Data-driven in-situ remediation system and method for electrically stimulating a biological water body

Abstract

The application discloses a data-driven electric stimulation biological water body in-situ remediation system and method, and the system comprises a water body in-situ remediation device, a data sampling system capable of collecting data of the water body in-situ remediation device, a data analysis system for training and optimizing a mathematical model according to the collected data, and a control system for controlling equipment operation according to optimal control parameters obtained by the data analysis system. The application can rely on data driving to realize dynamic adjustment of key control parameters in water body in-situ remediation, and is helpful to keep the remediation system efficient in automatic degradation of pollutants without manual intervention.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water body remediation, in particular to an in-situ remediation system and method for electrically stimulating biological water bodies based on data driving. BACKGROUND

[0002] In the process of water body site pollution remediation, biological electrochemical system / biological electric stimulation system (BES) has become a competitive alternative solution due to its excellent degradation efficiency, environmental sustainability and lower operating cost. Compared with open circuit system, weak electric stimulation can significantly enhance the metabolic activity of electroactive bacteria, significantly improve the degradation rate of pollutants, and almost no degradation ability is observed in non-biological cathode.

[0003] Microbial electrode respiration technology provides great sustainability benefits for groundwater remediation, however, the complexity of hydrological and hydrochemical environment, the heterogeneity of pollution and the diversity of functional microorganisms significantly increase the difficulty of regulating BES system. It is often necessary to conduct detailed or orthogonal experiments in the laboratory to obtain the best system design and operating characteristics, which is usually costly, labor-intensive and unsustainable. In addition, it is very challenging to find similar scenarios with matching pollution characteristics, reaction conditions and hydrogeological environment according to existing research and experience, which makes it very difficult to develop a comprehensive reaction model. It should also be noted that the environmental conditions of contaminated sites are dynamically changing. In order to cope with severe environmental fluctuations, it is necessary to develop differential solutions for different scenarios, and the complex and uncontrollable operating environment determines that it is impossible to provide solutions for all foreseeable and unforeseeable scenarios. Even if a robust strategy system is constructed and appropriate technical parameter indicators are adopted, the reactor cannot achieve the best degradation effect when the environment fluctuates slightly, because this set of best solutions is only the best solution under a single environmental condition. Therefore, in order to obtain good dechlorination effect in terms of efficiency and economy, it is necessary to develop a control system for dynamic optimization design of reaction device and process parameters. SUMMARY

[0004] In view of the defects of the prior art, the purpose of the present application is to provide an in-situ remediation system and method for electrically stimulating biological water bodies based on data driving, which can dynamically adjust the key control parameters of the in-situ remediation device of the water body by relying on data driving, so as to efficiently degrade and purify groundwater halogenated pollutants.

[0005] The technical scheme of the present application is as follows:

[0006] The application discloses a data-driven electric stimulation in-situ remediation system for biological water body, which comprises an in-situ remediation device for water body, a data sampling system for sampling data of the in-situ remediation device, a data analysis system for analyzing the sampling data obtained by the data sampling system and a device operation control system for controlling the system according to the analysis data obtained by the data analysis system. The in-situ remediation device comprises a double-chamber bioelectrochemical system reactor with an anode chamber and a cathode chamber communicated through a proton exchange membrane, a constant temperature control device capable of sensing and controlling the temperature of the cathode chamber, a cathode chamber water inflow adjusting device capable of sensing and controlling the water inflow of the cathode chamber, a power supply and a power voltage regulator capable of controlling the voltage of the power supply. The anode chamber is provided with an anode electrode communicated with the positive pole of the power supply, and the cathode chamber is provided with a cathode electrode communicated with the negative pole of the power supply. The anode chamber is further provided with an anode chamber water inlet and an anode chamber water outlet. The cathode chamber is further provided with a cathode chamber water inlet, a cathode chamber water outlet, a cathode chamber water inlet sampling port for sampling the water inflow of the cathode chamber, a cathode chamber water outlet sampling port for sampling the water outflow of the cathode chamber and a cathode biofilm sampling port for sampling the sludge mixture water sample near the cathode electrode. The data analysis system comprises a model module and an output optimization module. The model module comprises a mathematical analysis model which is trained according to the sampling data, and the output optimization module calculates the optimal process parameters of the in-situ remediation device for water body according to the trained mathematical model.

