Industrial park-based carbon emission online monitoring inversion method

Abstract

The invention discloses a carbon emission online monitoring inversion method based on an industrial park, and the method comprises the steps: S1, building a monitoring model according to an industrial park monitoring object; determining the position of an emission source, the position of a monitoring point and a real-time wind direction through the monitoring model; s2, updating the position of the monitoring point in real time according to the real-time wind direction, and confirming an upwind direction monitoring point and a downwind direction monitoring point; s3, calculating a carbon emission concentration value of each emission source to the corresponding downwind monitoring point in combination with the wind speed of each monitoring point; s4, constructing a carbon emission inversion model to calculate the carbon emission; the response relation between the concentration value and the carbon emission is determined by monitoring the concentration value of the carbon emission, online monitoring inversion is achieved, and then the carbon emission in the park is accurately obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon accounting, and more specifically to an inversion method based on online monitoring of carbon emissions in industrial parks. Background Art

[0002] At present, industrial parks mainly use accounting methods to quantify carbon emissions, but with the introduction of the principle of "accounting as the main and monitoring as the auxiliary", monitoring of carbon emissions has gradually become a hot topic.

[0003] At present, the inversion methods for organized carbon emissions monitoring are relatively mature, but the inversion methods for unorganized carbon emissions monitoring are still under continuous exploration. For industrial parks, there is still a lack of a reasonable and accurate online carbon emissions monitoring inversion method.

[0004] According to atmospheric diffusion theory, the carbon emission concentration at a certain location downwind of the emission source is proportional to the carbon emission amount. If the relevant factors affecting the emission are known, the carbon emission amount can be inverted based on the carbon emission concentration at that location. However, the wind direction in the park will change in real time, which will cause the downwind monitoring point of the emission source to change accordingly, making the diffusion process more complicated, greatly affecting the difficulty and accuracy of the inversion.

[0005] Therefore, how to realize the inversion of solar emission monitoring in the park and improve the accuracy of the inversion is an urgent problem to be solved by those skilled in the art. Summary of the invention

[0006] In view of this, the present invention provides an online monitoring inversion method for carbon emissions in an industrial park. By monitoring the concentration values ​​of carbon emissions, the response relationship between the concentration values ​​and the carbon emissions is confirmed, online monitoring inversion is achieved, and the carbon emissions in the park are accurately obtained.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] A method for online monitoring and inversion of carbon emissions in industrial parks is characterized by comprising:

[0009] S1: Construct a monitoring model based on the monitoring objects of the industrial park; confirm the emission source location, monitoring point location and real-time wind direction through the monitoring model;

[0010] S2: updating the position of the monitoring point in real time according to the real-time wind direction, and confirming the upwind detection point and the downwind monitoring point;

[0011] S3: Calculate the carbon emission concentration value of each emission source to the corresponding downwind monitoring point based on the wind speed of each monitoring point;

[0012] S4: Construct a carbon emission inversion model to calculate carbon emissions.

[0013] Preferably, the emission sources include organized carbon emission sources and unorganized emission sources.

[0014] Preferably, S3 specifically includes:

[0015] S31: Calculate the carbon concentration of the organized carbon emission sources diffused to the downwind monitoring point;

[0016] S32: Calculate the carbon concentration of the unorganized carbon emission sources diffused to the downwind monitoring point.

[0017] Preferably, the S31 is specifically as follows: inputting the location of the organized emission source and the location of the downwind monitoring point into a pre-built first diffusion model to obtain the carbon concentration of the organized carbon emission source diffused to the downwind monitoring point; the first diffusion model is:

[0018]

[0019] Among them, C o represents the carbon concentration of the organization’s carbon emission source diffused to the downwind monitoring point, x(P m ), y(P m ), z(P m ) represents the downwind monitoring point P m The position of the monitoring point, μ represents the wind speed at the downwind monitoring point; H represents the effective source height of the carbon emission source, and Q(Ar) represents the intensity of the organized carbon emission source; represents the diffusion coefficient on the y-axis; represents the diffusion coefficient in the z-axis.

[0020] Preferably, the S31 further comprises: monitoring the wind direction, when the position coordinates of the organized carbon emission source are changed from (x(A r ),y(A r ),z(A r )) becomes (x′(A r ),y′(A r ),z′(A r )), the downwind monitoring point position coordinates will be (x(P m ),y(P m ),z(P m )) becomes (x′(P m ),y′(P m ),z′(P m ), then the contribution of the carbon dioxide concentration from the organized carbon dioxide emission sources in the industrial park to the monitoring point downwind of the park is:

[0021]

[0022] Among them, y′(P m )-y′(Ar ) represents the lateral distance from the organized carbon emission source in the park to the downwind monitoring point.

