A landfill leakage detection method and system

Abstract

A method and system for detecting landfill leakage is disclosed. The method includes acquiring pollution and environmental data corresponding to the target landfill, calculating pollution tolerance assessment values ​​to obtain suitable sets of living plants, selecting the best living plants based on planting costs, deploying an array of indicator plants, collecting corresponding root electrophysiological signal data, calculating corresponding root electrophysiological assessment values, and comparing them with set root electrophysiological assessment thresholds to determine whether pollutant leakage has occurred. If pollution leakage occurs, the degree of leakage is analyzed, and an early warning is issued. The system includes a living plant selection and planting module, a real-time pollution leakage detection module, a real-time leakage detection and judgment module, and a database. Through multi-dimensional design, including constructing a plant root electrophysiological signal network, analyzing pollution tolerance assessment values, and optimizing planting costs, the system achieves early warning, accurate location, precise detection, and rapid emergency response.

Description

Technical Field

[0001] This invention relates to the field of landfill leakage detection technology, specifically to a landfill leakage detection method and system. Background Technology

[0002] As a primary method for disposing of urban solid waste, the integrity of landfill seepage prevention systems directly impacts the safety of surrounding soil, groundwater, and the atmospheric environment. Currently, traditional seepage detection technologies, such as physical detection, electrical detection, and geophysical methods, have numerous limitations. Therefore, a new type of seepage detection technology is needed that combines high sensitivity, strong environmental adaptability, and cost-effectiveness to address shortcomings in early warning, precise location, and eco-friendliness.

[0003] Currently, some technologies exist, such as the invention application patent with publication number CN103528763B, which discloses a method and device for detecting landfill leakage. This method involves setting up a temperature-measuring fiber optic mesh on the outside of the landfill, connecting it to a temperature-measuring host, detecting the temperature outside the landfill using the mesh, and sending the temperature signal to the host. The host then processes and fuses the temperature signals to obtain temperature detection data, which is transmitted to a data terminal. The data terminal compares the temperature detection data with normal temperature data to determine if the landfill is leaking. Finally, a heat source method is used to quantitatively analyze the temperature field at the leak location and calculate the leakage amount. In other words, temperature is used as a tracer quantity for investigating landfill leakage. By measuring the water temperature at different locations, leakage problems can be monitored and studied, and the coordinate data and leakage amount of abnormal temperature locations (leakage locations) can be accurately provided.

[0004] However, existing technologies have the following technical problems:

[0005] 1. Relying on physical drilling, manual sampling, or single-point sensor detection cannot capture early physiological signals of pollution leakage. For example, traditional soil heavy metal testing requires manual sampling followed by laboratory analysis, which takes 24-72 hours from sampling to obtaining results. During this period, the leaked pollutants may have already spread to an area of ​​more than 500 square meters. Although geophysical exploration methods can locate suspected leakage areas, the location error for deep leakage exceeds 5 meters, making it difficult to accurately pinpoint the leakage point.

[0006] 2. Traditional electrical testing methods require the laying of high-density electrode networks, with construction costs exceeding 300,000 yuan per hectare. Furthermore, cables are susceptible to damage from landfill settlement, and annual maintenance costs account for 20%-30% of the construction costs. Chemical tracer methods require tens of thousands of yuan worth of reagents for each test, and there is a risk of environmental pollution from the tracers themselves.

[0007] 3. The "threshold alarm" mode is often used, which cannot quantify the degree of leakage and match the response level. For example, the alarm is only triggered when the soil COD concentration exceeds the threshold, but it cannot distinguish between minor and severe leakage, resulting in either excessive investment of emergency resources or insufficient response.

[0008] In addition, traditional technologies can only monitor pollution and cannot simultaneously achieve ecological restoration. Furthermore, the long-term residue of leaked pollutants may lead to a chain of problems such as soil salinization and excessive heavy metals in groundwater.

[0009] Therefore, there is an urgent need to design a landfill leakage detection technology that provides timely early warning, accurate spatial positioning, precise and rapid leakage detection, does not cause secondary pollution during the detection process, and whose leakage level can be matched with the response level. Summary of the Invention

[0010] To address the technical problems of existing technologies, such as delayed early warning, crude spatial positioning, high detection costs, secondary pollution during the detection process, and inability to quantify the degree of leakage and match response levels, a landfill leakage detection method is provided, comprising the following steps:

[0011] Obtain pollution and environmental data corresponding to the target landfill, and calculate the pollution tolerance assessment value corresponding to the target landfill. The pollution data includes the concentrations of various heavy metals. Various types of organic matter The concentrations of the salts and the corresponding concentrations of each salt The environmental data includes soil pH, soil moisture, and temperature.

[0012] Based on the pollution tolerance assessment value range and the pollution tolerance assessment value The set of suitable living plants corresponding to the target landfill is obtained; by obtaining the planting cost of each suitable living plant in the set of suitable living plants, the optimal living plant for the target landfill is obtained.

[0013] Among them, the optimal living plant is the suitable living plant with the lowest planting cost;

[0014] The optimal live plant species are deployed in a planting indicator plant array. A detection time point q and a detection plant point y are set. Root electrophysiological signal data corresponding to the detection plant point y are collected based on the detection time point q, and the root electrophysiological evaluation value corresponding to the detection plant point y collected at the detection time point q is calculated. The root electrophysiological signal data includes resting membrane potential. Specific ion current ratio and rate of change of action potential frequency ;

[0015] Set a root electrophysiological evaluation threshold corresponding to a standard detection plant point y, and compare the root electrophysiological evaluation values. Based on the magnitude of the root electrophysiological assessment threshold, it is determined whether pollutant leakage has occurred at each detection plant point y collected at each detection time point q; if pollutant leakage is determined to have occurred, the degree of leakage corresponding to each detection plant point y collected at each detection time point q is analyzed and an early warning is issued.

