Point source methane emission flux real-time monitoring method, device, equipment and medium

Abstract

The embodiment of the invention discloses a point source methane emission flux real-time monitoring method, device, equipment and medium, and relates to the technical field of environmental monitoring, the method comprises the following steps: acquiring methane column concentration data of a rasterized monitoring area, generating a horizontal net flux of each grid, extracting to obtain a plume coverage area, and calculating the concentration of the plume coverage area; obtaining a first integral region and a second integral region in sequence; and performing area integral in the second integral region, and outputting the point source methane emission amount of the methane emission point source in the rasterized monitoring region. By adopting the method provided by the invention, the plume coverage area and the integral area are extracted, so that the accurate emission estimation can be realized on the premise of no prior data and accurate plume contour, the point source methane emission can be obtained in real time, and the time sequence of long-time emission of the point source can be monitored on the basis of the accurate emission estimation. The problems of methane emission leakage and environmental pollution can be quickly solved.

Description

Technical Field

[0001] The present application relates to the field of environmental monitoring technology, and in particular to a method, device, equipment and medium for real-time monitoring of point source methane emission flux. Background Art

[0002] As the world's second largest greenhouse gas, the uncertainty of methane's environmental impact exceeds that of carbon dioxide in many aspects. Therefore, the control of methane emissions is of great significance.

[0003] Among them, point source emissions have the most significant impact on methane emissions, such as anthropogenic methane point source emissions from coal mine ventilation vents, oil and gas facilities, livestock and poultry farms, landfills and sewage treatment plants. These point sources are small in scale, spatially concentrated and have large temporal variations. Therefore, it is difficult to quantify the instantaneous methane emissions from each point source.

[0004] At present, point source emissions can be observed in point and strip forms through high-resolution remote sensing satellite technology, and regional and surface observations can also be achieved. However, in the case of strip observations, the emission inversion algorithm based on the Gaussian plume model cannot guarantee the integrity of regional plume enhancement, and will overly rely on the robustness of the wind field and the regularity of gas transmission, resulting in high computational costs and low computational efficiency; in the case of point observations, due to the need for more sophisticated Lagrangian diffusion models and Euler diffusion models, the computational efficiency is low, resulting in the inability to achieve high-precision real-time quantification; in the case of surface observations, the accuracy of inversion algorithms such as IME and DI is overly dependent on the integrity of the extracted emission plume and the accurate fitting of the effective wind speed, and cannot achieve real-time and low-cost monitoring of point source emissions.

[0005] Therefore, there is currently a lack of a real-time quantification method for point source emissions that is not constrained by the accuracy of the extracted plume profile and does not require the transmission model to reconstruct the surface observed wind speed. Summary of the invention

[0006] The present application provides a method, device, equipment and storage medium for real-time monitoring of point source methane emission flux, which are used to solve the defects of the above-mentioned related technologies. The technical solution is as follows:

[0007] In a first aspect, an embodiment of the present application provides a method for real-time monitoring of point source methane emission flux, comprising:

[0008] Obtain methane column concentration data in the gridded monitoring area;

[0009] Performing gradient calculations based on the methane column concentration data of each grid to obtain the gradient of the corresponding grid, and generating the horizontal net flux of each grid based on the gradient and the real-time wind field vector data;

[0010] Extracting a plume coverage area of ​​the rasterized monitoring area, and determining a first integral area based on the plume coverage area;

[0011] Based on the first integral region, a second integral region that meets the constraint condition is obtained; wherein the constraint condition is determined based on the methane background concentration flux and the wind divergence flux in the first integral region;

[0012] Surface integration is performed in the second integral region to output the point source methane emissions of the methane emission point sources in the rasterized monitoring area.

