwind;

[0024] If a grid with a particulate matter concentration equal to the particulate matter concentration threshold is obtained from the particulate matter concentration matrix, then the boundary of the grid is the boundary of the flux monitoring section.

[0025] In one embodiment, obtaining the target heavy metal content of particulate matter in each of the unorganized source zones includes:

[0026] Particulate matter is collected onto a sampling membrane using a multi-stage impactor particulate sampler.

[0027] The target heavy metal content on the sampling membrane is analyzed to obtain the target heavy metal content of particulate matter in the unorganized source zone.

[0028] In one embodiment, the step of summing the heavy metal emissions of all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix, and the target heavy metal content to obtain the heavy metal emissions of each of the unorganized source zones includes:

[0029] During the production cycle, the heavy metal emissions of all grids within the boundary of the flux monitoring section are summed according to formula (1) to obtain the heavy metal emissions of each of the unorganized source zones at different particle sizes.

[0030] Formula (1): ;

[0031] Calculate the average value of the heavy metal emissions under the same particle size multiple times, and sum the average values ​​of the heavy metal emissions of different particle sizes to obtain the heavy metal emissions of each of the unorganized source zones;

[0032] in, The emissions of heavy metals at different particle sizes in different zones of the unorganized source are represented. This represents the total number of all grid cells within the boundary of the flux monitoring section. Coordinates are The area of ​​the grid, The target heavy metal content of particulate matter in the unorganized source zone. Coordinates are The particle concentration of the grid, This represents the particulate matter concentration at the upwind background point. Coordinates are The component of the wind vector in the direction perpendicular to the flux monitoring section of the grid.

[0033] Secondly, embodiments of this application provide a device for determining the amount of heavy metals emitted from fugitive sources, the device comprising:

[0034] The partitioning module is used to divide mining enterprises into multiple unorganized source zones;

[0035] A module is established to set the monitoring path for each of the unorganized source zones. Based on the monitoring path, a flux monitoring section composed of particulate matter concentration and wind vector is obtained. The flux monitoring section is gridded to obtain the particulate matter concentration and wind vector of each grid, and a particulate matter concentration matrix and a wind vector matrix corresponding to each grid are established respectively.

[0036] The determination module is used to determine the boundary of the flux monitoring section based on the particulate matter concentration matrix;

[0037] The acquisition module is used to acquire the target heavy metal content of particulate matter in each of the aforementioned unorganized source partitions;

[0038] The first calculation module is used to sum the heavy metal emissions of all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix and the target heavy metal content, so as to obtain the heavy metal emissions of each of the unorganized source zones.

[0039] The second calculation module is used to calculate the total heavy metal emissions of the mining enterprise's unorganized source areas based on the heavy metal emissions of each of the unorganized source zones.

[0040] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the computer program executes the method for determining the amount of fugitive heavy metal emissions provided in the first aspect when the processor is running.

[0041] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when run on a processor, executes the method for determining the amount of fugitive heavy metal emissions provided in the first aspect.

[0042] The method for determining fugitive heavy metal emissions provided in this application involves dividing a mining enterprise into multiple fugitive source zones; setting monitoring paths for each fugitive source zone; obtaining flux monitoring sections composed of particulate matter concentration and wind vector based on the monitoring paths; gridding the flux monitoring sections to obtain the particulate matter concentration and wind vector for each grid; establishing a particulate matter concentration matrix and a wind vector matrix corresponding to each grid; determining the boundary of the flux monitoring section based on the particulate matter concentration matrix; obtaining the target heavy metal content of particulate matter in each fugitive source zone; summing the heavy metal emissions of all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix, and the target heavy metal content to obtain the heavy metal emissions of each fugitive source zone; and calculating the total heavy metal emissions of the mining enterprise's fugitive source area based on the heavy metal emissions of each fugitive source zone. By constructing a particulate matter concentration matrix and a wind vector matrix, the values ​​of all grids within the boundary of the flux monitoring section are calculated to obtain the heavy metal emissions in the unorganized source area, thereby improving the accuracy of the calculation of heavy metal emissions in the unorganized source area. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and should not be considered as a limitation on the scope of protection of this application. In the various drawings, similar components are numbered similarly.

