A method and system for remediating heavy metal contaminated soil

Abstract

The application discloses a heavy metal contaminated soil remediation method and system, and relates to the field of electric digital data processing. The method adopts electric power and plant combined remediation. Heavy metal ions are attracted to the plant root system range through electric power, thereby making up the certainty of a single remediation method with a relatively long time period. The arrangement positions of the equipment of the two remediation modes are iterated based on computer intelligence, so that the maximum remediation effect is achieved with the least number of electrodes and the least number of plants. The error that some soil blocks are redundantly remediated or some soils cannot be remediated due to artificial subjective arrangement is prevented. The application does not need to completely collect all concentration distributions of the to-be-remediated soil. The data that are not collected can be supplemented through the interpolation method of the application, so that the artificial cost is reduced.

Description

A method and system for remediating heavy metal contaminated soil Technical Field

[0001] This application relates to the field of electronic digital data processing technology, and in particular to a method and system for remediating heavy metal contaminated soil. Background Technology

[0002] Heavy metal pollution in farmland is soil pollution caused by the excessive deposition of heavy metals from waste in the soil. The heavy metals polluting farmland soil mainly include elements with significant biological toxicity such as mercury, cadmium, lead, chromium, and metalloid arsenic, as well as elements with certain toxicity such as zinc, copper, and nickel.

[0003] Heavy metal pollution in farmland mainly originates from mining waste, pesticides, wastewater, sludge, and atmospheric deposition. For example, mercury primarily comes from mercury-containing wastewater, while cadmium and lead pollution mainly arise from smelting emissions and vehicle exhaust deposition. Arsenic is widely used as an insecticide, fungicide, rodenticide, and herbicide. Excessive heavy metals can cause physiological dysfunction and nutrient imbalances in plants. Elements such as cadmium and mercury have high enrichment coefficients in crop seeds, and even if they exceed food hygiene standards, they do not affect crop growth, development, or yield. Furthermore, mercury and arsenic can weaken and inhibit the activity of nitrifying and ammonifying bacteria in the soil, affecting nitrogen supply. Heavy metal pollutants themselves have very low mobility in the soil, are not easily leached by water, and are almost never degraded by microorganisms. Once they enter the human body through the food chain, they can easily affect health.

[0004] Soil heavy metal pollution remediation refers to the use of physical, chemical, and biological techniques to remove or transform heavy metals in soil, reducing the harmful concentration or toxicity of heavy metal pollutants to organisms. Based on remediation principles, it can be divided into physical remediation, chemical remediation, and bioremediation. Physical remediation uses physical means to separate heavy metal pollutants from the soil, mainly including soil replacement, heat treatment, vitrification, and electrokinetic remediation. It is simple to operate but costly, suitable for small-scale emergency remediation, and difficult to use on a large scale. Chemical remediation uses chemical reagents or solid materials to interact with heavy metals in the soil to remove or reduce their activity, including chemical fixation, soil solidification and stabilization, and soil leaching. It has the advantages of low cost, simple operation, and good results, but cannot guarantee the long-term stability of the remediation effect, and some chemical remediation methods are prone to secondary pollution and soil compaction. Bioremediation utilizes the metabolic or absorption activities of microorganisms / plants to reduce the toxicity of heavy metals in the soil or remove the content of heavy metals. It has the advantages of low energy consumption, low operating costs, and no environmental or health hazards, but has the disadvantages of long remediation cycles and harsh microbial growth conditions.

[0005] As can be seen from the above, the complete remediation of heavy metal contaminated soil depends on the time process. Soil remediation with good results all have the problem of long remediation time. Moreover, the arrangement and placement of remediation equipment is usually done by manually measuring the heavy metal content in the soil and placing the remediation equipment at high heavy metal content sites, such as placing electrodes or planting plants. Since the equipment layout stage, there is a problem of subjective experience error. Due to the poor mobility of heavy metal ions and subjective experience error, the coverage of soil remediation effect is not comprehensive, resulting in unsatisfactory remediation effect, or the redundant layout of remediation equipment leads to the problem of resource waste. Summary of the Invention

[0006] The main objective of this application is to provide a method and system for remediating heavy metal contaminated soil, in order to solve the problems of long remediation time and unsatisfactory remediation effect caused by subjective experience errors in equipment layout in the prior art.

[0007] To achieve the above objectives, this application provides the following technical solution:

[0008] A method for remediating heavy metal contaminated soil, the method being based on electrodynamic remediation and phytoremediation. Electrodynamic remediation involves guiding and absorbing heavy metal ions within a rectangular area using a pair of electrodes, while phytoremediation involves absorbing heavy metal ions within a hemispherical area of ​​the plant's root system. The remediation method includes:

[0009] Step S1: Using an external concentration detector, several heavy metal content indicators are measured in the area where the heavy metal-contaminated soil is located.

[0010] Step S2: Generate content contour lines based on all heavy metal content indicators using interpolation.

[0011] Step S3: Define the contour lines where the heavy metal content index is greater than or equal to the preset index threshold as the repair area;

[0012] Step S4: Define a rectangular area for electrodynamic repair as an electrodynamic repair rectangle;

[0013] Step S5: Iterate the number and position of the electrodynamic repair rectangles within the repair area until all electrodynamic repair rectangles completely cover the entire repair area and the overlapping area of ​​all electrodynamic repair rectangles reaches the minimum value.

[0014] Step S6: Define the circular surface of a hemispherical area of ​​a plant as a repair circle;

[0015] Step S7: Iterate the number and position of the repair circles within all electrodynamic repair rectangles until all repair circles completely cover all electrodynamic repair rectangles and the overlapping area of ​​all repair circles reaches the minimum value.

[0016] Step S8: Obtain the final positions of all electrodynamic repair rectangles and all repair circles, and place a pair of electrodes at the final position of each electrodynamic repair rectangle and plant a plant at the final position of each repair circle.

[0017] Step S9: Connect each pair of electrodes to perform soil remediation.

[0018] As a further improvement to this application, step S2, generating content contour lines based on all heavy metal content indicators using interpolation, includes:

[0019] Step S21: Obtain the geographical location of each heavy metal content index based on the heavy metal contaminated soil.

[0020] Step S22: Obtain the geographic coordinates of all geographic points and define the Euclidean distance between the interpolation location and all geographic points according to equation (1):

[0021]

[0022] Where, d i Let (x, y) be the Euclidean distance between the interpolated position and the i-th geographic point, and let (x, y) be the coordinates of the interpolated position. i ,y i () represents the geographic coordinates of the i-th geographic point;

[0023] Step S23, calculate the weight value of the i-th geographic point based on the interpolated position according to equation (2):

[0024]

[0025] Among them, w i The weight value of the i-th geographic point based on the interpolated position, where p is an adjustment parameter that takes the value of 2 or 3;

[0026] Step S24, calculate the function value of the interpolation position according to equation (3):

[0027]

[0028] Where z(x,y) is the function value of the interpolation position, z i Let be the radial basis function for the i-th geographic point. The sum of the radial basis functions of all geographic points multiplied by their corresponding weight values. It is the sum of all weight values. and The ratio is the function value at the interpolation position;

[0029] Step S25: Obtain the (x,y) value in the function value, which is the interpolation coordinate of the interpolation position;

[0030] Step S26: Obtain the digital elevation model of the area where the heavy metal contaminated soil is located;

[0031] Step S27: Input all heavy metal content indicators and all corresponding geographic locations into the digital elevation model;

[0032] Step S28: Input all interpolated coordinates and all corresponding function values ​​into the digital elevation model;

[0033] Step S29: Linearly connect all equal heavy metal content indicators and function values ​​to obtain the content contour lines.

[0034] As a further improvement to this application, step S2, generating content contour lines based on all heavy metal content indicators using interpolation, includes:

[0035] Step S210: Obtain the geographical location of each heavy metal content index based on the heavy metal contaminated soil.

[0036] Step S220: Calculate the Euclidean distance and semivariogram between every two geographic points based on all geographic points;

[0037] Step S230: Solve for the fitting curves of all Euclidean distances and all semivariograms, so that the fitting curves can be calculated based on any Euclidean distance to obtain the corresponding semivariograms.