[0013] In an optional solution of the first aspect, performing gradient calculation based on the methane column concentration data of each grid to obtain the gradient of the corresponding grid, and generating the horizontal net flux of each grid based on the gradient and real-time wind field vector data, comprises:

[0014] The gradient of the methane column concentration data of each grid is calculated, and the gradient is multiplied by the wind vector of the real-time wind field vector data to obtain the horizontal net flux of each grid, and the formula is applied:

[0015]

[0016] Among them, V CH4 For the methane column concentration data of each grid, is the gradient operator, is the x-component of the wind vector and D is the horizontal net flux for each of the grids.

[0017] In an optional solution of the first aspect, before generating the horizontal net flux of each grid based on the gradient and wind field vector data, the method further includes:

[0018] Obtain real-time wind field vector data;

[0019] Difference calculation is performed based on the real-time wind field vector data, and the accuracy difference of the wind vector is set to the same accuracy as the rasterized monitoring area.

[0020] In an optional solution of the first aspect, the extracting to obtain a plume coverage area of ​​the rasterized monitoring area, and determining to obtain a first integral area based on the plume coverage area, comprises:

[0021] The difference between the methane column concentration data of each grid in the gridded monitoring area and the corresponding methane background concentration is calculated based on the KW test algorithm. If the difference is less than or equal to a preset test threshold, the corresponding grid is excluded; otherwise, the corresponding grid is retained, and the plume coverage area is extracted based on all the retained grids;

[0022] Determine an endpoint of the plume coverage area along the plume direction in the plume coverage area and an endpoint of the plume coverage area at a preset distance opposite to the plume direction, determine an integral endpoint of the first integral area based on the plume coverage area endpoint, and obtain the first integral area based on the integral endpoint.

[0023] In an optional solution of the first aspect, the constraint condition includes:

[0024]

[0025] in, is the methane background concentration in the second plot area, X CH4 is the methane column concentration data in the second integral region, V air is the density of the air column, M CH4 is the number of moles of methane, is the gradient operator, is the methane background concentration flux, is the wind divergence flux.

[0026] In an optional solution of the first aspect, performing surface integration in the second integral region and outputting the point source methane emissions of the methane emission point sources in the rasterized monitoring area includes:

[0027] Perform surface integration based on the horizontal net flux of all grids in the second integration area, applying the formula:

[0028]

[0029] Based on the integration result, the point source methane emission of the methane emission point source in the gridded monitoring area is obtained;

[0030] Wherein, E is the point source methane emission and D is the horizontal net flux.

[0031] In an optional solution of the first aspect, before performing the surface integration in the second integral area and outputting the point source methane emission of the methane emission point source in the rasterized monitoring area, the method further includes:

[0032] Calculate the correlation coefficient between the background concentration flux of methane and the horizontal net flux in the second integration region, using the formula:

[0033]

[0034] If the correlation coefficient If it is greater than 0, the horizontal net flux is corrected and the formula is applied:

[0035]

[0036] The performing of surface integration in the second integral region to output the point source methane emission of the methane emission point source in the gridded monitoring area includes:

[0037] Performing surface integration based on the corrected horizontal net flux, outputting point source methane emissions of methane emission point sources in the rasterized monitoring area;

[0038] Among them, D CH4 is the horizontal net flux before correction in the second integration region, is the methane background concentration flux in the second integration region, D CH4 ′ is the corrected horizontal net flux.

[0039] In a second aspect, the present application also provides a point source methane emission flux real-time monitoring device, comprising:

[0040] A data acquisition module, used to acquire methane column concentration data in a gridded monitoring area;

[0041] A horizontal net flux calculation module, used to perform gradient calculation based on the methane column concentration data of each grid to obtain the gradient of the corresponding grid, and generate the horizontal net flux of each grid based on the gradient and real-time wind field vector data;

[0042] An integral region calculation module, used for extracting a plume coverage area of ​​the rasterized monitoring area, and determining a first integral region based on the plume coverage area;

[0043] The integral region calculation module is further used to obtain a second integral region that meets the constraint condition according to the first integral region; wherein the constraint condition is determined based on the methane background concentration flux and the wind divergence flux in the first integral region;

[0044] The point source methane emission calculation module is used to perform surface integration in the second integral area and output the point source methane emission of the methane emission point source in the rasterized monitoring area.