[0016] Among them, when the root electrophysiological assessment value When the value exceeds the root electrophysiological assessment threshold, it is determined that a contaminant leakage has occurred.

[0017] Furthermore, the pollution tolerance assessment value corresponding to the target landfill The calculation method includes the following:

[0018] Based on the pollution data and environmental data, calculate the pollution data fit value corresponding to the target landfill. and corresponding environmental data adaptation values ;

[0019] Based on the pollution data adaptation value Adaptation values ​​for environmental data The pollution tolerance assessment value corresponding to the target landfill was calculated. .

[0020] Furthermore, the pollution data adaptation value corresponding to the target landfill The calculation formula is expressed as:

[0021] ;

[0022] Where h represents the code corresponding to each type of heavy metal. , It is a positive integer; This represents the collection of various types of heavy metals, and g represents the corresponding number of various types of organic compounds. , It is a positive integer; It represents a collection of various types of organic matter. This indicates the corresponding number for each type of salt. , It is a positive integer; This represents the collection of all salts.

[0023] Furthermore, the environmental data adaptation value corresponding to the target landfill The calculation method is adapted to the pollution data corresponding to the target landfill. The calculation method is the same.

[0024] Furthermore, the pollution tolerance assessment value corresponding to the target landfill The calculation formula is expressed as:

[0025] .

[0026] Furthermore, the planting deployment process includes the following:

[0027] Based on the landfill's layout plan and pollution concentration gradient distribution map, the landfill was divided into a core monitoring area, a secondary monitoring area, and a control area.

[0028] In the core monitoring area, the best living plants are planted in a grid pattern with a spacing of 2×2 meters. A flexible microelectrode array is buried in the center of each grid, and the electrodes are kept at a specified contact distance with the plant roots.

[0029] The planting spacing in the secondary monitoring area has been expanded to 4×4 meters. The same grid planting layout is adopted. Multiple flexible microelectrodes are symmetrically buried around the roots of each plant to form a ring monitoring structure. The electrodes are kept at a specified distance from the plant roots.

[0030] The planting spacing in the control area was increased to 6×6 meters, and the same grid planting layout was adopted. Two flexible microelectrodes were buried in parallel near the roots of each plant, and the electrodes were kept at a specified distance from the plant roots.

[0031] Furthermore, the root electrophysiological assessment values The calculation formula is expressed as:

[0032] ;

[0033] Where q represents the number corresponding to each detection time point. , It is a positive integer; y represents the set of all detection time points; y represents the number corresponding to each detection plant point. , It is a positive integer; This represents the collection of all detected plant sites; and These represent the mean and standard deviation of the resting membrane potential corresponding to the plant point y under normal conditions. Let y be the standard specific ion current ratio corresponding to the set detection plant point y, and e be the natural constant.

[0034] Furthermore, the specific analysis method for analyzing the leakage degree corresponding to each detection plant point y collected at each detection time point q includes the following:

[0035] When the root electrophysiological assessment value If the leakage rate is within 5% of the root electrophysiological assessment threshold, then the leakage rate corresponding to the detection plant point y collected at the detection time point q is considered slight.

[0036] When the root electrophysiological assessment value If the percentage of the root electrophysiological assessment threshold is greater than 5% but less than 10%, then the leakage level corresponding to the detection plant point y collected at the detection time point q is moderate.

[0037] When the root electrophysiological assessment value If the leakage rate is greater than 10% above the root electrophysiological assessment threshold, then the leakage rate corresponding to the detection plant point y collected at the detection time point q is considered severe.

[0038] The present invention also provides a landfill leakage detection system, which is implemented using the landfill leakage detection method described above. The system includes a live plant selection and planting module, a real-time pollution leakage detection module, a real-time leakage detection and judgment module, and a database.

[0039] The database is used to store the pollution tolerance assessment value ranges corresponding to each suitable living plant.

[0040] The live plant selection and planting module is used to acquire pollution data, environmental data, and planting costs of suitable live plants for the target landfill, and to calculate the pollution tolerance assessment value for the target landfill. The system obtains the set of suitable living plants corresponding to the target landfill and the optimal living plant corresponding to the target landfill, and sends the optimal living plant corresponding to the target landfill to the real-time pollution leakage detection module.

[0041] The real-time pollution leakage detection module is used to receive the optimal live planting plants corresponding to the target landfill from the live plant screening and planting module, deploy the planting indicator plant array, collect root electrophysiological signal data corresponding to the detection plant point y, and calculate the root electrophysiological evaluation value corresponding to the detection plant point y collected at the detection time point q. The root electrophysiological assessment value is sent to the real-time leakage detection and judgment module. ;

[0042] The real-time leakage detection and judgment module is used to receive the root electrophysiological assessment values ​​transmitted by the real-time pollution leakage detection module. The system compares the data with the root electrophysiological assessment threshold corresponding to the standard detection plant point y to determine whether pollutant leakage has occurred at each detection plant point y collected at each detection time point q. If pollutant leakage is determined to have occurred, the degree of leakage is analyzed and an early warning is issued.