[0044] Figure 1 This paper illustrates a flowchart of a method for determining fugitive heavy metal emissions provided in an embodiment of this application.

[0045] Figure 2 This paper illustrates another flowchart of the method for determining fugitive heavy metal emissions provided in an embodiment of this application.

[0046] Figure 3 This illustration shows another flowchart of the method for determining fugitive heavy metal emissions provided in an embodiment of this application;

[0047] Figure 4 This paper illustrates another flowchart of the method for determining fugitive heavy metal emissions provided in an embodiment of this application.

[0048] Figure 5 A schematic diagram of a wind vector monitoring section provided in an embodiment of this application is shown;

[0049] Figure 6 A schematic diagram of the concentration monitoring section and the boundary line of the boundary grid provided in the embodiment of this application is shown;

[0050] Figure 7 A schematic diagram of the structure of the device for determining the amount of heavy metals from fugitive sources provided in an embodiment of this application is shown.

[0051] Icons: 700 - Device for determining the amount of heavy metal emissions from unorganized sources, 701 - Division module, 702 - Establishment module, 703 - Determination module, 704 - Acquisition module, 705 - First calculation module, 706 - Second calculation module. Detailed Implementation

[0052] The technical solutions in 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.

[0053] The components of the embodiments of this application described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0054] In the following, the terms “comprising,” “having,” and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as excluding, firstly, the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more features, numbers, steps, operations, elements, components, or combinations thereof.

[0055] Furthermore, the terms "first," "second," and "third" are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0056] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0057] Example 1

[0058] Fugitive source emissions refer to ground-based pollution sources without fixed emission measures or with an emission height of less than 15m. These emissions are typically irregular, not occurring through centralized emission facilities such as chimneys or exhaust stacks, but rather being released directly into the environment in the form of gases or dust, containing large amounts of heavy metal pollutants. To determine the amount of heavy metals emitted, this application provides a method for determining the amount of heavy metals emitted from fugitive sources.

[0059] See Figure 1 The method for determining the amount of heavy metal emissions from unorganized sources includes steps S101-S106:

[0060] S101: Divide the mining enterprise into multiple unorganized source zones.

[0061] In this embodiment, zones are defined based on the characteristics of heavy metal enrichment under different production environments. Unorganized source areas in mining enterprises can generally be divided into crushing and screening zones, grinding and flotation zones, waste rock dumps, and tailings ponds. The types and amounts of heavy metals generated at different production stages vary. Crushing and screening zones and grinding and flotation zones mainly generate dust containing heavy metals such as lead, arsenic, cadmium, copper, and zinc; the heavy metal content in waste rock dumps and tailings areas varies depending on the mineral processing technology and is usually much lower than the heavy metal emissions from crushing, screening, and grinding and flotation.

[0062] S102: Set the monitoring path for each of the unorganized source zones, obtain the flux monitoring section composed of particulate matter concentration and wind vector according to the monitoring path, grid the flux monitoring section to obtain the particulate matter concentration and wind vector of each grid, and establish the particulate matter concentration matrix and wind vector matrix corresponding to each grid respectively.

[0063] In this embodiment, a reasonable monitoring path is set for each unorganized source zone based on its emission direction and length. This path covers the main diffusion direction of the emission source. Real-time monitoring is performed along the set monitoring path using particulate matter lidar and wind lidar to obtain a flux monitoring cross-section composed of particulate matter concentration and wind vector. The cross-sectional data accurately reflects the distribution of pollutant concentration and wind field.

[0064] Optionally, each flux monitoring section can be divided into grids, that is, the continuous data on the monitoring path can be discretized into a series of small grids. Each grid contains particulate matter concentration values ​​corresponding to multiple samplings. The size of the grid should be determined according to the monitoring requirements and the accuracy of data analysis, so as to ensure the detail of the data while avoiding excessive data redundancy.

[0065] On the other hand, similar to the particulate matter concentration matrix, each grid also corresponds to multiple wind vector values, including wind speed and wind direction components. Optionally, the positioning accuracy of the lidar must not be less than 5m, and mobile monitoring is carried out during the production cycle, with multiple samplings at preset time intervals. The flux of the multiple calculation results is taken, and the average value of the multiple fluxes is calculated as the final result of heavy metal emissions.