[0023] Preferably, the S32 is specifically:

[0024] Collect the actual carbon emission concentration at the downwind monitoring point;

[0025] Obtain the carbon emission background value measured at the upwind monitoring point;

[0026] The carbon concentration of the unorganized carbon emission source diffused to the downwind monitoring point is obtained by subtracting the carbon emission background value measured at the upwind monitoring point and the carbon concentration of organized carbon emissions to the downwind monitoring point from the actual carbon emission concentration at the downwind monitoring point.

[0027] Preferably, the carbon emission background value adopts the average value of carbon concentrations of all upwind monitoring points.

[0028] Preferably, S4 includes:

[0029] According to the carbon concentration value of each downwind monitoring point combined with the pre-built second diffusion model, the source strength of each unorganized carbon emission source is obtained, and the response relationship coefficient between the unorganized carbon emission source and the concentration value of the monitoring point is obtained;

[0030] The unorganized carbon emissions are calculated based on the source strength and relationship coefficient, and further combined with the organized carbon emissions to obtain the total carbon emissions.

[0031] Preferably, the second diffusion model is:

[0032]

[0033] Among them, C d represents the carbon concentration of the organization’s carbon emission source diffused to the downwind monitoring point, x(P m ), y(P m ), z(P m ) represents the downwind monitoring point P m The position of the monitoring point, μ represents the wind speed at the downwind monitoring point; H represents the effective source height of the carbon emission source; Q(D t ) represents the intensity of organized carbon emission sources; represents the diffusion coefficient on the y-axis; represents the diffusion coefficient in the z-axis.

[0034] Preferably, the S32 further includes: monitoring the wind direction, and the contribution value of the diffusion of the unorganized carbon dioxide emission source to the downwind monitoring point position is:

[0035]

[0036] Among them, (x′(P m),y′(P m ),z′(P m )) is the coordinate of the downwind monitoring point after the wind direction changes.

[0037] It can be seen from the above technical solution that compared with the prior art, the present invention discloses an online monitoring inversion method for carbon emissions in industrial parks, which can confirm the response relationship between concentration values ​​and carbon emissions by monitoring the concentration values ​​of carbon emissions, realize online monitoring inversion, and then accurately obtain the carbon emissions in the park. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0039] Figure 1 A schematic diagram of an inversion method for online monitoring of carbon emissions in industrial parks provided by the present invention.

[0040] Figure 2 It is a schematic diagram of a monitoring model established with a certain industrial park as a monitoring scene in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] The embodiment of the present invention discloses an inversion method based on online monitoring of carbon emissions in an industrial park, comprising the following steps:

[0043] S1: Construct a monitoring model based on the monitoring objects of the industrial park; confirm the emission source location, monitoring point location and real-time wind direction through the monitoring model.

[0044] S2: updating the monitoring point positions in real time according to the real-time wind direction, and confirming the upwind detection points and the downwind monitoring points.

[0045] S3: Calculate the carbon emission concentration value of each emission source for the corresponding downwind monitoring point based on the wind speed of each monitoring point.

[0046] S4: Construct a carbon emission inversion model to calculate carbon emissions.

[0047] Next, each step of this embodiment is described in detail:

[0048] In S1, the present invention constructs a monitoring model according to the actual selected monitoring scene, such as Figure 2 As shown, Figure 2 The monitoring model is established with an industrial park as the monitoring scene. The center of the industrial park is set as the origin O, and the east and north directions of this point are defined as the coordinate system established by the x-axis and y-axis respectively. In this coordinate system, the location of each monitoring point and the location of the emission source are described; including the downwind monitoring point P of the industrial park m (m=1,2,...,M), upwind monitoring point (environmental background carbon concentration monitoring point) P n (n=1,2,...,N), organized carbon emission source A r (r=1,2,...,R), unorganized carbon emission source D t The position coordinates of (t=1,2,...,T). The letters m, n, r, and t represent the number of downwind monitoring points, upwind monitoring points (i.e., environmental background concentration monitoring points), organized carbon emission sources, and unorganized carbon emission sources in the industrial park, respectively; the letters M, N, R, and T represent the total number of downwind monitoring points, upwind monitoring points, organized carbon emission sources, and unorganized carbon emission sources in the industrial park, respectively.

