Non-ferrous metal mine acid wastewater heavy metal discharge flux simulation and verification method based on material flow

Abstract

The invention discloses a nonferrous metal mine acid wastewater heavy metal discharge flux simulation and verification method based on material flow, belongs to the technical field of acid wastewater heavy metal discharge flux simulation, constructs a material flow model of the whole process of nonferrous metal mining acid wastewater migration, and comprises the links of mining, mineral separation, wastewater treatment and tailings. Determining the flow of the acid wastewater in each link and the input, output and storage conditions of heavy metals, and collecting the related parameters of the discharge flux of the heavy metals in the acid wastewater in each link, including the pipeline length, the pool body area and the wastewater heavy metal concentration in each process link; the method comprises the following steps: simulating the discharge flux of acid wastewater input into soil through a pipeline and a pool body, and establishing an acid wastewater heavy metal discharge flux verification system by using uncertainty of parameters and model errors in a Monte Carlo simulation model, including field monitoring, laboratory analysis and data space statistical analysis, and performing space interaction analysis.

Description

Technical Field

[0001] The present invention relates to a simulation of heavy metal emission flux of acidic wastewater, and in particular to a simulation and calibration method of heavy metal emission flux of acidic wastewater in nonferrous metal mines based on material flow, belonging to the technical field of heavy metal emission flux simulation of acidic wastewater. Background Art

[0002] With the rapid development of the nonferrous metals industry, acidic wastewater generated during mining and mineral processing has become a significant source of heavy metal pollution. Acidic wastewater generated during nonferrous metal mining and processing is characterized by large volumes, complex and variable pollutant components, and strong environmental mobility. To date, acidic wastewater has not been effectively managed and utilized, seriously hindering sustainable socioeconomic development and impacting scientific decision-making. Current technology for simulating heavy metal emission fluxes from acidic wastewater faces the following bottlenecks:

[0003] (1) Lack of quantification of the entire process: Traditional research focuses on the problem of heavy metals in a certain production link or specific process, and lacks a systematic quantitative study of the material migration of the entire process of "mining-ore dressing-wastewater treatment-tailings", resulting in an unclear material migration path.

[0004] (2) Insufficient process capture: Non-ferrous metal enterprises often use sampling monitoring, hidden danger investigation, spatial analysis, etc. to identify pollution nodes in the production process of enterprises, which makes it difficult to capture the results of process impact;

[0005] (3) Spatial correlation is broken: The spatial interaction between heavy metal discharge from acidic wastewater and heavy metal accumulation in soil has not been established, making it impossible to accurately locate pollution hotspots. Therefore, to address the above issues, the present invention proposes a system solution based on material flow. By constructing a full-process material flow model, developing an algorithm for simulating the discharge flux of heavy metals from acidic wastewater, and a spatial calibration method, this solution has important practical significance for achieving source control of heavy metal pollution. Summary of the Invention

[0006] The main purpose of the present invention is to provide a material flow-based method for simulating and verifying the heavy metal emission flux of acidic wastewater in non-ferrous metal mines.

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

[0008] A method for simulating and verifying heavy metal emission fluxes from acidic mine drainage in nonferrous metal mines based on material flow includes the following steps:

[0009] Step 1: Construct a material flow model for the entire migration process of acidic wastewater from non-ferrous metal mining and dressing, including mining, dressing, wastewater treatment, and tailings, and clarify the flow of acidic wastewater and the input, output, and storage of heavy metals in each link;

[0010] Step 2: Collect parameters related to heavy metal discharge flux of acidic wastewater in each link, including pipeline length, tank area, and heavy metal concentration of wastewater in each process link;

[0011] Step 3: Based on the material flow model and the collected parameters, simulate the discharge flux of acidic wastewater through pipes and tanks to the soil;

[0012] Step 4: Use Monte Carlo simulation to analyze the uncertainty of parameters and model errors in the model;

[0013] Step 5: Establish a heavy metal emission flux calibration system for acidic wastewater, including on-site monitoring, laboratory analysis, and data spatial statistical analysis, and conduct spatial interaction analysis.

