Refuse landfill pollution assessment method, system, equipment and medium

Abstract

The invention relates to the technical field of pollution detection, in particular to a pollution assessment method, system, equipment and medium for a refuse landfill, and the method comprises the following steps: firstly, obtaining full-spectrum induced polarization data of the landfill to construct a stratum electrochemical attribute model; resolving a retardation factor distribution field by using the physical and chemical parameters of the pollution carrier and the model; constructing a Darcy velocity field in combination with hydrogeological parameters, and generating a pollution carrier migration velocity field through retardation factor correction; and finally, streamline tracing simulation is executed based on the velocity field, so that a target monitoring well coordinate and a risk early warning level are output. The technical problems that the dominant flow channel of the structural fracture is difficult to identify under the complex geology and evaluation distortion is caused by non-synchronous migration caused by the interface electrochemical action of the micro-nano carrier in the traditional method are solved; accurate positioning of the hidden leakage channel and accurate prediction of the penetration time are achieved, and the early warning capacity and the management and control efficiency of landfill environment risks are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of pollution detection technology, and in particular to a pollution assessment method, system, equipment and medium for landfills. Background Technology

[0002] As an important terminal facility for the disposal of urban solid waste, the environmental safety assessment of landfills during their service life and after closure is a core part of environmental supervision. Under the current industry standards and technical guidelines, the environmental risk assessment of landfills usually adopts a comprehensive evaluation model that combines source term seepage prevention system detection with monitoring of the surrounding groundwater environment.

[0003] Specifically, the assessment work mainly relies on regional hydrogeological survey data, uses numerical simulation methods to construct groundwater solute transport models, and plans the layout of monitoring well networks based on simulation results. Groundwater samples are collected regularly for physicochemical index analysis to define the diffusion range and environmental risk level of pollution plumes, thereby guiding subsequent pollution prevention and control decisions.

[0004] However, in practical engineering applications, especially in complex geological environments such as red mudstone distribution areas, karst development areas, or plateau permafrost areas, traditional groundwater environment monitoring and risk assessment methods are usually based on the equivalent continuous medium theory model, which assumes that the groundwater aquifer is homogeneous and isotropic in terms of hydraulic properties. This assessment model based on idealized assumptions often fails to cover the structural fractures or preferential flow channels that objectively exist in heterogeneous strata when guiding the layout of monitoring points.

[0005] Specifically, due to the lack of ability to identify and locate discontinuous and rapid migration channels, in actual monitoring, even if the monitoring wells deployed according to regulations cover the theoretical downstream area, the water quality data collected may not be able to characterize the high-flux pollutant migration characteristics in adjacent fracture channels because the monitoring points may be located in low-permeability matrix rock blocks. This representativeness bias of the monitoring data makes it easy for risk assessment reports to draw controllable misjudgments, which in turn prevents managers from obtaining true flux information in the early stages of pollution diffusion, resulting in lag and failure in environmental risk management. Summary of the Invention

[0006] The main objective of this invention is to provide a pollution assessment method for landfills, aiming to solve the technical problem that existing assessment methods have large assessment errors in low-permeability matrix rock blocks.

[0007] To achieve the above objectives, the present invention provides a pollution assessment method for landfills, the method comprising the following steps:

[0008] Full-spectrum excitation polarization data of the landfill area are obtained, and a formation electrochemical property model is constructed based on the full-spectrum excitation polarization data. The formation electrochemical property model is used to describe the surface conductivity and polarization characteristics of the underground medium at different frequencies.

[0009] Obtain the physicochemical characteristic parameters of the pollutant carrier, and obtain the distribution field of the blocking factor based on the physicochemical characteristic parameters and the formation electrochemical property model;

[0010] Hydrogeological parameters were obtained, and a Darcy velocity field of groundwater was constructed based on the hydrogeological parameters. The migration velocity field of the pollutant carrier was obtained by combining the distribution field of the retardation factor.

[0011] Streamline tracing simulations were performed based on the migration velocity field to obtain the escape path and penetration time of the contaminant carrier.

[0012] The coordinates of the targeted monitoring wells and the environmental risk warning level are obtained based on the escape path and penetration time.

[0013] Optionally, the step of obtaining full-spectrum excited polarization data of the landfill area and constructing a formation electrochemical property model based on the full-spectrum excited polarization data includes the following sub-steps:

[0014] Acquire complex resistivity data at different frequencies within the detection area, and extract the phase response spectrum based on the complex resistivity data;

[0015] The phase response spectrum was inverted and fitted using the complex resistivity relaxation model to obtain the polarizability parameters and time constant parameters of the subsurface medium.

[0016] An electrochemical mapping relationship is constructed based on polarizability parameters, time constant parameters, and preset pore geometry factors;

[0017] The specific surface area and surface conductivity parameters of the fracture wall were obtained by analyzing the electrochemical mapping relationship.

[0018] A formation electrochemical property model is constructed based on the specific surface area parameter and surface conductivity parameter.

[0019] Optionally, obtaining the physicochemical characteristic parameters of the contaminant carrier and obtaining the distribution field of the retardation factor based on the physicochemical characteristic parameters and the formation electrochemical property model includes the following sub-steps:

[0020] Obtain the charge density and particle size parameters of the contaminant carrier;

[0021] The Zeta potential distribution on the fracture wall is obtained based on the surface conductivity parameters in the formation electrochemical property model.

[0022] A potential energy function is constructed based on the charge density parameter of the contaminant and the Zeta potential distribution of the fissure wall. This potential energy function is used to quantify the interaction force between the contaminant and the fissure wall.

[0023] The distribution coefficient is calculated based on the potential energy function, and the distribution field of the retardation factor is obtained based on the distribution coefficient.

[0024] The retardation factor distribution field is used to characterize the degree of lag or slippage of the pollutant carrier relative to water molecules.

[0025] Optionally, the step of obtaining hydrogeological parameters, constructing a Darcy velocity field for groundwater based on the hydrogeological parameters, and obtaining the migration velocity field of the pollutant carrier by combining the retardation factor distribution field includes the following sub-steps:

[0026] Obtain the hydraulic gradient parameters and matrix permeability parameters of the underground aquifer;

[0027] The Darcy velocity field of groundwater is calculated based on hydraulic gradient parameters and matrix permeability parameters. The Darcy velocity field of groundwater is used to characterize the average flow velocity of solutes in an ideal porous medium.

