A method and system for accurate detection of multi-medium new pollutants

Abstract

The present application relates to the technical field of pollutant detection, in particular to a precise detection method and system for multi-medium new pollutants, comprising: setting a plurality of detection positions around the factory area and collecting PFAS concentration, correcting the concentration based on the distance and relative direction of the detection position from the factory area, combining the concentration difference between the detection positions, using the correlation of different detection positions and the correlation of the concentration, obtaining the migration rate in the corresponding direction, combining the distance of the detection position and the concentration difference, calculating the first migration degree and the second migration degree, combining the component content change in PFAS and the first migration degree and the second migration degree to calculate the real migration parameter, correcting the concentration of the relevant detection position using the real migration parameter, obtaining other source performance parameters, and then performing pollution warning. The present application improves the precision of pollutant detection and can effectively predict and control pollution in a larger range.

Description

Technical Field

[0001] This invention relates to the field of pollutant detection technology, specifically to a precise detection method and system for novel pollutants in multiple media. Background Technology

[0002] With the acceleration of social development and industrialization, the impact of industrial pollution on the environment is becoming increasingly severe, and the detection and treatment of pollutants have become key tasks. For example, PFAS (perfluoroalkyl and polyfluoroalkyl substances) contained in factory exhaust gases have become a major concern. PFAS emitted with exhaust gases not only have a profound impact on human health, but may also pollute nearby soil and water resources. Therefore, PFAS detection near factories provides support for the comprehensive assessment and early warning of pollutants, and can better predict the diffusion trend and potential risks of pollutants.

[0003] In the process of detecting pollutants, sampling is usually carried out directly at different locations in a single medium, which lacks sufficient accuracy and diversity. At the same time, the migration of PFAS discharged with exhaust gas between different media is not considered, which makes it impossible to directly reflect new sources of pollutants. Furthermore, general migration analysis only considers the concentration relationship of PFAS in different media, but ignores the migration characteristics of long and short chains of PFAS, resulting in low accuracy of migration analysis. Summary of the Invention

[0004] This invention provides a precise detection method and system for novel pollutants in multiple media to solve existing problems.

[0005] The present invention provides a precise detection method and system for novel pollutants in multiple media, employing the following technical solution:

[0006] One embodiment of the present invention provides a method for accurate detection of novel pollutants in multiple media, the method comprising the following steps:

[0007] Several detection locations are set up around the factory area, and PFAS concentrations are collected at these locations. These detection locations are divided into ground detection locations and aerial detection locations.

[0008] For any detection location, the PFAS concentration at the detection location is corrected based on the distance between the detection location and the factory area and the direction relative to the factory area, combined with the difference in PFAS concentration changes between detection locations.

[0009] By utilizing the correlation between aerial and ground detection locations in the direction relative to the plant area, the relevant detection locations of the aerial detection locations in the corresponding directions are determined. Based on the correlation between the PFAS concentrations of the aerial detection locations and the corresponding relevant detection locations in any direction, the migration rate in the corresponding direction is obtained.

[0010] By combining the distance between the relevant detection location and the aerial detection location in any direction, and the difference in PFAS concentration between the relevant detection location and the aerial detection location, the first migration degree of the relevant detection location and the second migration degree of the aerial detection location are calculated respectively.

[0011] By combining the changes in component content in PFAS at relevant detection locations and aerial detection locations, as well as the first migration degree and the second migration degree, the true migration parameters between relevant detection locations and corresponding migration source locations are calculated.

[0012] By correcting the PFAS concentration at relevant detection locations using actual migration parameters, other source performance parameters at relevant detection locations are obtained, and pollution alarms are then triggered using the magnitude of these other source performance parameters.

[0013] Furthermore, the specific method for setting up several detection locations around the factory area and collecting PFAS concentrations at these locations includes:

[0014] A polar coordinate system is established, with the plant area as the center of the polar coordinate system. On the polar coordinate system, PFAS concentration data at aerial and ground detection locations are obtained at several different radii and directions. The PFAS concentration data is divided into short-chain PFAS concentration data and long-chain PFAS concentration data.

[0015] Furthermore, the method for correcting the PFAS concentration at the detection location based on the distance between the detection location and the factory area, as well as its direction relative to the factory area, and in conjunction with the differences in PFAS concentration changes between detection locations, includes the following specific methods:

[0016] Obtain the PFAS concentration at all detection locations with radii of any direction, and sort the PFAS concentrations at the detection locations in ascending order of the radii corresponding to the detection locations to obtain the PFAS concentration sequence for the corresponding direction; establish a window of a preset size and take any data point in the PFAS concentration sequence as the center point of the window, and use the window to traverse the PFAS concentration sequence, recording the data formed by all data points within the window as window data during the traversal process.

[0017] For detection positions with different directions but the same radius, the deviation rate of the data points is calculated based on the difference in data change within the corresponding window when the data points corresponding to the detection positions are used as the center point of the window.

[0018] The reciprocal of the deviation rate of each data point is used as the data deviation rate as the weight, and the weighted least squares method is used to perform linear fitting on all data points in any PFAS concentration sequence to obtain the regression value of each data point. The regression value is used as the corrected PFAS concentration of the corresponding data point.

[0019] Furthermore, the specific method for obtaining the deviation rate of the data points is as follows:

[0020] For any window of data, the slope of each data point within the window is obtained, and the average slope of all data points in the window is taken as the window slope of the data point corresponding to the center point of the window. Any data point is designated as the target data point. Data points corresponding to other detection positions with the same radius but different directions as the target data point are taken as reference data points. The absolute value of the difference between the window slopes corresponding to the target data point and any reference data point is obtained and denoted as the window slope difference between the target data point and the reference data point. The absolute value of the difference between the directions corresponding to the target data point and any reference data point is obtained and denoted as the detection direction difference between the target data point and the reference data point. Based on the window slope difference and the detection direction difference between the target data point and the reference data point, the deviation rate of the target data point is calculated. The window slope difference is positively correlated with the deviation rate, and the detection direction difference is negatively correlated with the deviation rate.

