Distribution rule analysis method for specific pollutants of polluted land parcels

Abstract

The invention discloses a distribution rule analysis method for characteristic pollutants of a polluted land parcel, and relates to the technical field of environmental monitoring and pollution abatement, the analysis method comprises the following specific steps: S100, sample collection and pretreatment: collecting a soil or water sample according to a collection rule. Precise identification and concentration determination of specific pollutants of polluted land parcels are realized, and the problems of tedious operation, long time consumption and insufficient sensitivity often exist in a traditional pollutant detection method, however, absorption and scattering spectrum data of soil and water body samples can be rapidly obtained by utilizing unique properties of a terahertz spectrum, so that the detection accuracy of the pollutants in the polluted land parcels is improved. The method has the advantages that the method is simple in operation, the characteristic pollutant types in the sample can be accurately identified by comparing the characteristic pollutant types with the standard spectrum database, the concentration of each pollutant in the sample can be further calculated by utilizing the spectrum concentration interaction polynomial model, and accurate data support is provided for treatment and restoration of polluted land parcels.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring and pollution control technology, specifically to a method for analyzing the distribution patterns of characteristic pollutants in polluted sites. Background Technology

[0002] With the acceleration of industrialization and the expansion of urbanization, environmental pollution problems are becoming increasingly serious. In particular, soil and water pollution has become a global concern. In the process of environmental pollution control and remediation, accurately analyzing the distribution patterns of characteristic pollutants in polluted sites is a prerequisite for formulating scientific control plans. However, polluted sites are often large in area, complex in composition, and contain a wide variety of pollutants. Traditional pollutant detection methods are difficult to meet the needs of efficient and accurate detection, which provides the technical background for the development of this invention.

[0003] Traditional technologies have several shortcomings when it comes to detecting characteristic pollutants in contaminated sites. Firstly, traditional methods such as chemical analysis and biomonitoring often require complex sample pretreatment and cumbersome experimental procedures, which are not only time-consuming but also costly. Secondly, traditional methods have limitations in sensitivity and accuracy, making it difficult to accurately identify and determine the concentration of pollutants. This, to some extent, hinders the progress of environmental pollution control and remediation efforts. Furthermore, traditional methods fail to visually represent the spatial distribution characteristics and migration and diffusion patterns of pollutants, making it difficult to formulate targeted remediation measures.

[0004] Therefore, a method for analyzing the distribution patterns of characteristic pollutants in contaminated sites was developed, which enables efficient and accurate identification and concentration measurement of characteristic pollutants in contaminated sites. At the same time, it can intuitively show the spatial distribution characteristics and migration and diffusion patterns of pollutants, providing strong technical support for environmental pollution control and remediation. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a method for analyzing the distribution patterns of characteristic pollutants in contaminated sites. This method integrates multiple technical aspects, including terahertz spectroscopy measurement, spectral data analysis, imaging system construction and debugging, and distribution pattern analysis and visualization. By employing terahertz spectroscopy technology, it achieves efficient and accurate identification of characteristic pollutants in soil and water samples and can construct a three-dimensional distribution model of pollutants. Furthermore, combined with a comprehensive map generated using GIS technology, it provides strong data support and decision-making basis for the treatment and remediation of environmental pollution.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for analyzing the distribution patterns of characteristic pollutants in contaminated sites, the specific steps of which are as follows:

[0007] S100, Sample collection and pretreatment: Collect soil or water samples according to the collection rules, and record the information and number in detail. Soil samples are stored after being air-dried, impurities removed, ground and sieved. Water samples are stored under cold storage after being filtered and protected with a preservative.

[0008] S200, Terahertz Spectroscopy Measurement: After calibrating the terahertz spectrometer, the monitoring parameters are set according to the characteristics of pollutants and the performance of the instrument. The pretreated soil sample is evenly spread and fixed, covered with matching liquid, and then measured multiple times. After the water sample is injected into the sample cell and the air bubbles are removed, it is measured multiple times according to the same procedure. The data quality is monitored in real time during the measurement process, and the terahertz absorption and scattering spectrum data of soil and water samples are recorded and saved.