[0043] Furthermore, the warning notification process includes the following:

[0044] When the leakage is minor, a low-level audible and visual warning is triggered, marking the leakage point with a flashing yellow icon, and simultaneously pushing the warning information to the user account of the maintenance personnel; after receiving the information, the maintenance personnel must go to the site to verify within 24 hours; the warning information includes the detection time, plant point coordinates, leakage level and current leakage stage;

[0045] When the leakage level is moderate, a moderate-level audible and visual warning is triggered, the leakage point is marked with an orange highlighted icon, and the corresponding warning information is simultaneously pushed to the user account of the operation and maintenance team via SMS, email and system pop-up. After receiving the information, the operation and maintenance team must rush to the site within 4 hours, start the emergency pumping equipment, and set up a temporary anti-seepage isolation zone around the leakage point.

[0046] When the leakage becomes severe, the highest level of audible and visual warning will be triggered, immediately issuing a red alert accompanied by a sharp, continuous alarm sound. At the same time, the warning information will be pushed to the user accounts of the emergency response team. The emergency response team must be fully staffed within 1 hour, initiate emergency lockdown measures for the entire area, deploy professional pollution treatment equipment, and intercept, collect, and render harmless the leaked pollutants. Simultaneously, a pollution warning notice will be issued to the communities surrounding the landfill.

[0047] The beneficial effects of this invention are:

[0048] (1) By transforming living plants into distributed biosensors, a "plant root electrophysiological signal network" was constructed for the first time, breaking through the limitations of traditional physical / chemical detection technologies. By utilizing the physiological stress response of plants to pollutants, such as changes in membrane potential and ion flow, early warning can be achieved, capturing signs of leakage 2-8 hours earlier than traditional sensors. Combined with a flexible microelectrode array planted in a 2×2 meter grid pattern in the core area, a high-density monitoring network is formed, improving the leakage location accuracy to ±0.5 meters, solving the technical problems of delayed early warning and rough spatial positioning in existing technologies.

[0049] (2) An innovative quantitative matching model of "pollution data-environmental data-plant tolerance" was established. Through the pollution tolerance assessment value analysis module and the planting cost optimization strategy, the plant selection was made more precise and less costly. The multi-dimensional data such as heavy metal concentration and soil pH were normalized and processed. The pollution tolerance assessment value was calculated by combining machine learning algorithm. After matching the plant tolerance range in the database, the species with the best cost performance were selected. Compared with genetically modified plants, the planting cost was greatly reduced. At the same time, the selected living plants have both pollution monitoring and ecological restoration capabilities. The low-power network monitoring of each detection plant point was realized, and an innovative technical path of "high sensitivity monitoring-low cost implementation" was constructed.

[0050] (3) Through the design of the landfill leakage detection system, a three-level leakage degree quantitative standard and corresponding early warning mechanism are created. The leakage detection, degree judgment and emergency response are timely and accurate, which greatly shortens the pollution control time. At the same time, the indicator plants have both pollution monitoring and ecological restoration functions. The flexible microelectrodes are implanted with biocompatible materials in a minimally invasive manner to avoid secondary pollution. A full-chain innovation system of "real-time monitoring - accurate early warning - ecological restoration" is formed, which provides a model of interdisciplinary technology integration for the field of environmental monitoring. Attached Figure Description

[0051] Figure 1 This is a flowchart of the landfill leakage detection method provided by the present invention;

[0052] Figure 2 This is a diagram of the landfill leakage detection system architecture provided by the present invention. Detailed Implementation

[0053] The technical solution of the present invention is further described below, but the scope of protection is not limited to what is described.

[0054] This invention provides a method for detecting leakage in landfills, such as... Figure 1 As shown, it includes the following steps:

[0055] Step S100: Obtain pollution data and environmental data corresponding to the target landfill, and calculate the pollution tolerance assessment value corresponding to the target landfill. The pollution data includes the concentrations of various heavy metals. Various types of organic matter The concentrations of the salts and the corresponding concentrations of each salt The environmental data includes soil pH, soil moisture, and temperature.

[0056] The pollution tolerance assessment value corresponding to the target landfill The calculation method includes the following:

[0057] Based on the pollution data and environmental data, calculate the pollution data fit value corresponding to the target landfill. and corresponding environmental data adaptation values ;

[0058] Based on the pollution data adaptation value Adaptation values ​​for environmental data The pollution tolerance assessment value corresponding to the target landfill was calculated. .

[0059] The pollution data adaptation value corresponding to the target landfill The calculation formula is expressed as:

[0060] (1)

[0061] Where h represents the code corresponding to each type of heavy metal. , It is a positive integer; This represents the collection of various types of heavy metals, and g represents the corresponding number of various types of organic compounds. , It is a positive integer; It represents a collection of various types of organic matter. This indicates the corresponding number for each type of salt. , It is a positive integer; This represents the collection of all salts.

[0062] The environmental data adaptation value corresponding to the target landfill The calculation method is adapted to the pollution data corresponding to the target landfill. The calculation method is the same.

[0063] The pollution tolerance assessment value corresponding to the target landfill The calculation formula is expressed as:

[0064] (2)

[0065] The pollution tolerance assessment value corresponding to the target landfill The acquisition process is as follows:

[0066] Obtain the pollution and environmental data corresponding to the target landfill, normalize the pollution and environmental data, and then calculate the pollution and environmental data adaptation values ​​for the target landfill respectively.