[0066] See Figure 2 In one embodiment, setting the monitoring path for each of the unorganized source partitions includes steps S201-S203:

[0067] S201: Determine the monitoring distance based on the emission length of the unorganized source zone.

[0068] In this embodiment, the unorganized source zone consists of multiple workshops and factories. The length of the emission source directly affects the diffusion range and concentration distribution of its emissions. Generally speaking, the longer the emission source, the wider the diffusion range of its emissions may be in the direction perpendicular to the emission direction. Therefore, a range based on the emission source length (L) is proposed, that is, the monitoring distance D should satisfy L≤D≤2L.

[0069] S202: Determine the scanning direction based on the exhaust direction of the unorganized source partition.

[0070] In this embodiment, based on the monitoring distance D determined in step S201, a scanning direction perpendicular to the exhaust direction of the emission source is set downwind of the unorganized source zone, that is, the scanning direction is also parallel to the emission source (workshop building).

[0071] S203: Set the monitoring path according to the monitoring distance and the scanning direction.

[0072] In this embodiment, based on the monitoring distance D determined in step S201 and the scanning direction perpendicular to the exhaust direction, optionally, for example, a workshop in the crushing and emission area is 34 meters long and 20 meters high. Considering the characteristics of fugitive emissions from mining enterprises, namely that the emissions may spread with the wind and cause pollution within a certain range, a monitoring path perpendicular to the emission direction is set up downwind of the workshop, 50 meters away from the boundary of the emission source. The length of the monitoring path is not limited.

[0073] See Figure 3 In one embodiment, the flux monitoring section includes a concentration monitoring section and a wind vector monitoring section. The step of obtaining the flux monitoring section composed of particulate matter concentration and wind vector based on the monitoring path, and then gridding the flux monitoring section to obtain the particulate matter concentration and wind vector for each grid, includes steps S301-S302:

[0074] S301: The particulate matter lidar is used to monitor along the monitoring path at preset positioning accuracy intervals within the production cycle to obtain multiple concentration monitoring sections composed of particulate matter concentration. Each concentration monitoring section is gridded to obtain multiple particulate matter concentrations corresponding to each grid.

[0075] In this embodiment, a particulate matter lidar is used for real-time monitoring along the monitoring path. Optionally, the preset positioning accuracy is 5m to ensure data consistency. The particulate matter concentration values ​​obtained through monitoring constitute the concentration monitoring cross-sections along the entire path. The concentration monitoring cross-sections obtained from each monitoring are divided into a grid, with each grid having a fixed area. That is, the entire concentration monitoring cross-section is divided into multiple small grids, and each grid corresponds to the particulate matter concentration data obtained from multiple monitoring sessions.

[0076] See Figure 4 In one embodiment, the step of using a particulate matter lidar to monitor along the monitoring path at preset time intervals during the production cycle to obtain multiple concentration monitoring sections composed of particulate matter concentration includes steps S401-S403:

[0077] S401: Pre-establish the extinction coefficient distribution and particulate matter concentration response function of the lidar.

[0078] In this embodiment, before monitoring begins, a response function between the extinction coefficient distribution of the lidar and the particulate matter concentration is established in advance through experiments or theoretical derivation. Optionally, a multiple regression analysis method is used to establish the relationship between the extinction coefficient of the lidar and the particulate matter number concentration along the monitoring path, converting the extinction coefficient into a specific particulate matter concentration value (such as PM10 concentration). Optionally, the specific response function in this embodiment is... ,in Extinction coefficient, unit: ; Particulate matter Concentration, in units of .

[0079] S402: At preset positioning accuracy intervals, obtain the current extinction coefficient of the particulate matter lidar on the monitoring path.

[0080] In this embodiment, during the monitoring process, at preset positioning accuracies (e.g., 5m), particulate lidar is used to obtain the current extinction coefficient data distribution along the monitoring path.

