Remediation method and system for heavy metal contaminated soil

Abstract

The invention discloses a heavy metal contaminated soil remediation method and system, and relates to the field of electrical digital data processing.The method adopts electrodynamic force and plant combined remediation, heavy metal ions are attracted into the plant root system range through the electrodynamic force, and therefore the certainty that the time period of a single remediation means is long is made up; meanwhile, the equipment arrangement positions of the two remediation modes are intelligently iterated based on a computer, so that the maximum remediation effect is achieved through the minimum number of electrodes and the minimum number of plants, and errors caused by redundant remediation of some soil blocks or incapability of remediation of some soil due to manual subjective arrangement are prevented; and all concentration distribution of the to-be-restored soil does not need to be completely collected, and data which are not collected can be supplemented through the interpolation method, so that the labor cost is reduced.

Description

Technical Field

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

[0002] Farmland heavy metal pollution is soil pollution caused by excessive deposition of heavy metals in the soil from waste. 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, nickel, etc.

[0003] Farmland heavy metal pollution mainly comes from mining waste residues, pesticides, wastewater, sludge, and atmospheric deposition, etc. For example, mercury mainly comes from mercury-containing wastewater, cadmium and lead pollution mainly come from smelting emissions and automobile exhaust deposition, and arsenic is widely used as insecticides, fungicides, rodenticides, and herbicides. Excessive heavy metals can cause disorders in plant physiological functions and nutritional imbalances. The enrichment coefficients of elements such as cadmium and mercury in crop seeds are relatively high. Even if they exceed the food hygiene standards, they do not affect the growth, development, and yield of crops. In addition, mercury and arsenic can weaken and inhibit the activities of nitrifying and ammonifying bacteria in the soil, affecting nitrogen supply. Heavy metal pollutants themselves have very little mobility in the soil, are not easily leached by water, and are hardly degraded by microorganisms. After entering the human body through the food chain, they are likely to affect health.

[0004] Soil heavy metal pollution remediation refers to the use of physical, chemical, and biological technical means to remove or transform heavy metals in the soil, reducing the harmful concentration or toxicity of heavy metal pollutants to organisms. According to the remediation principle, it can be divided into physical remediation, chemical remediation, and biological remediation. Among them, physical remediation is a technology that uses physical means to separate heavy metal pollutants from the soil, mainly including methods such as soil replacement, heat treatment, vitrification, and electrokinetic remediation. It is simple to operate but has a high cost, is suitable for emergency remediation in small areas, and is difficult to use on a large scale; chemical remediation is a technology that uses chemical reagents or solid materials to interact with heavy metals in the soil to remove heavy metals or reduce the activity of heavy metals, including chemical fixation methods, soil solidification and stabilization, soil leaching methods, etc. It has the advantages of low cost, simple operation, and good effect, but it cannot guarantee the long-term stability of the remediation effect, and some chemical remediation methods are prone to secondary pollution and soil compaction problems; biological remediation uses 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 in the soil. It has the advantages of low energy consumption, low operating cost, no environmental and health hazards, but has the disadvantages of a long remediation cycle and harsh growth conditions for microorganisms.

[0005] As can be seen from the above, the complete remediation of heavy metal contaminated soil depends on the time process. All soil remediations with good effects have the problem of long remediation time. Usually, the arrangement and placement of remediation equipment are carried out by manually measuring the heavy metal content in the soil and placing the remediation equipment at the high points of the heavy metal content, such as placing electrodes or planting plants. There are manual subjective experience errors since the equipment layout stage. Due to the immobility of heavy metal ions and manual subjective experience errors, the coverage range of the soil remediation effect is not comprehensive, resulting in unsatisfactory remediation effects, or redundant layout of remediation equipment leading to waste of resources. Summary of the Invention

[0006] The main purpose of this application is to provide a remediation method and system for heavy metal contaminated soil to solve the problems of long remediation time for heavy metal contaminated soil and unsatisfactory remediation effects due to manual subjective experience errors in equipment layout in the prior art.

[0007] To achieve the above purpose, this application provides the following technical solutions:

[0008] A remediation method for heavy metal contaminated soil, the remediation method is based on electrokinetic remediation and phytoremediation. One electrokinetic remediation guides and absorbs heavy metal ions within a rectangular range through a pair of electrodes, and one phytoremediation absorbs heavy metal ions within the hemispherical range of the plant's absorption roots. The remediation method includes:

[0009] Step S1, detecting several heavy metal content indexes of the area where the heavy metal contaminated soil is located through an external concentration detector;

[0010] Step S2, generating content contour lines by interpolation based on all heavy metal content indexes;

[0011] Step S3, defining the content contour lines with heavy metal content indexes greater than or equal to the preset index threshold as the remediation area;

[0012] Step S4, defining the rectangular range of one electrokinetic remediation as an electrokinetic remediation rectangle;

[0013] Step S5, iterating the number and positions of the rectangles of the electrokinetic remediation rectangle within the remediation area until all electrokinetic remediation rectangles completely cover all remediation areas and the overlapping area of all electrokinetic remediation rectangles reaches the minimum value;

[0014] Step S6, defining the circular surface of the hemispherical range of one plant as a remediation circle;

[0015] Step S7, iterating the number and positions of the circles of the remediation circle within all electrokinetic remediation rectangles until all remediation circles completely cover all electrokinetic remediation rectangles and the overlapping area of all remediation circles reaches the minimum value;

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

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

[0018] As a further improvement of this application, in step S2, generate content contour lines by interpolation based on all heavy metal content indicators, including:

[0019] Step S21: Obtain the geographical positions of each heavy metal content indicator based on the heavy metal contaminated soil respectively.

[0020] Step S22: Obtain the geographical coordinates of all geographical positions and define the Euclidean distance between the interpolation position and all geographical positions according to formula (1):

[0021]

[0022] where d i is the Euclidean distance between the interpolation position and the i-th geographical position, (x, y) is the coordinate of the interpolation position, and (x i , y i ) is the geographical coordinate of the i-th geographical position;

[0023] Step S23: Calculate the weight value of the i-th geographical position based on the interpolation position according to formula (2):

[0024]

[0025] where w i is the weight value of the i-th geographical position based on the interpolation position, and p is an adjustment parameter with a value of 2 or 3;

[0026] Step S24: Calculate the function value of the interpolation position according to formula (3):

[0027]

[0028] where z(x, y) is the function value of the interpolation position, z i is the radial basis function of the i-th geographical position, is the sum of the radial basis functions of all geographical positions multiplied by the corresponding weight values, is the sum of all weight values, and the ratio of is the function value of the interpolation position;

[0029] Step S25: Obtain the (x, y) values in the function values, which are the interpolation coordinates 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 geographical points in the digital elevation model.

[0032] Step S28: Input all interpolation coordinates and all corresponding function values in the digital elevation model.

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

[0034] As a further improvement of this application, step S2: Generate content contour lines by interpolation based on all heavy metal content indicators, including:

[0035] Step S210: Respectively obtain the geographical points of each heavy metal content indicator based on the geographical points of the heavy metal contaminated soil.

