Method for evaluating heavy metal pollution range of strip mine soil

Abstract

The invention aims to provide a strip mine soil heavy metal pollution range evaluation method for solving the problems of the existing soil heavy metal pollution range evaluation technology. The method comprises the steps of sampling point arrangement, sampling and detection, vertical depth heavy metal distribution simulation, heavy metal distribution estimation in different depth horizontal extension directions, and heavy metal distribution contour line making. According to the method provided by the invention, the heavy metal distribution conditions of different depths corresponding to different positions of the strip mine pollution source can be obtained according to the known pollutant content information of the soil sampling point, so that the heavy metal distribution isopleth of the soil pollution area in the vertical direction and the horizontal direction is made; and a land treatment mode or a reclamation mode of the mine can be guided through the isoline of heavy metal distribution.

Description

Technical Field

[0001] The invention belongs to the technical field of mine restoration, and in particular relates to a method for assessing the scope of heavy metal pollution in open-pit mine soil. Background Art

[0002] During the long-term mining process, the ecological environment will be affected to a certain extent. The water, soil and atmosphere inside and around the mining area are easily disturbed by pollutants in the ore. Studies have found that during the years of resource mining, the soil around the open-pit mining area has changed significantly, and the impact of heavy metals on the soil is particularly serious.

[0003] When reclaiming land in mining areas where heavy metal pollution has ended, a large amount of cost needs to be invested in soil treatment. Therefore, it is particularly important to accurately delineate the scope of soil contaminated by heavy metals around the mining area. This can not only indicate the area for land pollution treatment, but also avoid unnecessary cost investment. The scope of soil heavy metal pollution is reflected in both depth and breadth. It is not only related to the physical and chemical properties of the soil itself, but also to the external environment. However, the impact range of soil pollution in large open-pit mining areas is large. During the sampling process of contaminated soil, it is impossible to test and analyze all the contaminated soil. Only partial sampling can be done. This involves the problem of how to determine the soil pollution situation in the unsampled area and the concentration of pollutants at different depths in the depth direction (because it is impossible to test a sample of a vertical depth at different depths, and only a certain depth position can be taken for representative testing).

[0004] Existing technologies have also studied the assessment methods of soil heavy metal pollution, including:

[0005] The Chinese patent application with publication number CN118521897A, “A method, system, terminal and medium for monitoring and early warning of heavy metal pollution in farmland soil”, uses spectral technology to identify the heavy metal content in the surface soil, but cannot detect the heavy metal situation in the deep soil; the Chinese patent application with publication number CN118522382A, “A method for predicting the effective chromium content in soil”, mainly carried out the prediction of chromium content concentration, but did not study the distribution of chromium, especially at different depths and distances from the pollution source. Chinese patent CN202310612967.4, “A method and system for determining the scope of single heavy metal pollution in soil of contaminated sites”, mainly studies the pollution scope of single heavy metal in the soil layer 0.5m deep, and cannot reflect the horizontal influence law of heavy metals. Moreover, in the literature on the above-mentioned sources of soil heavy metal pollution, there are few studies that reflect the direction of pollutant migration. Summary of the invention

[0006] The purpose of the present invention is to provide a method for assessing the scope of heavy metal pollution in open-pit mine soils in order to solve the problems existing in existing technologies for assessing the scope of heavy metal pollution in soils. The method provided by the present invention can obtain the distribution of heavy metals at different depths corresponding to different locations from the pollution source of the open-pit mine based on the known pollutant content information of the soil sampling points, thereby making heavy metal distribution contour lines of the soil pollution area in both vertical and horizontal directions, and can guide the land management method or reclamation model of the mine through the contour lines of heavy metal distribution.

[0007] The present invention proposes a method for assessing the scope of heavy metal pollution in open-pit mine soil, comprising the following steps:

[0008] Step 1: Sampling point layout, sampling and testing

[0009] Sampling points shall be arranged according to the spatial and geographical scope of the soil to be evaluated, as well as the sampling cost and feasibility, and the soil shall be sampled according to the arranged sampling points, and then the physical and chemical properties and heavy metal content of the collected soil samples shall be tested; the distance between adjacent sampling points shall not exceed 200 meters;

[0010] Specifically include:

[0011] Step 1.1: Sampling point layout

[0012] The layout of sampling points needs to consider issues such as spatial scope, sampling cost and sampling feasibility. According to the national "Technical Specifications for Soil Environmental Monitoring" HJ / T166-2004, the soil is gridded and the sites at different depths of the grid center are taken as soil sampling points.

