A method for ecological risk assessment of heavy metal contaminated soil

Abstract

The invention discloses a method for assessing the ecological risk of heavy metal polluted soil, which belongs to the technical field of pollution assessment, and specifically comprises: dividing a polluted area to be tested into a plurality of grids, collecting indicators in the soil at each grid intersection, and calculating the pollution risk score of each grid intersection; performing interpolation data fitting in the grids by a radial basis function interpolation method, and generating a pollution risk score map contour map; selecting the contour line with the largest value in the contour line map, marking it as the initial contour line, and determining the starting connection point, sequentially searching for the end connection point with the longest distance from the starting connection point of the current contour line in the next level contour line, connecting all the connection lines, marking the obtained line segment set as a heavy metal pollution path, and taking corresponding heavy metal pollution control measures according to the distribution of soil pH value, soil ventilation and soil water content in the pollution path; the invention realizes clear identification of serious pollution areas and diffusion trends.

Description

Technical Field

[0001] The present invention relates to the technical field of pollution assessment, and in particular to a method for assessing ecological risks of heavy metal-contaminated soil. Background Art

[0002] With the acceleration of industrialization and the modernization of agricultural production, heavy metal pollution in soil has become a serious environmental problem facing the world. Heavy metal pollution not only destroys soil structure and affects soil function, but also may accumulate through the food chain, posing a threat to human health. Therefore, it is crucial to accurately assess and effectively control heavy metal pollution in soil.

[0003] Traditional soil heavy metal pollution assessment methods mostly use direct sampling analysis. Although this method can provide accurate pollution concentration data, it is difficult to quickly and comprehensively understand the ecological risk distribution of large-scale polluted areas. In addition, due to the heterogeneity of soil properties, relying solely on discrete point sampling data often cannot fully reveal the continuous distribution characteristics of pollution in space.

[0004] In recent years, geographic information system (GIS) technology and local statistical methods have been increasingly used in environmental science research. By establishing a two-dimensional map of the area to be tested and gridding it, soil samples can be collected at each grid intersection and their pH value, ventilation, water content and other indicators can be tested. These indicators can reflect the basic physical and chemical properties of the soil and are closely related to the degree of heavy metal pollution. However, how to convert these spatially dispersed data into a continuous pollution risk distribution map to explore the trajectory of heavy metal pollution remains a technical challenge. Summary of the invention

[0005] The purpose of the present invention is to provide a method for ecological risk assessment of heavy metal contaminated soil to solve the following technical problems:

[0006] Due to the heterogeneity of soil properties, relying solely on discrete point sampling data often cannot fully reveal the continuous distribution characteristics of pollution in space.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A method for assessing ecological risk of heavy metal contaminated soil comprises the following steps:

[0009] Establish a two-dimensional map of the polluted area to be tested, divide the polluted area to be tested into several grids, collect indicators in the soil at each grid intersection, the indicators include soil pH value, soil ventilation and soil moisture content, and calculate the pollution risk score of each grid intersection based on the superior and inferior solution distance method;

[0010] The pollution risk score interpolation data is fitted in the grid by radial basis function interpolation method, interpolation points are generated, the pollution risk score map after interpolation is obtained, and the pollution risk score contour map is generated based on the two-dimensional data map;

[0011] Select the contour line with the largest value in the contour map, mark it as the initial contour line, and select the next level contour line adjacent to the initial contour line, select several grid intersections from the initial contour line as pending starting points, and draw several straight lines from each pending starting point to the periphery, each of the straight lines is perpendicular to the tangent line of at least one point in the next level contour line, select the pending starting point and end point corresponding to the longest vertical line, mark them as the first connection point and the second connection point respectively, then take the second connection point as the starting point, draw a vertical line from the tangent line where the second connection point is located to the adjacent next level contour line, and similarly mark the connection point corresponding to the longest vertical line as the third connection point, and repeat the above process until it is connected to the contour line with the lowest value;

[0012] Connect all the connecting lines and mark the obtained line segment set as the heavy metal pollution path. According to the distribution of soil pH value, soil ventilation and soil water content in the pollution path, take corresponding heavy metal pollution control measures.