[0009] S300, Spectral Data Analysis and Pollutant Identification: The measured terahertz spectral data is baseline corrected using a dynamic baseline correction formula. A database covering the terahertz spectral characteristics of various pollutants under different concentrations and environmental conditions is established. The preprocessed sample spectral data is compared with the standard spectra in the database using the spectral similarity index to identify the types of characteristic pollutants present in the sample. Based on the spectral data, the concentration of each pollutant in the sample is calculated using the spectral concentration interaction polynomial model.

[0010] S400, Imaging System Setup and Debugging: Build a terahertz imaging system that includes a terahertz radiation source, detector, and optical imaging components. Debug each component, adjust the position and angle of the optical components, calibrate the spatial resolution, set the parameters of the data acquisition and processing module, and determine the parameters of the imaging area, scanning step size, and imaging frequency according to the actual situation of the contaminated site. Build a pollution distribution image based on the information scanned by the imaging system.

[0011] S500, Distribution Pattern Analysis and Visualization: It integrates spectral concentration data with distribution images, and uses image processing and analysis software to analyze the spatial distribution characteristics, concentration gradients, and aggregation areas of pollutants. It combines geological structures to infer migration and diffusion patterns and interrelationships, analyzes influencing factors, establishes models, and generates comprehensive maps using GIS technology.

[0012] Furthermore, in S100, the collection rules in sample collection and preprocessing are as follows:

[0013] Sampling point setup: For large contaminated areas, use the zonal sampling method and professional judgment method; for small areas with uniform pollution distribution, use the systematic random sampling method; for areas with obvious pollution gradients, increase the sampling point density along the direction of the pollution gradient in areas where pollution changes are obvious.

[0014] Sampling methods: For surface soil, the hardened surface layer should be removed before sampling. When collecting deep soil, a column sampler should be used to drill vertically into the soil and collect samples from different layers at the specified depth.

[0015] Sampling Depth and Quantity: Soil: Topsoil samples should be collected from 0 to 0.5 meters. Samples from deeper soil layers below 0.5 meters should be collected using a judgment-based sampling method. Sampling intervals between 0.5 and 6 meters should not exceed 2 meters. At least one soil sample should be collected from each soil layer of different properties, and at least one soil sampling point should be set up near the groundwater level. If the thickness of a soil layer of the same property is large or obvious signs of pollution are observed, additional sampling points should be added at that layer as needed. 3-5 parallel samples should be collected at each depth for each sampling point. Groundwater: Generally, groundwater sampling depth should be 0.5 meters below the water surface of the monitoring well. For groundwater contaminated with low-density non-water-soluble organic pollutants, sampling should be conducted at the top of the aquifer; for groundwater contaminated with high-density non-water-soluble organic pollutants, sampling should be conducted at the bottom of the aquifer. 1-3 liters of water sample should be collected at each sampling location.

[0016] Furthermore, the formula for calculating the soil terahertz absorption spectrum in the S200 terahertz spectroscopy measurement is as follows: ,in, It is the high Hertz absorption spectrum of soil. For frequency, The intensity of transmitted light. The incident light intensity For soil porosity, It is a constant related to the effect of porosity on the absorption spectrum; the formula for calculating the terahertz scattering spectrum of soil is: ,in, It is the high Hertz scattering spectrum of soil. The intensity of the scattered light. It is the first The average particle size of soil particles in the specified particle size range It is the average particle size of soil particles across all particle size ranges. It is the first Mass fraction of soil particles within a certain size range It refers to the number of particle size ranges. It is a constant related to soil scattering characteristics.

[0017] Furthermore, in S200, the formula for calculating the terahertz absorption spectrum of water in the terahertz spectroscopy measurement is as follows: ,in, It is the terahertz absorption spectrum of water. The intensity of transmitted light from the water sample. The intensity of incident light on the water sample. It is the actual temperature of the water. This is a reference temperature. It is a constant related to the effect of temperature on the absorption spectrum; the formula for calculating the terahertz scattering spectrum of water is: ,in It is the terahertz scattering spectrum of water. The intensity of the scattered light from the water sample. It is the total content of dissolved gases in water. It refers to the dissolved gas content. and It is a constant related to the water scattering properties.