[0014] Preferably, the step of constructing the material flow model specifically includes collecting production process flow, pollution emission information, wastewater treatment system operating parameters and climate rainfall data of non-ferrous metal enterprises;

[0015] Organize data, clarify process flow and sewage discharge nodes, and divide system boundaries and process units;

[0016] The amount of acid wastewater is calculated for each process unit, including the waste rock dump and stope, sewage treatment plant, concentrator, and tailings plant.

[0017] Preferably, the calculation formula for the amount of acidic wastewater generated in the waste rock dump and stope process units during the mining process in step 1 is:

[0018] AMW FC =S×R×L;

[0019] Among them, AMW FC The amount of acidic drainage generated from waste rock dumps and quarries;

[0020] S is the catchment area of ​​the stope or waste rock dump;

[0021] R is the rainfall intensity;

[0022] L is the comprehensive runoff coefficient.

[0023] Preferably, the formula for calculating the amount of wastewater discharged from the wastewater treatment plant process unit after treatment in step 1 is:

[0024] AMW R =AMW FC ×η;

[0025] AMW R For external wastewater, AMW FC is the acidic wastewater generated in the mining area and waste rock dump, and η is the wastewater treatment rate of the sewage treatment plant.

[0026] Preferably, in step 3, a pipeline and pool leakage emission model is established, and the calculation formula is:

[0027] D i,wastewater(pipe) =T×k i,wastewater(pipe) ×L pipe ×Qc×c i,wastewater ;

[0028] D i,wastewater(pond) =T×k i,wastewater(pond) ×S pond ×Qc×

[0029] c i,wastewater ;

[0030] Among them, D i,wastewater(pipe) and D i,wastewater(pond) are the amount of pollutants discharged into the soil through pipelines and tank leakage (g);

[0031] k i,wastewater(pipe) and k i,wastewater(pond) are the maximum leakage coefficients of the pipeline and the pool under normal working conditions respectively;

[0032] L pipe is the pipe length (m), S pond is the pool area (m 2 );

[0033] c i,wastewater is the heavy metal concentration in the acidic wastewater of each link (mg / L);

[0034] T is the running time (a);

[0035] Qc is the output of acidic wastewater in the production process (m 3 ).

[0036] Preferably, the running time T follows a uniform distribution, and the probability distributions of the pipeline length and the pool area are normal geometric distributions.

[0037] Preferably, the establishment of the acid wastewater heavy metal discharge flux calibration system in step 5 specifically includes:

[0038] Collect soil samples and analyze for total heavy metal content;

[0039] Use ArcGIS buffer tools to analyze the scope of pipeline and pool pollution;

[0040] The inverse distance weighted method was used to draw the soil heavy metal concentration distribution map;

[0041] Calculate the total amount of heavy metal pollution on the site using the following formula:

[0042] S = C × H × A × D;

[0043] Where S is the total amount of heavy metals in soil;

[0044] C is the heavy metal content;

[0045] H is the soil thickness;

[0046] A is the grid area;

[0047] D is the soil bulk density.

[0048] Preferably, in step 5, the spatial interaction analysis uses bivariate Moran index analysis, and the calculation formula is:

[0049]

[0050] In the formula, and are the heavy metal discharge fluxes of acidic wastewater and the total amount of heavy metals in soil for variables a and b at locations i and j, respectively;

[0051] Variables a and b represent the wastewater heavy metal discharge flux and total heavy metal values ​​within the grid, respectively;

[0052] w ij is the spatial weight matrix of locations i and j;

[0053] Calculated based on the Euclidean distance weights between locations i and j;

[0054] I ab The local Moran index representing the a-attribute at grid i and the b-attribute at grid j.

[0055] Preferably, the heavy metals include As and Cd, but are not limited to these two heavy metals.

[0056] Beneficial technical effects of the present invention:

[0057] The present invention provides a material flow-based method for simulating and verifying heavy metal emission fluxes from acidic mine drainage in non-ferrous metal mines. This full-process material flow perspective differs from traditional methods that focus on a single link (such as mining or wastewater treatment) and constructs a material input / output inventory for each link in the entire life cycle of a non-ferrous metal mining enterprise.