[0013] Step 1.2: Collect soil samples on site

[0014] Use GPS to locate the sampling points arranged above, use professional soil sampling equipment to collect samples in layers, and put them into sample bags. Each sample is divided into two bags, and the following are marked and recorded: time, location, number, depth, longitude and latitude, etc.

[0015] Step 1.3: Sample analysis

[0016] The physical and chemical properties and heavy metal content of soil samples must comply with national standards for soil pH determination, soil organic matter determination, soil moisture content determination, cation exchange capacity determination, and atomic absorption method for heavy metal content determination;

[0017] Step 1.3.1: Testing of soil physical and chemical properties

[0018] Including pH value, organic matter, water content, cation exchange capacity, etc.;

[0019] Step 1.3.2: Detection of heavy metal content in soil

[0020] Before determining the heavy metal content in soil samples, the samples must first be subjected to microwave digestion to digest the detected elements in the soil samples into ionic states in order to better determine the data;

[0021] Step 2: Vertical depth heavy metal distribution simulation

[0022] Based on the detection data of the sampling points in the vertical direction, the heavy metal content at different depths at a certain time point in the vertical direction is simulated to obtain the heavy metal distribution map at different depths in the entire area;

[0023] Step 3: Estimation of heavy metal distribution in horizontal extension directions at different depths

[0024] The soil information of the sampling point to be estimated (hereinafter referred to as the estimated point) is estimated based on the soil information of the known points at a certain distance around it (i.e. the soil sampling points where samples have been taken). The soil information includes multiple soil properties. The soil information of the estimated point is proportional to the soil information of the known points, inversely proportional to the 1 to 3 power of the distance between the estimated point and each known point, and has an outward gradient decreasing trend with the distance from the pollution source.

[0025] The specific steps include:

[0026] Step 3.1: Determine the scope of impact

[0027] Assuming that the influencing factors are isotropic, the influence range in two-dimensional space is a circle; that is, a circle with the point to be estimated as the center and the range (the maximum distance between samples with correlation) as the radius R;

[0028] The radius of variation is generally obtained by fitting the semivariogram function (calculated data from some discrete points) based on the semivariogram experimental function of geostatistics. It can also be obtained by empirically determining the value according to different ore body types and sampling intervals.

[0029] Step 3.2: Calculate the distance between each known point and the center of the point to be estimated, and find the known points within the influence range;

[0030] Step 3.3: Calculate the attribute value of the point to be estimated;

[0031] Consider a certain measurement area, at several known points x i (i=1,2,…) The value of a certain property of a set of soil measured is z(x i ), assuming that the soil sample information of the estimated point x0 is unknown, and the value of one of its attributes is z(x0); then the value of one of the attributes z(x0) of all known points within the influence range i ) Treat the average value of an unknown attribute of the estimation point by linear summation To make a valuation,

[0032]

[0033] Where: i is a known point x i The weight of

[0034] For the weight λ i The determination principle is: within a certain area, the weight of the known point to the estimated point decreases as the distance from the measured point increases; i It can be obtained by the following formula:

[0035]

[0036] Where: d(x i ,x0) is a known point x i The distance from the estimated point x0; the selection of exponent p controls the weight λ i The speed of the trend toward 0 is theoretically related to the physical and chemical properties of the soil, water movement, etc., and p is usually between 1 and 3;

