Underground water outdoor in-situ characteristic organic pollutant monitoring method and system

Abstract

The invention discloses an underground water outdoor in-situ characteristic organic pollutant monitoring method and system. The system mainly comprises a characteristic organic pollutant monitoring probe, a power supply module and a data acquisition and transmission module, the characteristic organic pollutant monitoring probe is arranged in an underground water monitoring well and is used for detecting the concentration of characteristic organic pollutants in underground water in situ, outputting a detection signal and transmitting data to the management platform; the data acquisition and transmission module is connected with the characteristic organic pollutant monitoring probe, acquires a detection signal of the characteristic organic pollutant monitoring probe, and sends detection data to the remote monitoring terminal by using the wireless transmission module; and the power supply module drives the data acquisition and transmission module and the characteristic organic pollutant monitoring probe. The underground water outdoor in-situ characteristic organic pollutants are monitored in real time through the probe, the accuracy of water quality measurement is improved, and the problem that errors are large during measurement is solved.

Description

Technical Field

[0001] The present application relates to the field of water quality monitoring technology, and in particular to an in-situ monitoring method and system for groundwater organic pollutants that is suitable for long-term outdoor work and does not require manual operation. Background Art

[0002] With the growth of the world's population and the development of industrial and agricultural production, water consumption is also increasing. At the same time, due to human production and life, surface and groundwater bodies are polluted, water quality deteriorates, and limited water resources are even more scarce. In the case of such a shortage of water resources, water quality measurement is of great significance. Among them, water quality measurement refers to the unified regular or irregular detection of chemical substances, suspended matter, sediments and water ecosystems in water, the determination of the types, concentrations and changing trends of pollutants in water, and the evaluation of water quality conditions.

[0003] Traditional monitoring of characteristic organic pollutants in groundwater requires manual sampling at regular intervals, and then the samples are transported to the laboratory for analysis and testing. This method has many shortcomings, such as heavy workload, high cost, and delayed detection. On the other hand, although there are also practices of installing analytical instruments on site, most instruments require reliable power supply and manual operation and maintenance, and it is difficult to work in harsh outdoor environments for a long time.

[0004] The methods of water quality monitoring in the prior art, such as patent application 201711408003.9, disclose an integrated automatic control device for groundwater online monitoring and representative water sample collection and its control method, which relates to the field of groundwater monitoring and water sample collection technology. The present invention includes a control operation station arranged on the ground, a representative water sample judgment and collection system, and an online in-situ monitoring system connected to the control operation station by a rope and placed under the groundwater level in the well; the representative water sample judgment and collection system is connected to a water pump located under the groundwater level through a water pipe; the water pump is connected to a stagnant water collector and a water sample collector through a water pipe, and the online spectral water quality monitor 2 and the conventional parameter water quality analyzer 2 of the representative water sample judgment and collection system are used to monitor and analyze the water in the stagnant water collector and the water sample collector. However, in order to ensure that the monitored water sample is fresh from the aquifer, the patent application needs to dig a certain depth of water to perform multi-point sampling of the water sample, which is not applicable in actual use.

[0005] Patent application 202210005589.9 discloses an in-situ monitoring device and method for VOC gas in soil, which relates to the field of volatile organic compound contaminated soil and groundwater treatment technology. The in-situ monitoring rod group includes a monitoring rod and a probe connected in sequence from top to bottom. The side wall of the monitoring rod has a monitoring hole, and the side wall of the probe has an air extraction hole; the monitoring hole is connected to the monitoring pipeline, and the monitoring pipeline is provided with an extraction influence range monitoring component. The air extraction hole, the gas detection device and the air pump are connected in sequence through the air extraction pipeline, and the outlet of the air pump is respectively connected to the tail gas pipeline and the gas collection device; the control module is respectively connected to the extraction influence range monitoring component, the gas detection device and the air pump. Although this patent application can continuously monitor the characteristic organic pollutant gas in the soil in situ, the monitoring method is through the collection of gas samples, and the emission of gas is only a way of characteristic organic pollutants. Therefore, there is a problem of inaccurate monitoring, which is difficult to apply to the characteristic organic pollutant monitoring of groundwater.