[0021] Furthermore, the method of determining the relevant detection position of the aerial detection position in the corresponding direction by utilizing the correlation between the aerial detection position and the ground detection position in the direction relative to the factory area, and obtaining the migration rate in the corresponding direction based on the correlation between the PFAS concentration of the aerial detection position and the corresponding relevant detection position in any direction, includes the following specific methods:

[0022] The first aerial detection position is defined as the aerial detection position with the largest radius in any direction corresponding to the aerial detection position. The distance between the first aerial detection position and the center of the circle in the polar coordinate system is used as the first parameter. A second parameter is preset. A horizontal rectangular region with the first parameter as the length and the second parameter as the width is established. The center line of the long side of the horizontal rectangular region overlaps with the straight line where the center of the circle and the aerial detection position are located in any direction. The corresponding horizontal rectangular regions in all directions are obtained. The ground detection positions in the corresponding horizontal rectangular regions in any direction are obtained as the related detection positions of the aerial detection positions in the same direction. The PFAS concentrations at the ground detection positions are arranged in ascending order of the radius corresponding to the ground detection positions. The resulting PFAS concentration sequence is denoted as the ground PFAS concentration sequence.

[0023] By utilizing the spatial relationship between the aerial detection positions and related detection positions in any direction, and combining the PFAS concentration at the aerial detection positions for interpolation, a PFAS concentration interpolation sequence in the stated direction is obtained. Based on the correlation between the PFAS concentration interpolation sequence and the ground PFAS concentration sequence, the mobility in the stated direction is obtained.

[0024] Furthermore, the specific method for obtaining the mobility in the aforementioned direction is as follows:

[0025] Obtain a straight line formed by aerial detection positions in any direction, denoted as the first straight line. Obtain the relevant detection positions of the aerial detection positions in the direction. Use the vertical projection points of the relevant detection positions on the first straight line as interpolation points to obtain several interpolation points on the first straight line. The number of interpolation points is the same as the number of relevant detection positions. Based on the PFAS concentration of all aerial detection positions in the direction and combined with a linear interpolation algorithm, obtain the PFAS concentration corresponding to each interpolation point. Sort the PFAS concentrations of all interpolation points in ascending order of their corresponding radii on the first straight line to obtain a PFAS concentration interpolation sequence. Calculate the correlation between the PFAS concentration interpolation sequence in the direction and the ground PFAS concentration sequence using a cross-correlation function, and normalize the correlation to obtain the mobility in the direction.

[0026] Furthermore, the method for calculating the first migration degree of the relevant detection location and the second migration degree of the aerial detection location by combining the distance between the relevant detection location and the aerial detection location in any direction, and the difference in PFAS concentration between the relevant detection location and the aerial detection location, includes the following specific methods:

[0027] Project all aerial detection positions in any direction onto the ground, record any aerial detection position as the target aerial detection position, obtain the relevant detection position that is the smallest in distance from the target aerial detection position on the ground in the stated direction, and use the target aerial detection position as the migration source position of the relevant detection position.

[0028] The ratio of the PFAS concentration at any relevant detection location to the PFAS concentration at the corresponding migration source location is denoted as the migration factor of the relevant detection location. Based on the migration factor of the relevant detection location and the migration rate in the corresponding direction of the relevant detection location, the first migration degree of the relevant detection location is calculated. Both the migration factor and the migration rate are positively correlated with the migration degree.

[0029] For any aerial detection location, a second migration degree of the aerial detection location is calculated based on the relative distance between the aerial detection location and the corresponding related detection location, as well as the migration degree of the related detection location.

[0030] Furthermore, the specific method for calculating the true migration parameters between the relevant detection location and the corresponding migration source location by combining the changes in component content in the PFAS at the relevant detection location and the aerial detection location, as well as the first migration degree and the second migration degree, includes:

[0031] The concentrations of short-chain PFAS and long-chain PFAS in the PFAS concentrations of all aerial detection locations and related detection locations are obtained respectively. The proportion of long-chain PFAS concentration in the PFAS concentration of any aerial detection location and any related detection location is calculated and denoted as the long-chain proportion. The long-chain proportions of the aerial detection locations and related detection locations are denoted as the first long-chain proportion of the aerial detection location and the second long-chain proportion of the related detection location, respectively. The first long-chain proportions of all aerial detection locations in any direction are sorted in ascending order of their corresponding radii and the resulting sequence is denoted as the aerial long-chain proportion sequence. Similarly, the ground long-chain proportion sequence is obtained. The aerial long-chain proportion sequence and the ground long-chain proportion sequence are collectively referred to as the long-chain proportion sequence.

[0032] Let any element in the long chain proportion sequence be the target element. Calculate the difference between the target element and the long chain proportion corresponding to the previous element in the arbitrary long chain proportion sequence, and use it as the long chain proportion decrease rate of the target element. The long chain proportion decrease rate obtained by using the air long chain proportion sequence is recorded as the first decrease rate, and the long chain proportion decrease rate obtained by using the ground long chain proportion sequence is recorded as the second decrease rate.

[0033] The absolute value of the difference between the second descent rate of the element corresponding to any relevant detection location in the ground long chain proportion sequence and the first descent rate of the element corresponding to the migration source location in the air long chain proportion sequence is recorded as the long chain proportion trend degree of the relevant detection location and the migration source location. Based on the long chain proportion trend degree of the relevant detection location and the migration source location, the first migration degree of the relevant detection location and the second migration degree of the migration source location, the true migration parameters of the relevant detection location and the corresponding migration source location are obtained.

