A regional carbon emission monitoring method, device, equipment and storage medium

Abstract

The application provides a regional carbon emission monitoring method and device, electronic equipment, computer program and storage medium, wherein the method comprises: obtaining regional environmental measurement data; constructing an edge surface fitting model according to the geographic position data to obtain a measurement edge surface; calculating the gas flow of the measurement edge surface according to the meteorological data and the measurement edge surface, wherein the gas flow comprises gas inflow and gas outflow; and calculating the carbon emission of the current measurement region according to the gas flow of the measurement edge surface. The number of sampling points can be freely controlled, which is suitable for various types and conditions of emission sources. When sampling and monitoring the whole region, multiple predictions can be made to improve the accuracy and robustness of the results. Meanwhile, the edge sampling method can quickly obtain the carbon emission prediction value, reduce the endurance requirement of the unmanned aerial vehicle, and improve the monitoring efficiency.

Description

Technical Field

[0001] This application relates to the field of environmental monitoring technology, and in particular to a method, apparatus, equipment, computer product, and storage medium for monitoring regional carbon emissions. Background Technology

[0002] Global greenhouse gas emissions are continuously increasing, causing serious environmental impacts. Monitoring greenhouse gas emissions has become a crucial task for global environmental protection. Traditional monitoring methods mainly rely on ground-based observation stations and satellite remote sensing, but these suffer from limitations such as narrow monitoring range, insufficient periodicity, and poor data timeliness. In recent years, the rapid development of unmanned aerial vehicle (UAV) technology has provided new possibilities for atmospheric monitoring. UAVs can quickly and flexibly acquire air quality data over large areas and conduct multi-dimensional observations at different altitudes and locations, providing more comprehensive data support for greenhouse gas monitoring. Existing UAV technology mainly focuses on monitoring stationary emission sources, typically employing flight plans covering the entire region or targeting key areas to obtain the gas concentration distribution and airflow conditions within the region. Emissions are then calculated using inversion methods.

[0003] However, existing drone monitoring technologies still have many shortcomings and deficiencies:

[0004] 1. It requires a large number of regional flights, which increases the complexity of monitoring and the difficulty of operation;

[0005] 2. The limited flight time of drones restricts their ability to operate over large areas;

[0006] 3. It places high demands on the inversion algorithm, requiring high-precision data and complex data processing algorithms, which increases the difficulty and cost of technical implementation;

[0007] 4. For unorganized emission sources, it is difficult to quickly obtain regional emissions using a Gaussian diffusion model for stationary sources. Summary of the Invention

[0008] Based on the technical problems raised in the background art, the present invention provides a method, device, computer product and storage medium for monitoring regional carbon emissions, which can significantly reduce the number of flight measurement points and improve the robustness and accuracy of the inversion algorithm, thereby enabling more effective monitoring and measurement of greenhouse gas emissions.

[0009] In a first aspect, the present invention provides a method for monitoring regional carbon emissions, comprising:

[0010] Acquire regional environmental measurement data, which includes geographic location data and meteorological data;

[0011] Based on the geographic location data, an edge surface fitting model is constructed to obtain the measured edge surface;

[0012] Based on the meteorological data and the measured edge surface, the gas flow rate of the measured edge surface is calculated, wherein the gas flow rate includes the gas inflow rate and the gas outflow rate;

[0013] The carbon emissions of the current measurement area are calculated based on the gas flow rate at the measured edge surface.

[0014] Further, the step of constructing an edge surface fitting model based on the geographic location data to obtain the measured edge surface includes:

[0015] The geographic location data is preprocessed to obtain the data to be fitted, wherein the data preprocessing method includes a default value processing method and a spatial interpolation method;

[0016] The data to be fitted is fitted using a pre-defined fitting algorithm to obtain a fitted surface, which is then identified as the measurement edge surface. The pre-defined fitting algorithm includes a linear interpolation fitting algorithm and a nonlinear fitting algorithm.

[0017] Further, the step of calculating the gas flow rate at the measuring edge surface based on the meteorological data and the measuring edge surface includes:

[0018] Based on the meteorological data, the gas concentration and wind speed data of the measurement edge surface are obtained;

[0019] Based on the gas concentration and wind speed data, the gas inflow and outflow at the measurement edge are calculated using atmospheric dynamics principles and mass balance equations.

[0020] The net outflow of the measured edge surface is obtained by the difference between the gas inflow and the gas outflow.

