Heavy metal area environment risk assessment method and device and storage medium

Abstract

The invention relates to the technical field of environmental risk assessment, and particularly discloses a heavy metal area environmental risk assessment method and device and a storage medium, and the method comprises the steps: selecting a research object area, and employing the combination of an administrative region boundary and a grid partitioning method to divide assessment units; establishing an evaluation index system, selecting regional environment risk evaluation indexes in the evaluation index system, and obtaining index weights of the evaluation index system by using an analytic hierarchy process; obtaining an environmental risk value of the evaluation unit in combination with the evaluation index system and the index weight; grading the quantified environmental risk value of each evaluation unit; and performing spatial rendering on the graded evaluation units to obtain a regional environment risk grading and partitioning map. The problem that in the prior art, it is difficult to comprehensively and deeply reflect the environmental risk situation of a heavy metal-related area by simply analyzing sudden elements is solved.

Description

Technical Field

[0001] The present application relates to the technical field of environmental risk assessment, and in particular to a method, device and storage medium for heavy metal regional environmental risk assessment. Background Art

[0002] Effectively carrying out regional environmental risk assessments for environmental incidents, mass incidents, blood lead incidents, cadmium exceeding the standard in food and other heavy metal pollution incidents caused by heavy metals will help to systematically identify the types of regional environmental risks, accurately control key areas and key links with potential environmental risks, and improve the management departments' ability to prevent, control and manage environmental risks, which is of practical significance in actual management work.

[0003] At present, the domestic environmental risk assessment system basically belongs to the category of sudden environmental risks, including the "Recommended Methods for Risk Assessment of Sudden Environmental Events in Administrative Regions" (hereinafter referred to as the "Recommended Methods") issued by the former Ministry of Environmental Protection in January 2018, which belongs to the regional assessment of environmental risks, but also focuses on sudden environmental risk assessment. In view of the significant characteristics of environmental risks of heavy metal pollution such as long-term, cumulative and persistent, it is difficult to comprehensively and deeply reflect the environmental risk situation in heavy metal-related regions by simply analyzing sudden factors. Summary of the invention

[0004] The purpose of this application is to provide a heavy metal regional environmental risk assessment method, device and storage medium to solve the problem in the prior art that simply analyzing sudden factors is difficult to comprehensively and deeply reflect the environmental risk situation in heavy metal-related regions.

[0005] To achieve the above-mentioned purpose, the embodiment of the present application provides a method for regional environmental risk assessment of heavy metals, comprising the following steps: selecting a research object area, dividing the assessment unit by combining administrative area boundaries with a grid partitioning method;

[0006] Establishing an evaluation index system, selecting regional environmental risk assessment indicators in the evaluation index system, and obtaining the indicator weights of the evaluation index system using a hierarchical analysis method;

[0007] Combining the evaluation index system and index weights, obtaining the environmental risk value of the evaluation unit;

[0008] Classifying the quantified environmental risk value of each assessment unit;

[0009] The graded assessment units are spatially rendered to obtain a regional environmental risk classification zoning map.

[0010] Optionally, the evaluation index system includes a two-level index system constructed from two aspects: the risk of regional environmental pollution sources and the vulnerability of regional environmental risk receptors. The two-level index system includes a primary index layer and a secondary index layer. The primary index layer includes two specific indicators: the risk of regional environmental pollution sources and the vulnerability of regional environmental risk receptors.

[0011] The secondary indicator layer corresponding to the risk of regional environmental pollution sources includes: the number of regional heavy metal-related enterprises, the ratio of regional environmental risk material inventory to critical quantity, the number of regional environmental risk level enterprises above a high level, the number of environmental incidents in the region in the past five years, the number of regional tailings ponds, the total discharge of heavy metals in regional wastewater, the total discharge of heavy metals in regional waste gas, the amount of general solid waste generated in the region, and the amount of hazardous waste generated in the region;

[0012] The secondary indicator layer corresponding to the vulnerability of the regional environmental risk receptor includes: regional population, regional population density, number of settlements in the region, regional cultivated land area, regional ecological red line range, drinking water source area in the region, water sensitivity in the region, and GDP per capita;

[0013] The indicators of the secondary indicator layer are the selected regional environmental risk assessment indicators.

