Comprehensive evaluation method for heavy metal pollution of soil environment

Abstract

The invention relates to the technical field of heavy metal pollution detection, identification and evaluation, in particular to a soil environment heavy metal pollution comprehensive evaluation method, which comprises the following steps: constructing an evaluation index system of the pollution degree of heavy metals in soil, and respectively evaluating and judging the pollution degree, the influence range and the ecological risk by the index system. The method comprises the following steps: establishing a metal pollution numerical simulation model, calculating an interference factor, and analyzing a result value, 0 represents that interference of heavy metal pollution in the regional soil has a positive effect on the interior of the regional soil, and in the later development process, improvement agents can be adopted to change the existence form of heavy metal in the soil for treatment; if alpha < lt >; if the interference coefficient of the regional soil is smaller than 0, the negative effect of heavy metal pollution in the regional soil on the regional soil is achieved, the smaller the interference coefficient of the regional soil is, the more obvious the negative effect is, and the mode of removing heavy metal from the soil needs to be considered in the later development process for treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of heavy metal pollution detection, identification and evaluation, and in particular to a comprehensive evaluation method for heavy metal pollution in a soil environment. Background Art

[0002] Heavy metal pollution refers to environmental pollution caused by heavy metals or their compounds, mainly caused by human factors such as mining, waste gas emissions, sewage irrigation and the use of products with excessive heavy metals. The degree of harm depends on the concentration and chemical form of heavy metals in the environment, food and organisms. From the perspective of environmental pollution, heavy metals refer to heavy metals with significant biological toxicity such as mercury, cadmium, lead and "metalloids" such as arsenic. The five most toxic to the human body are lead, mercury, arsenic, cadmium and chromium. These heavy metals are difficult to decompose. After entering the human body, their toxicity is amplified and they combine with other toxins to form more toxic organic matter.

[0003] By searching the existing Chinese patent number 201210124951.0 for the method of generating a comprehensive evaluation map of heavy metal pollution in reclaimed land soil, it can be seen that the existing detection and identification of heavy metal pollution in the soil environment, the evaluation method is mainly based on a single indicator or a few indicators, which cannot fully reflect the complexity and comprehensiveness of heavy metal pollution. The lack of a comprehensive evaluation method limits the accurate assessment of the overall status of heavy metal pollution, and it is impossible to give a method for treating the polluted soil based on the results. Summary of the invention

[0004] The purpose of the present invention is to provide a comprehensive evaluation method for heavy metal pollution in soil environment in view of the shortcomings of the prior art, so as to solve the problems raised in the background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for comprehensive evaluation of heavy metal pollution in soil environment, characterized in that it comprises the following steps:

[0006] Step 1: Construct an evaluation index system for the degree of heavy metal pollution in soil. The index system evaluates and determines the degree of pollution, scope of impact and ecological risk respectively. Then, the soil composition in the required collection area is determined, and random sampling is carried out in different regions.

[0007] Step 2: Collecting heavy metal pollution data in the soil environment according to the indicator system constructed in step 1, wherein the heavy metal pollution data includes sampling data and monitoring data, and preprocessing the collected data;

[0008] Step 3: According to the comprehensive risk assessment of heavy metal pollution, determine the types of heavy metals to be detected in the study area and number them. If there are n types of heavy metals to be detected, the metals are numbered 1, 2, ... n; measure the concentrations of n heavy metals in each sample one by one, and calculate the average concentration value of each heavy metal respectively;

[0009] Step 4: Determine the weight of each indicator according to its importance and contribution, and establish a weight set A = {a1, a2..., aX} according to the pollution degree of the pollution factor, where a1, a2..., aX represent the type of pollution, pollution range, pollution category and the weight of other pollution factors respectively;

[0010] Step 5: Establish a numerical simulation model for metal pollution;

[0011] Step 6: Calculate the interference factor;

[0012] Step 7: When calculating according to the maximum membership principle of fuzzy mathematics, if there are two or more identical or approximately equal maximum values ​​in the calculation results, the environmental quality evaluation level shall be determined according to the second largest level principle.

[0013] Preferably, the determination of the membership of each pollution factor to the evaluation level to obtain the corresponding relationship matrix B includes calculating the membership according to the measured value of the pollution factor and the classification standard value. Assuming that the measured value of the pollution factor a1, a2..., aX is x, then the pollution factor a1, a2..., aX has the following membership:

[0014] The membership degree of the evaluation level is expressed as:

[0015]

[0016] a1, a2..., aX in the above represent the membership of pollution factor ui to each evaluation level.

