Polluted site environment risk assessment method

Abstract

The invention discloses a pollution site environment risk assessment method, which belongs to the technical field of pollution site environment risk assessment, and comprises the following steps: (1) standardizing a parameter system and constructing a scene library; (2) finite element numerical simulation; (2.1) geological modeling; (2.2) carrying out multi-physics field coupling solution; (2.3) optional coupling is carried out; and (3) dynamic risk assessment: converting dynamic data output by finite element simulation into a dynamic risk index, comprehensively reflecting the severity of the risk by integrating a plurality of indexes through the dynamic risk index, performing risk grade division based on the maximum value of the dynamic risk index DRI and the value or average value of a specific time point, constructing a risk grade discrimination table, and performing risk assessment to obtain a risk assessment result. And providing action suggestions. According to the method, the problem that the potential risk after the sudden environmental hazard event cannot be accurately predicted and efficiently coped due to the fact that an existing assessment method is insufficient in perspectiveness, predictability and scene dynamic simulation can be solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of contaminated site environmental risk assessment, and particularly relates to a contaminated site environmental risk assessment method. BACKGROUND

[0002] At present, a technical specification system represented by the Technical Guidelines for Risk Assessment of Soil Pollution in Construction Sites (HJ 25.3-2019) has been established in the field of contaminated site environmental risk assessment in China, which provides an important basis for site risk management and determination of remediation targets. However, with the refinement and complexity of environmental management requirements, the existing assessment methods gradually reveal their limitations in practical application, especially in terms of forward-looking, predictive and scenario dynamic simulation, which cannot meet the demand for accurate prediction and efficient response to potential risks after sudden environmental hazards.

[0003] Specifically, the defects of the prior art mainly lie in that the evaluation orientation focuses on static evaluation of the current situation, and lacks prediction simulation of sudden events. The core idea of the existing evaluation system is mostly based on the investigation and analysis of the current pollution status of the site, which is a kind of static evaluation for "fait accompli". The evaluation parameters are mainly based on historical data and current monitoring, and the evaluation model is mostly run under the assumption of steady state or quasi-steady state. This method cannot effectively simulate and predict the risk hazards caused by the dramatic changes in the boundary conditions of the contaminated site after the impact of sudden environmental hazards. SUMMARY

[0004] The purpose of the present application is to provide a contaminated site environmental risk assessment method, which solves the problems of insufficient forward-looking, predictive and scenario dynamic simulation of the existing assessment methods, and cannot accurately predict and efficiently respond to potential risks after sudden environmental hazards.

[0005] A contaminated site environmental risk assessment method, comprising the following steps: (1) Parameter system standardization and scenario library construction: Parameter standardization system: Collect and organize various parameters required for finite element simulation inherent to the site, including: geohydrological parameters, pollutant characteristic parameters, and receptor exposure parameters; Sudden scenario library construction: Define possible sudden events as driving conditions for simulation, including leakage scenarios, meteorological and hydrological scenarios, and engineering disturbance scenarios; (2) Finite element numerical simulation: (2.1) Geological modeling: Use the three-dimensional modeling function of the finite element software to construct a three-dimensional heterogeneous model that truly reflects the stratigraphic structure and hydrogeological conditions of the site based on the geohydrological parameters in step (1); (2.2) Multi-physical field coupling solution: Flow field simulation: First, solve the groundwater flow governing equation to simulate the groundwater flow field distribution under natural or scenario-driven conditions; Solute transport simulation: Coupled with the solution of the pollutant convection-dispersion-adsorption-degradation equation, the flow field results are used as input to dynamically predict the concentration distribution of pollutants in different scenarios over time and space; (2.3) Optional coupling: Coupling stress field as needed to achieve multi-field coupling analysis.

[0006] (3) Dynamic risk assessment: Convert the dynamic data output by the finite element simulation into a dynamic risk index, which comprehensively reflects the severity of the risk by integrating multiple indicators. Based on the maximum value, specific time point value, or average value of the dynamic risk index DRI, risk level classification is performed, a risk level discrimination table is constructed, risk assessment is performed, and action recommendations are provided.

[0007] Further, in step (1), the geohydrological parameters are used to construct an accurate geological model, including soil stratification, permeability coefficient, porosity, and specific yield; The pollutant characteristic parameters define the chemical behavior in solute transport simulation, including the degradation rate of pollutants in soil and water, adsorption coefficient, and solubility.

