Yellow River basin multi-source coal-based solid waste environmental risk comprehensive assessment method
By constructing an environmental risk assessment method for coal-based solid waste in the Yellow River Basin, the problem of lack of regional specificity in existing technologies has been solved. This method enables quantitative assessment of the environmental risks of coal-based solid waste and identification of risk factors, supporting safe utilization and ecological protection.
Patent Information
- Application Number
- CN202511750801.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-26
- Publication Date
- 2026-02-24
AI Technical Summary
Existing technologies lack environmental risk assessment methods for coal-based solid waste in the Yellow River Basin, making it difficult to identify regionally specific risk factors and failing to accurately quantify multi-media migration patterns and long-term cumulative risks.
An environmental risk assessment method for multi-source coal-based solid waste in the Yellow River Basin was developed. By collecting samples and analyzing their physicochemical properties, the leaching concentrations and toxicity of heavy metals and harmful elements were determined. The potential ecological risk index method and toxicity response coefficient were combined to calculate single-factor and comprehensive potential ecological risk indices, determine relative toxicity weights, and achieve quantitative assessment and grade determination.
It significantly improves the accuracy of identifying key risk factors, systematically reflects the migration and transformation patterns of pollutants, and provides scientific evidence to support safe utilization and ecological protection.
Smart Images
Figure CN121563002A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of environmental risk assessment technology, and in particular relates to a comprehensive environmental risk assessment method for multi-source coal-based solid waste in the Yellow River Basin. Background Technology
[0002] The large-scale mining and utilization of coal resources is a crucial pillar of economic and social development in the Yellow River Basin. However, this has generated massive amounts of coal-based solid waste, including coal gangue, fly ash, and coal gasification slag. The stockpiling and disposal of these solid wastes can pose a series of environmental risks, particularly in the migration of heavy metals and harmful elements, water alkalization, and damage to soil ecological functions. Furthermore, the stockpiling or utilization of alkaline solid wastes such as fly ash and gasification slag can lead to an increase in the pH value of surrounding soil and water bodies, affecting microbial activity and normal plant growth. Improper disposal can also allow heavy metals to enter groundwater and soil through leachate, and the dispersion of fine particulate matter can cause air pollution, posing long-term potential risks to ecosystems and human health.
[0003] Current environmental risk assessments of coal-based solid waste in the Yellow River Basin have significant shortcomings: First, the Yellow River Basin has a large volume of solid waste with significant differences in composition, but existing assessment methods lack regional specificity and are difficult to identify key risk factors in different river sections and industrial layout areas; second, the basin is ecologically fragile and has scarce water resources, and the migration patterns and long-term accumulation risks of pollutants in the multi-media environment during the storage and utilization of solid waste are still unclear.
[0004] Therefore, there is an urgent need to establish a risk assessment methodology system for coal-based solid waste that is specifically applicable to the geographical and environmental characteristics of the Yellow River Basin, in order to accurately quantify regional environmental risks and grasp the spatial differentiation patterns. Summary of the Invention
[0005] To address the shortcomings of existing technologies, such as the lack of regionally targeted assessments of the environmental risks of coal-based solid waste in the Yellow River Basin, the difficulty in quantifying multi-media migration patterns, and the challenges in long-term cumulative risks, this invention aims to provide a method specifically applicable to the environmental risk assessment of coal-based solid waste in the Yellow River Basin. This method can identify key risk factors, achieve risk classification and zoning assessment, and provide a scientific basis for the safe management and control of large-scale utilization.
[0006] To achieve the above objectives, this invention provides a comprehensive environmental risk assessment method for multi-source coal-based solid waste in the Yellow River Basin, comprising: Samples of coal-based solid waste from the Yellow River Basin were collected and their physicochemical properties were analyzed to obtain the results. Based on the physicochemical property analysis results, the leaching concentration and toxicity content of heavy metals and harmful elements in the sample were determined under different environmental conditions. Based on the leaching concentration and toxicity content, the single-factor potential ecological risk index of each pollutant is calculated using the potential ecological risk index method and by introducing the toxicity response coefficient. Based on the single-factor potential ecological risk index, the comprehensive potential ecological risk index of the sample is calculated, and the relative toxicity weights of different heavy metals in the ecological context of the Yellow River Basin are determined. Based on the comprehensive potential ecological risk index and relative toxicity weight, and according to the preset risk level classification standards, the environmental risks of coal-based solid waste are quantitatively assessed and graded, and key risk factors and their spatial differentiation patterns are identified.