[0045] In a third aspect, an embodiment of the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method provided in the first aspect of the embodiment of the present application or any one of the implementation methods of the first aspect is implemented.

[0046] In a fourth aspect, the present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided by the first aspect of the embodiment of the present application or any one of the implementations of the first aspect.

[0047] The beneficial effects brought about by the technical solutions provided by some embodiments of the present application include at least:

[0048] (1) Compared with the algorithms for inverting point source emissions in related technologies, the present application is less dependent on the accuracy of the meteorological field and realizes automatic correction of wind field errors and background methane concentration errors through an intelligent optimization algorithm.

[0049] (2) This application does not require any manual visual interpretation or input of prior emissions, nor does it require accurate methane plume contour extraction. By extracting the plume coverage area and extracting the integral area, accurate emissions estimation can be achieved without prior data and accurate plume contours.

[0050] (3) The present application can obtain point source methane emissions in real time, and based on this, can monitor the time series of long-term point source emissions, and can quickly respond to methane emission leaks and environmental pollution problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 It is a flow chart of a method for real-time monitoring of point source methane emission flux according to an embodiment of the present application;

[0053] Figure 2 It is a structural schematic diagram of a point source methane emission flux real-time monitoring device provided in an embodiment of the present application;

[0054] Figure 3 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0056] The terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or modules is not limited to the listed steps or modules, but may optionally include steps or modules that are not listed, or may optionally include other steps or modules that are inherent to these processes, methods, products or devices.

[0057] It should be noted that the terms "first\second" involved in the present application are only used to distinguish similar objects, and do not represent a specific order for the objects. It is understandable that "first\second" can be interchanged with a specific order or sequence where permitted. It should be understood that the objects distinguished by "first\second" can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those described or illustrated herein.

[0058] At present, there is a lack of reference examples and rules for the unconstrained real-time quantification of methane point source emissions using high-resolution satellites. Designing an effective real-time methane point source emission quantification scheme can not only fill the gap in this field, but also have the potential to become an industry standard. To this end, the present invention proposes a FI-SCAPE point source methane emission real-time quantification method using high-resolution satellite image data, which quantifies the emission flux of the methane point source by using the methane full column concentration data set obtained by high-resolution remote sensing satellite inversion and the high-resolution wind field data set, calculates the horizontal net flux in the area near the point source, and further introduces the sine-cosine optimization method (SCA), selects the optimized integral region, and performs surface integration on the horizontal net flux in the integral region to obtain the real-time emission flux estimate of the point source. Thereby, the current methane point source emission monitoring algorithm can solve the problems of too many constraints, the need for prior values, and poor real-time performance, and can not only quickly invert the methane emissions of the point source under the condition of no priori, but also can correct the reported value of the emission inventory in real time through the monitoring results, and can provide technical support for the rapid early warning and emergency plan deployment of emergencies such as methane leaks.

[0059] The present application is described in detail below with reference to specific embodiments.

[0060] Next, combine Figure 1 , introduces a method for real-time monitoring of point source methane emission flux provided in an embodiment of the present application, Figure 1 A flow chart of a method for real-time monitoring of methane emission flux from a point source provided in an embodiment of the present application is shown. The method for real-time monitoring of methane emission flux from a point source comprises the following steps:

[0061] S101, obtaining methane column concentration data in a gridded monitoring area;

[0062] S102, performing gradient calculation based on the methane column concentration data of each grid to obtain the gradient of the corresponding grid, and generating the horizontal net flux of each grid based on the gradient and the real-time wind field vector data;

[0063] S103, extracting a plume coverage area of ​​the rasterized monitoring area, and determining a first integral area based on the plume coverage area;

[0064] S104, obtaining a second integral region that meets the constraint condition based on the first integral region; wherein the constraint condition is determined based on the methane background concentration flux and the wind divergence flux in the first integral region;

[0065] S105, performing surface integration in the second integral area, and outputting the point source methane emission of the methane emission point source in the rasterized monitoring area.