[0018] Furthermore, in S300, during spectral data analysis and pollutant identification, baseline correction is performed on the measured terahertz spectral data using a dynamic baseline correction formula, which is: ,in, This is the corrected baseline function, where R is the abscissa of the spectral data. This is the initial baseline value. It is the attenuation coefficient. It is the offset of the baseline.

[0019] Furthermore, in step S300, the spectral data analysis and pollutant identification process uses a spectral similarity index to compare the preprocessed sample spectral data with standard spectra in the database to calculate and identify the types of characteristic pollutants present in the sample. Let the sample spectral data vector be... The standard spectral data vector of a certain pollutant in the database is The formula is: ,in and These are the average values ​​of the sample spectrum and the standard spectrum, respectively. and It is a weighting coefficient. When the calculated Sim value is greater than the threshold of 0.7, it is considered that the sample contains a characteristic pollutant species corresponding to the standard spectrum.

[0020] Furthermore, in S300, during spectral data analysis and pollutant identification, the concentration of each pollutant in the sample is calculated based on the spectral data using a spectral concentration interaction polynomial model. Let the spectral data contain n features, namely... The pollutant concentration is C, and the model construction formula is: ,in It is a constant term. Spectral characteristics The coefficient of the first term, Spectral characteristics and Interaction term coefficients , Spectral characteristics of Secondary coefficient , It is a feature The highest power.

[0021] Furthermore, the specific steps for building a soil pollution distribution image during the setup and debugging of the imaging system in S400 are as follows:

[0022] (1) Install a terahertz imaging system on the contaminated site, initialize each component of the system, and set the parameters of the radiation source power, detector sensitivity and data acquisition device.

[0023] (2) Select the scanning mode based on the characteristics of the land parcel, plan the scanning path, and clarify the starting point and the traversal order of each scanning point;

[0024] (3) At each scanning point, a terahertz wave is emitted by a radiation source to penetrate the soil. The detector receives the reflected wave and converts it into an electrical signal, and records the signal and corresponding coordinate information simultaneously.

[0025] (4) Process the collected data according to the electrical signal strength. Mapping a two-dimensional image plane, the grayscale value of each pixel in the image. The calculation formula is: , and These are grayscale mapping parameters. A three-dimensional distribution model of pollutants in the soil is constructed using a layer-by-layer scanning algorithm. Let K layers be scanned, and the thickness of each layer be... Then the image data of the w-th layer is , Three-dimensional image data is represented by a three-dimensional array. It means that, among them .

[0026] Furthermore, the specific steps for building a water pollution distribution image during the setup and debugging of the imaging system in S400 are as follows:

[0027] (1) Determine the installation depth of the imaging probe in the groundwater monitoring well, and adjust the probe emission angle according to the radius of the monitoring well and the length of the target detection area;

[0028] (2) The probe emits terahertz waves into the groundwater. The waves propagate in the water, interact with pollutants, and are received by the probe. The signals are collected in real time at a set frequency and transmitted to the host.

[0029] (3) Amplify the weak electrical signals collected, remove noise through a filter, and convert the continuous analog signal into a discrete digital signal;

[0030] (4) The processed signal data is mapped to a two-dimensional plane according to the algorithm to generate a two-dimensional image. Let the horizontal coordinate be x and the vertical coordinate be y on the two-dimensional plane, and let the gray value of each pixel be... The calculation formula is: Where S is the signal strength, and As mapping parameters, data from different layers is acquired through scanning with multiple probes. A linear interpolation algorithm is then used to generate a 3D image. For data from adjacent layers... and ,exist grayscale value of interpolation points in the direction Represented as: , and The z-coordinates are the z-coordinates of two adjacent layers.

[0031] Furthermore, in S500, the distribution pattern analysis and visualization process fuses spectral concentration data with the distribution image through a concentration-related three-dimensional coordinate mapping formula. Let the three-dimensional pixel coordinates of the terahertz imaging image be... Imaging system in , , The pixel dimensions in the directions are respectively , , The initial coordinates of the image in three-dimensional space are For the sampling points in spectral analysis, their coordinates are... Concentration value Pixels Corresponding actual geographic coordinates The calculation formula is: , , ,in , , The images are respectively in , , Maximum number of pixels in the direction, , , This is a coefficient related to the influence of concentration on coordinates. For concentration fusion, let the concentration values ​​of the 26 neighboring pixels (in three-dimensional space) around the sampling point be respectively... , Then pixel Fusion concentration value for: .