[0007] In some embodiments, the sample of each sampling port is transmitted to the data sampling system by one or more of gravity flow, pressure flow generated by water inflow and pressure flow generated by a water pump.

[0008] In some embodiments, the constant temperature control device comprises a thermistor sensor and a power regulator.

[0009] In some embodiments, the cathode chamber water inflow adjusting device comprises an ultrasonic flow sensor and a flow regulating valve.

[0010] In some embodiments, the data sampling system comprises a temperature sensing device arranged in the constant temperature control device, a flow sensing device arranged in the cathode chamber water inflow adjusting device, a water quality detection device for detecting the water quality parameters of the water samples of the cathode chamber water outlet sampling port and the cathode chamber water inlet sampling port, a biological detection device for detecting the biological information in the water sample of the cathode biofilm sampling port and a voltage detection device for detecting the voltage value of the power supply.

[0011] In some embodiments, the sampling data comprises cathode chamber temperature, cathode chamber influent flow rate, water quality parameters of water sample at cathode chamber effluent sampling port, water quality parameters of water sample at cathode chamber influent sampling port, biological information in water sample at cathode biofilm sampling port, and power supply voltage value.

[0012] In some embodiments, the water quality parameters comprise one or more of pH value, chemical oxygen demand (COD), biochemical oxygen demand (BOD), conductivity, total nitrogen amount, total phosphorus amount, ammonia nitrogen amount, nitrate content, phosphate content, residual chlorine amount, total chlorine amount, heavy metal (such as lead, cadmium, mercury, etc.) concentration, hardness, and turbidity.

[0013] In some embodiments, the water quality detection device comprises one or more of pH detector, spectrophotometer, digestion reactor, potassium permanganate titration method instrument, COD rapid determination instrument, respirometer, rapid enzyme method or fluorescence quenching method instrument, conductivity detector, ion selective electrode method (ISE) or colorimetric method instrument, X-ray fluorescence spectrometer (XRF), EDTA titration method instrument, LaMotte 5-EP hardness determination instrument, and scattered light turbidimeter.

[0014] In some embodiments, the pH detector can obtain pH value; the spectrophotometer, digestion reactor, or potassium permanganate titration method instrument can obtain chemical oxygen demand (COD); the respirometer, rapid enzyme method or fluorescence quenching method instrument can obtain biochemical oxygen demand (BOD); the conductivity detector can obtain conductivity; the ion selective electrode method (ISE) or colorimetric method instrument can obtain total nitrogen, total phosphorus, ammonia nitrogen, nitrate, phosphate, residual chlorine, and total chlorine content; the X-ray fluorescence spectrometer (XRF) can obtain heavy metal (such as lead, cadmium, mercury, etc.) concentration; the EDTA titration method instrument or LaMotte 5-EP hardness determination instrument can obtain hardness; and the scattered light turbidimeter can obtain turbidity.

[0015] In some embodiments, the biological information comprises one or more of refractive index of microorganism-containing water sample under light illumination of different wavelengths and / or directions, abundance and uniformity of biological macromolecules (such as proteins, peptides, carbohydrates, and lipids), community genome, colony morphological characteristics, and number.

[0016] In some embodiments, the biological detection device comprises one or more of stained or unstained flow cytometer, MALDI-TOF (Matrix-Assisted Laser Desorption / Ionization Time-of-Flight Mass Spectrometry) mass spectrometer, high-throughput sequencing instrument, and plate culture instrument.