[0017] Among them, e1 and e2 are the classification standard values ​​of pollution factors a1, a2..., aX.

[0018] Preferably, in the step 4, the heavy metal pollution degree in the soil is evaluated by the evaluation index system described in the step 1, and the risk level is represented by D. When D < 0.25, the risk level is low risk; when 0.25 < D ≤ 0.5, the risk level is medium risk; when 0.5 < D ≤ 0.75, the risk level is high risk.

[0019] When 0.75<D≤1, the risk level is extremely high, which can be expressed as:

[0020]

[0021] Preferably, when calculating the average values ​​respectively, a1, a2 ..., aX in the step three are used for the comprehensive risk assessment of heavy metal pollution in the soil by the evaluation index system described in the step one, and the types of heavy metals to be detected within the study area are determined and numbered. If there are n types of heavy metals to be detected in total, the metals are numbered A, B, C, D ... n, and the concentrations of the n heavy metals in each sample are measured one by one, and the average concentration value of each heavy metal is calculated respectively.

[0022] Preferably, the step 5 establishes a numerical simulation model for metal pollution, and the conceptual model grid is set as follows:

[0023] (1) The number of grids in the conceptual model is nx*ny*(nz1+1+nz2), where nx is the number of grids in the x direction, ny is the number of grids in the y direction, nz1 is the number of grids in the z direction of the first soil, and nz2 is the number of grids in the z direction of the second soil);

[0024] (2) The size of each grid is dx*dy*dz, where dx is the grid length in the x direction, dy is the grid length in the y direction, and dz is the grid length of the soil or interlayer in the z direction. The requirements are: dx*nx = well spacing in the x direction, dy*ny = well spacing in the y direction, nz1 ≥ 1, nz2 ≥ 1.

[0025] Preferably, in step five, the combined drainage of multiple pollution sources including main pollution sources and non-main pollution sources are taken into consideration, and the main pollution sources and non-main pollution sources are defined as the first pollution source, the second pollution source, the third pollution source, and so on, respectively. According to the data collected in step one, by controlling different assignment methods, multiple sets of numerical simulation models are established on the basis of the construction of the aforementioned grid model.

[0026] Preferably, in step 5, the first set of model parameters is set as follows:

[0027] (A1) assigning parameter attribute values ​​to the 1st, 2nd, ..., nz1th layer grids and the nz1+2nd, nz1+3rd, ..., nz1+1+nz2th layer grids according to the collected first coal seam attribute data;

[0028] (A2) assigning the collected interlayer attribute data to the nz1+1th layer grid;

[0029] (A3) Based on the collected pollution source data, define the mixed pollution area of ​​the first pollution source and the second pollution source.

[0030] The second set of model parameters are set as follows:

[0031] (B1) assigning parameter attribute values ​​to the 1st, 2nd, ..., nz1th layer grids according to the collected first pollution source attribute data;

[0032] (B2) assigning parameter attribute values ​​to the nz1+2, nz1+3, ..., nz1+1+nz2 layer grids according to the collected second pollution source attribute data;

[0033] (B3) Assign the collected pollution source attribute data to the nz1+1th layer grid;

[0034] (B4) Based on the collected pollution source data, define the pollution solution area for the first pollution source and the second pollution source.

[0035] Preferably, in S3, for the multiple sets of numerical simulation models established in step five, numerical simulation software is used to simulate the heavy metal contamination process of soil, and the dynamic change data of heavy metal content in the soil of each region is obtained. During the simulation, the heavy metal content data of the soil in the j-th region of model one at the t-th time step is recorded as Qdj(t), and the heavy metal content data of the soil in the j-th region of model two at the t-th time step is recorded as Qhj(t).

[0036] Preferably, in step six: calculating the interference factors, the simulated single-region heavy metal pollutant content data and multi-region combined production data are obtained.

[0037] Calculate the interference factor α:

[0038] in

[0039] If α>0, it means that the interference of heavy metal pollution in the regional soil has a positive effect on the soil in the region. In the later development process, it can be treated by applying modifiers to change the existence form of heavy metals in the soil; if α<0, the heavy metal pollution in the regional soil has a negative effect on the soil in the region, and the smaller the interference coefficient of the regional soil, the more significant the negative effect. In the later development process, it is necessary to consider removing heavy metals from the soil for treatment.