[0066] Specifically, in S101, a high-resolution satellite may be used to capture images around a point source emitting methane, and rasterization may be performed based on the captured images to divide the images into multiple grids of the same size, wherein each grid may include one or more pixels, which is not limited in the present application.

[0067] It can be understood that the methane column concentration data source can be multi-source data such as ground monitoring station data, airborne data, and satellite-borne high-resolution data.

[0068] Specifically, the monitoring area can be a region within 5 km of the methane emission point source as the center, and the monitoring area can be rasterized to determine the methane column concentration data within the geographical range of each grid, that is, the methane column concentration corresponding to the grid.

[0069] Specifically, in S102, calculation is performed based on the methane column concentration data of each grid obtained in the gridded monitoring area obtained in S101.

[0070] It should be noted that in local areas where the wind speed is not too high (generally considered to be less than 10m / s) and the terrain gradient is gentle (the absolute value of the elevation change is less than 50m), newly emitted methane is usually concentrated around the emission source.

[0071] Specifically, the calculation theory derivation process of quantifying methane point source emissions based on the horizontal flux integration method in this application comes from solving the continuity equation. Ignoring the horizontal turbulent transport, the three-dimensional gas transport continuity equation can be expressed as:

[0072]

[0073] Among them, by solving the partial differential equation and integrating x, y, and z respectively, the calculation formula of the horizontal net flux of the methane observation column is obtained:

[0074]

[0075] where u and v are the x and y components of the wind vector, respectively, and F is the vertical flux; τ c is the chemical lifetime of methane, C CH4 is the methane gas concentration, V CH4 is the methane column concentration, z0 represents the elevation, that is, the full column integration of the methane gas concentration data in the grid is used to obtain the methane column concentration V CH4 .

[0076]

[0077] in, is called the concentration gradient term, is the gradient operator, is called the terrain term, and V CH4 / τ is called the chemical term, and the last two terms are the errors corresponding to the topographic and chemical terms;

[0078] and Represents 100m and 10m vector wind respectively; is the gradient of surface elevation; β is called the inverse of the methane scale height (in m -1 ), D is the horizontal net flux.

[0079] It should be noted that since the 100-m wind is widely used to characterize the horizontal transport in the planetary boundary layer (PBL), it is generally believed that there is almost no difference between the full-column concentration and the column concentration in the inner layer of the PBL during horizontal transport, and thus the full-column concentration is used for calculation in this application.

[0080] It should be noted that in order to make full use of the data and reduce the gradient jump caused by orbital splicing, the gradient numerical calculation method adopted in this application is the second-order difference according to the orbit, and the horizontal wind vector is converted from geodetic coordinates to orbital coordinates according to the rotation direction of the orbital pixel.

[0081] It should be noted that since the spatial range of the quantified flux field is distributed in a very small area around the emission point source, it can be approximately considered that the influence of terrain on the quantification of the flux field is small. Therefore, unlike the regional large-scale flux quantification, the terrain term can be approximately ignored when calculating point source emissions, and it can be regarded as one of the components of emission estimation uncertainty. Since methane has a lifetime of 20 years or even longer in the atmosphere and almost maintains a steady state in the short term in the emission enhancement area, the process of chemical or deposition reaction is far less likely than NO X The chemical terms can be ignored.

[0082] Therefore, the calculation formula for the horizontal net flux of methane near a point source is as follows:

[0083]

[0084] The above formula is applied to calculate the gradient of the methane column concentration data of each grid, and the gradient is dot-multiplied with the wind vector of the real-time wind field vector data to obtain the horizontal net flux of each grid.

[0085] Furthermore, in order to make the model converge faster and minimize the impact of other emission point sources on the quantified emission sources, it is necessary to adjust the integration area, and execute step S103 to determine the first integration area.

[0086] Specifically, the shape of the plume can be briefly extracted through the mask method, that is, the plume coverage area of ​​the rasterized monitoring area can be obtained.