[0014] Optionally, the obtaining the indicator weights of the evaluation indicator system by using the hierarchical analysis method specifically includes:

[0015] The entire evaluation index system is analyzed by using the hierarchical analysis method, the target layer and the criterion layer are determined, and a hierarchical structure model is established to construct a judgment matrix. The 1-9 scaling method of the TLSaaty hierarchical analysis is used to assign values ​​to the judgment matrix, and the eigenvector and the maximum eigenroot of the judgment matrix are calculated and a consistency test is performed. Finally, the indicator weight values ​​of the environmental risk assessment indicators of each region are obtained.

[0016] Optionally, the judgment matrix is ​​as shown below:

[0017]

[0018] Among them, the element A in the judgment matrix il Represents element A i For element A l The relative importance of the data is divided into five levels: equally important, slightly important, relatively important, very important, absolutely important, A i With A l Both represent one of the secondary indicators corresponding to one of the primary indicators, and k is 8 or 9.

[0019] Optionally, the performing consistency check specifically includes:

[0020] Use the consistency test formula to perform consistency test:

[0021]

[0022] Among them, CR is the matrix consistency test coefficient, CI is the matrix consistency compatibility index, RI is the average random consistency index, λmax is the maximum eigenvalue of the judgment matrix, n is the non-zero eigenvalue, and the smaller the CI value, the better the consistency of the judgment matrix.

[0023] Optionally, obtaining the environmental risk value specifically includes:

[0024] The index values ​​obtained by statistics of each evaluation unit are standardized, and the standardization formula is as follows:

[0025]

[0026] Among them, W′ i is the standard value of the factor; W i is the original value of the factor; is the factor average value; σ is the factor mean square error; the index value is the value corresponding to the regional environmental risk assessment index;

[0027] The standard values ​​of each indicator obtained after standardization are summed with weights to obtain the environmental risk receptor vulnerability score and pollution source risk score of each assessment unit. The environmental risk value of each assessment unit is calculated by multiplying the scores of the pollution source risk and environmental risk receptor vulnerability indicators and taking the square root.

[0028] The acquisition of each indicator value is achieved through GIS technology, and the spatial statistical analysis function of the GIS system is used to count all indicator layer information within the evaluation unit by superimposing the grid vector range and various basic quantity data, calculate the intersection between the two feature classes, and cross-tabulate the area, length or number of the intersecting elements.

[0029] Optionally, grading the quantified environmental risk value of each assessment unit specifically includes:

[0030] According to the numerical value of the comprehensive environmental risk value of the assessment unit, the regional environmental risk of the assessment unit is divided into three levels: high, relatively high, medium and low.

[0031] Optionally, the step of spatially rendering the graded assessment units to obtain a regional environmental risk graded zoning map specifically includes:

[0032] After combining the graded assessment units with GIS technology to complete spatial rendering, a regional environmental risk classification zoning map is obtained.

[0033] To achieve the above-mentioned purpose, the present application also provides a heavy metal regional environmental risk assessment device, comprising: a memory; and

[0034] A processor connected to the memory, the processor being configured to execute the steps of the method as described above.

[0035] To achieve the above objectives, the present application also provides a computer storage medium on which a computer program is stored, wherein the computer program implements the steps of the above method when executed by a machine.

[0036] The embodiments of the present application have the following advantages:

[0037] Through the above methods, combined with existing environmental risk assessment ideas, starting from the suddenness and accumulation of environmental risks, we studied and established a heavy metal environmental risk assessment system, carried out quantitative classification of regional environmental risks, and combined the grid zoning method with GIS technology to spatially visualize the classification results, providing a way for management departments to intuitively and conveniently understand the regional environmental risk situation, and at the same time providing a basis for making scientific, objective and targeted heavy metal pollution prevention and control decisions. This solves the problem that it is difficult to comprehensively and deeply reflect the regional environmental risk situation involving heavy metals by simply analyzing sudden factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the implementation methods of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings described below are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0039] Figure 1 A flowchart of a heavy metal regional environmental risk assessment method provided for at least one embodiment of the present application;

[0040] Figure 2 A technical roadmap for a heavy metal regional environmental risk assessment method provided for at least one embodiment of the present application;

[0041] Figure 3 A hierarchical relationship diagram of regional environmental risk assessment indicators for a method for regional environmental risk assessment of heavy metals provided by at least one embodiment of the present application;

[0042] Figure 4 A schematic diagram of an indicator importance judgment matrix of a heavy metal regional environmental risk assessment method provided by at least one embodiment of the present application;

