High-density gridding co2 concentration spatiotemporal distribution delineation and carbon emission total quantity metering method

Abstract

The application provides a high-density gridding CO2 concentration space-time distribution delineation and carbon emission total amount metering method, which comprises the following steps: regarding a to-be-measured area as a cuboid, and equally spacing the x, y and z axes of the cuboid to divide high-density grids, each grid corresponding to multiple measurement points; regarding each grid as uniformly distributed, measuring the CO2 concentration of each grid by using a high-frequency CO2 gas sensor, and further obtaining the carbon emission amount of the whole space based on the gridding carbon concentration-volume integration. Different from the traditional method of replacing the whole space carbon concentration with a single-point CO2 concentration, the application adopts a refined grid measurement and calculation method, and can delineate the high-precision space-time distribution of the CO2 concentration of the target park from points to surfaces and from surfaces to volumes, and significantly improve the carbon metering precision.

Description

Technical Field

[0001] This invention relates to the field of CO2 measurement technology, and in particular to a method for depicting the spatiotemporal distribution of CO2 concentration using a high-density gridded grid and for measuring total carbon emissions. Background Technology

[0002] CO2 is one of the main greenhouse gases in the atmosphere. Increased CO2 concentration leads to global warming and various environmental problems. Therefore, CO2 detection and control are crucial for protecting the environment and human health. In the environmental protection field, the main task of CO2 detection is to monitor and control the concentration of CO2 in the atmosphere. In the industrial sector, CO2 detection is mainly used to monitor and control emissions from various industrial processes. For example, in industries such as petrochemicals and coal chemicals, large amounts of CO2 are generated during production. By detecting and controlling this CO2, environmental pollution can be effectively reduced. Furthermore, CO2 detection can also be used to monitor energy consumption in industrial production processes, helping companies achieve their energy conservation and emission reduction goals.

[0003] There are two main types of existing carbon monitoring methods: one is carbon monitoring based on gas sensors, which can only measure the CO2 concentration at a certain point in space, while the other is remote sensing technology, which can only obtain a rough planar distribution of CO2 concentration at a distance. Neither of these methods can obtain accurate CO2 concentration distribution and total carbon emissions. Summary of the Invention

[0004] In view of this, the present invention proposes a method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using a high-density gridded method, in order to solve the technical problem that neither of the two carbon monitoring methods proposed in the background art can obtain accurate CO2 concentration distribution and total carbon emissions.

[0005] The technical solution of this invention is implemented as follows:

[0006] This invention provides a method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using a high-density gridded system, comprising the following steps:

[0007] Measurement points are set at equal intervals along the three dimensions of x-axis, y-axis and z-axis in the area to be measured of the cuboid. The measurement points divide the area to be measured into a grid of several small cuboids.

[0008] Acquire CO2 concentration data measured by the sensor at each measurement point;

[0009] The total carbon emissions and average CO2 concentration for each grid are calculated based on the CO2 concentration data measured at each measurement point. The formula for calculating the total carbon emissions is as follows:

[0010] G=∫ρ(x,y,z)dV;

[0011] In the formula, ρ x ρ y ρ z Let dV be the CO2 concentration measured along the x, y, and z axes of the small cuboid, and let dV be the volume integral unit of the small cuboid.

[0012] Based on the average CO2 concentration of each grid, the spatiotemporal distribution of CO2 concentration in the area to be measured is depicted;

[0013] The total carbon emissions of the area to be measured are calculated based on the total carbon emissions of each grid.

[0014] Based on the above technical solution, preferably, the step of setting measurement points at equal intervals along the three dimensions of the x-axis, y-axis, and z-axis in the measurement area of ​​the cuboid specifically includes:

[0015] Choose any point in space as a reference point and set measurement points. Form a cuboid measurement area from the reference point along the length, width, and height. Set measurement points at equal intervals from the reference point along the x-axis, y-axis, and z-axis.