[0028] The corrected carrier velocity vector is obtained by calculating the ratio between the velocity vector in the Darcy velocity field of groundwater and the resistance value in the resistance factor distribution field.

[0029] The entire space grid is traversed and corrected to obtain the migration velocity field of the pollutant carrier.

[0030] Optionally, the step of performing streamline tracing simulation based on the migration velocity field to obtain the escape path and penetration time of the contaminant carrier includes the following sub-steps:

[0031] Define the set of pollution source locations and the set of downstream boundaries;

[0032] In the migration velocity field, multiple potential migration trajectories emanating from the set of pollution source locations are obtained based on the streamline tracing algorithm;

[0033] The cumulative penetration time of a potential migration trajectory is obtained by integrating the reciprocal of the migration velocity along each potential migration trajectory.

[0034] The trajectory with the shortest cumulative penetration time was selected as the escape path of the pollutant carrier, and the shortest cumulative penetration time was taken as the final penetration time.

[0035] Optionally, obtaining the target monitoring well deployment coordinates and environmental risk warning level based on the escape path and penetration time includes the following sub-steps:

[0036] Obtain the intersection point of the escape path and the downstream boundary set, and determine the three-dimensional spatial coordinates of the intersection point as the deployment coordinates of the targeted monitoring well;

[0037] Obtain the design and control response cycle of the landfill;

[0038] The penetration time is compared with the designed prevention and control response cycle to obtain the carrier penetration risk index;

[0039] The environmental risk warning level is determined based on the numerical range of the carrier penetration risk index.

[0040] Optionally, the inversion fitting of the phase response spectrum based on the complex resistivity relaxation model includes the following sub-steps:

[0041] Construct a theoretical model of Cole-Cole complex resistivity;

[0042] Based on the nonlinear least squares algorithm, the model parameters are globally optimized with the goal of minimizing the mean square error between the measured phase response spectrum and the theoretical model output spectrum. When the mean square error is less than the preset convergence threshold, the current optimal parameter combination is output as the polarizability parameter and the time constant parameter.

[0043] To achieve the above objectives, the present invention also provides a pollution assessment system, the system comprising:

[0044] An electrochemical modeling module is used to acquire full-spectrum excitation polarization data of the landfill area and construct a formation electrochemical property model based on the full-spectrum excitation polarization data. The formation electrochemical property model is used to describe the surface conductivity and polarization characteristics of the underground medium at different frequencies.

[0045] The retardation calculation module is used to obtain the physicochemical characteristic parameters of the pollutant carrier and obtain the retardation factor distribution field based on the physicochemical characteristic parameters and the formation electrochemical property model.

[0046] A velocity field construction module is used to obtain hydrogeological parameters, construct a Darcy velocity field for groundwater based on the hydrogeological parameters, and obtain the migration velocity field of the pollutant carrier by combining the distribution field of the retardation factor.

[0047] The tracer simulation module is used to perform streamline tracer simulation based on the migration velocity field to obtain the escape path and penetration time of the pollutant carrier.

[0048] The analysis and evaluation module is used to obtain the coordinates of the targeted monitoring wells and the environmental risk warning level based on the escape path and penetration time.

[0049] To achieve the above objectives, the present invention also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program and the processor executes the computer program to implement the above-described method.

[0050] To achieve the above objectives, the present invention also provides a computer-readable storage medium storing a computer program, wherein a processor executes the computer program to implement the above-described method.

[0051] The beneficial effects that this invention can achieve are as follows:

[0052] This invention constructs a formation electrochemical property model by inverting full-spectrum induced polarization data of landfill areas, constructs a nonlinear retardation factor distribution field by combining the microscopic physicochemical characteristic parameters of the pollutant carrier, and spatially couples this distribution field with the Darcy velocity field based on hydrogeological parameters. Then, it uses the modified migration velocity field to perform streamline tracing simulation to lock the escape path. This solves the technical problems of existing assessment technologies in complex heterogeneous geological conditions such as red mudstone or karst development areas, which cannot identify dominant flow channels such as tectonic fractures due to the assumption of equivalent continuous medium theory, and ignore the asynchronous transport characteristics of micro-nano plastic carriers relative to groundwater flow due to micro-interface electrochemical effects. This leads to representative blind spots in the layout of monitoring points and false negatives in environmental risk assessment results. This invention achieves accurate location of underground hidden high-flux leakage channels and accurate prediction of the penetration time of micro-nano particulate pollutants.

[0053] This invention overcomes the limitations of traditional reliance on hydrodynamic models. By quantifying the nonlinear correction of macroscopic transport velocity through microscopic double-layer interactions, it successfully distinguishes between ordinary groundwater flow paths and high-risk pollutant escape paths. This transforms environmental monitoring from traditional empirical grid-based blind monitoring to targeted and precise interception based on physical evidence. It not only significantly improves the spatial hit rate of monitoring well deployment and pollutant capture efficiency, enabling the immediate detection and early warning of pollution fronts that rapidly escape through advantageous channels, but also provides managers with quantitative risk indicators based on real physical processes. This greatly shortens the decision-making window for emergency response, thereby effectively reducing long-term operation and maintenance and repair costs while fundamentally improving the environmental safety management and early warning capabilities of landfills throughout their entire life cycle. Attached Figure Description

[0054] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0055] Figure 1 This is a flowchart illustrating the method in Embodiment 1 of the present invention;

[0056] Figure 2This is a structural block diagram of the system in Embodiment 2 of the present invention.

[0057] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0058] 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 a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0059] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0060] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0061] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text includes three parallel solutions; for example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0062] Example 1:

[0063] As attached Figure 1As shown in the figure, this embodiment provides a pollution assessment method for landfills, the method comprising the following steps:

[0064] Full-spectrum excitation polarization data of the landfill area are obtained, and a formation electrochemical property model is constructed based on the full-spectrum excitation polarization data. The formation electrochemical property model is used to describe the surface conductivity and polarization characteristics of the underground medium at different frequencies.

[0065] Obtain the physicochemical characteristic parameters of the pollutant carrier, and obtain the distribution field of the blocking factor based on the physicochemical characteristic parameters and the formation electrochemical property model;

[0066] Hydrogeological parameters were obtained, and a Darcy velocity field of groundwater was constructed based on the hydrogeological parameters. The migration velocity field of the pollutant carrier was obtained by combining the distribution field of the retardation factor.