[0043] Figure 5Another schematic diagram of an indicator importance judgment matrix of a heavy metal regional environmental risk assessment method provided by at least one embodiment of the present application;

[0044] Figure 6 A schematic diagram of the spatial statistical analysis principle of a heavy metal regional environmental risk assessment method provided in at least one embodiment of the present application;

[0045] Figure 7 A schematic diagram of an example of gridded environmental risk characterization of a heavy metal regional environmental risk assessment method provided in at least one embodiment of the present application;

[0046] Figure 8 A module block diagram of a heavy metal regional environmental risk assessment device provided in at least one embodiment of the present application. DETAILED DESCRIPTION

[0047] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0048] It should be noted that the steps in the claims and description of the present application may be executed substantially in parallel or in reverse order under appropriate circumstances, depending on the functions involved.

[0049] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0050] The present application provides a method for regional environmental risk assessment of heavy metals. The method takes regions as research objects, divides assessment units by grid zoning method, establishes an assessment index system, uses analytic hierarchy process to scientifically calculate index weights, extends the grid zoning method applicable to counties to other regional areas, combines the established index system, quantifies grid risk values ​​by calculation rules, and then uses GIS technology to complete spatial rendering to obtain a regional environmental risk classification zoning map, providing a way for management departments to intuitively and conveniently understand regional environmental risk situations, and at the same time providing a basis for making scientific, objective and targeted decisions on heavy metal pollution prevention and control.

[0051] A method for assessing regional environmental risk of heavy metals provided in one embodiment of the present application is described in detail in Figure 1 , Figure 1A flowchart of a heavy metal regional environmental risk assessment method is provided in at least one embodiment of the present application. It should be understood that the method may also include additional boxes not shown and / or the boxes shown may be omitted, and the scope of the present application is not limited in this respect.

[0052] In step 101, a research object area is selected, and assessment units are divided using a combination of administrative area boundaries and a grid partitioning method.

[0053] At step 102, an evaluation index system is established, regional environmental risk assessment indicators in the evaluation index system are selected, and the index weights of the evaluation index system are obtained using the analytic hierarchy process.

[0054] In step 103, the environmental risk value of the assessment unit is obtained by combining the assessment index system and the index weight.

[0055] At step 104, the quantified environmental risk value of each assessment unit is graded.

[0056] At step 105, the graded assessment units are spatially rendered to obtain a regional environmental risk graded zoning map.

[0057] In some embodiments, the research object area refers to a region as the research object, and the grid division method applicable to districts and counties is extended to other regional areas.

[0058] In some embodiments, the division of assessment units refers to the use of grid zoning to divide units with reference to the "Recommended Methods for Risk Assessment of Sudden Environmental Events in Administrative Regions". With reference to the corresponding content of the "Recommended Methods for Risk Assessment of Sudden Environmental Events in Administrative Regions" regarding the division of grid areas in geographic space, for administrative regions with sufficient data and relatively accurate geographic coordinates of environmental risk sources and receptors, the assessment area can be divided into several grid areas according to geographic space, and regional environmental risk analysis can be performed with grids as assessment units.

[0059] In some embodiments, the grid accuracy of the evaluation units divided by the grid partitioning method can be determined according to the size of the evaluation area and actual needs. For example, the grid range is set between (5km×5km) and (1km×1km).

[0060] In some embodiments, the establishment of an assessment index system refers to the selection of regional environmental risk assessment indicators; the selection of regional environmental risk assessment indicators refers to referring to the relevant provisions of the "Recommended Methods for Risk Assessment of Sudden Environmental Events in Administrative Regions". When the various indicators involved in the environmental risk prevention and control and emergency response capability index are difficult to obtain, the environmental risk macro-zoning may only consider two aspects: the pollution intensity of the risk area and the vulnerability of the regional environmental receptors.

[0061] In some embodiments, the establishment of the evaluation index system and the selection of the regional environmental risk assessment index in the evaluation index system specifically include: the regional environmental risk assessment index system described in the embodiment of the present application includes a two-level index system constructed from two aspects of the risk of regional environmental pollution sources (S) and the vulnerability of regional environmental risk receptors (V), and the two-level index system includes a primary index layer and a secondary index layer, and the primary index layer includes two specific indicators of the risk of regional environmental pollution sources (S) and the vulnerability of regional environmental risk receptors (V);