[0038] Step S240: Solve for the semivariograms among all geographic locations based on the fitted curves and define the optimal coefficients of all semivariograms according to equation (4):

[0039]

[0040] Where, r ij Let λ be the semivariogram between the i-th and j-th points. i Let r be the optimal coefficient between the i-th point and other points. io Let φ be the semivariogram from the i-th interpolation position to all points, and φ be the Lagrange multiplier.

[0041] Step S250: The function values ​​of all points are weighted and summed according to all optimal coefficients to obtain the function value of the interpolation position;

[0042] Step S260: Obtain the digital elevation model of the area where the heavy metal contaminated soil is located;

[0043] Step S270: Input all heavy metal content indicators and all corresponding geographic locations into the digital elevation model;

[0044] Step S280: Input the coordinates of all interpolation positions and all corresponding function values ​​into the digital elevation model;

[0045] Step S290: Linearly connect all equal heavy metal content indicators and function values ​​to obtain the content contour lines.

[0046] As a further improvement to this application, the semi-variogram is characterized by equation (5):

[0047]

[0048] Among them, z i Let z be the function value for the i-th geographic point. j Let E(·) be the function value of the j-th geographic point, and E(·) be the expected function.

[0049] As a further improvement to this application, step S5 iterates the number and position of the electrodynamic repair rectangles within the repair area until all electrodynamic repair rectangles completely cover the entire repair area and the overlapping area of ​​all electrodynamic repair rectangles reaches a minimum, including:

[0050] Step S51: Define four random solutions for each electrodynamic repair rectangle, with each corner of the electrodynamic repair rectangle having a random solution, and constrain the relative positions of the four random solutions based on the current electrodynamic repair rectangle.

[0051] Step S52, define the optimization result of all random solutions as the minimum value of the overlapping area of ​​the mutually overlapping rectangles repaired by electrodynamics;

[0052] Step S53: Initialize the position of each random solution, and update the current position and current velocity of each random solution respectively;

[0053] Step S54: During the iteration process, delete the electrodynamic repair rectangles that completely exceed the repair area;

[0054] Step S55: Based on each update, obtain the individual optimal solution and the global optimal solution for each random solution;

[0055] Step S56: Determine whether the difference between the optimal solution of each individual and the optimal solution of each individual updated in the previous step is less than or equal to the first preset adaptation threshold. If all are less than the threshold, proceed to step S57.

[0056] Step S57: Determine whether the difference between each global optimal solution and each of the previously updated global optimal solutions is less than or equal to the second preset adaptation threshold. If all are less than the threshold, proceed to step S58.

[0057] Step S58: Determine that the optimal solution for all electrodynamically repaired rectangles has been obtained;

[0058] Step S59: Obtain the number of rectangles and the position of the rectangles corresponding to the optimal solution.

[0059] As a further improvement of this application, step S7 iterates the number and position of the repair circles within all electrodynamic repair rectangles until all repair circles completely cover all electrodynamic repair rectangles and the overlapping area of ​​all repair circles reaches a minimum, including:

[0060] Step S71: Obtain the positions of all rectangles and merge them into one iterative region;

[0061] Step S72: Define several random solutions in the iteration region, each random solution corresponding to a repair circle;

[0062] Step S73, define the optimization result of all random solutions as the minimum value of the overlapping area of ​​all repair circles;

[0063] Step S74: Initialize the position of each random solution, and update the current position and current velocity of each random solution respectively;

[0064] Step S75: Based on each update, obtain the individual optimal solution and the global optimal solution for each random solution;

[0065] Step S76: Determine whether the difference between the optimal solution of each individual and the optimal solution of each individual updated in the previous step is less than or equal to the first preset adaptation threshold. If all are less than the threshold, proceed to step S77.

[0066] Step S77: Determine whether the difference between each global optimal solution and each of the previously updated global optimal solutions is less than or equal to the second preset adaptation threshold. If all are less than the threshold, proceed to step S78.

[0067] Step S78: Determine that the optimal solution for all repaired circles has been obtained;

[0068] Step S79: Obtain the number of circles and the position of the circles corresponding to the optimal solution.

[0069] As a further improvement to this application, step S9 involves connecting each pair of electrodes to perform soil remediation operations, followed by:

[0070] Step S10: Output the digital elevation model, all electrodynamic repair rectangles, and all repair circles to an external visualization terminal;

[0071] Step S20: Based on the external visualization terminal, add a pair of electrodes within each electrodynamic repair rectangle and a plant at the center of each repair circle.

[0072] Step S30: In response to an external touch operation, a visual pattern is selected by a single click based on the touch operation.

[0073] Step S40: Drag all selected visual patterns based on the sliding trajectory of the touch operation.

[0074] To achieve the above objectives, this application also provides the following technical solutions:

[0075] A remediation system for heavy metal contaminated soil, the remediation system being applied to the remediation method described above, the remediation system comprising:

[0076] The heavy metal content index acquisition module is used to obtain several heavy metal content indices in the area of ​​heavy metal-contaminated soil by means of an external concentration detection device.

[0077] Content Contour Line Generation Module: This module generates content contour lines based on all heavy metal content indicators using an interpolation method.

[0078] The repair area definition module is used to define the content contour lines where the heavy metal content index is greater than or equal to the preset index threshold as the repair area.

[0079] The Electrodynamic Repair Rectangle Definition Module is used to define the rectangular range of an electrodynamic repair as an electrodynamic repair rectangle.

[0080] The electrodynamic repair rectangle iteration module is used to iterate the number and position of the electrodynamic repair rectangles within the repair area until all electrodynamic repair rectangles completely cover the entire repair area and the overlapping area of ​​all electrodynamic repair rectangles reaches the minimum value.

[0081] The Repair Circle Definition Module is used to define a circular surface within a hemispherical area of ​​a plant as a repair circle;

[0082] The repair circle iteration module is used to iterate the number and position of the repair circles within all electrodynamic repair rectangles until all repair circles completely cover all electrodynamic repair rectangles and the overlapping area of ​​all repair circles reaches the minimum value.

[0083] The repair facility placement module is used to obtain the final position of all electrodynamic repair rectangles and the final position of all repair circles, and to place a pair of electrodes at the final position of each electrodynamic repair rectangle and plant a plant at the final position of each repair circle.

[0084] The remediation facility activation module is used to connect each pair of electrodes individually to perform soil remediation operations.

[0085] To achieve the above objectives, this application also provides the following technical solutions:

[0086] An electronic device includes a processor and a memory coupled to the processor, the memory storing program instructions executable by the processor; when the processor executes the program instructions stored in the memory, it implements the repair method as described above.

[0087] To achieve the above objectives, this application also provides the following technical solutions:

[0088] A storage medium storing program instructions that, when executed by a processor, enable the aforementioned repair method.

[0089] This application uses external concentration detectors to measure several heavy metal content indicators in the area of ​​heavy metal-contaminated soil; generates content contour lines based on all heavy metal content indicators using interpolation; defines the content contour lines where the heavy metal content is greater than or equal to a preset threshold as remediation areas; defines a rectangular area for electrodynamic remediation as an electrodynamic remediation rectangle; iterates the number and position of the electrodynamic remediation rectangles within the remediation area until all electrodynamic remediation rectangles completely cover all remediation areas and the overlapping area of ​​all electrodynamic remediation rectangles reaches a minimum; defines the hemispherical area of ​​a plant as a remediation circle; iterates the number and position of the remediation circles within all electrodynamic remediation rectangles until all remediation circles completely cover all electrodynamic remediation rectangles and the overlapping area of ​​all remediation circles reaches a minimum; obtains the final positions of all electrodynamic remediation rectangles and all remediation circles, places a pair of electrodes at the final position of each electrodynamic remediation rectangle, and plants a plant at the final position of each remediation circle; and connects each pair of electrodes to perform soil remediation operations. This application employs a combined electrodynamic and phytoremediation approach. Electrodynamics attracts heavy metal ions to the root system of plants, thus mitigating the uncertainty of long time cycles associated with single remediation methods. Furthermore, it utilizes computer-aided intelligent iteration to optimize the placement of equipment for both remediation methods, maximizing remediation effectiveness with minimal electrode and plant counts. This prevents errors caused by subjective manual placement, such as redundant remediation of certain soil areas or failure to remediate certain soils. Additionally, this application does not require complete collection of all concentration distributions in the soil to be remediated; missing data can be supplemented using interpolation methods, thereby reducing labor costs. Attached Figure Description

[0090] Figure 1 is a schematic flowchart of one embodiment of the remediation method for heavy metal contaminated soil according to this application;

[0091] Figure 2 is a schematic diagram illustrating a soil remediation example of an embodiment of the remediation method for heavy metal contaminated soil according to this application.