[0013] As a further solution of the present invention: the process of calculating the pollution risk score by the superior and inferior solution distance method is:

[0014] Soil pH, soil ventilation and soil water content are converted into extremely large indices and then converted into standardized indices through standardization. The grid intersection points and interpolation points are collectively referred to as coordinate points and sorted. The jth index of the coordinate point with sequence number i is marked as X. ij , then the standardized index corresponding to this index is Z ij ; Based on the standardized index Z ij Construct the matrix Z:

[0015] ;

[0016] Calculate the Euclidean distance D between each standardized indicator in the matrix and the maximum value of the indicator type i + , and to the minimum value Z of the indicator type - The Euclidean distance D i - ; Calculate the initial score of the coordinate point with serial number i , and the initial score is normalized, then the pollution risk score F of the coordinate point with serial number i is i for: .

[0017] As a further solution of the present invention: the conversion process of the extremely large index and the standardized index is:

[0018] For any indicator X ij , then the extremely large index corresponding to this index is X' ij =max(X 1j ,X 2j ,...,X nj )-X ij , where i∈n, then by the formula:

[0019] ;

[0020] Standardize each extremely large index to obtain the standardized index Z ij .

[0021] As a further solution of the present invention: the calculation process of the Euclidean distance is:

[0022] Mark the maximum value of any type of normalized indicator as Z j + , the minimum value is marked as Z j - , then the Euclidean distance D of any index i + and D i - The calculation formula is:

[0023] , .

[0024] As a further solution of the present invention: the process of data fitting by radial basis function interpolation method is:

[0025] Select several grid intersections as core nodes, and select linear radial basis function as kernel function. The formula is φ(r) = r, where r represents the distance between the interpolation target point and any core node. Each core node corresponds to a kernel function. The coordinates of the interpolation target point are marked as (x, y), and the coordinates of any core node are marked as (x k ,y k ), then the formula of the interpolation function is:

[0026] ;

[0027] Where f(xy) represents the predicted score of the interpolation target point, N represents the number of core nodes, and w represents the weight of each core node. Represents the Euclidean distance between the target interpolation point and any core node.

[0028] As a further solution of the present invention: when the number of the longest vertical lines is greater than one, each longest vertical line is connected to the next level contour line until it is connected to the contour line with the lowest value, and the single path composed of the longest connecting lines is used as the heavy metal pollution path.

[0029] As a further solution of the present invention: the isovalue distance between each contour line and the adjacent contour lines is the same. When there are multiple central contour lines in the contour map and the difference between the central contour lines is less than a preset threshold, the heavy metal pollution path is taken from each central contour line respectively.

[0030] As a further solution of the present invention: the soil ventilation volume is the total volume of air passing through a unit volume of soil under unit time and unit pressure.

[0031] Beneficial effects of the present invention:

[0032] (1) The present invention comprehensively considers indicators such as soil pH, ventilation and water content, which reflect the basic physical and chemical properties of soil and are closely related to the degree of heavy metal pollution. The pollution risk score is calculated by the superior-inferior solution distance method, which can objectively reflect the pollution risk level of each grid intersection. Then, the radial basis function interpolation method is used to fit spatial data to generate a high-precision pollution risk score map. This method effectively fits and predicts the distribution of spatial continuous data by selecting core nodes and appropriate basis functions, providing reliable data support for subsequent pollution control.

[0033] (2) The pollution risk score contour map generated based on the two-dimensional data map can intuitively show the distribution of heavy metal pollution in the soil. The density and shape of the contour lines can clearly identify the serious pollution areas and diffusion trends. The heavy metal pollution path was determined through systematic steps, and corresponding heavy metal pollution control measures were proposed based on the distribution of soil pH, ventilation and water content in the pollution path. This method not only takes into account the distribution range of pollution, but also the transmission pathway and influencing factors of pollution. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The present invention will be further described below in conjunction with the accompanying drawings.

[0035] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] See also Figure 1 As shown, the present invention is a method for assessing ecological risk of heavy metal contaminated soil, comprising the following steps:

[0038] 1. Create a 2D map and divide it into grids

[0039] Create a map: Use a geographic information system (GIS) or other related software to create a two-dimensional map of the contaminated area to be tested.

[0040] Grid division: Divide the entire polluted area into several grids. Each grid represents a small area, which is convenient for data collection and management.

[0041] 2. Data Collection

[0042] At each grid intersection, we need to collect the following indicators:

[0043] Soil pH: A measure of soil acidity or alkalinity.