[0067] Streamline tracing simulations were performed based on the migration velocity field to obtain the escape path and penetration time of the contaminant carrier.

[0068] The coordinates of the targeted monitoring wells and the environmental risk warning level are obtained based on the escape path and penetration time.

[0069] It should be noted that in the environmental risk assessment of landfills, traditional methods are based on the equivalent continuous medium theory model to construct a groundwater solute transport model. This model assumes that the groundwater aquifer is homogeneous and isotropic in terms of hydraulic properties. However, in complex geological environments such as red mudstone distribution areas, karst development areas, or plateau permafrost areas, the actual strata have discontinuous structural fractures or preferential flow channels. As a result, the monitoring wells deployed according to this model may be located in low-permeability matrix blocks. The water quality data collected cannot characterize the pollutant migration characteristics in the adjacent fracture channels, thus causing a deviation in the representativeness of the monitoring data. This leads to the risk assessment conclusions not matching the actual situation, and the environmental risk control measures are delayed.

[0070] It should also be noted that, based on the above-mentioned problems, this embodiment provides a pollution assessment method for landfills. Through a series of steps, it achieves high-precision prediction of the transport path and time of pollutants, thereby guiding the deployment of monitoring wells and risk early warning. Specifically, firstly, full-spectrum excitation polarization data of the landfill area is acquired, and a formation electrochemical property model is constructed based on this data. This formation electrochemical property model is used to describe the surface conductivity and polarization characteristics of the underground medium at different frequencies. By deploying an electrode array in the landfill area, injecting currents of different frequencies underground, and measuring the corresponding voltage responses, full-spectrum excitation polarization data is obtained. Subsequently, using empirical formulas or simplified physical models, these measurement data are converted into parameters reflecting the formation electrochemical properties. By directly fitting the resistivity and phase variation curves with frequency, the electrochemical response characteristics of the formation are estimated, thereby constructing the formation electrochemical property model.

[0071] Secondly, the physicochemical characteristics of the contaminant carrier are obtained, and the distribution field of the hindrance factor is derived based on these parameters and the formation electrochemical property model. The physicochemical characteristics of the contaminant carrier can be obtained through laboratory analysis of leachate samples, such as measuring pH, ion concentration, and organic matter content. When obtaining the distribution field of the hindrance factor, certain physicochemical characteristics of the contaminant carrier (e.g., adsorption coefficient) can be simply correlated with parameters reflecting adsorption capacity in the formation electrochemical property model based on known empirical relationships. This allows for the estimation of the hindrance effect of the contaminant carrier in different formations and the generation of the hindrance factor distribution field.

[0072] Next, hydrogeological parameters are acquired, and a Darcy velocity field for groundwater is constructed based on these parameters. Simultaneously, the migration velocity field of contaminants is obtained by combining this with the distribution field of the hindrance factor. Hydrogeological parameters can be obtained through field surveys, borehole sampling, and hydrological tests, such as measuring groundwater level, aquifer thickness, and permeability coefficient. When constructing the Darcy velocity field, numerical methods such as finite difference or finite element methods can be used to solve the groundwater flow equation based on the hydrogeological parameters, thereby obtaining the groundwater velocity at various locations. Subsequently, the groundwater velocity can be initially corrected by performing simple multiplication or division operations between the Darcy velocity field and the hindrance factor distribution field to reflect the migration velocity of contaminants in the actual strata, thus obtaining the migration velocity field of the contaminants.

[0073] Then, streamline tracer simulation is performed based on the migration velocity field to obtain the escape path and penetration time of the contaminant carrier. Streamline tracer simulation can depict the trajectory of a particle by releasing virtual particles from the contaminant source location within the migration velocity field and progressively calculating the particle's position based on the velocity vector at each time step. When obtaining the penetration time, a preliminary estimate can be obtained by simply dividing the total distance the particle travels from the contaminant source to the downstream boundary by its average migration velocity.

[0074] Finally, the deployment coordinates of the targeted monitoring wells and the environmental risk warning level are obtained based on the escape path and penetration time. When determining the deployment coordinates of the targeted monitoring wells, several points in the downstream area of ​​the escape path obtained from the simulation can be selected as candidate locations for the monitoring wells. When obtaining the environmental risk warning level, the penetration time can be compared with several preset time thresholds. If the penetration time is less than a certain threshold, it is judged as high risk; if it is greater than another threshold, it is judged as low risk, thus determining the environmental risk warning level.

[0075] In summary, the above steps, by introducing full-spectrum excited polarization data to construct a formation electrochemical property model, can characterize the heterogeneity of the subsurface medium, particularly improving the ability to identify preferential flow channels such as fractures. Through this electrochemical property model, subsurface fractures that are difficult to detect using traditional hydrogeological surveys can be identified; these fractures play a crucial role in pollutant transport.

[0076] In this embodiment, the process of acquiring full-spectrum excited polarization data of the landfill area and constructing a formation electrochemical property model based on the full-spectrum excited polarization data includes the following sub-steps:

[0077] Acquire complex resistivity data at different frequencies within the detection area, and extract the phase response spectrum based on the complex resistivity data;

[0078] The phase response spectrum was inverted and fitted using the complex resistivity relaxation model to obtain the polarizability parameters and time constant parameters of the subsurface medium.

[0079] An electrochemical mapping relationship is constructed based on polarizability parameters, time constant parameters, and preset pore geometry factors;

[0080] The specific surface area and surface conductivity parameters of the fracture wall were obtained by analyzing the electrochemical mapping relationship.

[0081] A formation electrochemical property model is constructed based on the specific surface area parameter and surface conductivity parameter.

[0082] In this embodiment, the inversion fitting of the phase response spectrum based on the complex resistivity relaxation model includes the following sub-steps:

[0083] Construct a theoretical model of Cole-Cole complex resistivity;

[0084] Based on the nonlinear least squares algorithm, the model parameters are globally optimized with the goal of minimizing the mean square error between the measured phase response spectrum and the theoretical model output spectrum. When the mean square error is less than the preset convergence threshold, the current optimal parameter combination is output as the polarizability parameter and the time constant parameter.

[0085] It should be noted that the key step of obtaining full-spectrum excitation polarization data of the landfill area and constructing a formation electrochemical property model is not only to obtain physical structure information of the geological body, but also to gain insight into the electrochemical properties of the micro-interface of the formation medium, thereby providing underlying data support for subsequent calculations of the nonlinear retardation effect of micro-nano plastic carriers.