[0006] Therefore, improvement is urgently needed. Summary of the invention

[0007] Based on this, the primary purpose of the present invention is to provide a method and system for outdoor in-situ characteristic organic pollutant monitoring of groundwater. This method and system can improve the accuracy of water quality measurement by using probes to monitor outdoor in-situ characteristic organic pollutants in groundwater in real time, thereby avoiding the problem of large errors caused by measurement.

[0008] Another object of the present invention is to provide a method and system for outdoor in-situ monitoring of characteristic organic pollutants in groundwater. The method and system can obtain the concentration data of characteristic organic pollutants in groundwater in real time and accurately by inserting the probe into the water well. No manual operation and maintenance are required, and the method and system can adapt to long-term outdoor work, which is convenient and practical.

[0009] Another object of the present invention is to provide a method and system for outdoor in-situ monitoring of characteristic organic pollutants in groundwater. The method and system are powered by solar energy and have low operating costs. The detection data are transmitted wirelessly to facilitate remote monitoring.

[0010] To achieve the above object, the technical solution of the present invention is:

[0011] A groundwater outdoor in-situ characteristic organic pollutant monitoring system, the system mainly comprises: a characteristic organic pollutant monitoring probe, a power module, a data acquisition module, and a transmission module.

[0012] The characteristic organic pollutant monitoring probe is set in the groundwater monitoring well to detect the concentration of characteristic organic pollutants in groundwater in situ. The characteristic organic pollutant monitoring probe adopts a high-pressure sealed cabin design, in which the signal board and optical elements are arranged. The organic matter in the water is detected through the fluorescent micro-efficient excitation and high-throughput collection optical system, which can better test the monitoring factors, output the detection signal, and transmit the data to the management platform;

[0013] The data acquisition and transmission module is connected to the characteristic organic pollutant monitoring probe to obtain its detection value (the calculation algorithm is located inside the probe). The data acquisition and transmission module includes a data acquisition module and a transmission module. The transmission module receives the digital data from the data acquisition module and uses wireless transmission technology, such as 4G / 5G network, to send the data to the remote monitoring terminal safely and efficiently.

[0014] The power module drives the data acquisition and transmission module and the characteristic organic pollutant monitoring probe.

[0015] Furthermore, the characteristic organic pollutant monitoring probe is composed of an outer shell, a characteristic organic pollutant sensor, a signal processing circuit and a data line; the outer shell is made of corrosion-resistant material, and a plurality of characteristic organic pollutant sensors are installed at its lower part for detecting the concentration of different types of characteristic organic pollutant molecules in groundwater. The original signal output by the characteristic organic pollutant sensor is amplified, filtered and processed by the signal processing circuit, and the digital data is obtained and then output through the data line.

[0016] Furthermore, the system may also include solar panels or batteries to provide continuous power for the system.

[0017] Furthermore, the power module is usually installed near the wellhead so that the existing solar panels or batteries can be used to power the entire system.

[0018] The monitoring system of the present invention can obtain the characteristic organic pollutant concentration data of groundwater in real time and accurately by inserting the probe into the water well. Since it does not require manual operation and maintenance, it can adapt to long-term outdoor work.

[0019] It can be powered by solar energy or batteries, with low operating costs; detection data is transmitted wirelessly, making remote monitoring convenient.

[0020] The present invention also provides a method for monitoring outdoor in-situ characteristic organic pollutants in groundwater, the method comprising the following steps:

[0021] Step 1, characteristic organic pollutant monitoring probe collects groundwater data;

[0022] The groundwater data includes the concentrations of different types of characteristic organic pollutant molecules.

[0023] The concentration of the characteristic organic pollutant molecules is collected by the following algorithm:

[0024] Use linear regression or other appropriate statistical methods to establish a calibration curve based on the fluorescence intensity and concentration data of the standard solution. The formula is:

[0025] I=k·C+b

[0026] Where: I is the fluorescence intensity, C is the concentration of characteristic organic pollutants, k is the proportionality constant, and b is the intercept.

[0027] The specific implementation steps are as follows:

[0028] 101, measuring the fluorescence intensity of the sample;

[0029] 102, the calibration curve was established using the linear regression method;

[0030] 103, calculate sample concentrations using the calibration curve.