[0092] Figure 3 is a schematic diagram of the functional modules of an embodiment of a heavy metal contaminated soil remediation system of this application;

[0093] Figure 4 is a schematic diagram of the structure of an embodiment of the electronic device of this application;

[0094] Figure 5 is a schematic diagram of the structure of a storage medium according to an embodiment of this application. Detailed Implementation

[0095] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0096] The terms "first," "second," and "third" in this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0097] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0098] As shown in Figure 1, this embodiment provides an example of a method for remediating heavy metal contaminated soil. In this embodiment, the remediation method is based on electrodynamic remediation and phytoremediation. Electrodynamic remediation guides and absorbs heavy metal ions within a rectangular area through a pair of electrodes, while phytoremediation absorbs heavy metal ions within a hemispherical area of ​​the root system through plants.

[0099] Preferably, in the actual electrodynamic remediation process, it can be known that the influence range of a set of electrodynamic remediation is approximately a cuboid, which is completely submerged in the soil, and the upper surface of the cuboid is flush with the soil surface. Viewed from above with the soil surface as the plane, it is a rectangle. Since the shape of the part below the soil surface is the same as the shape of the upper surface, only the rectangular shape of the surface needs to be considered. Similarly, the phytoremediation range is the same as the root growth range. The root system of the plant is approximately a hemisphere, that is, the part on the soil surface is circular. Since the part of the plant root system is determined by the variety, the circular shape of the soil surface can be iterated when determining the plant variety, while also taking into account reasonable planting density.

[0100] Preferably, activators can also be used in the soil remediation process to accelerate the remediation process and shorten the remediation cycle. The use of good activators can improve soil structure: soil activators can effectively improve the physical properties of soil, increase soil looseness, reduce compaction, and improve soil aeration and permeability; adjust soil pH: by adjusting the soil acidity and alkalinity, the soil becomes more suitable for plant growth; increase soil fertility: soil activators contain humus, beneficial bacteria and fungi, which can improve soil structure, increase soil organic matter content, and thus improve soil fertility.

[0101] Among them, the methods of using activators in soil remediation mainly include spraying, basal application, trenching, hole application, and fertilizer mixing.

[0102] It is worth noting that the use of activators is a mature existing technology. The use of activators in this embodiment is also conventional. The method and steps of using activators will not be described again in this embodiment.

[0103] Specifically, the repair method includes the following steps:

[0104] Step S1 involves using external concentration detectors to measure several heavy metal content indicators in the area where the soil is contaminated with heavy metals.

[0105] Preferably, the methods for detecting heavy metal content in soil mainly include the following:

[0106] ① Atomic absorption spectrometry (AAS): It has high sensitivity, high selectivity and good precision. It quantitatively analyzes the heavy metal content in soil samples by measuring the absorption of radiation of a specific wavelength by the ground state atoms of the analyte. AAS is easy to operate and is widely used in the routine detection of heavy metals in soil.

[0107] ② Inductively Coupled Plasma Mass Spectrometry (ICP-MS): This method uses high-temperature plasma to ionize the elements in a sample and then detects them using a mass spectrometer. ICP-MS has advantages such as low detection limit and fast analysis speed, making it particularly suitable for the determination of trace heavy metal elements in soil.

[0108] ③ Atomic fluorescence spectrometry (AFS): This method quantitatively analyzes the heavy metal content in soil by measuring the fluorescence intensity of the analyte. AFS has advantages such as high sensitivity and good selectivity, and is particularly suitable for the detection of low concentrations of heavy metals.

[0109] ④ X-ray fluorescence spectrometry (XRF): This method analyzes heavy metal elements in soil by measuring the fluorescent X-rays emitted by a sample under X-ray excitation. XRF is simple to operate and requires minimal sample preparation, making it suitable for rapid screening of heavy metal pollution in soil.

[0110] ⑤ Electrochemical analysis: This method quantitatively analyzes the heavy metal content in soil by measuring the changes in current or potential generated during electrode reactions. Electrochemical analysis equipment is simple and easy to operate, making it suitable for rapid on-site testing.

[0111] ⑥ Laser-induced breakdown spectroscopy: Real-time and rapid qualitative and quantitative analysis of chemical elements.

[0112] ⑦ Biological methods: Biological detection methods have the advantages of being easy to operate and inexpensive, making them suitable for preliminary screening.

[0113] Preferably, the unit for heavy metal content is milligrams per kilogram (mg / kg).

[0114] Step S2: Generate content contour lines based on all heavy metal content indicators using interpolation.

[0115] Preferably, it is equivalent to topographic contour lines, where areas with the same heavy metal content index value are connected by lines.

[0116] Step S3: Define the contour lines where the heavy metal content index is greater than or equal to the preset index threshold as the repair area.

[0117] Preferably, the heavy metal content index can be determined based on the soil use and user requirements:

[0118] ①Class I soil: Primarily suitable for nature reserves, centralized drinking water sources, etc., where heavy metal content should be maintained at natural background levels. Specific restrictions are as follows:

[0119] Cadmium (Cd) ≤ 0.2 mg / kg.

[0120] Mercury (Hg) ≤ 0.15 mg / kg.

[0121] Arsenic (As) ≤15mg / kg (paddy field) or ≤15mg / kg (dry land).

[0122] Copper (Cu) ≤ 35 mg / kg.

[0123] Lead (Pb) ≤ 35 mg / kg.

[0124] Chromium (Cr) ≤90mg / kg (paddy field) or ≤90mg / kg (dry land).

[0125] Zinc (Zn) ≤ 100 mg / kg.

[0126] Nickel (Ni)≤40mg / kg.

[0127] ②Class II soil: Suitable for general farmland, vegetable fields, etc., ensuring agricultural production and protecting human health. Specific limitations are as follows:

[0128] Cadmium (Cd) ≤ 0.3 mg / kg (pH < 6.5) or ≤ 1.0 mg / kg (pH > 7.5).

[0129] Mercury (Hg) ≤ 0.3 mg / kg (pH < 6) or ≤ 1.0 mg / kg (pH > 7.5).

[0130] Arsenic (As) ≤30mg / kg (paddy field) or ≤40mg / kg (dry land).

[0131] Copper (Cu) ≤50mg / kg (pH<6) or ≤100mg / kg (pH>6.5).

[0132] Lead (Pb) ≤250mg / kg (pH<6) or ≤350mg / kg (pH>7.5).

[0133] Chromium (Cr) ≤250mg / kg (paddy field) or ≤150mg / kg (dry land).

[0134] Zinc (Zn) ≤200mg / kg (pH<6) or ≤300mg / kg (pH>7.5).

[0135] Nickel (Ni)≤40mg / kg.

[0136] ③Class III Soil: Suitable for forest land and soils with high background values ​​and large pollutant capacity, ensuring agricultural and forestry production and normal plant growth. Specific restrictions are as follows:

[0137] Mercury (Hg) ≤ 1.5 mg / kg.

[0138] Arsenic (As) ≤30mg / kg (paddy field), ≤40mg / kg (dry land).

[0139] Copper (Cu) ≤ 400 mg / kg.

[0140] Lead (Pb) ≤ 500 mg / kg.

[0141] Chromium (Cr) ≤400mg / kg (paddy field), ≤300mg / kg (dry land).

[0142] Zinc (Zn) ≤ 500 mg / kg.

[0143] Nickel (Ni)≤200mg / kg.

[0144] Step S4: Define a rectangular area for electrodynamic repair as an electrodynamic repair rectangle.