[0036] Step S220: Respectively calculate the Euclidean distance and semivariogram between every two geographical points based on all geographical points.

[0037] Step S230: Solve the fitting curve of all Euclidean distances and all semivariograms, so that the fitting curve can calculate the corresponding semivariogram according to any Euclidean distance.

[0038] Step S240: Solve the semivariogram between all geographical points according to the fitting curve and define the optimal coefficient of all semivariograms according to formula (4):

[0039]

[0040] where r ij is the semivariogram between the i-th point and the j-th point, λ i is the optimal coefficient of the i-th point and other points, r io is the semivariogram from the i-th interpolation position to all points, and φ is the Lagrange multiplier;

[0041] Step S250: Perform weighted summation on the function values of all points 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 geographical positions in the digital elevation model;

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

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

[0046] As a further improvement of the present application, the semivariogram is characterized by formula (5):

[0047]

[0048] where z i is the function value of the i-th geographical position, and z j is the function value of the j-th geographical position, and E(·) is the expectation function.

[0049] As a further improvement of the present application, in step S5, iterate the number of rectangles and the positions of the electrokinetic remediation rectangles within the remediation area until all electrokinetic remediation rectangles completely cover all remediation areas and the overlapping area of all electrokinetic remediation rectangles reaches the minimum value, including:

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

[0051] Step S52: Define the optimization result of all random solutions as the overlapping area of the electrokinetic remediation rectangles reaching the minimum value;

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

[0053] Step S54: Delete the electrokinetic remediation rectangles that completely exceed the remediation area during the iteration process;

[0054] Step S55: Obtain the individual optimal solution and the global optimal solution of each random solution based on each update respectively;

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

[0056] Step S57: Determine whether the difference between each global optimal solution and the corresponding global optimal solution in the previous update is less than or equal to the second preset adaptation threshold. If all are less, then execute step S58;

[0057] Step S58, determine that the optimal solutions of all electrokinetic remediation rectangles have been obtained;

[0058] Step S59, obtain the number of rectangles and the rectangle positions corresponding to the optimal solutions.

[0059] As a further improvement of the present application, in step S7, iterate the number of circles and the circle positions of the repair circles within all electrokinetic remediation rectangles until all repair circles completely cover all electrokinetic remediation rectangles and the overlapping area of all repair circles reaches the minimum value, including:

[0060] Step S71, obtain all rectangle positions and fuse them into an iterative region;

[0061] Step S72, define a number of random solutions within the iterative region, and each random solution corresponds to a repair circle;

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

[0063] Step S74, initialize the positions of each random solution, and update the current position and the current speed of each random solution respectively;

[0064] Step S75, obtain the individual optimal solutions and the global optimal solutions of each random solution respectively based on each update;

[0065] Step S76, respectively determine whether the difference between each individual optimal solution and the corresponding individual optimal solution in the previous update is less than or equal to a first preset adaptation threshold. If all are less, then execute step S77;

[0066] Step S77, respectively determine whether the difference between each global optimal solution and the corresponding global optimal solution in the previous update is less than or equal to a second preset adaptation threshold. If all are less, then execute step S78;

[0067] Step S78, determine that the optimal solutions of all repair circles have been obtained;

[0068] Step S79, obtain the number of circles and the circle positions corresponding to the optimal solutions.

[0069] As a further improvement of the present application, in step S9, connect each pair of electrodes respectively to perform the soil remediation operation, and then, including:

[0070] Step S10, output the digital elevation model, all electrokinetic remediation rectangles, and all repair circles to an external visualization terminal;

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

[0072] Step S30: In response to an external touch operation, select a visualization pattern based on a single click of the touch operation.

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

[0074] To achieve the above object, the present application also provides the following technical solutions:

[0075] A remediation system for heavy metal contaminated soil, the remediation system is applied to the remediation method as described above, and the remediation system includes:

[0076] A heavy metal content index acquisition module, configured to obtain several heavy metal content indexes of the area where the heavy metal contaminated soil is located through an external concentration detection component;

[0077] A content contour generation module, configured to generate content contours by interpolation based on all heavy metal content indexes;

[0078] A remediation area definition module, configured to define the content contours with heavy metal content indexes greater than or equal to a preset index threshold as the remediation area;

[0079] An electrokinetic remediation rectangle definition module, configured to define a rectangular range of an electrokinetic remediation as an electrokinetic remediation rectangle;

[0080] An electrokinetic remediation rectangle iteration module, configured to iterate the number and position of the electrokinetic remediation rectangles within the remediation area until all electrokinetic remediation rectangles completely cover all remediation areas and the overlapping area of all electrokinetic remediation rectangles reaches the minimum value;

[0081] A remediation circle definition module, configured to define a circular surface of a hemispherical range of a plant as a remediation circle;

[0082] A remediation circle iteration module, configured to iterate the number and position of the remediation circles within all electrokinetic remediation rectangles until all remediation circles completely cover all electrokinetic remediation rectangles and the overlapping area of all remediation circles reaches the minimum value;

[0083] A remediation facility placement module, configured to obtain the final positions of all electrokinetic remediation rectangles and the final positions of all remediation circles, and place a pair of electrodes at the final positions of each electrokinetic remediation rectangle and plant a plant at the final positions of each remediation circle;

[0084] A repair facility startup module for separately connecting each pair of electrodes to perform soil repair operations.

[0085] To achieve the above object, the present application also provides the following technical solutions:

[0086] An electronic device includes a processor and a memory coupled to the processor. The memory stores program instructions executable by the processor. When the processor executes the program instructions stored in the memory, the above-described repair method is implemented.

[0087] To achieve the above object, the present application also provides the following technical solutions:

[0088] A storage medium stores program instructions that can implement the above-described repair method when executed by a processor.

[0089] The present application detects several heavy metal content indicators in the area of heavy metal contaminated soil through an external concentration detector; generates content contour lines by interpolation based on all heavy metal content indicators; defines the content contour lines with heavy metal content indicators greater than or equal to a preset indicator threshold as repair areas; defines a rectangular range of electrokinetic remediation as an electrokinetic remediation rectangle; iterates the number and position of rectangles of the electrokinetic remediation rectangle within the repair area until all electrokinetic remediation rectangles completely cover all repair areas and the overlapping area of all electrokinetic remediation rectangles reaches the minimum value; defines the circular surface of the hemispherical range of a plant as a repair circle; iterates the number and position of circles of the repair circle within all electrokinetic remediation rectangles until all repair circles completely cover all electrokinetic remediation rectangles and the overlapping area of all repair circles reaches the minimum value; obtains the final positions of all electrokinetic remediation rectangles and the final positions of all repair circles, places a pair of electrodes at the final position of each electrokinetic remediation rectangle, and plants a plant at the final position of each repair circle; separately connects each pair of electrodes to perform soil repair operations. The present application adopts the combined remediation of electrokinetics and plants, attracts heavy metal ions to the range of plant roots through electrokinetics, thus making up for the certainty of the long time period of a single remediation method. At the same time, based on computer intelligence, the device arrangement positions of the two remediation methods are iterated to achieve the maximum remediation effect with the least number of electrodes and the least number of plants, preventing errors caused by manual subjective arrangement, such as redundant remediation of some soil blocks or non-remediation of some soil. Moreover, the present application does not need to completely collect all concentration distributions of the soil to be remediated, and the data that has not been collected can be supplemented by the interpolation method of the present application, thereby reducing labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] Figure 1 It is a schematic flowchart of the steps of an embodiment of a method for remediating heavy metal contaminated soil of the present application;

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

[0092] Figure 3 This is the schematic diagram of the functional modules for an embodiment of a system for remediating heavy metal contaminated soil in this application.