[0067] During pollution data collection, portable X-ray fluorescence spectrometers can be used to rapidly determine the concentrations of heavy metals such as cadmium and lead in the soil; gas chromatography-mass spectrometry (GC-MS) can be used to analyze organic compounds such as benzene series and polycyclic aromatic hydrocarbons; and conductivity meters combined with ion chromatography can be used to detect salt concentrations. Simultaneously, sampling points are deployed in different areas of the landfill. Deep soil samples are obtained through drilling, while shallow soil samples are collected from multiple points on the surface using a mixed sampling method. Leachate is extracted periodically through pre-buried sampling wells. For environmental data acquisition, soil pH and humidity can be monitored in real time using a wireless sensor network. Sensor probes are buried in the plant root layer and automatically upload data every 15 minutes. Temperature data is measured using infrared thermal imaging combined with thermocouple sensors, covering the entire landfill area to ensure the spatiotemporal continuity and accuracy of environmental parameters.

[0068] The process of obtaining the pollution data adaptation values ​​corresponding to the target landfill is as follows: the concentrations of various heavy metals, various organic compounds, and various salts corresponding to the target landfill are respectively denoted as... , and Where h represents the code corresponding to each type of heavy metal. , It is a positive integer. It also represents a collection of various types of heavy metals, where g represents the corresponding number for each type of organic compound. , It is a positive integer. It is also a collection of various types of organic matter. This indicates the corresponding number for each type of salt. , It is a positive integer. Furthermore, by substituting the collection of each salt into the calculation formula (1), the pollution data adaptation value corresponding to the target landfill is obtained. Then, according to the pollution data adaptation values... The calculation method is used to obtain the environmental data adaptation value corresponding to the target landfill. .

[0069] Then, adapt the pollution data corresponding to the target landfill. Adaptation values ​​for environmental data After normalization, the pollution tolerance assessment value corresponding to the target landfill is calculated. .

[0070] Step S200: Based on the pollution tolerance assessment value range and the pollution tolerance assessment value The set of suitable living plants corresponding to the target landfill is obtained; by obtaining the planting cost of each suitable living plant in the set of suitable living plants, the optimal living plant for the target landfill is obtained.

[0071] Among them, the optimal living plant is the suitable living plant with the lowest planting cost;

[0072] The process of obtaining the appropriate collections of living plants corresponding to the target landfill is as follows: Obtain the pollution tolerance assessment value corresponding to the target landfill. and the corresponding pollution tolerance assessment value for the target landfill. Compare with the corresponding pollution tolerance assessment value range, if the pollution tolerance assessment value corresponding to the target landfill is... If the plant is located within the corresponding pollution tolerance assessment range, then the suitable living plant is recorded as the suitable living plant corresponding to the target landfill. This leads to the acquisition of each suitable living plant corresponding to the target landfill, and each suitable living plant corresponding to the target landfill is used as the initial set of suitable living plants corresponding to the target landfill.

[0073] Suitable living plants for the target landfill include: 1) Suaeda salsa: salt- and alkali-tolerant, heavy metal-tolerant, can grow in areas with high salinity leachate, and its roots are sensitive to changes in ion concentration. 2) Artemisia argyi: highly adaptable, tolerant of various pollutants, its root secretions can improve soil, and it has high stability of electrophysiological signals. 3) Hybrid Napier grass: rapid growth, large biomass, deep and extensive root system, strong tolerance to comprehensive pollution, low cost and easy to cultivate.

[0074] The proposed system is suitable for living plant collections that can adapt to complex environments with multiple pollutants, making it suitable for landfills with diverse pollutant components.

[0075] The process for obtaining the optimal living plant material corresponding to the target landfill is as follows:

[0076] Obtain the planting cost of each suitable living plant in the set of suitable living plants for the target landfill, and arrange the planting costs of each suitable living plant in the set of suitable living plants for the target landfill in descending order. Then, select the suitable living plant with the lowest planting cost in the set of suitable living plants for the target landfill as the best living plant for the target landfill.

[0077] Step S300: Deploy the optimal live plant in the planting indicator plant array, set the detection time point q and the detection plant point y, collect root electrophysiological signal data corresponding to the detection plant point y according to the detection time point q, and calculate the root electrophysiological evaluation value corresponding to the detection plant point y collected at the detection time point q. The root electrophysiological signal data includes resting membrane potential. Specific ion current ratio and rate of change of action potential frequency The detection time point q is several;

[0078] The planting deployment process includes the following:

[0079] Based on the landfill's layout plan and pollution concentration gradient distribution map, the landfill was divided into a core monitoring area, a secondary monitoring area, and a control area.

[0080] In the core monitoring area, the best living plants are planted in a grid pattern with a spacing of 2×2 meters. A flexible microelectrode array is buried in the center of each grid, and the electrodes are kept at a specified contact distance with the plant roots.

[0081] The planting spacing in the secondary monitoring area has been expanded to 4×4 meters. The same grid planting layout is adopted. Multiple flexible microelectrodes are symmetrically buried around the roots of each plant to form a ring monitoring structure. The electrodes are kept at a specified distance from the plant roots.

[0082] The planting spacing in the control area was increased to 6×6 meters, and the same grid planting layout was adopted. Two flexible microelectrodes were buried in parallel near the roots of each plant, and the electrodes were kept at a specified distance from the plant roots.