[0016] Based on the above technical solution, preferably, the setting of measurement points at equal intervals along the three dimensions of x-axis, y-axis, and z-axis specifically includes:

[0017] The distance between two adjacent measurement points in the same dimension is the same, while the distance between adjacent measurement points in different dimensions may be the same or different.

[0018] Based on the above technical solutions, preferably, the method further includes: calculating the CO2 concentration at any location within each grid based on the CO2 concentration data measured at each measurement point, specifically including: assuming the CO2 concentration at the reference point as the reference concentration ρ. o Based on the CO2 concentration data measured at each measurement point, the rate of change of concentration at a certain point (x, y, z) within the grid relative to the reference point is obtained:

[0019] H = h x ×h y ×h z ;

[0020] In the formula, H is the rate of change of CO2 concentration at point (x,y,z) relative to the CO2 concentration at the reference point, and h is... x Let h be the rate of change of CO2 concentration at point (x,0,0) relative to the CO2 concentration at the reference point. y Let h be the rate of change of CO2 concentration at point (0,y,0) relative to the CO2 concentration at the reference point. z Let be the rate of change of CO2 concentration at point (0,0,z) relative to the CO2 concentration at the reference point;

[0021] The formula for calculating the CO2 concentration at any position (x, y, z) is:

[0022] ρ=ρ0×H;

[0023] In the formula, ρ is the CO2 concentration at any position (x,y,z), and ρ0 is the CO2 concentration at the reference point.

[0024] Based on the above technical solutions, preferably, the average CO2 concentration of each grid is obtained by dividing the total carbon emissions of the grid by the volume of the grid.

[0025] Based on the above technical solutions, a preferred embodiment further includes: using color changes to represent the rate of change of CO2 concentration at any location within the grid relative to a reference point.

[0026] Based on the above technical solutions, preferably, the step of depicting the spatiotemporal distribution of CO2 concentration in the area to be measured based on the average CO2 concentration of each grid includes: converting the average CO2 concentration of each grid into an intuitive three-dimensional model using three-dimensional visualization technology to depict the CO2 concentration distribution in the entire area to be measured.

[0027] Based on the above technical solution, preferably, after obtaining the average CO2 concentration of each grid in the area to be measured, the method further includes: summing the average CO2 concentrations of each grid and then averaging the results to obtain the average CO2 concentration of the area to be measured.

[0028] Based on the above technical solutions, preferably, the total carbon emissions of the area to be measured are calculated according to the total carbon emissions of each grid. Specifically, this includes: summing the total carbon emissions of each grid to obtain the total carbon emissions of the area to be measured. When calculating the total carbon emissions of each grid, if the measurement point is located at one boundary, the result should be reduced to 1 / 2 of the original value; if the measurement point is located at the intersection of two boundaries, the result should be reduced to 1 / 4 of the original value; if the measurement point is located at the intersection of three boundaries, the result should be reduced to 1 / 8 of the original value.

[0029] Based on the above technical solution, preferably, after the measurement points divide the area to be measured into a grid of several small cuboids, the method further includes: for each grid, setting measurement points at equal intervals in the length, width, and height dimensions, thereby further dividing the grid into several cuboid measurement micro-elements.

[0030] The high-density gridded method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions of the present invention has the following advantages over the prior art:

[0031] (1) This invention sets measurement points at equal intervals along the three dimensions of x-axis, y-axis and z-axis in the measurement area of ​​a cuboid. The total carbon emissions of each grid are calculated based on the CO2 concentration data measured at each measurement point. It adopts a measurement method from point to surface and from surface to volume, which avoids the crude measurement of CO2 concentration at all points in the entire space. This ensures measurement accuracy while saving manpower and expenses. It also limits the measurement space. By integrating the concentration and volume of CO2 and monitoring in real time, the change of the total amount of CO2 in the space can be obtained, thus realizing quantitative monitoring of CO2.

[0032] (2) By ensuring that the distance between two adjacent measurement points in the same dimension is the same, and the distance between adjacent measurement points in different dimensions is the same or different, high-density measurement points can be set up in areas with high CO2 emissions and large variations to ensure accuracy, while low-density measurement points can be set up in areas with low CO2 emissions and small variations to save costs.