[0062] The secondary indicator layer corresponding to the risk of regional environmental pollution sources includes: the number of regional heavy metal-related enterprises, the ratio of regional environmental risk material inventory to critical quantity, the number of regional environmental risk level enterprises above a high level, the number of environmental incidents in the region in the past five years, the number of regional tailings ponds, the total discharge of heavy metals in regional wastewater, the total discharge of heavy metals in regional waste gas, the amount of general solid waste generated in the region, and the amount of hazardous waste generated in the region;

[0063] The secondary indicator layer corresponding to the vulnerability of the regional environmental risk receptor includes: regional population, regional population density, number of settlements in the region, regional cultivated land area, regional ecological red line range, drinking water source area in the region, water sensitivity in the region, and GDP per capita;

[0064] The above two secondary indicator layers have a total of 17 specific indicators. The indicators of the secondary indicator layer are the selected regional environmental risk assessment indicators. The environmental pollution source risk (S) indicator and the regional environmental risk receptor vulnerability (V) indicator are shown in Table 1, and the indicator level is shown in Table 2. Figure 3 .

[0065] Table 1: Comprehensive environmental risk indicators for heavy metal-related regions

[0066]

[0067] In some embodiments, obtaining the indicator weights refers to scientifically calculating the indicator weights using the analytic hierarchy process. The specific method includes: using the analytic hierarchy process (AHP) to analyze the entire evaluation indicator system, determine the target layer, the criterion layer and establish a hierarchical structure model, construct a judgment matrix, combine the Delphi method, use the TLSaaty hierarchical analysis 1-9 scaling method to assign values ​​to the judgment matrix, calculate the eigenvector and the maximum eigenroot of the judgment matrix and perform a consistency test, and finally obtain the indicator weight values ​​of each of the regional environmental risk assessment indicators.

[0068] Specifically, the indicators at the indicator layer and the criterion layer in the hierarchical model are compared in pairs, combined with the Delphi method, and the indicator importance is selected, and then the indicator importance is converted into a corresponding score in combination with the 1-9 scaling method.

[0069] In some embodiments, the judgment matrix is ​​established as shown in the following formula (1):

[0070]

[0071] Among them, the element A in the judgment matrix il Represents element A i For element A l The relative importance of the data is divided into five levels: equally important, slightly important, relatively important, very important, absolutely important, A i With A l Each represents one of the secondary indicators corresponding to one of the primary indicators, and k is 8 or 9. The qualitative judgment quantification process of the 1-9 scaling method is shown in Table 2.

[0072] Table 2: Quantification process of the scaling method qualitative results

[0073]

[0074] In some embodiments, in the process of assigning values ​​to the judgment matrix, in order to avoid logical errors such as A1 is more important than A2, A2 is more important than A3, and A3 is more important than A1, the judgment matrix needs to be checked for consistency. The consistency check formulas (2) and (3) are shown. The smaller the CI value in the formula, the better the consistency of the judgment matrix. If the CR value is less than 0.1, it can be considered that the judgment matrix has passed the consistency check, and the eigenvector of the matrix is ​​acceptable for use as weights.

[0075]

[0076] Among them, in formula (2), CR is the matrix consistency test coefficient, CI is the matrix consistency compatibility index, and RI is the average random consistency index (fixed value).

[0077] In formula (3), CI is the matrix consistency compatibility index, λmax is the maximum eigenvalue of the judgment matrix, and n is the non-zero eigenvalue.

[0078] Specifically, the judgment matrix constructed using the hierarchical analysis method is used to assign scores to the relative importance of each indicator. Figure 4 and Figure 5 As shown. After obtaining the importance judgment matrix, the eigenvector, weight value and maximum eigenroot (used to calculate CI value, CI value is used for consistency test) are calculated according to the judgment matrix. The weight of each indicator in the indicator system is obtained, and the determination of the indicator weight is completed accordingly.

[0079] In some embodiments, the obtaining of the environmental risk value specifically includes: firstly, standardizing the index value obtained by statistics of each evaluation unit, and the standardization formula is as follows:

[0080]

[0081] Among them, W′ in formula (4) i is the standard value of the factor; W i is the original value of the factor; is the factor average value; σ is the factor mean square error; the index value is the value corresponding to the regional environmental risk assessment index;

[0082] The standard values ​​of each indicator obtained after standardization are summed with weights to obtain the environmental risk receptor vulnerability (V) score and pollution source risk (S) score of each assessment unit. The environmental risk value is calculated by the pollution source risk (S) and the environmental risk receptor vulnerability (V). The environmental risk value of each assessment unit is calculated by multiplying the scores of the two indicators and taking the square root (refer to formula (5)).