[0058] Construct a verification method for the spatial interaction relationship of "field monitoring-laboratory analysis-spatial statistical model". BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a flow chart of a preferred embodiment of a method for simulating and verifying heavy metal discharge flux of acidic non-ferrous metal mine drainage based on material flow according to the present invention;

[0060] Figure 2 A production process flow chart of a non-ferrous metal mining enterprise according to a preferred embodiment of a method for simulating and verifying heavy metal emission flux of acidic non-ferrous metal mine drainage based on material flow of the present invention;

[0061] Figure 3 A diagram of waste rock dump and stope process units according to a preferred embodiment of a material flow-based method for simulating and verifying heavy metal discharge fluxes of acidic nonferrous metal mine drainage according to the present invention;

[0062] Figure 4 A diagram of an acid reservoir process unit according to a preferred embodiment of a material flow-based method for simulating and verifying heavy metal discharge fluxes of acidic nonferrous metal mine drainage;

[0063] Figure 5 A unit diagram of a beneficiation plant process according to a preferred embodiment of a material flow-based method for simulating and verifying heavy metal discharge fluxes of acidic nonferrous metal mine drainage;

[0064] Figure 6 A process unit diagram of a fine tailings plant according to a preferred embodiment of a material flow-based simulation and verification method for heavy metal discharge flux of acidic nonferrous metal mine drainage according to the present invention;

[0065] Figure 7 This is a Monte Carlo simulation result diagram of a preferred embodiment of a method for simulating and verifying heavy metal discharge flux of acidic non-ferrous metal mine drainage based on material flow according to the present invention;

[0066] Figure 8 The diagram is a spatial quantitative expression of the heavy metal emission flux of wastewater leaking from pipelines and pools according to a preferred embodiment of a material flow-based simulation and verification method for heavy metal emission flux of acidic wastewater in non-ferrous metal mines of the present invention.

[0067] Figure 9 Schematic diagram of the spatial distribution of heavy metals As and Cd in soil according to a preferred embodiment of a method for simulating and verifying heavy metal emission fluxes of acidic non-ferrous metal mine drainage based on material flow of the present invention;

[0068] Figure 10 This is a schematic diagram of the spatial correlation between the heavy metal emission flux of acidic wastewater and the total amount of heavy metals in soil according to a preferred embodiment of a material flow-based simulation and verification method for heavy metal emission flux of acidic wastewater in non-ferrous metal mines of the present invention. DETAILED DESCRIPTION

[0069] In order to make the technical solution of the present invention more clear and specific to those skilled in the art, the present invention is further described in detail below with reference to embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0070] S1, based on mass balance, constructs a material flow model for the entire migration process of acidic wastewater in non-ferrous metal mining and dressing, including material flow models for mining, mineral processing, wastewater treatment, and tailings. This model clarifies the flow of acidic wastewater and the input, output, and storage of heavy metals in each link, enabling pollution identification throughout the entire process. Specifically, in the mining process, factors such as rainfall intensity, the area of ​​the mining site and waste rock dump, and the intensity of surface runoff are considered; in the mineral processing process, the process of re-purification of tailings and concentrate is analyzed; in the wastewater treatment process, the removal efficiency of heavy metals by the wastewater treatment process and the discharge destination are determined;

[0071] S2, collect and organize the relevant parameters of the heavy metal emission flux of acidic wastewater in each link, including pipeline length, tank area, and heavy metal concentration of wastewater in each process link; based on the material flow model, combined with the maximum allowable leakage of pipelines and tanks, estimate the emission flux of acidic wastewater through pipelines and tanks to the soil; use the uncertainty of parameters and model errors in the Monte Carlo simulation model to improve the reliability of model simulation results.

[0072] S3. To verify the accuracy of the simulation results, a calibration system for acidic wastewater heavy metal emission fluxes was established, encompassing field monitoring, laboratory analysis, and spatial statistical analysis of data. Specifically, soil heavy metal sampling points were set up, soil samples were collected, and the total amount of heavy metals was analyzed. Spatial interaction analysis was then conducted with the acidic wastewater heavy metal emission fluxes.