[0086] It should also be noted that, in the specific implementation process, a high-density full-spectrum excitation polarization monitoring array needs to be deployed in the landfill and surrounding controlled areas. The array transmits a multi-frequency sweep current covering the range from millihertz to kilohertz, and simultaneously collects the raw signal containing potential difference and phase difference at the receiving end. Then, the complex resistivity data of different spatial locations in the detection area at different frequencies is calculated, and the phase response spectrum that is most sensitive to the interface polarization effect is extracted from it.

[0087] To extract intrinsic parameters reflecting the microscopic pore structure and charge state from the macroscopic phase response spectrum, an inversion fitting step is required. In this process, the Cole-Cole complex resistivity relaxation model is introduced as the theoretical core of the inversion. This model accurately describes the polarization relaxation behavior of heterogeneous geological bodies under alternating electric fields, and its expression satisfies:

[0088] ;

[0089] in, The frequency-varying complex resistivity is directly derived from the measured results of the full-spectrum excited polarization array in the previous step;

[0090] ω is the angular frequency;

[0091] i is the imaginary unit;

[0092] DC resistivity, or zero-frequency resistivity, reflects the overall conductivity and pore connectivity of pore fluids.

[0093] m is the polarizability, a dimensionless parameter used to quantify the ability of a medium to store charge. Its value is directly related to the degree of development of the electric double layer on the fracture wall.

[0094] τ is a time constant that characterizes the characteristic time required for the polarization process to complete. This parameter is physically closely related to the characteristic scale of the polarization unit (i.e., pores or particles).

[0095] c is the frequency correlation coefficient, used to describe the width of the relaxation time distribution.

[0096] In the actual calculation of the above expression, the nonlinear least squares algorithm is used to minimize the mean square error between the measured data and the theoretical model output. The above parameters are then iteratively optimized globally to obtain a uniquely determined polarizability parameter m and time constant parameter τ at each spatial grid point.

[0097] After obtaining the aforementioned macroscopic polarization parameters, the next core task is to transform them into microscopic chemical properties, i.e., to construct an electrochemical mapping relationship. Since polarizability and time constant are not directly equivalent to chemical properties, it is necessary to utilize the double-layer polarization theory. Based on the physical correlation between polarization characteristic time and characteristic length, the following analytical expression for the pore structure is designed:

[0098] ;

[0099] in, is the diffusion coefficient of the counterion in the Stern layer;

[0100] is the characteristic length of the polarization unit.

[0101] The time constant is transformed into the characteristic length of the fracture using the above expression, and then combined with a preset pore geometry factor (usually denoted as ). (Based on statistical analysis of historical samples), using geometric relationships. The specific surface area parameters of the fracture wall were obtained by analysis. ), and the specific surface area parameter is a key geometric indicator that determines the number of adsorption sites.

[0102] Subsequently, to further obtain chemical indicators reflecting charge density, an analytical formula for surface conductivity was constructed. This formula was designed using the response mechanism between polarizability and microscopic parameters, and its specific expression is as follows:

[0103] ;

[0104] in, The imaginary part of the complex conductivity represents the energy storage capacity (i.e., capacitance effect) of the underground medium under the action of an alternating electric field, which is generated by the polarization displacement of charges.

[0105] This is a pore surface area parameter, representing the total surface area of ​​the pores within a unit volume of rock;

[0106] It is a dimensionless parameter used to correct the distortion effect of pore shape (such as cylindrical or flat slit shape) on the current conduction path;

[0107] The core target chemical parameter that needs to be solved in the end is an intrinsic quantity that is only related to the mineral composition and surface charge density of the fracture wall, and directly reflects the electrochemical activity of the solid-liquid interface.

[0108] The aforementioned geometric parameters reflecting the pore structure have been obtained. However, these geometric parameters alone cannot determine whether the fracture walls are charged. Furthermore, the polarization effect of the subsurface medium (manifested as the imaginary part of the complex conductivity) primarily originates from the tangential migration of ions within the electrical double layer at the solid-liquid interface. Therefore, to "decouple" chemical parameters that directly characterize charge density from the macroscopic imaginary part of conductivity, a quantitative mapping equation is established between the macroscopic imaginary part of conductivity and the microscopic geometric and chemical parameters. This expression links the measurable macroscopic electrical properties with the indirectly measurable microscopic surface chemical properties.

[0109] In summary, by recombining and mapping these two datasets, which accurately characterize the microscopic interface properties of subsurface media, according to their actual spatial coordinates, a so-called "formation electrochemical property model" is constructed. This model is no longer an ordinary structural diagram, but a three-dimensional numerical matrix containing rich electrochemical information. It can clearly identify which subsurface fracture channels have high inner surface charge density (meaning strong adsorption or repulsion of charged pollutants) and which channels have low charge density. This model provides the most fundamental and crucial physicochemical boundary condition input for the subsequent steps of accurately calculating the nonlinear retardation factor of micro / nano plastic carriers.

[0110] It is understandable that the underground medium is not an ideal resistor or capacitor, but a complex RC network with wide frequency domain relaxation characteristics. Through the above expression, the measured complex resistivity can be decomposed into a pure ohmic conductive part and an interface polarization part.

[0111] In this embodiment, obtaining the physicochemical characteristic parameters of the contaminant carrier and obtaining the distribution field of the retardation factor based on the physicochemical characteristic parameters and the formation electrochemical property model includes the following sub-steps:

[0112] Obtain the charge density and particle size parameters of the contaminant carrier;

[0113] The Zeta potential distribution on the fracture wall is obtained based on the surface conductivity parameters in the formation electrochemical property model.

[0114] A potential energy function is constructed based on the charge density parameter of the contaminant and the Zeta potential distribution of the fissure wall. This potential energy function is used to quantify the interaction force between the contaminant and the fissure wall.

[0115] The distribution coefficient is calculated based on the potential energy function, and the distribution field of the retardation factor is obtained based on the distribution coefficient.

[0116] The retardation factor distribution field is used to characterize the degree of lag or slippage of the pollutant carrier relative to water molecules.

