Quantification method for the value of soil and groundwater ecological environment damage with natural attenuation monitoring as the restoration plan

Abstract

The present invention discloses a method for quantifying the value of ecological environment damage to soil and groundwater with monitored natural attenuation as the restoration plan. By establishing numerical simulation models for monitored natural attenuation and enhanced natural attenuation, exploring the restoration laws and effects of contaminated soil and groundwater under natural conditions and different enhancement measures, and obtaining a model input sample set; based on the model input sample set, randomly sampling to obtain multiple groups of model input sample data, conducting simulation predictions of natural attenuation under different enhancement measures, and constructing prediction models for monitored natural attenuation and enhanced natural attenuation; coupling the theoretical treatment cost method and the resource value method, conducting optimization analysis on the costs of monitored natural attenuation, enhanced natural attenuation, and interim damage based on a multi-objective optimization model, and selecting the monitored natural attenuation and enhanced natural attenuation plan with the lowest total cost. The present invention solves the problem that it is difficult to quantitatively determine the damage value with monitored and enhanced natural attenuation as the restoration plan.

Description

Technical Field

[0001] The present invention relates to the technical field of quantifying the value of ecological environment damage to soil and groundwater, and particularly to a method for quantifying the value of ecological environment damage to soil and groundwater with monitored natural attenuation as the restoration plan. Background Art

[0002] Soil and groundwater play an important role in aspects such as social development, resource utilization, and ecological environmental protection. Quantifying the damage value based on the restoration plan is one of the keys to the control and remediation of soil and groundwater. The treatment and remediation of soil and groundwater pollution in operating enterprises have its particularity and difficulty. Long-term strong disturbance construction on the ground may affect the normal production of enterprises, and phenomena such as pollution rebound are likely to occur after treatment and remediation. The monitored natural attenuation technology reduces the content of pollutants in soil and groundwater to an acceptable risk level through the implementation of a planned monitoring program and strengthening measures, relying on the physical, chemical, and biological effects that occur naturally on the site. Based on the development trend of future low-carbon remediation technologies and the good application prospects for the remediation of operating enterprises, quantifying the value of ecological environment damage to soil and groundwater with monitored natural attenuation as the restoration plan is of great importance. Currently, the methods for quantifying the value of ecological environment damage to soil and groundwater in China are mainly applicable to short-term recoverable plans or long-term non-recoverable plans, focusing on single basic damage quantification or single-period damage quantification. However, the monitored natural attenuation technology has a large span of recovery period, the strengthening measures are not unique, and the degree of damage is difficult to quantify. Therefore, simple value quantification methods cannot meet the calculation requirements.

[0003] Therefore, aiming at problems such as the long period of quantifying the value of ecological environment damage to soil and groundwater in the monitored natural attenuation plan and the unclear calculation method, based on a multi-objective optimization model, coupling the theoretical treatment cost and the calculation method of the period damage cost, a method for quantifying the value of ecological environment damage to soil and groundwater with monitored natural attenuation as the restoration plan is proposed to realize the selection of the monitored natural attenuation and strengthening plan with the lowest total cost under the condition of meeting the human health risk standard, which is one of the important research trends in the technical field of quantifying the value of ecological environment damage to soil and groundwater. Summary of the Invention

[0004] The purpose of the present invention is to propose a method for quantifying the value of ecological environment damage to soil and groundwater with monitored natural attenuation as the restoration plan, which can optimize the selection of the monitored natural attenuation and strengthening plan for the polluted site and find a restoration plan with the lowest total cost under the constraint condition of meeting the human health risk standard.

[0005] To achieve the above object, the technical solution of the present invention is as follows:

[0006] The present invention provides a method for quantifying the value of ecological environment damage to soil and groundwater with monitored natural attenuation as the restoration plan, including the following steps:

[0007] By establishing numerical simulation models of natural attenuation and enhanced natural attenuation, explore the restoration laws and effects of contaminated soil and groundwater under natural conditions and different enhancement measures, and obtain the model input sample set;

[0008] Use the Monte Carlo method for random sampling to obtain multiple sets of model input sample data, and adopt the neural network method to simulate the pollutant migration under different enhancement measures, and construct a natural attenuation monitoring and enhanced natural attenuation prediction model;

[0009] Couple the calculation methods of theoretical treatment cost and interim damage cost, and construct a multi-objective optimization model with the lowest monitoring and enhanced natural attenuation damage cost as the goal and the pollutant concentration reduced below the maximum acceptable risk to human health at the end of the restoration period as the constraint condition;

[0010] Based on the multi-objective optimization model, conduct an optimization analysis of the natural attenuation monitoring cost, enhanced natural attenuation cost, and interim damage cost, and obtain the natural attenuation monitoring and enhanced natural attenuation plan with the lowest total cost.

