A soil microplastic detection method, device, equipment and medium

Abstract

The application discloses a kind of soil microplastic detection method, device, equipment and medium, comprising: obtaining several soil samples in target area, and determine the soil parameters of soil sample;According to the soil parameters, the target area is divided, and first area and second area are obtained;The soil sample of first area is pretreated, and microplastic sample is obtained;The microplastic sample is analyzed, and the microplastic parameter corresponding to the microplastic sample is obtained;According to the microplastic parameter, determine the migration risk;According to the migration risk and the area of first area, determine the detection interval period of the soil microplastic of target area.The application belongs to the field of microplastic detection.The application can accurately determine the microplastic detection period.

Description

Technical Field

[0001] This invention relates to the field of microplastic detection, and more particularly to a method, apparatus, equipment, and medium for detecting soil microplastics. Background Technology

[0002] With the increasing severity of microplastic pollution, its occurrence and migration risks in the soil environment have attracted widespread attention. Traditional detection methods often involve uniform sampling of the target area, neglecting the heterogeneity of soil physical structure and the non-uniformity of pollutant spatial distribution, resulting in low monitoring efficiency and delayed risk warnings. Furthermore, the microplastic detection process is cumbersome; excessively high detection frequency wastes significant human and material resources, while low detection frequency fails to provide timely assessment of soil conditions.

[0003] The relevant patent document CN202410501202.8 also provides a method for adjusting the frequency, but it only compares and adjusts based on the comprehensive indicator value of soil microplastic migration, and does not provide specific adjustment methods. Therefore, there is an urgent need for an intelligent detection method to improve the accuracy of soil microplastic monitoring. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and medium for detecting microplastics in soil, which solves the technical problem of unreasonable microplastic detection cycles in the prior art and achieves the technical effect of improving the rationality of microplastic detection cycles.

[0005] In a first aspect, the present invention provides a method for detecting soil microplastics, comprising:

[0006] Acquire several soil samples from the target area and determine the soil parameters of the soil samples, including soil particle size and pore size;

[0007] Based on soil parameters, the target area is divided into a first area and a second area, where the first area is the outer area of ​​the second area.

[0008] Soil samples from the first region were pretreated to obtain microplastic samples;

[0009] The microplastic samples were analyzed to obtain the corresponding microplastic parameters, including microplastic particle size and microplastic abundance.

[0010] Determine migration risk based on microplastic parameters;

[0011] The detection interval for soil microplastics in the target area is determined based on the migration risk and the area of ​​the first region.

[0012] Furthermore, based on microplastic parameters, migration risks are determined, including:

[0013] ,

[0014] in, To mitigate migration risks, The abundance of microplastics after dimensionless scaling. This is the reference particle size for microplastics. For microplastic particle size, This is an empirical coefficient. .

[0015] Furthermore, based on the migration risk and the area of ​​the first region, the detection interval for soil microplastics in the target area is determined, including:

[0016] ,

[0017] in, The detection interval period, For standard cycles, For adjustment coefficients, , To mitigate the risks of standard migration, The area of ​​the first region. This is a historical experience coefficient. The area of ​​the target region.

[0018] Furthermore, based on soil parameters, the target area is divided into a first region and a second region, including:

[0019] ,

[0020] in, The width of the first region. To preset standard width, as well as All are preset weights. Standard soil particle size, The soil particle size of the soil sample. The pore size of the soil sample. Standard pore size;

[0021] Using the boundary of the target region as the boundary, extend inward by the width of the first region to obtain the first region, and take the part of the target region other than the first region as the second region.

[0022] Furthermore, soil samples from the first region were pretreated to obtain microplastic samples, including:

[0023] Soil samples from the first region were allowed to air dry and then subjected to initial screening.

[0024] Organic matter was removed from soil samples in the first region using the hydrogen peroxide oxidation method.

[0025] Inorganic mineral removal was performed on soil samples from the first region using acid digestion.

[0026] Microplastics were enriched in soil samples from the first region using density flotation to obtain microplastic samples from the first region.

[0027] Furthermore, the microplastic samples were analyzed to obtain the corresponding microplastic parameters, including:

[0028] The enriched microplastic sample was filtered through a filter membrane.

[0029] The number of microplastic particles was determined using stereomicroscopy, and the abundance of microplastics was determined based on the number of microplastic particles and the weight of soil samples from the first region.