[0049] In addition, the monitoring model can calculate organized carbon emissions by combining various organized carbon emission sources.

[0050] In S2, the monitoring model can update the location of each monitoring point and emission source according to the real-time wind direction; specifically, as the wind direction changes, the coordinate system also changes; therefore, the monitoring model can update the coordinates before the change to the coordinate system coordinates after the change to describe the change in wind direction. At the same time, as the wind direction and the coordinate system change, the type of monitoring point, that is, the upwind monitoring point and the downwind monitoring point, will also change.

[0051] In the present invention, the origin is the center of the industrial park, and the x-axis represents the wind direction. Therefore, the y-axis is used as the boundary between the upwind direction and the downwind direction, thereby realizing the division of the upwind and downwind directions.

[0052] Specifically, the wind direction in the industrial park will change constantly, which is not conducive to determining the location of the downwind monitoring point. Therefore, before determining the location of the downwind monitoring point, it is necessary to first clarify the wind direction angle θ (0°≤θ≤360°). This section proposes a method for determining the location of the industrial park monitoring point. First, based on the online monitoring scenario of carbon emissions in industrial parks built in Section 2.1, the east direction of the coordinate origin (that is, the x-axis of the initial monitoring scenario) is used as the initial wind direction standard axis. If there is a change in wind direction, the wind direction is rotated counterclockwise, and the rotation angle at this time is defined as the wind direction angle θ; then, the wind direction at this time is redefined as the new x-axis. At this time, the y-axis and z-axis will rotate simultaneously by θ° to re-establish the online monitoring scenario. After the rotation, the location coordinates of the organized carbon emission source will be changed from (x(A r ),y(A r ),z(A r )) becomes (x′(A r ),y′(A r ),z′(A r )), the expression is as follows:

[0053]

[0054] At this time, the location of the park monitoring point will be (x(P m ),y(P m ),z(P m )) becomes (x′(P m ),y′(P m ),z′(P m )) to determine the location coordinates of the monitoring point. The expression is as follows:

[0055]

[0056] The following method is used to determine the upwind and downwind monitoring points:

[0057] Assume that a carbon emission source A in the industrial park i , the position coordinates are (x′(A i ),y′(A i ),z′(A i )), there is a monitoring point with the coordinates (x′(P m ),y′(P m ),z′(P m )), when x′(P m )<x′(A i ), the monitoring point is carbon emission source A i The upwind monitoring point; when x′(P m )>x′(A i ), the monitoring point is carbon emission source A iTherefore, when x′(P m ) is less than the horizontal coordinates of all carbon emission sources in the online monitoring scene, the coordinate point (x′(P m ),y′(P m ),z′(P m )) is determined as the upwind monitoring point of the online monitoring scene; when x′(P m ) is greater than the horizontal coordinate of the carbon emission source in the online monitoring scene, the coordinate point (x′(P m ),y′(P m ),z′(P m )) was identified as the downwind monitoring point in the online monitoring scenario.

[0058] In S3, in order to realize the inversion of unorganized carbon emissions, it is necessary to confirm the diffusion model of organized carbon emissions and the diffusion model of unorganized carbon emissions respectively, and confirm the contribution relationship of organized carbon emissions and unorganized carbon emissions to the downwind monitoring points through the diffusion model.

[0059] In actual calculations, the actual contribution of unorganized carbon emissions to the downwind monitoring points can be obtained by combining the forward diffusion results of organized carbon emissions and the carbon emission background values ​​measured at the upwind monitoring points. The carbon emission inversion model is then used to further confirm the source strength of each unorganized carbon emission source and the proportional relationship of its contribution to different downwind monitoring points.

[0060] Specifically, for the forward diffusion of organized carbon emissions, the present invention adopts a Gaussian plume model for an elevated point source as the first diffusion model.

[0061] Based on the monitoring scenarios and monitoring models confirmed in S1, determine the specific location of the organized carbon emission source A r (r=1,2,...,R). Then there is an organized carbon emission source A r Spread to the downwind monitoring point P m (x(P m ),y(P m ),z(P m )) Carbon concentration C o for:

[0062]

[0063] Among them, C o represents the carbon concentration of the organization’s carbon emission source diffused to the downwind monitoring point, x(P m ), y(P m ), z(P m ) represents the downwind monitoring point P m The position of the monitoring point, μ represents the wind speed at the downwind monitoring point; H represents the effective source height of the carbon emission source, and Q(Ar) represents the intensity of the organized carbon emission source; represents the diffusion coefficient on the y-axis; represents the diffusion coefficient in the z-axis.