[0008] Further, in step (1), the leakage scenario is constructed by setting the leakage source location, leakage substance, leakage rate, and duration; The meteorological and hydrological scenario is specifically set as extreme rainfall intensity, flood water level, and drought period as the model boundary conditions; The engineering disturbance scenario is specifically to simulate the changes in hydrogeological conditions caused by construction around the site and groundwater exploitation.

[0009] Further, step (3) is specifically: (3.1) Core index definition and quantification: Four core indexes are extracted and defined from the finite element simulation results: C(t)-Receptor dynamic exposure concentration: Under a specific scenario, the average concentration of pollutants measured at a predetermined sensitive receptor location changes over time t; Qcumulative-Pollutant cumulative release / migration amount: From the occurrence of the incident to the assessment time point T, the total amount of pollutants released and migrated out of the source area from the pollution source, used to reflect the intensity of the pollution source and the overall load on the environment; Dmax-Maximum diffusion distance: The farthest distance from the center of the pollution source to the point where the concentration of pollutants exceeds the background value or a certain threshold, used to reflect the spatial influence range of the pollution plume; Thazard - Duration of hazardous concentration: The total duration of the pollutant concentration exceeding the specified limit at the sensitive receptor location, used to reflect the length of time the receptor is exposed to the hazardous environment; (3.2) Comprehensive dynamic risk index equation: A multi-index weighted summation model is constructed, and first, each index is normalized to eliminate the influence of dimension; (3.2.1) Index normalization: Each index is normalized to the interval [0, 1], where 1 represents the highest risk level; (3.2.2) Weighted summation to calculate the dynamic risk index DRI; (3.3) According to the maximum value of the calculated dynamic risk index DRI, the value or average value at a specific time point, risk level classification is carried out, a risk level discrimination table is constructed, risk assessment is carried out, and action suggestions are provided.

[0010] Further, in step (3.2.1), the index normalization specifically includes: Exposure concentration risk value (RC): RC(t) = min( C(t) / Cstandard, 1.0 ) Where: Cstandard is the selected standard concentration, and when the real-time concentration exceeds the standard, the risk value is capped at 1; Cumulative release quantity risk value (RQ): RQ = min( Qcumulative / Qthreshold, 1.0 ) Where: Qthreshold is the preset cumulative release quantity threshold, which is set according to the site size and pollutant toxicity, and is considered to be extremely high risk when it exceeds the threshold; Diffusion range risk value (RD): RD = min( Dmax / Dthreshold, 1.0 ) Where: Dthreshold is the preset diffusion distance threshold, i.e. the distance to the nearest sensitive receptor or the distance to the site boundary, and the closer or beyond the receptor the pollution plume is, the higher the risk value; Duration risk value (RT): RT = min( Thazard / Tsimulation, 1.0 ) Where: Tsimulation is the total simulation time. RT directly represents the proportion of time that the hazardous concentration lasts in the total simulation time.

[0011] Further, in step (3.2.2), the specific formula for calculating the dynamic risk index DRI by weighted summation is as follows: DRI(t) = wC * RC(t) + wQ * RQ + wD * RD + wT * RT Where: DRI(t) is the comprehensive dynamic risk index at time t, with a value range of [0, 1]; wC, wQ, wD, wT are the weighting coefficients corresponding to exposure concentration, cumulative release, diffusion range, and duration, respectively, and satisfy wC + wQ + wD + wT = 1.

[0012] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. Introduce a scenario-driven risk assessment model: By pre-setting various sudden environmental hazard event scenarios (such as different leakage amounts and different rainfall intensities), simulate and assess the risk level of the site at different future time points after a sudden environmental event, realize the leap from "post-event assessment" to "pre-event warning", provide forward-looking basis for risk warning and emergency decision-making, help managers identify the most dangerous scenarios and the most critical risk migration paths, thereby prioritizing the allocation of monitoring and protection resources and winning valuable time for emergency response.

[0013] 2. Shift from static assessment to dynamic prediction: Establish a new environmental risk assessment system driven by numerical simulation based on the finite element method. This system can accurately depict complex geological conditions and heterogeneity, and more realistically reflect the actual behavior of pollutants in the environment than traditional analytical models. This improves the reliability of assessment results and enables dynamic simulation and prediction of the migration and transformation processes of pollutants under complex geological conditions and sudden scenarios.