[0034] Furthermore, the method of correcting the PFAS concentration at the relevant detection location using the actual migration parameters to obtain other source performance parameters at the relevant detection location, and then using the magnitude of the other source performance parameters to issue a pollution alarm, includes the following specific methods:

[0035] The true migration parameters of all relevant detection locations and corresponding migration source locations are normalized using a linear normalization function to obtain normalized true migration parameters. The PFAS concentrations of relevant detection locations are then corrected using the normalized true migration parameters to obtain other source performance parameters of relevant detection locations. The other source performance parameters are negatively correlated with the normalized true migration parameters, while the other source performance parameters are positively correlated with the PFAS concentrations.

[0036] The performance parameters of other sources at all relevant detection locations are linearly normalized, and a threshold for the performance parameters is preset. The relevant detection locations where the normalized performance parameters of other sources are greater than the threshold are taken as ground detection locations with other pollution sources.

[0037] Mark and alert ground-based detection locations that have other sources of pollution.

[0038] A precision detection system for novel pollutants in multiple media includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any one of the precision detection methods for novel pollutants in multiple media.

[0039] The beneficial effects of the technical solution of this invention are as follows: By setting multiple detection locations around the factory area, including ground and air detection locations, and combining the distance and direction of these locations from the factory area, the PFAS concentration at different detection locations can be corrected, thereby improving detection accuracy and avoiding deviations in traditional methods; by combining the correlation between air and ground detection locations, the migration rate of pollutants can be accurately calculated, which is crucial for predicting the direction of pollutant diffusion and forecasting potential pollution areas; by analyzing the differences in PFAS concentrations in different media in the air and on the ground, and combining the migration characteristics of long-chain and short-chain PFAS, the limitations of traditional single-media sampling methods in reflecting pollutants in different media are overcome. This method overcomes the limitations of inter-source migration, thus enabling a more comprehensive assessment of pollution sources and their diffusion. By combining changes in PFAS component content, migration degree, and actual migration parameters, the location of pollution sources can be accurately traced, thereby improving the efficiency of pollution source identification and tracing, and providing more targeted early warning information for pollution control. By correcting the PFAS concentration at relevant detection locations using the above methods, more accurate parameters of other sources can be obtained, providing a more accurate basis for judgment in the pollution alarm system, reducing false alarms and missed alarms, and improving the overall environmental governance effect. In summary, this method not only improves the accuracy of pollutant detection but also enables effective pollution prediction and control on a larger scale. Attached Figure Description

[0040] 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.

[0041] Figure 1 This is a flowchart illustrating the steps of a precise detection method for novel pollutants in multiple media according to the present invention.

[0042] Figure 2 This is a schematic diagram of a polar coordinate system provided for one embodiment of the present invention. Detailed Implementation

[0043] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a precise detection method and system for novel multi-media pollutants proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0045] The following description, in conjunction with the accompanying drawings, details a specific scheme for a precise detection method and system for novel pollutants in multiple media provided by this invention.

[0046] Please see Figure 1 The diagram illustrates a flowchart of a method for accurate detection of novel pollutants in multiple media, according to an embodiment of the present invention. The method includes the following steps:

[0047] Step S001: Set up several detection locations around the factory area and collect PFAS concentrations at the detection locations.

[0048] Specifically, in order to achieve the accurate detection method for new pollutants in multiple media proposed in this embodiment, it is first necessary to collect PFAS concentrations at ground-based and airborne detection locations. The specific process is as follows:

[0049] First, for PFAS data collection, airborne and ground-based data are primarily collected. The specific collection method is as follows: Using the factory area as the center, construct several concentric circles of different radii, with a radius interval between adjacent circles of different radii. Then, straight lines are drawn in the north-south, east-west, northwest-southeast, and southwest-northeast directions. Ground and aerial detection positions are arranged at the intersections of these lines and the circle. These ground and aerial detection positions are collectively referred to as detection positions. This is the preset first parameter.

[0050] It should be noted that, in the embodiments of the present invention, the first parameter is preset based on experience. The distance is 50m. Additionally, because PFAS propagation is limited on the ground, a denser detection network is needed. Specifically, the interval between ground detection positions is 20 meters. In other embodiments, the first parameter... The interval between the detection position and the actual position can be adjusted according to the actual situation, and the embodiments of the present invention do not impose specific limitations.

[0051] Then, a dual-channel atmospheric sampler was used as the sampling device. The two channels operated independently and collected particulate and gaseous PFAS at the same time to avoid cross-contamination. After the UAV took off, it arrived at the first sampling point according to the planned route, hovered and positioned itself to carry out the sampling work.

[0052] Finally, a polar coordinate system was established, with the plant area as the center of the polar coordinate system. On the polar coordinate system, PFAS concentration data at aerial and ground detection locations were obtained at several different radii and directions. The PFAS concentration data was divided into short-chain PFAS concentration data and long-chain PFAS concentration data. The short-chain PFAS included PFBS (perfluorobutyric acid) and PFHxA (perfluorohexanoic acid), while the long-chain PFAS included PFOA (perfluorooctanoic acid) and PFOS (perfluorooctane sulfonate).

[0053] It should be noted that, as Figure 2 The diagram shows a polar coordinate system. In this system, several intersection points are formed by straight lines in different directions and concentric circles of different radii. Each intersection point corresponds to a ground detection position and an aerial detection position. The dots in the diagram represent several detection positions of different radii in the same direction. For aerial detection position sampling, a drone carrying sampling equipment is used to perform aerial and ground sampling. The aerial detection position is at least 50 meters above the ground. Ground sampling equipment is installed manually. The same sampling time interval of 5 seconds is set for both aerial and ground detection positions. The height of the aerial detection position above the ground and the sampling time interval are only one specific embodiment of the present invention. In other embodiments, adjustments can be made according to actual conditions. The embodiments of the present invention are not specifically limited.

[0054] Thus, PFAS concentration data for several airborne and ground-based detection locations were obtained using the above method.

[0055] Step S002: For any detection location, based on the distance between the detection location and the factory area and its direction relative to the factory area, and combined with the differences in PFAS concentration changes between detection locations, the PFAS concentration at the detection location is corrected.