[0044] Soil ventilation: the total volume of air passing through a unit volume of soil per unit time and unit pressure.

[0045] Soil moisture content: the amount of water in the soil.

[0046] 3. Calculate the contamination risk score

[0047] The pollution risk score of each grid intersection is calculated using the superior-inferior solution distance method. The specific steps include:

[0048] Convert to very large quantities: Convert soil pH, soil aeration and soil moisture content to very large quantities.

[0049] Normalization: These extremely large indicators are converted into standardized indicators through normalization.

[0050] Build Matrix: Build a matrix based on standardized indicators.

[0051] Calculate Euclidean distance: Calculate the Euclidean distance between each standardized indicator and the maximum value of the indicator type and the Euclidean distance to the minimum value.

[0052] Initial score: Calculate the initial score of each coordinate point and normalize it to obtain the final pollution risk score.

[0053] 4. Interpolation data fitting

[0054] The pollution risk score interpolation data is fitted in the grid by radial basis function interpolation method, interpolation points are generated, the pollution risk score map after interpolation is obtained, and the pollution risk score contour map is generated based on the two-dimensional data map.

[0055] 5. Determine the path of heavy metal pollution

[0056] Select contour lines: Select the contour line with the largest value from the contour line map, mark it as the initial contour line, and select the next level contour line adjacent to the initial contour line.

[0057] Select starting point: Select several grid intersection points from the initial contour lines as the pending starting points.

[0058] Draw perpendicular lines: Draw several straight lines from each pending starting point to the periphery. Each straight line is perpendicular to the tangent line of at least one point in the next level of contour lines. Select the pending starting point and end point corresponding to the longest perpendicular line, and mark them as the first connection point and the second connection point respectively.

[0059] Repeat the process: Starting from the second connection point, repeat the above process until you connect to the contour line with the lowest value.

[0060] Connecting line segments: Connect all the connecting lines and mark the obtained line segment set as the heavy metal pollution path.

[0061] 6. Take remedial measures

[0062] According to the distribution of soil pH, soil ventilation and soil water content in the pollution path, corresponding heavy metal pollution control measures should be taken. These measures may include soil remediation, vegetation restoration, chemical treatment, etc. The specific plan needs to be determined according to the actual situation and the nature of the pollutants.

[0063] The present invention is based on the use of contour lines to represent the distribution of heavy metal pollution. By selecting the longest connecting line segment between each contour line and the adjacent contour line, the longer the connecting line segment, the slower the heavy metal risk score decreases, and the longest connecting line segment also represents the protrusion of the contour line. Therefore, by finding the longest vertical line between adjacent contour lines, the direction in which the heavy metal concentration decays more slowly, that is, the pollution path of the heavy metal, can be determined. At the same time, this also corresponds to the distribution trend of soils that are easily diffused by heavy metals.

[0064] In a preferred embodiment of the present invention, the process of calculating the pollution risk score using the superior and inferior solution distance method is as follows:

[0065] Soil pH, soil ventilation and soil water content are converted into extremely large indices and then converted into standardized indices through standardization. The grid intersection points and interpolation points are collectively referred to as coordinate points and sorted. The jth index of the coordinate point with sequence number i is marked as X. ij , then the standardized index corresponding to this index is Z ij ; Based on the standardized index Z ij Construct the matrix Z:

[0066] ;

[0067] Calculate the Euclidean distance D between each standardized indicator in the matrix and the maximum value of the indicator type i + , and to the minimum value Z of the indicator type - The Euclidean distance D i - ; Calculate the initial score of the coordinate point with serial number i , and the initial score is normalized, then the pollution risk score F of the coordinate point with serial number i is i for: .

[0068] In a preferred case of this embodiment, the conversion process of the extremely large index and the standardized index is:

[0069] For any indicator X ij , then the extremely large index corresponding to this index is X' ij =max(X 1j ,X 2j ,...,X nj )-X ij , where i∈n, then by the formula:

[0070] ;

[0071] Standardize each extremely large index to obtain the standardized index Z ij .

[0072] In another preferred embodiment of the present invention, the calculation process of the Euclidean distance is as follows:

[0073] Mark the maximum value of any type of normalized indicator as Z j + , the minimum value is marked as Z j - , then the Euclidean distance D of any index i + and D i - The calculation formula is:

[0074] , .