[0093] Figure 4 This is the schematic diagram of the structure for an embodiment of an electronic device in this application.

[0094] Figure 5 This is the schematic diagram of the structure for an embodiment of a storage medium in this application. Specific embodiments

[0095] Next, the technical solutions in the embodiments of this application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of this application.

[0096] The terms "first", "second", and "third" in this application are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first", "second", and "third" may explicitly or implicitly include at least one of such features. In the description of this application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically and clearly defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of this application are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the drawings). If the specific posture changes, then the directional indications will also change accordingly. In addition, the terms "include" and "have" 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 optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0097] Referring to "embodiments" herein means that the specific features, structures, or characteristics described in conjunction with the embodiments may be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0098] As Figure 1 shown, this embodiment provides an embodiment of a method for remediating heavy metal contaminated soil. In this embodiment, the remediation method is based on electrokinetic remediation and phytoremediation. One electrokinetic remediation guides and absorbs heavy metal ions within a rectangular range through a pair of electrodes, and one phytoremediation absorbs heavy metal ions within the hemispherical range of the plant's root system.

[0099] Preferably, during the actual electrokinetic remediation process, it can be known that the influence range of a group of electrokinetic remediations is approximately a cuboid. The cuboid is completely immersed in the soil, and the upper surface of the cuboid is flush with the soil surface. When viewed from above with the soil surface as a plane, it is a rectangle. Since the shape of the part below the soil surface is the same as that of the upper surface, only the rectangular shape on the surface needs to be considered. Similarly, the phytoremediation range is the same as the growth range of the roots. The roots of the plant are approximately a hemisphere, that is, the part on the soil surface is a circle. Since the root part of the plant is determined by the variety, the circle on the soil surface can be iterated when determining the plant variety, and reasonable close planting can also be taken into account.

[0100] Preferably, an activator can also be used during the soil remediation process to accelerate the remediation process in order to achieve the purpose of shortening the remediation cycle. The use of a good activator can improve the soil structure: the soil activator can effectively improve the physical properties of the soil, increase the looseness of the soil, reduce the hardening phenomenon, and improve the air permeability and water permeability of the soil; adjust the soil pH value: by adjusting the acidity and alkalinity of the soil, make the soil more suitable for plant growth; increase soil fertility: the soil activator contains components such as humus, beneficial bacteria, and fungi, which can improve the soil structure and increase the organic matter content of the soil, thereby increasing soil fertility.

[0101] Among them, the methods for using the activator in soil remediation mainly include spraying method, basal application method, furrow application method, hole application method, and fertilizer mixing method.

[0102] It should be noted that the use of the activator is already a mature existing technology, and the use of the activator in this embodiment is also a conventional use. The use methods and steps of the activator will not be elaborated in this embodiment.

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

[0104] Step S1, detect several heavy metal content indicators in the area where the heavy metal contaminated soil is located through an external concentration detector.

[0105] Preferably, the detection methods for soil heavy metal content mainly include the following several types:

[0106] ①Atomic Absorption Spectrometry (AAS): It has high sensitivity, high selectivity and good precision. By measuring the absorption of the ground-state atoms of the element to be measured for specific wavelength radiation, it quantitatively analyzes the heavy metal content in soil samples. AAS is easy to operate and is widely used in the routine detection of soil heavy metals.

[0107] ②Inductively Coupled Plasma Mass Spectrometry (ICP-MS): It uses a high-temperature plasma to ionize the elements in the sample and detects them through a mass spectrometer; ICP-MS has the advantages of low detection limit and fast analysis speed, and is especially suitable for the determination of trace heavy metal elements in soil.

[0108] ③Atomic Fluorescence Spectrometry (AFS): It quantitatively analyzes the heavy metal content in soil by measuring the fluorescence intensity of the element to be measured. AFS has the advantages of high sensitivity and good selectivity, and is especially suitable for the detection of low-concentration heavy metals.

[0109] ④X-ray Fluorescence Spectrometry (XRF): It analyzes the heavy metal elements in soil by measuring the fluorescent X-rays emitted by the sample under X-ray excitation. XRF is easy to operate and the sample preparation is simple, and it is suitable for quickly screening heavy metal pollution in soil.

[0110] ⑤Electrochemical analysis method: It quantitatively analyzes the heavy metal content in soil by measuring the current or potential change generated during the electrode reaction process. The electrochemical analysis method has simple equipment and convenient operation, and is suitable for on-site rapid detection.

[0111] ⑥Laser Induced Breakdown Spectroscopy: It qualitatively and quantitatively analyzes chemical elements in real time and quickly.

[0112] ⑦Biological. The biological detection method has the advantages of simple operation and low cost, and is suitable for preliminary screening.

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

[0114] Step S2, generate content contour lines by interpolation based on all heavy metal content indexes.

[0115] Preferably, equivalent to the topographic contour lines, connect the places with the same numerical value of the heavy metal content index with lines.

[0116] Step S3, define the content contour lines with heavy metal content indexes greater than or equal to the preset index threshold as the repair area.

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

[0118] ① Class I soils: Mainly applicable to nature reserves, centralized drinking water sources, etc., and the heavy metal content should maintain the natural background level. The specific limits are as follows:

[0119] Cadmium (Cd) ≤ 0.2 mg / kg.

[0120] Mercury (Hg) ≤ 0.15 mg / kg.

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

[0122] Copper (Cu) ≤ 35 mg / kg.

[0123] Lead (Pb) ≤ 35 mg / kg.

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

[0125] Zinc (Zn) ≤ 100 mg / kg.

[0126] Nickel (Ni) ≤ 40 mg / kg.

[0127] ② Class II soils: Applicable to general farmland, vegetable fields, etc., to ensure agricultural production and maintain human health. The specific limits 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) ≤ 30 mg / kg (paddy field) or ≤ 40 mg / kg (dry land).

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

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

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

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

[0135] Nickel (Ni) ≤ 40 mg / kg.

[0136] ③ Class III soils: Suitable for forest land and soils with high background values and large pollutant capacities, etc., to ensure agricultural and forestry production and the normal growth of plants. The specific limitations are as follows:

[0137] Mercury (Hg) ≤ 1.5 mg / kg.

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

[0139] Copper (Cu) ≤ 400 mg / kg.

[0140] Lead (Pb) ≤ 500 mg / kg.

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

[0142] Zinc (Zn) ≤ 500 mg / kg.

[0143] Nickel (Ni) ≤ 200 mg / kg.

[0144] Step S4, define a rectangular range of electrokinetic remediation as an electrokinetic remediation rectangle.