[0087] Specifically, the plume areas where methane diffuses with the wind field can be identified through the principle of KW test, that is, through Kruskal-Wallis one-way analysis of variance, including:

[0088] Hypothesis H0: There is no significant difference between the methane concentration in the grid corresponding area and the methane background concentration;

[0089] H1: The methane concentration in the grid corresponding area is significantly different from the methane background concentration field;

[0090] The preset inspection threshold A=0.05 can be taken.

[0091] Specifically, the value of the difference value H can be calculated using the formula:

[0092]

[0093] N=∑n i ;

[0094] If the difference between the calculated methane column concentration data of each grid and the corresponding methane background concentration is less than or equal to the preset inspection threshold, the corresponding grid is excluded; if the difference between the calculated methane column concentration data of each grid and the corresponding methane background concentration is greater than the preset inspection threshold, the corresponding grid is retained, and the plume coverage area is extracted based on all retained grids.

[0095] Further, the endpoints of the plume coverage area along the plume direction and the endpoints of the plume coverage area at a preset distance opposite to the plume direction are determined, and the integral endpoints of the first integral area are determined based on the plume coverage area endpoints, and the first integral area is obtained based on the integral endpoints.

[0096] It can be understood that the first integral area is a rectangular area determined based on the endpoints of the plume coverage area, wherein one corner point is obtained by continuing to extend the plume endpoint of the plume coverage area along the plume direction corresponding to the wind direction, for example, extending by about 1.5 times the distance; the other corner point can be obtained by extending a number of grids based on the point source position in the plume coverage area in the plume direction against the wind direction, for example, extending 15 pixels on the image.

[0097] Therefore, the first integration area can be determined based on the plume coverage area.

[0098] In some embodiments, considering that in point source detection and quantification with finer resolution, the horizontal flux has not undergone the spatial averaging and temporal averaging equalization steps, the instantaneous horizontal flux is more affected by the background flux and wind divergence. The choice of the integration area directly determines the accuracy of the inversion result. Therefore, the embodiment of the present application requires further selection of the integration area.

[0099] It should be noted that the full column concentration of methane in each grid is generally the sum of the methane concentration emitted by the point source and the methane background concentration, that is:

[0100]

[0101] Where, ΔV CH4 is the methane column concentration emitted from point sources, is the methane background column concentration, is the average methane concentration in the monitoring area.

[0102] It should be noted that since it is very difficult to obtain the background concentration, the regional concentration mean can generally be used to replace the methane background concentration. The target pixel can be selected as the center, and 11 pixels can be taken on the top, bottom, left and right sides for sliding average calculation to obtain the average methane concentration in the corresponding monitoring area.

[0103] Therefore, the actual observed methane column concentration data is:

[0104]

[0105] It can also be expressed as:

[0106]

[0107] in, is the horizontal net flux of methane emitted by point sources, is the background net flux of methane background concentration, is the wind divergence flux.

[0108] Furthermore, it is necessary to ensure that the influence of the background concentration horizontal flux is as small as possible, that is, the background emission value through the rectangular area is as small as possible, and at the same time, the wind divergence has a certain degree of influence on the spatial divergence of the methane column concentration. The present application uses the sine-cosine optimization algorithm SCA to solve the optimization problem and executes step S104:

[0109] First, the search area is determined based on the first integral area as follows:

[0110]

[0111] Further apply the following formula, iterate continuously in the search area given above, and obtain the second integral area, including:

[0112]

[0113] Specifically, the obtained second integral region needs to satisfy the following constraints on the methane background concentration flux and wind divergence flux:

[0114]

[0115] The numerical results of the above constraints are D1 and D2 respectively, and the fitness function f of the optimization algorithm is written in the least squares form:

[0116] f=‖D1‖ 2 +λ‖D2‖ 2 ;

[0117] in, The vector formed by the coordinates of the upper left corner and lower right corner of the rectangle corresponding to the second integral region, expressed as (x1, x2, y1, y2) T ; L max is the diagonal of the rectangle corresponding to the first integration region, Indicates the calculation result obtained by iteration t, where T is the total number of iterations. is the methane background concentration in the second integral region, X CH4 is the methane column concentration data in the second integral region, V air is the density of the air column, M CH4 is the number of moles of methane, is the gradient operator, is the methane background concentration flux, is the wind divergence flux, r1, r2, r3 and r4 are random parameters.