[0145] Preferably, only a rectangle needs to be defined on the soil surface.

[0146] Step S5: Iterate the number and position of the electrodynamic repair rectangles within the repair area until all electrodynamic repair rectangles completely cover the entire repair area and the overlapping area of ​​all electrodynamic repair rectangles reaches the minimum value.

[0147] Step S6: Define the circular surface of a hemispherical area of ​​a plant as a repair circle.

[0148] Preferably, it is only necessary to define the circle of the soil surface.

[0149] Step S7: Iterate the number and position of the repair circles within all electrodynamic repair rectangles until all repair circles completely cover all electrodynamic repair rectangles and the overlapping area of ​​all repair circles reaches the minimum value.

[0150] Preferably, in this embodiment, the iterative functions of steps S5 and S7 are implemented through a global optimization algorithm.

[0151] Step S8: Obtain the final positions of all electrodynamic repair rectangles and all repair circles, and place a pair of electrodes at the final position of each electrodynamic repair rectangle and plant a plant at the final position of each repair circle.

[0152] Step S9: Connect each pair of electrodes to perform soil remediation.

[0153] Preferably, referring to Figure 2, soil heavy metal pollution is characterized by complex pollution processes, significant hazards, and difficulties in remediation, making remediation imperative. Electrodynamic phytoremediation aims to compensate for the respective disadvantages of electrodynamics and phytoremediation, synergistically leveraging their advantages to address the prominent problems of electrodynamics' inability to completely remove heavy metals from soil and the slow and limited scope of phytoremediation. In the electrodynamic phytoremediation system, the interaction between electrodynamics and plants can have both beneficial and detrimental effects on heavy metal removal, while also exhibiting many synergistic effects in overcoming their respective limitations. The electrodynamic phytoremediation process is mainly controlled by the type, arrangement, and intensity of the electric field, pH evolution, and additives. Electrodynamics, through mechanisms such as improving the spatial and speciation distribution of heavy metals, promoting nutrient absorption, and stimulating rhizosphere secretion, can effectively enhance the absorption and accumulation of heavy metals by plants and the remediation effect of contaminated soil.

[0154] Further, in step S2, content contour lines are generated based on all heavy metal content indicators using interpolation, including:

[0155] Step S21: Obtain the geographical location of each heavy metal content index based on the heavy metal contaminated soil.

[0156] Step S22: Obtain the geographic coordinates of all geographic points and define the Euclidean distance between the interpolation location and all geographic points according to equation (1):

[0157]

[0158] Where, d i Let (x, y) be the Euclidean distance between the interpolation location and the i-th geographic point, and let (x, y) be the coordinates of the interpolation location. i ,y i ) represents the geographic coordinates of the i-th geographic point.

[0159] Step S23, calculate the weight value of the i-th geographic point based on the interpolated location according to equation (2):

[0160]

[0161] Among them, w i is the weight value of the i-th geographic point based on the interpolated position, and p is an adjustment parameter that takes the value of 2 or 3.

[0162] Preferably, if p is 2, it means that the interpolation position conforms to the Euclidean distance; if p is 3, it means that the interpolation position conforms to the Manhattan distance. Users can choose the value of p according to their actual needs.

[0163] Preferably, Euclidean distance, also known as Euclidean metric, is a commonly used definition of distance, referring to the true distance between two points in m-dimensional space, or the natural length of a vector (i.e., the distance from the point to the origin). In two-dimensional and three-dimensional space, Euclidean distance is the actual distance between two points.

[0164] Preferably, the Manhattan distance is the distance between two points along the longitudinal normal (north-south direction) plus the distance along the lateral normal (east-west direction). For a layout with a regular north-south and east-west orientation, the distance from one point to another is the sum of the distance traveled in the north-south direction and the distance traveled in the east-west direction. Furthermore, the Manhattan distance is not a distance invariant; the distance between points will change as the coordinate axes shift. The advantage of the Manhattan distance lies in the computational power of floating-point operations. If the Euclidean distance of AB is used directly, floating-point operations are necessary. Using AC and CB, only addition and subtraction are required, thus improving computational speed and eliminating errors.

[0165] Step S24, calculate the function value of the interpolation position according to equation (3):

[0166]

[0167] Where z(x,y) is the function value of the interpolation position, z i Let be the radial basis function for the i-th geographic point. The sum of the radial basis functions of all geographic points multiplied by their corresponding weight values. It is the sum of all weight values. and The ratio is the function value at the interpolation position.

[0168] Preferably, steps S22 to S24 can be implemented using the Matplotlib library in Python.

[0169] Step S25: Obtain the (x,y) value in the function value, which is the interpolation coordinate of the interpolation position.

[0170] Step S26: Obtain the digital elevation model of the area where the heavy metal contaminated soil is located.

[0171] Step S27: Input all heavy metal content indicators and all corresponding geographic locations into the digital elevation model.

[0172] Step S28: Input all interpolated coordinates and all corresponding function values ​​into the digital elevation model.

[0173] Step S29: Linearly connect all equal heavy metal content indicators and function values ​​to obtain content contour lines.

[0174] Further, in step S2, content contour lines are generated based on all heavy metal content indicators using interpolation, including:

[0175] Step S210: Obtain the geographical location of each heavy metal content index based on the heavy metal contaminated soil.

[0176] Step S220: Calculate the Euclidean distance and semivariogram between every two geographic points based on all geographic points.

[0177] Step S230: Solve for the fitting curves of all Euclidean distances and all semivariograms, so that the fitting curves can be used to calculate the corresponding semivariograms based on any Euclidean distance.

[0178] Step S240: Solve for the semivariograms among all geographic locations based on the fitted curves and define the optimal coefficients of all semivariograms according to equation (4):

[0179]

[0180] Where, r ij Let λ be the semivariogram between the i-th and j-th points. i Let r be the optimal coefficient between the i-th point and other points. io Let φ be the semivariogram from the i-th interpolation position to all points, and φ be the Lagrange multiplier.

[0181] Step S250: The function values ​​of all points are weighted and summed according to all optimal coefficients to obtain the function value of the interpolation position.

[0182] Step S260: Obtain the digital elevation model of the area where the heavy metal contaminated soil is located.

[0183] Step S270: Input all heavy metal content indicators and all corresponding geographic locations into the digital elevation model.

[0184] Step S280: Input the coordinates of all interpolation positions and all corresponding function values ​​into the digital elevation model.

[0185] Step S290: Linearly connect all equal heavy metal content indicators and function values ​​to obtain content contour lines.

[0186] Furthermore, the semivariogram is characterized by equation (5):

[0187]

[0188] Among them, z iLet z be the function value for the i-th geographic point. j Let E(·) be the function value of the j-th geographic point, and E(·) be the expected function.

[0189] Preferably, the calculation process for steps S220 to S250 is as follows:

[0190] Define the Kriging interpolation formula

[0191] in, Interpolation position (x) o ,y o The estimated value of λ i The optimal coefficients for the i-th point and other points.

[0192] At this point, the interpolation position (x) is satisfied. o ,y o The estimated value of ) Compared with the true value z o The set of optimal coefficients with the smallest variance (i.e., the function values ​​at the interpolation positions in step S67 above):

[0193] This expression satisfies the condition for an unbiased estimator. Here, E(x) is the expectation function.

[0194] Kriging interpolation From This is the unbiased constraint condition.

[0195] Specifically, in ordinary Kriging interpolation, for any point (x, y), the interpolation position z(x, y) has the same expected value c and variance σ. 2 :

[0196]

[0197] The next step is to optimize the coefficients. Unfold, and you get:

[0198]

[0199] Where Cov(x,y) is the covariance.

[0200]

[0201] The next step is to calculate the optimal solution with the optimal coefficients:

[0202] Define the semi-mutation function r ij =σ 2 -Cov(zi ,z j and unbiased constraints and substitute get:

[0203]

[0204] calculate The smallest set of λ i :

[0205] Where i = 1, 2, ..., n.

[0206] Next, construct the objective function based on Lagrange multiplication:

[0207]

[0208] Calculate the minimum parameter set φ,λ1,λ2,…,λ of the objective function. i ,…,λ n :

[0209]

[0210] Simplifying the above equation, we get:

[0211]

[0212] Characterized as a system of linear equations:

[0213]

[0214] Converting this system of linear equations into a matrix gives equation (4).