[0021] Furthermore, the acquisition of regional environmental measurement data includes:

[0022] Environmental measurement data of the area is acquired by a drone, wherein the drone is configured to fly along the edge of the carbon emission source area and collect data.

[0023] Furthermore, the acquisition of regional environmental measurement data includes:

[0024] Environmental measurement data of the area is acquired by a drone, wherein the drone is configured to fly across the entire area of ​​the carbon emission source region and collect data.

[0025] Furthermore, the step of calculating the carbon emissions of the current measurement area based on the gas flow rate at the measurement edge surface also includes:

[0026] Obtain the net outflow at each measured edge surface;

[0027] Obtain the weight of each measurement edge surface, and calculate the carbon emissions of the current measurement area based on the net outflow of the measurement edge and its corresponding weight. The weight of the measurement edge surface is inversely proportional to the distance between the measurement edge surface and the carbon emission source.

[0028] Secondly, the present invention also provides a regional carbon emission monitoring device, comprising:

[0029] The data acquisition module is used to acquire regional environmental measurement data, which includes geographic location data and meteorological data.

[0030] The edge surface fitting module is used to construct an edge surface fitting model based on the geographic location data to obtain the measured edge surface;

[0031] A gas flow acquisition module is used to calculate the gas flow rate of the measuring edge surface based on the meteorological data and the measuring edge surface, wherein the gas flow rate includes gas inflow and gas outflow.

[0032] The carbon emission acquisition module is used to calculate the carbon emission of the current measurement area based on the gas flow rate of the measurement edge surface.

[0033] Thirdly, the present invention also provides a computer device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the regional carbon emission monitoring method as described in the first aspect.

[0034] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program that, when the computer program is executed, controls the device on which the computer-readable storage medium is located to perform the regional carbon emission monitoring method as described in the first aspect.

[0035] Fifthly, the present invention also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the regional carbon emission monitoring method as described in the first aspect.

[0036] This invention acquires regional environmental measurement data, including geographic location data and meteorological data; based on the geographic location data, it constructs an edge surface fitting model to obtain a measurement edge surface; based on the meteorological data and the measurement edge surface, it calculates the gas flow rate of the measurement edge surface, wherein the gas flow rate includes gas inflow and gas outflow; based on the gas flow rate of the measurement edge surface, it calculates the carbon emissions of the current measurement area. The number of sampling points in this invention is freely controllable, applicable to various emission source types and situations. Multiple predictions can be performed when sampling and monitoring the entire area to improve the accuracy and robustness of the results. Furthermore, the edge sampling method described in this invention can obtain carbon emission prediction values ​​more quickly, reducing the endurance requirements of drones and improving monitoring efficiency.

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Attached Figure Description

[0038] Figure 1 A flowchart illustrating the steps of a regional carbon emission monitoring method provided in an exemplary embodiment;

[0039] Figure 2 A point cloud diagram of data collected by a drone in an exemplary embodiment of a regional carbon emission monitoring method.

[0040] Figure 3 This is a schematic diagram illustrating an application scenario of a regional carbon emission monitoring method provided in an exemplary embodiment.

[0041] Figure 4 This is a schematic diagram of a module for a regional carbon emission monitoring device provided in an exemplary embodiment;

[0042] Figure 5 This is an internal structure diagram of a computer device configured as a server, provided in one exemplary embodiment.

[0043] Figure 6 This is an internal structure diagram of a computer device configured as a terminal, provided in one exemplary embodiment. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0045] It should be understood that the described embodiments are merely some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of the embodiments of this application.

[0046] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the embodiments of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0047] In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims. In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0048] Furthermore, in the description of this application, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0049] Based on the technical problems mentioned in the background section, this application provides a method for monitoring regional carbon emissions, such as... Figure 1 As shown, the method includes the following steps:

[0050] S201: Obtain regional environmental measurement data, which includes geographical location data and meteorological data.

[0051] In this embodiment, a drone is controlled to fly over the area to be measured, and a sampling frequency is set to acquire measurement data corresponding to each sampling point. The environmental measurement data collected by the drone is generally point cloud data including coordinates, gas concentration, three-dimensional wind speed, temperature, air pressure, and time. Specifically, based on the application environment of carbon emission monitoring in this application, the gas concentration is generally the concentration of carbon dioxide or methane at the sampling point. In actual measurement, this gas concentration is measured and acquired by a gas sensor carried by the drone. Meanwhile, information such as temperature, air pressure, and wind speed can also be acquired using meteorological instruments carried by the drone, such as temperature, humidity, air pressure, and wind speed measuring instruments.