[0145] Preferably, it is only necessary to define the rectangle on the soil surface.

[0146] Step S5, iterate the number and position of rectangles of the electrokinetic remediation rectangle within the remediation area until all electrokinetic remediation rectangles completely cover all remediation areas and the overlapping area of all electrokinetic remediation rectangles reaches the minimum value.

[0147] Step S6, define the circular surface of the hemispherical range of a plant as a remediation circle.

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

[0149] Step S7, iterate the number and position of circles of the remediation circle within all electrokinetic remediation rectangles until all remediation circles completely cover all electrokinetic remediation rectangles and the overlapping area of all remediation circles reaches the minimum value.

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

[0151] Step S8, obtain the final positions of all electrokinetic remediation rectangles and the final positions of all remediation circles, and place a pair of electrodes at the final position of each electrokinetic remediation rectangle and plant a plant at the final position of each remediation circle.

[0152] Step S9, connect each pair of electrodes respectively to perform soil remediation operations.

[0153] Preferably, referring to Figure 2 , soil heavy metal pollution is characterized by complex pollution processes, prominent hazards, and difficult remediation. Remediation is urgent. Electrokinetic phytoremediation aims to make up for the respective disadvantages of electrokinetics and phytoremediation, synergistically leverage their advantages, and solve prominent problems such as the inability of electrokinetics to completely remove heavy metals from the soil and the slow speed and limited scope of action of phytoremediation. In the electrokinetic phytoremediation system, electrokinetics and plants interact, and there are effects that are either beneficial or detrimental to heavy metal removal. There are also many synergistic effects between the two in overcoming their own limitations; the electrokinetic phytoremediation process is mainly controlled by factors such as the type of electric field, the arrangement and intensity of the electric field, pH evolution, and additives. Electrokinetics can effectively improve the absorption and enrichment of heavy metals by plants and the remediation effect of contaminated soil through mechanisms such as improving the spatial and morphological distribution of heavy metals, promoting nutrient absorption, and stimulating rhizosphere secretion.

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

[0155] Step S21, respectively obtain the geographical positions of each heavy metal content indicator based on the heavy metal contaminated soil.

[0156] Step S22, obtain the geographical coordinates of all geographical positions and define the Euclidean distance between the interpolation position and all geographical positions according to Equation (1):

[0157]

[0158] where d i is the Euclidean distance between the interpolation position and the i-th geographical position, (x, y) is the coordinate of the interpolation position, and (x i , y i ) is the geographical coordinate of the i-th geographical position.

[0159] Step S23, calculate the weight value of the i-th geographical position based on the interpolation position according to Equation (2):

[0160]

[0161] where w i is the weight value of the i-th geographical position based on the interpolation position, and p is a regulation parameter with a value of 2 or 3.

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

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

[0164] Preferably, the Manhattan distance is the distance between two points in the longitudinal normal direction (north-south direction) plus the distance in the transverse normal direction (east-west direction). For a layout with regular north-south and east-west directions, the distance from one point to another is exactly the distance traveled in the north-south direction plus the distance traveled in the east-west direction. And the Manhattan distance is not a distance invariant. When the coordinate axes change, the distance between points will be different. The advantage of the Manhattan distance lies in the computing power of floating-point operations. If the Euclidean distance of AB is directly used, floating-point operations must be performed. If AC and CB are used, only addition and subtraction need to be calculated, thus improving the operation speed and there is no error.

[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 is the radial basis function of the i-th geographical point position, is the sum of the radial basis functions of all geographical point positions multiplied by the corresponding weight values, is the sum of all weight values, and The ratio of is the function value of the interpolation position.

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

[0169] Step S25, obtain the (x, y) values in the function value, which are the interpolation coordinates 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 geographical point positions in the digital elevation model.

[0172] Step S28, input all interpolation coordinates and all corresponding function values in the digital elevation model.

[0173] Step S29, linearly connect all equal heavy metal content indicators and function values to obtain the content contour line.

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

[0175] In step S210, the geographical positions of the heavy metal polluted soil corresponding to each heavy metal content index are obtained respectively.

[0176] In step S220, the Euclidean distance and semi-variogram between every two geographical positions are calculated respectively based on all the geographical positions.

[0177] In step S230, the fitting curve of all the Euclidean distances and all the semi-variograms is solved so that the corresponding semi-variogram can be calculated according to any Euclidean distance for the fitting curve.

[0178] In step S240, the semi-variograms between all the geographical positions are solved according to the fitting curve and the optimal coefficients of all the semi-variograms are defined according to formula (4):

[0179]

[0180] where r ij is the semi-variogram between the i-th position and the j-th position, λ i is the optimal coefficient of the i-th position and other positions, r io is the semi-variogram from the i-th interpolation position to all positions, and φ is the Lagrange multiplier.

[0181] In step S250, the function values of all positions are weighted and summed according to all the optimal coefficients to obtain the function value of the interpolation position.

[0182] In step S260, the digital elevation model of the area where the heavy metal polluted soil is located is obtained.

[0183] In step S270, all the heavy metal content indexes and all the corresponding geographical positions are input into the digital elevation model.

[0184] In step S280, the coordinates of all the interpolation positions and all the corresponding function values are input into the digital elevation model.

[0185] In step S290, all the equal heavy metal content indexes and function values are linearly connected to obtain the content contour lines.

[0186] Further, the semi-variogram is characterized by formula (5):

[0187]

[0188] where z i is the function value of the i-th geographical position, z jis the function value of the j-th geographical point, and E(·) is the expectation function.

[0189] Preferably, the calculation process from step S220 to step S250 is as follows:

[0190] Define the Kriging interpolation formula

[0191] where is the estimated value at the interpolation position (x o , y o ), and λ i is the optimal coefficient between the i-th point and other points.

[0192] At this time, a set of optimal coefficients that minimize the variance between the estimated value at the interpolation position (x o , y o ) and the true value z o (i.e., the function value at the interpolation position in step S67 above):

[0193] This formula satisfies the condition of unbiased estimation where E(x) is the expectation function.

[0194] Substitute the Kriging interpolation formula obtained to get the unbiased constraint condition.

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

[0196]

[0197] Next, expand the optimal coefficient to get:

[0198]

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

[0200]

[0201] Next, calculate the optimal solution of the optimal coefficient:

[0202] Define the semivariogram r ij = σ 2 - Cov(z i , z j ) and the unbiased constraint condition and substitute into to get:

[0203]

[0204] Calculate the smallest set of λ i :

[0205] where i = 1, 2, …, n.

[0206] Next, construct the objective function according to the Lagrange multiplier method:

[0207]

[0208] Calculate the minimum parameter sets φ, λ of this objective function 1 , λ 2 , …, λ i , …, λ n :

[0209]

[0210] Simplify the above formula to get:

[0211]

[0212] Characterize it as a system of linear equations:

[0213]

[0214] Convert this system of linear equations into a matrix, which is Equation (4).

[0215] Just find the inverse matrix of the matrix in Equation (4).