[0033] (3) Combining the rate of change of CO2 concentration at each point in the space relative to the reference point, the CO2 concentration distribution of the entire space was depicted using drawing software and three-dimensional modeling technology, which makes it easier to intuitively understand the CO2 concentration distribution.

[0034] (4) For each grid, continue to set measurement points at equal intervals in the three dimensions of length, width and height, and further divide the grid into several rectangular measurement micro-elements. This nested division can improve measurement accuracy. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a flowchart illustrating the high-density gridded CO2 concentration spatiotemporal distribution depiction and total carbon emission measurement method of the present invention.

[0037] Figure 2 This is a schematic diagram of the CO2 concentration distribution under passive conditions according to the present invention;

[0038] Figure 3 This is a schematic diagram of the CO2 concentration distribution under active conditions according to the present invention;

[0039] Figure 4 This is a schematic diagram of the high-density gridded CO2 concentration spatiotemporal distribution depiction and carbon emission total measurement device of the present invention.

[0040] Figure 5 This is a schematic diagram of the structure of the terminal device of the present invention;

[0041] Figure 6 This is a schematic diagram of the sensor grid distribution and measurement sequence of the present invention;

[0042] Figure 7 A schematic diagram illustrating the establishment of coordinate axes for the sensor grid distribution of this invention.

[0043] Figure labeling: 100 - Grid generation module, 200 - Data acquisition module, 300 - Total carbon emissions calculation module. Detailed Implementation

[0044] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0045] A first aspect of the present invention, referred to Figure 1 As shown, a method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded methods is proposed, including the following steps:

[0046] Step S1: Set measurement points at equal intervals along the three dimensions of x-axis, y-axis and z-axis in the area to be measured of the cuboid. The measurement points divide the area to be measured into a grid of several small cuboids.

[0047] Step S2: Obtain CO2 concentration data measured by the sensor at each measurement point;

[0048] Step S3: Calculate the total carbon emissions and average CO2 concentration for each grid based on the CO2 concentration data measured at each measurement point. The formula for calculating the total carbon emissions is as follows:

[0049] G = ∫ρ(x, y, z)dV;

[0050] In the formula, ρ x ρ y ρ z Let dV be the CO2 concentration measured along the x, y, and z axes of the small cuboid, and let dV be the volume integral unit of the small cuboid.

[0051] The average CO2 concentration of a grid can be obtained by dividing the total carbon emissions of that grid by the grid's volume.

[0052] Step S4: Describe the spatiotemporal distribution of CO2 concentration in the area to be measured based on the average CO2 concentration of each grid.

[0053] Step S5: Calculate the total carbon emissions of the area to be measured based on the total carbon emissions of each grid.

[0054] In step S5, the average CO2 concentration of the area to be measured can also be calculated. The average CO2 concentration of the area to be measured can be obtained by summing the average CO2 concentrations of each grid and then averaging them.

[0055] It should be noted that a large number of measurement points are set along the length, width, and height of a certain space to conduct high-density measurements. The measurement points cover almost all areas within the space, including corners, edges, and any possible blind spots. Each dimension of the space is divided into multiple small cuboids. The CO2 concentration sensor used has high precision and collects data at a high frequency. The measurement frequency is adjustable (the measurement frequency of this invention is set to once per second, but is not limited to this value), and the sensor can continuously monitor CO2 concentration for a long time. The CO2 concentration data has multiple dimensions, including time, spatial location, and concentration value, forming a high-dimensional dataset. In addition to monitoring CO2 concentration, other environmental parameters (such as temperature and humidity) are also monitored to consider the influence of environmental factors on CO2 concentration. As people move or change activities within the space, the CO2 concentration sensor can update the measurement data in real time.