[0017] The refractive index under illumination of different wavelengths and / or different directions can be obtained by a flow cytometer with or without staining; the time of flight of biological macromolecules (such as proteins, peptides, carbohydrates and lipids) can be obtained by a MALDI-TOF mass spectrometer; the community genome can be obtained by a high-throughput sequencing instrument; the separation of microorganisms, the colony morphological characteristics and the number of colonies can be obtained by a plate culture instrument.

[0018] Preferably, the biological detection device is a flow cytometer and / or a MALDI-TOF mass spectrometer.

[0019] In some embodiments, the voltage detection device is one or more of a potentiometer, a voltmeter, a digital multimeter, an oscilloscope, a bridge, a differential amplifier, a precision voltage sensor, an intelligent voltage monitoring system, a power analyzer, a current probe, a voltage divider, and an application-specific integrated circuit (ASIC) integrated with measurement and monitoring functions.

[0020] The voltage detection device measures the power supply voltage, and in some embodiments, a reference electrode can be arranged in the cathode chamber, and the power supply voltage is replaced by measuring and adjusting the voltage of the reference electrode.

[0021] The data sampling system and the data analysis system, and the data analysis system and the device operation control system, are in signal communication through wired and / or wireless (such as through radio frequency communication, 5G communication, Wi-Fi communication, etc.) signals.

[0022] In some embodiments, the mathematical analysis model takes the cathode chamber temperature, the cathode chamber water inflow, the water quality parameters of the water sample at the cathode chamber water inlet sampling port, the biological information in the water sample at the cathode biofilm sampling port, and the power supply voltage value as inputs, and takes the water quality parameters of the water sample at the cathode chamber water outlet sampling port as output.

[0023] In some embodiments, the output optimization module is based on the trained mathematical analysis model, and obtains the optimal process parameters that can achieve the optimal output condition of the trained mathematical analysis model through an optimization algorithm, including the cathode chamber water inflow, the power supply voltage value, and the cathode chamber temperature.

[0024] In some embodiments, the mathematical analysis model comprises one or more of a linear regression model, a ridge regression model, a random forest model, an extreme learning machine model, a support vector machine model, a decision tree model, a logistic regression model, a Bayesian model, a K-nearest neighbor model, a principal component analysis model, a gradient boosting machine model, a neural network model, a long short-term memory model, a self-organizing map model, a Gaussian process regression model, a Markov chain Monte Carlo model, an XGBoost model, a LightGBM model, a CatBoost model, a Bayesian network model, an entropy weight method model, a partial least squares regression model, an ensemble learning model, a factor analysis model, a principal component regression model, a weighted least squares method model, an elastic net regression model, a quantile regression model, a time series analysis model, an adaptive boosting neural network model, a multilayer perceptron model, a Gaussian mixture model, a t-SNE model, a U-Net model, a generative adversarial network model, a variational autoencoder model, a sparse representation model, an independent component analysis model, a causal inference model, a graph neural network model, a Laplace regularization model.

[0025] In some embodiments, the optimization algorithm is selected from one or more of an exhaustive method, a greedy algorithm, a dynamic programming algorithm, a divide-and-conquer algorithm, a backtracking algorithm, a branch-and-bound algorithm, a simulated annealing algorithm, a tabu search algorithm, an ant colony optimization algorithm, a particle swarm optimization algorithm, an artificial bee colony algorithm, a genetic algorithm, a Monte Carlo method, a gradient descent algorithm, a forgetting learning algorithm, a neural network algorithm, a genetic programming algorithm, a reinforcement genetic algorithm, a Bayesian optimization algorithm, a Lagrangian relaxation algorithm, a convex optimization algorithm, a Newton's method, a quasi-Newton method, an interior point method, a Lagrange multiplier method, an alternating direction method of multipliers, a graph algorithm, a permutation algorithm, a probabilistic graphical model, a fuzzy logic algorithm, a neuro-fuzzy system, a quantum algorithm, a linear programming algorithm, a nonlinear programming algorithm, a multi-objective optimization algorithm, a Markov decision process, a game theory algorithm, a differential evolution algorithm.