[0216] Preferably, in the above calculation process, the semivariogram is defined as r ij = σ 2 - Cov(z i , z j ), then from

[0217] R i = z i - c, it can be obtained that z i - z j = R i - R j , where R i is the random error at the i-th point, and R j is the random error at the j-th point.

[0218] According to z i - z j = R i - R j it can be obtained that:

[0219]

[0220] Since

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

[0222] Further, in step S5, iterate the number and positions of the rectangles of the electrokinetic remediation rectangle within the remediation area until all the electrokinetic remediation rectangles completely cover all the remediation areas and the overlapping area of all the electrokinetic remediation rectangles reaches the minimum value, including:[[]]

[0223] Step S51, define four random solutions for each electrokinetic remediation rectangle respectively. Each corner of each electrokinetic remediation rectangle has a random solution, and the relative positions of the four random solutions are constrained based on the current electrokinetic remediation rectangle.[[]]

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

[0225]

[0226] where P i is the set of all random solutions, p 1 , p 2 ,..., p i ,…, p N-1 , p N are each random solution respectively, i is the label of the random solution, N is the number of all random solutions; V i is the set of the velocities of all random solutions, v 1 , v 2 ,..., v i ,…, v N-1 , v N are the velocities of each random solution respectively.[[]]

[0227] Step S52, define the optimization result of all random solutions as the overlapping area of the electrokinetic remediation rectangles reaching the minimum value.[[]]

[0228] Step S53, initialize the positions 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 respectively according to the following formula based on the same random solution:[[]]

[0230]

[0231] Among them, v id is the velocity of the i-th random solution at the d-th step, ω·v id-1 is the velocity inertia of the i-th random solution at the (d-1)-th step, ω is the inertia coefficient, c 1 ·rand·(P best,i -p i ) is the self-cognition representation of the i-th random solution, c 2 ·rand·(G best,i -p i ) is the social-cognition representation of the i-th random solution; c 1 and c 2 are both learning factors, rand is a random number in [0,1], P best,i is the individual optimal solution obtained by the i-th random solution, G best,i is the global optimal solution obtained by the i-th random solution, p id is the i-th random solution at the d-th step, p id-1 is the i-th random solution at the (d-1)-th step.

[0232] Preferably, the value range of c 1 is [0, 0.5], preferably 0.4; the value range of c 2 is [0.5, 1], preferably 0.8.

[0233] Step S54, in the iterative process, delete the electrokinetic remediation rectangle that completely exceeds the remediation area.

[0234] Step S55, based on each update, obtain the individual optimal solution and the global optimal solution of each random solution respectively.

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

[0236]

[0237] Among them, ω id is the optimized inertia coefficient of the i-th random solution at the d-th step, ω ini is the initial inertia coefficient, Pace current is the current update step number, Pace max is the maximum update step number.

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

[0239] Step S56, respectively judge whether the difference between each individual optimal solution and each individual optimal solution in the previous update is less than or equal to the first preset adaptation threshold. If all are less, execute Step S57.

[0240] In step S57, it is determined whether the difference between each globally optimal solution and each globally optimal solution updated last time is less than or equal to a second preset fitness threshold. If all are less, step S58 is executed.

[0241] Preferably, the values of the first preset fitness threshold and the second preset fitness threshold need to be adjusted according to specific problems, generally according to the calculation results. If the fitness threshold is set too small, it may cause the algorithm to stop prematurely and the optimal solution cannot be obtained; if the fitness threshold is set too large, it may cause the algorithm to be updated excessively, wasting computing resources.

[0242] Preferably, the fitness threshold can also be evaluated by one of the Griewank function, Rastrigin function, Schaffer function, Ackley function, and Rosenbrock function.

[0243] It should be noted that the symbol meanings in the above additional content are not interoperable with other parts of the embodiment.

[0244] In step S58, it is determined that the optimal solutions of all electrokinetic remediation rectangles have been obtained.

[0245] In step S59, the number of rectangles and the rectangle positions corresponding to the optimal solutions are obtained.

[0246] Furthermore, in step S7, the number of circles and the circle positions in all electrokinetic remediation rectangles are iteratively repaired until all the repaired circles completely cover all the electrokinetic remediation rectangles and the overlapping area of all the repaired circles reaches the minimum value, including:

[0247] In step S71, all rectangle positions are obtained and merged into an iterative region.

[0248] In step S72, a number of random solutions are defined in the iterative region, and each random solution corresponds to a repaired circle.

[0249] In step S73, the optimization result of all random solutions is defined as the overlapping area of all repaired circles reaching the minimum value.

[0250] In step S74, the position of each random solution is initialized, and the current position and current speed of each random solution are updated respectively.

[0251] In step S75, the individual optimal solution and the global optimal solution of each random solution are obtained respectively based on each update.

[0252] In step S76, it is determined whether the difference between each individual optimal solution and each individual optimal solution updated last time is less than or equal to a first preset fitness threshold. If all are less, step S77 is executed.

[0253] Step S77: Determine whether the difference between each globally optimal solution and each globally optimal solution updated last time is less than or equal to a second preset adaptation threshold. If all are less, then execute Step S78.

[0254] Step S78: Determine that the optimal solutions of all repair circles have been obtained.

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

[0256] Preferably, the iteration of the repair circles is based on the same principle as the iteration of the electrokinetic repair rectangles above. In this embodiment, the formulas and principles of the above additional content are not elaborated again.

[0257] Further, in Step S9, each pair of electrodes is connected separately to perform the soil repair operation. After that, it includes:

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

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

[0260] Step S30: In response to an external touch operation, select a visualization pattern based on a single click touch of the touch operation.

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

[0262] In this embodiment, several heavy metal content indicators in the area of heavy metal contaminated soil are detected by an external concentration detector; based on all the heavy metal content indicators, a content contour line is generated by interpolation; the content contour line with a heavy metal content indicator greater than or equal to a preset indicator threshold is defined as a remediation area; a rectangular range of electrokinetic remediation is defined as an electrokinetic remediation rectangle; in the remediation area, the number of rectangles and the positions of the rectangles of the electrokinetic remediation rectangle are iterated until all the electrokinetic remediation rectangles completely cover all the remediation areas and the overlapping area of all the electrokinetic remediation rectangles reaches the minimum value; the circular surface of the hemispherical range of a plant is defined as a remediation circle; in all the electrokinetic remediation rectangles, the number of circles and the positions of the circles of the remediation circle are iterated until all the remediation circles completely cover all the electrokinetic remediation rectangles and the overlapping area of all the remediation circles reaches the minimum value; the final positions of all the electrokinetic remediation rectangles and the final positions of all the remediation circles are obtained, and a pair of electrodes are placed at the final position of each electrokinetic remediation rectangle and a plant is planted at the final position of each remediation circle; each pair of electrodes is connected respectively to perform soil remediation operations. This embodiment adopts the combined remediation of electrokinetics and plants, and attracts heavy metal ions to the range of plant roots through electrokinetics, thus making up for the certainty of the long time period of a single remediation method. At the same time, based on computer intelligence, the arrangement positions of the two remediation methods are iterated to achieve the maximum remediation effect with the least number of electrodes and the least number of plants, preventing errors such as redundant remediation of some soil blocks or non-remediation of some soil caused by manual subjective arrangement. Moreover, this embodiment does not need to completely collect all the concentration distributions of the soil to be remediated, and the data that have not been collected can be supplemented by the interpolation method of this embodiment, thus reducing the labor cost.