[0031] Step 2, the characteristic organic pollutant monitoring probe packages the collected groundwater data and sends it to the data acquisition and transmission module using the MODBUS protocol in 485 or 232 communication mode;

[0032] Step 3: The data acquisition and transmission module transmits the concentrations of different types of characteristic organic pollutant molecules in the collected groundwater to the remote monitoring terminal.

[0033] Furthermore, in step 103, a calculation algorithm for the concentration of characteristic organic pollutants in groundwater is set inside the characteristic organic pollutant monitoring probe 1. The algorithm not only takes into account the fluorescence intensity data, but also comprehensively considers the influence of various environmental factors such as temperature, pH value, dissolved oxygen, conductivity, turbidity, pressure, and total organic carbon to improve the accuracy and reliability of the measurement, as follows:

[0034] 1) Modified Stern-Volmer equation: Taking into account the static and dynamic quenching effects, the relationship between fluorescence intensity and the concentration of characteristic organic pollutants can be more accurately described. The fitted modified Stern-Volmer equation is:

[0035] Formula: I = I0 / (1+K*f*[Q])

[0036] Where I is the observed fluorescence intensity, I0 is the fluorescence intensity without quenching, K is the Stern-Volmer constant, f is the fraction of accessible fluorophores, and [Q] is the concentration of the quencher (i.e., the characteristic organic pollutant);

[0037] 2) Temperature correction: Use the Arrhenius equation to correct the effect of temperature on the reaction rate. This is critical to ensure consistency of measurements under different temperature conditions. The formula is as follows:

[0038] Correction factor: exp((Ea / R)*(1 / T0-1 / T))

[0039] Where Ea is the activation energy, R is the gas constant, T0 is the standard temperature, and T is the actual temperature;

[0040] 3) pH correction: Based on a variant of the Henderson-Hasselbalch equation, the effect of pH on the dissociation state of certain characteristic organic pollutants is taken into account. The formula is as follows:

[0041] pKa = correction factor * assumed pKa value

[0042] Correction factor: 1 / (1+10^(pH-pKa)) where pKa is the acid dissociation constant.

[0043] 4) Dissolved oxygen correction: The exponential decay model is used to simulate the effect of dissolved oxygen on the oxidation of certain characteristic organic pollutants. The formula is as follows:

[0044] Correction factor: 1-exp(-DO / 5)

[0045] Where DO is the dissolved oxygen concentration.

[0046] 5) Conductivity correction: Polynomial fitting is used to consider the effect of ionic strength in water on fluorescence.

[0047] Correction factor: 1+0.001*conductivity-0.000001*conductivity^2

[0048] 6) Turbidity correction: Based on a variation of the Beer-Lambert law, taking into account scattering and absorption effects.

[0049] Correction factor: exp(-0.01*turbidity)

[0050] 7) Pressure correction: A linear model is used to consider the effect of pressure on the solubility of characteristic organic pollutants.

[0051] Correction factor: pressure / standard_pressure

[0052] 8) Total organic carbon (TOC) interference correction: takes into account the interference of other organic matter on the measurement.

[0053] Correction factor: 1 / (1+0.01*total_organic_carbon)

[0054] 9) Spectral interference correction: Based on the excitation-emission matrix, the mutual influence of different wavelengths is taken into account.

[0055] Correction factor: 1 / mean(emission_excitation_matrix)

[0056] 10) Nonlinear response correction: Use polynomial fitting to simulate nonlinear effects at high concentrations.

[0057] Correction factor: 1+0.1*concentration-0.001*concentration^2

[0058] 11) Uncertainty estimate: Provide a confidence interval for the measurement result, assuming a relative uncertainty of 10%.

[0059] By comprehensively considering these factors, the algorithm can significantly improve the accuracy and reliability of characteristic organic pollutant concentration measurements. It not only takes into account factors that directly affect the measurement, but also includes possible interference sources and nonlinear effects. This complex algorithm can help researchers more accurately assess the pollution of characteristic organic pollutants in groundwater and provide more reliable data support for environmental monitoring and pollution control.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] The present invention uses a probe to monitor outdoor in-situ characteristic organic pollutants in groundwater in real time, thereby improving the accuracy of water quality measurement and avoiding the problem of large errors caused by real-time measurement.

[0062] The present invention can obtain the characteristic organic pollutant concentration data of groundwater in real time and accurately by inserting the probe into the water well in its original position, without the need for manual operation and maintenance, and can adapt to long-term outdoor work, which is convenient and practical.