[0117] In the pollution assessment method of this embodiment, the step of obtaining the physicochemical characteristic parameters of the pollution carrier and constructing the distribution field of the hindrance factor essentially establishes a quantitative relationship between microscopic interfacial chemical interactions and macroscopic solute transport behavior. In specific operations, firstly, the physicochemical properties of the target pollution carrier are measured using laboratory analysis methods to obtain its charge density and particle size parameters. These two parameters are intrinsic factors determining the colloidal stability of the carrier in groundwater. Simultaneously, the formation electrochemical property model constructed in the previous step is invoked to extract the double-layer surface conductivity parameters (DMT) of each spatial grid point. Since the surface conductivity of the double layer directly reflects the double layer structure of the fracture wall, the surface conductivity parameters can be inverted into the Zeta potential distribution of the fracture wall using the classic Gouy-Chapman double layer theory formula. Thus, the electrochemical boundary conditions at both ends of the "carrier" and "wall" in the microscopic interaction system are obtained.

[0118] To quantify the microscopic force field experienced by the contaminant carrier near the fracture wall, a potential energy function needs to be constructed. This process introduces the DLVO (Derjaguin-Landau-Verwey-Overbeek) colloidal stability theory. This theory posits that the total interaction energy between colloidal particles (i.e., the contaminant carrier) and the solid surface (i.e., the fracture wall) is the superposition of van der Waals attraction potential and electrostatic double-layer interaction potential. Based on this, the following microscopic interaction potential energy function is constructed:

[0119] ;

[0120] In the formula, This represents the total potential energy of microscopic interactions.

[0121] h represents the separation distance between the surface of the contaminant carrier and the crack wall;

[0122] This is the electrostatic double-layer repulsive potential energy. It can be understood that this term is calculated based on the charge density parameter of the carrier (or its corresponding Zeta potential) and the Zeta potential distribution on the fracture wall. When like charges (such as the common negatively charged microplastics and negatively charged rock surfaces) approach each other, this term is positive, acting as a repulsive energy barrier, preventing the carrier from approaching the wall.

[0123] The attraction potential energy for De Waals depends on the Hamaker constant of the material. This constant is usually obtained from a physical chemistry handbook based on the carrier material (such as polyethylene) and the rock mineral composition (such as quartz or clay). This term is usually negative and represents an attraction effect, causing the carrier to be adsorbed and retained by the wall.

[0124] After obtaining the total potential energy curve, in order to convert this microscopic energy into macroscopic transport parameters, it is necessary to further calculate the distribution coefficient. The distribution coefficient, from the perspective of statistical mechanics, describes the probability density distribution of the carrier appearing on the fracture cross-section. Therefore, the following formula for calculating the distribution coefficient is constructed:

[0125] ;

[0126] In the formula, The distribution coefficient is a dimensionless parameter, and its physical meaning is the ratio of the average concentration of the carrier in the fracture to the concentration in the mainstream region of the pore center.

[0127] b is the half-pore diameter of the fracture, which is derived from the pore geometry parameters or characteristic length obtained in the previous inversion step;

[0128] Boltzmann's constant;

[0129] T represents absolute temperature.

[0130] It is understandable that the above expression integrates the Boltzmann factor over the entire fracture cross section to comprehensively evaluate the average existence state of the carrier in the entire channel. If the repulsive potential energy is large, the integral result will be less than 1, which means that the carrier is "squeezed" to the central region with the fastest flow velocity, resulting in velocity gain. If the attractive potential energy dominates, the integral result may be greater than 1, which means that the carrier tends to be adsorbed on the wall, resulting in hysteresis.

[0131] Finally, to directly serve macro-risk assessment, the final hindrance factor distribution field is generated using the allocation coefficients. The hindrance factor is a key coefficient for correcting the Darcy flow velocity, and its calculation formula is as follows:

[0132] ;

[0133] In the formula, It is a blocking factor;

[0134] The bulk density of the medium;

[0135] θ represents the effective porosity.

[0136] Understandably, using the above expression, a specific retardation factor can be calculated for each grid cell within the assessment area. When it is less than 1, it indicates that the micro-nano plastic carrier undergoes "slippage" due to strong electrostatic repulsion, and its migration speed will exceed the groundwater flow rate. When it is greater than 1, it indicates that the carrier is subject to adsorption retardation, and its migration speed lags behind. The collection of these values ​​in space constitutes the retardation factor distribution field, providing a physical basis for subsequent accurate simulation of the asynchronous transport of pollutant carriers.

[0137] In this embodiment, the steps of obtaining hydrogeological parameters, constructing a Darcy velocity field for groundwater based on the hydrogeological parameters, and obtaining the migration velocity field of the contaminant carrier by combining the retardation factor distribution field include the following sub-steps:

[0138] Obtain the hydraulic gradient parameters and matrix permeability parameters of the underground aquifer;

[0139] The Darcy velocity field of groundwater is calculated based on hydraulic gradient parameters and matrix permeability parameters. The Darcy velocity field of groundwater is used to characterize the average flow velocity of solutes in an ideal porous medium.

[0140] The corrected carrier velocity vector is obtained by calculating the ratio between the velocity vector in the Darcy velocity field of groundwater and the resistance value in the resistance factor distribution field.

[0141] The entire space grid is traversed and corrected to obtain the migration velocity field of the pollutant carrier.

[0142] It should be noted that, in this embodiment, the step of obtaining hydrogeological parameters, constructing a Darcy velocity field for groundwater based on the hydrogeological parameters, and obtaining the migration velocity field of the pollutant carrier by combining the distribution field of the retardation factor is the core process of coupling the microscopic electrochemical retardation effect obtained in the previous step with the macroscopic hydrodynamic transport mechanism. Its fundamental purpose is to correct the traditional solute transport model, and advance from simply describing how water flows to describing how pollutants carried by micro-nano plastic particles flow.

[0143] In practice, the basic hydrogeological parameters of the study area must first be obtained. Hydraulic head measurements are then performed using a network of groundwater monitoring wells deployed on-site. Finally, the hydraulic gradient parameters for the entire area (denoted as ) are obtained through Kriging interpolation. Simultaneously, by combining data from pumping or injection tests, as well as laboratory permeability tests on core samples, the matrix permeability parameters of the aquifer medium (denoted as ) are obtained. Furthermore, the effective porosity parameter (θ) obtained through full-spectrum excited polarization inversion in the steps of this embodiment is directly used to ensure the consistency of the hydrodynamic model and the electrochemical model in terms of medium properties.