[0032] Compared with existing technologies, this method for analyzing the distribution patterns of characteristic pollutants in contaminated sites has the following advantages:

[0033] I. This invention, by introducing terahertz spectroscopy technology, achieves accurate identification and concentration determination of characteristic pollutants in contaminated sites. Traditional pollutant detection methods often suffer from cumbersome operation, long processing time, and insufficient sensitivity. However, this invention utilizes the unique properties of terahertz spectroscopy to quickly acquire absorption and scattering spectral data of soil and water samples. By comparing these data with standard spectral databases, it accurately identifies the types of characteristic pollutants present in the samples. Furthermore, using a spectral concentration interaction polynomial model, it can further calculate the concentration of each pollutant in the sample, providing precise data support for the remediation and restoration of contaminated sites.

[0034] Second, this invention, by constructing an imaging system encompassing terahertz radiation sources, detectors, and optical imaging components, and by finely adjusting each component, can acquire high-quality images of contaminated site distribution. Based on this, by fusing spectral concentration data with distribution images, it further analyzes the spatial distribution characteristics, concentration gradients, and aggregation areas of pollutants. Combined with geological structures, it infers the migration and diffusion patterns and interrelationships of pollutants. This not only helps researchers to more intuitively understand the pollution status of contaminated sites, but also provides strong support for relevant departments to formulate scientific and reasonable remediation plans.

[0035] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0037] Figure 1 This is a flowchart of a method for analyzing the distribution patterns of characteristic pollutants in contaminated sites;

[0038] Figure 2 This is a flowchart illustrating a method for analyzing the distribution patterns of characteristic pollutants in contaminated sites. Detailed Implementation

[0039] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0040] Example 1:

[0041] Analysis of the distribution patterns of characteristic pollutants in a certain industrial contaminated soil plot

[0042] Sample Collection and Pretreatment: Given the large area of ​​this industrial contaminated site, a zoning and sampling method, along with expert judgment, was employed. For surface soil, the hardened surface layer was removed before sampling. For deeper soil samples, a columnar sampler was used to drill vertically into the soil, collecting samples from different layers at the prescribed depths. Samples were collected from the 0-0.5 meter surface soil layer, and from depths below 0.5 meters using a judgment-based sampling method. Sampling intervals between 0.5-6 meter layers were no more than 2 meters. At least one soil sample was collected from each soil layer with different properties, and at least one soil sampling point was set up near the groundwater level. If a layer of the same soil type was thick or showed obvious signs of contamination, additional sampling points were added at that layer as needed. 3-5 parallel samples were collected at each depth from each sampling point. After collection, the soil samples were air-dried, impurities removed, ground, sieved, and properly stored, with detailed information and numbering recorded.

[0043] Terahertz spectroscopy measurement: The pretreated soil sample was evenly spread and fixed, covered with matching solution, and multiple measurements were performed using a terahertz spectrometer. Data quality was monitored in real time during the measurement process, and the terahertz absorption and scattering spectral data of the soil sample were recorded and saved. The formula for calculating the soil terahertz absorption spectrum is as follows: The formula for calculating the terahertz scattering spectrum of soil is: .

[0044] Spectral data analysis and pollutant identification: Baseline correction is performed on the measured terahertz spectral data using a dynamic baseline correction method, with the following formula: By utilizing a database covering the spectral characteristics of various pollutants, the preprocessed sample spectral data is compared with standard spectra in the database using a spectral similarity index to identify the types of characteristic pollutants present in the samples. Let the sample spectral data vector be... The standard spectral data vector of a certain pollutant in the database is The formula is: When the calculated Sim value is greater than the threshold of 0.7, it is considered that the sample contains characteristic pollutants corresponding to the standard spectrum, such as heavy metal pollutants or organic pollutants. The concentration of each pollutant in the sample is then calculated based on the spectral data. The model construction formula is as follows: , .