[0026] In some embodiments, the device operation control system is an embedded control system, comprising one or more of a PLC (programmable logic controller), a PAC (programmable automation controller), a Linux system board, a microcontroller, a single-chip microcomputer.

[0027] The present application ensures and promotes the efficient and sustainable operation of the biological electric stimulation water in-situ remediation system by automatically adjusting the operating parameters of the water in-situ remediation device BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 A structural schematic diagram of the water in-situ remediation system in Example 1;

[0029] Figure 2 A flowchart of a remediation method of the water in-situ remediation system in Example 1;

[0030] Figure 3 Structure diagram of water body in-situ remediation system in Example 9;

[0031] Figure 4 Flow diagram of a remediation method of water body in-situ remediation system in Example 9;

[0032] Wherein:

[0033] X1-anode chamber, X2-cathode chamber, 1-anode chamber water outlet, 2-anode electrode, 3-anode chamber water inlet, 4-thermostatic device, 4a-thermistor sensor, 4b-thermostatic device power regulator, 5-power supply voltage regulator, 6-power supply, 7-perforated mudguard, 8-cathode biofilm sampling port, 9-cathode chamber water outlet sampling port, 10-cathode electrode, 11-cathode chamber water inlet sampling port, 12-cathode chamber water outlet, 13-cathode chamber water inlet flow adjustment device, 13a-ultrasonic flow sensor, 13b-flow regulating valve, 14-cathode chamber water inlet, 15-exchange membrane, 16a-reference electrode, 16b-reference electrode voltage regulator. DETAILED DESCRIPTION

[0034] The present application is described in detail below with reference to the embodiments and drawings, but it should be understood that the embodiments and drawings are only used to exemplarily describe the present application, and cannot constitute any limitation on the protection scope of the present application. All reasonable modifications and combinations within the scope of the inventive concept of the present application fall within the protection scope of the present application.

[0035] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "exemplary embodiment", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the exemplary description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0036] Example 1

[0037] Referring to the accompanying drawings, Figure 1 , the data-driven-based electric stimulation biological water body in-situ remediation system of the present application comprises a water body in-situ remediation device, a data sampling system, a data analysis system and a device operation control system.

[0038] The water in-situ remediation device comprises an H-shaped double-chamber BES reactor, which comprises an anode chamber X1 provided with an anode electrode 2, a cathode chamber X2 provided with a cathode electrode 10, a power supply 6 and a power supply voltage regulator 5 capable of regulating the voltage of the power supply 6, wherein the anode chamber X1 and the cathode chamber X2 are communicated through a proton exchange membrane 15; the anode electrode 2 is communicated with the positive electrode of the power supply 6, and the cathode electrode 10 is communicated with the negative electrode of the power supply 6; the bottom of the cathode chamber X2 is further provided with a constant temperature regulating device capable of regulating the temperature of the cathode chamber X2; the anode chamber X1 and the cathode chamber X2 are both provided with water inlet and outlet ports, i.e. anode chamber water outlet port 1, anode chamber water inlet port 3, cathode chamber water outlet port 12 and cathode chamber water inlet port 14; wherein the cathode chamber water inlet port 14 is provided with a cathode chamber water inlet flow adjusting device for regulating the water inlet flow of the cathode chamber X2 and a cathode chamber water inlet sampling port 11 for sampling the cathode chamber water inlet; the cathode chamber water outlet port 12 is provided with a cathode chamber water outlet sampling port 9 for sampling the cathode chamber water outlet; the vicinity of the cathode electrode 10 is provided with a cathode biofilm sampling port 8 for sampling the sludge mixture water sample near the cathode electrode 10.

