Method, equipment and medium for determining hierarchy of measurement point according to pollutant concentration
By collecting pollutant concentration data, using Gaussian function to construct the fitted image and setting the threshold, the problem of height misjudgment of the atmospheric boundary layer in the prior art is solved, and the precise distinction between the night boundary layer and the residual layer is realized and the hierarchical switching time is quantified.
Patent Information
- Application Number
- CN202510606334.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-12
- Publication Date
- 2025-09-02
AI Technical Summary
The existing methods of extracting the height of the atmospheric boundary layer are easily affected by echo signal noise and aerosol layer structure, resulting in low accuracy, especially when the multi-layer structure exists, the misjudgment is serious.
By collecting pollutant concentration data, a pollutant concentration fitting image is constructed based on the Gaussian function, the threshold for the transition zone of the boundary layer is determined, and the level judgment algorithm of the residual layer and the boundary layer is used to analyze the level where the measurement points are located.
It significantly improves the accuracy of the boundary layer height determination, clearly distinguishes the night boundary layer from the residual layer, solves the problem that traditional methods cannot quantify the hierarchical switching time window, and improves the accuracy of the boundary layer height.
Smart Images
Figure CN120577474A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of atmospheric monitoring technology, and in particular to a method, device and medium for determining the level of a measurement point based on pollutant concentration. Background Art
[0002] Methods for extracting the atmospheric boundary layer height include the gradient method and the ideal profile method. The gradient method uses the rate at which the distance-squared corrected signal decays with altitude as the basis for determining the atmospheric boundary layer height. Specifically, the altitude at which the gradient of the distance-squared corrected signal reaches its minimum value is defined as the atmospheric boundary layer height. However, the gradient method is susceptible to the influence of echo signal noise and the structure of the aerosol layer, resulting in poor stability and resulting in deviations in the extracted atmospheric boundary layer height.
[0003] The ideal profile method derives the atmospheric boundary layer height by fitting the atmospheric backscatter coefficient. This method is very sensitive to aerosol layers and cloud layers. When multiple layers of the atmosphere are present, such as residual layers and cloud layers, the ideal profile method can misjudge the atmospheric boundary layer height. Consequently, existing methods for extracting the atmospheric boundary layer height suffer from low accuracy.
[0004] The traditional method of confirming the specific value of the boundary layer height is often affected by the suspension layer, making the obtained boundary layer height less accurate. Summary of the Invention
[0005] Based on the above deficiencies in the existing technology, the present invention provides a method, device, and medium for determining the layer at which a measurement point is located based on pollutant concentration, analyzes the layer at which the measurement point is located during the monitoring period, and improves the accuracy of boundary layer height determination.
[0006] To solve the above technical problems, the first aspect of the present invention discloses a method for determining pollutants, the method comprising:
[0007] Collect pollutant concentration data at the measurement points within a preset time period and construct a pollutant concentration fitting image based on the Gaussian function;
[0008] determining a boundary layer transition zone threshold according to the pollutant concentration fitting image;
[0009] The layer where the measurement point is located is determined according to the layer judgment algorithm of the residual layer and the boundary layer.
[0010] In some embodiments, constructing a pollutant concentration fitting image based on a Gaussian function includes:
[0011] Calculate the hourly average concentration difference between the ground measurement point and the high-altitude measurement point;
[0012] Dividing the hourly average concentration difference into preset intervals to generate a frequency distribution;
[0013] The frequency distribution is fitted by a Gaussian function to obtain a pollutant concentration fitting image, which is a distribution image of concentration difference and frequency.
[0014] In some embodiments, a boundary layer transition zone threshold is determined based on the pollutant concentration fitting image;
[0015] When the pollutant concentration fitting image presents a double-peak shape, the boundary layer transition zone threshold is determined according to the peak position and the half-peak width.
[0016] In some embodiments, the boundary layer transition zone threshold includes a first threshold and a second threshold; the first threshold is the first peak position minus half of its half-peak width; the second threshold is the second peak position plus half of its half-peak width.