[0011] Furthermore, in the present invention, by establishing numerical simulation models of natural attenuation and enhanced natural attenuation, explore the restoration laws and effects of contaminated soil and groundwater under natural conditions and different enhancement measures, and obtain the model input sample set, specifically including:

[0012] Investigate the current situation of natural attenuation of soil and groundwater in the contaminated site, including indicators such as pollutant concentration, geochemical parameters, and hydrogeological conditions, as the constant parameters input into the numerical simulation model;

[0013] Set different degrees of enhanced natural attenuation measures as the model input variables, construct a numerical simulation model of natural attenuation of soil and groundwater, and simulate the changes in the scope and degree of pollution and diffusion at different times.

[0014] Furthermore, in the present invention, use the Monte Carlo method for random sampling to obtain multiple sets of model input sample data, and adopt the neural network method to simulate the pollutant migration under different enhancement measures, and construct a natural attenuation monitoring and enhanced natural attenuation prediction model, specifically including:

[0015] Use the Monte Carlo random sampling method to extract sample data, input the obtained sample data into the numerical simulation model, and obtain multiple sets of input and output sample data as the training and test data sets for the neural network method;

[0016] Adopt the neural network method to conduct natural attenuation monitoring and enhanced natural attenuation simulation, use different degrees of enhancement measures as the input variables, and use the residual pollutant concentration, the volume of contaminated soil / groundwater, and the repair time as the output variables to construct a natural attenuation prediction model of soil and groundwater.

[0017] Furthermore, in the present invention, a calculation method for coupling theoretical treatment cost and period damage cost is used to construct a multi-objective optimization model with the goal of minimizing the damage cost of monitoring and enhanced natural attenuation and with the constraint that the pollutant concentration at the end of the restoration period is reduced below the maximum acceptable risk to human health. Specifically, it includes:

[0018] Based on the theoretical treatment cost, calculate the costs of monitoring natural attenuation and enhanced natural attenuation. The cost of monitoring natural attenuation mainly includes the cost of monitoring well layout, the cost of monitoring well management and maintenance, and the cost of sampling and detection of each monitoring index; the cost of enhanced natural attenuation is the cost of enhancement measures, and the cost is specifically calculated according to the enhancement measures adopted in the pollution site restoration plan;

[0019] Based on the resource value method, calculate the damage cost during natural attenuation, mainly including the value of damaged soil resources and the value of damaged groundwater resources;

[0020] Refer to the formula in the Technical Guidelines for Risk Assessment of Soil Pollution in Construction Land (HJ 25.3—2019) to calculate the carcinogenic risk and non-carcinogenic hazard quotient of the site characteristic pollutants. Among them, the carcinogenic risk should be reduced to the range of 10 -6 ~10 -4 Magnitude range, and the non-carcinogen hazard quotient should be <1 to ensure that the human health risk of the evaluation factors at the end of the site restoration period is reduced to the maximum acceptable level.

[0021] Based on the above limiting conditions, with the costs of monitoring natural attenuation, enhanced natural attenuation, and period damage as the objective functions, and with enhancement measures, restoration time, the volume of contaminated soil and groundwater, and the residual concentration of pollutants as decision variables, construct a multi-objective optimization model for quantifying the damage value with monitoring natural attenuation as the restoration plan.

[0022] Furthermore, in the present invention, based on the multi-objective optimization model, perform an optimization analysis on the costs of monitoring natural attenuation, enhanced natural attenuation, and period damage to obtain a natural attenuation monitoring and enhanced natural attenuation plan with the lowest total cost. Specifically, it includes:

[0023] Use the particle swarm optimization algorithm to solve the multi-objective optimization model, obtain the optimal restoration plan set of monitoring and enhanced natural attenuation with the lowest cost for each, analyze the data in the optimal solution set, select the monitoring natural attenuation and enhanced natural attenuation plan with the lowest total cost, and realize the quantification of its damage value.