[0037] Step 3.4: Heavy metal geological isotropic zone division

[0038] Since the distribution of heavy metal concentrations in the mining area soil has obvious directionality at the same level, that is, the farther away from the pollution source, the lower the concentration, while formula (1) is only related to the distance and cannot reflect the characteristic of directionality, it is easy to cause the evaluation results to deviate from the true value or even be wrong, so directional constraints are needed; according to the heavy metal concentration set Z(x) of all collected samples and the closest distance set D(x) between the sample collection point and the pollution source, a heavy metal distance gradient concentration function Z[D(x)] that varies with distance can be fitted; however, the terrain of mining areas is generally complex, and the physical and chemical properties of the soil are greatly affected by rainwater and groundwater, which causes the distribution of heavy metals in the soil to have directionality; this means that the distance gradient concentration function Z[D(x)] has different characteristics in different directions, so the distance gradient concentration function considering the direction can be expressed as Due to the limited data collection of mines and the complexity of the on-site geographical environment, in a certain direction There is little or no sample data on , so a broad area and linear interpolation rule need to be given;

[0039] According to the geographical environment of the mining area, combined with the above-mentioned heavy metal distribution characteristics and simulation results, the soil around the mining area is divided into multiple fan-shaped areas, and the midline of each area is the orientation of this area; therefore, in the orientation Directional distance gradient concentration function Use the known points in the geological isotropic region where the direction is located for nonlinear fitting; in a small open-pit mine, the distance gradient concentration function corresponding to different directions of each partition Can be approximately the same;

[0040] Step 3.5: Linear interpolation gradient transition distance gradient concentration function

[0041] The concentration of heavy metals in the soil of the mining area is a regional random variable and a function of time, which means that the content of heavy metals at different points has temporal and spatial correlation. However, for large open-pit mines, due to the large mining area, the geological isotropic area division range made in step 3.4 is also relatively large. It is unreasonable to use the same distance gradient concentration function in such a large range, and it is easy to cause data mutations in two adjacent areas, which does not conform to the temporal and spatial correlation of heavy metal content. Therefore, for two adjacent geological isotropic areas, with their respective midline orientations as constraints, linear interpolation and gradual transition are used, with the east orientation as 0°, and counterclockwise rotation, to obtain the distance gradient concentration function of different orientations within the constraint range:

[0042]

[0043] Where: direction and direction Indicates the median orientation of two adjacent partitions; Indicates location and direction Somewhere in between; Indicates direction The distance gradient concentration function;

[0044] Step 3.7: The heavy metal concentration z(x0) of a certain estimated point x0 with a distance D(x0) from the pollution source consists of two parts, one is the direction-constrained distance gradient concentration function, and the other is a linear function based on the inverse distance method; the details are as follows:

[0045]

[0046] Where: D(x i ) represents a known point x i The distance from the pollution source; In represents the direction of the point x0 to be estimated, that is, the "certain direction" in formula 3;

[0047] Step 4: Create contour lines of heavy metal distribution

[0048] Based on step 3 and formula (4), the distribution of heavy metals at different depths corresponding to different locations from the open-pit mine pollution source can be obtained, and then the heavy metal distribution contour lines in the soil pollution area, including vertical and horizontal directions, can be made; the contour lines based on heavy metal distribution can be used to guide mines to adopt different land management methods or reclamation models in different areas.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The method of the present invention can obtain the distribution of heavy metals at different depths corresponding to different locations from the open-pit mine pollution source based on the pollutant content information of the known soil sampling points, thereby making heavy metal distribution contour lines in the soil pollution area, including vertical and horizontal directions. Based on the contour lines of heavy metal distribution, it is possible to guide mines to adopt different land management methods or reclamation models in different areas, improve the efficiency of mine ecological restoration and reduce the cost of mine reclamation. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 Schematic diagram of the inverse distance weighted method for estimating the physical and chemical properties of soil at the estimated point;

[0052] The black circles in the figure represent known points; the circle z(x0) in the center represents the point to be estimated; the dotted line indicates the effective range involved in the valuation; and the open-pit mining area represents the pollution source.

[0053] Figure 2 This is a schematic diagram of the geological isotropic area division around the pollution source in the mining area;

[0054] Figure 3 Schematic diagram of linear interpolation of concentration gradient at different azimuth distances in contaminated soil area. DETAILED DESCRIPTION

[0055] In order to explain the problem in a vivid and intuitive manner, and in particular to quantitatively evaluate the effectiveness of the method of the present invention, this example uses actual mine data information to illustrate the process operation (the geological coordinate information has been encrypted).