[0017] In some embodiments, determining the level of the measurement point according to a residual layer and boundary layer level determination algorithm includes:
[0018] When the concentration difference is greater than a first threshold, the measurement point is located in the residual layer;
[0019] When the concentration difference is less than the second threshold, the measurement point is located in the nighttime boundary layer.
[0020] In some embodiments, at least one ground sampling point and one high-altitude sampling point are set in the same target area.
[0021] In some embodiments, the Gaussian function is:
[0022]
[0023] Where y0 is the bottom value, S is the peak area, w is twice the standard deviation, x is the peak area, e is the peak position.
[0024] In some embodiments, the preset time period is from 20:00 to 6:00 the next day for at least ten consecutive days; and the pollutants include ozone, nitrogen dioxide and / or sulfur dioxide.
[0025] In a second aspect, a computer device is disclosed, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the steps of any one of the above methods for determining the level of a measurement point based on pollutant concentration.
[0026] In a third aspect, a computer storage medium is disclosed, on which a computer program is stored. When the computer program is executed by a processor, the method of determining the level of a measurement point according to the pollutant concentration as described in any one of the above items is implemented.
[0027] Compared with the prior art, the present invention has the following beneficial effects:
[0028] The present invention provides a method, device, and medium for determining the layer of a measurement point based on pollutant concentration. This method analyzes pollutant concentration data from high-altitude and ground-based measurement points and constructs a fitted pollutant concentration image based on a Gaussian function. This effectively avoids the misjudgment problems caused by noise and multi-layer aerosol structures in gradient and ideal profile methods, improves the accuracy of boundary layer height determination, and significantly enhances the accuracy of distinguishing between the nighttime boundary layer and the residual layer. By clearly distinguishing whether a measurement point belongs to the residual layer or the nighttime boundary layer in different time periods, it overcomes the problem of traditional methods' inability to quantify the time window for layer switching. BRIEF DESCRIPTION OF THE DRAWINGS
[0029] Figure 1 This is a flow chart of the method for determining the level of a measurement point based on pollutant concentration provided by the present invention;
[0030] Figure 2 A pollutant concentration fitting diagram in the method for determining the level of a measurement point based on pollutant concentration provided by the present invention;
[0031] Figure 3 This is a flow chart of step S in the method for determining the level of a measurement point based on pollutant concentration provided by the present invention;
[0032] Figure 4 Schematic diagram of the atmospheric layers of the method for determining the layer of a measurement point based on pollutant concentration provided by the present invention. DETAILED DESCRIPTION
[0033] For better understanding and implementation, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings 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 making creative efforts shall fall within the scope of protection of the present invention.
[0034] The terms "including" and "having" and any variations thereof in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus that includes a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products or apparatus.
[0035] The embodiment of the present invention discloses a method for determining the layer at which a measurement point is located according to the concentration of pollutants, analyzes the layer at which the measurement point is located during a monitoring period, and improves the accuracy of boundary layer height determination.
[0036] like Figure 1 As shown, the method includes:
[0037] Step S1: Collect pollutant concentration data of measurement points within a preset time period and pre-process the pollutant concentration data.
[0038] To obtain accurate pollutant concentration data, a simultaneous high-altitude / ground-based monitoring solution is employed. Generally, ground-based measurement points are set up in open, unobstructed areas to ensure they represent the overall levels of local atmospheric pollutants. High-altitude measurements utilize drones or tethered balloons equipped with monitoring equipment, or by setting up corresponding high-altitude measurement points at different heights within buildings to collect data at different altitudes.
[0039] Generally, the preset time period is from 20:00 to 6:00 the next day for at least ten consecutive days; because the atmospheric boundary layer is relatively stable at this time, it is less affected by solar radiation and human activities, and the pollutant concentration distribution can better reflect the true structure of the atmospheric boundary layer. Data sets with different observation durations show significant differences in atmospheric boundary layer research. Short-term data sets, such as daily observation data, can capture rapid changes in the atmosphere, but are easily affected by accidental factors and have poor data stability. Long-term data sets, such as annual observation data, can reflect the overall trend, but may mask seasonal and short-term fluctuation characteristics. Therefore, the preset time period is generally set to ten to thirty days.