[0118] Based on step S104, a second integral area with a smaller range can be further obtained on the basis of the first integral area obtained in S103, thereby avoiding the influence of wind divergence flux and methane background concentration flux and improving the detection accuracy of point source methane emissions as much as possible.

[0119] Further, an area integral is performed based on the second integral region, and step S105 is executed to perform an area integral based on the horizontal net flux of all grids in the second integral region. Specifically, the horizontal net flux D is converted into the total emission E (kg / hr) of the point source, and a spatial integral is performed on the given second integral region, and the formula is applied:

[0120]

[0121] Based on the integration result, the point source methane emission of the methane emission point source in the gridded monitoring area is obtained;

[0122] Wherein, E is the point source methane emission and D is the horizontal net flux.

[0123] In some embodiments, considering that the column concentration is actually determined by X CH4 The number of moles of air in the column V based on the surface pressure of the HRRR air Calculate and apply the formula:

[0124]

[0125] In some embodiments, considering the influence of the methane background concentration flux of each grid in the second integration area on the horizontal net flux, a first-order linear correction is required for the horizontal net flux of each grid.

[0126] Specifically, the correlation coefficient between the methane background concentration flux and the horizontal net flux in the second integral region is calculated using the formula:

[0127]

[0128] If the correlation coefficient If it is greater than 0, the horizontal net flux is corrected and the formula is applied:

[0129]

[0130] After the correction, the step S105 is executed to perform surface integration in the second integral region and output the point source methane emission of the methane emission point source in the gridded monitoring area, including:

[0131] Performing surface integration based on the corrected horizontal net flux, outputting point source methane emissions of methane emission point sources in the rasterized monitoring area;

[0132] Among them, DCH4 is the horizontal net flux before correction in the second integration region, is the methane background concentration flux in the second integral region, D CH4 ′ is the corrected horizontal net flux.

[0133] In some embodiments, if the correlation coefficient is less than or equal to 0, it indicates that the impact of background emissions on point source emissions in the corresponding area is negligible, and no correction is required. Based on the horizontal net flux D before correction, CH4 Execute step S105.

[0134] Based on the above embodiments, the embodiment of the present application performs an area integral on the corrected horizontal net flux in the optimized second integral region, so that the impact of the background concentration flux and the wind divergence flux on the point source emissions is globally minimized in the second integral region, and the impact of the background methane concentration is completely removed by a first-order linear correction. Therefore, in the second integral region optimized by the present application, it can be considered that the horizontal instantaneous net flux is completely derived from the new methane emissions from the point source, and the most accurate emission estimate can be obtained under the premise of global optimization.

[0135] In some embodiments, the present application obtains the real-time methane emissions of the point source through steps S101-S105, and can further measure the methane emissions of the monitored point source at each moment based on the monitoring data at multiple moments, and then output the methane emission time series of the point source, thereby reflecting the changes in the emissions of the point source, with good real-time performance, and can monitor the emission changes of each point source in real time and accurately.

[0136] The following are device embodiments of the present application, which can be used to execute the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0137] See next Figure 2 , is a schematic diagram of the structure of a point source methane emission flux real-time monitoring device provided by an exemplary embodiment of the present application. The device can be implemented as all or part of a terminal through software, hardware, or a combination of both, and can also be integrated on a server as an independent module. The point source methane emission flux real-time monitoring device in the embodiment of the present application can be applied to a terminal or a cloud. The device 20 includes a data acquisition module 210, a horizontal net flux calculation module 220, an integral area calculation module 230, and a point source methane emission calculation module 240, wherein:

[0138] The data acquisition module 210 is used to acquire methane column concentration data in the gridded monitoring area;