[0063] Moreover, the present invention can be powered by solar energy, and has low operating costs; detection data is transmitted wirelessly, which is convenient for remote monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for describing the embodiments are briefly introduced below.

[0065] Figure 1 It is a structural diagram of the system implemented by the present invention.

[0066] Figure 2 It is a schematic diagram of an implementation method of a data processing device for water quality monitoring implemented by the present invention.

[0067] Figure 3 It is a schematic diagram of an implementation method of a data processing device for water quality monitoring implemented by the present invention.

[0068] Figure 4 It is a schematic diagram of an embodiment of a computer-readable storage medium implemented in the present invention.

[0069] Figure 5 It is a circuit schematic diagram of the signal processing circuit implemented by the present invention. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0071] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0072] It should also be noted that when an element is referred to as being "fixed on" or "disposed on" another element, it may be directly on the other element or there may be an intermediate element at the same time. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intermediate element at the same time.

[0073] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0074] It can be understood that the data processing method for water quality monitoring adopted in the present invention can be applied to industries including but not limited to water quality measurement. The following embodiments take water quality measurement as an example to introduce the measurement method of the present invention in detail, and the water quality measurement in the embodiments of the present invention can specifically include the measurement of iodine ions, heavy metals, volatile phenols and other substances in water quality samples.

[0075] like Figure 1As shown, it is a groundwater characteristic organic pollutant monitoring system implemented by the present invention. As shown in the figure, the system includes a characteristic organic pollutant monitoring probe 1, a power module 2 and a data acquisition and transmission module 3.

[0076] Among them, characteristic organic pollutant monitoring probe 1 is as follows Figure 2 As shown, the characteristic organic pollutant monitoring probe 1 is mainly composed of an outer shell 11, a characteristic organic pollutant sensor 12, and a signal processing circuit 13 (such as Figure 5 The outer shell 11 is made of corrosion-resistant material, and a plurality of characteristic organic pollutant sensors 12 are installed at the bottom thereof, which are used to detect the concentration of different types of characteristic organic pollutant molecules in groundwater. The characteristic organic pollutant monitoring probe 1 adopts a high-pressure sealed cabin design, in which the signal board and optical elements are arranged, and the organic matter in the water is detected by the fluorescent micro-high-efficiency excitation and high-throughput collection optical system, which can better test the monitoring factors, output the detection signal, and transmit the data to the management platform; the original signal output by the characteristic organic pollutant sensor 12 is amplified, filtered, etc. by the signal processing circuit 13, and the digital data is obtained and output through the data line 14.

[0077] Power module 2 Figure 3 As shown, the power module 2 includes a solar panel 21 and a battery pack 22. The solar panel 21 absorbs sunlight and converts it into electrical energy to charge the battery pack 22. The battery pack 22 provides working power for the entire system.

[0078] Data acquisition and transmission module 3 Figure 4 As shown, the module 3 includes a data acquisition unit 31, a wireless transmission unit 32 and an antenna 33. The data acquisition unit 31 is connected to the probe 1 via a data line to obtain characteristic organic pollutant detection data. The wireless transmission unit 32 transmits the detection data to a remote terminal in a wireless manner via the antenna 33.

[0079] The above system does not require manual operation and maintenance, and can use solar energy to work stably in an outdoor environment for a long time, thereby realizing real-time online monitoring of characteristic organic pollutants in groundwater.

[0080] The present invention also provides a method for outdoor in-situ monitoring of characteristic organic pollutants in groundwater implemented by the above monitoring system, the method mainly comprising the following steps:

[0081] Step 1, characteristic organic pollutant monitoring probe collects groundwater data;

[0082] The groundwater data include the concentrations of different types of characteristic organic pollutant molecules;

[0083] The concentration of the characteristic organic pollutant molecules is collected by the following algorithm:

[0084] Use linear regression or other appropriate statistical methods to establish a calibration curve based on the fluorescence intensity and concentration data of the standard solution. The formula is:

[0085] I=k·C+b

[0086] Where: I is the fluorescence intensity, C is the concentration of characteristic organic pollutants, k is the proportional constant, and b is the intercept;

[0087] Step 2, the characteristic organic pollutant monitoring probe packages the collected groundwater data and sends it to the data acquisition and transmission module using the MODBUS protocol in 485 or 232 communication mode;

[0088] Step 3: The data acquisition and transmission module transmits the concentrations of different types of characteristic organic pollutant molecules in the collected groundwater to the remote monitoring terminal.