[0075] The superiority and inferiority solution distance method (TOPSIS) is an effective multi-factor decision analysis method, which ranks the advantages and disadvantages of each evaluation object by calculating the distance between each evaluation object and the optimal solution and the worst solution. By converting indicators such as soil pH, soil ventilation and soil moisture content into extremely large indicators and performing standardization, the dimensional differences between different indicators can be effectively eliminated, so that each indicator can be compared on the same scale, thereby improving the accuracy and objectivity of the evaluation.

[0076] Applying TOPSIS to soil pollution risk scoring can comprehensively consider the impact of multiple indicators and objectively reflect the pollution risk level of each grid intersection. However, this method still obtains scores of discrete points, which need further processing to generate a continuous risk distribution map.

[0077] In another preferred embodiment of the present invention, the process of performing data fitting by radial basis function interpolation method is as follows:

[0078] Select several grid intersections as core nodes, and select linear radial basis function as kernel function. The formula is φ(r) = r, where r represents the distance between the interpolation target point and any core node. Each core node corresponds to a kernel function. The coordinates of the interpolation target point are marked as (x, y), and the coordinates of any core node are marked as (x k ,y k ), then the formula of the interpolation function is:

[0079] ;

[0080] Where f(xy) represents the predicted score of the interpolation target point, N represents the number of core nodes, and w represents the weight of each core node. Represents the Euclidean distance between the target interpolation point and any core node.

[0081] The radial basis function (RBF) interpolation method has been widely used in the field of spatial data interpolation due to its flexibility and strong adaptability. By selecting appropriate core nodes and basis functions, the RBF interpolation method can effectively fit and predict the distribution of spatial continuous data. In soil pollution risk assessment, the RBF interpolation method is used to perform spatial fitting on the discrete pollution risk scores calculated by TOPSIS, which can generate a high-precision pollution risk score map, and then draw a contour map based on it to intuitively show the pollution distribution.

[0082] In the radial basis function interpolation method, different types of kernel functions (such as linear, Gaussian, etc.) can be selected, and the number and position of core nodes can be adjusted, thereby increasing the flexibility of the model. This means that the model structure can be optimized according to the specific application scenario and data characteristics to obtain a better fitting effect. The process of this method can be automatically executed by a computer program, including the selection of core nodes, the calculation of kernel functions, and the final interpolation prediction.

[0083] In another preferred embodiment of the present invention, when the number of the longest vertical lines is greater than one, each longest vertical line is connected to the next level contour line until it is connected to the contour line with the lowest value, and the single path composed of the longest connecting lines is used as the heavy metal pollution path.

[0084] By determining the longest vertical line and establishing connecting lines until the lowest value contour is reached, these steps help to clearly identify and define the transmission path of heavy metal pollution. This not only helps to understand the movement trend of pollutants in the environment, but also provides a clear direction for subsequent pollution control work, so that more targeted control measures can be formulated.

[0085] When there are multiple longest vertical lines, the connecting lines of each vertical line are established separately to ensure the accuracy and completeness of the assessment, which helps to fully understand the pollution situation in the polluted area and avoid missing any possible pollution hotspots.

[0086] In another preferred embodiment of the present invention, the contour distance between each contour line and the adjacent contour lines is the same. When there are multiple central contour lines in the contour map and the difference between the central contour lines is less than a preset threshold, the heavy metal pollution path is taken from each central contour line respectively.

[0087] In the contour map, if there are multiple central contours and the difference between them is less than the preset threshold, the heavy metal pollution path is drawn from each central contour, which helps to accurately capture the local differences and complexity of pollution. This method improves the accuracy of the assessment, especially when the pollution is unevenly distributed or there are multiple pollution sources.

[0088] Keeping the isovalue intervals between contour lines the same as those between adjacent contour lines helps to clearly display changes in pollution levels on the map, making the visualization of pollution more standardized and easier to understand, thereby improving the efficiency of risk assessment.

[0089] In another preferred embodiment of the present invention, the soil ventilation volume is the total volume of air passing through a unit volume of soil under unit time and unit pressure.

[0090] The detailed definition of soil aeration emphasizes the importance of soil permeability for pollution assessment. Soil aeration is one of the key factors affecting the migration and transformation of heavy metals in soil. Accurately measuring and considering this indicator can help to more comprehensively assess the health of soil, thereby more effectively guiding soil management and remediation efforts.