[0030] Based on ImageJ or NIS-Elements, the particle size of each microplastic is determined, and the median particle size of each microplastic is used as the microplastic particle size in the microplastic parameters.

[0031] Furthermore, several soil samples were obtained from the target area, and the soil parameters of the soil samples were determined, including:

[0032] Based on the grid method, several sampling points are set up in the target area, and soil samples are collected at the sampling points;

[0033] Based on the sedimentation method, the particle size of each particle in the soil sample is estimated, and the median of the particle size is taken as the soil particle size.

[0034] The pore size of soil samples was determined using X-ray micro-CT.

[0035] Secondly, the present invention provides a soil microplastic detection device, comprising:

[0036] The acquisition module is used to acquire several soil samples in the target area and determine the soil parameters of the soil samples, including soil particle size and pore size.

[0037] The partitioning module is used to divide the target area according to soil parameters to obtain a first area and a second area, wherein the first area is the outer area of ​​the second area;

[0038] The microplastic processing module is used to preprocess soil samples from the first region to obtain microplastic samples;

[0039] The analysis module is used to analyze microplastic samples and obtain the corresponding microplastic parameters, including microplastic particle size and microplastic abundance.

[0040] The risk module is used to determine migration risk based on microplastic parameters;

[0041] The cycle determination module is used to determine the detection interval cycle of soil microplastics in the target area based on the migration risk and the area of ​​the first region.

[0042] Thirdly, the present invention provides an electronic device, comprising:

[0043] processor;

[0044] Memory used to store processor-executable instructions;

[0045] The processor is configured to execute a soil microplastic detection method as provided in the first aspect.

[0046] Fourthly, the present invention provides a non-transitory computer-readable storage medium, wherein when the instructions in the non-transitory computer-readable storage medium are executed by a processor of an electronic device, the electronic device is able to perform a soil microplastic detection method as provided in the first aspect.

[0047] One or more technical solutions provided in this invention have at least the following technical effects or advantages:

[0048] This invention achieves a leap from empirically fixed boundaries to physically driven adaptive spatial delineation by dynamically coupling measured soil particle size and pore size parameters into the regional delineation logic. Based on soil particle size and pore size, this invention anchors the spatial range of the "boundary effect," providing a clear target area for subsequent differentiated strategies and overcoming the shortcomings of traditional homogeneous delineation that ignores soil spatial heterogeneity. The first region in this invention, serving as a buffer zone surrounding the target area, is more susceptible to external environmental inputs and is a sensitive frontier for the intrusion and accumulation of pollutants such as microplastics. Prioritizing its collection improves the targeting and early warning capabilities of pollution monitoring.

[0049] This invention, by introducing a reference particle size and an empirical power exponent, can sensitively reflect the nonlinear amplification effect of particle size changes on risk. Simultaneously, dimensionless processing ensures the comparability of data from different regions and with different sampling volumes. High abundance implies a larger potential release source, while small particle size indicates stronger penetration and transport capabilities. This invention, through a parameterized method, not only improves the scientific rigor and efficiency of risk assessment but also provides an intuitive and operable technical basis for identifying priority control areas, optimizing the allocation of remediation resources, and formulating policies.

[0050] This invention introduces a migration risk ratio based on a standard detection cycle, which automatically shortens the detection interval for areas with higher migration risk and appropriately increases the detection interval for areas with lower migration risk, thereby improving the timeliness of response in high-risk situations. At the same time, it combines the area ratio of the first region in the target region, so that the detection frequency increases accordingly when the boundary sensitive area is larger, avoiding the masking of local high risk by the overall average. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a schematic flowchart of a soil microplastic detection method provided by the present invention. Detailed Implementation

[0053] This invention provides a method for detecting microplastics in soil, which solves the technical problem of unreasonable microplastic detection cycles in the prior art.

[0054] The technical solution of this invention is to solve the above-mentioned technical problems, and the overall idea is as follows:

[0055] A method for detecting soil microplastics includes: acquiring several soil samples from a target area and determining soil parameters for the soil samples, wherein the soil parameters include soil particle size and pore size; dividing the target area into a first area and a second area based on the soil parameters, wherein the first area is the outer area of ​​the second area; preprocessing the soil samples from the first area to obtain microplastic samples; analyzing the microplastic samples to obtain microplastic parameters corresponding to the microplastic samples, wherein the microplastic parameters include microplastic particle size and microplastic abundance; determining the migration risk based on the microplastic parameters; and determining the detection interval for soil microplastics in the target area based on the migration risk and the area of ​​the first area.