[0039] The application method is as follows: in order to start the water in-situ remediation device, sludge is added to the cathode chamber X2, water is injected into the anode chamber water inlet port 3 of the anode chamber X1 to submerge the anode electrode 2, water is injected into the cathode chamber water inlet port 14 of the cathode chamber X2 and discharged from the cathode chamber water outlet port 12, the water inlet flow of the cathode chamber X1 is controlled by the cathode chamber water inlet flow adjusting device to keep a certain hydraulic retention time of the cathode chamber X2, then the power supply 6 is turned on, the functional bacteria group in the sludge added to the cathode chamber X2 receives electrons from the cathode electrode 10, so as to stimulate the bacteria group to accelerate the removal of water pollutants, and in this process, the constant temperature regulating device is turned on to maintain a certain temperature of the cathode chamber X2.

[0040] Embodiment 2

[0041] In the data-driven electrically stimulated biological water in-situ remediation system shown in embodiment 1, the constant temperature regulating device comprises a thermistor sensor 4a and a power regulator 4b.

[0042] Embodiment 3

[0043] In the data-driven electrically stimulated biological water in-situ remediation system shown in embodiment 1, the cathode chamber water inlet flow adjusting device comprises an ultrasonic flow sensor 13a and a flow regulating valve 13b.

[0044] Embodiment 4

[0045] Preferably, the upper part of the cathode electrode 2 is provided with a porous mud baffle 7 for reducing the loss of the cathode biofilm on the cathode electrode 2 caused by water flow scouring.

[0046] Embodiment 5

[0047] In the data-driven electric stimulation biological water body in-situ remediation system shown in Embodiment 1, the data sampling system comprises: an effluent outlet sampling device capable of determining the COD value of the water sample of the effluent outlet sampling port 9 and the cathode chamber water inlet sampling port 11, such as a COD photometric rapid determination instrument; a sampling device capable of determining the numerical distribution information of the forward and lateral scattering light of the water sample of the cathode biofilm sampling port 8 at different wavelengths, such as a flow cytometer; and a device capable of determining the power voltage value, such as a potentiometer.

[0048] Embodiment 6

[0049] Referring to the accompanying Figure 2 In the data-driven electric stimulation biological water body in-situ remediation system shown in Embodiment 1, the data analysis system comprises a model module and an output optimization module, wherein the model module contains a mathematical analysis model; the data analysis system communicates with the data sampling system through a 4G DTU wireless data transmission device, and can store and run a feedforward artificial neural network model and a genetic algorithm;

[0050] The feedforward artificial neural network model takes the COD of the water sample of the cathode chamber water inlet sampling port 11, the numerical distribution information of the forward and lateral scattering light of the water sample of the cathode biofilm sampling port 8 at different wavelengths, the power voltage, the cathode chamber temperature obtained through the constant temperature control device, and the cathode chamber water inlet flow obtained through the cathode chamber water inlet flow adjustment device as inputs, and takes the COD of the water sample of the cathode chamber effluent outlet sampling port 9 as output.

[0051] The optimization process of the output optimization module includes: taking the lower limit value of the water quality of the cathode chamber effluent outlet sampling port reaching the requirements of the surface water quality of the II type surface water in the surface water environmental quality standard (GB3838-2022) as the target output value, calculating the input parameters that can obtain the target output through the genetic algorithm, and the adjusted input parameters include the COD of the water sample of the cathode chamber water inlet sampling port 11 and the numerical distribution information of the forward and lateral scattering light of the water sample of the cathode biofilm sampling port 8 at different wavelengths using the measured values.

[0052] The genetic algorithm obtains different output values by adjusting the input parameters based on the mathematical analysis model, and when the difference between the COD of the water sample of the cathode chamber effluent outlet sampling port and the target output value is less than 0.5, the optimization process is exited, and the optimal input parameters, i.e. the optimal power voltage, cathode chamber temperature and cathode chamber water inlet flow, are obtained, which are transmitted to the equipment operation control system through the 4G DTU wireless data transmission device.

[0053] The neural network used in the feedforward artificial neural network model has one hidden layer and five hidden layer neurons.