[0073] This method is suitable for quantitatively determining the heavy metal emission flux of acidic wastewater from non-ferrous metal mining and dressing enterprises, establishing the spatial correlation between production processes and on-site soil pollution, and providing a basic methodology and solution for shifting soil management from end-of-pipe treatment to source prevention and control.

[0074] Construct a material flow model for the entire life cycle of non-ferrous metal enterprises, identify pollution throughout the entire production process, and with quality conservation as the core, construct a material flow model including mining-ore dressing-wastewater treatment-tailings, and clarify the input and output migration paths of each process.

[0075] S11: Collect information on production processes and pollution discharge of non-ferrous metal enterprises;

[0076] The relevant information collected on non-ferrous metal mining and dressing enterprises mainly includes production process flow, pollution emission information, wastewater treatment system operating parameters, industrial activity information and other data information.

[0077] ① Production process flow: including the company's floor plan (production area, storage area, living area), the company's production process flow chart, the company's raw and auxiliary material usage, the intermediate process environmental material usage, the company's historical monitoring data, environmental impact assessment report, years of operation, etc.;

[0078] ② Pollution emission information: including acid wastewater discharge nodes, discharge node locations and discharge volumes, main discharge pathways, intermediate products and wastes, and main wastewater and solid waste discharge treatment;

[0079] ③Operating parameters of the wastewater treatment system, such as pH, redox potential and residence time;

[0080] ④ Climate and rainfall data: Collect rainfall intensity and surface runoff data in the areas where non-ferrous metal enterprises are located;

[0081] S12: Organize information and calculate the amount of wastewater at the discharge nodes of the production process;

[0082] Organize data, clarify process flow and sewage discharge nodes;

[0083] Organize the collected data and clarify the system boundaries of the research object, including key nodes such as production process flow, wastewater treatment units and discharge ports.

[0084] S13: Delineate system boundaries and process units;

[0085] It covers the entire process of mining-ore dressing-wastewater treatment-tailings, focuses on the nodes of process units, determines the input and output of acidic wastewater, and stores it in Excel in the form of data.

[0086] ① Waste rock dump and stope process unit;

[0087] This unit produces acidic wastewater, the input of which is precipitation and process spray dust suppression water, which enters the acidic water reservoir, and the output is acidic wastewater that enters the wastewater treatment plant.

[0088] The amount of acidic wastewater produced is calculated according to formula (1).

[0089] AMW FC =S×R×L (1);

[0090] Among them, AMW FC The amount of acidic wastewater generated in waste rock dumps and mines (m 3 );

[0091] S is the catchment area of ​​the quarry or waste rock dump (m 2 );

[0092] R is the rainfall intensity at the location of the nonferrous metal mining and dressing enterprise, calculated as 2700 mm / a;

[0093] L is the comprehensive runoff coefficient of the non-ferrous metal mining waste rock dump and the mining area, which is 0.7.

[0094] ②Sewage treatment plant process unit:

[0095] This unit mainly receives treated acidic wastewater from acidic reservoirs, with the input mainly coming from acidic reservoir wastewater and the output mainly being rivers and sperm tailings plants.

[0096] Acidic wastewater enters the river after being treated in sewage treatment plants (AMW R ) is calculated according to formula (2):

[0097] AMW R =AMW FC ×η (2);

[0098] In the formula, AMW R Indicates the wastewater discharged after treatment by the sewage treatment plant (m 3 );AMW FC Acidic wastewater from mining and waste rock dumps (m 3 ), η is the wastewater treatment rate of the sewage treatment plant (%).

[0099] ③ Plant selection process unit:

[0100] This process unit is mainly a mineral processing unit. Its input includes new water and tailings water reuse; its output includes acidic wastewater that enters the tailings plant with tailings and acidic wastewater that enters the tailings plant with concentrate.

[0101] The amount of new water used can be calculated using the mineral output and the water consumption coefficient, formula (3):

[0102]

[0103] In the formula, W x is the amount of new water (m 3 ), P C is the output of the mining and dressing plant (t), is the water consumption coefficient (m 3 / t).