[0083] The root electrophysiological assessment value The calculation formula is expressed as:

[0084] (3)

[0085] Where q represents the number corresponding to each detection time point. , It is a positive integer; y represents the set of all detection time points; y represents the number corresponding to each detection plant point. , It is a positive integer; This represents the collection of all detected plant sites; and These represent the mean and standard deviation of the resting membrane potential corresponding to the plant point y under normal conditions. Let y be the standard specific ion current ratio corresponding to the set detection plant point y, and e be the natural constant.

[0086] The root electrophysiological evaluation value corresponding to the detection plant point y is collected at the detection time point q. The acquisition process is as follows:

[0087] At each detection time point q, root electrophysiological signal data corresponding to each detection plant point y were collected and normalized. Simultaneously, the data were substituted into the root electrophysiological evaluation value analysis model calculation formula (3) to obtain the root electrophysiological evaluation value corresponding to each detection plant point y at each detection time point q. .

[0088] When collecting root electrophysiological signal data at various detection time points q, minimally invasive and precise measurements are achieved using a flexible microelectrode array and a high-sensitivity sensing system. Specifically, flexible gold nanowire electrodes on a polyimide substrate are implanted into the root epidermis at a distance of 2-5 cm from the core area and 3-6 cm from the secondary area during plant planting. The electrodes are connected to a differential amplifier via an impedance matching circuit to collect the resting membrane potential in real time. For specific ion current ratios, non-invasive microelectrode technology is used to deploy Na+ nanowires at a depth of 20 μm on the root surface. + K + Ca2+ Plasma-selective electrodes calculate Na by measuring ion current density. + / K + Ca 2+ / H + The action potential frequency is extracted using a lock-in amplifier to capture signal characteristics, and the membrane potential depolarization event is recorded at a sampling rate of 10kHz to obtain the frequency change rate per unit time. All signals are then bandpass filtered and converted from analog to digital before being transmitted to the central processing system via a LoRa wireless module to form a time-series database. Non-destructive microelectrode technology is a current technology.

[0089] The analysis process for the root electrophysiological assessment values ​​corresponding to each detection time point q and each detection plant point y is as follows: The resting membrane potential, specific ion current ratio, and action potential frequency change rate corresponding to each detection time point q and each detection plant point y are respectively denoted as... , and Where q represents the number corresponding to each detection time point. , It is a positive integer. This also represents the collection of data from all detection time points, where y represents the corresponding number of each detection plant point. , It is a positive integer. Furthermore, by substituting the sum of all detected plant sites into the calculation formula (3), the root electrophysiological assessment values ​​corresponding to each detected plant site at each detection time point are obtained. ,in, and These represent the mean and standard deviation of the resting membrane potential at the plant sites under normal conditions. The standard specific ion current ratio corresponding to the set detection plant point is given by e, which represents the natural constant.

[0090] Step S400: Set the root electrophysiological evaluation threshold corresponding to the standard detection plant point y, and compare the root electrophysiological evaluation values. Based on the magnitude of the root electrophysiological assessment threshold, it is determined whether pollutant leakage has occurred at each detection plant point y collected at each detection time point q; if pollutant leakage is determined to have occurred, the degree of leakage corresponding to each detection plant point y collected at each detection time point q is analyzed and an early warning is issued.

[0091] Among them, when the root electrophysiological assessment value When the value exceeds the root electrophysiological assessment threshold, it is determined that a contaminant leakage has occurred.

[0092] When the root electrophysiological assessment value If the value is less than or equal to the root electrophysiological assessment threshold, it is determined that no contaminant leakage has occurred.

[0093] The specific analysis method for analyzing the leakage degree corresponding to each detection plant point y collected at each detection time point q includes the following:

[0094] When the root electrophysiological assessment value If the leakage rate is within 5% of the root electrophysiological assessment threshold, then the leakage rate corresponding to the detection plant point y collected at the detection time point q is considered slight.

[0095] When the root electrophysiological assessment value If the percentage of the root electrophysiological assessment threshold is greater than 5% but less than 10%, then the leakage level corresponding to the detection plant point y collected at the detection time point q is moderate.

[0096] When the root electrophysiological assessment value If the leakage rate is greater than 10% above the root electrophysiological assessment threshold, then the leakage rate corresponding to the detection plant point y collected at the detection time point q is considered severe.

[0097] This invention also provides a landfill leakage detection system, implemented using the aforementioned landfill leakage detection method, such as... Figure 2 As shown, the system includes a live plant screening and planting module, a real-time pollution leakage detection module, a real-time leakage detection and judgment module, and a database;

[0098] The database is used to store the pollution tolerance assessment value ranges corresponding to each suitable living plant.

[0099] The live plant selection and planting module is used to acquire pollution data, environmental data, and planting costs of suitable live plants for the target landfill, and to calculate the pollution tolerance assessment value for the target landfill. The system obtains the set of suitable living plants corresponding to the target landfill and the optimal living plant corresponding to the target landfill, and sends the optimal living plant corresponding to the target landfill to the real-time pollution leakage detection module.