[0139] The horizontal net flux calculation module 220 is used to perform gradient calculation based on the methane column concentration data of each grid to obtain the gradient of the corresponding grid, and generate the horizontal net flux of each grid based on the gradient and the real-time wind field vector data;

[0140] The integral region calculation module 230 is used to extract the plume coverage area of ​​the rasterized monitoring area, and determine the first integral region based on the plume coverage area;

[0141] The integral region calculation module 230 is further used to obtain a second integral region that meets the constraint condition according to the first integral region; wherein the constraint condition is determined based on the methane background concentration flux and the wind divergence flux in the first integral region;

[0142] The point source methane emission calculation module 240 is used to perform surface integration in the second integral area and output the point source methane emission of the methane emission point source in the gridded monitoring area.

[0143] It should be noted that the device 20 provided in the above embodiment only uses the division of the above functional modules as an example when executing the point source methane emission flux real-time monitoring method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device provided in the above embodiment and the embodiment of the point source methane emission flux real-time monitoring method belong to the same concept, and its implementation process is detailed in the method embodiment, which will not be repeated here.

[0144] An embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the above-mentioned method embodiments when executing the program.

[0145] See also Figure 3 , which is a structural block diagram of an electronic device provided in an embodiment of the present application.

[0146] like Figure 3 As shown, the electronic device 300 includes: a processor 301 and a memory 302 .

[0147] In the embodiment of the present application, the processor 301 is the control center of the computer system, which can be a processor of a physical machine or a processor of a virtual machine. The processor 301 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 301 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array).

[0148] The processor 301 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also called a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state.

[0149] The memory 302 may include one or more computer-readable storage media, which may be non-transitory. The memory 302 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments of the present application, the non-transitory computer-readable storage medium in the memory 302 is used to store at least one instruction, which is used to be executed by the processor 301 to implement the method in the embodiment of the present application.

[0150] In some embodiments, the electronic device 300 further includes: a peripheral device interface 303 and at least one peripheral device 304. The processor 301, the memory 302 and the peripheral device interface 303 can be connected via a bus or a signal line. Each peripheral device 304 can be connected to the peripheral device interface 303 via a bus, a signal line or a circuit board. Specifically, the peripheral device 304 includes: a display screen, a camera and an audio circuit. The peripheral device interface 303 can be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 301 and the memory 302.

[0151] In some embodiments of the present application, the processor 301, the memory 302, and the peripheral device interface 303 are integrated on the same chip or circuit board; in some other embodiments of the present application, any one or two of the processor 301, the memory 302, and the peripheral device interface 303 can be implemented on a separate chip or circuit board. This embodiment of the present application does not specifically limit this.

[0152] The electronic device structure block diagram shown in the embodiment of the present application does not constitute a limitation on the electronic device 300. The electronic device 300 may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0153] The embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method of any of the above embodiments are implemented. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a micro drive, and a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0154] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution can be essentially or in other words, the part that contributes to the relevant technology can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiment.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for real-time monitoring of point source methane emission flux, characterized in that: include: Obtain methane column concentration data in the gridded monitoring area; Performing gradient calculations based on the methane column concentration data of each grid to obtain the gradient of the corresponding grid, and generating the horizontal net flux of each grid based on the gradient and the real-time wind field vector data; Extracting a plume coverage area of ​​the rasterized monitoring area, and determining a first integral area based on the plume coverage area; Based on the first integral region, a second integral region that meets the constraint condition is obtained; wherein the constraint condition is determined based on the methane background concentration flux and the wind divergence flux in the first integral region; Surface integration is performed in the second integral region to output the point source methane emissions of the methane emission point sources in the gridded monitoring area.