[0081] S403: The current particulate matter concentration is obtained through the response function and the current extinction coefficient. Based on the particulate matter concentration, a current concentration monitoring section is constructed, and finally, multiple current concentration monitoring sections are obtained within the production cycle.

[0082] In this embodiment, the acquired extinction coefficient data is substituted into a pre-established response function for calculation to obtain the corresponding particulate matter concentration value. Then, a concentration monitoring section is constructed based on the distribution of particulate matter concentration values ​​along the monitoring path. Finally, multiple current concentration monitoring sections are obtained within the production cycle. Each concentration monitoring section will display the concentration distribution of pollutants at different time periods during the production cycle, and the final average concentration distribution is obtained as the concentration distribution of pollutants in the unorganized source zone.

[0083] S302: The wind-measuring lidar monitors the wind along the monitoring path at preset time intervals during the production cycle to obtain multiple wind vector monitoring sections composed of wind vectors. Each wind vector monitoring section is then gridded to obtain multiple wind vectors corresponding to each grid.

[0084] In this embodiment, see Figure 5 This is a schematic diagram of a wind vector monitoring section, where the horizontal axis represents the width of the monitoring section and the vertical axis represents its height. A wind-measuring lidar is used for real-time monitoring along the monitoring path. Similarly, monitoring is performed at preset positioning accuracy intervals within the production cycle to acquire the distribution of wind vector data from unorganized sources. The wind vector data includes wind direction and speed. The obtained wind vector data forms the wind vector monitoring section. Each monitoring section is then divided into grids, consistent with the gridding of the concentration monitoring section. Each grid contains multiple wind vector data points obtained from multiple monitoring sessions.

[0085] S103: Determine the boundary of the flux monitoring section based on the particulate matter concentration matrix.

[0086] In this embodiment, the particulate matter concentration of the background point is obtained by monitoring at a fixed height (uncontaminated) upwind of the workshop, and is used as the particulate matter concentration threshold. The target boundary grid is obtained by obtaining the particulate matter concentration of the flux monitoring grid that returns to the particulate matter concentration threshold. The boundary of the target boundary grid is used as the boundary of the flux monitoring section.

[0087] In one embodiment, step S103 includes: setting a particulate concentration threshold for the boundary grid based on the particulate concentration of the upwind background point; obtaining grids from the particulate concentration matrix whose particulate concentration is equal to the particulate concentration threshold, wherein the boundary of the grid is the boundary of the flux monitoring section.

[0088] In this embodiment, in order to distinguish between areas with high pollutant concentrations (i.e., areas affected by pollution sources) and areas with low background concentrations (areas with low pollution source impact), a particulate matter concentration threshold is determined based on the upwind background point monitoring values ​​of the monitored fugitive source areas, historical data, environmental quality standards, and recommended values ​​from scientific research, reflecting significant changes in pollutant concentrations within the monitoring area.

[0089] Optionally, each grid in the particulate matter concentration matrix is ​​traversed, and its particulate matter concentration value is compared with a set threshold. If the particulate matter concentration of a certain grid is equal to the set particulate matter concentration threshold, then that grid is considered a boundary grid. See [link to relevant documentation]. Figure 6 This is a schematic diagram of the boundary line of a specific boundary grid. The boundary line is both the boundary line of the particulate matter concentration of each grid and the boundary line of the extinction coefficient of each grid. Within the boundary line, the extinction coefficient of each grid is greater than zero and the particulate matter concentration is greater than the threshold. The smaller the extinction coefficient of the monitoring section, the smaller the particulate matter concentration; the larger the extinction coefficient, the larger the particulate matter concentration. At the point of maximum concentration, the extinction coefficient is generally greater than 1.6000.

[0090] S104: Obtain the target heavy metal content of particulate matter in each of the aforementioned unorganized source zones.

[0091] In this embodiment, it is necessary to obtain the target heavy metal content of particulate matter of different particle sizes in different unorganized source partitions. The target heavy metal content includes lead content, arsenic content, cadmium content and mercury content, and the sum of the contents of each heavy metal is taken as the target heavy metal content.

[0092] In one embodiment, step S104 includes: collecting particulate matter into a sampling membrane using a multi-stage impactor; analyzing the target heavy metal content on the sampling membrane to obtain the target heavy metal content in the particulate matter in the unorganized source zone.