[0089] In step 1, the specific implementation is as follows:

[0090] 101, measuring the fluorescence intensity of the sample;

[0091] 102, the calibration curve was established using the linear regression method;

[0092] 103, calculate sample concentrations using the calibration curve.

[0093] This system uses an advanced multivariate correction algorithm to calculate the concentration of characteristic organic pollutants in groundwater. The calculation algorithm is located inside the characteristic organic pollutant monitoring probe 1. The algorithm not only takes into account the fluorescence intensity data, but also integrates the influence of multiple environmental factors to improve the accuracy and reliability of the measurement. The following are the main components of the algorithm and its principles:

[0094] 1) Modified Stern-Volmer equation: This is the core of the algorithm and is used to calculate the initial characteristic organic pollutant concentration. It takes into account static and dynamic quenching effects and can more accurately describe the relationship between fluorescence intensity and characteristic organic pollutant concentration.

[0095] Formula: I = I0 / (1+K*f*[Q])

[0096] Where I is the observed fluorescence intensity, I0 is the fluorescence intensity without quenching, K is the Stern-Volmer constant, f is the fraction of accessible fluorophores, and [Q] is the concentration of the quencher (i.e., the characteristic organic pollutant).

[0097] 2) Temperature correction (Arrhenius equation): Use the Arrhenius equation to correct for the effect of temperature on the reaction rate. This is critical to ensure consistent measurements under different temperature conditions.

[0098] Correction factor: exp((Ea / R)*(1 / T0-1 / T))

[0099] Among them, Ea is the activation energy, R is the gas constant, T0 is the standard temperature, and T is the actual temperature.

[0100] 3) pH correction: Based on a variant of the Henderson-Hasselbalch equation, the effect of pH on the dissociation state of certain characteristic organic pollutants is taken into account.

[0101] Correction factor: 1 / (1+10^(pH-pKa)) where pKa is the acid dissociation constant.

[0102] 4) Dissolved oxygen correction: Use an exponential decay model to simulate the effect of dissolved oxygen on the oxidation of certain characteristic organic pollutants.

[0103] Correction factor: 1-exp(-DO / 5)

[0104] Where DO is the dissolved oxygen concentration.

[0105] 5) Conductivity correction: Polynomial fitting is used to consider the effect of ionic strength in water on fluorescence.

[0106] Correction factor: 1+0.001*conductivity-0.000001*conductivity^2

[0107] 6) Turbidity correction: Based on a variation of the Beer-Lambert law, taking into account scattering and absorption effects.

[0108] Correction factor: exp(-0.01*turbidity)

[0109] 7) Pressure correction: A linear model is used to consider the effect of pressure on the solubility of characteristic organic pollutants.

[0110] Correction factor: pressure / standard_pressure

[0111] 8) Total organic carbon (TOC) interference correction: takes into account the interference of other organic matter on the measurement.

[0112] Correction factor: 1 / (1+0.01*total_organic_carbon)

[0113] 9) Spectral interference correction: Based on the excitation-emission matrix, the mutual influence of different wavelengths is taken into account.

[0114] Correction factor: 1 / mean(emission_excitation_matrix)

[0115] 10) Nonlinear response correction: Use polynomial fitting to simulate nonlinear effects at high concentrations.

[0116] Correction factor: 1+0.1*concentration-0.001*concentration^2

[0117] 11) Uncertainty estimate: Provide a confidence interval for the measurement result, assuming a relative uncertainty of 10%.

[0118] By comprehensively considering these factors, the algorithm can significantly improve the accuracy and reliability of characteristic organic pollutant concentration measurements. It not only takes into account factors that directly affect the measurement, but also includes possible interference sources and nonlinear effects. This complex algorithm can help researchers more accurately assess the pollution of characteristic organic pollutants in groundwater and provide more reliable data support for environmental monitoring and pollution control.

[0119] In particular, the correction factor can reliably correct the interference caused by temperature, pH value, dissolved oxygen, conductivity, turbidity, pressure, total organic carbon, spectral interference and nonlinear response, and accurately calculate the concentration of characteristic organic pollutants, making the detection more accurate.