[0040] The present invention has the following beneficial effects:

[0041] This comprehensive evaluation method for heavy metal pollution in soil environment can provide a comprehensive and accurate heavy metal pollution evaluation method through the combination of data collection and processing and comprehensive evaluation model construction, provide a scientific basis for soil environmental management and decision-making, and help improve water environment quality and protect the ecological environment. At the same time, based on the importance and contribution of the indicators, the hierarchical analysis method determines the weight of each indicator, considering the relative importance of multiple factors, making the evaluation results more accurate, and the quality of contaminated soil in the region can be evaluated based on different results. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1It is a schematic diagram summarizing the overall determination process of the present invention;

[0043] Figure 2 It is a schematic diagram of the process determination module of the present invention. DETAILED DESCRIPTION

[0044] 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.

[0045] See also Figure 1-2 In this embodiment: a comprehensive evaluation method for heavy metal pollution in soil environment, characterized in that: it includes the following steps:

[0046] Step 1: Construct an evaluation index system for the degree of heavy metal pollution in soil. The index system evaluates and determines the degree of pollution, scope of impact and ecological risk respectively. Then, the soil composition in the required collection area is determined, and random sampling is carried out in different regions.

[0047] Step 2: Collecting heavy metal pollution data in the soil environment according to the indicator system constructed in step 1, wherein the heavy metal pollution data includes sampling data and monitoring data, and preprocessing the collected data;

[0048] Step 3: According to the comprehensive risk assessment of heavy metal pollution, determine the types of heavy metals to be detected in the study area and number them. If there are n types of heavy metals to be detected, the metals are numbered 1, 2, ... n; measure the concentrations of n heavy metals in each sample one by one, and calculate the average concentration value of each heavy metal respectively;

[0049] Step 4: Determine the weight of each indicator according to its importance and contribution, and establish a weight set A = {a1, a2..., aX} according to the pollution degree of the pollution factor, where a1, a2..., aX represent the type of pollution, pollution range, pollution category and the weight of other pollution factors respectively;

[0050] Step 5: Establish a numerical simulation model for metal pollution;

[0051] Step 6: Calculate the interference factor;

[0052] Step 7: When calculating according to the maximum membership principle of fuzzy mathematics, if there are two or more identical or approximately equal maximum values ​​in the calculation results, the environmental quality evaluation level shall be determined according to the second largest level principle.

[0053] Furthermore, the membership of each pollution factor to the evaluation level is determined, and the corresponding relationship matrix B is obtained, including the membership calculated according to the measured value of the pollution factor and the classification standard value. Assuming that the measured value of the pollution factor a1, a2..., aX is x, the membership of the pollution factor a1, a2..., aX to each evaluation level is expressed as:

[0054]

[0055] a1, a2..., aX in the above represent the membership of pollution factor ui to each evaluation level.

[0056] Among them, e1 and e2 are the classification standard values ​​of pollution factors a1, a2..., aX.

[0057] Furthermore, in step 4, the degree of heavy metal pollution in the soil is evaluated by the evaluation index system of step 1, and the risk level is represented by D. When D < 0.25, the risk level is low risk; when 0.25 < D ≤ 0.5, the risk level is medium risk; when 0.5 < D ≤ 0.75, the risk level is high risk; when 0.75 < D ≤ 1, the risk level is extremely high risk, which can be expressed as:

[0058]

[0059] Furthermore, when calculating the average values ​​of a1, a2, ..., aX in step three, the evaluation index system in step one is used for comprehensive risk assessment of heavy metal pollution in soil, and the types of heavy metals to be detected within the study area are determined and numbered. If there are n types of heavy metals to be detected in total, the metals are numbered A, B, C, D...n, and the concentrations of the n heavy metals in each sample are measured one by one, and the average concentration value of each heavy metal is calculated respectively.

[0060] Furthermore, in step 5, a numerical simulation model of metal pollution is established, and the conceptual model grid is set as follows:

[0061] (1) The number of grids in the conceptual model is nx*ny*(nz1+1+nz2), where nx is the number of grids in the x direction, ny is the number of grids in the y direction, nz1 is the number of grids in the z direction of the first soil, and nz2 is the number of grids in the z direction of the second soil);

[0062] (2) The size of each grid is dx*dy*dz, where dx is the grid length in the x direction, dy is the grid length in the y direction, and dz is the grid length of the soil or interlayer in the z direction. The requirements are: dx*nx = well spacing in the x direction, dy*ny = well spacing in the y direction, nz1 ≥ 1, nz2 ≥ 1.