[0052] S202: Based on the geographical location data, construct an edge surface fitting model to obtain the measured edge surface.

[0053] Specifically, the data obtained by drone sampling is represented by multiple sampling points in space. However, it is obviously impossible to calculate carbon emissions using this type of data. Therefore, a curved surface in the measurement area is fitted based on the spatial coordinates of the sampling points, and this curved surface is used as the measurement edge surface. After obtaining the spatial information, the gas flow rate through this surface can be determined.

[0054] In a preferred embodiment, the method for obtaining the measured edge surface includes:

[0055] The geographic location data is preprocessed to obtain the data to be fitted, wherein the data preprocessing method includes a default value processing method and a spatial interpolation method;

[0056] The data to be fitted is fitted using a pre-defined fitting algorithm to obtain a fitted surface, which is then identified as the measurement edge surface. The pre-defined fitting algorithm includes a linear interpolation fitting algorithm and a nonlinear fitting algorithm.

[0057] In this embodiment, the sampling frequency of the UAV is set to 1 time / s, and the flight speed is approximately 1.5 m / s. This means that during the UAV's data collection process, there will be a large number of blank areas between points, where the environmental measurement data is unknown. However, the measurement accuracy can be improved through default value processing and spatial interpolation methods. Specifically, spatial interpolation is based on the assumption that spatially distributed ground features are spatially correlated, and that nearby ground features have similar attributes. Therefore, in this application, spatial interpolation processing is performed on the blank areas based on the statistical regularity of the measurement data and data from nearby sampling points to improve measurement accuracy. Alternatively, the default value processing method can be used to represent the measurement data of the surrounding space of the sampling point, thereby improving measurement accuracy.

[0058] Linear interpolation fitting is a common data fitting method used to estimate unknown values ​​between a set of data points. This algorithm assumes that the relationship between the data can be approximated by a straight line. In this embodiment, two known sampling points are acquired, and the equation of a spatial straight line is determined using these two points. Then, the values ​​of the unknown area points are calculated based on the required interpolation location, and the edge surface is fitted and measured based on the interpolated result.

[0059] Since this application requires fitting a surface in space, a nonlinear fitting method can also be used to obtain the fitted surface. A nonlinear fitting algorithm is a method for fitting nonlinear relational data. Unlike linear fitting, nonlinear fitting can adapt to more complex data patterns, including the surface data in this application. Common nonlinear fitting algorithms include, but are not limited to: least squares (Levenberg-Marquardt algorithm), Gaussian Process Regression (GPR), Artificial Neural Networks (ANNs) pre-trained for surface fitting, decision trees and random forest algorithms, spline interpolation algorithms, etc.

[0060] like Figure 3 As shown, Figure 3 This is a schematic diagram of the measured edge surface fitted in an exemplary example.

[0061] S203: Calculate the gas flow rate of the measuring edge surface based on the meteorological data and the measuring edge surface, wherein the gas flow rate includes the gas inflow rate and the gas outflow rate.

[0062] In a preferred example, calculating the gas flow rate at the measuring edge includes:

[0063] Based on the meteorological data, the gas concentration and wind speed data of the measurement edge surface are obtained; based on the gas concentration and wind speed data, the gas inflow and gas outflow of the measurement edge surface are calculated using atmospheric dynamics principles and mass balance equations; the net outflow of the measurement edge surface is obtained by the difference between the gas inflow and gas outflow.

[0064] S204: Calculate the carbon emissions of the current measurement area based on the gas flow rate at the measured edge surface.

[0065] In a preferred example, the carbon emissions for the current measurement area are calculated as follows:

[0066] Obtain the net outflow at each measured edge surface;

[0067] Obtain the weight of each measurement edge surface, and calculate the carbon emissions of the current measurement area based on the net outflow of the measurement edge and its corresponding weight. The weight of the measurement edge surface is inversely proportional to the distance between the measurement edge surface and the carbon emission source.