[0120] The specific implementation process of the algorithm is as follows:

[0121]

[0122]

[0123]

[0124]

[0125] Invention Embodiments.

[0126] The following is a specific embodiment: The monitoring system is deployed in a groundwater monitoring well with a depth of 80 meters near a chemical park. The monitoring well is located 1 km downstream of the chemical park and is used to monitor the possible spread of groundwater pollution.

[0127] System composition:

[0128] Characteristic organic pollutant monitoring probe:

[0129] Model:S310.

[0130] Size: diameter 50mm, length 500mm.

[0131] Material: 316L stainless steel housing, anti-corrosion coating.

[0132] Sensor: Composite sensor array of 8 specific characteristic organic pollutants.

[0133] Measuring range: 0.1-1000ppb.

[0134] Resolution: 0.1ppb.

[0135] Response time: <60 seconds.

[0136] Power module:

[0137] Solar panel: 200W monocrystalline silicon, conversion efficiency>20%.

[0138] Battery pack: 24V, 200Ah lithium-ion battery, supports >7 days of operation without sunlight.

[0139] Data acquisition and transmission module:

[0140] Processor: ARM Cortex-M4, 168MHz.

[0141] Storage: 32GB SD card, can store >1 year of data.

[0142] Communication: 4G LTE module, supports remote data transmission and system control.

[0143] Monitoring process:

[0144] The system performs a complete monitoring cycle every 30 minutes. The specific steps are as follows:

[0145] The probe activates and performs a self-test and calibration.

[0146] Raw fluorescence data were collected for 60 seconds.

[0147] Environmental parameters are measured simultaneously: temperature, pH, dissolved oxygen, conductivity, turbidity, pressure and total organic carbon. The data are processed using algorithms to calculate the concentration of characteristic organic pollutants.

[0148] Transmit the results to a remote server.

[0149] Data processing:

[0150] The following is a specific data processing example:

[0151]

[0152]

[0153]

[0154] Monitoring results:

[0155] The system continued to run stably in the first three months after deployment, collecting a total of 4,320 data points. Here are some key findings:

[0156] Average characteristic organic pollutant concentration: 5.73±0.58ppb.

[0157] The highest characteristic organic pollutant concentration: 12.45±1.25ppb (occurred after a heavy rain).

[0158] Minimum characteristic organic pollutant concentration: 0.82±0.08ppb.

[0159] The concentration of characteristic organic pollutants showed a significant positive correlation with rainfall (correlation coefficient r = 0.72).

[0160] The main characteristic organic pollutants detected include: benzene, toluene, xylene and trichloroethylene.

[0161] The long-term operation of this embodiment shows that the system can meet the requirements of long-term stable operation without manual maintenance, accurately monitor the changes of characteristic organic pollutants in groundwater, and the monitoring data can be reliably transmitted to the remote monitoring terminal.

[0162] In summary, the present invention improves the accuracy of water quality measurement by using the probe to monitor outdoor in-situ characteristic organic pollutants in groundwater in real time, thereby avoiding the problem of large errors caused by real-time measurement.

[0163] The present invention can obtain the characteristic organic pollutant concentration data of groundwater in real time and accurately by inserting the probe into the water well in its original position, without the need for manual operation and maintenance, and can adapt to long-term outdoor work, which is convenient and practical.

[0164] Moreover, the present invention can be powered by solar energy, and has low operating costs; detection data is transmitted wirelessly, which is convenient for remote monitoring.

[0165] The above descriptions are merely embodiments of the present application and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for monitoring outdoor in-situ characteristic organic pollutants in groundwater. It is characterized in that The method comprises the following steps: Step 1, characteristic organic pollutant monitoring probe collects groundwater data; The groundwater data include the concentrations of different types of characteristic organic pollutant molecules; The concentration of the characteristic organic pollutant molecules is collected by the following algorithm: The calibration curve was established based on the fluorescence intensity and concentration data of the standard solution. The formula is: I=k·C+b Where: I is the fluorescence intensity, C is the concentration of characteristic organic pollutants, k is the proportional constant, and b is the intercept; Step 2, the characteristic organic pollutant monitoring probe packages the collected groundwater data and sends it to the data acquisition and transmission module using the MODBUS protocol in 485 or 232 communication mode; Step 3: The data acquisition and transmission module transmits the concentrations of different types of characteristic organic pollutant molecules in the collected groundwater to the remote monitoring terminal.