[0054] Example 7

[0055] The device operation control system adjusts and updates parameters of the power supply voltage, the cathode chamber temperature and the cathode chamber water inflow through the power supply voltage regulator 5, the constant temperature power regulator 4b and the cathode chamber water inflow regulating valve 13b respectively according to the stored operation parameters and the optimized process parameters from the data analysis system, which can be implemented by devices such as single-chip microcomputers. More specifically, when the stored operation parameters are inconsistent with the data from the data analysis system, the power supply voltage, the cathode chamber temperature and the cathode chamber water inflow are adjusted to be consistent with the data from the data analysis system through the power supply voltage regulator 5, the constant temperature power regulator 4b and the cathode chamber water inflow regulating valve 13b, and the original stored operation parameters are updated by the operation parameters at this time.

[0056] In the operation of the water body in-situ remediation device, the above data sampling system, data analysis system calculation and device operation control system parameter adjustment are repeated, so as to realize the automatic operation of the biological electric stimulation water body in-situ remediation system without manual intervention and maintain the high efficiency of the system remediation.

[0057] Example 8

[0058] In a specific operation mode, when the proton exchange rate in the water body in-situ remediation device is limited, such as when the proton exchange membrane 15 is blocked, H + may accumulate in the anode chamber X1, which is reflected by the continuous increase of the pH value. At this time, the water in the anode chamber X1 can be replaced by draining and then injecting water through the anode chamber water inlet 3, or continuously injecting water through the anode chamber water inlet 3 and discharging water through the anode chamber water outlet 1.

[0059] Example 9

[0060] In another specific operation mode, referring to FIG. 8, a reference electrode 16a and a reference electrode voltage regulator 16b are added to the water body in-situ remediation device, wherein the reference electrode 16a is a saturated calomel electrode. The remediation by the water body in-situ remediation system with the reference electrode is shown in FIG. 9, which does not need to collect the voltage data of the power supply 6, but collects the voltage data of the reference electrode 16a, and adjusts the voltage of the reference electrode 16a through the reference electrode voltage regulator 16b in the device operation control system. Figure 3 Figure 4 Figure 2

[0061] ​​​Finally, it should be noted that the above is only to illustrate the technical solutions of the present application and is not limiting. Although the embodiments are described in detail, those of ordinary skill in the art should understand that the technical solutions of the present application (such as pump type, charging form, step sequence, etc.) can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A water in-situ remediation method based on a data-driven electric stimulation water body in-situ remediation system, characterized in that, The data-driven based electric stimulation biological water in-situ remediation system comprises a water in-situ remediation device for water in-situ remediation, a data sampling system for sampling the water in-situ remediation device, a data analysis system for analyzing the sampling data obtained by the data sampling system, and a device operation control system for regulating the water in-situ remediation device based on the analysis data obtained by the data analysis system. The water in-situ remediation device comprises a double-chamber bioelectrochemical system reactor with an anode chamber and a cathode chamber connected by a proton exchange membrane, a constant temperature regulating device for sensing and regulating the temperature of the cathode chamber, a cathode chamber water inflow adjusting device for sensing and regulating the water inflow of the cathode chamber, a power supply, and a power supply voltage regulator for regulating the voltage of the power supply. The anode chamber is provided with an anode electrode connected with the positive electrode of the power supply, and the cathode chamber is provided with a cathode electrode connected with the negative electrode of the power supply. The anode chamber is further provided with an anode chamber water inlet and an anode chamber water outlet. The cathode chamber is further provided with a cathode chamber water inlet, a cathode chamber water outlet, a cathode chamber water inlet sampling port arranged near the cathode chamber water inlet for sampling the water inflow of the cathode chamber, a cathode chamber water outlet sampling port arranged near the cathode chamber water outlet for sampling the water outflow of the cathode chamber, and a cathode biofilm sampling port for sampling the water sample containing sludge mixture near the cathode electrode. The data analysis system comprises a model module and an output optimization module. The model module comprises a mathematical analysis model trained according to the sampling data, and the output optimization module calculates the optimal process parameters of the water in-situ remediation device according to the trained mathematical analysis model. The water in-situ remediation method comprises the following steps: collecting the sampling data of the water in-situ remediation device during water remediation by the data collection system, wherein the sampling data comprises the cathode chamber temperature, the cathode chamber water inflow, the water quality parameters of the water sample at the cathode chamber water outlet sampling port, the water quality parameters of the water sample at the cathode chamber water inlet sampling port, the biological information in the water sample at the cathode biofilm sampling port, and the power supply voltage or reference electrode voltage value; training the mathematical analysis model according to the sampling data by the data analysis system; taking the cathode chamber temperature, the cathode chamber water inflow, the water quality parameters of the water sample at the cathode chamber water inlet sampling port, the biological information in the water sample at the cathode biofilm sampling port, and the power supply voltage or reference electrode voltage value as inputs, and taking the water quality parameters of the water sample at the cathode chamber water outlet sampling port as outputs; based on the trained mathematical analysis model, the output optimization module of the data analysis system obtains the optimal process parameters, including the cathode chamber water inflow, the power supply voltage or reference electrode voltage value, and the cathode chamber temperature, under the optimal output condition of the trained mathematical analysis model by using an optimization algorithm.The obtained optimal process parameters are transmitted to the equipment operation control system as a control target, and the operation parameters of the water body in-situ remediation device are regulated by the equipment operation control system to reach the control target.