[0144] Based on the above parameters, a Darcy velocity field for groundwater needs to be constructed to describe the average flow behavior of groundwater solutes in an ideal porous medium. This process is based on the modified Darcy's law, and the following formula for calculating the average linear velocity is constructed:

[0145] ;

[0146] In the formula, This is the Darcy velocity vector for groundwater.

[0147] After obtaining the background velocity field, the next crucial step is to nonlinearly correct this velocity field using electrochemical retardation properties, thereby obtaining the migration velocity field of the contaminant carrier. The system will then call upon the retardation factor distribution field (containing the full-space grid) generated in the previous steps. The Darcy velocity field of groundwater is traversed point by point to construct the following formula for correcting the carrier migration velocity:

[0148] ;

[0149] In the formula, This represents the migration velocity vector of the contaminant carrier.

[0150] Understandably, by traversing and correcting the entire space grid, the system ultimately generates a pollution carrier migration velocity field containing three-dimensional spatial coordinates and corresponding velocity vectors. In this velocity field, for regions with high surface charge density, narrow pore structure, and strong electrostatic repulsion (i.e., dominant channels), the velocity vector magnitude will be significantly greater than the background water flow velocity; while for regions exhibiting strong van der Waals adsorption, the velocity vector magnitude will approach zero. This velocity field, corrected by electrochemical-hydrodynamic dual coupling, provides a kinetic basis consistent with physical facts for subsequent accurate simulation of pollutant escape paths and penetration times.

[0151] In this embodiment, the step of performing streamline tracing simulation based on the migration velocity field to obtain the escape path and penetration time of the contaminant carrier includes the following sub-steps:

[0152] Define the set of pollution source locations and the set of downstream boundaries;

[0153] In the migration velocity field, multiple potential migration trajectories emanating from the set of pollution source locations are obtained based on the streamline tracing algorithm;

[0154] The cumulative penetration time of a potential migration trajectory is obtained by integrating the reciprocal of the migration velocity along each potential migration trajectory.

[0155] The trajectory with the shortest cumulative penetration time was selected as the escape path of the pollutant carrier, and the shortest cumulative penetration time was taken as the final penetration time.

[0156] The above process no longer relies on traditional empirical formulas for estimation. Instead, it uses a Lagrange perspective from fluid mechanics to numerically track the entire lifecycle of thousands of virtual particles representing pollution carriers. This allows for the precise identification of rapid leakage channels that are easily overlooked in complex geological media. Specifically, it requires defining boundary conditions in the numerical model space and, based on the landfill's engineering design drawings and hydrogeological survey boundaries, defining the set of pollution source locations (denoted as...). ) and downstream boundary set (denoted as In this context, the pollution source location set is typically defined as a high-risk area for landfill geomembrane damage or a fully covered area at the bottom of the reservoir, while the downstream boundary set is defined as the geometric plane where environmental protection targets (such as village wells or river sections) are located.

[0157] Subsequently, in the constructed pollution carrier migration velocity field, a high-precision streamline tracing is performed using the fourth-order Runge-Kutta algorithm or the Euler iterative algorithm. The algorithm takes each grid node in the pollution source location set as the starting point and iterates stepwise according to the instantaneous velocity vector direction at that point, thereby drawing multiple potential migration trajectories. To describe this physical process, the following trajectory differential equation is constructed:

[0158] ;

[0159] In the formula, The spatial position vector of the virtual particle;

[0160] t represents the evolution time, which is the independent variable during the tracking process;

[0161] This represents the migration velocity vector of the contaminant carrier.

[0162] After obtaining multiple geometric trajectories (denoted as...) After (where k is the trajectory number), it is necessary to further calculate the cumulative penetration time corresponding to each trajectory. This is a key step in converting spatial distance into a time dimension. For this purpose, the following path integral formula is constructed:

[0163] ;

[0164] In the formula, Let be the cumulative penetration time of the k-th potential migration trajectory;

[0165] This is the integration path, i.e., the k-th geometric curve generated by the above trajectory differential equation;

[0166] s represents the differential unit of arc length along the trajectory;

[0167] The magnitude of the carrier migration velocity vector is obtained by interpolating the coordinates of the path in the migration velocity field. The larger this value is (e.g. in the dominant fissure channel), the smaller the integrand and the shorter the contribution time increment. Conversely, if the carrier is trapped in a high adsorption region (velocity approaches 0), the time increment will tend to infinity.

[0168] Finally, the system filters and makes decisions on all simulated trajectories and their corresponding cumulative penetration times, selecting the best ones from tens of thousands of simulation results based on the principle of risk conservatism. The trajectory with the smallest numerical value is defined as the escape path of the contaminant, and its corresponding... This is the final penetration time.

[0169] In this embodiment, obtaining the target monitoring well deployment coordinates and environmental risk warning level based on the escape path and penetration time includes the following sub-steps:

[0170] Obtain the intersection point of the escape path and the downstream boundary set, and determine the three-dimensional spatial coordinates of the intersection point as the deployment coordinates of the targeted monitoring well;

[0171] Obtain the design and control response cycle of the landfill;

[0172] The penetration time is compared with the designed prevention and control response cycle to obtain the carrier penetration risk index;

[0173] The environmental risk warning level is determined based on the numerical range of the carrier penetration risk index.

[0174] In the above steps, regarding the determination of the coordinates of the targeted monitoring wells, the system performs a spatial geometric intersection operation. In the previous steps, the escape path with the shortest cumulative penetration time (denoted as the geometric curve) has already been selected. Meanwhile, during the model initialization phase, a set of downstream boundaries representing environmental protection targets or groundwater compliance points was defined. Using spatial analytical geometry algorithms, the curves were calculated. With curved surfaces The precise intersection point is used to lock the three-dimensional spatial coordinate vector (x, y, z) of this intersection point as the coordinates for the deployment of targeted monitoring wells. Deploying the filter pipe section of the monitoring well at this location can intercept the first wave of high-concentration pollutants with the highest probability, thus avoiding the risks of missed detection or dilution that may exist with traditional grid-based monitoring methods.

[0175] Subsequently, to quantify the urgency of assessing environmental risks, a time-dimensional evaluation indicator was introduced. The system first obtained the design prevention and control response cycle of the landfill (denoted as...). This parameter is typically determined based on the design life of the landfill's seepage prevention system, the construction period of the emergency interception wall, or the emergency response time limit stipulated by the local environmental protection department. Next, the final penetration time calculated in the previous steps ( To achieve normalized quantitative risk classification, a formula for calculating the carrier penetration risk index is constructed by comparing the risk with the designed prevention and control response cycle:

[0176] ;

[0177] In the formula, The risk index is used as a carrier to penetrate.