[0014] 3. Achieve comprehensive analysis through multi-physics coupling: Couple and simulate pollutant concentration fields, groundwater flow fields, soil stress fields, etc., to more realistically reflect the risk formation mechanism in complex environmental systems. Attached Figure Description

[0015] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0017] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0018] Refer to the instruction manual. Figure 1 , A method for environmental risk assessment of contaminated sites includes the following steps: (1) Standardization of parameter system and construction of scenario library Parameter standardization system: This system systematically collects and organizes various site-specific parameters required for finite element simulation, and categorizes them as follows: Geological and hydrological parameters: obtained through geological exploration and pumping tests, such as soil stratification, permeability coefficient, porosity, and specific yield, are used to construct accurate geological models.

[0019] Pollutant characteristic parameters, such as the degradation rate, adsorption coefficient (Kd), and solubility of pollutants in soil / water, are used to define the chemical behavior in solute transport simulations.

[0020] Receptor exposure parameters: refer to HJ 25.3, but allow them to change dynamically with the simulated scenario (such as simulating the scenario of recipient evacuation or return after a sudden event).

[0021] Constructing a database of contingency scenarios: This is crucial for improving static evaluation. A series of possible contingency events are defined as driving conditions for the simulation. Leakage scenario: Define the location of the leak source, the leaking substance, the leak rate, and the duration.

[0022] Meteorological and hydrological scenarios: set extreme rainfall intensity, flood level, drought cycle, etc. as boundary conditions for the model.

[0023] Engineering disturbance scenario: Simulates the changes in hydrogeological conditions caused by human activities such as construction and groundwater extraction around the site.

[0024] (2) Finite element numerical simulation (2.1) Geological modeling: Using the three-dimensional modeling function of finite element software (such as COMSOL Multiphysics, FEFLOW, visualMODFLOW, etc.), based on the geological and hydrological parameters in step (1), a three-dimensional heterogeneous model that can truly reflect the site's stratigraphic structure and hydrogeological conditions is constructed.

[0025] (2.2) Multiphysics coupling solution: Flow field simulation: First, solve the groundwater flow control equations (such as Darcy's law) to simulate the groundwater flow field distribution under natural or scenario-driven conditions (such as rainfall infiltration).

[0026] Solute transport simulation: Using flow field results as input, the convection-dispersion-adsorption-degradation equations of pollutants are coupled and solved to dynamically predict the changes in the concentration distribution of pollutants over time and space under different scenarios. This directly solves the problem that existing technologies cannot predict risk evolution.

[0027] (2.3) Optional coupling: When needed, stress fields (such as the effect of earthquakes on soil permeability) can also be coupled to achieve more complex multi-field coupling analysis.

[0028] (3) Dynamic risk assessment The dynamic data output from finite element simulation is transformed into a comprehensive and quantifiable Dynamic Risk Index (DRI). This index integrates multiple key indicators to comprehensively reflect the severity of the risk.

[0029] (3.1) Definition and quantification of core indicators First, we extract and define four core metrics from the finite element simulation results: C(t) - Receptor dynamic exposure concentration: The average concentration (mg / L or mg / kg) of pollutants measured at a preset sensitive receptor location (such as a drinking water well or a residential area) under a specific scenario, changing with time t.

[0030] Qcumulative - Cumulative Release / Migration of Pollutants: The total amount (kg) of pollutants released from the pollution source and migrated out of the source area from the occurrence of the incident to the assessment time point T. This reflects the intensity of the pollution source and its overall environmental impact.

[0031] Dmax - Maximum Distance of Dispersion: The farthest distance (in meters) from the center of the pollution source to where the pollutant concentration exceeds the background value or a specific threshold (such as the detection limit). This reflects the spatial extent of the pollution plume.

[0032] Thazard - Duration of Hazardous Concentration: The total duration (in days) during which contaminant concentrations at sensitive receptor sites exceed specific limits (such as preliminary remediation targets or water quality standards calculated based on HJ 25.3). This reflects the length of time the receptor is exposed to a hazardous environment.

[0033] (3.2) Comprehensive Dynamic Risk Index (DRI) Equation To comprehensively assess risk, we construct a multi-indicator weighted summation model. First, we need to normalize each indicator to eliminate the influence of dimensions.