[0040] The measurement duration can be set according to the actual situation. Long-term measurement can ensure the presence of a night boundary layer and a residual layer at the measurement point. A relatively long time period can more accurately obtain a pollutant concentration fitting image and obtain more accurate analysis results. In this application, at least one ground sampling point and a high-altitude sampling point are set in the same target area. The high-altitude sampling point is spatially matched with the ground sampling point, and a corresponding sampling point is set at a high-altitude position vertically above the ground sampling point. The pollutant concentration in the same target area is measured to ensure that the vertical gradient characteristics of the pollutant concentration difference can be accurately captured.
[0041] Through long-term measurements at this high-altitude sampling point, the vertical gradient characteristics of pollutants between the boundary layer and the residual layer can be accurately captured. Single-point long-term continuous observations can accumulate sufficient spatiotemporal data, and then through the bimodal Gaussian fitting of the frequency distribution of pollutant concentration differences, the dynamic layer switching law of the measurement site as the boundary layer evolves during the day and night can be revealed. If more high-altitude sampling points are further added, such as 200-meter, 500-meter, and 800-meter gradient distributions, the vertical profile structure of pollutant concentrations can be simultaneously analyzed, eliminating the sensitivity of single-height data to misjudgment of the top boundary of the boundary layer. At the same time, multi-point horizontal grid layout, such as a 5 km × 5 km grid, can quantify the spatiotemporal heterogeneity of pollutants, and improve the spatial resolution and statistical confidence of layer attribution determination through data fusion technology, providing high-precision observation basis for the study of atmospheric pollution transmission mechanisms and the optimization of environmental model parameters.
[0042] When screening pollutant types, representative pollutants with long nighttime lifespans can be selected, such as PM2.5, PM10, SO2, NO2, O3, etc. At the same time, the source and chemical properties of the pollutants must also be considered to ensure that the selected pollutants reflect the characteristics of different layers within the atmospheric boundary layer and do not suffer huge losses in the boundary layer during transmission from the ground to the upper atmosphere, resulting in a similar difference in pollutant concentrations between the residual layer and the ground. In this application, ozone, nitrogen dioxide, and / or sulfur dioxide are used as pollutants. They have long nighttime lifespans and stable chemical properties.
[0043] Step S2: constructing a pollutant concentration fitting image based on a Gaussian function;
[0044] The collected pollutant concentration data are preprocessed to remove outliers and perform smoothing to facilitate the construction of a pollutant concentration fitting image.
[0045] like Figure 2 As shown in FIG, constructing a pollutant concentration fitting image based on a Gaussian function includes the following steps:
[0046] Step S21, calculating the hourly average concentration difference between the ground measurement point and the high-altitude measurement point;
[0047] Step S22: Divide the hourly average concentration difference into preset intervals to generate a frequency distribution;
[0048] Step S23 : fitting the frequency distribution by a Gaussian function to obtain a pollutant concentration fitting image, wherein the pollutant concentration fitting image is a distribution image of concentration difference and frequency.
[0049] Calculate the difference in pollutant concentration between the upper-altitude measurement point and the ground-based measurement point over the course of an hour. For example, if the ozone concentration at the upper-altitude measurement point is 45 ppb and at the ground level is 30 ppb, the concentration difference for that hour is 15 ppb. Calculate the concentration difference for each hour and take the arithmetic mean to obtain the hourly average concentration difference.
[0050] In this application, the hourly average concentration difference between the ground and high-altitude measurement points is divided into continuous intervals with intervals of 1. For example, a difference of 0-1 ppb is interval 1, 1-2 ppb is interval 2, and so on. The number of data points in each interval is counted. For example, if there are 20 data points in the 5-6 ppb difference interval, the frequency is 20. A scatter plot or frequency histogram is generated with the hourly average concentration difference as the x-axis and the frequency as the y-axis.
[0051] The above data is input into a Gaussian function, which is:
[0052]
[0053] Where y0 is the bottom value, S is the peak area, w is twice the standard deviation, x is the peak area, e is the peak position.