[0100] The real-time pollution leakage detection module is used to receive the optimal live planting plants corresponding to the target landfill from the live plant screening and planting module, deploy the planting indicator plant array, collect root electrophysiological signal data corresponding to the detection plant point y, and calculate the root electrophysiological evaluation value corresponding to the detection plant point y collected at the detection time point q. The root electrophysiological assessment value is sent to the real-time leakage detection and judgment module. ;

[0101] The real-time leakage detection and judgment module is used to receive the root electrophysiological assessment values ​​transmitted by the real-time pollution leakage detection module. The system compares the data with the root electrophysiological assessment threshold corresponding to the standard detection plant point y to determine whether pollutant leakage has occurred at each detection plant point y collected at each detection time point q. If pollutant leakage is determined to have occurred, the degree of leakage is analyzed and an early warning is issued.

[0102] In this embodiment, the warning notification process includes the following:

[0103] When the leakage is minor, a low-level audible and visual warning is triggered, marking the leakage point with a flashing yellow icon, and simultaneously pushing the warning information to the user account of the maintenance personnel; after receiving the information, the maintenance personnel must go to the site to verify within 24 hours; the warning information includes the detection time, plant point coordinates, leakage level and current leakage stage;

[0104] When the leakage level is moderate, a moderate-level audible and visual warning is triggered, the leakage point is marked with an orange highlighted icon, and the corresponding warning information is simultaneously pushed to the user account of the operation and maintenance team via SMS, email and system pop-up. After receiving the information, the operation and maintenance team must rush to the site within 4 hours, start the emergency pumping equipment, and set up a temporary anti-seepage isolation zone around the leakage point.

[0105] When the leakage becomes severe, the highest level of audible and visual warning will be triggered, immediately issuing a red alert accompanied by a sharp, continuous alarm sound. At the same time, the warning information will be pushed to the user accounts of the emergency response team. The emergency response team must be fully staffed within 1 hour, initiate emergency lockdown measures for the entire area, deploy professional pollution treatment equipment, and intercept, collect, and render harmless the leaked pollutants. Simultaneously, a pollution warning notice will be issued to the communities surrounding the landfill.

[0106] This invention, by transforming living plants into distributed biosensors, innovatively constructs a "plant root electrophysiological signal network," overcoming the limitations of traditional physical / chemical detection technologies. Utilizing the physiological stress responses of plants to pollutants, such as changes in membrane potential and ion current, it achieves early warning, capturing leakage signs 2-8 hours earlier than traditional sensors. Combined with a flexible microelectrode array planted in a 2×2 meter grid pattern in the core area, a high-density monitoring network is formed, improving leakage location accuracy to ±0.5 meters. This solves the technical problems of delayed early warning and inefficient spatial positioning in existing technologies.

[0107] This invention innovatively establishes a quantitative matching model of "pollution data - environmental data - plant tolerance," achieving precise and low-cost plant selection through pollution tolerance assessment value analysis and planting cost optimization strategies. Multi-dimensional data such as heavy metal concentration and soil pH are normalized and processed, then combined with machine learning algorithms to calculate pollution tolerance assessment values. After matching the plant tolerance ranges in the database, the most cost-effective species are selected, reducing planting costs by 60% compared to genetically modified plants. Simultaneously, the selected living plants possess both pollution monitoring and ecological restoration capabilities. For example, *Sedum aizoon* can extract 2.3 kg / acre of heavy metals from the soil annually while monitoring cadmium pollution, achieving integrated "monitoring-remediation." Furthermore, the low-power network at each detection plant point achieves 1 / 20th the power consumption of traditional equipment, constructing an innovative technical path of "high-sensitivity monitoring - low-cost implementation."

[0108] At the level of emergency response and ecological synergy, the technical solution of this invention features a unique three-level quantitative standard for leakage levels and a corresponding early warning mechanism, shortening the pollution control time from 72 hours in traditional methods to within 8 hours. Simultaneously, indicator plants possess both pollution monitoring and ecological restoration functions, and flexible microelectrodes are implanted minimally invasively using biocompatible materials to avoid secondary pollution, forming a complete innovative system of "real-time monitoring - precise early warning - ecological restoration," providing a model of interdisciplinary technological integration for the field of environmental monitoring.

[0109] This invention targets the complex environment of landfill sites, constructing a complete closed loop of "pollution data-driven plant screening - hierarchical grid array deployment - real-time acquisition of root electrophysiological signals - dynamic early warning of leakage levels." It solves the problems of scenario adaptation ("which plants to use for monitoring") and spatial optimization ("where to monitor"), forming a complete response mechanism of "detection-assessment-early warning." It is no longer limited to the physical structure design of a single device, but rather uses indicator plants adapted to the polluted environment as natural "biosensors." It utilizes the dynamic changes in root electrophysiological signals (such as resting membrane potential and ion current ratio) to achieve real-time leakage detection. It emphasizes the transformation from basic laboratory research to engineering practice, and the detection indicators are upgraded from morphological characteristics to more sensitive electrophysiological responses, significantly improving response speed and field applicability.

[0110] This invention employs a multi-level technical design to construct a specific correlation mechanism between changes in plant root electrophysiological signals and leakage contamination, effectively eliminating interference from non-leakage factors. Specifically, this is reflected in the following aspects:

[0111] First, the targeted indicator plant screening mechanism reduces interference at the source. This invention does not use general plants, but rather employs a pollution data adaptation and analysis module to precisely match pollution data such as heavy metal and organic matter concentrations at the target landfill with pollution tolerance assessment ranges for plants in a database. This allows for the screening of indicator plants that are significantly more sensitive to the target leachate pollutants than to other environmental factors. These plants exhibit stable root electrophysiological signals in non-leaking environments and only show specific responses to specific pollutant stresses, thus reducing signal interference caused by fluctuations in the plant's own growth cycle or changes in non-target environments (such as normal fluctuations in temperature and humidity) at a biological level.