[0007] Preferably, the process of collecting and analyzing the physicochemical properties of coal-based solid waste samples from the Yellow River Basin to obtain the physicochemical property analysis results includes: Based on the industrial distribution characteristics of different sections of the Yellow River Basin, coal-based solid waste samples were collected; wherein, the coal-based solid waste samples include coal gangue, fly ash, and coal gasification slag; The physical properties and chemical composition of the coal-based solid waste samples were analyzed to obtain basic physicochemical characteristic data of the samples.
[0008] Preferably, the process of determining the leaching concentration and toxicity of heavy metals and harmful elements in a sample under different environmental conditions includes: Based on the simulation experiment scheme under different environmental conditions, the samples were subjected to leaching toxicity tests to obtain the leaching toxicity test results. Based on the leaching toxicity test results, the leaching concentration data of heavy metals and harmful elements are obtained; The toxicity response coefficients of each element were obtained based on the toxicity content determination method.
[0009] Preferably, the process of calculating the single-factor potential ecological risk index of each pollutant includes: Based on leaching concentration data, toxicity response coefficients, and ecological background reference values of the Yellow River Basin, the single-factor potential ecological risk index value for each pollutant was calculated using the single-factor potential ecological risk index calculation formula.
[0010] Preferably, the formula for the single-factor potential ecological risk index is as follows: in, The potential ecological risk index of a pollutant; i represents the i-th type of pollutant; Indicates the toxicity response coefficient of a pollutant; Indicates the measured concentration of pollutants in the environmental medium; This indicates the background reference value for pollutants.
[0011] Preferably, the process of calculating the comprehensive potential ecological risk index of the sample based on the single-factor potential ecological risk index includes: Based on the single-factor potential ecological risk index of all pollutants, the cumulative processing results are obtained by summing the results using the comprehensive potential ecological risk index calculation formula. Based on the accumulated processing results, the comprehensive potential ecological risk index of the sample is obtained.
[0012] Preferably, the formula for the comprehensive potential ecological risk index is as follows: in, The potential ecological risk index of a pollutant; i represents the i-th type of pollutant; Indicates the toxicity response coefficient of a pollutant; Indicates the measured concentration of pollutants in the environmental medium; RI represents the background reference value of pollutants; RI represents the comprehensive potential ecological risk index of multiple pollutants; n represents the number of pollutant types.
[0013] Preferably, the process of determining the relative toxicity weights of different heavy metals in the ecological context of the Yellow River Basin includes: Based on the ratio of the single-factor potential ecological risk index to the comprehensive potential ecological risk index of each pollutant, the relative toxicity weight of each pollutant is calculated using the relative toxicity weight calculation formula. The formula for the relative toxicity weight is as follows: in, This represents the relative toxicity weight of the i-th pollutant; RI represents the potential ecological risk index of pollutants; n represents the number of pollutant types; and i represents the i-th pollutant.
[0014] Preferably, the process of quantitatively assessing and classifying the environmental risks of coal-based solid waste includes: Based on the single-factor potential ecological risk index and the comprehensive potential ecological risk index, the comparison results were obtained by referring to the risk level classification threshold table. Based on the comparison results, the ecological risk level of each pollutant and the overall ecological risk level of the sample are determined.
[0015] Preferably, the process of identifying key risk factors and their spatial differentiation patterns includes: The pollutants are sorted according to their relative toxicity weight values to obtain the sorting results. Based on the ranking results, the pollutant with the highest relative toxicity weight was identified as the key risk factor. Based on the evaluation results of different sampling points, the spatial distribution characteristics of the key risk factors in the Yellow River Basin were analyzed to obtain the spatial differentiation pattern.
[0016] Compared with the prior art, the present invention has the following advantages and technical effects: This invention is the first to construct a method system for environmental risk assessment of coal-based solid waste specifically for the geographical and environmental characteristics of the Yellow River Basin. By combining the physicochemical properties of solid waste, the occurrence forms of heavy metals, and the migration data of multiple environmental media within the basin, it effectively overcomes the problem of lack of regional adaptability of existing general methods and significantly improves the accuracy of identifying key risk factors and determining risk levels.
[0017] This invention introduces the potential ecological risk index method and couples parameters such as toxicity response coefficient and relative toxicity weight to achieve quantitative calculation of single-factor and comprehensive potential ecological risks of various heavy metals and harmful elements. Simultaneously, based on the "source-pathway-receptor" framework, a multi-media monitoring index system is constructed, which can systematically reflect the migration and transformation patterns and long-term cumulative risks of pollutants in the atmosphere, water bodies, and soil.