[0056] It should be noted that, due to the spatial limitations of pollutant propagation, pollutant detection is primarily conducted in the vicinity of the pollution source. Step S001 obtains PFAS concentrations at different locations around the factory. PFAS propagation in the air is affected by propagation distance, and the concentration of PFAS in the air is also influenced by airflow, making it unstable. Therefore, the data from the sampling points may not fully reflect the true PFAS concentration in the corresponding area. In reality, as the distance from the pollution source increases, PFAS concentration decreases due to diffusion attenuation, and the two exhibit a clear linear relationship. Therefore, the linear relationship between PFAS concentration and distance can be used to correct inaccurate PFAS concentration data.

[0057] Specifically, firstly, for any detection location, obtain the PFAS concentration at all detection locations with radii of any direction, and sort the PFAS concentrations at the detection locations in ascending order of the radii corresponding to the detection locations to obtain the PFAS concentration sequence for the corresponding direction; establish a window of a preset size and take any data point in the PFAS concentration sequence as the center point of the window, and use the window to traverse the PFAS concentration sequence, recording the data formed by all data points within the window as window data during the traversal process.

[0058] It should be noted that, in the embodiments of the present invention, the window size is preset to 5 based on experience, and can be adjusted according to the actual situation. The embodiments of the present invention do not make specific limitations. In addition, when the data point located at the sequence boundary in the PFAS concentration sequence is used as the center point of the window, if the number of data points in the window does not correspond to the window size, then no window is constructed.

[0059] Then, for detection positions with different directions but the same radius, the deviation rate of the data points is calculated based on the difference in data change within the corresponding window when the data point corresponding to the detection position is used as the center point of the window.

[0060] As a preferred embodiment, the method for obtaining the deviation rate of the data points includes: for any window of data, obtaining the slope of each data point within the window of data, and taking the average slope of all data points in the window of data as the window slope of the data point corresponding to the center point of the window; designating any data point as the target data point, and taking the data points corresponding to other detection positions with the same radius but different directions as the target data point as reference data points; obtaining the absolute value of the difference between the window slopes corresponding to the target data point and any reference data point, and designating it as the window slope difference between the target data point and the reference data point; obtaining the absolute value of the difference between the directions of the detection positions corresponding to the target data point and any reference data point, and taking it as the detection direction difference between the target data point and the reference data point; and calculating the deviation rate of the target data point based on the window slope difference and the detection direction difference between the target data point and the reference data point, wherein the window slope difference is positively correlated with the deviation rate, and the detection direction difference is negatively correlated with the deviation rate.

[0061] As an optional embodiment, the specific method for calculating the deviation rate of the target data points is as follows:

[0062]

[0063] in, This represents the deviation rate of the target data points; Indicates the target data point and the first The detection direction difference of each reference data point; Indicates the target data point and the first The window slope difference of each reference data point; This indicates the number of reference data points for the target data point.

[0064] It should be noted that the deviation rate quantifies the degree of anomaly in PFAS concentration data at a single detection location, reflecting the reliability of the measured values ​​affected by local disturbances (such as airflow disturbances, instrument errors, etc.). , The smaller the value (i.e., the closer the reference point is to the target point in the same direction), the greater the weight. This is because PFAS should have similar diffusion attenuation laws in the same propagation direction; for The difference in window slope indicates the difference in the linear trend of concentration change with distance. When PFAS diffuses in the air, the concentration decreases approximately linearly with distance. If the slope difference between the target point and the reference point is large, it indicates that the point may be affected by instantaneous airflow.

[0065] Finally, the reciprocal of the deviation rate of each data point is used as the data deviation rate as the weight, and the weighted least squares method is used to perform linear fitting on all data points in any PFAS concentration sequence to obtain the regression value of each data point. The regression value is used as the corrected PFAS concentration of the corresponding data point.

[0066] Similarly, the corrected PFAS concentrations corresponding to all detection locations are obtained, and the fitting function corresponding to each PFAS concentration sequence directly reflects the changing trend of PFAS concentration.

[0067] It should be noted that, in the embodiments of the present invention, the PFAS concentrations used in subsequent processes are all corrected PFAS concentrations.

[0068] Thus, the corrected PFAS concentration at each detection location is obtained using the above method.

[0069] Step S003: Utilize the correlation between the aerial detection position and the ground detection position in the direction relative to the plant area to determine the relevant detection position of the aerial detection position in the corresponding direction. Based on the correlation between the PFAS concentration of the aerial detection position and the corresponding relevant detection position in any direction, obtain the migration rate in the corresponding direction.

[0070] It should be noted that pollutant propagation involves migration. For example, PFAS (phosphorus alkaloids) emitted into the air can migrate to the soil or water on the ground. PFAS migration typically occurs through natural sedimentation or rainwater carryover. During the current monitoring process, PFAS concentration data are simultaneously collected at soil monitoring locations. Therefore, it is necessary to analyze the migration and propagation of PFAS by analyzing the correlation between PFAS concentrations at the air and ground monitoring locations. When PFAS migrate from the air to the soil or water, the migration direction is directly vertically downwards. Therefore, it is first necessary to determine the ground monitoring locations that exhibit this migration pattern based on the monitoring locations along the radius, i.e., to determine the corresponding ground monitoring locations for any airborne monitoring location in any direction.

[0071] Specifically, firstly, the aerial detection position with the largest radius in the direction corresponding to any aerial detection position is obtained and denoted as the first aerial detection position. The distance between the first aerial detection position and the center of the circle in the polar coordinate system is used as the first parameter. A second parameter is preset, and a horizontal rectangular region with the first parameter as the length and the second parameter as the width is established. The center line of the long side of the horizontal rectangular region overlaps with the straight line where the center of the circle and the aerial detection position are located in any direction, thus obtaining the corresponding horizontal rectangular regions in all directions. The ground detection positions in the corresponding horizontal rectangular regions in any direction are obtained as the relevant detection positions of the aerial detection positions in the same direction. The PFAS concentrations at the ground detection positions are arranged in ascending order of the radius corresponding to the ground detection positions, and the resulting PFAS concentration sequence is denoted as the ground PFAS concentration sequence.