[0024] The present invention has the following beneficial effects:

[0025] The present invention discloses a method for quantifying the value of soil and groundwater ecological environment damage with monitored natural attenuation as the restoration plan. Aiming at the problem that it is difficult to accurately quantify the damage value with monitored natural attenuation as the restoration plan in the quantification of soil and groundwater damage value in contaminated sites, a numerical simulation model of natural attenuation and enhanced natural attenuation and a neural network prediction model are established. By coupling the theoretical treatment cost method and the resource value method, and based on a multi-objective optimization model, an optimal analysis is carried out on the cost of monitored natural attenuation, the cost of enhanced natural attenuation, and the interim damage, so as to obtain a monitored natural attenuation and enhanced natural attenuation plan with the lowest total cost. Existing value quantification methods focus on the calculation of single basic damage or single interim damage, and are only applicable to the quantification of damage value in short-term specific restoration plans or long-term irreparable plans. Moreover, the restoration period of the natural attenuation plan is long, the solute transport range is wide, and the spatio-temporal differentiation is high, making it difficult to accurately quantify the interim damage. The present invention solves the above problems, realizes the quantification of the value of soil and groundwater environmental damage under the monitored and enhanced natural attenuation plans, and the minimization analysis of the restoration cost under the condition of limiting human health risks, providing a reference basis for the determination of the natural attenuation restoration plan for contaminated sites and its damage quantification. Brief Description of the Drawings

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will introduce the accompanying drawings related to the technical solutions in the embodiments or the prior art. It should be understood that the accompanying drawings introduced below are only for the convenience of clearly expressing some embodiments of the technical solutions in the present invention, and those of ordinary skill in the art can also obtain the accompanying drawings of other embodiments based on these drawings without creative efforts.

[0027] Figure 1 It is a schematic flow chart of a method for quantifying the value of soil and groundwater ecological environment damage with monitored natural attenuation as the restoration plan of the present invention. Detailed Embodiments

[0028] In order to be able to more clearly understand the above-mentioned objects, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments described below by referring to the accompanying drawings are exemplary and are only used to explain the present application, and should not be construed as a limitation to the present application.

[0029] Many specific details are set forth in the following description in order to provide a thorough understanding of the present invention. However, the present invention may be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0030] In view of this, the present invention provides a method for calculating the cost of soil and groundwater ecological environment damage with natural attenuation monitoring and enhanced natural attenuation as the restoration plan. This method can quantify the value of soil and groundwater ecological environment damage with monitoring natural attenuation as the restoration plan, and calculate the monitoring and enhancement plan with the lowest total cost under the condition that the human health risk meets the standard.

[0031] As Figure 1 shown, the present invention provides a method for quantifying the value of soil and groundwater ecological environment damage with monitoring natural attenuation as the restoration plan, including the following steps:

[0032] By establishing a numerical simulation model of natural attenuation and enhanced natural attenuation, explore the restoration laws and effects of contaminated soil and groundwater under natural conditions and different enhancement measures, and obtain the model input sample set;

[0033] Use the Monte Carlo method for random sampling to obtain multiple groups of model input sample data, and use the neural network method to simulate the pollutant transport under different enhancement measures to construct a natural attenuation monitoring and enhanced natural attenuation prediction model;

[0034] Couple the theoretical treatment cost and the calculation method of the damage cost during the period, and construct a multi-objective optimization model with the lowest damage cost of monitoring and enhanced natural attenuation as the goal and the reduction of the pollutant concentration to below the maximum acceptable risk of human health at the end of the restoration period as the constraint condition;

[0035] Based on the multi-objective optimization model, conduct an optimization analysis of the monitoring natural attenuation cost, the enhanced natural attenuation cost, and the damage cost during the period to obtain the natural attenuation monitoring and enhanced natural attenuation plan with the lowest total cost.

[0036] The present invention solves the problem that it is difficult to quantify the damage value with monitoring natural attenuation as the restoration plan, realizes the quantification of the damage value of natural attenuation monitoring and enhancement plan and the minimization analysis of the restoration cost under the condition of human health risk as the limit, and provides a reference basis for the determination of the natural attenuation restoration plan of contaminated site soil and groundwater and its damage quantification.