[0018] This invention can not only quantitatively assess the level of environmental risk, but also clarify the hazard level and spatial differentiation pattern of different heavy metals by ranking their contribution rate to ecological risk. This provides a direct scientific basis for the differentiated, zoned, classified, safe management and large-scale utilization path selection of coal-based solid waste in the Yellow River Basin, and helps the coordinated development of the green transformation of the coal industry and the ecological protection of the basin. Attached Figure Description
[0019] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of the method flow according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the principle of the environmental risk classification and evaluation model for coal-based solid waste utilization according to an embodiment of the present invention. Detailed Implementation
[0020] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.
[0021] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.
[0022] like Figure 1 As shown in this embodiment, a comprehensive environmental risk assessment method for multi-source coal-based solid waste in the Yellow River Basin is provided, including: Samples of coal-based solid waste from the Yellow River Basin were collected and their physicochemical properties were analyzed to obtain the results. Based on the physicochemical property analysis results, the leaching concentration and toxicity content of heavy metals and harmful elements in the sample were determined under different environmental conditions. Based on leaching concentration and toxicity content, and using the potential ecological risk index method with the introduction of toxicity response coefficient, the single-factor potential ecological risk index of each pollutant is calculated. Based on the single-factor potential ecological risk index, the comprehensive potential ecological risk index of the sample was calculated, and the relative toxicity weights of different heavy metals in the ecological context of the Yellow River Basin were determined. Based on the comprehensive potential ecological risk index and relative toxicity weight, and according to the preset risk level classification standards, the environmental risks of coal-based solid waste are quantitatively assessed and classified, and key risk factors and their spatial differentiation patterns are identified.
[0023] Furthermore, the process of collecting and analyzing the physicochemical properties of coal-based solid waste samples from the Yellow River Basin, and obtaining the results of the physicochemical property analysis, includes: Based on the industrial distribution characteristics of different sections of the Yellow River Basin, coal-based solid waste samples were collected; among them, coal-based solid waste samples included coal gangue, fly ash, and coal gasification slag. The physical properties and chemical composition of coal-based solid waste samples were analyzed to obtain basic physicochemical characteristic data of the samples.
[0024] Furthermore, the process of determining the leaching concentration and toxicity of heavy metals and harmful elements in the sample under different environmental conditions includes: Based on the simulation experiment scheme under different environmental conditions, the samples were subjected to leaching toxicity tests to obtain the leaching toxicity test results. Based on the leaching toxicity test results, the leaching concentration data of heavy metals and harmful elements were obtained; The toxicity response coefficients of each element were obtained based on the toxicity content determination method.
[0025] Furthermore, the process of calculating the single-factor potential ecological risk index for each pollutant includes: Based on leaching concentration data, toxicity response coefficients, and ecological background reference values of the Yellow River Basin, the single-factor potential ecological risk index value for each pollutant was calculated using the single-factor potential ecological risk index calculation formula.
[0026] Furthermore, the formula for the single-factor potential ecological risk index is as follows: in, The potential ecological risk index of a pollutant; i represents the i-th type of pollutant; Indicates the toxicity response coefficient of a pollutant; Indicates the measured concentration of pollutants in the environmental medium; This indicates the background reference value for pollutants.
[0027] Furthermore, the process of calculating the comprehensive potential ecological risk index of the sample based on the single-factor potential ecological risk index includes: Based on the single-factor potential ecological risk index of all pollutants, the cumulative processing results are obtained by summing the results using the comprehensive potential ecological risk index calculation formula. Based on the cumulative processing results, the comprehensive potential ecological risk index of the sample is obtained.
[0028] Furthermore, the formula for the comprehensive potential ecological risk index is as follows: in, The potential ecological risk index of a pollutant; i represents the i-th type of pollutant; Indicates the toxicity response coefficient of a pollutant; Indicates the measured concentration of pollutants in the environmental medium; RI represents the background reference value of pollutants; RI represents the comprehensive potential ecological risk index of multiple pollutants; n represents the number of pollutant types.
[0029] Furthermore, the process of determining the relative toxicity weights of different heavy metals in the ecological context of the Yellow River Basin includes: Based on the ratio of the single-factor potential ecological risk index to the comprehensive potential ecological risk index of each pollutant, the relative toxicity weight of each pollutant is calculated using the relative toxicity weight calculation formula. The formula for the relative toxicity weight is as follows: in, This represents the relative toxicity weight of the i-th pollutant; RI represents the potential ecological risk index of pollutants; n represents the number of pollutant types; and i represents the i-th pollutant.