[0034] (3.2.1): Indicator Normalization Each indicator is normalized to the range [0, 1], where 1 represents the highest risk level.

[0035] Exposure concentration risk value (RC): RC(t) = min( C(t) / Cstandard, 1.0 ) Note: Cstandard is the selected standard concentration, such as the site-specific risk control value calculated according to HJ 25.3 or the national environmental quality standard. When the real-time concentration exceeds the standard, the risk value is capped at 1.

[0036] Cumulative Release Risk Value (RQ): RQ = min( Qcumulative / Qthreshold, 1.0 ) Note: Qthreshold is a preset cumulative release threshold that can be set based on site size and pollutant toxicity. Exceeding this threshold is considered an extremely high risk.

[0037] Risk Value for Propagation Range (RD): RD = min( Dmax / Dthreshold, 1.0 ) Note: Dthreshold is a preset diffusion distance threshold, such as the distance to the nearest sensitive receptor or the distance to the site boundary. The closer the contamination plume is to or beyond the receptor, the higher the risk value.

[0038] Duration Risk Value (RT): RT = min(Thazard / Tsimulation, 1.0) Note: Tsimulation is the total simulation duration. RT directly represents the "percentage of time" during which the harmful concentration persists within the total simulation time.

[0039] (3.2.2): Calculate the dynamic risk index (DRI) using weighted summation. DRI(t) = wC * RC(t) + wQ * RQ + wD * RD + wT * RT Parameter description: DRI(t): The overall dynamic risk index at time t, with a range of [0, 1]. The larger the value, the higher the overall risk.

[0040] wC, wQ, wD, wT: These are the weight coefficients of the corresponding indicators, and they satisfy wC + wQ + wD + wT = 1.

[0041] Weighting principles: wC (exposure concentration) is usually given the highest weight because it is most directly related to receptor health.

[0042] wQ (cumulative release) and w_D (diffusion range) reflect the severity of pollution and spatial threat, with weights being secondary.

[0043] wT (duration) reflects the persistence of the risk.

[0044] Example weight allocation (can be adjusted according to management needs): wC = 0.4, wQ = 0.2, wD = 0.2, wT = 0.2.

[0045] (3.3) Risk Level Judgment Table Based on the calculated maximum DRI value, value at a specific time point, or average value, risk levels are classified, a risk level discrimination table is constructed, risk assessment is conducted, and action recommendations are provided, as shown in Table 1.

[0046] Table 1 The above description constitutes an embodiment of the present invention. The foregoing descriptions are preferred embodiments of the present invention. Unless there is a clear contradiction or a prerequisite for a particular preferred embodiment, the preferred embodiments can be arbitrarily combined and used. The embodiments and specific parameters described are merely for clearly illustrating the verification process of the invention and are not intended to limit the scope of patent protection of the present invention. The scope of patent protection of the present invention is still determined by its claims. Similarly, any equivalent structural changes made based on the description and drawings of the present invention should also be included within the scope of protection of the present invention.

Claims

1. A method for environmental risk assessment of contaminated sites, characterized in that, Includes the following steps: (1) Standardization of parameter system and construction of scenario library: Parameter standardization system: collect and organize various site-specific parameters required for finite element simulation, including: geological and hydrological parameters, pollutant characteristic parameters, and receptor exposure parameters; Emergency scenario database construction: Define possible emergencies as driving conditions for simulation, including leakage scenarios, meteorological and hydrological scenarios, and engineering disturbance scenarios; (2) Finite element numerical simulation: (2.1) Geological modeling: Using the three-dimensional modeling function of finite element software, based on the geological and hydrological parameters in step (1), a three-dimensional heterogeneous model that truly reflects the site's stratigraphic structure and hydrogeological conditions is constructed. (2.2) Multiphysics coupling solution: Flow field simulation: First, solve the groundwater flow control equations to simulate the groundwater flow field distribution under natural or scenario-driven conditions; Solute transport simulation: Using flow field results as input, the pollutant convection-dispersion-adsorption-degradation equation is solved in a coupled manner to dynamically predict the changes in pollutant concentration distribution over time and space under different scenarios; (2.3) Optional coupling: Couple the stress field as needed to achieve multi-field coupling analysis; (3) Dynamic risk assessment: The dynamic data output from the finite element simulation is transformed into a dynamic risk index. The dynamic risk index integrates multiple indicators to comprehensively reflect the severity of the risk. Based on the maximum value, value or average value of the dynamic risk index DRI at a specific time point, the risk level is classified, a risk level discrimination table is constructed, risk assessment is carried out, and action recommendations are provided.