[0037] Furthermore, in the present invention, by establishing a numerical simulation model of natural attenuation and enhanced natural attenuation, explore the restoration laws and effects of contaminated soil and groundwater under natural conditions and different enhancement measures, and obtain the model input sample set, specifically including:

[0038] Investigate the current situation of natural attenuation of soil and groundwater in the contaminated site, including indicators such as pollutant concentration, geochemical parameters, and hydrogeological conditions, as the constant parameters for inputting into the numerical simulation model;

[0039] It should be noted that the pollutant concentration index mainly refers to the concentrations of characteristic pollutants in the site, such as total petroleum hydrocarbons, benzene series, volatile phenols, ammonia nitrogen, etc.; the geochemical parameter indexes include pH, dissolved oxygen content, total dissolved solids content, redox potential, permanganate index, temperature, etc.; the hydrogeological condition indexes include groundwater depth, groundwater flow velocity, hydraulic gradient, permeability coefficient, dispersivity, net recharge, and aquifer medium, etc.;

[0040] It should be noted that the specific input indexes can be adjusted according to the actual situation of the polluted site. This method only lists the common pollutant concentrations, geochemical parameters, and hydrogeological condition indexes;

[0041] Set different levels of enhanced natural attenuation measures as model input variables, and construct a numerical simulation model of soil and groundwater natural attenuation to simulate the changes in the scope and degree of pollution and diffusion at different times;

[0042] It should be noted that the enhanced natural attenuation measures mainly include bioaugmentation measures, chemical oxidation enhancement measures, air injection enhancement measures, and hydrodynamic enhancement measures, etc., which are specifically determined according to the pollution site restoration plan;

[0043] It should be noted that different levels of enhancement measures refer to the changes in the pollutant attenuation rate with the changes in the dosage of bioagents added, the dosage of chemical agents added, the aeration volume, and the hydraulic gradient, etc., that is, the changes in the chemical attenuation coefficient, biological attenuation coefficient, and hydrogeological key parameters of pollutants in the numerical simulation model, specifically including the maximum degradation rate of pollutants, the half-saturation constant of pollutants, the number of microorganisms, the activity of microorganisms, the permeability coefficient, and the dispersion coefficient, etc.;

[0044] Furthermore, in the present invention, the Monte Carlo method is used for random sampling to obtain multiple groups of model input sample data, and the neural network method is used for simulating the pollutant migration under different enhancement measures to construct a natural attenuation monitoring and enhanced natural attenuation prediction model, specifically including:

[0045] Use the Monte Carlo random sampling method to extract input data, and input the obtained sample data into the numerical simulation model to obtain multiple groups of input and output sample data as the training and test data sets for the neural network method;

[0046] It should be noted that the extraction of sample data using the Monte Carlo method mainly includes steps such as establishing a probability model, determining the variable distribution of the model, and implementing random sampling. First, clarify the mathematical model and objective function of the problem, as well as the variables or parameters to be solved, and establish a mathematical model that can express the relationship between the target variable and multiple variables, as well as the probability distribution of each variable in the model. Further, select an appropriate random number generation method to generate random samples. Further, according to the probability distribution of the variables, determine their sampling methods, and perform sampling based on the generated random numbers.

[0047] It should be noted that in this method, the input variable to be optimized in the numerical simulation model is the intensity of the strengthening measure, and the output variables are the repair time, the residual concentration of pollutants, and the volume of contaminated soil and groundwater.

[0048] Adopt the neural network method to establish a natural attenuation monitoring and enhanced natural attenuation prediction model, use the key parameters of the strengthening measure as the input variables, and the repair time, the residual concentration of pollutants, and the volume of contaminated soil and groundwater as the output variables to predict the natural attenuation status of soil and groundwater.

[0049] It should be noted that in this method, the BP neural network is used to construct the prediction model. The input training data set is used to complete the establishment of the natural attenuation monitoring and enhanced natural attenuation neural network prediction model. The test data set is substituted into the established model for simulation prediction, and its approximation accuracy is calculated.