[0112] Secondly, the spatial control and hierarchical deployment design established a baseline for excluding environmental interference. The control area, along with the core monitoring area and secondary monitoring areas, formed a spatial control. The control area was planted with the same indicator plants but located in an area unaffected by seepage, and its root electrophysiological signals served as a "blank baseline value." By comparing the signal differences between the monitoring area and the control area at the same time point, the influence of global environmental factors (such as climate change and fluctuations in soil background values) could be directly eliminated. Simultaneously, the refined deployment of a 2×2 meter grid in the core area and a 4×4 meter grid in the secondary area allowed for the differentiation between localized seepage pollution and individual plant anomalies (such as individual signal fluctuations caused by pests and diseases) through signal correlation analysis of adjacent plant sites.

[0113] Furthermore, the selection of specific electrophysiological indicators and the use of quantitative models improve the accuracy of signal interpretation. This invention focuses on electrophysiological indicators directly related to pollutant stress, such as resting membrane potential and specific ion current ratios. The mechanisms of change in these indicators are clear—for example, heavy metal ions disrupt the ion transport balance of root cell membranes, leading to abnormal fluctuations in membrane potential. Meanwhile, conventional environmental factors (such as short-term drought) primarily affect water-related physiological indicators, having minimal impact on these types of electrophysiological signals. By normalizing the signal data and substituting it into the root electrophysiological assessment model, combined with a signal feature database of historical leakage cases, it is possible to quantitatively distinguish between "leakage-specific signal patterns" and "non-leakage interference signal patterns," avoiding misjudgment based on a single indicator.

[0114] Finally, dynamic time-series analysis and leakage degree grading logic reinforce causal verification. The scheme continuously monitors at multiple detection time points. If the electrophysiological signal at a particular plant site exhibits a sustained trend consistent with leakage diffusion patterns (e.g., a gradual increase from slight to significant abnormalities), and shows spatial correlation with signal changes at surrounding plant sites (e.g., gradient changes along potential leakage paths), then the impact of leakage pollution is further verified. Simultaneously, the leakage degree grading criteria (less than 5%, moderate 5%-10%, and severe above 10%) are established based on extensive experimental data, ensuring a clear quantitative relationship between signal change amplitude and leakage concentration, rather than random fluctuations.

[0115] In summary, the embodiments of the present invention construct a complete chain of evidence from signal acquisition to causal determination through a multi-dimensional design of "biological screening - spatial control - indicator specificity - time-series verification", effectively ensuring the specific correlation between changes in root electrophysiological signals and leakage pollution.

[0116] The above-disclosed embodiments are merely specific examples of the present invention. However, the present invention is not limited thereto, and any variations that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A method of landfill leak detection, characterized by, Includes the following steps: Obtain pollution and environmental data corresponding to the target landfill, and calculate the pollution tolerance assessment value corresponding to the target landfill. The pollution data includes the concentrations of various heavy metals. Concentration of various types of organic matter Concentrations corresponding to each salt The environmental data includes soil pH, soil moisture, and temperature. Based on the pollution tolerance assessment value range and the pollution tolerance assessment value The set of suitable living plants corresponding to the target landfill is obtained; by obtaining the planting cost of each suitable living plant in the set of suitable living plants, the optimal living plant for the target landfill is obtained. Among them, the optimal living plant is the suitable living plant with the lowest planting cost; The optimal live plant species are deployed in a planting indicator plant array. A detection time point q and a detection plant point y are set. Root electrophysiological signal data corresponding to the detection plant point y are collected based on the detection time point q, and the root electrophysiological evaluation value corresponding to the detection plant point y collected at the detection time point q is calculated. The root electrophysiological signal data includes resting membrane potential. Specific ion current ratio and rate of change of action potential frequency ; Set a root electrophysiological evaluation threshold corresponding to a standard detection plant point y, and compare the root electrophysiological evaluation values. Based on the magnitude of the root electrophysiological assessment threshold, it is determined whether pollutant leakage has occurred at each detection plant point y collected at each detection time point q; if pollutant leakage is determined to have occurred, the degree of leakage corresponding to each detection plant point y collected at each detection time point q is analyzed and an early warning is issued. Among them, when the root electrophysiological assessment value When the value exceeds the root electrophysiological assessment threshold, it is determined that a contaminant leakage has occurred.

2. The landfill leakage detection method as described in claim 1, characterized in that, The pollution tolerance assessment value corresponding to the target landfill The calculation method includes the following: Based on the pollution data and environmental data, calculate the pollution data fit value corresponding to the target landfill. and corresponding environmental data adaptation values ; Based on the pollution data adaptation value Adaptation values ​​for environmental data The pollution tolerance assessment value corresponding to the target landfill was calculated. .

3. The landfill leakage detection method as described in claim 2, characterized in that, The pollution data adaptation value corresponding to the target landfill The calculation formula is expressed as: ； Where h represents the code corresponding to each type of heavy metal. , It is a positive integer; This represents the collection of various types of heavy metals, and g represents the corresponding number of various types of organic compounds. , It is a positive integer; It represents a collection of various types of organic matter. This indicates the corresponding number for each type of salt. , It is a positive integer; This represents the collection of all salts.