[0063] Furthermore, in the step five, the combined drainage of multiple pollution sources including main pollution sources and non-main pollution sources are considered, and the main pollution sources and non-main pollution sources are defined as the first pollution source, the second pollution source, the third pollution source, and so on. According to the data collected in the step one, by controlling different assignment methods, multiple sets of numerical simulation models are established on the basis of the aforementioned grid model construction.

[0064] Furthermore, in step 5, the first set of model parameters is set as follows:

[0065] (A1) assigning parameter attribute values ​​to the 1st, 2nd, ..., nz1th layer grids and the nz1+2nd, nz1+3rd, ..., nz1+1+nz2th layer grids according to the collected first coal seam attribute data;

[0066] (A2) assigning the collected interlayer attribute data to the nz1+1th layer grid;

[0067] (A3) Based on the collected pollution source data, define the mixed pollution area of ​​the first pollution source and the second pollution source.

[0068] The second set of model parameters are set as follows:

[0069] (B1) assigning parameter attribute values ​​to the 1st, 2nd, ..., nz1th layer grids according to the collected first pollution source attribute data;

[0070] (B2) assigning parameter attribute values ​​to the nz1+2, nz1+3, ..., nz1+1+nz2 layer grids according to the collected second pollution source attribute data;

[0071] (B3) Assign the collected pollution source attribute data to the nz1+1th layer grid;

[0072] (B4) Based on the collected pollution source data, define the pollution solution area for the first pollution source and the second pollution source.

[0073] Furthermore, in S3, for the multiple sets of numerical simulation models established in step five, numerical simulation software is used to simulate the heavy metal contamination process of soil, and the dynamic change data of heavy metal content in the soil of each region is obtained. During the simulation, the heavy metal content data of the soil in the j-th region of model one at the t-th time step is recorded as Qdj(t), and the heavy metal content data of the soil in the j-th region of model two at the t-th time step is recorded as Qhj(t).

[0074] Furthermore, in step six: calculating the interference factors, the simulated single-region heavy metal pollutant content data and multi-region combined production data are obtained.

[0075] Calculate the interference factor α:

[0076] in

[0077] If α>0, it means that the interference of heavy metal pollution in the regional soil has a positive effect on the soil in the region. In the later development process, it can be treated by applying modifiers to change the existence form of heavy metals in the soil; if α<0, the heavy metal pollution in the regional soil has a negative effect on the soil in the region, and the smaller the interference coefficient of the regional soil, the more significant the negative effect. In the later development process, it is necessary to consider removing heavy metals from the soil for treatment.

[0078] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A comprehensive evaluation method for heavy metal pollution in soil environment, characterized by: The following steps are involved: Step 1: Construct an evaluation index system for the degree of heavy metal pollution in soil. The index system evaluates and determines the degree of pollution, scope of impact and ecological risk respectively. Then, the soil composition in the required collection area is determined, and random sampling is carried out in different regions. Step 2: Collecting heavy metal pollution data in the soil environment according to the indicator system constructed in step 1, wherein the heavy metal pollution data includes sampling data and monitoring data, and preprocessing the collected data; Step 3: According to the comprehensive risk assessment of heavy metal pollution, determine the types of heavy metals to be detected in the study area and number them. If there are n types of heavy metals to be detected, the metals are numbered 1, 2, ... n; measure the concentrations of n heavy metals in each sample one by one, and calculate the average concentration value of each heavy metal respectively; Step 4: Determine the weight of each indicator according to its importance and contribution, and establish a weight set A = {a1, a2..., aX} according to the pollution degree of the pollution factor, where a1, a2..., aX represent the type of pollution, pollution range, pollution category and the weight of other pollution factors respectively; Step 5: Establish a numerical simulation model for metal pollution; Step 6: Calculate the interference factor; Step 7: When calculating according to the maximum membership principle of fuzzy mathematics, if there are two or more identical or approximately equal maximum values ​​in the calculation results, the environmental quality evaluation level shall be determined according to the second largest level principle.

2. A comprehensive evaluation method for heavy metal pollution in soil environment according to claim 1, characterized in that: The determination of the membership of each pollution factor to the evaluation level obtains the corresponding relationship matrix B, including the membership calculated according to the measured value of the pollution factor and the classification standard value. Assuming that the measured value of the pollution factor a1, a2..., aX is x, the membership of the pollution factor a1, a2..., aX to each evaluation level is expressed as: a1, a2..., aX in the above represent the membership of pollution factor ui to each evaluation level. Among them, e1 and e2 are the classification standard values ​​of pollution factors a1, a2..., aX.