[0083]

[0084] In some embodiments, the quantified environmental risk value of each assessment unit is graded, specifically including: referring to the "Recommended Methods for Risk Assessment of Sudden Environmental Events in Administrative Regions" and dividing the regional environmental risk of the assessment unit into three levels: high, relatively high, medium, and low according to the numerical value of the comprehensive environmental risk value of the assessment unit. The boundary value of the division index can be determined based on the environmental risk value of each assessment unit and in combination with the actual local management requirements.

[0085] In some embodiments, examples of environmental risk level classification rules are shown in Table 3.

[0086] Table 3: Example of regional environmental risk level classification

[0087]

[0088] In some embodiments, the regional environmental risk classification and zoning map specifically includes: combining the classified assessment units with GIS technology to complete spatial rendering to obtain a regional environmental risk classification and zoning map.

[0089] In some embodiments, the acquisition of each of the index values ​​in the present application is achieved through GIS technology, and the spatial statistical analysis function of the GIS system is used to perform statistics on all the index layer information in the evaluation unit by superimposing the grid vector range and each basic quantity data, calculate the intersection between the two feature classes and cross-tabulate the area, length or number of the intersecting elements. The statistical principle is shown in FIG. Figure 6 After the spatial information is counted, each evaluation unit will obtain the parameter values ​​of 17 indicator information.

[0090] The technical solution of this application is further described below in conjunction with specific embodiments:

[0091] A method for heavy metal regional environmental risk assessment adopts the technical roadmap in the above embodiment and is specifically applied according to the steps in the above embodiment.

[0092] (1) A certain area was selected as the research object area, and the assessment unit was divided by combining administrative area boundaries with the grid zoning method. The area was divided into several sub-areas according to the administrative area boundaries (to avoid fuzzy processing involving confidentiality), and the assessment area was divided into several grid areas according to the geographic space. The grid size was (5 km × 5 km), and the regional environmental risk analysis was carried out using the grid as the unit.

[0093] (2) Establish an evaluation index system and select regional environmental risk assessment indicators. The regional environmental risk assessment index system of this application constructs a two-level index system from two aspects: the risk of regional environmental pollution sources (S) and the vulnerability of regional environmental risk receptors (V). That is, the first-level index layer includes two specific indicators: the risk of regional environmental pollution sources (S) and the vulnerability of regional environmental risk receptors (V); the second-level index layer includes the number of regional heavy metal-related enterprises, the ratio of regional environmental risk material inventory to critical quantity, the number of enterprises with a high regional environmental risk level, the number of environmental incidents in the region in the past five years, the number of regional tailings ponds, the total heavy metal discharge of regional wastewater, the total heavy metal discharge of regional waste gas, the amount of general solid waste generated in the region, the amount of hazardous waste generated in the region, the number of regional population, the regional population density, the number of settlements in the region, the area of ​​regional cultivated land, the scope of regional ecological red lines, the area of ​​drinking water sources in the region, the sensitivity of the water bodies in the region, and GDP per capita, totaling 17 specific indicators. The analytic hierarchy process is used to scientifically calculate the indicator weights, determine the target layer and the criterion layer, and establish a hierarchical model. After selecting the evaluation scale, the judgment matrix is ​​constructed. Combined with the Delphi method, the 1-9 scaling method of the TLSaaty hierarchical analysis is used to assign values ​​to the judgment matrix, calculate the matrix eigenvector and the maximum eigenroot, and perform consistency tests. Finally, the weight values ​​of each evaluation factor are obtained. The indicators of the indicator layer and the criterion layer in the hierarchy are compared pairwise, combined with the Delphi method, and the indicator importance is selected, and then the importance is converted into the corresponding weight score in combination with the 1-9 scaling method.

[0094] (3) The environmental risk value is calculated by combining the established indicator system and the calculated indicator weights. First, the indicator values ​​obtained from each grid area are standardized. The standardized standard values ​​of each indicator with weights are added to obtain the environmental risk receptor vulnerability (V) score and pollution source risk (S) score of each grid area. The comprehensive environmental risk value is obtained by the pollution source risk (S) and the environmental risk receptor vulnerability (V). The environmental risk index of each grid area is calculated by multiplying the two indicators and taking the square root.