[0104] The tailings water reuse amount is calculated using the tailings water volume and the reuse rate, formula (4);

[0105] WS w =W×α (4);

[0106] In the formula, W is the tailings water volume (m 3 ), α is the tail water reuse rate (%).

[0107] The amount of acidic wastewater in the form of concentrate to the tailings plant is calculated using formula (5):

[0108]

[0109] JS in the formula J Indicates the amount of acidic wastewater entering the concentrate tailings plant along with the concentrate (m 3 ), PJC represents the output of concentrate in the concentrator (t), It is the moisture content (%) in the concentrate of the concentrator.

[0110] It is sent to the tailings refinery in the form of tailings and is calculated using formula (6):

[0111] JS w =P w ×δ (6);

[0112] In the formula, JS w Indicates the acid wastewater from the concentrator entering the tailings plant along with the tailings (m 3 ), P w It represents the amount of tailings in the concentrator (t), and δ represents the moisture content of tailings in the concentrator (%).

[0113] ④ Process unit of the fine tailing plant;

[0114] This unit is mainly for tailings concentrating and wastewater treatment process, with inputs including new water, acidic wastewater from tailings of dressing plant and acidic wastewater from concentrate of dressing plant.

[0115] The new water is calculated by using the concentrate output and the water consumption coefficient, referring to formula (3).

[0116] The tailings from the dressing plant and the concentrate wastewater from the dressing plant are calculated using formula (5) and formula (6).

[0117] S14: Create a material flow list for the production process;

[0118] Based on the principle of conservation of mass, the input and output processes of acidic wastewater and pollutants in the production process units of non-ferrous metal mining and dressing enterprises are established. The amount of heavy metals is calculated based on basic data and sampling analysis and measurement data. The input and output lists of the process units are compiled, and the key nodes of pollution emissions are identified.

[0119] Table 1 List of input and output of acidic wastewater in non-ferrous metal mining and dressing enterprises;

[0120]

[0121]

[0122] Rainfall is (mm / a); others are (million m 3 / a)

[0123] S21: Collection and analysis of data related to heavy metal emission fluxes from acidic wastewater;

[0124] ① Collect relevant parameters of heavy metal emissions leaking through pipelines and pools;

[0125] Parameters related to heavy metal emissions from pipeline and pool leakage include the length of acid wastewater pipelines and pool area data of non-ferrous metal enterprises; information such as the operating time of non-ferrous metal enterprises, and the maximum leakage coefficient of pipelines and pools.

[0126] ② Collect and analyze the heavy metal content of acidic wastewater in test pipelines and pools;

[0127] The contents of heavy metals As and Cd in acidic wastewater were determined by on-site sampling and analysis.

[0128] Sampling points and sampling: Sampling points are set up at the pipeline outlet and at the top, middle and bottom of the tank body. Acidic wastewater is collected monthly. The pipeline uses online automatic sampling and the tank body uses portable samplers to collect water samples. Nitric acid is used to adjust the pH to prevent heavy metal adsorption or precipitation.

[0129] Analysis and treatment: The laboratory digests, heats, and adds acid to decompose the organic matter in the water sample, completely releasing the heavy metals into the solution. After filtration, the As and Cd contents in the supernatant are determined using ICP-MS.

[0130] Table 2 Heavy metal concentrations in acidic wastewater (μg / L);

[0131]

[0132]

[0133] L means below the detection limit;

[0134] S22: Establish pipeline and tank leakage emission models to simulate the heavy metal emission flux of acidic wastewater;

[0135] The impact of wastewater on soil heavy metals is divided into pipeline leakage and pool leakage. The calculation method refers to the "Code for Construction and Acceptance of Water Supply and Drainage Pipeline Engineering" (GB 50268-2008) and the "Code for Construction and Acceptance of Water Supply and Drainage Structure Engineering" (GB50141-2008). The heavy metal emissions from pipeline and pool leakage are calculated according to formulas (7) and (8):

[0136] D i,wastewater(pipe) =T×k i,wastewater(pipe) ×L pipe ×Qc×c i,wastewater (7);