[0056] A method for assessing the scope of heavy metal pollution in open-pit mine soil comprises the following steps:

[0057] Step 1: Sampling point layout. The layout of sampling points needs to consider issues such as spatial scope, sampling cost and sampling feasibility. According to the national "Technical Specifications for Soil Environmental Monitoring" HJ / T166-2004, ArcGIS 10.8 combined with 91 Satellite Map Assistant is used to divide the soil into 50×50 grids, and the center point of the grid is taken as the soil sampling point. The distance between adjacent sampling points does not exceed 200 meters.

[0058] Step 2: Collect soil samples on site. Affected by the on-site rock and soil and the constraints of the engineering environment, 5 sampling points were set up around the open pit, 5 sampling points around the spoil dump, 5 sampling points around the tailings pond, and 4 sampling points in the area affected by the three together; at the same time, in order to study the migration characteristics in the horizontal and vertical directions, the data collected this time refer to the sampling standards to collect the surface (0-25cm), middle (25-60cm), and deep (60-100cm) soil.

[0059] Step 3: Sample pretreatment. After the samples are collected, first spread the soil samples on paper trays indoors, air-dry them under natural conditions, and crush and turn them over in time to remove gravel, sand and plant roots in the soil; then use a small hammer, wooden stick or other tools to break up the blocky soil or use a white porcelain mortar to grind it, and pick out impurities again; then use nylon sieves with different pore sizes (10 mesh, 20 mesh, 60 mesh and 100 mesh) to sieve the soil samples, of which 10 mesh, 20 mesh and 60 mesh soil samples are used to determine soil pH, moisture content, organic matter and cation exchange capacity, and 100 mesh soil samples are used to determine the content of heavy metal elements in the soil; finally, bag the samples and mark the mesh number for testing.

[0060] Step 4: Sample testing. The physical and chemical properties and heavy metal content of soil samples must comply with national standards such as soil pH determination, soil organic matter determination, soil moisture determination, cation exchange capacity determination, and atomic absorption spectrometry for heavy metal content. The technical standard reference document numbers are (HJ 962-2018) (GB9834-88) (GB 7172-87) (HJ889-2017) (JJG694-2009). The main experimental testing equipment and reagents used in the analysis and testing are shown in Tables 1 and 2.

[0061] Table 1 Experimental equipment and instruments

[0062]

[0063] Table 2 Experimental reagents

[0064]

[0065] Step 4.1: Soil physical and chemical properties testing. pH was determined using the potentiometric method; organic matter was determined using the triangular flask-automatic zeroing burette-electric sand bath-o-phenanthroline indicator-ferrous sulfate standard solution method; and moisture content was determined using the halogen moisture meter HX204.

[0066] Step 4.2: Detection of heavy metal content in soil. The samples were digested by microwave using a fully automatic microwave digester (ADB-50), and the content of Cu, Zn, Cr and Ni in the soil was detected using an atomic absorption spectrometer-flame atomic absorption spectrometry. Table 3 shows the comprehensive statistics of heavy metals at three vertical depths at all sampling points.

[0067] Table 3 Statistics of characteristic values ​​of heavy metal elements in soil around open pit

[0068]

[0069] Step 5: Vertical depth heavy metal distribution simulation: Based on the limited test data of the sampling points in the vertical direction, Comsol Multiphyscis simulation software was used to simulate the heavy metal content at different depths at a certain time point in the vertical direction to obtain the heavy metal distribution map of all sampling points at different depths.

[0070] Step 6: Estimation of heavy metal distribution in the horizontal direction at different depths (heavy metal distribution in the horizontal direction at different depths, such as 0.5m or 0.8m vertically from the surface)

[0071] The soil information of the sampling point to be estimated (hereinafter referred to as the estimated point) is estimated based on the soil information of the known points at a certain distance around it (i.e. the soil sampling points where samples have been taken). The soil information includes multiple soil properties. The soil information of the estimated point is proportional to the soil information of the known points, inversely proportional to the 1 to 3 power of the distance between the estimated point and each known point, and has an outward gradient decreasing trend with the distance from the pollution source.