[0215] The matrix in equation (4) can be inverted.

[0216] Preferably, the semi-variogram function is defined as r in the above calculation process. ij =σ 2 -Cov(z i ,z j ), then by

[0217] R i =z i -c can be used to obtain z i -z j =R i -R j , where R i Let R be the random error at the i-th point. jLet be the random error at the j-th point.

[0218] According to z i -z j =R i -R j We can conclude that:

[0219]

[0220] because

[0221] Substitute r ij =σ 2 -Cov(z i ,z j Equation (5) can be obtained from ).

[0222] Further, in step S5, the number and position of the electrodynamic repair rectangles are iteratively calculated within the repair area until all electrodynamic repair rectangles completely cover the entire repair area, and the overlapping area of ​​all electrodynamic repair rectangles reaches its minimum value, including:

[0223] Step S51: Define four random solutions for each electrodynamic repair rectangle, with each corner of the electrodynamic repair rectangle having a random solution, and constrain the relative positions of the four random solutions based on the current electrodynamic repair rectangle.

[0224] Preferably, all random solutions can be defined according to the following formula:

[0225]

[0226] Among them, P i Let p1, p2, ..., p be the set of all random solutions. i ,…,p N-1 ,p N Let i be the index of each random solution, and N be the total number of random solutions; V i Let v1, v2, ..., v be the set of velocities of all random solutions. i ,…,v N-1 ,v N The speeds for each random solution are respectively.

[0227] Step S52, define the optimization result of all random solutions as the minimum value of the overlapping area of ​​the mutually overlapping rectangles repaired by electrodynamics.

[0228] Step S53: Initialize the position of each random solution, and update the current position and current velocity of each random solution respectively.

[0229] Preferably, the current position and current velocity can be updated based on the same random solution according to the following formula:

[0230]

[0231] Among them, v id Let ω·v be the velocity of the i-th random solution at step d. id-1 Let ω be the velocity inertia of the i-th random solution at step d-1, and ω be the inertia coefficient, c1·rand·(P best,i -p i Let be the self-cognitive representation of the i-th random solution, c2·rand·(G best,i -p i ) represents the social cognitive representation of the i-th random solution; c1 and c2 are both learning factors, rand is a random number in [0,1], and P best,i G represents the individual optimal solution obtained for the i-th random solution. best,i For the i-th random solution, p is the globally optimal solution that has been obtained. id For the i-th random solution in step d, p id-1 Let be the i-th random solution in the (d-1)-th step.

[0232] Preferably, the value range of c1 is [0, 0.5], and more preferably 0.4; the value range of c2 is [0.5, 1], and more preferably 0.8.

[0233] Step S54: During the iteration process, delete the electrodynamic repair rectangles that completely exceed the repair area.

[0234] Step S55: Based on each update, obtain the individual optimal solution and the global optimal solution for each random solution.

[0235] Preferably, the inertia coefficient can be linearly decreased once for each update according to the following formula:

[0236]

[0237] Where, ω id Let ω be the inertia coefficient of the i-th random solution after optimization in step d. ini Pace is the initial inertia coefficient. current For the current update steps, Pace max This represents the maximum number of update steps.

[0238] Preferably, the initial inertia coefficient is generally set to 0.5, and the maximum number of update steps is generally set according to actual needs. In this embodiment, it can be set to 10,000 times.

[0239] Step S56: Determine whether the difference between the optimal solution of each individual and the optimal solution of each individual updated in the previous step is less than or equal to the first preset adaptation threshold. If all are less than the threshold, proceed to step S57.

[0240] Step S57: Determine whether the difference between each global optimal solution and each of the previously updated global optimal solutions is less than or equal to the second preset adaptation threshold. If all are less than the threshold, proceed to step S58.

[0241] Preferably, the values ​​of the first preset adaptation threshold and the second preset adaptation threshold need to be adjusted according to the specific problem, and generally need to be adjusted based on the calculation results. If the adaptation threshold is set too small, the algorithm may stop prematurely and fail to obtain the optimal solution; if the adaptation threshold is set too large, the algorithm may over-update, wasting computational resources.

[0242] Preferably, the adaptation threshold can also be evaluated using one of the following functions: Griewank, Rastrigin, Schaffer, Ackley, or Rosenbrock.

[0243] It should be noted that the meanings of the symbols in the above additional content are not interchangeable with those in other parts of the embodiments.

[0244] Step S58: Determine that the optimal solution for all electrodynamically repaired rectangles has been obtained.

[0245] Step S59: Obtain the number of rectangles and the position of the rectangles corresponding to the optimal solution.

[0246] Further, in step S7, the number and position of the repair circles within all electrodynamic repair rectangles are iterated until all repair circles completely cover all electrodynamic repair rectangles, and the overlapping area of ​​all repair circles reaches its minimum, including:

[0247] Step S71: Obtain the positions of all rectangles and merge them into an iterative region.

[0248] Step S72: Define several random solutions in the iteration region, with each random solution corresponding to a repair circle.

[0249] Step S73: Define the optimization result of all random solutions as the minimum value of the overlapping area of ​​all repaired circles.

[0250] Step S74: Initialize the position of each random solution, and update the current position and current velocity of each random solution respectively.

[0251] Step S75: Based on each update, obtain the individual optimal solution and the global optimal solution for each random solution.

[0252] Step S76: Determine whether the difference between the optimal solution of each individual and the optimal solution of each individual updated in the previous step is less than or equal to the first preset adaptation threshold. If all are less than the threshold, proceed to step S77.

[0253] Step S77: Determine whether the difference between each global optimal solution and each of the previously updated global optimal solutions is less than or equal to the second preset adaptation threshold. If all are less than the threshold, proceed to step S78.

[0254] Step S78: Determine that the optimal solution for all repaired circles has been obtained.

[0255] Step S79: Obtain the number of circles and their positions corresponding to the optimal solution.

[0256] Preferably, the iteration of the repair circle is based on the same principle as the iteration of the electrodynamic repair rectangle described above, and the formulas and principles of the above additional content will not be repeated in this embodiment.

[0257] Further, in step S9, each pair of electrodes is switched on to perform soil remediation operations, followed by:

[0258] Step S10: Output the digital elevation model, all electrodynamic repair rectangles, and all repair circles to an external visualization terminal.

[0259] Step S20: Based on the external visualization terminal, add a pair of electrodes within each electrodynamic repair rectangle and a plant at the center of each repair circle.

[0260] Step S30: In response to an external touch operation, a visual pattern is selected by a single click of the touch operation.

[0261] Step S40: Drag all selected visual patterns based on the sliding trajectory of the touch operation.

[0262] This embodiment uses an external concentration detection device to measure several heavy metal content indicators in the area of ​​heavy metal-contaminated soil. Based on all heavy metal content indicators, content contour lines are generated using interpolation. Contour lines with heavy metal content indicators greater than or equal to a preset threshold are defined as remediation areas. A rectangular area for electrodynamic remediation is defined as an electrodynamic remediation rectangle. Within the remediation area, the number and position of the electrodynamic remediation rectangles are iterated until all electrodynamic remediation rectangles completely cover all remediation areas, and the overlapping area of ​​all electrodynamic remediation rectangles reaches a minimum. The hemispherical area of ​​a plant is defined as a remediation circle. Within all electrodynamic remediation rectangles, the number and position of the remediation circles are iterated until all remediation circles completely cover all electrodynamic remediation rectangles, and the overlapping area of ​​all remediation circles reaches a minimum. The final positions of all electrodynamic remediation rectangles and all remediation circles are obtained. A pair of electrodes is placed at the final position of each electrodynamic remediation rectangle, and a plant is planted at the final position of each remediation circle. Each pair of electrodes is then connected to perform soil remediation operations. This embodiment employs a combined electrodynamic and phytoremediation approach. Electrodynamics attracts heavy metal ions to the root system of plants, thus mitigating the uncertainty of long time cycles associated with single remediation methods. Furthermore, computer-aided intelligent iteration of the equipment placement for both remediation methods maximizes remediation effectiveness with minimal electrode and plant counts, preventing errors caused by subjective manual placement that could lead to redundant remediation of certain soil areas or failure to remediate certain soil types. Additionally, this embodiment does not require complete collection of all concentration distributions in the soil to be remediated; missing data can be supplemented using interpolation, thereby reducing labor costs.