[0050] It should be noted that in the process of constructing the BP neural network prediction model, the calculation steps mainly include initializing the neural network parameters, calculating the output through forward propagation, calculating the error, updating the weights and biases through backpropagation, and repeating the iterative training, etc. First, complete the initialization of the neural network parameters, determine the number of neurons in the input layer, hidden layer, and output layer of the neural network prediction model, initialize the weight and bias parameters, set the error function, calculation accuracy value, and maximum number of learning times, etc. Further, input the sample data into the input layer neurons. In the forward propagation process, the input data passes through the input layer, hidden layer, and output layer in sequence, and the output value is calculated according to the weight and bias parameters. Further, compare the output value of the neural network with the output value of the numerical simulation model, and calculate the error between the prediction ability of the network and the actual target. Further, in backpropagation, the neural network updates the weights and biases in the network through the gradient descent algorithm according to the error between the predicted value and the true value. Further, judge whether the network error meets the requirements. If the error reaches the preset accuracy or the number of learning times reaches the maximum number of times, the training process ends. Otherwise, continue to select the next learning sample and the corresponding expected output sample, and repeat the above steps for training.

[0051] It should be noted that in this method, three indicators, namely the coefficient of determination, the mean absolute error, and the mean relative error, are used to evaluate the approximation accuracy of the BP neural network prediction model. Let the input sample data of the model be x i (i = 1, 2, 3, ……, m), and the output data be y i (i = 1, 2, 3, ……, m). The calculation formulas for the above indicators are as follows:

[0052]

[0053]

[0054]

[0055] It should be noted that among them, n is the total number of input samples; y i is the output sample data of the numerical simulation model; is the output sample data of the neural network prediction model; is the average value of the output sample data of the numerical simulation model;

[0056] It should be noted that for these three indicators, when the value of the coefficient of determination is larger (closer to 1), and at the same time the values of the mean absolute error and the mean relative error are smaller, it means that the fitting effect of the BP neural network prediction model is better, and the approximation accuracy for the numerical simulation model is higher;

[0057] Furthermore, in the present invention, a calculation method for coupling the theoretical treatment cost and the period damage cost is used to construct a multi-objective optimization model with the goal of minimizing the monitoring and enhanced natural attenuation costs and with the constraint condition that the pollutant concentration at the end of the recovery period is reduced below the maximum acceptable risk to human health. Specifically, it includes:

[0058] Calculating the monitoring natural attenuation and enhanced natural attenuation costs based on the theoretical treatment cost. Among them, the monitoring natural attenuation cost mainly includes the monitoring well layout cost, the monitoring well management and maintenance cost, and the sampling and detection cost of each monitoring index; the enhanced natural attenuation cost is the enhanced measure cost, and the cost is specifically calculated according to the enhanced measures adopted in the pollution site recovery plan;

[0059] It should be noted that the calculation formula for the monitoring natural attenuation cost is y 1 = ∑K j ×f×t + n×(W d + t×W m ). Among them, j is the monitoring index, K j is the sampling and detection cost (yuan) of the index, f is the sampling frequency (times / year), t is the recovery period (years), n is the number of monitoring wells, W d is the well layout cost (yuan), W mis the monitoring well maintenance cost (yuan / year);

[0060] It should be noted that the strengthening measures are specifically determined according to the pollution site restoration plan. The calculation formula for the cost of enhanced natural attenuation is y 2 = Q m × P m + Q b × P b + V g × P g + P f + P h , and the calculation formulas for the costs of commonly used strengthening measures are listed here: The cost of chemical oxidation strengthening is Q m × P m , where Q m is the chemical dosage (kg), and P m is the unit price of the chemical agent (yuan / kg); The cost of chemical strengthening is Q b × P b , where Q b is the biological bacteria dosage (kg), and P b is the unit price of the bacteria agent (yuan / kg); The cost of air injection strengthening is V g × P g , where V g is the aeration volume (m 3 ), and P g is the energy consumption cost per unit volume of gas (yuan / m 3 ); The cost of hydrodynamic strengthening is P f + P h , where P f is the cost of the well group control system equipment and installation (yuan), and P h is the energy consumption cost of manually pumping groundwater or injecting water into the aquifer (yuan);

[0061] Based on the resource value method, the calculation of the damage cost during natural attenuation mainly includes the value of damaged soil resources and the value of damaged groundwater resources;