[0072] Step 6.1: Assume that the influencing factors are isotropic and the influence range in two-dimensional space is a circle; that is, a circle with the point to be estimated as the center and the range (the maximum distance with correlation between samples) as the radius R; the range radius is generally obtained by fitting the semi-variogram experimental function of geological statistics (which is some discrete point calculation data) into a semi-variogram function; it can also be obtained through experience based on different ore body types and sampling intervals.

[0073] In this example, the plane search radius is determined to be 200m. The coordinates of the point to be estimated are x0 (9553.875, 6024.566), and there are 5 known sample points within the search radius, with coordinates of x1 (9459.361, 6087.976), x2 (9441.44, 5925.716), x3 (9559.557, 5928.931), x4 (9692.339, 5975.248), and x5 (9604.918, 6105.589). In view of the confidentiality of geographic information, the above coordinates have been converted.

[0074] Step 6.2: Calculate the distance between each soil sample point with known data and the center of the estimated sample point, and find the known points within the influence range. According to the distance calculation method, the distance d(x1, x0) between the known point x1 and the unknown point x0 is 113.814m. Similarly, the distances between other known points and unknown points are: 149.71m, 95.804m, 146.985m, 95.761m.

[0075] Step 6.3: Use formulas (1) and (2) to calculate the attribute value of the estimated sample point.

[0076] Consider a certain measurement area, at several known points x i (i=1,2,…) The value of a certain property of a set of soil measured is z(x i ), assuming that the soil sample information of the estimated point x0 is unknown, and the value of one of its attributes is z(x0); then a certain attribute z(xi) of all known points within the influence range is linearly summed to obtain the average value of a certain unknown attribute of the estimated point To make a valuation,

[0077]

[0078] Where: i is a known point x i The weight of

[0079] For the weight λ i The determination principle is: within a certain area, the weight of the known point to the estimated point decreases as the distance from the measured point increases; i It can be obtained by the following formula:

[0080]

[0081] Where: d(x i ,x0) is the distance between the known point xi and the estimated point x0; the selection of exponent p controls the weight λ i The speed of the trend toward 0 is theoretically related to the physical and chemical properties of the soil, water movement, etc., and p is usually between 1 and 3;

[0082] Through comprehensive analysis of the data, it is more appropriate to use the index P of 2; according to formula (2), the weights λ of the five known points involved in the estimation of the unknown point x0 are 0.1999, 0.1156, 0.2822, 0.1199, and 0.2824 respectively. Taking the concentration of heavy metal Ni in the surface layer as an example, the concentration data of the five known sampling points are: 64.3641 mg / kg, 47.5481 mg / kg, 45.2626 mg / kg, 41.2000 mg / kg, and 49.1274 mg / kg. According to formula (1), the preliminary estimate of the unknown point x0 is 49.9504 mg / kg. Figure 1 shown.

[0083] Step 6.4: Heavy metal geological isotropic zone division

[0084] Since the distribution of heavy metal concentrations in the mining area soil has obvious directionality at the same level, that is, the farther away from the pollution source, the lower the concentration, while formula (1) is only related to the distance and cannot reflect the characteristic of directionality, it is easy to cause the evaluation results to deviate from the true value or even be wrong, so directional constraints are needed; according to the heavy metal concentration set Z(x) of all collected samples and the closest distance set D(x) between the sample collection point and the pollution source, a heavy metal distance gradient concentration function Z[D(x)] that varies with distance can be fitted; however, the terrain of mining areas is generally complex, and the physical and chemical properties of the soil are greatly affected by rainwater and groundwater, which causes the distribution of heavy metals in the soil to have directionality; this means that the distance gradient concentration function Z[D(x)] has different characteristics in different directions, so the distance gradient concentration function considering the direction can be expressed as Due to the limited data collection of mines and the complexity of the on-site geographical environment, in a certain direction There is little or no sample data on , so a broad area and linear interpolation rule need to be given;

[0085] According to the geographical environment of the mining area, combined with the above-mentioned heavy metal distribution characteristics and simulation results, the soil around the mining area is divided into multiple fan-shaped areas, and the midline of each area is the orientation of this area; therefore, in the orientation Directional distance gradient concentration function Use the known points in the geological isotropic region where the direction is located for nonlinear fitting; in a small open-pit mine, the distance gradient concentration function corresponding to different directions of each partition Can be approximately the same;