[0263] As shown in Figure 3, this embodiment provides an example of a remediation system for heavy metal contaminated soil. In this embodiment, the remediation system is applied to the remediation method described in the above embodiment.

[0264] Specifically, the repair system includes, in sequence, a heavy metal content index acquisition module 1, a content contour line generation module 2, a repair area definition module 3, an electrodynamic repair rectangle definition module 4, an electrodynamic repair rectangle iteration module 5, a repair circle definition module 6, a repair circle iteration module 7, a repair facility placement module 8, and a repair facility activation module 9, all electrically connected.

[0265] The system comprises the following modules: Heavy metal content acquisition module 1, which uses external concentration detectors to obtain several heavy metal content indicators for the area of ​​heavy metal-contaminated soil; content contour line generation module 2, which generates content contour lines based on all heavy metal content indicators using interpolation; remediation area definition module 3, which defines content contour lines with heavy metal content indicators greater than or equal to a preset threshold as remediation areas; electrodynamic remediation rectangle definition module 4, which defines a rectangular area for electrodynamic remediation as an electrodynamic remediation rectangle; and electrodynamic remediation rectangle iteration module 5, which iterates the number and position of electrodynamic remediation rectangles within the remediation area until all electrodynamic remediation rectangles completely cover the entire remediation area, and all... The overlapping area of ​​the electrodynamic remediation rectangles reaches a minimum; the remediation circle definition module 6 defines the hemispherical area of ​​a plant as a remediation circle; the remediation circle iteration module 7 iterates the number and position of the remediation circles within all electrodynamic remediation rectangles until all remediation circles completely cover all electrodynamic remediation rectangles and the overlapping area of ​​all remediation circles reaches a minimum; the remediation facility placement module 8 obtains the final position of all electrodynamic remediation rectangles and the final position of all remediation circles, and places a pair of electrodes at the final position of each electrodynamic remediation rectangle and plants a plant at the final position of each remediation circle; the remediation facility activation module 9 connects each pair of electrodes to perform soil remediation operations.

[0266] Furthermore, the content contour line generation module 2 specifically includes a first content contour line generation submodule, a second content contour line generation submodule, a third content contour line generation submodule, a fourth content contour line generation submodule, a fifth content contour line generation submodule, a sixth content contour line generation submodule, a seventh content contour line generation submodule, an eighth content contour line generation submodule, and a ninth content contour line generation submodule that are electrically connected in sequence; the first content contour line generation submodule is electrically connected to the heavy metal content index acquisition module 1, and the ninth content contour line generation submodule is electrically connected to the repair area definition module 3.

[0267] The first content contour line generation submodule is used to obtain the geographical location of each heavy metal content index based on the heavy metal contaminated soil.

[0268] The second content contour line generation submodule is used to obtain the geographic coordinates of all geographic points and define the Euclidean distance between the interpolation position and all geographic points according to equation (1):

[0269]

[0270] Where, d i Let (x, y) be the Euclidean distance between the interpolation location and the i-th geographic point, and let (x, y) be the coordinates of the interpolation location. i ,yi ) represents the geographic coordinates of the i-th geographic point.

[0271] The third content contour line generation submodule is used to calculate the weight value of the i-th geographic point based on the interpolation location according to equation (2):

[0272]

[0273] Among them, w i is the weight value of the i-th geographic point based on the interpolated position, and p is an adjustment parameter that takes the value of 2 or 3.

[0274] The fourth content contour line generation submodule is used to calculate the function value of the interpolation position according to equation (3):

[0275]

[0276] Where z(x,y) is the function value of the interpolation position, z i Let be the radial basis function for the i-th geographic point. The sum of the radial basis functions of all geographic points multiplied by their corresponding weight values. It is the sum of all weight values. and The ratio is the function value at the interpolation position.

[0277] The fifth content contour line generation submodule is used to obtain the (x,y) value in the function value, which is the interpolation coordinate of the interpolation position.

[0278] The sixth content contour line generation submodule is used to obtain the digital elevation model of the area where heavy metal contaminated soil is located.

[0279] The seventh content contour line generation submodule is used to input all heavy metal content indicators and all corresponding geographic locations into the digital elevation model.

[0280] The eighth content contour line generation submodule is used to input all interpolated coordinates and all corresponding function values ​​into the digital elevation model.

[0281] The ninth content contour line generation submodule is used to linearly connect all equal heavy metal content indicators and function values ​​to obtain content contour lines.

[0282] Furthermore, the content contour line generation module 2 specifically includes a tenth content contour line generation submodule, an eleventh content contour line generation submodule, a twelfth content contour line generation submodule, a thirteenth content contour line generation submodule, a fourteenth content contour line generation submodule, a fifteenth content contour line generation submodule, a sixteenth content contour line generation submodule, a seventeenth content contour line generation submodule, and an eighteenth content contour line generation submodule, which are electrically connected in sequence. The tenth content contour line generation submodule is electrically connected to the heavy metal content index acquisition module 1, and the eighteenth content contour line generation submodule is electrically connected to the repair area definition module 3.

[0283] The tenth content contour line generation submodule is used to obtain the geographical location of each heavy metal content index based on the heavy metal contaminated soil.

[0284] The eleventh content contour line generation submodule is used to calculate the Euclidean distance and semivariogram between every two geographic points based on all geographic points.

[0285] The twelfth content contour line generation submodule is used to solve the fitting curves of all Euclidean distances and all semivariograms, so that the fitting curves can be used to calculate the corresponding semivariograms based on any Euclidean distance.

[0286] The thirteenth content contour line generation submodule is used to solve the semivariogram among all geographic points based on the fitted curve and to define the optimal coefficients of all semivariograms according to equation (4):

[0287]

[0288] Where, r ij Let λ be the semivariogram between the i-th and j-th points. i Let r be the optimal coefficient between the i-th point and other points. io Let φ be the semivariogram from the i-th interpolation position to all points, and φ be the Lagrange multiplier.

[0289] The fourteenth content contour line generation submodule is used to perform a weighted summation of the function values ​​of all points based on all optimal coefficients to obtain the function value of the interpolation position.

[0290] The fifteenth content contour line generation submodule is used to obtain the digital elevation model of the area where heavy metal contaminated soil is located.

[0291] The sixteenth content contour line generation submodule is used to input all heavy metal content indicators and all corresponding geographic locations into the digital elevation model.

[0292] The seventeenth content contour line generation submodule is used to input the coordinates of all interpolation locations and all corresponding function values ​​in the digital elevation model.

[0293] The eighteenth content contour line generation submodule is used to linearly connect all equal heavy metal content indicators and function values ​​to obtain content contour lines.

[0294] Furthermore, the eleventh content contour line generation submodule is also equipped with a semi-variogram function characterized by equation (5):

[0295]

[0296] Among them, z i Let z be the function value for the i-th geographic point. j Let E(·) be the function value of the j-th geographic point, and E(·) be the expected function.

[0297] Furthermore, the electrodynamic repair rectangle iteration module 5 specifically includes a first electrodynamic repair rectangle iteration submodule, a second electrodynamic repair rectangle iteration submodule, a third electrodynamic repair rectangle iteration submodule, a fourth electrodynamic repair rectangle iteration submodule, a fifth electrodynamic repair rectangle iteration submodule, a sixth electrodynamic repair rectangle iteration submodule, a seventh electrodynamic repair rectangle iteration submodule, an eighth electrodynamic repair rectangle iteration submodule, and a ninth electrodynamic repair rectangle iteration submodule that are electrically connected in sequence; the first electrodynamic repair rectangle iteration submodule is electrically connected to the electrodynamic repair rectangle definition module 4, and the ninth electrodynamic repair rectangle iteration submodule is electrically connected to the repair circle definition module 6.