[0062] It should be noted that the value of damaged soil and groundwater resources is calculated by referring to the resource value method in "Technical Guidelines for Identification and Assessment of Ecological Environment Damage - Part 1: Soil and Groundwater" (GB / T 39792.1—2020). The formula is y 3 = V r × V p , where V r = V b × γ. Among them, y 3 is the damage cost during the period (yuan); V r is the value of damaged soil / groundwater resources (yuan / m 3 ); V bis the non - use benchmark value of soil / groundwater resources (yuan / m 3 ); V p is the volume of damaged soil / groundwater (m 3 ); γ is the adjustment coefficient, which is related to the maximum multiple of the pollutant concentration exceeding the standard in soil and groundwater;

[0063] Refer to the formula in "Technical Guidelines for Risk Assessment of Soil Pollution in Construction Land" (HJ 25.3 - 2019) to calculate the carcinogenic risk and non - carcinogenic hazard quotient of site characteristic pollutants. Among them, the carcinogenic risk should be reduced to the range of 10 -6 ~10 -4 magnitude, and the non - carcinogen hazard quotient should be < 1 to ensure that the human health risks of each evaluation factor are reduced to the maximum acceptable level at the end of the site restoration period;

[0064] It should be noted that the formula for calculating the carcinogenic risk of characteristic pollutants in soil and groundwater is CR = ER×c t ×SF, where ER is the pollutant exposure amount (kg / kg·d), c t is the concentration of pollutants in soil / groundwater (mg / kg, mg / L), and SF is the carcinogenic slope factor (kg·d / mg); the formula for calculating the non - carcinogen hazard quotient is where RfD is the reference dose of pollutants absorbed by the human body through different pathways (mg / kg·d), and WAF is the reference dose distribution ratio for exposure to groundwater, dimensionless;

[0065] Based on the above - mentioned limiting conditions, with the monitoring natural attenuation cost, enhanced natural attenuation cost, and interim damage cost as the objective function, and enhanced measures, remediation time, volume of contaminated soil and groundwater, and residual pollutant concentration as decision variables, a multi - objective optimization model for quantifying damage value with monitoring natural attenuation as the restoration plan is constructed;

[0066] It should be noted that in actual projects, an optimization plan that only meets a single index often cannot meet the actual overall optimization requirements. In this context, the multi - objective optimization problem arises. Multi - objective optimization is to find the optimal solution under certain constraint conditions so that a set of objective function values can reach the minimum value (or maximum value) as much as possible simultaneously, and the comprehensive effect obtained is the best. The multi - objective optimization problem of the present invention can be expressed by the following formula:

[0067]

[0068] It should be noted that in the process of multi-objective optimization design for quantifying the damage value of the restoration plan with monitoring and enhanced natural attenuation as the restoration plan, the minimum monitoring natural attenuation cost, the minimum enhanced natural attenuation cost, and the minimum interim damage cost are used as the objective functions, and the carcinogenic risk to human health and the hazard of non-carcinogens reaching an acceptable level are used as the constraints, thus constituting a multi-objective optimization model for quantifying the damage value of the restoration plan with monitoring natural attenuation as the restoration plan;

[0069] Furthermore, in the present invention, based on the multi-objective optimization model, an optimization analysis is carried out on the monitoring natural attenuation cost, the enhanced natural attenuation cost, and the interim damage cost, and the natural attenuation monitoring and enhanced natural attenuation restoration plan with the lowest total cost is selected, which specifically includes:

[0070] The particle swarm optimization algorithm is used to solve the multi-objective optimization model to obtain the optimal restoration plan set with the lowest cost for each item. The data in the optimal solution set is analyzed to select the monitoring natural attenuation and enhanced natural attenuation plan with the lowest total cost, and the quantification of its damage value is realized.

[0071] It should be noted that the steps of the particle swarm optimization algorithm mainly include initializing the particle swarm parameters, calculating the particle fitness, updating the particle velocity and position, judging whether the termination condition is met, outputting the optimal value, etc.: First, initialize the particle swarm parameters, mainly including setting the population size (N) and the number of iterations, randomly initializing the position (x i ) and velocity (v i ) of each particle, setting the individual best position of each particle and the global best position of the entire population, etc.; Furthermore, calculate the fitness value (F it ) of each particle, and update the individual optimal position (p best ) according to the fitness value; Furthermore, find out the individual optimal positions of all particles and update the global optimal position (g best );Furthermore, according to the individual optimal position and the global optimal position, update the velocity (v i ) and position (x i ) of the particle; Furthermore, judge whether the termination condition is met. If the termination condition is met (the error is small enough or the preset maximum number of iterations is reached), the algorithm ends and outputs the solution corresponding to the global best position as the optimal solution of the optimization problem. Otherwise, return to the second step to continue the iteration.