[0054] Through optimization algorithms such as nonlinear least squares method, the parameters of the Gaussian function are adjusted so that the curve of the Gaussian function matches the original frequency distribution. After fitting is completed, the curve of the Gaussian function is superimposed with the original frequency histogram or scatter plot to obtain the pollutant concentration fitting image.
[0055] Step S3, determining a boundary layer transition zone threshold according to the pollutant concentration fitting image;
[0056] Specifically, when the pollutant concentration fitting image presents a bimodal shape, the boundary layer transition zone threshold is determined based on the peak position and the half-peak width; the boundary layer transition zone threshold includes a first threshold and a second threshold; the first threshold is the first peak position minus half of its half-peak width; the second threshold is the second peak position plus half of its half-peak width.
[0057] If the graph exhibits a bimodal shape, this indicates that some measurement points are located within the residual layer and others within the boundary layer. The boundary layer transition zone threshold can be used to assist in determining the location of the measurement points. In this application, the first peak position is the peak position with the largest concentration difference, while the second peak position is the peak position with the smallest concentration difference. This means that the peak area at the first peak position is larger than the peak area at the second peak position.
[0058] The first threshold is the first peak position minus half of its half-peak width, and the second threshold is the second peak position plus half of its half-peak width. The half-peak width FWHM refers to the width of the Gaussian curve at half of its peak. That is, the first threshold is x e1 –1 / 2FWHM1, the second threshold is x e2 +1 / 2FWHM2.
[0059] Step S4: Determine the level of the measurement point according to the level judgment algorithm of the residual layer and the boundary layer.
[0060] Specifically, when the concentration difference is greater than the first threshold, the measurement point is located in the residual layer; when the concentration difference is less than the second threshold, the measurement point is located in the night boundary layer. e1 –1 / 2FWHM1, the measurement point is located in the residual layer; when x<x e2 At +1 / 2FWHM2, the measurement point is located in the nighttime boundary layer.
[0061] The concentration difference between high altitude and ground is taken as the difference between the two. Taking ozone as an example, due to the long atmospheric life of ozone, the loss during the transmission process is relatively small. Based on this principle, it is determined that the peak with relatively large loss is in the residual layer. The position of the peak is as follows: Figure 2 As shown, the interval with relatively large loss is the right peak. According to the above calculation method, half of the half-peak width is taken as the error value. The ozone located in the boundary layer is not affected by the transformation between layers and is well mixed in the boundary layer at night, which is a peak with relatively small loss.
[0062] After one month of measurement, we can get Figure 3 The pollutant concentration fitting diagram is shown in Figure 2. Figure 4 As shown, this method determines whether the measured altitude at the measurement point falls between the nighttime boundary layer and the residual layer. Because the volatility of the nighttime boundary layer is difficult to determine, the relationship between the measurement point and the boundary layer can be determined by measuring altitude samples near the boundary layer. For example, if a Gaussian function plot obtained by analyzing ten days of measurement data exhibits a distinct bimodal structure, the peak with the smaller difference represents the altitude of the nighttime boundary layer, while the peak with the larger difference represents the residual layer.
[0063] The present invention can significantly improve the accuracy of distinguishing the nighttime boundary layer from the residual layer by analyzing the frequency distribution of the difference in pollutant concentration between high-altitude and ground measurement points and its Gaussian fitting results. Through Gaussian function analysis, the misjudgment problem caused by noise and multi-layer aerosol structure in the gradient method and the ideal profile method is effectively avoided, and the accuracy of boundary layer height determination is improved; based on the threshold setting of the half-peak width (FWHM), it can clearly distinguish whether the measurement point belongs to the residual layer or the nighttime boundary layer in different time periods, solving the problem that the traditional method cannot quantify the layer switching time window; it is applicable to long-lived pollutants such as O3, NO2, and PM2.5, and can simultaneously reflect the coupling relationship between the transmission loss characteristics of pollutants in the vertical direction and the evolution process of the boundary layer, providing dual support for pollution tracing and diffusion mechanism research; by accumulating data for multiple consecutive days, the significance of the bimodal distribution is enhanced, overcoming the limitation that single observations are easily affected by instantaneous fluctuations in the boundary layer, and improving the robustness and practicality of the method.