[0093] In this embodiment, a multi-stage impactor particulate matter sampler is used to collect particulate matter. Aerosol particles of different aerodynamic diameters are separated and collected onto sampling membranes at each stage according to aerodynamic principles. This is used to analyze the heavy metal content of particulate matter of different diameters and to understand the distribution characteristics of heavy metals in particulate matter of different diameters. In this embodiment, particulate matter... The heavy metal content of the target metals (lead, arsenic, cadmium and total mercury) was analyzed, and the experimental results are shown in Table 1.

[0094] Table 1 Dust Reduction in Workshop Heavy metal test results (mg / kg)

[0095]

[0096] The contents of lead, arsenic, and cadmium were detected using inductively coupled plasma mass spectrometry, while the contents of mercury were detected using atomic fluorescence spectrometry.

[0097] S105: Based on the particulate matter concentration matrix, the wind vector matrix, and the target heavy metal content, sum the heavy metal emissions of all grids within the boundary of the flux monitoring section to obtain the heavy metal emissions of each of the unorganized source zones.

[0098] In this embodiment, it is necessary to use lidar to acquire particulate matter concentration matrices, wind vector matrices, and target heavy metal content at different particle sizes multiple times during the production cycle, calculate the average heavy metal emission amount of each experiment at that particle size, and sum the heavy metal emission amounts corresponding to each particle size to obtain the heavy metal emission amount of each unorganized source zone.

[0099] In one embodiment, step S105 includes: during the production cycle, summing the heavy metal emissions of all grids within the boundary of the flux monitoring section according to formula (1) to obtain the heavy metal emissions of each of the unorganized source zones at different particle sizes; formula (1): ; Calculate the average value of the heavy metal emissions from multiple sources at the same particle size, and sum the average values ​​of the heavy metal emissions from different particle sizes to obtain the heavy metal emissions from each of the unorganized source zones; wherein, The emissions of heavy metals at different particle sizes in different zones of the unorganized source are represented. This represents the total number of all grid cells within the boundary of the flux monitoring section. Coordinates are The area of ​​the grid, The target heavy metal content of particulate matter in the unorganized source zone. Coordinates are The particle concentration of the grid, The concentration of particulate matter outside the boundary grid. Coordinates are The component of the wind vector in the direction perpendicular to the flux monitoring section of the grid.

[0100] In this embodiment, optionally, the flux monitoring section is gridded to form... A number of gridded matrices, each with an area of... According to formula (1), the heavy metal emission amount in any unorganized source zone can be calculated multiple times. And calculate the average value during the production cycle. The heavy metal emissions of each of the aforementioned unorganized source zones are obtained by summing the average values ​​of heavy metal emissions from different particle sizes. .

[0101] S106: Calculate the total heavy metal emissions of the mining enterprise's unorganized source areas based on the heavy metal emissions of each of the aforementioned unorganized source zones.

[0102] In this embodiment, since the heavy metal emissions of each of the unorganized source zones are obtained through step S105... Then each Summing the results, we obtain the total heavy metal emissions from the mining company as follows: By statistically analyzing the heavy metal emission flux at each grid point in space, we can achieve accurate accounting of fugitive emissions and provide a basis for environmental management.

[0103] The method for determining fugitive heavy metal emissions provided in this embodiment divides a mining enterprise into multiple fugitive source zones; sets monitoring paths for each fugitive source zone; obtains flux monitoring sections composed of particulate matter concentration and wind vector based on the monitoring paths; grids the flux monitoring sections to obtain the particulate matter concentration and wind vector for each grid, and establishes a particulate matter concentration matrix and a wind vector matrix corresponding to each grid; determines the boundary of the flux monitoring section based on the particulate matter concentration matrix; obtains the target heavy metal content of particulate matter in each fugitive source zone; sums the heavy metal emissions of all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix, and the target heavy metal content to obtain the heavy metal emissions of each fugitive source zone; and calculates the total heavy metal emissions of the mining enterprise's fugitive source area based on the heavy metal emissions of each fugitive source zone. By constructing a particulate matter concentration matrix and a wind vector matrix, the values ​​of all grids within the boundary of the flux monitoring section are calculated to obtain the heavy metal emissions in the unorganized source area, thereby improving the accuracy of the calculation of heavy metal emissions in the unorganized source area.