[0072] It should be noted that after calculating the optimal solution set using the particle swarm optimization algorithm, calculate the sum of the monitoring natural attenuation cost, the enhanced natural attenuation cost, and the interim damage for each group in the optimal solution set, and sort to obtain the restoration plan with the lowest total cost.

[0073] In summary, the method for quantifying the value of soil and groundwater ecological environment damage with natural attenuation monitoring as the restoration plan in the present invention has wide applicability and is easy to implement. It can address the limitations of existing value quantification methods that focus on calculating single basic damage or single-period damage, and are only applicable to calculating short-term specific restoration plans or long-term non-restorable plans, as well as the problem that it is difficult to accurately quantify the damage during the natural attenuation plan. It conducts damage value quantification and minimum restoration cost analysis for monitoring and enhanced natural attenuation plans, providing a reference basis for determining the natural attenuation restoration plan for contaminated sites and its damage quantification, and having good application prospects.

[0074] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope provided by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for quantifying the value of soil and groundwater ecological environmental damage based on monitoring natural attenuation as a restoration plan, characterized by: The following steps are involved: 1) Through the establishment of natural attenuation monitoring and enhanced natural attenuation numerical simulation models, explore the restoration rules and effects of contaminated soil groundwater under natural conditions and different enhancement measures, and obtain the model input sample set; 2) Use the Monte Carlo method for random sampling to obtain multiple sets of model input sample data, use the neural network method to simulate and predict natural attenuation under different enhancement measures, and build a natural attenuation monitoring and enhanced natural attenuation prediction model; Use BP neural network to build the prediction model, input the training data set to complete the natural attenuation monitoring and strengthen the establishment of the natural attenuation neural network prediction model, substitute the test data set into the built model for simulation prediction, and calculate its approximation accuracy; 3) Couple the theoretical governance cost and the calculation method of the period damage cost, and construct a multi-objective optimization model with the goals of monitoring the natural attenuation cost, enhancing the natural attenuation cost, and minimizing the period damage cost, and with the constraint that the pollutant concentration is reduced to below the maximum acceptable risk to human health at the end of the restoration period; 4) Based on the multi-objective optimization model, the cost of monitoring natural attenuation, the cost of enhancing natural attenuation and the cost of damage during the period are optimized to obtain the natural attenuation monitoring and enhanced natural attenuation plan with the lowest total cost; The particle swarm optimization algorithm is used to solve the multi-objective optimization model to obtain the optimal solution set of natural attenuation monitoring and enhanced natural attenuation restoration with the lowest cost. The data in the optimal solution set is analyzed to obtain the natural attenuation monitoring and enhanced natural attenuation restoration plan with the lowest total cost, thereby quantifying its damage value. The specific steps of step 3) are as follows: The natural attenuation monitoring is carried out based on the theoretical governance cost, and the calculation of the enhanced natural attenuation cost is carried out. The natural attenuation monitoring cost mainly includes the cost of monitoring well layout, monitoring well management and maintenance costs, and the sampling and testing costs of various monitoring indicators; The cost of enhanced natural attenuation is the cost of enhanced measures, which is calculated based on the enhanced measures adopted in the contaminated site restoration plan; The calculation of the damage cost during the natural attenuation period is based on the resource value method, which mainly includes the value of damaged soil resources and damaged groundwater resources; Refer to the formula in the Technical Guidelines for Soil Pollution Risk Assessment for Construction Land (HJ 25.3-2019) to calculate the carcinogenic risk and non-carcinogenic hazard quotient of the characteristic pollutants of the site, among which the carcinogenic risk should be reduced to 10 -6 ~10 -4 Within the magnitude range, the non-carcinogen hazard quotient should be less than 1, ensuring that the human health risk of each evaluation factor is reduced to the maximum acceptable level at the end of the site restoration period; Based on the above constraints, a multi-objective optimization model for quantifying the damage value with natural attenuation monitoring as the restoration plan was constructed, with the cost of monitoring natural attenuation, enhancing natural attenuation and period damage cost as the objective function, and the enhancement measures, restoration time, volume of contaminated soil and groundwater and residual concentration of pollutants as the decision variables.