[0064] Furthermore, when the wind direction of the park changes, the Cartesian coordinate system is re-established with the center of the park as the origin. At this time, the coordinates of the location of the organized carbon emission source will be changed from (x(A r ),y(A r ),z(A r )) becomes (x′(A r ),y′(A r ),z′(A r )), the downwind monitoring point position coordinates will be (x(P m ),y(P m ),z(P m )) becomes (x′(P m ),y′(P m ),z′(P m ), then the contribution of the carbon dioxide concentration from the organized carbon dioxide emission sources in the industrial park to the monitoring point downwind of the park is:

[0065]

[0066] Among them, y′(P m )-y′(A r ) represents the lateral distance from the organized carbon emission source in the park to the downwind monitoring point, and It represents the diffusion coefficient in the y-axis direction and the diffusion coefficient in the z-axis direction in the new coordinate system after the wind direction changes.

[0067] For the concentration contribution of unorganized carbon emissions, the present invention adopts the difference method to calculate. The carbon dioxide concentration at the downwind monitoring point of the industrial park consists of three parts, namely the upwind background concentration value of carbon dioxide emissions, the contribution of organized carbon emission sources to the downwind monitoring point, and the contribution of unorganized carbon emission sources to the downwind monitoring point. Therefore, the concentration contribution C of the unorganized carbon emission sources in the industrial park to the downwind monitoring point is d It can be expressed as follows:

[0068] C d =C a -C o -C b

[0069] Among them, C a represents the carbon emission concentration detected at the downwind monitoring point, C o Indicates the carbon concentration of organized carbon emissions to the downwind monitoring point, C b Represents the background value of carbon emissions measured at the upwind monitoring point.

[0070] Furthermore, in order to reduce the error, the background value of carbon emissions in the industrial park adopts the average value of carbon concentrations at all upwind monitoring points, which is expressed as follows:

[0071]

[0072] Where w is the number of upwind monitoring points.

[0073] In addition, for the diffusion of unorganized carbon emissions, the present invention adopts a ground continuous Gaussian plume diffusion model as the second diffusion model.

[0074] Based on the monitoring scenarios and monitoring models in S1, the specific location of the unorganized carbon emission source can be confirmed. t (t=1,2,...,T). Then it spreads to the downwind monitoring point P m (x(P m ),y(P m ),z(P m )) Organized carbon emission sources D t The carbon dioxide concentration C d for:

[0075]

[0076] Among them, C d represents the carbon concentration of the organization’s carbon emission source diffused to the downwind monitoring point, x(P m ), y(P m ), z(P m ) represents the downwind monitoring point P m The position of the monitoring point, μ represents the wind speed at the downwind monitoring point; H represents the effective source height of the carbon emission source; Q(D t ) represents the intensity of organized carbon emission sources; represents the diffusion coefficient on the y-axis, represents the initial diffusion coefficient on the y-axis; represents the diffusion coefficient in the z-axis, represents the initial diffusion coefficient in the z-axis.

[0077]

[0078] Where l represents the length of the fugitive emission source in the y direction.

[0079] Furthermore, when the wind direction in the industrial park changes, the coordinates of the downwind monitoring point will change from (x(P m ),y(P m ),z(P m )) becomes (x′(P m ),y′(P m ),z′(P m), then the calculated carbon concentration of the unorganized carbon emission source diffused to the monitoring point downwind of the park is:

[0080]

[0081] In S4, the present invention inverts the unorganized carbon emissions and determines the total emissions.

[0082] Specifically, it is assumed that there are G total carbon emission sources in the industrial park, and W monitoring points are set in the park. The variation coefficient K is introduced, which reflects the response relationship between a carbon emission source in the industrial park and the concentration value of the monitoring point. The unorganized carbon emission concentration data of each downwind monitoring point is the superposition of the carbon concentration contributed by each unorganized carbon emission source. The contribution of G carbon emission sources to the carbon emission concentration of W monitoring points at the same time can be described by the following formula:

[0083] Q d K=C d

[0084] Where Q d Represents the carbon emissions of each unorganized carbon emission source; C d It represents the carbon concentration of unorganized emissions at each monitoring point. The calculation formula of the coefficient of variation K is:

[0085]

[0086] Expanding into matrix form, we get:

[0087]

[0088] Among them, q g represents the source intensity of the g-th emission source; represents the contribution of the fugitive carbon emission concentration measured at the wth monitoring point; k wg It represents the proportional relationship between the carbon concentration at the wth downwind monitoring point and the source strength of the gth emission source.