[0045] Imaging System Setup and Debugging: A terahertz imaging system was installed on the contaminated site. All system components were initialized, relevant parameters were set, a suitable scanning mode was selected based on the site characteristics, the scanning path was planned, and the starting point and the traversal order of each scanning point were determined. At each scanning point, a terahertz wave was emitted from a radiation source to penetrate the soil. The detector received the reflected wave and converted it into an electrical signal, simultaneously recording the signal and corresponding coordinate information. The collected data was processed based on the electrical signal strength. Mapping a two-dimensional image plane, the grayscale value of each pixel in the image. The calculation formula is: A three-dimensional distribution model of pollutants in soil was constructed using a layer-by-layer scanning algorithm. Assume K layers were scanned, each with a thickness of [missing information]. Then the image data of the w-th layer is Three-dimensional image data is represented by a three-dimensional array. It means that among them .

[0046] Distribution Pattern Analysis and Visualization: Spectral concentration data is fused with distribution images. Let the three-dimensional pixel coordinates of the terahertz imaging image be... Imaging system in , , The pixel dimensions in the directions are respectively , , The initial coordinates of the image in three-dimensional space are For the sampling points in spectral analysis, their coordinates are... Concentration value , pixels Corresponding actual geographic coordinates The calculation formula is: , , Let the concentration values ​​of the 26 neighboring pixels (in three-dimensional space) around the sampling point be respectively , Then pixel Fusion concentration value for: Using image processing and analysis software, the spatial distribution characteristics, concentration gradients, and aggregation areas of pollutants in the soil are analyzed. Combined with the geological structure of the site, the migration and diffusion patterns and interrelationships of pollutants are inferred. Influencing factors are analyzed and models are established. Finally, visualization technology is used to present the distribution patterns, and a comprehensive map is generated using GIS technology to intuitively display the pollution status.

[0047] In summary, this invention, in the sample collection stage, employs appropriate sampling methods and site selection based on the characteristics of the land parcel to obtain soil and water samples. In terahertz spectroscopy measurement, it accurately calculates the absorption and scattering spectra of soil and water using formulas. By leveraging dynamic baseline correction and spectral comparison, it identifies pollutant types and calculates concentrations. Through careful construction and debugging of the imaging system, it constructs distribution images of pollutants in soil and water. Finally, it integrates spectral concentration and image data, and combines geological structure analysis to identify migration and diffusion patterns. This invention achieves a complete innovation from sample collection to pattern presentation, laying a solid foundation for the precise remediation of contaminated sites.

[0048] Example 2:

[0049] Analysis of the distribution patterns of characteristic pollutants in a polluted water body area

[0050] Sample Collection and Pretreatment: For contaminated water areas, the sampling depth is determined based on the water depth. If the water depth is less than 5 meters, samples are taken from the surface and bottom layers; if the water depth is between 5 and 10 meters, samples are taken from the surface, middle, and bottom layers. For groundwater contaminated with low-density non-water-soluble organic pollutants, the sampling location should be set at the top of the aquifer; for groundwater contaminated with high-density non-water-soluble organic pollutants, the sampling location should be set at the bottom of the aquifer. 1-3 liters of water sample are collected from each sampling location. After collection, the water samples are filtered, protected with a preservative, and then refrigerated. Detailed information is recorded and numbered.

[0051] Terahertz spectroscopy measurement: After injecting the water sample into the sample cell and removing air bubbles, the sample is measured multiple times using a terahertz spectrometer according to the prescribed procedure. Data quality is closely monitored during the measurement process. The terahertz absorption and scattering spectral data of the water sample are recorded and saved. The formula for calculating the terahertz absorption spectrum of water is: The formula for calculating the terahertz scattering spectrum of water is: .

[0052] Spectral data analysis and pollutant identification: Terahertz spectral data are processed using dynamic baseline correction, with the following formula: Based on existing pollutant spectral databases, the pretreated spectral data of water samples are compared with standard spectra. Let the sample spectral data vector be... The standard spectral data vector of a certain pollutant in the database is The formula is: When the calculated Sim value is greater than the threshold of 0.7, it is considered that the sample contains a characteristic pollutant species corresponding to the standard spectrum. The characteristic pollutants in the water, such as certain chemical substances or microbial metabolites, are identified using the spectral similarity index, and their concentrations are calculated based on the spectral data using the following formula: , .