[0056] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0057] First, it should be clarified that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0058] This invention provides, for example Figure 1 The method for detecting microplastics in soil shown includes steps S11-S16:

[0059] Step S11: Obtain several soil samples from the target area and determine the soil parameters of the soil samples, including soil particle size and pore size.

[0060] Specifically, this includes: setting up several sampling points in the target area based on the grid method and collecting soil samples at the sampling points; calculating the particle size of each particle in the soil sample based on the sedimentation method and taking the median particle size as the soil particle size; and determining the pore size of the soil sample based on X-ray micro-CT.

[0061] The target area can be a field or other area used for crop production. The target area can be regular or irregular, and there are no restrictions in this invention.

[0062] The target area can be regularly divided using a grid method, and sampling points can be set at each grid intersection or center location to ensure that the samples are spatially representative and have uniform coverage.

[0063] Undisturbed or disturbed soil samples were collected at each sampling point. Particle size analysis was performed on the collected soil samples using the sedimentation method: This method is based on the difference in sedimentation velocity of particles of different sizes in a liquid. By measuring the change in particle concentration over time during sedimentation, the content distribution of each particle size in the soil is calculated, and the median of the particle size distribution is further calculated as the representative soil particle size of the sample (in addition to the median, the mean can also be used as the soil particle size).

[0064] To obtain information on the microstructure of soil, X-ray micro-computed tomography (Micro-CT) technology can be used to perform non-destructive three-dimensional imaging of soil samples. Through image reconstruction and pore segmentation algorithms, the spatial distribution, morphology, and size characteristics of pores inside the soil can be accurately identified and quantified, thereby determining its pore size (average pore diameter).

[0065] In addition to the methods mentioned above for determining soil particle size based on sedimentation and pore size based on X-ray micro-CT, soil particle size can also be determined by laser particle size analyzer, sieving method or dynamic image analysis.

[0066] The pore size can be characterized by methods such as mercury intrusion porosimetry, gas adsorption, nuclear magnetic resonance, scanning electron microscopy (SEM) combined with image processing, and soil-water characteristic curve inversion.

[0067] Step S12: Based on soil parameters, the target area is divided into a first area and a second area, wherein the first area is the outer area of ​​the second area.

[0068] Specifically, it includes:

[0069] ,

[0070] in, The width of the first region. To preset standard width, as well as All are preset weights. Standard soil particle size, The soil particle size of the soil sample. The pore size of the soil sample. Standard pore size;

[0071] Using the boundary of the target region as the boundary, extend inward by the width of a first region to obtain the first region, and take the part of the target region other than the first region as the second region.

[0072] Step S12 achieves a leap from empirical fixed boundaries to physical mechanism-driven adaptive spatial delineation by dynamically coupling the measured soil particle size and pore size parameters into the regional delineation logic.

[0073] The soil boundary region (i.e., the first region) is often a sensitive frontier for water transport, pollutant intrusion, or ecological interaction, and its functional behavior is highly dependent on the local soil physical structure characteristics. Under natural air drying or structural disturbance conditions, when soil particles are small in size and the soil structure is relatively loose, with strong macropore or effective pore connectivity, the likelihood of soil particles migrating under the influence of natural factors such as wind increases significantly. Therefore, when small soil particle size and large effective pore size or pore connectivity are detected, the area of ​​the first region needs to be appropriately increased to cover the potentially high-risk migration boundary zone.

[0074] This invention anchors the spatial range of the "boundary effect" based on soil particle size and pore size, providing a clear target area for subsequent differentiation strategies and overcoming the shortcomings of traditional homogenization that ignores the spatial heterogeneity of soil.

[0075] The preset standard width, standard aperture size, and preset standard width can be determined based on the actual situation of the target area or historical experience values, and are not limited in this invention.

[0076] Step S13: Preprocess the soil sample from the first region to obtain a microplastic sample.

[0077] The process includes: naturally drying soil samples from the first region and performing initial screening on the soil samples from the first region; removing organic matter from the soil samples from the first region using the hydrogen peroxide oxidation method; removing inorganic minerals from the soil samples from the first region using the acid digestion method; and enriching the soil samples from the first region with microplastics using the density flotation method to obtain microplastic samples from the first region.

[0078] First, the soil sample can be air-dried under natural conditions. Then, large particles (such as stones, plant debris, etc.) are removed by primary screening to obtain a fine soil sample with a suitable particle size.