[0072] It should be noted that by measuring the distance between the ground projection of the detection location along a radius and the ground detection location, a related PFAS concentration sequence along a radius is determined. In this case, the two sequences reflect the actual PFAS concentrations in the air and on the ground, respectively. In reality, PFAS concentrations in the air migrate to the ground soil or water. This migration causes the PFAS concentration at the ground detection location to be affected by the PFAS concentration at the air detection location. The specific relationship reflects the probability of PFAS concentration migrating from the air to the ground.

[0073] Then, by utilizing the spatial positional relationship between the aerial detection positions and related detection positions in any direction, and combining the PFAS concentration at the aerial detection positions for interpolation, a PFAS concentration interpolation sequence in the stated direction is obtained. Based on the correlation between the PFAS concentration interpolation sequence and the ground PFAS concentration sequence, the mobility in the stated direction is obtained.

[0074] As a preferred embodiment, the method for obtaining the mobility in the stated direction is as follows:

[0075] Obtain a straight line formed by aerial detection positions in any direction, denoted as the first straight line. Obtain the relevant detection positions of the aerial detection positions in the direction. Use the vertical projection points of the relevant detection positions on the first straight line as interpolation points to obtain several interpolation points on the first straight line. The number of interpolation points is the same as the number of relevant detection positions. Based on the PFAS concentration of all aerial detection positions in the direction and combined with a linear interpolation algorithm, obtain the PFAS concentration corresponding to each interpolation point. Sort the PFAS concentrations of all interpolation points in ascending order of their corresponding radii on the first straight line to obtain a PFAS concentration interpolation sequence. Calculate the correlation between the PFAS concentration interpolation sequence in the direction and the ground PFAS concentration sequence using a cross-correlation function, and normalize the correlation to obtain the mobility in the direction.

[0076] As an optional embodiment, the specific method for calculating the mobility rate in any direction is as follows:

[0077]

[0078] in, This indicates the migration rate in the stated direction. This indicates the correlation between the PFAS concentration interpolation sequence on the vector and the ground PFAS concentration sequence.

[0079] It should be noted that the output value of the cross-correlation function has a range of values. ,in To normalize the result, the range of values ​​is... Furthermore, the mobility rate reflects the ability of PFAS concentrations to migrate and spread from the air to the ground.

[0080] Thus, the migration rate is obtained through the above method.

[0081] Step S004: Combining the distance between the relevant detection location and the aerial detection location in any direction, and the difference in PFAS concentration between the relevant detection location and the aerial detection location, calculate the first migration degree of the relevant detection location and the second migration degree of the aerial detection location, respectively.

[0082] It should be noted that by obtaining the correlation between PFAS concentration sequences in any direction and their corresponding related PFAS concentration sequences, the migration probability of PFAS concentration from the air to the ground is determined. However, the above process considers the overall migration over all distances in one direction. In reality, PFAS concentrations in the air differ at different locations from the pollution source, and the migration of different PFAS concentrations from the air to the ground varies. Therefore, the migration at different detection locations needs to be determined separately in practice. It is known that the PFAS concentration at the ground detection location is affected by the PFAS concentration at the air detection location, with this effect manifesting in the vertical direction. Therefore, the migration behavior of PFAS concentration can be reflected by the spatial distribution of PFAS concentrations at the air and ground detection locations and the relationship between their concentrations.

[0083] Specifically, firstly, all aerial detection positions in any direction are projected onto the ground, and any aerial detection position is recorded as the target aerial detection position. Then, the relevant detection position that is the smallest in distance from the target aerial detection position on the ground in the stated direction is obtained, and the target aerial detection position is used as the migration source position of the relevant detection position.

[0084] Then, the ratio of the PFAS concentration at any relevant detection location to the PFAS concentration at the corresponding migration source location is denoted as the migration factor of the relevant detection location; based on the migration factor of the relevant detection location and the migration rate in the corresponding direction of the relevant detection location, the first migration degree of the relevant detection location is calculated, wherein both the migration factor and the migration rate are positively correlated with the migration degree.

[0085] As an optional embodiment, the specific calculation method for the first migration degree of the relevant detection location is as follows:

[0086]

[0087] in, This indicates the first degree of migration at the relevant detection location; This represents the migration rate in the direction corresponding to the relevant detection location; The migration factor represents the relevant detection location.

[0088] It should be noted that the first migration degree is used to describe the degree of migration and change of PFAS concentration at the corresponding detection location. The larger the value of the migration factor, the greater the degree of migration of PFAS concentration at the corresponding detection location. Furthermore, the greater the probability of migration in the direction corresponding to the relevant detection location, the greater the degree of migration of PFAS concentration at the relevant detection location.

[0089] Finally, for any aerial detection position, a second migration degree of the aerial detection position is calculated based on the relative distance between the aerial detection position and the corresponding related detection position, as well as the migration degree of the related detection position.

[0090] As an optional embodiment, for any aerial detection location, the specific method for calculating the second migration degree of the aerial detection location is as follows:

[0091]

[0092] in, This indicates the second degree of migration of the aerial detection location; This represents the projection of the aerial detection position onto the ground and the corresponding first... The distance between each relevant detection location; Indicates the first position corresponding to the aerial detection location. The degree of migration of each relevant detection location; This indicates the number of all relevant detection locations in the direction corresponding to the aerial detection location; This represents the sum of distances between the aerial detection location and all corresponding related detection locations.