[0053] Imaging System Setup and Debugging: Determine the installation depth of the imaging probe in the groundwater monitoring well. Based on the well radius and the length of the target detection area, adjust the probe's emission angle. The probe emits terahertz waves into the groundwater. After receiving the reflected waves, the weak electrical signals are amplified, noise is removed by a filter, and the signals are converted into discrete digital signals. The processed signal data is then mapped onto a two-dimensional plane according to an algorithm to generate a two-dimensional image. Let the x-axis be the horizontal coordinate and the y-axis be the vertical coordinate on the two-dimensional plane, and let the grayscale value of each pixel be... The calculation formula is: Where S is the signal strength, and As mapping parameters, data from different layers is acquired through scanning with multiple probes. A linear interpolation algorithm is then used to generate a 3D image. For data from adjacent layers... and ,exist grayscale value of interpolation points in the direction Represented as: , and The z-coordinates are the z-coordinates of two adjacent layers.

[0054] Distribution Pattern Analysis and Visualization: This involves fusing spectral concentration data with images of pollutant distribution in water bodies. The three-dimensional pixel coordinates of the terahertz imaging image are given. Imaging system in , , The pixel dimensions in the directions are respectively , , The initial coordinates of the image in three-dimensional space are For the sampling points in spectral analysis, their coordinates are... Concentration value , pixels Corresponding actual geographic coordinates The calculation formula is: , , Let the concentration values ​​of the 26 neighboring pixels (in three-dimensional space) around the sampling point be respectively , then pixels Fusion concentration value for: By using specialized software to analyze the spatial distribution and concentration trends of pollutants in water bodies, and combining this with the geological and water flow conditions around the water bodies, we can infer the migration paths and diffusion ranges of pollutants. We can also analyze influencing factors and build models, present the distribution patterns through visualization technology, and generate comprehensive maps using GIS technology, thus providing strong support for pollution control.

[0055] In summary, this invention establishes strict rules and calculation models for different types of land parcels and samples during the sampling and spectral analysis stages to ensure the reliability and representativeness of the data. The construction and debugging of the imaging system provides an intuitive display of pollutant distribution. Its unique scanning, signal processing, and image generation methods can be effectively applied in both soil and water environments. The overall method achieves the integration of multiple technologies, from microscopic spectral identification to macroscopic distribution pattern analysis, bringing new breakthroughs and practical tools to the field of environmental monitoring and pollution control.

[0056] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for analyzing the distribution patterns of characteristic pollutants in contaminated sites, characterized in that, The specific steps of this analysis method are as follows: S100, Sample collection and pretreatment: Collect soil or water samples according to the collection rules, and record the information and number in detail. Soil samples are stored after being air-dried, impurities removed, ground and sieved. Water samples are stored under cold storage after being filtered and protected with a preservative. S200, Terahertz Spectroscopy Measurement: After calibrating the terahertz spectrometer, the monitoring parameters are set according to the characteristics of pollutants and the performance of the instrument. The pretreated soil sample is evenly spread and fixed, covered with matching liquid, and then measured multiple times. After the water sample is injected into the sample cell and the air bubbles are removed, it is measured multiple times according to the same procedure. The data quality is monitored in real time during the measurement process, and the terahertz absorption and scattering spectrum data of soil and water samples are recorded and saved. S300, Spectral Data Analysis and Pollutant Identification: The measured terahertz spectral data is baseline corrected using a dynamic baseline correction formula. A database covering the terahertz spectral characteristics of various pollutants under different concentrations and environmental conditions is established. The preprocessed sample spectral data is compared with the standard spectra in the database using the spectral similarity index to identify the types of characteristic pollutants present in the sample. Based on the spectral data, the concentration of each pollutant in the sample is calculated using the spectral concentration interaction polynomial model. S400, Imaging System Setup and Debugging: Build a terahertz imaging system that includes a terahertz radiation source, detector, and optical imaging components. Debug each component, adjust the position and angle of the optical components, calibrate the spatial resolution, set the parameters of the data acquisition and processing module, and determine the parameters of the imaging area, scanning step size, and imaging frequency according to the actual situation of the contaminated site. Build a pollution distribution image based on the information scanned by the imaging system. S500, Distribution Pattern Analysis and Visualization: It integrates spectral concentration data with distribution images, and uses image processing and analysis software to analyze the spatial distribution characteristics, concentration gradients, and aggregation areas of pollutants. It combines geological structures to infer migration and diffusion patterns and interrelationships, analyzes influencing factors, establishes models, and generates comprehensive maps using GIS technology.