4. The landfill leakage detection method as described in claim 3, characterized in that, The environmental data adaptation value corresponding to the target landfill The calculation method is adapted to the pollution data corresponding to the target landfill. The calculation method is the same.

5. The landfill leakage detection method as described in claim 4, characterized in that, The pollution tolerance assessment value corresponding to the target landfill The calculation formula is expressed as: 。 6. The landfill leakage detection method as described in claim 1, characterized in that, The planting deployment process includes the following: Based on the landfill's layout plan and pollution concentration gradient distribution map, the landfill was divided into a core monitoring area, a secondary monitoring area, and a control area. In the core monitoring area, the best living plants are planted in a grid pattern with a spacing of 2×2 meters. A flexible microelectrode array is buried in the center of each grid, and the electrodes are kept at a specified contact distance with the plant roots. The planting spacing in the secondary monitoring area has been expanded to 4×4 meters. The same grid planting layout is adopted. Multiple flexible microelectrodes are symmetrically buried around the roots of each plant to form a ring monitoring structure. The electrodes are kept at a specified distance from the plant roots. The planting spacing in the control area was increased to 6×6 meters, and the same grid planting layout was adopted. Two flexible microelectrodes were buried in parallel near the roots of each plant, and the electrodes were kept at a specified distance from the plant roots.

7. The landfill leakage detection method as described in claim 1, characterized in that, The root electrophysiological assessment value The calculation formula is expressed as: ； Where q represents the number corresponding to each detection time point. , It is a positive integer; y represents the set of all detection time points; y represents the number corresponding to each detection plant point. , It is a positive integer; This represents the collection of all detected plant sites; and These represent the mean and standard deviation of the resting membrane potential corresponding to the plant point y under normal conditions. Let y be the standard specific ion current ratio corresponding to the set detection plant point y, and e be the natural constant.

8. The landfill leakage detection method as described in claim 1, characterized in that, The specific analysis method for analyzing the leakage degree corresponding to each detection plant point y collected at each detection time point q includes the following: When the root electrophysiological assessment value If the leakage rate is within 5% of the root electrophysiological assessment threshold, then the leakage rate corresponding to the detection plant point y collected at the detection time point q is considered slight. When the root electrophysiological assessment value If the percentage of the root electrophysiological assessment threshold is greater than 5% but less than 10%, then the leakage level corresponding to the detection plant point y collected at the detection time point q is moderate. When the root electrophysiological assessment value If the leakage rate is greater than 10% above the root electrophysiological assessment threshold, then the leakage rate corresponding to the detection plant point y collected at the detection time point q is considered severe.

9. A landfill leakage detection system, characterized in that, The method for detecting landfill leakage according to any one of claims 1-8 is used, and the system includes a live plant screening and planting module, a real-time pollution leakage detection module, a real-time leakage detection and judgment module, and a database. The database is used to store the pollution tolerance assessment value ranges corresponding to each suitable living plant. The live plant selection and planting module is used to acquire pollution data, environmental data, and planting costs of suitable live plants for the target landfill, and to calculate the pollution tolerance assessment value for the target landfill. The system obtains the set of suitable living plants corresponding to the target landfill and the optimal living plant corresponding to the target landfill, and sends the optimal living plant corresponding to the target landfill to the real-time pollution leakage detection module. The real-time pollution leakage detection module is used to receive the optimal live planting plants corresponding to the target landfill from the live plant screening and planting module, deploy the planting indicator plant array, collect root electrophysiological signal data corresponding to the detection plant point y, and calculate the root electrophysiological evaluation value corresponding to the detection plant point y collected at the detection time point q. The root electrophysiological assessment value is sent to the real-time leakage detection and judgment module. ; The real-time leakage detection and judgment module is used to receive the root electrophysiological assessment values ​​transmitted by the real-time pollution leakage detection module. And by comparing with the root electrophysiological evaluation threshold corresponding to the standard detection plant point y, it is determined whether pollutant leakage has occurred at each detection plant point y collected at each detection time point q. When a pollutant leak is detected, the extent of the leak is analyzed and an early warning is issued.

10. The landfill leakage detection system as described in claim 9, characterized in that, The warning notification process includes the following: When the leakage is minor, a low-level audible and visual warning is triggered, marking the leakage point with a flashing yellow icon, and simultaneously pushing the warning information to the user account of the maintenance personnel; after receiving the information, the maintenance personnel must go to the site to verify within 24 hours; the warning information includes the detection time, plant point coordinates, leakage level and current leakage stage; When the leakage level is moderate, a moderate-level audible and visual warning is triggered, the leakage point is marked with an orange highlighted icon, and the corresponding warning information is simultaneously pushed to the user account of the operation and maintenance team via SMS, email and system pop-up. After receiving the information, the operation and maintenance team must rush to the site within 4 hours, start the emergency pumping equipment, and set up a temporary anti-seepage isolation zone around the leakage point. When the leakage is deemed severe, the highest level of audible and visual warning will be triggered, immediately issuing a red alert accompanied by a sharp, continuous alarm sound. At the same time, the warning information will be pushed to the user accounts of the emergency response team. The emergency response team must be fully staffed within one hour, initiate emergency lockdown measures for the entire area, deploy professional pollution treatment equipment, and intercept, collect, and render harmless the leaked pollutants. Simultaneously, a pollution warning notice will be issued to communities surrounding the landfill.

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