[0086] Step 6.5: Linear interpolation gradient transition distance gradient concentration function

[0087] The concentration of heavy metals in the soil of the mining area is a regional random variable and a function of time, which means that the content of heavy metals at different points has temporal and spatial correlation. However, for large open-pit mines, due to the large mining area, the geological isotropic area division range made in step 3.4 is also relatively large. It is unreasonable to use the same distance gradient concentration function in such a large range, and it is easy to cause data mutations in two adjacent areas, which does not conform to the temporal and spatial correlation of heavy metal content. Therefore, for two adjacent geological isotropic areas, with their respective midline orientations as constraints, linear interpolation and gradual transition are used, with the east orientation as 0°, and counterclockwise rotation, to obtain the distance gradient concentration function of different orientations within the constraint range:

[0088]

[0089] Where: direction and direction Indicates the median orientation of two adjacent partitions; Indicates location and direction Somewhere in between; Indicates direction The distance gradient concentration function;

[0090] According to the geographical environment of the mining area, combined with the heavy metal distribution characteristics and simulation results in steps 4 and 5, the soil around the mining area is divided into multiple fan-shaped areas. The unknown point x0 in the case study is located at the 292.5° azimuth between the midline azimuths of 225.3° and 335.6°. The concentration gradient functions of these two midline azimuths are based on the known distances of the sample points from the pollution source and the corresponding heavy metal concentration values ​​in the partitions where these two azimuths are located. Data fitting is performed in the Excel table, and the results are:

[0091] Z[D(x),225.3°]=-9.272ln[D(x)]+93.326

[0092] Z[D(x),335.6°]=-6.135ln[D(x)]+71.314

[0093] According to formula (3), linear interpolation is used to obtain the distance gradient concentration function of the unknown point x0 (2292.5°):

[0094] Z[D(x),292.5°]=-7.361ln[D(x)]+79.915

[0095] Step 6.5: The heavy metal concentration z(x0) of a certain estimated point x0 with a distance D(x0) from the pollution source consists of two parts, one is the direction-constrained distance gradient concentration function, and the other is a linear function based on the inverse distance method; the details are as follows:

[0096]

[0097] Where: D(x i ) represents a known point x i The distance from the pollution source; In represents the direction of the point x0 to be estimated, that is, the "certain direction" in formula 3;

[0098] The distance D(x0) between the unknown sample point x0 and the pollution source is 116.5m, and the distances between the known sample points involved in the estimation and the pollution source are 26m, 170m, 213m, 238m, and 82m, respectively. Combined with formula (4), the heavy metal concentration Z(x0) of the unknown sample point x0 is 44.892mg / kg.

[0099] Step 7: Based on the above process, the concentration value of a certain type of heavy metal at any unknown point can be obtained. After the heavy metal concentration values ​​of all unknown points are obtained, the heavy metal concentration contour lines can be drawn according to the concentration value distribution characteristics, thereby guiding the mine soil management and reclamation work.