[0056] The high-density gridded CO2 concentration spatiotemporal distribution depiction and total carbon emission measurement method proposed in this invention sets measurement points at equal intervals along the x, y, and z axes of the measurement area of ​​a cuboid. The total carbon emission of each grid is calculated based on the CO2 concentration data measured at each measurement point. This method adopts a measurement approach that moves from points to surfaces and from surfaces to volumes, avoiding the crude measurement of CO2 concentration at all points in the entire space. This ensures measurement accuracy while saving manpower and costs. Furthermore, the measurement space is limited. By multiplying the CO2 density by the volume and adding real-time monitoring, the change in the total CO2 in that space can be obtained, achieving quantitative monitoring of CO2.

[0057] In some embodiments, step S1, which involves setting measurement points at equal intervals along the x-axis, y-axis, and z-axis of the cuboid to be measured region, specifically includes: taking any point in space as a reference point and setting measurement points thereon; forming the cuboid to be measured region from the reference point along the length, width, and height; and setting measurement points at equal intervals along the x-axis, y-axis, and z-axis from the reference point.

[0058] In some embodiments, setting measurement points at equal intervals along the x-axis, y-axis, and z-axis specifically includes:

[0059] The distance between two adjacent measurement points in the same dimension is the same, while the distance between adjacent measurement points in different dimensions may be the same or different.

[0060] In some embodiments, the method further includes: calculating the CO2 concentration at any location within each grid based on the CO2 concentration data measured at each measurement point, specifically including: assuming the CO2 concentration at the reference point as the reference concentration ρ. o Based on the CO2 concentration data measured at each measurement point, the rate of change of concentration at a certain point (x, y, z) within the grid relative to the reference point is obtained:

[0061] H = h x ×h y ×h z ;

[0062] In the formula, H is the rate of change of CO2 concentration at point (x,y,z) relative to the CO2 concentration at the reference point, and h is... x Let h be the rate of change of CO2 concentration at point (x,0,0) relative to the CO2 concentration at the reference point. y Let h be the rate of change of CO2 concentration at point (0,y,0) relative to the CO2 concentration at the reference point. z Let be the rate of change of CO2 concentration at point (0,0,z) relative to the CO2 concentration at the reference point;

[0063] The formula for calculating the CO2 concentration at any position (x, y, z) is:

[0064] ρ=ρ0×H;

[0065] In the formula, ρ is the CO2 concentration at any position (x,y,z), and ρ0 is the CO2 concentration at the reference point.

[0066] In some embodiments, three sequences X are defined. a Y b Z c They satisfy:

[0067]

[0068] Integration can be reduced to summation:

[0069]

[0070] The total carbon emissions of each small cuboid are calculated, as well as the average CO2 concentration of each small cuboid.

[0071] In some embodiments, the method further includes: representing the rate of change of CO2 concentration at any location within the grid relative to a reference point through color changes; converting the measurement data of each measurement point into an intuitive three-dimensional model using three-dimensional visualization technology; depicting the CO2 concentration distribution throughout the entire measurement area based on the average CO2 concentration of each grid; and considering the influence of environmental factors such as temperature and humidity on CO2 diffusion and concentration distribution to depict the CO2 concentration distribution throughout the entire space. Specific CO2 concentration distributions can be found in [reference needed]. Figure 2 and Figure 3 , Figure 2 The CO2 concentration distribution under passive conditions is shown. Figure 3 The CO2 concentration distribution under active conditions is shown, revealing the differences in CO2 concentration at different altitudes and at different locations at the same altitude. This provides a clear understanding of the CO2 concentration distribution throughout the space.

[0072] In some embodiments, the total carbon emissions of the area to be measured are calculated based on the total carbon emissions of each grid. Specifically, this includes summing the total carbon emissions of each grid to obtain the total carbon emissions of the area to be measured. When calculating the total carbon emissions of each grid, if the measurement point is located at one boundary, the result is reduced to 1 / 2 of the original value; if the measurement point is located at the intersection of two boundaries, the result is reduced to 1 / 4 of the original value; and if the measurement point is located at the intersection of three boundaries, the result is reduced to 1 / 8 of the original value.