[0064] Based on the same inventive concept, the present invention also provides a computer device, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the steps of the above method for determining the level of the measurement point according to the pollutant concentration.
[0065] The processing method of the computer device can refer to the description of the above method and will not be repeated here.
[0066] An embodiment of the present application also provides a non-transitory machine-readable storage medium, on which an executable program is stored. When the executable program is executed by a microprocessor, the processor executes the method for determining the level of a measurement point based on the pollutant concentration as provided in the above embodiment.
[0067] An embodiment of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the described method of determining the level of a measurement point according to pollutant concentration.
[0068] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the method for determining the level of a measurement point based on pollutant concentration.
[0069] The embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the embodiments. Persons of ordinary skill in the art will be able to understand and implement the embodiments without inventive effort.
[0070] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.
[0071] Finally, it should be noted that the embodiments disclosed in the present invention are only preferred embodiments of the present invention, which are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.
Claims
1. A method for determining the level of a measurement point based on pollutant concentration, characterized in that: include: Collect pollutant concentration data at measurement points within a preset time period; Construct a pollutant concentration fitting image based on the Gaussian function; determining a boundary layer transition zone threshold according to the pollutant concentration fitting image; The layer where the measurement point is located is determined according to the layer judgment algorithm of the residual layer and the boundary layer.
2. The method for determining the level of a measurement point according to pollutant concentration according to claim 1, characterized in that: Construct a pollutant concentration fitting image based on the Gaussian function, including: Calculate the hourly average concentration difference between the ground measurement point and the high-altitude measurement point; Dividing the hourly average concentration difference into preset intervals to generate a frequency distribution; The frequency distribution is fitted by a Gaussian function to obtain a pollutant concentration fitting image, which is a distribution image of concentration difference and frequency.
3. The method for determining the level of a measurement point according to pollutant concentration according to claim 2, characterized in that: determining a boundary layer transition zone threshold according to the pollutant concentration fitting image; When the pollutant concentration fitting image presents a double-peak shape, the boundary layer transition zone threshold is determined according to the peak position and the half-peak width.
4. The method for determining the level of a measurement point according to pollutant concentration according to claim 3, characterized in that: The boundary layer transition zone threshold includes a first threshold and a second threshold; the first threshold is the first peak position minus half of its half-peak width; the second threshold is the second peak position plus half of its half-peak width.
5. The method for determining the level of a measurement point according to pollutant concentration according to claim 4, characterized in that: According to the layer judgment algorithm of the residual layer and the boundary layer, the layer where the measurement point is located is determined, including: When the concentration difference is greater than a first threshold, the measurement point is located in the residual layer; When the concentration difference is less than the second threshold, the measurement point is located in the nighttime boundary layer.
6. The method for determining the level of a measurement point according to pollutant concentration according to claim 3, characterized in that: In the same target area, at least one ground sampling point and one high-altitude sampling point shall be set up.
7. The method for determining the level of a measurement point according to pollutant concentration according to claim 6, characterized in that: The Gaussian function is: Where y0 is the bottom value, S is the peak area, w is twice the standard deviation, x is the peak area, e is the peak position.
8. The method for determining the level of a measurement point according to pollutant concentration according to claim 7, characterized in that: The preset time period is from 20:00 to 6:00 the next day for at least ten consecutive days; the pollutants include ozone, nitrogen dioxide and / or sulfur dioxide.
9. A computer device, characterized in that: include: A processor and a memory; wherein the memory stores a computer program, the computer program being suitable for being loaded by the processor and executing the steps of the method for determining the layer of a measurement point according to the pollutant concentration as claimed in any one of claims 1 to 8.
10. A computer storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the method for determining the layer where a measurement point is located according to the pollutant concentration as claimed in any one of claims 1 to 8 are implemented.