2. The method for analyzing the distribution patterns of characteristic pollutants in contaminated sites according to claim 1, characterized in that, In step S100, the sampling rules for sample collection and preprocessing are as follows: Sampling point setup: For large contaminated areas, a zoned sampling method and professional judgment method are used; For small plots with uniform pollution distribution, a systematic random sampling method is used; for plots with obvious pollution gradients, the sampling point density is increased along the direction of the pollution gradient in areas where pollution changes are obvious. Sampling methods: For surface soil, the hardened surface layer should be removed before sampling. When collecting deep soil, a column sampler should be used to drill vertically into the soil and collect samples from different layers at the specified depth. Sampling depth and quantity: Soil: Topsoil samples should be collected from 0 to 0.5 meters. Soil samples from depths below 0.5 meters should be collected using a sampling method based on judgment. Soil sampling intervals between 0.5m and 6m depths should not exceed 2m. At least one soil sample should be collected from each soil layer of different properties, and at least one soil sampling point should be set up near the groundwater level. When the thickness of a soil layer of the same property is large or obvious signs of pollution are observed, additional sampling points should be added at that layer as needed. 3-5 parallel samples should be collected at each depth for each sampling point. For groundwater: Generally, the sampling depth for groundwater samples should be 0.5m below the water surface of the monitoring well. For groundwater contaminated with low-density non-water-soluble organic pollutants, the sampling location should be at the top of the aquifer; for groundwater contaminated with high-density non-water-soluble organic pollutants, the sampling location should be at the bottom of the aquifer, and 1-3 liters of water sample should be collected at each sampling location.

3. The method for analyzing the distribution patterns of characteristic pollutants in contaminated sites according to claim 1, characterized in that, The formula for calculating the soil terahertz absorption spectrum in the S200 terahertz spectroscopy measurement is as follows: ,in, It is the high Hertz absorption spectrum of soil. For frequency, The intensity of transmitted light. The incident light intensity For soil porosity, It is a constant related to the effect of porosity on the absorption spectrum; the formula for calculating the terahertz scattering spectrum of soil is: ,in, It is the high Hertz scattering spectrum of soil. The intensity of the scattered light. It is the first The average particle size of soil particles within the specified particle size range It is the average particle size of soil particles across all particle size ranges. It is the first Mass fraction of soil particles within a certain size range It refers to the number of particle size ranges. It is a constant related to soil scattering characteristics.

4. The method for analyzing the distribution patterns of characteristic pollutants in contaminated sites according to claim 1, characterized in that, The formula for calculating the terahertz absorption spectrum of water in the S200 terahertz spectroscopy measurement is as follows: ,in, It is the terahertz absorption spectrum of water. The intensity of transmitted light from the water sample. The intensity of incident light on the water sample. It is the actual temperature of the water. This is a reference temperature. It is a constant related to the effect of temperature on the absorption spectrum; the formula for calculating the terahertz scattering spectrum of water is: ,in It is the terahertz scattering spectrum of water. The intensity of the scattered light from the water sample. It is the total content of dissolved gases in water. It refers to the dissolved gas content. and It is a constant related to the water scattering properties.

5. The method for analyzing the distribution patterns of characteristic pollutants in contaminated sites according to claim 1, characterized in that, In S300, during spectral data analysis and pollutant identification, baseline correction is performed on the measured terahertz spectral data using a dynamic baseline correction formula, which is: ,in, This is the corrected baseline function, where R is the abscissa of the spectral data. This is the initial baseline value. It is the attenuation coefficient. It is the offset of the baseline.