[0089] When W=G, direct matrix inversion can calculate the carbon emission inversion result. However, considering the actual scenario of industrial parks, the number of carbon emission sources is often less than the number of monitoring points, that is, W>G. The above equation becomes an overdetermined equation. Therefore, it is necessary to select a suitable method to solve it.

[0090] The least squares method is a mathematical optimization technique that searches for the best fit solution for data by minimizing the sum of squares of the residuals. The least squares method can be used to easily calculate unknown data so that the sum of squares of the errors between theoretical data and actual data is minimized. Therefore, this paper selects the least squares method to solve the overdetermined equation. The principle is expressed in matrix form as follows:

[0091]

[0092] θ=(X T X) -1 X T Y

[0093] Among them, X is the feature matrix, each column is a feature, and each row represents a sample; Y represents the observation value; θ represents the parameter; f(θ) is the loss function.

[0094] For carbon emission monitoring in industrial parks, the total carbon emission is the sum of organized carbon emission and unorganized carbon emission, expressed as Q, that is:

[0095] Q=Q o +Q d

[0096] Among them, Q o represents the organized carbon emissions of the park, Q d Represents the unorganized carbon emissions in the park.

[0097] In addition, in order to realize the correction of the calculation structure, the present invention also constructs an inverse diffusion model, through which the relationship between the concentration value of the monitoring point and the carbon emission is confirmed, and the source intensity of the carbon emission source is inferred through the inverse diffusion model.

[0098] Specifically, reverse diffusion establishes an atmospheric transmission model to deduce emissions from the carbon emission concentration downwind. Taking a point source as an example, the emission intensity of the point source and the atmospheric concentration fluctuation (c i -c i,b ) is:

[0099]

[0100] Where A represents the source area, c i represents the carbon concentration at the monitoring point, c i，b Represents the background gas concentration; f i (ξ) represents the atmospheric diffusion coefficient at the emission source location ξ; S(ξ) represents the emission intensity at the emission source location ξ; d(ξ) represents the differential with respect to the emission source location ξ, representing the small unit of the emission source location.

[0101] In the diffusion model inverse method, an atmospheric transmission model is used to calculate the ratio of carbon concentration to emission at a monitoring point P in the plume transmission path. The emission of the carbon emission source can be expressed as:

[0102]

[0103] Where Q represents the source intensity of the emission source; (c i / q) sim It represents the ratio of carbon concentration at the monitoring point to carbon emissions.

[0104] Assuming that the atmospheric diffusion model can accurately describe the atmospheric transmission process, the diffusion model has no strict restrictions on the shape, size and monitoring point P of the carbon emission source. The core of the diffusion model inverse method is to identify the influencing factors of carbon emission diffusion, reasonably select the applicable diffusion model, and indirectly derive the parameters (c i / q) sim .

[0105] In order to further implement the above technical solution, S3 also includes calculating the wind speed. In the diffusion model, the corresponding concentration value needs to be confirmed based on the wind speed. The present invention is based on the real-time environmental monitoring data collected by the ground monitoring terminal of the industrial park, and uses the average value of the hourly average wind direction of each monitoring point in the park as the wind speed data. The calculation formula is as follows:

[0106]

[0107] Among them, u represents the horizontal component of wind direction; v represents the vertical component of wind direction; μ represents the wind speed vector; and θ represents the wind direction angle.

[0108]

[0109] Among them, u m Indicates the horizontal component of the average wind speed; v m Indicates the component of average wind speed in the vertical direction; u i represents the hourly monitoring component of monitoring point i in the horizontal direction; v i Represents the hourly monitoring component of monitoring point i in the vertical direction.

[0110] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0111] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for online monitoring and inversion of carbon emissions in industrial parks, characterized in that: include: S1: Construct a monitoring model based on the monitoring objects of the industrial park; confirm the emission source location, monitoring point location and real-time wind direction through the monitoring model; S2: updating the position of the monitoring point in real time according to the real-time wind direction, and confirming the upwind detection point and the downwind monitoring point; S3: Calculate the carbon emission concentration value of each emission source to the corresponding downwind monitoring point based on the wind speed of each monitoring point; S4: Construct a carbon emission inversion model to calculate carbon emissions.