[0298] The first electrodynamic repair rectangle iteration submodule defines four random solutions for each electrodynamic repair rectangle, with each corner of the rectangle having a random solution, and constrains the relative positions of the four random solutions based on the current electrodynamic repair rectangle. The second electrodynamic repair rectangle iteration submodule defines the optimization result of all random solutions as minimizing the overlapping area of ​​the electrodynamic repair rectangles. The third electrodynamic repair rectangle iteration submodule initializes the position of each random solution and updates the current position and velocity of each random solution. The fourth electrodynamic repair rectangle iteration submodule deletes electrodynamic repair rectangles that completely exceed the repair area during the iteration process. The fifth electrodynamic repair rectangle iteration submodule... The first module is used to obtain the individual optimal solution and the global optimal solution for each random solution based on each update; the sixth electrodynamic repair rectangle iteration submodule is used to determine whether the difference between each individual optimal solution and the previous updated individual optimal solution is less than or equal to the first preset adaptation threshold; the seventh electrodynamic repair rectangle iteration submodule is used to determine whether the difference between each global optimal solution and the previous updated global optimal solution is less than or equal to the second preset adaptation threshold if all are less than the threshold; the eighth electrodynamic repair rectangle iteration submodule is used to determine that the optimal solution for all electrodynamic repair rectangles has been obtained if all are less than the threshold; the ninth electrodynamic repair rectangle iteration submodule is used to obtain the number of rectangles and the position of the rectangles corresponding to the optimal solution.

[0299] Furthermore, the repair circle iteration module 7 specifically includes a first repair circle iteration submodule, a second repair circle iteration submodule, a third repair circle iteration submodule, a fourth repair circle iteration submodule, a fifth repair circle iteration submodule, a sixth repair circle iteration submodule, a seventh repair circle iteration submodule, an eighth repair circle iteration submodule, and a ninth repair circle iteration submodule that are electrically connected in sequence; the first repair circle iteration submodule is electrically connected to the repair circle definition module 6, and the ninth repair circle iteration submodule is electrically connected to the repair facility placement module 8.

[0300] The system comprises the following modules: a first repair circle iteration submodule, which acquires all rectangle positions and merges them into an iteration region; a second repair circle iteration submodule, which defines several random solutions within the iteration region, each corresponding to a repair circle; a third repair circle iteration submodule, which defines the optimization result of all random solutions as minimizing the overlapping area of ​​all repair circles; a fourth repair circle iteration submodule, which initializes the position of each random solution and updates its current position and velocity; a fifth repair circle iteration submodule, which acquires the individual optimal solution and the global optimal solution for each random solution based on each update; a sixth repair circle iteration submodule, which determines whether the difference between each individual optimal solution and the previously updated individual optimal solution is less than or equal to a first preset adaptation threshold; a seventh repair circle iteration submodule, which, if both are less than the threshold, determines whether the difference between each global optimal solution and the previously updated global optimal solution is less than or equal to a second preset adaptation threshold; an eighth repair circle iteration submodule, which, if both are less than the threshold, determines that the optimal solution for all repair circles has been obtained; and a ninth repair circle iteration submodule, which acquires the number of circles and their positions corresponding to the optimal solution.

[0301] Furthermore, the repair system also includes a model visualization output module, a model visualization pattern addition module, a model visualization pattern selection module, and a model visualization pattern dragging module, which are electrically connected in sequence; the model visualization output module is electrically connected to the repair facility start-up module 9.

[0302] The model visualization output module outputs the digital elevation model, all electrodynamic repair rectangles, and all repair circles to an external visualization terminal. The model visualization pattern adding module adds a pair of electrodes to each electrodynamic repair rectangle and a plant to the center of each repair circle based on the external visualization terminal. The model visualization pattern selection module responds to external touch operations, selecting a visualization pattern with a single click. The model visualization pattern dragging module drags all selected visualization patterns based on the sliding trajectory of the touch operation.

[0303] It should be noted that this embodiment is a functional module embodiment based on the above method embodiment. For the preferred, extended, limited, exemplified and principle explanation parts of this embodiment, please refer to the above embodiment. This embodiment will not repeat them.

[0304] This embodiment uses an external concentration detection device to measure several heavy metal content indicators in the area of ​​heavy metal-contaminated soil. Based on all heavy metal content indicators, content contour lines are generated using interpolation. Contour lines with heavy metal content indicators greater than or equal to a preset threshold are defined as remediation areas. A rectangular area for electrodynamic remediation is defined as an electrodynamic remediation rectangle. Within the remediation area, the number and position of the electrodynamic remediation rectangles are iterated until all electrodynamic remediation rectangles completely cover all remediation areas, and the overlapping area of ​​all electrodynamic remediation rectangles reaches a minimum. The hemispherical area of ​​a plant is defined as a remediation circle. Within all electrodynamic remediation rectangles, the number and position of the remediation circles are iterated until all remediation circles completely cover all electrodynamic remediation rectangles, and the overlapping area of ​​all remediation circles reaches a minimum. The final positions of all electrodynamic remediation rectangles and all remediation circles are obtained. A pair of electrodes is placed at the final position of each electrodynamic remediation rectangle, and a plant is planted at the final position of each remediation circle. Each pair of electrodes is then connected to perform soil remediation operations. This embodiment employs a combined electrodynamic and phytoremediation approach. Electrodynamics attracts heavy metal ions to the root system of plants, thus mitigating the uncertainty of long time cycles associated with single remediation methods. Furthermore, computer-aided intelligent iteration of the equipment placement for both remediation methods maximizes remediation effectiveness with minimal electrode and plant counts, preventing errors caused by subjective manual placement that could lead to redundant remediation of certain soil areas or failure to remediate certain soil types. Additionally, this embodiment does not require complete collection of all concentration distributions in the soil to be remediated; missing data can be supplemented using interpolation, thereby reducing labor costs.

[0305] Figure 4 is a schematic diagram of the structure of an electronic device according to an embodiment of this application. As shown in Figure 4, the electronic device 10 includes a processor 101 and a memory 102 coupled to the processor 101.

[0306] The memory 102 stores program instructions for implementing a method for remediating heavy metal contaminated soil according to any of the above embodiments.

[0307] The processor 101 is used to execute program instructions stored in the memory 102 for the remediation of heavy metal contaminated soil.

[0308] The processor 101 can also be referred to as a CPU (Central Processing Unit). The processor 101 may be an integrated circuit chip with signal processing capabilities. The processor 101 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0309] Further, Figure 5 is a schematic diagram of the structure of a storage medium according to an embodiment of this application. Referring to Figure 5, the storage medium 11 of this embodiment stores program instructions 111 capable of implementing all the above methods. These program instructions 111 can be stored in the storage medium in the form of a software product, including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, or terminal devices such as computers, servers, mobile phones, and tablets.

[0310] In the several embodiments provided in this application, it should be understood that the disclosed systems, methods, and approaches can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0311] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for remediating heavy metal contaminated soil, the remediation method being based on electrodynamic remediation and phytoremediation, wherein electrodynamic remediation guides and absorbs heavy metal ions within a rectangular area through a pair of electrodes, and phytoremediation involves the absorption of heavy metal ions within a hemispherical area of ​​the plant's root system, characterized in that... The remediation method includes: Step S1, using an external concentration detector to measure several heavy metal content indicators in the area where the heavy metal contaminated soil is located; Step S2, generating content contour lines based on all heavy metal content indicators using interpolation; Step S3, defining the content contour lines where the heavy metal content indicators are greater than or equal to a preset threshold as remediation areas; Step S4, defining a rectangular area for electrodynamic remediation as an electrodynamic remediation rectangle; Step S5, iterating the number and position of the electrodynamic remediation rectangles within the remediation area until all electrodynamic remediation rectangles completely cover all remediation areas, and all electrodynamic remediation... Step S6: Define a repair circle as the circular surface of a plant's hemispherical area. Step S7: Iterate the number and position of the repair circles within all electrodynamic repair rectangles until all repair circles completely cover all electrodynamic repair rectangles and the overlapping area of ​​all repair circles reaches its minimum. Step S8: Obtain the final positions of all electrodynamic repair rectangles and all repair circles, and place a pair of electrodes at the final position of each electrodynamic repair rectangle and plant a plant at the final position of each repair circle. Step S9: Connect each pair of electrodes to perform soil remediation.