[0030] Furthermore, the process of quantitatively assessing and classifying the environmental risks of coal-based solid waste includes: Based on the single-factor potential ecological risk index and the comprehensive potential ecological risk index, the comparison results were obtained by referring to the risk level classification threshold table. Based on the comparison results, the ecological risk level of each pollutant and the comprehensive ecological risk level of the sample were determined.
[0031] Furthermore, the process of identifying key risk factors and their spatial differentiation patterns includes: The pollutants are sorted according to their relative toxicity weight values to obtain the sorting results. Based on the ranking results, the pollutant with the highest relative toxicity weight was identified as the key risk factor. Based on the assessment results of different sampling points, the spatial distribution characteristics of key risk factors in the Yellow River Basin were analyzed to obtain spatial differentiation patterns.
[0032] As a preferred implementation method, this embodiment provides a comprehensive environmental risk assessment method for multi-source coal-based solid waste in the Yellow River Basin, aiming to address the problems of existing assessment methods lacking regional specificity and difficulty in accurately identifying key risk factors under the specific environmental background of the Yellow River Basin. This invention constructs a systematic risk assessment process. First, it collects and analyzes the physicochemical properties of coal-based solid waste samples from the Yellow River Basin, then determines the leaching concentration and toxicity content of heavy metals and harmful elements under different environmental conditions. Based on the core principle of the potential ecological risk index method, it introduces a toxicity response coefficient to calculate the single-factor potential ecological risk index of each pollutant and the comprehensive potential ecological risk index of the samples. On this basis, it determines the relative toxicity weight of different heavy metals under the ecological background of the Yellow River Basin, and achieves quantitative assessment and level determination of the environmental risk of coal-based solid waste according to a preset risk level classification standard. This method can effectively identify key risk factors and their spatial differentiation patterns, providing a scientific basis for the large-scale safe utilization and regional ecological protection of coal-based solid waste in the Yellow River Basin. Specifically, it includes the following steps: Step S1: Collect coal-based solid waste samples from the Yellow River Basin and analyze their physicochemical properties.
[0033] Step S2: Using experimental testing methods, the leaching concentration and toxicity levels of heavy metals and harmful elements in the samples under different environmental conditions were determined, and the heavy metal content of the four coal-based solid wastes was obtained, as shown in Table 1 below: Table 1
[0034] Substitute the heavy metal content data in Table 1 into step S3 to calculate the single-factor potential ecological risk index of each pollutant.
[0035] Step S3: Based on the core principle of the potential ecological risk index method, the toxicity response coefficient of heavy metals is introduced, and the single-factor potential ecological risk index of each pollutant is calculated according to the formula.
[0036] Furthermore, the formula for calculating the single-factor potential ecological risk index of each pollutant in step S3 is as follows: in The potential ecological risk index of a pollutant; i represents the i-th type of pollutant; Indicates the toxicity response coefficient of a pollutant; Indicates the measured concentration of pollutants in the environmental medium; Indicates the background reference value for pollutants; Specifically, in step S3, the single-factor potential ecological risk index of each pollutant is obtained, as shown in Table 2 below: Table 2
[0037] Substitute the heavy metal content data from Table 2 into step S4 to calculate the comprehensive potential ecological risk index of the sample.
[0038] Step S4: Based on the results of steps S2 and S3, calculate the comprehensive potential ecological risk index of the sample using a formula, determine the relative toxicity weights of different heavy metals in the ecological context of the Yellow River Basin, and quantitatively assess and classify the environmental risks of coal-based solid waste according to the preset risk level classification standards, identifying key risk factors and their spatial differentiation patterns.
[0039] Furthermore, the formula for calculating the comprehensive potential ecological risk index of the sample in step S4 is as follows: in The potential ecological risk index of a pollutant; i represents the i-th type of pollutant; Indicates the toxicity response coefficient of a pollutant; Indicates the measured concentration of pollutants in the environmental medium; RI represents the background reference value of pollutants; RI represents the comprehensive potential ecological risk index of multiple pollutants; n represents the number of pollutant types.
[0040] Specifically, in step S4, the comprehensive potential ecological risk index of four types of coal-based solid waste is obtained: coal gangue is 541.17, coal gasification ash is 427.12, fly ash is 473.18, and slag is 571.17.