3. A comprehensive evaluation method for heavy metal pollution in soil environment according to claim 1, characterized in that: In the step 4, the heavy metal pollution degree in the soil is evaluated by the evaluation index system described in the step 1, and the risk level is represented by D. When D < 0.25, the risk level is low risk; when 0.25 < D ≤ 0.5, the risk level is medium risk; when 0.5 < D ≤ 0.75, the risk level is high risk; when 0.75 < D ≤ 1, the risk level is extremely high risk, which can be expressed as: 。 4. A comprehensive evaluation method for heavy metal pollution in soil environment according to claim 1, characterized in that: When calculating the average values ​​respectively, a1, a2 ..., aX in the step three are used for the comprehensive risk assessment of heavy metal pollution in the soil by the evaluation index system described in the step one, and the types of heavy metals to be detected within the study area are determined and numbered. If there are n types of heavy metals to be detected in total, the metals are numbered A, B, C, D ... n, and the concentrations of the n heavy metals in each sample are measured one by one, and the average concentration value of each heavy metal is calculated respectively.

5. A comprehensive evaluation method for heavy metal pollution in soil environment according to claim 1, characterized in that: The step 5 establishes a numerical simulation model for metal pollution, and the conceptual model grid is set as follows: (1) The number of grids in the conceptual model is nx*ny*(nz1+1+nz2), where nx is the number of grids in the x direction, ny is the number of grids in the y direction, nz1 is the number of grids in the z direction of the first soil, and nz2 is the number of grids in the z direction of the second soil); (2) The size of each grid is dx*dy*dz, where dx is the grid length in the x direction, dy is the grid length in the y direction, and dz is the grid length of the soil or interlayer in the z direction. The requirements are: dx*nx = well spacing in the x direction, dy*ny = well spacing in the y direction, nz1 ≥ 1, nz2 ≥ 1.

6. A comprehensive evaluation method for heavy metal pollution in soil environment according to claim 1, characterized in that: In the step five, the combined drainage of multiple pollution sources including main pollution sources and non-main pollution sources are considered, and the main pollution sources and non-main pollution sources are defined as the first pollution source, the second pollution source, the third pollution source, and so on. According to the data collected in the step one, by controlling different assignment methods, multiple sets of numerical simulation models are established on the basis of the above-mentioned grid model construction.

7. A method for comprehensive evaluation of heavy metal pollution in soil environment according to claim 6, characterized in that: In step 5, the first set of model parameters is set as follows: (A1) assigning parameter attribute values ​​to the 1st, 2nd, ..., nz1th layer grids and the nz1+2nd, nz1+3rd, ..., nz1+1+nz2th layer grids according to the collected first coal seam attribute data; (A2) assigning the collected interlayer attribute data to the nz1+1th layer grid; (A3) Based on the collected pollution source data, define the mixed pollution area of ​​the first pollution source and the second pollution source; The second set of model parameters are set as follows: (B1) assigning parameter attribute values ​​to the 1st, 2nd, ..., nz1th layer grids according to the collected first pollution source attribute data; (B2) assigning parameter attribute values ​​to the nz1+2, nz1+3, ..., nz1+1+nz2 layer grids according to the collected second pollution source attribute data; (B3) Assign the collected pollution source attribute data to the nz1+1th layer grid; (B4) Based on the collected pollution source data, define the pollution solution area for the first pollution source and the second pollution source.

8. A comprehensive evaluation method for heavy metal pollution in soil environment according to claim 7, characterized in that: In S3, for the multiple sets of numerical simulation models established in step 5, numerical simulation software is used to simulate the heavy metal contamination process of soil, and the dynamic change data of heavy metal content in the soil of each region is obtained. During the simulation, the heavy metal content data of the soil in the j-th region of model 1 at the t-th time step is recorded as Qdj(t), and the heavy metal content data of the soil in the j-th region of model 2 at the t-th time step is recorded as Qhj(t).

9. A method for comprehensive evaluation of heavy metal pollution in soil environment according to claim 8, characterized in that: Step 6: Calculate the interference factors, and simulate the single-region heavy metal pollutant content data and multi-region combined production data: Calculate the interference factor α: in If α>0, it means that the interference of heavy metal pollution in the regional soil has a positive effect on the soil in the region. In the later development process, it can be treated by applying modifiers to change the existence form of heavy metals in the soil; if α<0, the heavy metal pollution in the regional soil has a negative effect on the soil in the region, and the smaller the interference coefficient of the regional soil, the more significant the negative effect. In the later development process, it is necessary to consider removing heavy metals from the soil for treatment.

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