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

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

[0265] Among them, the heavy metal content index acquisition module 1 is used to obtain several heavy metal content indexes of the area where the heavy metal-contaminated soil is located through an external concentration detector; the content contour generation module 2 is used to generate content contours by interpolation based on all heavy metal content indexes; the remediation area definition module 3 is used to define the content contours with heavy metal content indexes greater than or equal to the preset index threshold as the remediation area; the electrokinetic remediation rectangle definition module 4 is used to define a rectangular range of electrokinetic remediation as an electrokinetic remediation rectangle; the electrokinetic remediation rectangle iteration module 5 is used to iterate the number and position of the rectangles of the electrokinetic remediation rectangle within the remediation area until all electrokinetic remediation rectangles completely cover all remediation areas and the overlapping area of all electrokinetic remediation rectangles reaches the minimum value; the remediation circle definition module 6 is used to define the circular surface of the hemispherical range of a plant as a remediation circle; the remediation circle iteration module 7 is used to iterate the number and position of the circles of the remediation circle within all electrokinetic remediation rectangles until all remediation circles completely cover all electrokinetic remediation rectangles and the overlapping area of all remediation circles reaches the minimum value; the remediation facility placement module 8 is used to obtain the final positions of all electrokinetic remediation rectangles and the final positions of all remediation circles, and place a pair of electrodes at the final position of each electrokinetic remediation rectangle and plant a plant at the final position of each remediation circle; the remediation facility activation module 9 is used to connect each pair of electrodes separately to perform soil remediation operations.

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

[0267] Among them, the first content contour generation sub-module is used to respectively obtain the geographical positions of each heavy metal content index based on the geographical positions of the heavy metal-contaminated soil.

[0268] The second content contour generation sub-module is used to obtain the geographical coordinates of all geographical positions and define the Euclidean distance between the interpolation position and all geographical positions according to formula (1):

[0269]

[0270] Among them, d i is the Euclidean distance between the interpolation position and the i-th geographical position, (x,y) is the coordinate of the interpolation position, (x i ,y i) is the geographical coordinate of the i-th geographical location point.

[0271] The third content contour line generation sub-module is used to calculate the weight value of the i-th geographical location point based on the interpolation position according to Equation (2):

[0272]

[0273] where, w i is the weight value of the i-th geographical location point based on the interpolation position, p is an adjustment parameter, and the value is 2 or 3.

[0274] The fourth content contour line generation sub-module 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 is the radial basis function of the i-th geographical location point, is the sum of the radial basis functions of all geographical location points multiplied by the corresponding weight values, is the sum of all weight values, and The ratio of is the function value of the interpolation position.

[0277] The fifth content contour line generation sub-module 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 sub-module is used to obtain the digital elevation model of the area where the heavy metal contaminated soil is located.

[0279] The seventh content contour line generation sub-module is used to input all heavy metal content indicators and all corresponding geographical location points into the digital elevation model.

[0280] The eighth content contour line generation sub-module is used to input all interpolation coordinates and all corresponding function values into the digital elevation model.

[0281] The ninth content contour line generation sub-module is used to linearly connect all equal heavy metal content indicators and function values to obtain the content contour line.

[0282] Further, the content contour generation module 2 specifically further includes a tenth content contour generation sub-module, an eleventh content contour generation sub-module, a twelfth content contour generation sub-module, a thirteenth content contour generation sub-module, a fourteenth content contour generation sub-module, a fifteenth content contour generation sub-module, a sixteenth content contour generation sub-module, a seventeenth content contour generation sub-module, and an eighteenth content contour generation sub-module that are electrically connected in sequence; the tenth content contour generation sub-module is electrically connected to the heavy metal content index acquisition module 1, and the eighteenth content contour generation sub-module is electrically connected to the remediation area definition module 3.

[0283] Among them, the tenth content contour generation sub-module is used to respectively obtain the geographical positions of each heavy metal content index based on the heavy metal contaminated soil.

[0284] The eleventh content contour generation sub-module is used to respectively calculate the Euclidean distance and the semivariogram between every two geographical positions based on all the geographical positions.

[0285] The twelfth content contour generation sub-module is used to solve the fitting curve of all the Euclidean distances and all the semivariograms, so that the fitting curve can calculate the corresponding semivariogram according to any Euclidean distance.

[0286] The thirteenth content contour generation sub-module is used to solve the semivariograms between all the geographical positions according to the fitting curve and define the optimal coefficients of all the semivariograms according to Equation (4):

[0287]

[0288] Among them, r ij is the semivariogram between the i-th position and the j-th position, λ i is the optimal coefficient of the i-th position and other positions, r io is the semivariogram from the i-th interpolation position to all positions, and φ is the Lagrange multiplier.

[0289] The fourteenth content contour generation sub-module is used to perform weighted summation on the function values of all positions according to all the optimal coefficients to obtain the function value of the interpolation position.

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

[0291] The sixteenth content contour generation sub-module is used to input all the heavy metal content indexes and all the corresponding geographical positions into the digital elevation model.

[0292] The seventeenth content contour generation sub-module is used to input the coordinates of all the interpolation positions and all the corresponding function values into the digital elevation model.

[0293] The eighteenth contour generation sub-module is used to linearly connect all equal heavy metal content indicators and function values to obtain the content contour.

[0294] Furthermore, the eleventh content contour generation sub-module is also equipped with the semi-variogram characterized by formula (5):

[0295]

[0296] where z i is the function value of the i-th geographical point, z j is the function value of the j-th geographical point, and E(·) is the expectation function.

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

[0298] Among them, the first electrokinetic remediation rectangle iteration sub-module is used to define four random solutions for each electrokinetic remediation rectangle, with one random solution at each corner of each electrokinetic remediation rectangle, and to constrain the relative positions of the four random solutions based on the current electrokinetic remediation rectangle; the second electrokinetic remediation rectangle iteration sub-module is used to define the optimization result of all random solutions as the minimum overlapping area of electrokinetic remediation rectangles; the third electrokinetic remediation rectangle iteration sub-module is used to initialize the positions of each random solution and update the current positions and current speeds of each random solution respectively; the fourth electrokinetic remediation rectangle iteration sub-module is used to delete electrokinetic remediation rectangles that completely exceed the remediation area during the iteration process; the fifth electrokinetic remediation rectangle iteration sub-module is used to obtain the individual optimal solutions and global optimal solutions of each random solution based on each update respectively; the sixth electrokinetic remediation rectangle iteration sub-module is used to determine whether the difference between each individual optimal solution and each individual optimal solution of the previous update is less than or equal to the first preset adaptation threshold respectively; the seventh electrokinetic remediation rectangle iteration sub-module is used to, if all are less, determine whether the difference between each global optimal solution and each global optimal solution of the previous update is less than or equal to the second preset adaptation threshold respectively; the eighth electrokinetic remediation rectangle iteration sub-module is used to, if all are less, determine that the optimal solutions of all electrokinetic remediation rectangles have been obtained; the ninth electrokinetic remediation rectangle iteration sub-module is used to obtain the number of rectangles and the rectangle positions corresponding to the optimal solutions.