[0093] It should be noted that the second migration degree of the aerial detection location is used to describe the degree of migration of PFAS concentration in the corresponding aerial detection location. This is achieved by obtaining the second migration degree of all aerial detection locations and the first migration degree of each relevant detection location, and then obtaining... This indicates the degree to which the PFAS concentration migration at the relevant detection locations reflects the degree to which the PFAS concentration migration occurs at the migration source location. The smaller the distance between the multiple relevant detection locations and their migration source locations projected on the ground, the better the degree of PFAS concentration migration reflects the degree of PFAS concentration migration at the migration source location.

[0094] Thus, the second migration degree of each aerial detection position is obtained through the above method.

[0095] Step S005: Combine the changes in component content in PFAS at relevant detection locations and aerial detection locations, as well as the first migration degree and the second migration degree, to calculate the true migration parameters between the relevant detection locations and the corresponding migration source locations.

[0096] It should be noted that the migration of PFAS in pollutants is affected by the PFAS chain length. Short-chain PFAS are mainly gaseous and can migrate long distances, while long-chain PFAS are mainly particulate-bound and their migration distance is limited. Therefore, the migration performance of PFAS concentration at different detection locations is influenced by the PFAS composition. Thus, in this embodiment of the invention, the actual migration performance is determined by the chain length composition of PFAS at different distances to accurately analyze the pollution source at ground detection locations. After determining the degree of PFAS concentration migration at airborne detection locations and the degree of PFAS concentration migration at related detection locations, it is necessary to further analyze the relationship between the changes in PFAS composition at airborne and related detection locations. The migration performance of PFAS compositions with different chain lengths differs. Long-chain PFAS have limited migration distances, resulting in significant migration differences within local areas. That is, as the distance from the pollution source increases, the migration of long-chain PFAS decreases significantly. Therefore, the difference in the performance of long-chain PFAS at airborne and ground-based detection locations can be used to reflect the actual migration performance at both locations.

[0097] Specifically, firstly, the concentrations of short-chain PFAS and long-chain PFAS in the PFAS concentrations of all aerial detection locations and related detection locations are obtained respectively. The proportion of long-chain PFAS concentration in the total PFAS concentration at any aerial detection location and any related detection location is calculated and denoted as the long-chain proportion. The long-chain proportions of the aerial detection locations and related detection locations are denoted as the first long-chain proportion of the aerial detection location and the second long-chain proportion of the related detection location, respectively. The first long-chain proportions of all aerial detection locations in any direction are sorted in ascending order of their corresponding radii and the resulting sequence is denoted as the aerial long-chain proportion sequence. Similarly, the ground long-chain proportion sequence is obtained. The aerial long-chain proportion sequence and the ground long-chain proportion sequence are collectively referred to as the long-chain proportion sequence.

[0098] Then, any element in the long chain proportion sequence is designated as the target element. The difference between the target element and the long chain proportion corresponding to the previous element in the arbitrary long chain proportion sequence is calculated as the long chain proportion decrease rate of the target element. The long chain proportion decrease rate obtained using the air long chain proportion sequence is designated as the first decrease rate, and the long chain proportion decrease rate obtained using the ground long chain proportion sequence is designated as the second decrease rate.

[0099] Finally, the absolute value of the difference between the second descent rate of the element corresponding to any relevant detection location in the ground long chain proportion sequence and the first descent rate of the element corresponding to the migration source location in the air long chain proportion sequence is obtained, and is denoted as the long chain proportion trend degree of the relevant detection location and the migration source location. Based on the long chain proportion trend degree of the relevant detection location and the migration source location, the first migration degree of the relevant detection location and the second migration degree of the migration source location, the true migration parameters of the relevant detection location and the corresponding migration source location are obtained.

[0100] It should be noted that the long chain proportion trend is used to reflect the consistency in the trend of long chain PFAS concentration in the PFAS concentration at the relevant detection location and the migration source location when the concentration proportion changes.

[0101] As an optional embodiment, for any relevant detection location and its corresponding migration source location, the specific calculation method for the true migration parameter between the relevant detection location and the corresponding migration source location is as follows:

[0102]

[0103] in, This represents the actual migration parameters between the relevant detection location and the corresponding migration source location; This indicates the trend of the proportion of long chains between the relevant detection locations and the migration source locations. Indicates the first degree of migration at the relevant detection location. This indicates the second degree of migration of the aerial detection location.

[0104] It should be noted that the true migration parameters are used to quantify the authenticity of the migration process and distinguish true migration contamination from contamination from other sources. This indicates that long-chain PFAS (such as PFOA and PFOS) migrate short distances, and their concentration percentage should decrease rapidly with distance. The smaller the value, the more consistent the trend of long-chain concentrations in the air and on the ground, reflecting accurate migration. Conversely, the larger the value, the less consistent the trend, potentially indicating interference from other factors. Additionally, the product of migration degree can be used... Amplify the interference effects at locations with high migration intensity, thereby demonstrating The larger the value, the more likely the migration path is to be dominated by non-migration factors.

[0105] Thus, based on the above steps, the true migration parameters of each relevant detection location and the corresponding migration source location are obtained.

[0106] Step S006: Correct the PFAS concentration at the relevant detection location using the actual migration parameters to obtain other source performance parameters at the relevant detection location, and then use the magnitude of other source performance parameters to issue a pollution alarm.

[0107] It should be noted that the PFAS concentration at the actual ground detection location may have different sources. In pollutant protection, it is necessary to understand the source of PFAS in a timely manner in order to formulate precise control measures. The PFAS concentration data collected at the ground detection location in the above process, as well as the actual migration parameters of the relevant detection location and the corresponding migration source location, can reflect the other source performance parameters of the PFAS concentration at the ground detection location.

[0108] First, the true migration parameters of all relevant detection locations and corresponding migration source locations are normalized using a linear normalization function to obtain normalized true migration parameters. The PFAS concentrations of relevant detection locations are then corrected using these normalized true migration parameters to obtain other source performance parameters for the relevant detection locations. These other source performance parameters are negatively correlated with the normalized true migration parameters, while they are positively correlated with the PFAS concentrations.