Claims

1. A method for assessing the scope of heavy metal pollution in open-pit mine soil, characterized in that: The following steps are involved: Step 1: Sampling point layout, sampling and testing Sampling points shall be arranged according to the spatial and geographical scope of the soil to be evaluated, as well as the sampling cost and feasibility, and the soil shall be sampled according to the arranged sampling points, and then the physical and chemical properties and heavy metal content of the collected soil samples shall be tested; the distance between adjacent sampling points shall not exceed 200 meters; Step 2: Vertical depth heavy metal distribution simulation Based on the detection data of the sampling points in the vertical direction, the heavy metal content at different depths at a certain time point in the vertical direction is simulated to obtain the heavy metal distribution map at different depths in the entire area; Step 3: Estimation of heavy metal distribution in horizontal extension directions at different depths The soil information of the sampling point to be estimated is estimated based on the soil information of the known points at a certain distance around it. The soil information includes multiple soil properties. The soil information of the estimated point is proportional to the soil information of the known points, inversely proportional to the 1 to 3 power of the distance between the estimated point and each known point, and has an outward gradient decreasing trend with the distance from the pollution source. The specific steps include: Step 3.1: Determine the scope of impact Assuming that the influencing factors are isotropic, the influence range in two-dimensional space is a circle, that is, a circle with the point to be estimated as the center and the range as the radius R; Step 3.2: Calculate the distance between each known point and the center of the point to be estimated, and find the known points within the influence range; Step 3.3: Calculate the attribute value of the point to be estimated; Consider a certain measurement area, at several known points x i (i=1,2,…) The value of a certain property of a set of soil measured is z(x i ), assuming that the soil sample information of the estimated point x0 is unknown, and the value of one of its attributes is z(x0); then the value of one of the attributes z(x0) of all known points within the influence range i ) Treat the average value of an unknown attribute of the estimation point by linear summation To make a valuation, Where: i is a known point x i The weight of For the weight λ i The determination principle is: within a certain area, the weight of the known point to the estimated point decreases as the distance from the measured point increases; i It can be obtained by the following formula: Where: d(x i ,x0) is a known point x i The distance from the estimated point x0; the selection of exponent p controls the weight λ i The speed of the trend toward 0 is theoretically related to the physical and chemical properties of the soil, water movement, etc., and p is usually between 1 and 3; Step 3.4: Heavy metal geological isotropic zone division Since the distribution of heavy metal concentrations in the mining area soil has obvious directionality at the same level, and since the physical and chemical properties of the soil are largely affected by rainwater and groundwater, the distribution of heavy metals in the soil has directionality; this means that the distance gradient concentration function Z[D(x)] has different characteristics in different directions. Therefore, the distance gradient concentration function considering the direction can be expressed as According to the geographical environment of the mining area, combined with the above-mentioned heavy metal distribution characteristics and simulation results, the soil around the mining area is divided into multiple fan-shaped areas, and the midline of each area is the orientation of this area; therefore, in the orientation Directional distance gradient concentration function Use the known points in the geological isotropic region where the direction is located for nonlinear fitting; in a small open-pit mine, the distance gradient concentration function corresponding to different directions of each partition Can be approximately the same; Step 3.5: Linear interpolation gradient transition distance gradient concentration function For large open-pit mines, due to the large mining area, the geological isotropic area division range made in step 3.4 is also relatively large. It is unreasonable to use the same distance gradient concentration function in such a large range. Therefore, for two adjacent geological isotropic areas, the respective midline orientations are constrained, and linear interpolation and gradual transition are adopted. The due east orientation is taken as the orientation 0°, and the distance gradient concentration functions at different orientations within the constraint range are obtained by rotating counterclockwise: Where: direction and direction Indicates the median orientation of two adjacent partitions; Indicates location and direction Somewhere in between; Indicates direction The distance gradient concentration function; Step 3.6: The heavy metal concentration z(x0) of a certain estimated point x0 with a distance D(x0) from the pollution source consists of two parts, one is the direction-constrained distance gradient concentration function, and the other is a linear function based on the inverse distance method; the details are as follows: Where: D(x i ) represents a known point x i Distance from pollution source; Step 4: Create contour lines of heavy metal distribution Based on step 3 and formula (4), the distribution of heavy metals at different depths corresponding to different locations from the open-pit mine pollution source can be obtained, and then the heavy metal distribution contour lines in the soil pollution area including vertical and horizontal directions can be drawn.

2. The method for assessing the scope of heavy metal pollution in open-pit mine soil according to claim 1, characterized in that: The step 1 specifically includes: Step 1.1: Sampling point layout The layout of sampling points needs to consider issues such as spatial scope, sampling cost and sampling feasibility. According to the national "Technical Specifications for Soil Environmental Monitoring" HJ / T166-2004, the soil is gridded and the sites at different depths of the grid center are taken as soil sampling points. Step 1.2: Collect soil samples on site Use GPS to locate the sampling points arranged above, use professional soil sampling equipment to collect samples in layers, and put them into sample bags. Each sample is divided into two bags, and the following are marked and recorded: time, location, number, depth, longitude and latitude, etc. Step 1.3: Sample analysis The physical and chemical properties and heavy metal content testing of soil samples must comply with national standards such as soil pH determination, soil organic matter determination, soil moisture content determination, cation exchange capacity determination and atomic absorption method detection of heavy metal content.

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