[0095] (4) Regional environmental risks are quantified and classified according to the Recommended Methods for Risk Assessment of Sudden Environmental Events in Administrative Regions and based on the numerical value of the comprehensive environmental risk index of the grid area, and the regional environmental risks are divided into three levels: high, relatively high, medium, and low.

[0096] (5) After the graded regional environmental risk zones are combined with GIS technology to complete spatial rendering, a regional environmental risk graded zone map is obtained. This application uses GIS technology to obtain each indicator parameter, and uses the spatial statistical analysis function of the GIS system to perform statistics on all indicator layer information within the basic unit grid by superimposing the grid vector range and each basic quantity data, calculate the intersection between the two feature classes, and cross-tabulate the area, length or number of the intersecting elements. See the grid representation example. Figure 7 .

[0097] Through the above methods, combined with existing environmental risk assessment ideas, starting from the dual perspectives of suddenness and accumulation, we studied and established a heavy metal environmental risk assessment system, carried out quantitative classification of regional environmental risks, and combined the grid zoning method with GIS technology to spatially visualize the classification results, providing a way for management departments to intuitively and conveniently understand the regional environmental risk situation, and at the same time providing a basis for making scientific, objective, and targeted heavy metal pollution prevention and control decisions. This solves the problem that it is difficult to comprehensively and deeply reflect the regional environmental risk situation involving heavy metals by simply analyzing sudden factors.

[0098] Figure 8 A block diagram of a heavy metal regional environmental risk assessment device provided in at least one embodiment of the present application. The device includes:

[0099] A memory 201; and a processor 202 connected to the memory 201, wherein the processor 202 is configured to: select a research object area, and divide the evaluation units by combining administrative area boundaries with a grid partitioning method;

[0100] Establishing an evaluation index system, selecting regional environmental risk assessment indicators in the evaluation index system, and obtaining the indicator weights of the evaluation index system using a hierarchical analysis method;

[0101] Combining the evaluation index system and index weights, obtaining the environmental risk value of the evaluation unit;

[0102] Classifying the quantified environmental risk value of each assessment unit;

[0103] The graded assessment units are spatially rendered to obtain a regional environmental risk classification zoning map.

[0104] In some embodiments, the processor 202 is further configured to: the evaluation index system includes a two-level index system constructed from two aspects of regional environmental pollution source risk and regional environmental risk receptor vulnerability, the two-level index system includes a primary index layer and a secondary index layer, the primary index layer includes two specific indicators of regional environmental pollution source risk and regional environmental risk receptor vulnerability;

[0105] The secondary indicator layer corresponding to the risk of regional environmental pollution sources includes: the number of regional heavy metal-related enterprises, the ratio of regional environmental risk material inventory to critical quantity, the number of regional environmental risk level enterprises above a high level, the number of environmental incidents in the region in the past five years, the number of regional tailings ponds, the total discharge of heavy metals in regional wastewater, the total discharge of heavy metals in regional waste gas, the amount of general solid waste generated in the region, and the amount of hazardous waste generated in the region;

[0106] The secondary indicator layer corresponding to the vulnerability of the regional environmental risk receptor includes: regional population, regional population density, number of settlements in the region, regional cultivated land area, regional ecological red line range, drinking water source area in the region, water sensitivity in the region, and GDP per capita;

[0107] The indicators of the secondary indicator layer are the selected regional environmental risk assessment indicators.

[0108] In some embodiments, the processor 202 is further configured to: the step of obtaining the indicator weights of the evaluation indicator system by using the hierarchical analysis method specifically includes:

[0109] The entire evaluation index system is analyzed by using the hierarchical analysis method, the target layer and the criterion layer are determined, and a hierarchical structure model is established to construct a judgment matrix. Combined with the Delphi method, the 1-9 scaling method of the TLSaaty hierarchical analysis is used to assign values ​​to the judgment matrix, and the eigenvector and the maximum eigenroot of the judgment matrix are calculated and a consistency test is performed. Finally, the indicator weight values ​​of each regional environmental risk assessment indicator are obtained.

[0110] In some embodiments, the processor 202 is further configured to: the judgment matrix is ​​as follows:

[0111]

[0112] Among them, the element A in the judgment matrix il Represents element A i For element A l The relative importance of the data is divided into five levels: equally important, slightly important, relatively important, very important, absolutely important, A i With A l Both represent one of the secondary indicators corresponding to one of the primary indicators, and k is 8 or 9.