[0079] The hydrogen peroxide oxidation method can be used to decompose the organic matter in the soil under normal temperature or mild heating conditions, effectively eliminating its interference with the identification of microplastics;

[0080] Acid digestion (usually using hydrochloric acid, nitric acid, or a mixture of strong acids) can be used to dissolve inorganic mineral components such as carbonates and metal oxides, thereby further purifying the residues.

[0081] Density flotation allows low-density microplastics to float to the surface while high-density mineral residues settle to the bottom, thus achieving selective separation and enrichment of microplastics.

[0082] The first region in this invention serves as a buffer zone surrounding the target region, making it more susceptible to external environmental inputs. It is a sensitive frontier area for the intrusion and accumulation of pollutants such as microplastics, and prioritizing its collection can improve the targeting and early warning capabilities of pollution monitoring.

[0083] In addition to the standard pretreatment process in step S13, which involves natural drying, primary screening, hydrogen peroxide oxidation, acid digestion, and density flotation, other methods can also be used to obtain microplastic samples from soil:

[0084] Using enzymatic digestion to selectively degrade biological organic matter reduces damage to microplastics;

[0085] Rapid screening of crude extract residues can be performed using near-infrared spectroscopy (NIR) or Raman imaging combined with automated identification.

[0086] In the flotation stage, ultrasonic-assisted flotation or centrifugal flotation can be used to improve the recovery efficiency of small-diameter microplastics.

[0087] Step S14: Analyze the microplastic sample to obtain the microplastic parameters corresponding to the microplastic sample, including microplastic particle size and microplastic abundance.

[0088] Specifically, this includes: filtering the enriched microplastic samples onto a filter membrane; determining the number of microplastic particles using a stereomicroscope, and determining the microplastic abundance based on the number of microplastic particles and the weight of the soil sample from the first region; determining the particle size of each microplastic using ImageJ or NIS-Elements, and using the median particle size of each microplastic as the microplastic particle size in the microplastic parameters.

[0089] Step S14 aims to quantitatively characterize the microplastic samples obtained from enrichment in step S13, and extract key microplastic particle size and microplastic abundance.

[0090] The enriched microplastic suspension can be vacuum filtered through a filter membrane, so that the microplastic particles are trapped on the surface of the filter membrane to form an observable sample layer.

[0091] The particles on the filter membrane are manually or semi-automatically identified and counted under a stereomicroscope to eliminate suspected interfering substances such as fibers and mineral crystals, and the total number of microplastic particles is obtained. The microplastic abundance is calculated by combining the original dry weight of the soil sample of the first region corresponding to the microplastic, which reflects the degree of pollution.

[0092] The microplastic images captured by the microscope are processed using image analysis software (such as the open-source ImageJ or the commercial NIS-Elements). By calibrating the scale bar, thresholding, and performing morphological analysis, the equivalent particle size (such as Feret diameter, area equivalent diameter, etc.) of each microplastic particle is accurately measured. Finally, the median (D50) (or average particle size) of all particles is taken as the microplastic particle size parameter after sorting all particle sizes by size.

[0093] Step S15: Determine the migration risk based on the microplastic parameters.

[0094] Specifically, it includes:

[0095] ,

[0096] in, To mitigate migration risks, The abundance of microplastics after dimensionless scaling. This is the reference particle size for microplastics. For microplastic particle size, This is an empirical coefficient. .

[0097] Among them, the empirical coefficient is used to characterize the nonlinear amplification effect of microplastic particle size variation on migration behavior, and its value range is set based on the migration experiment results under different soil structure conditions.

[0098] Dimensionlessness can be achieved through methods such as ratios relative to standard abundance or interval normalization, and is not limited in this invention. The reference particle size for microplastics can be a preset value, an empirical value, etc., and is not limited in this invention.

[0099] This invention, by introducing a reference particle size and an empirical power exponent, can sensitively reflect the nonlinear amplification effect of particle size changes on risk. Simultaneously, dimensionless processing ensures the comparability of data from different regions and with different sampling volumes. High abundance implies a larger potential release source, while small particle size indicates stronger penetration and transport capabilities. This invention, through a parameterized method, not only improves the scientific rigor and efficiency of risk assessment but also provides an intuitive and operable technical basis for identifying priority control areas, optimizing the allocation of remediation resources, and formulating policies.