2. The method for quantifying the value of soil and groundwater ecological environmental damage based on monitoring natural attenuation as a restoration plan according to claim 1 is characterized in that: The specific steps of step 1) are as follows: Investigate the status of natural attenuation of soil and groundwater in contaminated sites, including pollutant concentrations, geochemical parameters and hydrogeological condition indicators, as constant parameters for input into numerical simulation models; Different degrees of enhanced natural attenuation measures are set as model input variables, and a numerical simulation model of soil and groundwater natural attenuation is constructed to simulate the changes in the scope and degree of pollution and diffusion at different times.

3. The method for quantifying the value of soil and groundwater ecological environment damage based on monitoring natural attenuation as a restoration plan according to claim 2 is characterized in that: Enhanced natural attenuation measures mainly include biological enhancement measures, chemical oxidation enhancement measures, air injection enhancement measures and hydrodynamic enhancement measures; Different degrees of enhanced measures refer to changes in the pollutant attenuation rate as the dosage of biological agents added, the dosage of chemical agents added, the aeration volume and the hydraulic gradient change, that is, changes in the pollutant chemical attenuation coefficient, biological attenuation coefficient and key hydrogeological parameters in the numerical simulation model, specifically including the maximum degradation rate of pollutants, pollutant half-saturation constant, microbial number, microbial activity, permeability coefficient and diffusion coefficient.

4. The method for quantifying the value of soil and groundwater ecological environmental damage based on monitoring natural attenuation as a restoration plan according to claim 1 is characterized in that: The specific steps of step 2) are as follows: The sample data are extracted using the Monte Carlo random sampling method, and the obtained sample data are input into the numerical simulation model to obtain multiple sets of input and output sample data as the training data set and the test data set of the neural network model; A neural network model for monitoring natural attenuation and enhancing natural attenuation simulation was constructed. Different degrees of enhancement measures were used as input variables, and the residual concentration of pollutants, the volume of contaminated soil and groundwater, and the restoration time were used as output variables to construct a soil and groundwater natural attenuation prediction model. The three indicators of certainty coefficient, mean absolute error and mean relative error are used to evaluate the approximation accuracy of the BP neural network prediction model. Suppose the input sample data of the model is x i (i=1, 2, 3, ..., m), the output data is y i (i=1, 2, 3, ..., m), the calculation formula for the above indicators is: Where n is the total number of input samples; Output sample data for numerical simulation models; Output sample data for the neural network prediction model; is the average value of the output sample data of the numerical simulation model; For these three indicators, when the value of the certainty coefficient is larger, that is, closer to 1, and the values ​​of the mean absolute error and the mean relative error are smaller, it means that the fitting effect of the BP neural network prediction model is better and the approximation accuracy of the numerical simulation model is higher.

5. The method for quantifying the value of soil and groundwater ecological environment damage based on monitoring natural attenuation as a restoration plan according to claim 1 is characterized in that: The specific steps of step 4) are as follows: the particle swarm optimization algorithm steps mainly include initializing particle swarm parameters, calculating particle fitness, updating particle speed and position, judging whether the termination condition is met, and outputting the optimal value; First, initialize the particle swarm parameters, mainly including setting the swarm size (N) and the number of iterations, and randomly initializing the position of each particle (x i ) and speed (v i ), set the individual best position of each particle and the global best position of the entire group; further, calculate the fitness value of each particle (F it ), update the individual optimal position according to the fitness value (p best ); Furthermore, find the individual optimal positions of all particles and update the global optimal position (g best ); Furthermore, according to the individual optimal position and the global optimal position, the particle velocity (v i ) and position (x i ); Further, it is determined whether the termination condition is met. If the termination condition is met (the error is small enough or the preset maximum number of iterations is reached), the algorithm ends and outputs the solution corresponding to the global best position as the optimal solution to the optimization problem. Otherwise, it returns to the second step to continue iterating. After the optimal solution set is calculated using the particle swarm optimization algorithm, the sum of the monitoring natural attenuation cost, natural attenuation enhancement cost and period damage of each group in the optimal solution set is calculated, and the restoration plan with the lowest total cost is obtained after sorting.

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