[0113] In some embodiments, the processor 202 is further configured to: the performing of consistency check specifically includes:

[0114] Use the consistency test formula to perform consistency test:

[0115]

[0116] Among them, CR is the matrix consistency test coefficient, CI is the matrix consistency compatibility index, RI is the average random consistency index, λmax is the maximum eigenvalue of the judgment matrix, n is the non-zero eigenvalue, and the smaller the CI value, the better the consistency of the judgment matrix.

[0117] In some embodiments, the processor 202 is further configured to: obtain the environmental risk value, specifically including:

[0118] The index values ​​obtained by statistics of each evaluation unit are standardized, and the standardization formula is as follows:

[0119]

[0120] Among them, W′ i is the standard value of the factor; W i is the original value of the factor; is the factor average value; σ is the factor mean square error; the index value is the value corresponding to the regional environmental risk assessment index;

[0121] The standard values ​​of each indicator obtained after standardization are summed with weights to obtain the environmental risk receptor vulnerability score and pollution source risk score of each assessment unit. The environmental risk value of each assessment unit is calculated by multiplying the scores of the pollution source risk and environmental risk receptor vulnerability indicators and taking the square root.

[0122] The acquisition of each indicator value is achieved through GIS technology, and the spatial statistical analysis function of the GIS system is used to count all indicator layer information within the evaluation unit by superimposing the grid vector range and various basic quantity data, calculate the intersection between the two feature classes, and cross-tabulate the area, length or number of the intersecting elements.

[0123] In some embodiments, the processor 202 is further configured to: classify the quantified environmental risk value of each assessment unit, specifically including:

[0124] According to the numerical value of the comprehensive environmental risk value of the assessment unit, the regional environmental risk of the assessment unit is divided into three levels: high, relatively high, medium and low.

[0125] In some embodiments, the processor 202 is further configured to: spatially render the graded assessment units to obtain a regional environmental risk graded zoning map, specifically including:

[0126] After combining the graded assessment units with GIS technology to complete spatial rendering, a regional environmental risk classification zoning map is obtained.

[0127] The specific implementation method is referred to the aforementioned method embodiment and will not be described in detail here.

[0128] The present application may be a method, an apparatus, a system and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present application.

[0129] Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (non-exhaustive list) of computer readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination thereof. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0130] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0131] The computer program instructions for performing the operation of the present application can be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions can be executed completely on a user's computer, partially on a user's computer, executed as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet). In some embodiments, by using the state information of a computer-readable program instruction to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA) or a programmable logic array (PLA), the electronic circuit can execute a computer-readable program instruction, thereby realizing various aspects of the present application.

[0132] Various aspects of the present application are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0133] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0134] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0135] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the logical function of the specification. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can also be executed in the opposite order sometimes, depending on the function involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be realized by a dedicated hardware-based system that performs the function or action of the specification, or can be realized by a combination of special-purpose hardware and computer instructions.

[0136] Note that, unless otherwise directly stated, all features disclosed in this specification (including any attached claims, abstracts and drawings) may be replaced by alternative features for achieving the same, equivalent or similar purposes. Therefore, unless otherwise explicitly stated, each feature disclosed is only an example of a group of equivalent or similar features. Where used, further, preferably, further and more preferably are simple beginnings for elaborating another embodiment based on the aforementioned embodiment, and the content of the further, preferably, further or more preferably followed by the combination with the aforementioned embodiment constitutes a complete construction of another embodiment. Several further, preferably, further or more preferably settings following the same embodiment can be arbitrarily combined to form another embodiment.

[0137] Although the present application has been described in detail above with general descriptions and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements may be made to the present application. Therefore, these modifications or improvements made without departing from the spirit of the present application all fall within the scope of protection claimed in the present application.

Claims

1. A method for assessing regional environmental risk of heavy metals, characterized in that: The following steps are involved: The research area was selected and the assessment units were divided using a combination of administrative area boundaries and grid zoning; Establishing an evaluation index system, selecting regional environmental risk assessment indicators in the evaluation index system, and obtaining the indicator weights of the evaluation index system using a hierarchical analysis method; Combining the evaluation index system and index weights, obtaining the environmental risk value of the evaluation unit; Classifying the quantified environmental risk value of each assessment unit; The graded assessment units are spatially rendered to obtain a regional environmental risk classification zoning map.