[0073] In some embodiments, after dividing the area to be measured into a grid of several small cuboids, the measurement points further include: for each grid, setting measurement points at equal intervals along the length, width, and height, further dividing the grid into several cuboid measurement micro-elements. For example, in a cuboid space with length, width, and height of 10km, 10km, and 4m, the length can be divided into 1km intervals, the width into 1km intervals, and the height into 2m intervals. Thus, the cuboid is divided into several cuboid grids with length, width, and height of 1km, 1km, and 2m, respectively. The carbon concentration distribution and total carbon emissions within the entire cuboid space are calculated based on the above. For each grid with length, width, and height of 1km, 1km, and 2m, measurement points can be set at equal intervals along the length, width, and height, further dividing it into several small cuboid measurement micro-elements. The carbon concentration distribution and total carbon emissions within the aforementioned small cuboids with length, width, and height of 1km, 1km, and 2m are then calculated. The choice between nesting and non-nesting allows for greater flexibility in balancing measurement accuracy and cost. Nested solutions prioritize measurement accuracy, while non-nested solutions focus more on cost savings.

[0074] In a further embodiment, the CO2 concentration calculation of the outermost layer is defined as the first layer operation. After the first division, the CO2 concentration calculation for each small cuboid grid is defined as the second layer operation, and so on. When performing CO2 concentration calculations for the second layer and above, the distribution density of CO2 measurement points in different cuboids within the same layer can be inconsistent. For example, assuming the outermost layer is a single cuboid space, the measurement points in the small cuboids of the second layer operation closer to the CO2 emission source can be set more densely, while the measurement points in the small cuboids of the second layer operation farther from the CO2 emission source can be sparser. The specific point density depends on the actual situation. The inconsistent distribution density of CO2 measurement points in different cuboids within the same layer operation makes the control of accuracy and cost more flexible. In areas with high and fluctuating CO2 emissions, high-density measurement points can be set to ensure accuracy, while in areas with low and fluctuating CO2 emissions, low-density measurement points can be set to save costs.

[0075] A second aspect of the present invention is described below. Figure 4 As shown, a high-density gridded CO2 concentration spatiotemporal distribution depiction and carbon emission measurement device is proposed, including a grid division module 100, a data acquisition module 200, and a carbon emission calculation module 300, wherein:

[0076] The grid division module 100 is used to divide the area to be measured into a grid of several small cuboids, and to set measurement points at each vertex of the grid.

[0077] The data acquisition module 200 is used to acquire CO2 concentration data measured by the sensor at each measurement point;

[0078] The total carbon emissions calculation module 300 is used to calculate the total carbon emissions of each grid based on the CO2 concentration measured at each measurement point, and to calculate the total carbon emissions of the area to be measured based on the total carbon emissions of each grid.

[0079] A third aspect of the present invention, such as Figure 5 As shown, a terminal device is provided, including a memory and a processor;

[0080] The memory is used to store program code and transmit it to the processor. The memory can be an internal storage unit of the terminal device, such as a hard disk or RAM. Alternatively, the memory can be an external storage device of the terminal device, such as an external hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory can include both internal and external storage units of the terminal device. The memory is used to store computer programs and other programs and data required by the terminal device, and can also be used to temporarily store data that has been output or will be output.

[0081] The processor is used to execute the high-density gridded CO2 concentration spatiotemporal distribution depiction and carbon emission measurement method described in the first aspect embodiment according to instructions in the program code. The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate circuits or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0082] It should be noted that a computer program can be divided into one or more modules / units, which are stored in memory and executed by a processor to achieve the functions of this application. Each module / unit may contain a series of computer program instruction segments to describe the execution process of the computer program in a terminal device. The terminal device may be a desktop computer, laptop computer, handheld computer, cloud server, or other computing device. The terminal device may include, but is not limited to, a processor and memory. Those skilled in the art should understand that the description of these devices is not a limitation on the terminal device; the terminal device may include more or fewer components than illustrated, or combine certain components, or use different components. For example, the terminal device may also include input / output devices, network access devices, and buses, etc.