[0138] D i,wastewater(pond) =T×k i,wastewater(pond) ×S pond ×Qc×

[0139] c i,wastewater (8);

[0140] Among them, Di,wastewater(pipe) and D i,wastewater(pond) are the amount of pollutants discharged into the soil through pipelines and tank leakage (g), k i,wastewater(pipe) and k i,wastewater(pond) are the maximum leakage coefficients of the pipeline and the pool under normal working conditions, L pipe is the pipe length (m), S pond is the pool area (m 2 ), c i,wastewater is the heavy metal concentration in the acidic wastewater of each link (mg / L), T is the operation time (a), Qc is the output of acidic wastewater in the production process (m 3 ).

[0141] Table 3. Leakage emission flux of pools in nonferrous metal mining areas (g / a);

[0142]

[0143]

[0144] Table 4. Leakage emission flux of pools in nonferrous metal mining areas (g / a);

[0145]

[0146]

[0147] S23: Uncertainty analysis of heavy metal emission fluxes from acidic wastewater leaks;

[0148] ① Set the probability distribution for parameters such as heavy metal concentration of acidic wastewater and operation time in the model.

[0149] Probability distribution of heavy metal concentrations in acidic wastewater;

[0150] By measuring the concentration of heavy metals in acidic wastewater in pipes and tanks The probability density function of heavy metal concentrations in acidic wastewater is a geometric normal distribution (Equations 9 and 10);

[0151]

[0152] where μ c and μ' c are the logarithmic mean values ​​of heavy metal concentrations in pipeline and pool acidic wastewater, and Represent the standard deviation of heavy metal concentrations in pipeline and pool acidic wastewater respectively.

[0153] The running time T obeys uniform distribution (uniform distribution), and its probability density function is:

[0154]

[0155] Other parameters k i,wastewater(pipe) and k i,wastewater(pond) is the certainty value; L pipe The probability distribution of pipeline length is geometric normal distribution, S pond The probability distribution of the pool area is geometric normal distribution;

[0156] ②Simulating model uncertainty in CrystalBall.

[0157] Define the hypothesis unit;

[0158] In Excel, the distribution type is established based on the acidic wastewater heavy metal concentration, operation time, pipe length and tank area;

[0159] Define the decision variable D i,wastewater(pipe) and D i,wastewater(pond) Set them as prediction units respectively and run formulas (7) and (8).

[0160] The number of simulations was set to 1000, and the probability density curve of the emission flux was finally obtained ( Figure 7 ), a comprehensive analysis of the emission flux simulation results was conducted to obtain a 95% confidence interval for the emission flux, thus realizing uncertainty analysis of heavy metal emissions from acidic wastewater.

[0161] S31: Spatial distribution of leakage in pipes and tanks;

[0162] The pollution range of pool and pipeline leakage is distributed within a 0.5m radius around the pool and pipeline. Therefore, the pollution range of pipeline and pool bodies was analyzed using the ArcGIS buffer tool. Based on the pipeline and pool bodies, a buffer zone with a width of 0.5m was established around each pipeline and pool body to demonstrate the spatial impact of the emission flux of heavy metals in the wastewater of pipelines and pools due to leakage.

[0163] S32: spatial interpolation of soil heavy metals at the enterprise scale;

[0164] ① Analysis of heavy metal content in soil at actual enterprise sites;

[0165] According to the Technical Guidelines for Investigation of Soil Pollution Status in Construction Land (HJ25.1-2019) and the Technical Guidelines for Risk Control and Remediation of Soil Pollution in Construction Land (HJ25.2-2019), the site was divided into a grid with a resolution of 100 × 100 m using a systematic point distribution method combined with the distribution of pipelines and tanks during the on-site investigation. Sampling points were set within the grid and soil samples were collected. Heavy metals in the soil were digested using HNO3-H2O2, and the heavy metal content in the soil was determined and analyzed using ICP-MS.

[0166] Heavy metals in nonferrous metal mining sites are generally pollution-free at a depth of about 6 m, so it can be assumed that all exogenous heavy metals in the soil are contained within a sampling depth of 6 m.