2. The method for in-situ remediation of water bodies according to claim 1, characterized in that, Wherein, The double-chamber bioelectrochemical system reactor is a double-chamber reactor; the constant temperature regulation device comprises a thermistor sensor and a power regulator; and the water inflow adjustment device of the cathode chamber comprises an ultrasonic flow sensor and a flow regulating valve.

3. The method for in-situ remediation of water bodies as claimed in claim 1 wherein, Wherein, The data sampling system comprises: a temperature sensing device arranged in the constant temperature regulation device, a flow sensing device arranged in the water inflow adjustment device of the cathode chamber, a water quality detection device capable of detecting water quality parameters of water samples of the water outlet sampling port of the cathode chamber and the water inlet sampling port of the cathode chamber, a biological detection device capable of detecting biological information in water samples of the cathode biofilm sampling port, and a voltage detection device capable of detecting power voltage values; and the equipment operation control system comprises one or more of PLC, PAC, a Linux system board, a microcontroller, and a single-chip microcomputer.

4. The method for in-situ remediation of water bodies according to claim 3, characterized in that, The temperature sensing device is a thermistor sensor, the flow sensing device is an ultrasonic flow sensor, the water quality detection device is a rapid chemical oxygen demand detector, and the biological detection device is a flow cytometer and / or a MALDI-TOF mass spectrometer.

5. The method for in-situ remediation of water bodies as claimed in claim 1 wherein, It further comprises: a reference electrode arranged in the cathode chamber and a reference electrode voltage regulator.

6. The method for in situ remediation of water bodies according to claim 1, characterized in that, The water quality parameters comprise one or more of pH value, chemical oxygen demand, biochemical oxygen demand, conductivity, total nitrogen content, total phosphorus content, ammonia nitrogen content, nitrate content, phosphate content, residual chlorine content, total chlorine content, heavy metal concentration, hardness, and turbidity; and the biological information comprises one or more of the refractive index of water samples containing microorganisms under light illumination of different wavelengths and / or directions, the abundance and / or uniformity of biological macromolecules, community genomes, colony morphological characteristics, and the number of colonies. The double-chamber bioelectrochemical system reactor is a double-chamber reactor; the constant temperature regulation device comprises a thermistor sensor and a power regulator; and the water inflow adjustment device of the cathode chamber comprises an ultrasonic flow sensor and a flow regulating valve.

Images