[0068] Specifically, in the measurement process of this application, multiple measurement edge surfaces can be fitted, and different weights are assigned to each edge surface based on its position. Since the measurement edge surface closer to the carbon emission source is more representative of the carbon emission level, and due to objective phenomena such as sedimentation absorption and near-surface outflow, the accuracy of measurement locations farther from the carbon emission source is lower. Therefore, the measurement edge surface closer to the carbon emission source has a higher weight, and conversely, the measurement edge surface farther from the carbon emission source has a lower weight. It should be noted that for fugitive carbon emissions, since the location of the carbon emission source cannot be determined, setting weights is meaningless in this case. Figure 3 As shown, Figure 3 The location indicated by the chimney represents the carbon emission source, and the curve indicates the measurement edge surface. The inner curve, that is, the curve closer to the chimney, represents the measurement edge surface, which will be assigned a higher calculation weight, while the outer curve, that is, the curve farther away from the chimney, represents the measurement edge surface, which will be assigned a lower calculation weight.

[0069] In a preferred example, environmental measurement data of the area is acquired by a drone, wherein the drone is configured to fly along the edge of the carbon emission source area and collect data.

[0070] The measurement process will be illustrated below through a specific implementation scenario.

[0071] A pre-set drone flight path is used to control the drone to fly to the edge of the area to be monitored and collect regional environmental data at that edge. After acquiring the regional environmental data at the edge, the data on the edge surface is fitted based on the collected gas concentration and wind speed data to obtain the gas concentration and wind speed distribution on the monitored boundary. Then, the flow rate is calculated for each individual area, and the total gas outflow is obtained after integrating the flow rate for each area. Finally, the total gas outflow is converted according to the local air density to obtain the carbon emissions at the monitored boundary. The surface fitted to the monitored boundary is used as the measurement edge surface, and its carbon emissions represent the carbon emission level in that area.

[0072] In a preferred example, environmental measurement data of the area is acquired by a drone, wherein the drone is configured to fly across the entire area of ​​the carbon emission source region and collect data.

[0073] The measurement process will be illustrated below through a specific implementation scenario.

[0074] A pre-set drone flight path is used to control the drone to perform overall sampling of the entire area to be monitored. After acquiring regional environmental data for the entire area, data from multiple edge surfaces are fitted based on the collected gas concentration and wind speed data. Then, flow rate is calculated for each individual area of ​​each edge surface, and the total gas outflow from each edge surface is obtained by integrating the flow rate of each individual area. Finally, the total outflow from each edge surface is weighted and averaged to obtain a more accurate regional carbon emission level.

[0075] This application proposes a method for monitoring regional carbon emissions. The method involves acquiring regional environmental measurement data; constructing an edge surface fitting model based on the geographic location data to obtain a measurement edge surface; calculating the gas flow rate of the measurement edge surface based on meteorological data and the measurement edge surface, wherein the gas flow rate includes gas inflow and gas outflow; and calculating the carbon emissions of the current measurement area based on the gas flow rate of the measurement edge surface. The number of sampling points in this invention is freely controllable, applicable to various emission source types and situations. Multiple predictions can be performed when monitoring the entire region to improve the accuracy and robustness of the results. Furthermore, the edge sampling method described in this invention can obtain carbon emission prediction values ​​more quickly, reducing the endurance requirements of drones and improving monitoring efficiency.

[0076] This application also provides a regional carbon emission monitoring device 300, such as... Figure 4 As shown, it includes:

[0077] Data acquisition module 301 is used to acquire regional environmental measurement data, which includes geographical location data and meteorological data;

[0078] The edge surface fitting module 302 is used to construct an edge surface fitting model based on the geographic location data to obtain the measured edge surface;

[0079] The gas flow acquisition module 303 is used to calculate the gas flow rate of the measuring edge surface based on the meteorological data and the measuring edge surface, wherein the gas flow rate includes the gas inflow rate and the gas outflow rate;

[0080] The carbon emission acquisition module 304 is used to calculate the carbon emission of the current measurement area based on the gas flow rate of the measurement edge surface.

[0081] It should be noted that both a regional carbon emission monitoring device and a regional carbon emission monitoring method originate from the same inventive concept. For a related explanation of the regional carbon emission monitoring device, please refer to the embodiments in the regional carbon emission monitoring method, which will not be repeated here.

[0082] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network. When executed by the processor, the computer program implements a method for monitoring regional carbon emissions.

[0083] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for monitoring regional carbon emissions. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0084] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a regional carbon emission monitoring method as described in any of the above embodiments.

[0085] This invention can take the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to: phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0086] This application also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of a regional carbon emission monitoring method described in any of the above embodiments.

[0087] It should be understood that the embodiments of this application are not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from their scope. The scope of the embodiments of this application is limited only by the appended claims.

[0088] The above-described embodiments are merely illustrative of several implementation methods of the embodiments of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the embodiments of this application, and these all fall within the protection scope of the embodiments of this application.