[0167] ②Inverse distance weighted interpolation analysis of total soil heavy metal content;

[0168] The heavy metal concentration distribution map was drawn using the inverse distance weighted method (IDW) in ArcGIS, and the search radius was set to 1.5 times the grid side length.

[0169] Based on the grid-scale heavy metal concentrations, the total amount of heavy metal pollution at the site was calculated using formula (9).

[0170] S = C × H × A × D (9);

[0171] In the formula, S is the total amount of heavy metals in the soil of nonferrous metal enterprises (kg), C is the heavy metal content at the grid scale (mg / kg), H is the soil thickness (6m), and A is the grid area (m 2 ), D is the soil bulk density (kg / m 3 ).

[0172] S33: Spatial correlation Moran's index analysis;

[0173] The bivariate Moran index analysis (Formula 10) was performed on the heavy metal emission flux caused by acid wastewater leakage and the total amount of heavy metals in the soil to analyze the spatial interaction between the two, and the spatial correlation result map was output in ArcGIS.

[0174]

[0175] In the formula, and Variables a and b represent the heavy metal discharge flux of acidic wastewater and the total amount of heavy metals in soil at locations i and j, respectively. Variables a and b represent the heavy metal discharge flux of wastewater and the total amount of heavy metals in the grid, respectively. w ij is the spatial weight matrix of position i and j, which is calculated based on the Euclidean distance weight of position i and j. ab The local Moran index represents the a attribute at grid i and the b attribute at grid j. ab When it is significantly positive, the wastewater heavy metal discharge flux at grid i has a significant local positive correlation with the total amount of soil heavy metals at grid j; when I ab When it is significantly negative, it is considered that the wastewater heavy metal discharge flux at grid i has a significant local negative correlation with the total amount of soil heavy metals at grid j; when I ab If it is not significant, it is considered that there is no obvious spatial interaction between the wastewater heavy metal discharge flux at grid i and the total amount of soil heavy metals at grid j.

[0176] The spatial interaction between heavy metal discharge fluxes from acidic wastewater and total heavy metal content in soils revealed that high-to-high Moran index clusters were primarily located in production areas, and that heavy metal discharges from acidic wastewater and total heavy metal content in soils were spatially consistent. This spatial analysis validated the practicality of the acidic wastewater heavy metal discharge flux model.

[0177] The present invention adopts a method for calculating the heavy metal emission flux of acidic wastewater in the whole process of material flow, and constructs the spatial interaction between the wastewater emission flux and the total distribution of heavy metals in soil by performing a bivariate local Moran index analysis on the obtained wastewater emission flux and the total amount of heavy metals in soil, and then verifies the emission flux, providing directional role and guidance for the soil pollution management work of non-ferrous metal enterprises.

[0178] The above is only a further embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes based on the technical solutions and concepts of the present invention within the scope disclosed by the present invention, which fall within the scope of protection of the present invention.

Claims

1. A material flow-based method for simulating and verifying heavy metal discharge fluxes from acidic nonferrous metal mine drainage, characterized by: The following steps are involved: Step 1: Construct a material flow model for the entire migration process of acidic wastewater from non-ferrous metal mining and dressing, including mining, dressing, wastewater treatment, and tailings, and clarify the flow of acidic wastewater and the input, output, and storage of heavy metals in each link; Step 2: Collect parameters related to heavy metal discharge flux of acidic wastewater in each link, including pipeline length, tank area, and heavy metal concentration of wastewater in each process link; Step 3: Based on the material flow model and the collected parameters, simulate the discharge flux of acidic wastewater through pipes and tanks to the soil; Step 4: Use Monte Carlo simulation to analyze the uncertainty of parameters and model errors in the model; Step 5: Establish a heavy metal emission flux calibration system for acidic wastewater, including on-site monitoring, laboratory analysis, and data spatial statistical analysis, and conduct spatial interaction analysis.