2. The repair method according to claim 1, characterized in that, Step S2, generating content contour lines based on all heavy metal content indicators using interpolation, includes: Step S21, obtaining the geographical location of each heavy metal content indicator based on the heavy metal contaminated soil; Step S22, obtaining the geographical coordinates of all geographical locations and defining the Euclidean distance between the interpolation location and all geographical locations according to equation (1): Where, d i Let (x, y) be the Euclidean distance between the interpolated position and the i-th geographic point, and let (x, y) be the coordinates of the interpolated position. i ,y i Let be the geographic coordinates of the i-th geographic point; Step S23, calculate the weight value of the i-th geographic point based on the interpolated position according to equation (2): Among them, w i Let p be the weight value of the i-th geographic point based on the interpolated position, and p be an adjustment parameter with a value of 2 or 3; Step S24, calculate the function value of the interpolated position according to equation (3): Where z(x,y) is the function value of the interpolation position, z i Let be the radial basis function for the i-th geographic point. The sum of the radial basis functions of all geographic points multiplied by their corresponding weight values. It is the sum of all weight values. and The ratio is the function value of the interpolation position; Step S25, obtain the (x,y) value in the function value, which is the interpolation coordinate of the interpolation position; Step S26, obtain the digital elevation model of the area where the heavy metal contaminated soil is located; Step S27, input all heavy metal content indicators and all corresponding geographical points into the digital elevation model; Step S28, input all interpolation coordinates and all corresponding function values ​​into the digital elevation model; Step S29, linearly connect all equal heavy metal content indicators and function values ​​to obtain the content contour line.

3. The repair method according to claim 1, characterized in that, Step S2, generating content contour lines based on all heavy metal content indicators using interpolation, includes: Step S210, obtaining the geographical locations of each heavy metal content indicator based on the heavy metal contaminated soil; Step S220, calculating the Euclidean distance and semivariogram between every two geographical locations; Step S230, solving the fitting curves of all Euclidean distances and all semivariograms, so that the fitting curves can be calculated based on any Euclidean distance to obtain the corresponding semivariogram; Step S240, solving the semivariograms between all geographical locations based on the fitting curves and defining the optimal coefficients of all semivariograms according to equation (4): Where, r ij Let λ be the semivariogram between the i-th and j-th points. i Let r be the optimal coefficient between the i-th point and other points. io Let φ be the semi-variogram from the i-th interpolation position to all points, and φ be the Lagrange multiplier; Step S250: Sum the function values ​​of all points according to all optimal coefficients to obtain the function value of the interpolation position; Step S260: Obtain the digital elevation model of the area where the heavy metal contaminated soil is located; Step S270: Input all heavy metal content indicators and all corresponding geographical points into the digital elevation model; Step S280: Input the coordinates of all interpolation positions and all corresponding function values ​​into the digital elevation model; Step S290: Linearly connect all equal heavy metal content indicators and function values ​​to obtain the content contour lines.

4. The repair method according to claim 3, characterized in that, The semi-variogram is characterized by equation (5): Among them, z i Let z be the function value for the i-th geographic point. j Let E(·) be the function value of the j-th geographic point, and E(·) be the expected function.

5. The repair method according to claim 1, characterized in that, Step S5, iterating the number and position of the electrodynamic repair rectangles within the repair area until all electrodynamic repair rectangles completely cover the entire repair area and the overlapping area of ​​all electrodynamic repair rectangles reaches the minimum value, including: Step S51, defining four random solutions for each electrodynamic repair rectangle, with each corner of the electrodynamic repair rectangle having a random solution, and constraining the relative positions of the four random solutions based on the current electrodynamic repair rectangle; Step S52, defining the optimization result of all random solutions as the overlapping area of ​​the electrodynamic repair rectangles reaching the minimum value; Step S53, initializing the position of each random solution, and updating the current position and current velocity of each random solution respectively; Step S54, during the iteration process... Delete the electrodynamic repair rectangles that completely exceed the repair area; Step S55: Obtain the individual optimal solution and global optimal solution for each random solution based on each update; Step S56: Determine whether the difference between each individual optimal solution and the previous updated individual optimal solution is less than or equal to a first preset adaptation threshold. If both are less than the threshold, proceed to step S757; Step S57: Determine whether the difference between each global optimal solution and the previous updated global optimal solution is less than or equal to a second preset adaptation threshold. If both are less than the threshold, proceed to step S758; Step S58: Determine that the optimal solutions for all electrodynamic repair rectangles have been obtained; Step S59: Obtain the number of rectangles and the position of the rectangles corresponding to the optimal solutions.

6. The repair method according to claim 1, characterized in that, Step S7 involves iterating the number and position of the repair circles within all electrodynamic repair rectangles until all repair circles completely cover all electrodynamic repair rectangles and the overlapping area of ​​all repair circles reaches its minimum. This includes: Step S71, obtaining the positions of all rectangles and merging them into an iteration region; Step S72, defining several random solutions within the iteration region, each random solution corresponding to a repair circle; Step S73, defining the optimization result of all random solutions as the minimum overlapping area of ​​all repair circles; Step S74, initializing the position of each random solution and updating the current position and current velocity of each random solution respectively. Step S75: Obtain the individual optimal solution and the global optimal solution for each random solution based on each update; Step S76: Determine whether the difference between each individual optimal solution and the previous updated individual optimal solution is less than or equal to a first preset adaptation threshold. If both are less than the threshold, proceed to step S77; Step S77: Determine whether the difference between each global optimal solution and the previous updated global optimal solution is less than or equal to a second preset adaptation threshold. If both are less than the threshold, proceed to step S78; Step S78: Determine that the optimal solution for all repaired circles has been obtained; Step S79: Obtain the number of circles and the circle positions corresponding to the optimal solution.

7. The repair method according to claim 2, characterized in that, Step S9: Connect each pair of electrodes to perform soil remediation operations. Then, the process includes: Step S10: Output the digital elevation model, all electrodynamic remediation rectangles, and all remediation circles to an external visualization terminal; Step S20: Based on the external visualization terminal, add a pair of electrodes within each electrodynamic remediation rectangle and a plant at the center of each remediation circle; Step S30: In response to an external touch operation, select a visualization pattern with a single click; Step S40: Drag all selected visualization patterns based on the sliding trajectory of the touch operation.

8. A remediation system for heavy metal contaminated soil, said remediation system being applied to the remediation method as described in any one of claims 1 to 7, characterized in that, The remediation system includes: a heavy metal content index acquisition module, used to obtain several heavy metal content indices of the area where the heavy metal-contaminated soil is located using an external concentration detector; a content contour line generation module, used to generate content contour lines based on all heavy metal content indices using an interpolation method; a remediation area definition module, used to define content contour lines with heavy metal content indices greater than or equal to a preset index threshold as remediation areas; an electrodynamic remediation rectangle definition module, used to define a rectangular range for electrodynamic remediation as an electrodynamic remediation rectangle; and an electrodynamic remediation rectangle iteration module, used to iterate the number and position of the electrodynamic remediation rectangles within the remediation area until all electrodynamic remediation rectangles completely cover the entire remediation area. The system includes a repair circle definition module, which defines a circular area within the hemispherical range of a plant as a repair circle; a repair circle iteration module, which iterates the number and position of the repair circles within all the electrodynamic repair rectangles until all repair circles completely cover all the electrodynamic repair rectangles and the overlapping area of ​​all repair circles reaches a minimum; a repair facility placement module, which obtains the final positions of all the electrodynamic repair rectangles and all the repair circles, and places a pair of electrodes at the final position of each electrodynamic repair rectangle and plants a plant at the final position of each repair circle; and a repair facility activation module, which connects each pair of electrodes to perform soil remediation operations.

9. An electronic device, characterized in that, The device includes a processor and a memory coupled to the processor, the memory storing program instructions executable by the processor; when the processor executes the program instructions stored in the memory, it implements the repair method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores program instructions that, when executed by a processor, can implement the repair method as described in any one of claims 1 to 7.

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