6. The method for analyzing the distribution patterns of characteristic pollutants in contaminated sites according to claim 1, characterized in that, In step S300, the spectral data analysis and pollutant identification process uses a spectral similarity index to compare the preprocessed sample spectral data with standard spectra in the database to calculate and identify the types of characteristic pollutants present in the sample. Let the sample spectral data vector be... The standard spectral data vector of a certain pollutant in the database is The formula is: ,in and These are the average values ​​of the sample spectrum and the standard spectrum, respectively. and It is a weighting coefficient. When the calculated Sim value is greater than the threshold of 0.7, it is considered that the sample contains a characteristic pollutant species corresponding to the standard spectrum.

7. The method for analyzing the distribution patterns of characteristic pollutants in contaminated sites according to claim 1, characterized in that, In step S300, during spectral data analysis and pollutant identification, the concentration of each pollutant in the sample is calculated using a spectral concentration interaction polynomial model based on the spectral data. Let the spectral data contain n features, namely... The pollutant concentration is C, and the model construction formula is: ,in It is a constant term. Spectral characteristics The coefficient of the first term, Spectral characteristics and Interaction term coefficients , Spectral characteristics of Secondary coefficient , It is a feature The highest power.

8. The method for analyzing the distribution patterns of characteristic pollutants in contaminated sites according to claim 1, characterized in that, The specific steps for building a soil pollution distribution image during the setup and debugging of the S400 imaging system are as follows: (1) Install a terahertz imaging system on the contaminated site, initialize each component of the system, and set the parameters of the radiation source power, detector sensitivity and data acquisition device. (2) Select the scanning mode based on the characteristics of the land parcel, plan the scanning path, and clarify the starting point and the traversal order of each scanning point; (3) At each scanning point, a terahertz wave is emitted by a radiation source to penetrate the soil. The detector receives the reflected wave and converts it into an electrical signal, and records the signal and corresponding coordinate information simultaneously. (4) Process the collected data according to the electrical signal strength. Mapping a two-dimensional image plane, the grayscale value of each pixel in the image. The calculation formula is: , and These are grayscale mapping parameters. A three-dimensional distribution model of pollutants in the soil is constructed using a layer-by-layer scanning algorithm. Let K layers be scanned, and the thickness of each layer be... Then the image data of the w-th layer is , Three-dimensional image data is represented by a three-dimensional array. It means that, among them .

9. The method for analyzing the distribution patterns of characteristic pollutants in contaminated sites according to claim 1, characterized in that, The specific steps for building a water pollution distribution image during the setup and debugging of the imaging system in S400 are as follows: (1) Determine the installation depth of the imaging probe in the groundwater monitoring well, and adjust the probe emission angle according to the radius of the monitoring well and the length of the target detection area; (2) The probe emits terahertz waves into the groundwater. The waves propagate in the water, interact with pollutants, and are received by the probe. The signals are collected in real time at a set frequency and transmitted to the host. (3) Amplify the acquired weak electrical signals, remove noise through filters, and convert the continuous analog signals into discrete digital signals; (4) The processed signal data is mapped to a two-dimensional plane according to the algorithm to generate a two-dimensional image. Let the horizontal coordinate be x and the vertical coordinate be y on the two-dimensional plane, and let the gray value of each pixel be... The calculation formula is: Where S is the signal strength, and As mapping parameters, data from different layers is acquired through scanning with multiple probes. A linear interpolation algorithm is then used to generate a 3D image. For data from adjacent layers... and ,exist grayscale value of interpolation points in the direction Represented as: , and The z-coordinates are the z-coordinates of two adjacent layers.

10. The method for analyzing the distribution patterns of characteristic pollutants in contaminated sites according to claim 1, characterized in that, In the S500 process, the distribution pattern analysis and visualization fuses spectral concentration data with the distribution image using a concentration-related three-dimensional coordinate mapping formula. Let the three-dimensional pixel coordinates of the terahertz imaging image be... Imaging system in , , The pixel dimensions in the directions are respectively , , The initial coordinates of the image in three-dimensional space are For the sampling points in spectral analysis, their coordinates are... Concentration value , pixels Corresponding actual geographic coordinates The calculation formula is: , , ,in , , The images are in , , Maximum number of pixels in the direction, , , This is a coefficient related to the influence of concentration on coordinates. For concentration fusion, let the concentration values ​​of the 26 neighboring pixels (in three-dimensional space) around the sampling point be respectively... , Then pixel Fusion concentration value for: .

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