Claims

1. A method for monitoring regional carbon emissions, characterized in that, include: Acquire regional environmental measurement data, which includes geographic location data and meteorological data; Based on the geographic location data, an edge surface fitting model is constructed to obtain the measured edge surface; Based on the meteorological data and the measured edge surface, the gas flow rate of the measured edge surface is calculated, wherein the gas flow rate includes the gas inflow rate and the gas outflow rate; Calculate the carbon emissions of the current measurement area based on the gas flow rate at the measured edge surface; The step of constructing an edge surface fitting model based on the geographic location data to obtain the measured edge surface includes: The geographic location data is preprocessed to obtain the data to be fitted, wherein the data preprocessing method includes a default value processing method and a spatial interpolation method; The data to be fitted is fitted using a pre-defined fitting algorithm to obtain a fitted surface, and the fitted surface is identified as the measured edge surface. The pre-defined fitting algorithm includes a linear interpolation fitting algorithm and a nonlinear fitting algorithm. The step of calculating the gas flow rate at the measuring edge surface based on the meteorological data and the measuring edge surface includes: Based on the meteorological data, the gas concentration and wind speed data of the measurement edge surface are obtained; Based on the gas concentration and wind speed data, the gas inflow and outflow at the measurement edge are calculated using atmospheric dynamics principles and mass balance equations. The net outflow of the measured edge surface is obtained by the difference between the gas inflow and the gas outflow. The acquisition of regional environmental measurement data includes: Environmental measurement data of the area is acquired by a drone, wherein the drone is configured to fly along the edge of the carbon emission source area and collect data; The step of calculating the carbon emissions of the current measurement area based on the gas flow rate at the measurement edge surface also includes: Obtain the net outflow at each measured edge surface; Obtain the weight of each measurement edge surface, and calculate the carbon emissions of the current measurement area based on the net outflow of the measurement edge and its corresponding weight. The weight of the measurement edge surface is inversely proportional to the distance between the measurement edge surface and the carbon emission source.

2. The regional carbon emission monitoring method according to claim 1, characterized in that, The acquisition of regional environmental measurement data includes: Environmental measurement data of the area is acquired by a drone, wherein the drone is configured to fly across the entire area of ​​the carbon emission source region and collect data.

3. A regional carbon emission monitoring device, characterized in that, include: The data acquisition module is used to acquire regional environmental measurement data, which includes geographic location data and meteorological data. The edge surface fitting module is used to construct an edge surface fitting model based on the geographic location data to obtain the measured edge surface; A gas flow acquisition module is used to calculate the gas flow rate of the measuring edge surface based on the meteorological data and the measuring edge surface, wherein the gas flow rate includes gas inflow and gas outflow. The carbon emission acquisition module is used to calculate the carbon emission of the current measurement area based on the gas flow rate of the measurement edge surface; The edge surface fitting module is also used for: The geographic location data is preprocessed to obtain the data to be fitted, wherein the data preprocessing method includes a default value processing method and a spatial interpolation method; The data to be fitted is fitted using a pre-defined fitting algorithm to obtain a fitted surface, and the fitted surface is identified as the measured edge surface. The pre-defined fitting algorithm includes a linear interpolation fitting algorithm and a nonlinear fitting algorithm. The gas flow rate acquisition module is also used for: Based on the meteorological data, the gas concentration and wind speed data of the measurement edge surface are obtained; Based on the gas concentration and wind speed data, the gas inflow and outflow at the measurement edge are calculated using atmospheric dynamics principles and mass balance equations. The net outflow of the measured edge surface is obtained by the difference between the gas inflow and the gas outflow. The data acquisition module is also used for: Environmental measurement data of the area is acquired by a drone, wherein the drone is configured to fly along the edge of the carbon emission source area and collect data; The carbon emission acquisition module is also used for: Obtain the net outflow at each measured edge surface; Obtain the weight of each measurement edge surface, and calculate the carbon emissions of the current measurement area based on the net outflow of the measurement edge and its corresponding weight. The weight of the measurement edge surface is inversely proportional to the distance between the measurement edge surface and the carbon emission source.

4. A computer device, characterized in that, The method includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the steps of the regional carbon emission monitoring method according to any one of claims 1 to 2.

5. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when the computer program is executed, controls the device containing the computer-readable storage medium to perform the steps of the regional carbon emission monitoring method as described in any one of claims 1 to 2.

6. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the regional carbon emission monitoring method as described in any one of claims 1 to 2.

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