[0041] Substitute the comprehensive potential ecological risk index of the four coal-based solid wastes into step S4 to calculate the relative toxicity weight of different heavy metals under the ecological background of the Yellow River Basin.
[0042] Furthermore, the formula for determining the relative toxicity weights of different heavy metals in the ecological context of the Yellow River Basin in step S4 is as follows: in This represents the relative toxicity weight of the i-th pollutant; RI represents the potential ecological risk index of pollutants; n represents the number of pollutant types; and i represents the i-th pollutant.
[0043] Specifically, the relative toxicity weights of different heavy metals obtained in step S4 under the ecological background of the Yellow River Basin are shown in Table 3 below: Table 3
[0044] Furthermore, in steps S3 and S4, the potential ecological risk indices of different heavy metal single factors and the comprehensive potential ecological risk index are substituted into the Hakanson (1980) potential ecological risk assessment and grading standard to conduct an environmental and ecological risk assessment of coal-based solid waste in the Yellow River Basin.
[0045] Furthermore, the ecological risk contribution rates of different heavy metal elements in the coal-based solid waste environmental and ecological risk assessment of the Yellow River Basin were ranked, and the ecological hazard levels were classified to identify the heavy metal elements with the highest contribution rates.
[0046] Specifically, in this embodiment, the relative toxicity weights of different heavy metals obtained in step S4 under the ecological background of the Yellow River Basin are ranked, and combined with the Hakanson (1980) potential ecological risk assessment classification standard to obtain the ecological risk level of each coal-based solid waste. The Hakanson (1980) potential ecological risk assessment classification standard is shown in Table 4 below: Table 4
[0047] In step S4, the following results were obtained: The single-factor potential ecological risk indices for Hg and As in coal gangue were the highest, reaching 412.31 and 103.05 respectively, belonging to Level V (extremely strong ecological hazard) and Level IV (strong ecological hazard) levels; the remaining elements were all below 40, belonging to the level of slight ecological hazard. The ecological risk contribution rate of each heavy metal was ranked as Hg>As>Cu>Pb>Ni>Zn>Cr, with Hg having the highest contribution rate at 76.19%. The comprehensive potential ecological risk index (RI) of coal gangue was 541.17, placing it at the level of Level IV (strong ecological hazard). The single-element potential risk index values for Hg and As in coal gasification ash were 332.31 and 86.32 respectively, belonging to Level V (extremely strong ecological hazard) and Level IV (strong ecological hazard) levels; the remaining elements were all at the level of slight ecological hazard. The ecological risk contribution rate of heavy metals was ranked as Hg>As>Cu>Ni>Cr>Zn>Pb, with Hg contributing 77.80%. The RI value of coal gasification ash residue is 427.12, placing it at a Level IV severe ecological hazard level. The single-element potential risk indices of Hg and As in fly ash are 369.23 and 77.22, respectively, belonging to Level V extremely severe ecological hazard and Level IV severe ecological hazard levels; the remaining elements are all considered minor ecological hazards. The ecological risk contribution rate of each element is ranked as follows: Hg > As > Cu > Ni > Pb > Cr > Zn, with Hg contributing 78.03%. The RI value of fly ash is 473.18, placing it at a Level IV severe ecological hazard level. The single-element potential risk index values of As and Hg in slag are 262.78 and 258.46, respectively, both at a Level IV severe ecological hazard level; the remaining elements are all considered minor ecological hazards. The ecological risk contribution rate of heavy metals is ranked as follows: As > Hg > Zn > Cu > Pb > Ni > Cr, with As having the highest contribution rate at 46.01%. The RI value of the slag is 571.17, which is also at the level of Level IV, a severe ecological hazard.
[0048] This invention, through the specific embodiments described above, achieves a quantitative and systematic assessment of the environmental risks of coal-based solid waste in the Yellow River Basin. This method fully considers the geographical and environmental characteristics of the basin, accurately identifies key risk factors, and reveals their spatial differentiation patterns, providing reliable technical support for the safe utilization and ecological protection of coal-based solid waste in the Yellow River Basin. Those skilled in the art can make appropriate adjustments to the above embodiments without departing from the principles of this invention to adapt to the application needs of different scenarios.