2. The heavy metal regional environmental risk assessment method according to claim 1, characterized in that: The evaluation index system includes a two-level index system constructed from two aspects: the risk of regional environmental pollution sources and the vulnerability of regional environmental risk receptors. The two-level index system includes a primary index layer and a secondary index layer. The primary index layer includes two specific indicators: the risk of regional environmental pollution sources and the vulnerability of regional environmental risk receptors. The secondary indicator layer corresponding to the risk of regional environmental pollution sources includes: the number of regional heavy metal-related enterprises, the ratio of regional environmental risk material inventory to critical quantity, the number of regional environmental risk level enterprises above a high level, the number of environmental incidents in the region in the past five years, the number of regional tailings ponds, the total discharge of heavy metals in regional wastewater, the total discharge of heavy metals in regional waste gas, the amount of general solid waste generated in the region, and the amount of hazardous waste generated in the region; The secondary indicator layer corresponding to the vulnerability of the regional environmental risk receptor includes: regional population, regional population density, number of settlements in the region, regional cultivated land area, regional ecological red line range, drinking water source area in the region, water sensitivity in the region, and GDP per capita; The indicators of the secondary indicator layer are the selected regional environmental risk assessment indicators.

3. The heavy metal regional environmental risk assessment method according to claim 2, characterized in that: The method of using the analytic hierarchy process to obtain the indicator weights of the evaluation indicator system specifically includes: The entire evaluation index system is analyzed by the hierarchical analysis method, the target layer and the criterion layer are determined, and a hierarchical structure model is established to construct a judgment matrix. Combined with the Delphi method, the 1-9 scaling method of the TLSaaty hierarchical analysis is used to assign values ​​to the judgment matrix, and the eigenvector and the maximum eigenroot of the judgment matrix are calculated and a consistency test is performed. Finally, the indicator weight values ​​of the environmental risk assessment indicators of each region are obtained.

4. The heavy metal regional environmental risk assessment method according to claim 3, characterized in that: The judgment matrix is ​​shown as follows: Among them, the element A in the judgment matrix il Represents element A i For element A l The relative importance of the data is divided into five levels: equally important, slightly important, relatively important, very important, absolutely important, A i With A l Both represent one of the secondary indicators corresponding to one of the primary indicators, and k is 8 or 9.

5. The heavy metal regional environmental risk assessment method according to claim 3, characterized in that: The consistency check specifically includes: Use the consistency test formula to perform consistency test: Among them, CR is the matrix consistency test coefficient, CI is the matrix consistency compatibility index, RI is the average random consistency index, λmax is the maximum eigenvalue of the judgment matrix, n is the non-zero eigenvalue, and the smaller the CI value, the better the consistency of the judgment matrix.

6. The heavy metal regional environmental risk assessment method according to claim 2, characterized in that: The obtaining of the environmental risk value specifically includes: The index values ​​obtained by statistics of each evaluation unit are standardized, and the standardization formula is as follows: Among them, W′ i is the standard value of the factor; W i is the original value of the factor; is the factor average value; σ is the factor mean square error; the index value is the value corresponding to the regional environmental risk assessment index; The standard values ​​of each indicator obtained after standardization are summed with weights to obtain the environmental risk receptor vulnerability score and pollution source risk score of each assessment unit. The environmental risk value of each assessment unit is calculated by multiplying the scores of the pollution source risk and environmental risk receptor vulnerability indicators and taking the square root. The acquisition of each indicator value is achieved through GIS technology, and the spatial statistical analysis function of the GIS system is used to count all indicator layer information within the evaluation unit by superimposing the grid vector range and various basic quantity data, calculate the intersection between the two feature classes, and cross-tabulate the area, length or number of the intersecting elements.

7. The heavy metal regional environmental risk assessment method according to claim 2, characterized in that: The grading of the quantified environmental risk value of each assessment unit specifically includes: According to the numerical value of the comprehensive environmental risk value of the assessment unit, the regional environmental risk of the assessment unit is divided into three levels: high, relatively high, medium and low.

8. The method for heavy metal regional environmental risk assessment according to claim 2, characterized in that: The spatial rendering of the graded assessment units to obtain a regional environmental risk graded zoning map specifically includes: After combining the graded assessment units with GIS technology to complete spatial rendering, a regional environmental risk classification zoning map is obtained.

9. A heavy metal regional environmental risk assessment device, characterized in that: include: Memory; as well as A processor connected to the memory, the processor being configured to perform the steps of the method according to any one of claims 1 to 8.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a machine, the steps of the method according to any one of claims 1 to 8 are implemented.

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