2. A method for real-time monitoring of point source methane emission flux according to claim 1, characterized in that: The step of performing gradient calculation based on the methane column concentration data of each grid to obtain the gradient of the corresponding grid, and generating the horizontal net flux of each grid based on the gradient and the real-time wind field vector data, comprises: The gradient of the methane column concentration data of each grid is calculated, and the gradient is multiplied by the wind vector of the real-time wind field vector data to obtain the horizontal net flux of each grid, and the formula is applied: Among them, V CH4 For the methane column concentration data of each grid, is the gradient operator, is the x-component of the wind vector and D is the horizontal net flux for each of the grids.

3. A method for real-time monitoring of point source methane emission flux according to claim 2, characterized in that: Before generating the horizontal net flux of each grid based on the gradient and wind field vector data, the method further includes: Obtain real-time wind field vector data; Difference calculation is performed based on the real-time wind field vector data, and the accuracy difference of the wind vector is set to the same accuracy as the rasterized monitoring area.

4. The method for real-time monitoring of point source methane emission flux according to claim 1, characterized in that: The extracting and obtaining the plume coverage area of ​​the rasterized monitoring area, and determining and obtaining the first integral area based on the plume coverage area, include: The difference between the methane column concentration data of each grid in the gridded monitoring area and the corresponding methane background concentration is calculated based on the KW test algorithm. If the difference is less than or equal to a preset test threshold, the corresponding grid is excluded; otherwise, the corresponding grid is retained, and the plume coverage area is extracted based on all the retained grids; Determine an endpoint of the plume coverage area along the plume direction in the plume coverage area and an endpoint of the plume coverage area at a preset distance opposite to the plume direction, determine an integral endpoint of the first integral area based on the plume coverage area endpoint, and obtain the first integral area based on the integral endpoint.

5. The method for real-time monitoring of point source methane emission flux according to claim 1, characterized in that: The constraints include: in, is the methane background concentration in the second integral region, X Ch4 is the methane column concentration data in the second integral region, V air is the density of the air column, M CH4 is the number of moles of methane, is the gradient operator, is the methane background concentration flux, is the wind divergence flux.

6. A method for real-time monitoring of point source methane emission flux according to claim 2, characterized in that: The performing of surface integration in the second integral region to output the point source methane emission of the methane emission point source in the gridded monitoring area includes: Perform surface integration based on the horizontal net flux of all grids in the second integration area, applying the formula: Based on the integration result, the point source methane emission of the methane emission point source in the gridded monitoring area is obtained; Wherein, E is the point source methane emission and D is the horizontal net flux.

7. A method for real-time monitoring of point source methane emission flux according to claim 6, characterized in that: Before performing surface integration in the second integral region and outputting the point source methane emission of the methane emission point source in the rasterized monitoring area, the method further includes: Calculate the correlation coefficient between the background concentration flux of methane and the horizontal net flux in the second integration region, using the formula: If the correlation coefficient If it is greater than 0, the horizontal net flux is corrected and the formula is applied: The performing of surface integration in the second integral region to output the point source methane emission of the methane emission point source in the gridded monitoring area includes: Performing surface integration based on the corrected horizontal net flux, outputting point source methane emissions of methane emission point sources in the rasterized monitoring area; Among them, D CH4 is the horizontal net flux before correction in the second integration region, is the methane background concentration flux in the second integration region, D CH4 ′ is the corrected horizontal net flux.

8. A real-time monitoring device for point source methane emission flux, characterized in that: include: A data acquisition module, used to acquire methane column concentration data in a gridded monitoring area; A horizontal net flux calculation module, used to perform gradient calculation based on the methane column concentration data of each grid to obtain the gradient of the corresponding grid, and generate the horizontal net flux of each grid based on the gradient and real-time wind field vector data; An integral region calculation module, used for extracting a plume coverage area of ​​the rasterized monitoring area, and determining a first integral region based on the plume coverage area; The integral region calculation module is further used to obtain a second integral region that meets the constraint condition according to the first integral region; wherein the constraint condition is determined based on the methane background concentration flux and the wind divergence flux in the first integral region; The point source methane emission calculation module is used to perform surface integration in the second integral area and output the point source methane emission of the methane emission point source in the rasterized monitoring area.

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

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

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