[0049] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A comprehensive environmental risk assessment method for multi-source coal-based solid waste in the Yellow River Basin, characterized in that, include: Samples of coal-based solid waste from the Yellow River Basin were collected and their physicochemical properties were analyzed to obtain the results. Based on the physicochemical property analysis results, the leaching concentration and toxicity content of heavy metals and harmful elements in the sample were determined under different environmental conditions. Based on the leaching concentration and toxicity content, the single-factor potential ecological risk index of each pollutant is calculated using the potential ecological risk index method and by introducing the toxicity response coefficient. Based on the single-factor potential ecological risk index, the comprehensive potential ecological risk index of the sample is calculated, and the relative toxicity weights of different heavy metals in the ecological context of the Yellow River Basin are determined. Based on the comprehensive potential ecological risk index and relative toxicity weight, and according to the preset risk level classification standards, the environmental risks of coal-based solid waste are quantitatively assessed and graded, and key risk factors and their spatial differentiation patterns are identified.
2. The method according to claim 1, characterized in that, The process of collecting and analyzing the physicochemical properties of coal-based solid waste samples from the Yellow River Basin, and obtaining the results of the physicochemical property analysis, includes: Based on the industrial distribution characteristics of different sections of the Yellow River Basin, coal-based solid waste samples were collected; wherein, the coal-based solid waste samples include coal gangue, fly ash, and coal gasification slag; The physical properties and chemical composition of the coal-based solid waste samples were analyzed to obtain basic physicochemical characteristic data of the samples.
3. The method according to claim 1, characterized in that, The process of determining the leaching concentration and toxicity of heavy metals and harmful elements in samples under different environmental conditions includes: Based on the simulation experiment scheme under different environmental conditions, the samples were subjected to leaching toxicity tests to obtain the leaching toxicity test results. Based on the leaching toxicity test results, the leaching concentration data of heavy metals and harmful elements are obtained; The toxicity response coefficients of each element were obtained based on the toxicity content determination method.
4. The method according to claim 1, characterized in that, The process of calculating the single-factor potential ecological risk index for each pollutant includes: Based on leaching concentration data, toxicity response coefficients, and ecological background reference values of the Yellow River Basin, the single-factor potential ecological risk index value for each pollutant was calculated using the single-factor potential ecological risk index calculation formula.
5. The method according to claim 4, characterized in that, The formula for the single-factor potential ecological risk index is as follows: in, The potential ecological risk index of a pollutant; i represents the i-th type of pollutant; Indicates the toxicity response coefficient of a pollutant; Indicates the measured concentration of pollutants in the environmental medium; This indicates the background reference value for pollutants.
6. The method according to claim 1, characterized in that, The process of calculating the comprehensive potential ecological risk index of the sample based on the single-factor potential ecological risk index includes: Based on the single-factor potential ecological risk index of all pollutants, the cumulative processing results are obtained by summing the results using the comprehensive potential ecological risk index calculation formula. Based on the accumulated processing results, the comprehensive potential ecological risk index of the sample is obtained.
7. The method according to claim 6, characterized in that, The formula for the comprehensive potential ecological risk index is as follows: in, The potential ecological risk index of a pollutant; i represents the i-th type of pollutant; Indicates the toxicity response coefficient of a pollutant; Indicates the measured concentration of pollutants in the environmental medium; RI represents the background reference value of pollutants; RI represents the comprehensive potential ecological risk index of multiple pollutants; n represents the number of pollutant types.
8. The method according to claim 1, characterized in that, The process of determining the relative toxicity weights of different heavy metals in the ecological context of the Yellow River Basin includes: Based on the ratio of the single-factor potential ecological risk index to the comprehensive potential ecological risk index of each pollutant, the relative toxicity weight of each pollutant is calculated using the relative toxicity weight calculation formula. The formula for the relative toxicity weight is as follows: in, This represents the relative toxicity weight of the i-th pollutant; RI represents the potential ecological risk index of pollutants; n represents the number of pollutant types; and i represents the i-th pollutant.
9. The method according to claim 1, characterized in that, The process of quantitatively assessing and classifying the environmental risks of coal-based solid waste includes: Based on the single-factor potential ecological risk index and the comprehensive potential ecological risk index, the comparison results were obtained by referring to the risk level classification threshold table. Based on the comparison results, the ecological risk level of each pollutant and the overall ecological risk level of the sample are determined.
10. The method according to claim 1, characterized in that, The process of identifying key risk factors and their spatial differentiation patterns includes: The pollutants are sorted according to their relative toxicity weight values to obtain the sorting results. Based on the ranking results, the pollutant with the highest relative toxicity weight was identified as the key risk factor. Based on the evaluation results of different sampling points, the spatial distribution characteristics of the key risk factors in the Yellow River Basin were analyzed to obtain the spatial differentiation pattern.