[0083] The preferred embodiments of this method are described below with reference to experimental data:

[0084] This embodiment includes two implementation phases:

[0085] The first stage involves measuring the CO2 concentration within a defined space when no carbon emission sources are introduced:

[0086] Ventilate a certain space (room) by opening windows for about 15 minutes. After the CO2 concentration stabilizes, collect CO2 concentration data from multiple points in the target area. At the same time, record relevant environmental parameters (such as temperature, humidity, wind speed, etc.).

[0087] Based on the ventilation conditions described above, the target area is defined as a 4x4 grid (3.6m x 3.6m). Please refer to [link / reference]. Figure 6 The CO2 concentration data of multiple points on the grid were measured in sequence, and the longitudinal measurement interval was set to 1m. The CO2 concentration data at 0m, 1m and 2m above the ground were measured three times at each height.

[0088] Please see Figure 7 Set the bottom left corner as the origin of the coordinate system and establish the coordinate axes.

[0089] The measured CO2 concentration data is processed to obtain the concentration data for each grid side length:

[0090] First measurement:

[0091]

[0092] Table 1.1 (First Measurement) Concentration of passive 3.6m*3.6m*2m material at 0.1m above ground

[0093]

[0094] Table 1.2 (First Measurement) Concentration of passive 3.6m*3.6m*2m material at 1m above ground

[0095]

[0096] Table 1.3 (First Measurement) Concentration at 3.6m*3.6m*2m depth, 2m above ground (Second Measurement):

[0097]

[0098] Table 2.1 (Second Measurement) Concentration of passive material at 3.6m*3.6m*2m height, 0.1m above ground

[0099]

[0100] Table 2.2 (Second Measurement) Concentration of passive 3.6m*3.6m*2m material at 1m above ground

[0101] Table 2.3 (Second Measurement) Concentration at 3.6m*3.6m*2m depth, 2m above ground (Third Measurement):

[0102]

[0103] Table 3.1 (Third Measurement) Concentration of passive material at 3.6m*3.6m*2m height, 0.1m above ground

[0104]

[0105] Table 3.2 (Third Measurement) Concentration at 3.6m*3.6m*2m depth, 1m above ground

[0106]

[0107] Table 3.3 (Third Measurement) Concentration of passive 3.6m*3.6m*2m material at 2m above ground

[0108] The calculations show that the average CO2 concentrations in the entire space measured three times in the passive space were 1238.11 ppm, 1222.74 ppm, and 1204.20 ppm, with an average of 1221.68 ppm.

[0109] The second stage involves measuring the CO2 concentration when a carbon emission source is introduced into a specific space:

[0110] According to relevant data, the standard indoor CO2 concentration is around 1000 ppm. For a space of 3.6m*3.6m*2m, this is equivalent to 25.92L of CO2 gas. Therefore, emitting 15L of CO2 gas will increase the CO2 concentration by about 57.9%, and a significant change in CO2 concentration can be observed.

[0111] Therefore, after releasing 15L of CO2 gas into a certain space (room), the person measuring should wear a mask (to reduce the impact of CO2 produced by human respiration) and proceed accordingly. Figure 1 The measurements were taken in sequence, with the longitudinal measurement interval set to 1m. CO2 concentration data were measured at 0m, 1m, and 2m above the ground, with three measurements taken at each height. Considering that the CO2 concentration varies greatly at a height of 0.1m above the ground, which is close to the carbon emission source, more measurement points were taken in each direction at the height of 0.1m above the ground to obtain more accurate results.

[0112] Set the bottom left corner as the origin of the coordinate system, establish a coordinate axis, and process the measured CO2 concentration data to obtain the concentration data for each grid side length:

[0113] First measurement:

[0114]

[0115] Table 4.1 (First Measurement) Concentration of active material at 3.6m*3.6m*2m height, 0.1m above ground

[0116]

[0117] Table 4.2 (First Measurement) Concentration of active material at 3.6m*3.6m*2m height, 1m above ground

[0118]

[0119] Table 4.3 (First Measurement) Concentration of active material at 3.6m*3.6m*2m height, 2m above ground (Second Measurement)

[0120]

[0121] Table 5.1 (Second Measurement) Concentration of active material at 3.6m*3.6m*2m height, 0.1m above ground