2. According to claim 1, the inversion method based on online monitoring of carbon emissions in industrial parks is characterized in that: The emission sources include organized carbon emission sources and unorganized emission sources.

3. According to claim 2, the inversion method based on online monitoring of carbon emissions in industrial parks is characterized in that: The S3 specifically includes: S31: Calculate the carbon concentration of the organized carbon emission sources diffused to the downwind monitoring point; S32: Calculate the carbon concentration of the unorganized carbon emission sources diffused to the downwind monitoring point.

4. The inversion method based on online monitoring of carbon emissions in industrial parks according to claim 3 is characterized in that: The S31 is specifically as follows: inputting the location of the organized emission source and the location of the downwind monitoring point into a pre-built first diffusion model to obtain the carbon concentration of the organized carbon emission source diffused to the downwind monitoring point; the first diffusion model is: Among them, C o represents the carbon concentration of the organization’s carbon emission source diffused to the downwind monitoring point, x(P m ), y(P m ), z(P m ) represents the downwind monitoring point P m The position of the monitoring point, μ represents the wind speed at the downwind monitoring point; H represents the effective source height of the carbon emission source, and Q(Ar) represents the intensity of the organized carbon emission source; represents the diffusion coefficient on the y-axis; represents the diffusion coefficient in the z-axis.

5. The inversion method based on online monitoring of carbon emissions in industrial parks according to claim 4 is characterized in that: The S31 also includes: monitoring the wind direction, when the location coordinates of the organized carbon emission source are changed from (x(A r ),y(A r ),z(A r )) becomes (x′(A r ),y′(A r ),z′(A r )), the downwind monitoring point position coordinates will be (x(P m ),y(P m ),z(P m )) becomes (x′(P m ),y′(P m ),z′(P m ), then the contribution of the carbon dioxide concentration from the organized carbon dioxide emission sources in the industrial park to the monitoring point downwind of the park is: Among them, y′(P m )-y′(A r ) represents the lateral distance from the organized carbon emission source in the park to the downwind monitoring point.

6. The inversion method based on online monitoring of carbon emissions in industrial parks according to claim 3 is characterized in that: The S32 is specifically: Collect the actual carbon emission concentration at the downwind monitoring point; Obtain the carbon emission background value measured at the upwind monitoring point; The carbon concentration of the unorganized carbon emission source diffused to the downwind monitoring point is obtained by subtracting the carbon emission background value measured at the upwind monitoring point and the carbon concentration of organized carbon emissions to the downwind monitoring point from the actual carbon emission concentration at the downwind monitoring point.

7. The inversion method based on online monitoring of carbon emissions in industrial parks according to claim 6 is characterized in that: The carbon emission background value adopts the average value of carbon concentration of all upwind monitoring points.

8. The inversion method based on online monitoring of carbon emissions in industrial parks according to claim 3 is characterized in that: The S32 is specifically: calculating the carbon concentration of the unorganized carbon emission source diffused to the downwind monitoring point by constructing a second diffusion model, wherein the second diffusion model is: Among them, C d represents the carbon concentration of the organization’s carbon emission source diffused to the downwind monitoring point, x(P m ), y(P m ), z(P m ) represents the downwind monitoring point P m The position of the monitoring point, μ represents the wind speed at the downwind monitoring point; H represents the effective source height of the carbon emission source; Q(D t ) represents the intensity of organized carbon emission sources; represents the diffusion coefficient on the y-axis; represents the diffusion coefficient in the z-axis.

9. The inversion method based on online monitoring of carbon emissions in industrial parks according to claim 8 is characterized in that: The S32 further includes: monitoring the wind direction, and the contribution value of the unorganized carbon dioxide emission source diffused to the downwind monitoring point position is: Among them, (x′(P m ),y′(P m ),z′(P m )) is the coordinate of the downwind monitoring point after the wind direction changes.

10. The inversion method based on online monitoring of carbon emissions in industrial parks according to claim 6 or 8, characterized in that: The S4 includes: The source strength of carbon emission sources is inferred based on the carbon concentration values ​​of each downwind monitoring point combined with the coefficient of variation; Calculate the carbon emissions in any period of time based on the source intensity of the carbon emission source.

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