[0178] It should be noted that in the above expression, the simple absolute time (e.g., "arriving in 100 days") lacks a discriminative standard and cannot directly reflect the severity of the risk. For a temporary storage site with a design life of only 50 days, 100 days is safe; however, for a sudden leak requiring immediate response, 100 days may be too long. This formula, by introducing the design period as a benchmark, constructs a dimensionless relative index that can intuitively reflect the game relationship between "pollution arrival speed" and "engineering control capabilities." The formula as a whole measures the time margin for the pollutant to breach the defense line; the smaller the exponent, the narrower the response window for managers, and the higher the environmental risk.

[0179] Finally, based on the calculated carrier penetration risk index To determine the final environmental risk warning level, the system has a built-in risk classification threshold logic: when When <1, it means < This means that the contaminant will penetrate the defenses and reach downstream sensitive targets before engineering control measures take effect or before the end of the anti-seepage system's design life. This situation indicates that existing barrier measures cannot meet safety requirements, and the system will issue a red high-risk warning, suggesting the immediate activation of emergency blocking procedures or increased monitoring frequency.

[0180] When 1≤ When the value is less than S (S is the preset safety factor, usually 1.5 or 2.0), it indicates that although it has not theoretically penetrated, the time margin is insufficient, and there is a possibility of premature leakage due to geological uncertainties. The system judges this as an orange medium-risk warning.

[0181] when When the value is ≥S, it indicates that the pollutant migration is extremely slow and the site is safe within the design cycle. The system determines this as a green low-risk warning. Through this quantitative classification, the assessment method achieves dynamic and precise monitoring of the entire life cycle of the landfill.

[0182] Example 2:

[0183] As attached Figure 2 As shown, this embodiment provides a pollution assessment system, the system comprising:

[0184] An electrochemical modeling module is used to acquire full-spectrum excitation polarization data of the landfill area and construct a formation electrochemical property model based on the full-spectrum excitation polarization data. The formation electrochemical property model is used to describe the surface conductivity and polarization characteristics of the underground medium at different frequencies.

[0185] The retardation calculation module is used to obtain the physicochemical characteristic parameters of the pollutant carrier and obtain the retardation factor distribution field based on the physicochemical characteristic parameters and the formation electrochemical property model.

[0186] A velocity field construction module is used to obtain hydrogeological parameters, construct a Darcy velocity field for groundwater based on the hydrogeological parameters, and obtain the migration velocity field of the pollutant carrier by combining the distribution field of the retardation factor.

[0187] The tracer simulation module is used to perform streamline tracer simulation based on the migration velocity field to obtain the escape path and penetration time of the pollutant carrier.

[0188] The analysis and evaluation module is used to obtain the coordinates of the targeted monitoring wells and the environmental risk warning level based on the escape path and penetration time.

[0189] It should be noted that the electrochemical modeling module, serving as the system's data foundation and inversion core, is primarily responsible for processing the raw signals from the front-end full-spectrum excited polarization detection array. This module is equipped with a high-throughput data interface, capable of receiving measured complex resistivity data covering a wide frequency range, and incorporates a complex resistivity relaxation inversion algorithm. During operation, the module extracts features from the phase response spectrum, automatically resolving the polarizability and time constant parameters characterizing the microstructure of the subsurface medium. Then, combined with a rock physics model, it calculates the specific surface area and surface conductivity of the fracture walls point-by-point. Finally, the module outputs a formation electrochemical property model containing three-dimensional spatial information, providing refined medium boundary conditions for subsequent microscopic force field calculations.

[0190] The retardation calculation module inherits the aforementioned electrochemical property model and is responsible for the macroscopic quantification of microscopic interfacial chemical interactions. This module obtains the physicochemical characteristic parameters of specific pollutant carriers (such as micro / nano plastic particles) through a user interface or database interface, focusing on charge density and particle size data. Based on the electric double layer theory and DLVO colloidal stability theory, this module constructs a microscopic interaction potential energy function within the system, calculates the electrostatic repulsion or van der Waals attraction potential energy between the carrier and the fracture walls at different spatial locations, and further solves for the distribution coefficient through probability integration. Finally, this module generates a full-field retardation factor distribution field, which quantifies the degree of motion lag or slippage of the pollutant carrier relative to water molecules in different geological units.

[0191] The velocity field construction module acts as a bridge between hydrodynamics and electrochemistry. This module first reads regional hydrogeological parameters, including hydraulic gradient and matrix permeability, and then uses a modified Darcy's law to construct a background groundwater velocity field, characterizing the average flow state of solutes in an ideal porous medium. Subsequently, this module calls the retardation factor distribution field output by the retardation calculation module to perform nonlinear correction on the background velocity field. Specifically, this module calculates the ratio between the velocity vector and the corresponding retardation factor at each spatial grid node, thereby reconstructing a realistic pollutant carrier migration velocity field. This velocity field reflects the high-speed penetration region caused by electrochemical repulsion and the low-speed retention region caused by adsorption.

[0192] Subsequently, the tracer simulation module performs spatiotemporal evolution simulation based on the constructed migration velocity field. This module incorporates streamline tracing algorithms (such as the fourth-order Runge-Kutta algorithm) to simulate the migration trajectories of thousands of virtual particles in a complex velocity field, starting from a predetermined pollution source location. By integrating the reciprocal of the velocity along the trajectory, the module accurately calculates the cumulative penetration time of each potential path. Based on the principle of maximizing risk, it automatically selects the trajectory with the shortest duration as the escape path for the pollution carrier and locks the corresponding shortest time as the final penetration time. This process enables the accurate identification of concealed high-flux leakage channels.

[0193] Example 3:

[0194] Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0195] Example 4:

[0196] Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer-readable storage medium storing a computer program, and a processor executes the computer program to implement the above-described method.

[0197] Furthermore, in one embodiment, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, implements the steps of the methods described in the foregoing embodiments.

[0198] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or it may be a device including one or any combination of the above-mentioned memories. The computer may be a variety of computing devices, including smart terminals and servers.

[0199] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0200] As an example, executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple collaborating files (e.g., a file that stores one or more modules, subroutines, or code sections).