[0122]

[0123] Table 5.2 (Second Measurement) Concentration of active material at 3.6m*3.6m*2m height, 1m above ground

[0124]

[0125] Table 5.3 (Second Measurement) Concentration of active material at 3.6m*3.6m*2m height, 2m above ground (Third Measurement)

[0126]

[0127] Table 6.1 (Third Measurement) Concentration of active material at 3.6m*3.6m*2m height, 0.1m above ground

[0128]

[0129] Table 6.2 (Third Measurement) Concentration of active material at 3.6m*3.6m*2m height, 1m above ground

[0130]

[0131] Table 6.3 (Third Measurement) Concentration of active material at 3.6m*3.6m*2m height, 2m above ground

[0132] After processing the data, according to the method for calculating the average CO2 concentration as described in claim 5, the average CO2 concentrations in the entire space obtained from the three measurements within the active space were 1524.20 ppm, 1480.33 ppm, and 1492.92 ppm, respectively, with an average value of 1499.15 ppm.

[0133] The difference in average CO2 concentration between the active and passive spaces is 277.47 ppm. This translates to a CO2 volume change of approximately 0.27747 * 3.6 * 3.6 * 2 L ≈ 7.19 L. Considering the room volume is approximately 50 m³, this is reasonable. 3 The measured change in CO2 volume should be 7.19 / (3.6*3.6*2 / 50)=13.86L;

[0134] At the start of the experiment, 15L of CO2 gas was introduced into the space, so the measurement error was 7.6%, which is within 10% and meets the prediction standard.

[0135] The following examples illustrate the calculation of CO2 concentration at any location in each layer and the calculation of total CO2 concentration, using specific experimental data:

[0136] After obtaining the raw data of CO2 concentration for each layer, the raw data of CO2 concentration are shown in Table 7:

[0137]

[0138] Table 7

[0139] The horizontal and vertical rates of change were obtained by dividing the concentration in each layer by the concentration at the reference point, as shown in Table 8.

[0140]

[0141] Table 8

[0142] Multiply the rate of change in each horizontal direction by the rate of change in the vertical direction to obtain the rate of change at each intersection point, as shown in Table 9:

[0143]

[0144] Table 9

[0145] Assume the measurement area is a cuboid with dimensions of 4 meters on each side and 2 meters on the height. Five points are measured along the X-direction, allowing for a 4-eight-point division; five points are measured along the Y-direction, also allowing for a 4-eight-point division; and the z-direction is divided into 3 layers, allowing for a 2-eight-point division. Therefore, the original volume is 4 * 4 * 2 = 32 cubic meters. 3 The cuboid was divided into 32 sections, each with a volume of 1m³. 3 The concentration of CO2 at each point in each layer of a small rectangular prism is obtained by multiplying the concentration change rate at all intersection points by the volume and then by the concentration at each reference point. The concentrations are as follows (unit: cm). 3 See Table 10:

[0146]

[0147] Table 10

[0148] Considering that some dV will be outside the space at the boundary, it should be removed. That is, the data at the four corners of each layer in Table 10 needs to be multiplied by 1 / 8, the data around the four sides of each layer excluding the four corners needs to be multiplied by 1 / 4, and the remaining data needs to be multiplied by 1 / 2. The final data is shown in Table 11.

[0149]

[0150] Table 11

[0151] Ultimately, the total CO2 content in the measured area was calculated to be 37.8376 L, with an average CO2 concentration of 1182 ppm.