[0109] As an optional embodiment, for any relevant detection location, the specific calculation method for other source performance parameters of the relevant detection location is as follows:

[0110]

[0111] in, Other source performance parameters indicating the relevant detection location; This represents the actual migration parameters between the relevant detection location and the corresponding migration source location. This indicates the PFAS concentration at the relevant detection location; This represents the linear normalization function.

[0112] Then, the performance parameters of other sources at all relevant detection locations are linearly normalized, and a threshold for the performance parameters is preset. The relevant detection locations corresponding to the normalized performance parameters of other sources being greater than the threshold are taken as ground detection locations with other pollution sources.

[0113] It should be noted that the preset performance parameter threshold is 0.8 based on experience, and can be adjusted according to the actual situation. This embodiment of the invention does not impose specific limitations.

[0114] Finally, ground-based detection locations with other sources of pollution are marked and alerted.

[0115] The above steps complete the detection of the concentration of new pollutants in multiple media.

[0116] Secondly, one embodiment of the present invention provides a precision detection system for new pollutants in multiple media. The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the precision detection method for new pollutants in multiple media.

[0117] The memory can be volatile or non-volatile, or may include both. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which serves as an external cache. Many forms of RAM are available by way of example, but not limitation. Examples include Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Sync Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).

[0118] The aforementioned 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 or transistor logic devices, discrete hardware components, etc. General-purpose processors can be microprocessors or any conventional processor. It is worth noting that the processor can be a processor supporting Advanced Reduced Instruction Set Machines (ARM) architecture.

[0119] 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 principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for accurate detection of new pollutants in multi-medium, characterized in that, The method comprises the following steps: A plurality of detection positions are set around the plant area, and PFAS concentrations are collected at the detection positions, which are divided into ground detection positions and air detection positions; For any detection position, the PFAS concentration of the detection position is corrected based on the distance of the detection position from the plant area and the direction relative to the plant area, and in combination with the difference in PFAS concentration change between detection positions; The correlation of the air detection position and the ground detection position in the direction relative to the plant area is utilized to determine the relevant detection position of the air detection position in the corresponding direction, and the correlation of the PFAS concentrations of the air detection position and the relevant detection position in any direction is utilized to obtain the migration rate in the corresponding direction; The distance between the relevant detection position and the air detection position in any direction, and the difference in PFAS concentration between the relevant detection position and the air detection position are combined to calculate the first migration degree of the relevant detection position and the second migration degree of the air detection position, respectively; The change in the content of the PFAS components of the relevant detection position and the air detection position, and the first migration degree and the second migration degree are combined to calculate the real migration parameter between the relevant detection position and the corresponding migration source position; The PFAS concentration of the relevant detection position is corrected using the real migration parameter to obtain other source performance parameters of the relevant detection position, so that pollution warning is performed using the size of the other source performance parameters; The specific method for correcting the PFAS concentration of the detection position based on the distance of the detection position from the plant area and the direction relative to the plant area, and in combination with the difference in PFAS concentration change between detection positions comprises: The PFAS concentrations at all detection positions with the same radius in any direction are obtained, and the PFAS concentrations at the detection positions are sorted in ascending order of the radius corresponding to the detection positions to obtain a PFAS concentration sequence in the corresponding direction; a window of a preset size is established, and any data point in the PFAS concentration sequence is taken as a center point of the window, and the PFAS concentration sequence is traversed using the window, and the data formed by all data points in the window is recorded as window data during the traversal process; For detection positions with the same radius but different directions, the deviation rate of the data point is calculated according to the difference in data change in the corresponding window data when the data point corresponding to the detection position is taken as the center point of the window; The reciprocal of the deviation rate of each data point is taken as the deviation rate of the data as the weight, and all data points in any PFAS concentration sequence are linearly fitted using the weighted least squares method to obtain the regression value of each data point, and the regression value is taken as the corrected PFAS concentration of the corresponding data point. 2.The method of claim 1, wherein, The specific method for setting a plurality of detection positions around the plant area and collecting PFAS concentrations at the detection positions comprises: Establish a polar coordinate system, take the factory area as the center of the polar coordinate system, obtain the PFAS concentration data of the aerial detection position and the ground detection position at different radii and directions in the polar coordinate system, and divide the PFAS concentration data into short-chain PFAS concentration data and long-chain PFAS concentration data. 3.The method of claim 1, wherein the method comprises, The specific method for obtaining the deviation rate of the data point is as follows: For any window data, the slope of each data point in the window data is obtained, and the average slope of all data points in the window data is taken as the window slope of the data point corresponding to the center point of the window; any data point is taken as a target data point, and the data points corresponding to other detection positions with the same radius but different directions of the detection position corresponding to the target data point are taken as reference data points of the target data point, the absolute value of the difference between the window slopes corresponding to the target data point and any reference data point is taken as the window slope difference between the target data point and the reference data point; The absolute value of the difference between the directions of the detection positions corresponding to the target data point and any reference data point is taken as the detection direction difference between the target data point and the reference data point, and the deviation rate of the target data point is calculated according to the window slope difference and the detection direction difference between the target data point and the reference data point, wherein the window slope difference is positively correlated with the deviation rate, and the detection direction difference is negatively correlated with the deviation rate. 4.The method of claim 1, wherein, The specific method for determining the relevant detection position of the aerial detection position in the corresponding direction by using the correlation of the aerial detection position and the ground detection position in the direction relative to the factory area and obtaining the migration rate of the corresponding direction according to the correlation of the PFAS concentrations of the aerial detection position and the relevant detection position in any direction comprises the following steps: The aerial detection position with the largest radius in the direction corresponding to any aerial detection position is taken as a first aerial detection position, the distance between the first aerial detection position and the center of the polar coordinate system is taken as a first parameter, a second parameter is preset, a horizontal rectangular region with the first parameter as the length and the second parameter as the width is established, the center line of the long side direction of the horizontal rectangular region overlaps the straight line passing through the center and the aerial detection position in any direction, the horizontal rectangular region corresponding to each direction is obtained, the ground detection position in the horizontal rectangular region in any direction is taken as the relevant detection position of the aerial detection position in the same direction, and the PFAS concentrations at the ground detection positions are arranged in the order of the corresponding radii from small to large to obtain a PFAS concentration sequence, which is taken as a ground PFAS concentration sequence; The position relationship between the aerial detection position and the relevant detection position in space in any direction is used, and interpolation is performed on the PFAS concentration of the aerial detection position to obtain a PFAS concentration interpolation sequence in the direction, and the migration rate of the direction is obtained according to the correlation between the PFAS concentration interpolation sequence and the ground PFAS concentration sequence.