[0104] Example 2

[0105] In addition, this application provides a device for determining the emission of heavy metals from unorganized sources, which is applied to electronic devices.

[0106] like Figure 7 As shown, the fugitive source heavy metal emission determination device 700 includes:

[0107] The partitioning module 701 is used to divide the mining enterprise into multiple unorganized source zones;

[0108] A module 702 is established to set the monitoring path for each of the unorganized source zones. Based on the monitoring path, a flux monitoring section composed of particulate matter concentration and wind vector is obtained. The flux monitoring section is gridded to obtain the particulate matter concentration and wind vector of each grid, and a particulate matter concentration matrix and a wind vector matrix corresponding to each grid are established respectively.

[0109] The determination module 703 is used to determine the boundary of the flux monitoring section based on the particulate matter concentration matrix;

[0110] The acquisition module 704 is used to acquire the target heavy metal content of particulate matter in each of the aforementioned unorganized source partitions;

[0111] The first calculation module 705 is used to sum the heavy metal emissions of all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix and the target heavy metal content, so as to obtain the heavy metal emissions of each of the unorganized source zones.

[0112] The second calculation module 706 is used to calculate the total heavy metal emissions of the mining enterprise's unorganized source areas based on the heavy metal emissions of each of the unorganized source zones.

[0113] Optionally, the establishment module 702 shown is further configured to determine the monitoring distance based on the emission length of the fugitive source zone; determine the scanning direction based on the exhaust direction of the fugitive source zone; and set the monitoring path based on the monitoring distance and the scanning direction.

[0114] Optionally, the module 702 shown is further configured to perform monitoring along the monitoring path at preset positioning accuracies within the production cycle using a particulate matter lidar to obtain multiple concentration monitoring sections composed of particulate matter concentrations, and to grid each concentration monitoring section to obtain multiple particulate matter concentrations corresponding to each grid; and to perform monitoring along the monitoring path along the monitoring path at preset positioning accuracies within the production cycle using a wind-measuring lidar to obtain multiple wind vector monitoring sections composed of wind vectors, and to grid each wind vector monitoring section to obtain multiple wind vectors corresponding to each grid.

[0115] Optionally, the establishment module 702 shown is also used to pre-establish the extinction coefficient distribution of the lidar and the response function of the particulate matter concentration; obtain the current extinction coefficient of the particulate matter lidar on the monitoring path at preset positioning accuracy intervals; obtain the current particulate matter concentration through the response function and the current extinction coefficient; construct the current concentration monitoring section based on the particulate matter concentration; and finally obtain multiple current concentration monitoring sections within the production cycle.

[0116] Optionally, the determination module 703 shown is further configured to set a particulate concentration threshold for the boundary based on the particulate concentration of the upwind background point; and to obtain a grid from the particulate concentration matrix in which the particulate concentration is equal to the particulate concentration threshold, wherein the boundary of the grid is the boundary of the flux monitoring section.

[0117] Optionally, the acquisition module 704 shown is further configured to collect particulate matter to a sampling membrane via a multi-stage impactor; analyze the target heavy metal content on the sampling membrane to obtain the target heavy metal content of the particulate matter in the unorganized source partition.

[0118] Optionally, the first calculation module 705 shown is further configured to sum the heavy metal emissions of all grids within the boundary of the flux monitoring section according to formula (1) during the production cycle, to obtain the heavy metal emissions of each of the unorganized source zones at different particle sizes; formula (1): ; Calculate the average value of the heavy metal emissions from multiple sources at the same particle size, and sum the average values ​​of the heavy metal emissions from different particle sizes to obtain the heavy metal emissions from each of the unorganized source zones; wherein, The emissions of heavy metals at different particle sizes in different zones of the unorganized source are represented. This represents the total number of all grid cells within the boundary of the flux monitoring section. Coordinates are The area of ​​the grid, The target heavy metal content of particulate matter in the unorganized source zone. Coordinates are The particle concentration of the grid, This represents the particulate matter concentration at the upwind background point. Coordinates are The component of the wind vector in the direction perpendicular to the flux monitoring section of the grid.