[0152] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded mapping, characterized in that, Includes the following steps: Measurement points are set at equal intervals along the three dimensions of x-axis, y-axis and z-axis in the area to be measured of the cuboid. The measurement points divide the area to be measured into a grid of several small cuboids. The method of setting measurement points at equal intervals along the three dimensions of x-axis, y-axis, and z-axis in the measurement area of ​​the cuboid specifically includes: taking any point in space as a reference point and setting measurement points; forming the measurement area of ​​the cuboid along the three dimensions of length, width, and height from the reference point; and setting measurement points at equal intervals along the three dimensions of x-axis, y-axis, and z-axis from the reference point. Acquire CO2 concentration data measured by the sensor at each measurement point; The total carbon emissions and average CO2 concentration for each grid are calculated based on the CO2 concentration data measured at each measurement point. The formula for calculating the total carbon emissions is as follows: ； In the formula, , , Let dV be the CO2 concentration measured along the x, y, and z axes of the small cuboid, and let dV be the volume integral unit of the small cuboid. Based on the average CO2 concentration of each grid, the spatiotemporal distribution of CO2 concentration in the area to be measured is depicted; The total carbon emissions of the area to be measured are calculated based on the total carbon emissions of each grid.

2. The method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded CO2 concentration as described in claim 1, characterized in that, The setting of measurement points at equal intervals along the x-axis, y-axis, and z-axis specifically includes: The distance between two adjacent measurement points in the same dimension is the same, while the distance between adjacent measurement points in different dimensions may be the same or different.

3. The method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded CO2 concentration as described in claim 1, characterized in that... Also includes: The CO2 concentration at any location within each grid is calculated based on the CO2 concentration data measured at each measurement point. Specifically, this includes assuming the CO2 concentration at the baseline point as the reference concentration. Based on the CO2 concentration data measured at each measurement point, the rate of change of concentration at a certain point (x, y, z) within the grid relative to the reference point is obtained: ； In the formula, H is the rate of change of CO2 concentration at point (x,y,z) relative to the CO2 concentration at the reference point, and h is... x Let h be the rate of change of CO2 concentration at point (x,0,0) relative to the CO2 concentration at the reference point. y Let h be the rate of change of CO2 concentration at point (0,y,0) relative to the CO2 concentration at the reference point. z Let be the rate of change of CO2 concentration at point (0,0,z) relative to the CO2 concentration at the reference point; The formula for calculating the CO2 concentration at any position (x, y, z) is: ； In the formula, ρ is the CO2 concentration at any position (x,y,z), and ρ0 is the CO2 concentration at the reference point.

4. The method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded CO2 concentration as described in claim 3, characterized in that, The average CO2 concentration of each grid is obtained by dividing the total carbon emissions of that grid by the volume of that grid.

5. The method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded CO2 concentration as described in claim 4, characterized in that... Also includes: The color change represents the rate of change of CO2 concentration at any location within the grid relative to the reference point.

6. The method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded CO2 concentration as described in claim 4, characterized in that, The method of depicting the spatiotemporal distribution of CO2 concentration in the area to be measured based on the average CO2 concentration of each grid includes: using three-dimensional visualization technology to convert the average CO2 concentration of each grid into an intuitive three-dimensional model, and depicting the CO2 concentration distribution in the entire area to be measured.

7. The method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded CO2 concentration as described in claim 1, characterized in that, After obtaining the average CO2 concentration of each grid in the area to be measured, the method further includes: summing the average CO2 concentrations of each grid and then averaging the results to obtain the average CO2 concentration of the area to be measured.

8. The method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded CO2 concentration as described in any one of claims 1-7, characterized in that, The total carbon emissions of the area to be measured are calculated based on the total carbon emissions of each grid. Specifically, the total carbon emissions of the area to be measured are obtained by summing the total carbon emissions of each grid. When calculating the total carbon emissions of each grid, if the measurement point is located on one boundary, the result is reduced to 1 / 2 of the original value; if the measurement point is located at the intersection of two boundaries, the result is reduced to 1 / 4 of the original value; and if the measurement point is located at the intersection of three boundaries, the result is reduced to 1 / 8 of the original value.

9. The method for depicting the spatiotemporal distribution of CO2 concentration and measuring total carbon emissions using high-density gridded CO2 concentration as described in any one of claims 1-7, characterized in that, After dividing the area to be measured into a grid of several small cuboids, the measurement points further include: for each grid, setting measurement points at equal intervals in the length, width, and height dimensions, thereby further dividing the grid into several cuboid measurement micro-elements.

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