2. The method for simulating and verifying heavy metal discharge flux from acidic nonferrous metal mine drainage based on material flow according to claim 1, characterized in that: The construction of the material flow model specifically includes collecting the production process flow of non-ferrous metal enterprises, pollution emission information, wastewater treatment system operating parameters and climate and rainfall data; Organize data, clarify process flow and sewage discharge nodes, and divide system boundaries and process units; Calculate the amount of acid wastewater generated by each process unit, including the waste rock dump and stope, sewage treatment plant, concentrator, and tailings plant.

3. The method for simulating and verifying heavy metal discharge flux from acidic nonferrous metal mine drainage based on material flow according to claim 1, characterized in that: The calculation formula for the amount of acidic wastewater in the waste rock dump and stope process units is: AMW FC =S×R×L; Among them, AMW FC The amount of acidic drainage generated from waste rock dumps and quarries; S is the catchment area of ​​the stope or waste rock dump; R is the rainfall intensity; L is the comprehensive runoff coefficient.

4. The method for simulating and verifying heavy metal discharge flux from acidic nonferrous metal mine drainage based on material flow according to claim 1, characterized in that: The calculation formula for the amount of wastewater discharged from the process unit of the sewage treatment plant after treatment is: AMW R =AMW FC ×η; AMW R For external wastewater, AMW FC is the acidic wastewater generated in the mining area and waste rock dump, and η is the wastewater treatment rate of the sewage treatment plant.

5. The method for simulating and verifying heavy metal discharge flux from acid mine drainage in nonferrous metal mines based on material flow according to claim 1, characterized in that: Establish a pipeline and pool leakage emission model, and the calculation formula is: D i,wastewater(pipe) =T×k i,wastewater(pipe) ×L pipe ×Qc×c i,wastewater ; D i,wastewater(pond) =T×k i,wastewater(pond) ×S pond ×Qc× c i,wastewater ； Among them, D i,wastewater(pipe) and D i,wastewater(pond) are the amount of pollutants discharged into the soil through pipelines and tank leakage (g); k i,wastewater(pipe) and k i,wastewater(pond) are the maximum leakage coefficients of the pipeline and the pool under normal working conditions respectively; L pipe is the pipe length (m), S pond is the pool area (m 2 ); c i,wastewater is the heavy metal concentration in the acidic wastewater of each link (mg / L); T is the running time (a); Qc is the output of acidic wastewater in the production process (m 3 ).

6. The method for simulating and verifying heavy metal discharge flux from acidic nonferrous metal mine drainage based on material flow according to claim 1, characterized in that: The running time T follows a uniform distribution, and the probability distribution of the pipeline length and the pool area follows a geometric normal distribution.

7. The method for simulating and verifying heavy metal discharge flux from acid mine drainage in nonferrous metal mines based on material flow according to claim 1, characterized in that: The establishment of the acidic wastewater heavy metal discharge flux calibration system specifically includes: Collect soil samples and analyze for total heavy metal content; Use ArcGIS buffer tools to analyze the scope of pipeline and pool pollution; The inverse distance weighted method was used to draw the soil heavy metal concentration distribution map; Calculate the total amount of heavy metal pollution on the site using the following formula: S = C × H × A × D; Where S is the total amount of heavy metals in soil; C is the heavy metal content; H is the soil thickness; A is the grid area; D is the soil bulk density.

8. The method for simulating and verifying heavy metal discharge flux from acid mine drainage in nonferrous metal mines based on material flow according to claim 1, characterized in that: The spatial interaction analysis was performed using bivariate Moran's index analysis, and the calculation formula was: In the formula, and are the acidic wastewater heavy metal discharge fluxes and the total amount of heavy metals in soil for variables a and b at locations i and j, respectively; Variables a and b represent the wastewater heavy metal discharge flux and total heavy metal values ​​within the grid, respectively; w ij is the spatial weight matrix of locations i and j; Calculated based on the Euclidean distance weights between locations i and j; I ab The local Moran index representing the a-attribute at grid i and the b-attribute at grid j.

9. The method for simulating and verifying heavy metal discharge flux from acidic nonferrous metal mine drainage based on material flow according to claim 1, characterized in that: The heavy metals include As and Cd, but are not limited to these two heavy metals.

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