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

[0300] Among them, the first repair circle iteration sub-module is used to obtain all rectangle positions and fuse them into an iteration area; the second repair circle iteration sub-module is used to define several random solutions in the iteration area, and each random solution corresponds to a repair circle; the third repair circle iteration sub-module is used to define the optimization result of all random solutions as the minimum overlapping area of all repair circles; the fourth repair circle iteration sub-module is used to initialize the positions of each random solution and update the current position and current speed of each random solution respectively; the fifth repair circle iteration sub-module is used to obtain the individual optimal solution and global optimal solution of each random solution respectively based on each update; the sixth repair circle iteration sub-module is used to determine whether the difference between each individual optimal solution and each individual optimal solution in the previous update is less than or equal to the first preset adaptation threshold; the seventh repair circle iteration sub-module is used to determine whether the difference between each global optimal solution and each global optimal solution in the previous update is less than or equal to the second preset adaptation threshold if all are less; the eighth repair circle iteration sub-module is used to determine that the optimal solutions of all repair circles have been obtained if all are less; the ninth repair circle iteration sub-module is used to obtain the number of circles and circle positions corresponding to the optimal solutions.

[0301] Furthermore, the repair system further includes a model visualization output module, a model visualization pattern adding module, a model visualization pattern selecting module, and a model visualization pattern dragging module that are electrically connected in sequence; the model visualization output module is electrically connected to the repair facility activation module 9.

[0302] Among them, the model visualization output module is used to output the digital elevation model, all electrokinetic repair rectangles, and all repair circles to an external visualization terminal; the model visualization pattern adding module is used to add a visualization pattern of a pair of electrodes in each electrokinetic repair rectangle and a visualization pattern of a plant at the center of each repair circle based on the external visualization terminal; the model visualization pattern selecting module is used to select a visualization pattern in response to an external touch operation and based on a single click touch of the touch operation; the model visualization pattern dragging module is used to drag all selected visualization patterns based on the sliding track 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 description parts of this embodiment, please refer to the above embodiment, and this embodiment will not be elaborated here.

[0304] In this embodiment, several heavy metal content indicators in the area of heavy metal contaminated soil are detected by an external concentration detector; based on all the heavy metal content indicators, a content contour line is generated by interpolation; the content contour line with a heavy metal content indicator greater than or equal to the preset indicator threshold is defined as a remediation area; a rectangular range of electrokinetic remediation is defined as an electrokinetic remediation rectangle; the number and position of the rectangles of the electrokinetic remediation rectangle are iterated within the remediation area until all the electrokinetic remediation rectangles completely cover all the remediation areas and the overlapping area of all the electrokinetic remediation rectangles reaches the minimum value; the circular surface of the hemispherical range of a plant is defined as a remediation circle; the number and position of the circles of the remediation circle are iterated within all the electrokinetic remediation rectangles until all the remediation circles completely cover all the electrokinetic remediation rectangles and the overlapping area of all the remediation circles reaches the minimum value; the final positions of all the electrokinetic remediation rectangles and the final positions of all the remediation circles are obtained, and a pair of electrodes are placed at the final position of each electrokinetic remediation rectangle and a plant is planted at the final position of each remediation circle; each pair of electrodes is connected respectively to perform the soil remediation operation. This embodiment adopts the combined remediation of electrokinetics and plants. The heavy metal ions are attracted to the range of the plant roots through electrokinetics, thus making up for the certainty of the long time period of a single remediation method. At the same time, based on computer intelligence, the arrangement positions of the equipment of the two remediation methods are iterated to achieve the maximum remediation effect with the least number of electrodes and the least number of plants, preventing the error that some soil blocks are redundantly remediated or some soil is not remediated due to manual subjective arrangement. Moreover, this embodiment does not need to completely collect all the concentration distributions of the soil to be remediated, and the data that have not been collected can be supplemented by the interpolation method of this embodiment, thus reducing the labor cost.

[0305] Figure 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As Figure 4 shown, 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 one of the above embodiments.

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

[0308] Among them, 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, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0309] Furthermore, Figure 5 is a schematic structural diagram of a storage medium according to an embodiment of the present application. Refer to Figure 5 , the storage medium 11 of the embodiment of the present application stores program instructions 111 that can implement all the above methods. Among them, the program instructions 111 can be stored in the above storage medium in the form of a software product, including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs, or terminal devices such as computers, servers, mobile phones, and tablets.

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

[0311] In addition, each functional unit in various embodiments of the present application may be integrated into one processing unit, may exist separately as individual physical units, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware or in the form of software functional units. The above is only the implementation mode of the present application, and does not limit the patent scope of the present application. Any equivalent structural or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present application.

Claims

1. A method for remediating heavy metal contaminated soil, the method being based on electrodynamic remediation and phytoremediation, wherein an electrodynamic remediation method guides and absorbs heavy metal ions within a rectangular range through a pair of electrodes, and a phytoremediation method absorbs heavy metal ions within a hemispherical range of the root system through plants, characterized in that: The repair method comprises: Step S1, detecting several heavy metal content indicators of the area where the heavy metal contaminated soil is located through an external concentration detection component; Step S2, generating content contour lines by interpolation method based on all heavy metal content indicators; Step S3, defining the content contour line where the heavy metal content index is greater than or equal to the preset index threshold as the restoration area; Step S4, defining a rectangular range of electric power repair as an electric power repair rectangle; Step S5, iterating the number and position of the electric power repair rectangles in the repair area until all the electric power repair rectangles completely cover all the repair areas and the overlapping areas of all the electric power repair rectangles reach a minimum value; Step S6, defining a circular surface within the hemispherical range of a plant as a repair circle; Step S7, iterating the number and position of the repair circles in all the electrodynamic repair rectangles until all the repair circles completely cover all the electrodynamic repair rectangles and the overlapping area of ​​all the repair circles reaches a minimum value; Step S8, obtaining the final positions of all the electrodynamic repair rectangles and the final positions of all the repair circles, placing a pair of electrodes at the final position of each electrodynamic repair rectangle, and planting a plant at the final position of each repair circle; Step S9, connecting each pair of electrodes separately to perform soil remediation operation.