[0201] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0202] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0203] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0204] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a multimedia terminal device (which may be a mobile phone, computer, television receiver, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0205] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A pollution assessment method for landfills, characterized in that, The method includes the following steps: Full-spectrum excitation polarization data of the landfill area are obtained, and a formation electrochemical property model is constructed based on the full-spectrum excitation polarization data. The formation electrochemical property model is used to describe the surface conductivity and polarization characteristics of the underground medium at different frequencies. Obtain the physicochemical characteristic parameters of the pollutant carrier, and obtain the distribution field of the blocking factor based on the physicochemical characteristic parameters and the formation electrochemical property model; Hydrogeological parameters were obtained, and a Darcy velocity field of groundwater was constructed based on the hydrogeological parameters. The migration velocity field of the pollutant carrier was obtained by combining the distribution field of the retardation factor. Streamline tracing simulations were performed based on the migration velocity field to obtain the escape path and penetration time of the contaminant carrier. The coordinates of the targeted monitoring wells and the environmental risk warning level are obtained based on the escape path and penetration time.

2. The pollution assessment method for a landfill as described in claim 1, characterized in that, The process of obtaining full-spectrum induced polarization data of the landfill area and constructing a formation electrochemical property model based on the full-spectrum induced polarization data includes the following sub-steps: Acquire complex resistivity data at different frequencies within the detection area, and extract the phase response spectrum based on the complex resistivity data; The phase response spectrum was inverted and fitted using the complex resistivity relaxation model to obtain the polarizability parameters and time constant parameters of the subsurface medium. An electrochemical mapping relationship is constructed based on polarizability parameters, time constant parameters, and preset pore geometry factors; The specific surface area and surface conductivity parameters of the fracture wall were obtained by analyzing the electrochemical mapping relationship. A formation electrochemical property model is constructed based on the specific surface area parameter and surface conductivity parameter.

3. The pollution assessment method for a landfill as described in claim 2, characterized in that, The process of obtaining the physicochemical characteristic parameters of the contaminant carrier and obtaining the distribution field of the retardation factor based on the physicochemical characteristic parameters and the formation electrochemical property model includes the following sub-steps: Obtain the charge density and particle size parameters of the contaminant carrier; The Zeta potential distribution on the fracture wall is obtained based on the surface conductivity parameters in the formation electrochemical property model. A potential energy function is constructed based on the charge density parameter of the contaminant and the Zeta potential distribution of the fissure wall. This potential energy function is used to quantify the interaction force between the contaminant and the fissure wall. The distribution coefficient is calculated based on the potential energy function, and the distribution field of the retardation factor is obtained based on the distribution coefficient. The retardation factor distribution field is used to characterize the degree of lag or slippage of the pollutant carrier relative to water molecules.

4. The pollution assessment method for a landfill as described in claim 1, characterized in that, The process of obtaining hydrogeological parameters, constructing a Darcy velocity field for groundwater based on these parameters, and combining this with a retardation factor distribution field to obtain a migration velocity field for contaminants includes the following sub-steps: Obtain the hydraulic gradient parameters and matrix permeability parameters of the underground aquifer; The Darcy velocity field of groundwater is calculated based on hydraulic gradient parameters and matrix permeability parameters. The Darcy velocity field of groundwater is used to characterize the average flow velocity of solutes in an ideal porous medium. The corrected carrier velocity vector is obtained by calculating the ratio between the velocity vector in the Darcy velocity field of groundwater and the resistance value in the resistance factor distribution field. The entire space grid is traversed and corrected to obtain the migration velocity field of the pollutant carrier.

5. The pollution assessment method for a landfill as described in claim 1, characterized in that, The step of performing streamline tracing simulation based on the migration velocity field to obtain the escape path and penetration time of the contaminant carrier includes the following sub-steps: Define the set of pollution source locations and the set of downstream boundaries; In the migration velocity field, multiple potential migration trajectories emanating from the set of pollution source locations are obtained based on the streamline tracing algorithm; The cumulative penetration time of a potential migration trajectory is obtained by integrating the reciprocal of the migration velocity along each potential migration trajectory. The trajectory with the shortest cumulative penetration time was selected as the escape path of the pollutant carrier, and the shortest cumulative penetration time was taken as the final penetration time.

6. The pollution assessment method for a landfill as described in claim 5, characterized in that, The process of obtaining the target monitoring well deployment coordinates and environmental risk early warning level based on the escape path and penetration time includes the following sub-steps: Obtain the intersection point of the escape path and the downstream boundary set, and determine the three-dimensional spatial coordinates of the intersection point as the deployment coordinates of the targeted monitoring well; Obtain the design and control response cycle of the landfill; The penetration time is compared with the designed prevention and control response cycle to obtain the carrier penetration risk index; The environmental risk warning level is determined based on the numerical range of the carrier penetration risk index.

7. The pollution assessment method for a landfill as described in claim 2, characterized in that, The inversion and fitting of the phase response spectrum based on the complex resistivity relaxation model includes the following sub-steps: Construct a theoretical model of Cole-Cole complex resistivity; Based on the nonlinear least squares algorithm, the model parameters are globally optimized with the goal of minimizing the mean square error between the measured phase response spectrum and the theoretical model output spectrum. When the mean square error is less than the preset convergence threshold, the current optimal parameter combination is output as the polarizability parameter and the time constant parameter.

8. A pollution assessment system, characterized in that, The system includes: An electrochemical modeling module is used to acquire full-spectrum excitation polarization data of the landfill area and construct a formation electrochemical property model based on the full-spectrum excitation polarization data. The formation electrochemical property model is used to describe the surface conductivity and polarization characteristics of the underground medium at different frequencies. The retardation calculation module is used to obtain the physicochemical characteristic parameters of the pollutant carrier and obtain the retardation factor distribution field based on the physicochemical characteristic parameters and the formation electrochemical property model. A velocity field construction module is used to obtain hydrogeological parameters, construct a Darcy velocity field for groundwater based on the hydrogeological parameters, and obtain the migration velocity field of the pollutant carrier by combining the distribution field of the retardation factor. The tracer simulation module is used to perform streamline tracer simulation based on the migration velocity field to obtain the escape path and penetration time of the pollutant carrier. The analysis and evaluation module is used to obtain the coordinates of the targeted monitoring wells and the environmental risk warning level based on the escape path and penetration time.

9. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

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