[0100] Step S16: Determine the detection interval for soil microplastics in the target area based on the migration risk and the area of ​​the first region.

[0101] Specifically, it includes:

[0102] in, The detection interval period, For standard cycles, For adjustment coefficients, , To mitigate the risks of standard migration, The area of ​​the first region. This is a historical experience coefficient. The area of ​​the target region.

[0103] The relevant patent document CN202410501202.8 also provides a method for adjusting the frequency, but it only makes adjustments based on a comparative analysis of the comprehensive indicator values ​​of soil microplastic migration, and does not provide specific adjustment methods. The standard cycle can be set according to actual needs, such as 3 months, 6 months, etc. The adjustment coefficient is used to establish a buffer between the theoretically risk-driven detection cycle and actual monitoring conditions, ensuring that the adjustment of the detection interval responds to changes in migration risk without causing overly aggressive or frequent fluctuations. Specifically, it can be determined based on actual needs or historical experience values; the historical experience coefficient can be determined based on historical experience or experiments.

[0104] This invention introduces a migration risk ratio based on a standard detection cycle, which automatically shortens the detection interval for areas with higher migration risk and appropriately increases the detection interval for areas with lower migration risk, thereby improving the timeliness of response in high-risk situations. At the same time, it combines the area ratio of the first region in the target region, so that the detection frequency increases accordingly when the boundary sensitive area is larger, avoiding the masking of local high risk by the overall average.

[0105] In summary, this invention achieves a leap from empirically fixed boundaries to physically driven adaptive spatial delineation by dynamically coupling measured soil particle size and pore size parameters into the regional delineation logic. Based on soil particle size and pore size, this invention anchors the spatial range of the "boundary effect," providing a clear target area for subsequent differentiated strategies and overcoming the shortcomings of traditional homogeneous delineation that ignores soil spatial heterogeneity. The first region in this invention, serving as a buffer zone surrounding the target area, is more susceptible to external environmental inputs and is a sensitive frontier for the intrusion and accumulation of pollutants such as microplastics. Prioritizing its collection improves the targeting and early warning capabilities of pollution monitoring.

[0106] This invention, by introducing a reference particle size and an empirical power exponent, can sensitively reflect the nonlinear amplification effect of particle size changes on risk. Simultaneously, dimensionless processing ensures the comparability of data from different regions and with different sampling volumes. High abundance implies a larger potential release source, while small particle size indicates stronger penetration and transport capabilities. This invention, through a parameterized method, not only improves the scientific rigor and efficiency of risk assessment but also provides an intuitive and operable technical basis for identifying priority control areas, optimizing the allocation of remediation resources, and formulating policies.

[0107] This invention introduces a migration risk ratio based on a standard detection cycle, which automatically shortens the detection interval for areas with higher migration risk and appropriately increases the detection interval for areas with lower migration risk, thereby improving the timeliness of response in high-risk situations. At the same time, it combines the area ratio of the first region in the target region, so that the detection frequency increases accordingly when the boundary sensitive area is larger, avoiding the masking of local high risk by the overall average.

[0108] Based on the same inventive concept, the present invention provides a soil microplastic detection device, comprising:

[0109] The acquisition module is used to acquire several soil samples in the target area and determine the soil parameters of the soil samples, including soil particle size and pore size.

[0110] The partitioning module is used to divide the target area according to soil parameters to obtain a first area and a second area, wherein the first area is the outer area of ​​the second area;

[0111] The microplastic processing module is used to preprocess soil samples from the first region to obtain microplastic samples;

[0112] The analysis module is used to analyze microplastic samples and obtain the corresponding microplastic parameters, including microplastic particle size and microplastic abundance.

[0113] The risk module is used to determine migration risk based on microplastic parameters;

[0114] The cycle determination module is used to determine the detection interval cycle of soil microplastics in the target area based on the migration risk and the area of ​​the first region.

[0115] Based on the same inventive concept, the present invention also provides an electronic device, comprising:

[0116] processor;

[0117] Memory used to store processor-executable instructions;

[0118] The processor is configured to execute a soil microplastic detection method as described above.

[0119] Based on the same inventive concept, the present invention also provides a non-transitory computer-readable storage medium, which, when the instructions in the storage medium are executed by the processor of an electronic device, enables the electronic device to perform a soil microplastic detection method as described above.