5. The method of claim 4, wherein the method is for detecting new pollutants in multi-media. The specific method for obtaining the migration rate of the direction is as follows: A straight line formed by the aerial detection positions in any direction is obtained, denoted as a first straight line, and a related detection position in the direction is obtained, and a perpendicular projection point of the related detection position on the first straight line is taken as an interpolation point, so as to obtain a plurality of interpolation points on the first straight line, the number of the interpolation points being the same as that of the related detection positions, the PFAS concentration corresponding to each interpolation point is obtained according to the PFAS concentrations of all the aerial detection positions in the direction and in combination with a linear interpolation algorithm, the PFAS concentrations of all the interpolation points are sorted in ascending order of the corresponding radii of the interpolation points on the first straight line, so as to obtain a PFAS concentration interpolation sequence, the correlation between the PFAS concentration interpolation sequence in the direction and a ground PFAS concentration sequence is calculated by using a cross-correlation function, and normalization processing is performed on the correlation, so as to obtain a migration rate in the direction.

6. The method of claim 1, wherein the method is for detecting new pollutants in multi-media. The distance between the related detection position and the aerial detection position in any direction, and the difference between the PFAS concentration of the related detection position and the PFAS concentration of the aerial detection position are combined, and the first migration degree of the related detection position and the second migration degree of the aerial detection position are calculated, including the following specific method: Project all the aerial detection positions in any direction on the ground, and take any aerial detection position as a target aerial detection position, obtain a related detection position closest to the projected position of the target aerial detection position on the ground in the direction, and take the target aerial detection position as a migration source position of the related detection position; Take the ratio of the PFAS concentration of any related detection position to the PFAS concentration of the corresponding migration source position as a migration factor of the related detection position; According to the migration factor of the related detection position and the migration rate in the direction corresponding to the related detection position, the first migration degree of the related detection position is calculated, and the migration factor and the migration rate are positively correlated with the migration degree; For any aerial detection position, the second migration degree of the aerial detection position is calculated according to the relative distance between the aerial detection position and the corresponding related detection position and the migration degree of the related detection position.

7. The method of claim 1, wherein the method is for detecting new pollutants in multi-media. The change of the PFAS component content of the related detection position and the aerial detection position is combined, and the first migration degree and the second migration degree are combined, so as to calculate the real migration parameter between the related detection position and the corresponding migration source position, including the following specific method: The short-chain PFAS concentration and the long-chain PFAS concentration in the PFAS concentration of all the aerial detection positions and the related detection positions are obtained respectively, and the proportion of the long-chain PFAS concentration in the PFAS concentration of any aerial detection position and any related detection position is calculated, denoted as a long-chain proportion; The air detection position and the long-chain proportion of the related detection position are recorded as a first long-chain proportion of the air detection position and a second long-chain proportion of the related detection position respectively, the first long-chain proportions of all air detection positions in any direction are sorted in the order of the corresponding radius of the air detection position from small to large to form a sequence, which is recorded as an air long-chain proportion sequence, and a ground long-chain proportion sequence is obtained in the same way, and the air long-chain proportion sequence and the ground long-chain proportion sequence are collectively referred to as a long-chain proportion sequence; Any element in the long-chain proportion sequence is recorded as a target element, the difference between the long-chain proportions corresponding to the target element and the previous element of the target element in any long-chain proportion sequence is calculated as the long-chain proportion drop rate of the target element, the long-chain proportion drop rate obtained by using the air long-chain proportion sequence is recorded as a first drop rate, and the long-chain proportion drop rate obtained by using the ground long-chain proportion sequence is recorded as a second drop rate; The absolute value of the difference between the second drop rate of the corresponding element of any related detection position in the ground long-chain proportion sequence and the first drop rate of the corresponding element of the migration source position corresponding to the related detection position in the air long-chain proportion sequence is recorded as the long-chain proportion trend degree of the related detection position and the migration source position, and the real migration parameter of the related detection position and the corresponding migration source position is obtained according to the long-chain proportion trend degree of the related detection position and the migration source position, the first migration degree of the related detection position and the second migration degree of the migration source position. 8.The method of claim 1, wherein the method is used for multi-medium new pollutant detection. The PFAS concentration of the related detection position is corrected by using the real migration parameter to obtain other source performance parameters of the related detection position, so that the size of the other source performance parameters is used for pollution warning, and the specific method comprises: The real migration parameters of the related detection position and the corresponding migration source position are normalized by using a linear normalization function to obtain normalized real migration parameters, the PFAS concentration of the related detection position is corrected by using the normalized real migration parameters to obtain other source performance parameters of the related detection position, wherein the other source performance parameters are negatively correlated with the normalized real migration parameters, and the other source performance parameters are positively correlated with the PFAS concentration; The other source performance parameters of all related detection positions are linearly normalized, and a performance parameter threshold is preset, and the related detection position corresponding to the normalized other source performance parameter greater than the performance parameter threshold is taken as a ground detection position with other pollution sources; The ground detection position with other pollution sources is marked and warned. 9.A multi-medium new pollutant-oriented accurate detection system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the steps of the method of any one of claims 1-8.

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