2. The method for environmental risk assessment of a contaminated site according to claim 1, characterized in that, In step (1), geological and hydrological parameters are used to construct an accurate geological model, including soil stratification, permeability coefficient, porosity, and water yield. Pollutant characteristic parameters define the chemical behavior in solute transport simulations, including the degradation rate, adsorption coefficient, and solubility of pollutants in soil and water.

3. The environmental risk assessment method for contaminated sites according to claim 1, characterized in that, In step (1), the leakage scenario construction specifically involves setting the location of the leakage source, the leaking substance, the leakage rate, and the duration. The meteorological and hydrological scenarios are specifically set as extreme rainfall intensity, flood level, and drought period as boundary conditions for the model. The specific engineering disturbance scenario is: simulating the changes in hydrogeological conditions caused by construction around the site and groundwater extraction.

4. The environmental risk assessment method for contaminated sites according to claim 1, characterized in that, The specific steps (3) are as follows: (3.1) Definition and quantification of core indicators: Four core metrics are extracted and defined from the finite element simulation results: C(t) - Receptor dynamic exposure concentration: Under a specific scenario, the average concentration of pollutants measured at a preset sensitive receptor location as time t changes; Qcumulative - Cumulative release / migration of pollutants: The total amount of pollutants released from the pollution source and migrated out of the source area from the occurrence of the emergency to the assessment time point T, used to reflect the intensity of the pollution source and the overall environmental load; Dmax - Maximum Distance of Dispersion: The farthest distance from the center of the pollution source to where the pollutant concentration exceeds the background value or a specific threshold, used to reflect the spatial influence range of the pollution plume; Thazard - Duration of presence of hazardous concentration: The total duration for which the concentration of a contaminant exceeds a specific limit at a sensitive receptor site, reflecting the length of time the receptor is exposed to a hazardous environment; (3.2) Comprehensive dynamic risk index equation: To construct a multi-indicator weighted summation model, the indicators are first normalized to eliminate the influence of dimensions. (3.2.1) Indicator normalization: Each indicator is normalized to the interval [0, 1], where 1 represents the highest risk level; (3.2.2) Calculate the dynamic risk index (DRI) using a weighted summation method; (3.3) Based on the calculated maximum value, value or average value of the dynamic risk index DRI at a specific time point, classify the risk level, construct a risk level discrimination table, conduct risk assessment, and provide action recommendations.

5. The environmental risk assessment method for a contaminated site according to claim 4, characterized in that, In step (3.2.1), the index normalization specifically includes: Exposure concentration risk value (RC): RC(t) = min( C(t) / Cstandard, 1.0 ) Where: Cstandard is the selected standard concentration. When the real-time concentration exceeds the standard, the risk value is capped at 1. Cumulative release risk value (RQ): RQ = min( Qcumulative / Qthreshold, 1.0 ) Where: Qthreshold is a preset cumulative release threshold, set according to the site size and pollutant toxicity. Exceeding this threshold is considered to be extremely high risk. Risk value for diffusion range (RD): RD = min( Dmax / Dthreshold, 1.0 ) Where: Dthreshold is a preset diffusion distance threshold, that is, the distance to the nearest sensitive receptor or the distance to the site boundary. The closer the contamination plume is to or beyond the receptor, the higher the risk value. Durational risk value (RT): RT = min(Thazard / Tsimulation, 1.0) Where: Tsimulation is the total simulation duration, and RT directly represents the percentage of time during which the harmful concentration persists within the total simulation time.

6. The environmental risk assessment method for a contaminated site according to claim 4, characterized in that, In step (3.2.2), the specific formula for calculating the dynamic risk index DRI using weighted summation is as follows: DRI(t) = wC * RC(t) + wQ * RQ + wD * RD + wT * RT Where: DRI(t) is the comprehensive dynamic risk index at time t, with a value range of [0, 1]; wC, wQ, wD, wT are the weighting coefficients corresponding to exposure concentration, cumulative release, diffusion range, and duration, respectively, and satisfy wC + wQ + wD + wT = 1.

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