[0120] Since the electronic device described in this embodiment is an electronic device used to implement the information processing method in the embodiments of the present invention, those skilled in the art can understand the specific implementation methods and various variations of the electronic device in this embodiment based on the information processing method described in the embodiments of the present invention. Therefore, how the electronic device implements the method in the embodiments of the present invention will not be described in detail here. Any electronic device used by those skilled in the art to implement the information processing method in the embodiments of the present invention falls within the scope of protection of the present invention.

[0121] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0122] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0123] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0124] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0125] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0126] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for detecting microplastics in soil, characterized in that, include: Acquire several soil samples from the target area and determine the soil parameters of the soil samples, including soil particle size and pore size; Based on the soil parameters, the target area is divided into a first area and a second area, wherein the first area is the outer area of ​​the second area; Soil samples from the first region were pretreated to obtain microplastic samples; The microplastic sample was analyzed to obtain the microplastic parameters corresponding to the microplastic sample, wherein the microplastic parameters include: microplastic particle size and microplastic abundance; Based on the microplastic parameters, the migration risk is determined; Based on the migration risk and the area of ​​the first region, the detection interval for soil microplastics in the target area is determined; Based on the microplastic parameters, the migration risk is determined, including: ， in, To mitigate migration risks, The abundance of microplastics after dimensionless scaling. This is the reference particle size for microplastics. For microplastic particle size, This is an empirical coefficient. ; Based on the migration risk and the area of ​​the first region, the detection interval for soil microplastics in the target area is determined, including: ， in, The detection interval period, For standard cycles, For adjustment coefficients, , To mitigate the risks of standard migration, The area of ​​the first region. This is a historical experience coefficient. The area of ​​the target region; Based on the soil parameters, the target area is divided into a first region and a second region, including: ， in, The width of the first region. To preset standard width, as well as All are preset weights. Standard soil particle size, The soil particle size of the soil sample. The pore size of the soil sample. Standard pore size; Using the boundary of the target region as the boundary, extend inward by the width of the first region to obtain the first region, and take the part of the target region other than the first region as the second region.

2. The method for detecting soil microplastics as described in claim 1, characterized in that, Soil samples from the first region were pretreated to obtain microplastic samples, including: Soil samples from the first region were allowed to air dry and then subjected to initial screening. Organic matter was removed from soil samples in the first region using the hydrogen peroxide oxidation method. Inorganic mineral removal was performed on soil samples from the first region using acid digestion. Microplastics were enriched in soil samples from the first region using density flotation to obtain microplastic samples from the first region.

3. The method for detecting soil microplastics as described in claim 2, characterized in that, The microplastic sample was analyzed to obtain the corresponding microplastic parameters, including: The enriched microplastic sample was filtered through a filter membrane. The number of microplastic particles was determined using stereomicroscopy, and the abundance of microplastics was determined based on the number of microplastic particles and the weight of soil samples from the first region. Based on ImageJ or NIS-Elements, the particle size of each microplastic is determined, and the median particle size of each microplastic is used as the microplastic particle size in the microplastic parameters.

4. The method for detecting soil microplastics as described in claim 1, characterized in that, Obtain several soil samples from the target area and determine the soil parameters of the soil samples, including: Based on the grid method, several sampling points are set in the target area, and soil samples are collected at the sampling points; Based on the sedimentation method, the particle size of each particle in the soil sample is estimated, and the median of the particle size is taken as the soil particle size. The pore size of soil samples was determined using X-ray micro-CT.

5. A soil microplastic detection device, characterized in that, A method for detecting soil microplastics according to any one of claims 1-4, comprising: The acquisition module is used to acquire several soil samples in the target area and determine the soil parameters of the soil samples, including soil particle size and pore size. The division module is used to divide the target area according to the soil parameters to obtain a first area and a second area, wherein the first area is the outer area of ​​the second area; The microplastic processing module is used to preprocess soil samples from the first region to obtain microplastic samples; The analysis module is used to analyze the microplastic sample to obtain the microplastic parameters corresponding to the microplastic sample, wherein the microplastic parameters include: microplastic particle size and microplastic abundance; The risk module is used to determine the migration risk based on the microplastic parameters; The cycle determination module is used to determine the detection interval cycle of soil microplastics in the target area based on the migration risk and the area of ​​the first area.

6. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute a method for detecting soil microplastics as described in any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the non-transitory computer-readable storage medium are executed by the processor of the electronic device, the electronic device is able to perform a method for detecting soil microplastics as described in any one of claims 1 to 4.

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