[0119] The fugitive source heavy metal emission determination device 700 provided in this embodiment can realize the fugitive source heavy metal emission determination method provided in Embodiment 1. To avoid repetition, it will not be described again here.

[0120] The device for determining the amount of heavy metal emissions from fugitive sources provided in this embodiment divides a mining enterprise into multiple fugitive source zones; sets a monitoring path for each fugitive source zone; obtains a flux monitoring section composed of particulate matter concentration and wind vector based on the monitoring path; grids the flux monitoring section to obtain the particulate matter concentration and wind vector for each grid, and establishes a particulate matter concentration matrix and a wind vector matrix corresponding to each grid; determines the boundary of the flux monitoring section based on the particulate matter concentration matrix; obtains the target heavy metal content of particulate matter in each fugitive source zone; sums the heavy metal emissions of all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix, and the target heavy metal content to obtain the heavy metal emissions of each fugitive source zone; and calculates the total heavy metal emissions of the fugitive source area of ​​the mining enterprise based on the heavy metal emissions of each fugitive source zone. By constructing a particulate matter concentration matrix and a wind vector matrix, the values ​​of all grids within the boundary of the flux monitoring section are calculated to obtain the heavy metal emissions in the unorganized source area, thereby improving the accuracy of the calculation of heavy metal emissions in the unorganized source area.

[0121] Example 3

[0122] Furthermore, this application provides an electronic device, including a memory and a processor. The memory stores a computer program, which executes the method for determining the amount of fugitive heavy metal emissions provided in Embodiment 1 when the computer program is run on the processor.

[0123] The electronic device provided in this embodiment of the invention can execute the steps of the method for determining the amount of fugitive heavy metal emissions provided in the above-described method embodiment 1. To avoid repetition, these steps will not be repeated here.

[0124] Example 4

[0125] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for determining the amount of fugitive heavy metal emissions provided in Embodiment 1.

[0126] In this embodiment, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0127] The computer-readable storage medium provided in this embodiment can implement the method for determining the amount of fugitive heavy metal emissions provided in Embodiment 1. To avoid repetition, it will not be described again here.

[0128] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal that includes that element.

[0129] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0130] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for determining the amount of heavy metal emissions from fugitive sources, characterized in that, The method includes: The mining enterprises are divided into multiple unorganized source zones; Set the monitoring path for each of the aforementioned unorganized source zones, obtain the flux monitoring section composed of particulate matter concentration and wind vector according to the monitoring path, grid the flux monitoring section to obtain the particulate matter concentration and wind vector of each grid, and establish the particulate matter concentration matrix and wind vector matrix corresponding to each grid respectively. The boundary of the flux monitoring section is determined based on the particulate matter concentration matrix; Obtain the target heavy metal content of particulate matter in each of the aforementioned unorganized source zones; The heavy metal emissions of each of the unorganized source zones are obtained by summing the heavy metal emissions of all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix, and the target heavy metal content. The total heavy metal emissions from the unorganized source areas of the mining enterprise are calculated based on the heavy metal emissions from each of the aforementioned unorganized source zones.

2. The method according to claim 1, characterized in that, The setting of monitoring paths for each of the aforementioned unorganized source partitions includes: The monitoring distance is determined based on the emission length of the unorganized source zone; The scanning direction is determined based on the exhaust direction of the unorganized source partition; The monitoring path is set according to the monitoring distance and the scanning direction.

3. The method according to claim 1, characterized in that, The flux monitoring section includes a concentration monitoring section and a wind vector monitoring section. The flux monitoring section, composed of particulate matter concentration and wind vector, is obtained according to the monitoring path. The flux monitoring section is then gridded to obtain the particulate matter concentration and wind vector for each grid, including: By using a particulate matter lidar to monitor along the monitoring path at preset positioning accuracy intervals within the production cycle, multiple concentration monitoring sections composed of particulate matter concentrations are obtained. Each concentration monitoring section is then gridded to obtain multiple particulate matter concentrations corresponding to each grid. By using a wind-measuring lidar to monitor along the monitoring path at preset positioning accuracy intervals within the production cycle, multiple wind vector monitoring sections composed of wind vectors are obtained. Each wind vector monitoring section is then gridded to obtain multiple wind vectors corresponding to each grid.