[0091] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for assessing ecological risk of heavy metal contaminated soil, characterized in that: The following steps are involved: Establish a two-dimensional map of the polluted area to be tested, divide the polluted area to be tested into several grids, collect indicators in the soil at each grid intersection, the indicators include soil pH value, soil ventilation and soil moisture content, and calculate the pollution risk score of each grid intersection based on the superior and inferior solution distance method; The pollution risk score interpolation data is fitted in the grid by radial basis function interpolation method, interpolation points are generated, the pollution risk score map after interpolation is obtained, and the pollution risk score contour map is generated based on the two-dimensional data map; Select the contour line with the largest value in the contour map, mark it as the initial contour line, and select the next level contour line adjacent to the initial contour line, select several grid intersections from the initial contour line as pending starting points, and draw several straight lines from each pending starting point to the periphery, each of the straight lines is perpendicular to the tangent line of at least one point in the next level contour line, select the pending starting point and end point corresponding to the longest vertical line, mark them as the first connection point and the second connection point respectively, then take the second connection point as the starting point, draw a vertical line from the tangent line where the second connection point is located to the adjacent next level contour line, and similarly mark the connection point corresponding to the longest vertical line as the third connection point, and repeat the above process until it is connected to the contour line with the lowest value; Connect all the connecting lines and mark the obtained line segment set as the heavy metal pollution path. According to the distribution of soil pH value, soil ventilation and soil water content in the pollution path, take corresponding heavy metal pollution control measures; The process of calculating the pollution risk score using the superior and inferior solution distance method is as follows: Soil pH, soil ventilation and soil water content are converted into extremely large indices and then converted into standardized indices through standardization. The grid intersection points and interpolation points are collectively referred to as coordinate points and sorted. The jth index of the coordinate point with sequence number i is marked as X. ij , then the standardized index corresponding to this index is Z ij ; Based on the standardized index Z ij Construct the matrix Z: ； Calculate the Euclidean distance D between each standardized indicator in the matrix and the maximum value of the indicator type i + , and to the minimum value Z of the indicator type - The Euclidean distance D i - ; Calculate the initial score of the coordinate point numbered i , and the initial score is normalized, then the pollution risk score F of the coordinate point with serial number i is i for: ； The conversion process between extremely large indicators and standardized indicators is: For any indicator X ij , then the extremely large index corresponding to this index is X' ij =max(X 1j ,X 2j ,...,X nj )-X ij , where i∈n, then by the formula: ； Standardize each extremely large index to obtain the standardized index Z ij ; The calculation process of the Euclidean distance is: Mark the maximum value of any type of normalized indicator as Z j + , the minimum value is marked as Z j - , then the Euclidean distance D of any index i + and D i - The calculation formula is: ； 。 2. A method for ecological risk assessment of heavy metal contaminated soil according to claim 1, characterized in that: The process of data fitting by radial basis function interpolation is as follows: Select several grid intersections as core nodes, and select linear radial basis function as kernel function. The formula is φ(r) = r, where r represents the distance between the interpolation target point and any core node. Each core node corresponds to a kernel function. The coordinates of the interpolation target point are marked as (x, y), and the coordinates of any core node are marked as (x k ,y k ), then the formula of the interpolation function is: ； Where f(xy) represents the predicted score of the interpolation target point, N represents the number of core nodes, and w represents the weight of each core node. Represents the Euclidean distance between the target interpolation point and any core node.

3. A method for ecological risk assessment of heavy metal contaminated soil according to claim 1, characterized in that: When the number of the longest vertical lines is greater than one, each longest vertical line is connected to the next level contour line until it is connected to the contour line with the lowest value. The single path formed by the longest connecting lines is taken as the heavy metal pollution path.

4. The method for ecological risk assessment of heavy metal contaminated soil according to claim 1, characterized in that: The isovalue distance between each contour line and the adjacent contour lines is the same. When there are multiple central contour lines in the contour map and the difference between the central contour lines is less than the preset threshold, the heavy metal pollution path is drawn from each central contour line.

5. The method for ecological risk assessment of heavy metal contaminated soil according to claim 1, characterized in that: The soil ventilation rate is the total volume of air passing through a unit volume of soil under unit time and unit pressure.

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