2. The repair method according to claim 1, characterized in that: Step S2, generating content contour lines by interpolation method based on all heavy metal content indicators, including: Step S21, respectively obtaining the geographical location of each heavy metal content index based on the heavy metal contaminated soil; Step S22, obtain the geographic coordinates of all geographic points and define the Euclidean distance between the interpolation position and all geographic points according to formula (1): Among them, d i is the Euclidean distance between the interpolation position and the i-th geographic point, (x, y) is the coordinate of the interpolation position, (x i ,y i ) is the geographical coordinates of the ith geographical point; Step S23, calculating the weight value of the i-th geographic point based on the interpolated position according to formula (2): Among them, w i is the weight value of the i-th geographic point based on the interpolation position, p is an adjustment parameter, and its value is 2 or 3; Step S24, calculating the function value of the interpolation position according to formula (3): Among them, z(x,y) is the function value of the interpolation position, z i is the radial basis function of the ith geographic point, is the sum of the radial basis functions of all geographic points multiplied by the corresponding weight values, is the sum of all weight values, and The ratio of is the function value of the interpolation position; Step S25, obtaining the (x, y) value in the function value as the interpolation coordinates of the interpolation position; Step S26, obtaining a digital elevation model of the area where the heavy metal contaminated soil is located; Step S27, inputting all heavy metal content indicators and all corresponding geographical points into the digital elevation model; Step S28, inputting all interpolation coordinates and all corresponding function values ​​in 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 by interpolation method based on all heavy metal content indicators, including: Step S210, respectively obtaining the geographical location of each heavy metal content index based on the heavy metal contaminated soil; Step S220, calculating the Euclidean distance and semivariogram between every two geographic points based on all geographic points; Step S230, solving the fitting curves of all Euclidean distances and all semivariograms, so that the fitting curve can obtain the corresponding semivariogram according to any Euclidean distance calculation; Step S240, solving the semivariogram between all geographic points according to the fitting curve and defining the optimal coefficients of all semivariograms according to formula (4): Among them, r ij is the semivariogram between the i-th point and the j-th point, λ i is the optimal coefficient between the i-th point and other points, r io is the semivariogram from the i-th interpolation position to all points, and φ is the Lagrange multiplier; Step S250, performing weighted summation on the function values ​​of all points according to all optimal coefficients to obtain the function value of the interpolation position; Step S260, obtaining a digital elevation model of the area where the heavy metal contaminated soil is located; Step S270, inputting all heavy metal content indicators and all corresponding geographical points into the digital elevation model; Step S280, inputting the coordinates of all interpolation positions and all corresponding function values ​​in the digital elevation model; Step S290, linearly connect all equal heavy metal content indicators and function values ​​to obtain the content contour line.

4. The repair method according to claim 3, characterized in that: The semivariogram is represented by equation (5): Among them, z i is the function value of the ith geographic point, z j is the function value of the jth geographic point, and E(·) is the expected function.

5. The repair method according to claim 1, characterized in that: Step S5, iterating the number and position of the electric power repair rectangles in the repair area until all the electric power repair rectangles completely cover all the repair areas and the overlapping areas of all the electric power repair rectangles reach a minimum value, including: Step S51, defining four random solutions for each electrodynamic repair rectangle, each corner of the electrodynamic repair rectangle has 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 area of ​​overlap of the electric power repair rectangles reaching the minimum value; Step S53, initializing the position of each random solution, and updating the current position and current speed of each random solution respectively; Step S54, deleting the electric power repair rectangle that is completely beyond the repair area during the iteration process; Step S55, obtaining the individual optimal solution and the global optimal solution of each random solution based on each update; Step S56, respectively determining whether the difference between each individual optimal solution and each individual optimal solution updated last time is less than or equal to a first preset adaptation threshold, if both are less than, executing step S757; Step S57, respectively determining whether the difference between each global optimal solution and each global optimal solution updated last time is less than or equal to a second preset adaptation threshold, if both are less than, executing step S758; Step S58, determining that the optimal solution of all the electric power repair rectangles has been obtained; Step S59, obtaining the number and positions of rectangles corresponding to the optimal solution.

6. The repair method according to claim 1, characterized in that: Step S7, iterating the number and position of the repair circles in all the electrodynamic repair rectangles until all the repair circles completely cover all the electrodynamic repair rectangles and the overlapping area of ​​all the repair circles reaches a minimum value, including: Step S71, obtaining all rectangular positions and merging them into an iteration area; Step S72, defining a plurality of random solutions in the iteration area, each random solution corresponding to a repair circle; Step S73, defining the optimization result of all random solutions as the minimum overlap area of ​​all repair circles; Step S74, initializing the position of each random solution, and updating the current position and current speed of each random solution respectively; Step S75, obtaining the individual optimal solution and the global optimal solution of each random solution based on each update; Step S76, respectively determining whether the difference between each individual optimal solution and each individual optimal solution updated last time is less than or equal to a first preset adaptation threshold, if both are less than, executing step S77; Step S77, respectively determining whether the difference between each global optimal solution and each global optimal solution updated last time is less than or equal to a second preset adaptation threshold, if both are less than, executing step S78; Step S78, determining that the optimal solutions of all repair circles have been obtained; Step S79, obtaining the number of circles and the positions of the circles corresponding to the optimal solution.

7. The repair method according to claim 2, characterized in that: Step S9, respectively connecting each pair of electrodes to perform soil remediation operation, and then comprising: Step S10, outputting the digital elevation model, all the electric power repair rectangles, and all the repair circles to an external visualization terminal; Step S20, adding a visualization pattern of a pair of electrodes in each electrodynamic repair rectangle based on an external visualization terminal, and adding a visualization pattern of a plant at the center of each repair circle; Step S30, in response to an external touch operation, selecting a visual pattern based on a single click of the touch operation; Step S40: dragging all selected visualization patterns based on the sliding track of the touch operation.

8. A system for remediating heavy metal contaminated soil, the system being applied to the remediation method according to any one of claims 1 to 7, characterized in that: The repair system comprises: A heavy metal content index acquisition module is used to obtain several heavy metal content indexes of the area where the heavy metal contaminated soil is located through the external concentration detection component; Content contour generation module, used to generate content contours based on all heavy metal content indicators through interpolation method; A restoration area definition module, used to define the content contour line with heavy metal content index greater than or equal to a preset index threshold as a restoration area; An electric power repair rectangle definition module is used to define a rectangular range of an electric power repair as an electric power repair rectangle; An electric power repair rectangle iteration module, used for iterating the number and position of the electric power repair rectangles in the repair area until all the electric power repair rectangles completely cover all the repair areas and the overlapping area of ​​all the electric power repair rectangles reaches a minimum value; A repair circle definition module is used to define a circular surface within the hemispherical range of a plant as a repair circle; A repair circle iteration module, used for iterating the number and position of the repair circles in all the electrodynamic repair rectangles until all the repair circles completely cover all the electrodynamic repair rectangles and the overlapping area of ​​all the repair circles reaches a minimum value; A repair facility placement module is used to obtain the final positions of all electrodynamic repair rectangles and the final positions of all repair circles, and to place a pair of electrodes at the final position of each electrodynamic repair rectangle and to plant a plant at the final position of each repair circle; The remediation facility startup module is used to connect each pair of electrodes separately to perform soil remediation operations.

9. An electronic device, characterized in that: It comprises a processor and a memory coupled to the processor, wherein the memory stores program instructions executable by the processor; when the processor executes the program instructions stored in the memory, the repair method as described in any one of claims 1 to 7 is implemented.

10. A storage medium, characterized in that: The storage medium stores program instructions, and when the program instructions are executed by the processor, the repair method according to any one of claims 1 to 7 can be implemented.

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