4. The method according to claim 3, characterized in that, The process involves using a particulate matter lidar to monitor along the monitoring path at preset positioning accuracy intervals within the production cycle, resulting in multiple concentration monitoring sections composed of particulate matter concentrations, including: The extinction coefficient distribution and the response function of particulate matter concentration of the lidar are pre-established; The current extinction coefficient of the particulate matter lidar on the monitoring path is obtained at preset positioning accuracy intervals; The current particulate matter concentration is obtained through the response function and the current extinction coefficient. Based on the particulate matter concentration, a current concentration monitoring section is constructed, and finally, multiple current concentration monitoring sections are obtained within the production cycle.

5. The method according to claim 1, characterized in that, Determining the boundary of the flux monitoring section based on the particulate matter concentration matrix includes: The particulate matter concentration threshold of the boundary is set according to the particulate matter concentration of the background point upwind; If a grid with a particulate matter concentration equal to the particulate matter concentration threshold is obtained from the particulate matter concentration matrix, then the boundary of the grid is the boundary of the flux monitoring section.

6. The method according to claim 1, characterized in that, The acquisition of the target heavy metal content of particulate matter in each of the aforementioned unorganized source zones includes: Particulate matter is collected onto a sampling membrane using a multi-stage impactor particulate sampler. The target heavy metal content on the sampling membrane is analyzed to obtain the target heavy metal content of particulate matter in the unorganized source zone.

7. The method according to claim 1, characterized in that, The summation of heavy metal emissions from all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix, and the target heavy metal content yields the heavy metal emissions from each of the unorganized source zones, including: During the production cycle, the heavy metal emissions of all grids within the boundary of the flux monitoring section are summed according to formula (1) to obtain the heavy metal emissions of each of the unorganized source zones at different particle sizes. Formula (1): ; Calculate the average value of the heavy metal emissions under the same particle size multiple times, and sum the average values ​​of the heavy metal emissions of different particle sizes to obtain the heavy metal emissions of each of the unorganized source zones; in, The emissions of heavy metals at different particle sizes in different zones of the unorganized source are represented. This represents the total number of all grid cells within the boundary of the flux monitoring section. Coordinates are The area of ​​the grid, The target heavy metal content of particulate matter in the unorganized source zone. Coordinates are The particle concentration of the grid, This represents the particulate matter concentration at the upwind background point. Coordinates are The component of the wind vector in the direction perpendicular to the flux monitoring section of the grid.

8. A device for determining the amount of heavy metal emissions from fugitive sources, characterized in that, The device includes: The partitioning module is used to divide mining enterprises into multiple unorganized source zones; A module is established to set the monitoring path for each of the unorganized source zones. Based on the monitoring path, a flux monitoring section composed of particulate matter concentration and wind vector is obtained. The flux monitoring section is gridded to obtain the particulate matter concentration and wind vector of each grid, and a particulate matter concentration matrix and a wind vector matrix corresponding to each grid are established respectively. The determination module is used to determine the boundary of the flux monitoring section based on the particulate matter concentration matrix; The acquisition module is used to acquire the target heavy metal content of particulate matter in each of the aforementioned unorganized source partitions; The first calculation module is used to sum the heavy metal emissions of all grids within the boundary of the flux monitoring section based on the particulate matter concentration matrix, the wind vector matrix and the target heavy metal content, so as to obtain the heavy metal emissions of each of the unorganized source zones. The second calculation module is used to calculate the total heavy metal emissions of the mining enterprise's unorganized source areas based on the heavy metal emissions of each of the unorganized source zones.

9. An electronic device, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program that executes the method for determining the amount of fugitive heavy metal emissions according to any one of claims 1 to 7 when the processor is running.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when run on a processor, executes the method for determining the amount of fugitive heavy metal emissions as described in any one of claims 1 to 7.

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