2. The method for monitoring outdoor in-situ characteristic organic pollutants in groundwater according to claim 1, It is characterized in that In step 1, the specific implementation steps are as follows: 101, measuring the fluorescence intensity of the sample; 102, the calibration curve was established using the linear regression method; 103, calculate sample concentrations using the calibration curve.

3. The method for monitoring outdoor in-situ characteristic organic pollutants in groundwater according to claim 2, It is characterized in that In step 103, the calculation algorithm for the concentration of characteristic organic pollutants in groundwater is set inside the characteristic organic pollutant monitoring probe 1, and the specific algorithm is as follows: 1) Modified Stern-Volmer equation. The modified Stern-Volmer equation is: I=I0 / (1+K*f*[Q]) Where I is the observed fluorescence intensity, I0 is the fluorescence intensity without quenching, K is the Stern-Volmer constant, f is the fraction of accessible fluorophores, and [Q] is the concentration of the quencher (i.e., the characteristic organic pollutant); 2) Temperature correction: Use the Arrhenius equation to correct the effect of temperature on the reaction rate. The formula is as follows: Correction factor: exp((Ea / R)*(1 / T0-1 / T)) Where Ea is the activation energy, R is the gas constant, T0 is the standard temperature, and T is the actual temperature; 3) pH correction: Based on a variant of the Henderson-Hasselbalch equation, the effect of pH on the dissociation state of certain characteristic organic pollutants is taken into account: pKa = correction factor * assumed pKa value Correction factor: 1 / (1+10^(pH-pKa)) where pKa is the acid dissociation constant; 4) Dissolved oxygen correction: Use an exponential decay model to simulate the effect of dissolved oxygen on the oxidation of certain characteristic organic pollutants: Correction factor: 1-exp(-DO / 5) Where DO is the dissolved oxygen concentration; 5) Conductivity correction: Polynomial fitting is used to consider the effect of ionic strength in water on fluorescence. Correction factor: 1+0.001*conductivity-0.000001*conductivity^2; 6) Turbidity correction: Based on a variation of the Beer-Lambert law, taking into account scattering and absorption effects, Correction factor: exp(-0.01*turbidity); 7) Pressure correction: A linear model is used to consider the effect of pressure on the solubility of characteristic organic pollutants. Correction factor: pressure / standard_pressure; 8) Total organic carbon (TOC) interference correction: This takes into account the interference of other organic matter on the measurement. Correction factor: 1 / (1+0.01*total_organic_carbon); 9) Spectral interference correction: Based on the excitation-emission matrix, the mutual influence of different wavelengths is taken into account. Correction factor: 1 / mean(emission_excitation_matrix); 10) Nonlinear response correction: Use polynomial fitting to simulate nonlinear effects at high concentrations. Correction factor: 1+0.1*concentration-0.001*concentration^2.

4. The method for monitoring outdoor in-situ characteristic organic pollutants in groundwater according to claim 3, It is characterized in that In step 1, the calculation algorithm for the concentration of characteristic organic pollutants in groundwater further includes: 11) Uncertainty estimate: Provide a confidence interval for the measurement result, assuming a relative uncertainty of 10%.

5. A groundwater outdoor in-situ characteristic organic pollutant monitoring system as claimed in claim 1, It is characterized in that The system mainly includes: a characteristic organic pollutant monitoring probe, a power module and a data acquisition and transmission module; The characteristic organic pollutant monitoring probe is set in the groundwater monitoring well to detect the concentration of characteristic organic pollutants in the groundwater in situ, output the detection signal, and transmit the data to the management platform; the characteristic organic pollutant monitoring probe adopts a high-pressure sealed cabin design, in which the signal board and optical elements are arranged, and the organic matter in the water is detected through the fluorescent micro-high-efficiency excitation and high-throughput collection optical system; The data acquisition and transmission module is connected to the characteristic organic pollutant monitoring probe to obtain its detection value, wherein the data acquisition and transmission module includes a data acquisition module and a transmission module. The transmission module receives the digital data from the data acquisition module and uses wireless transmission technology to send the data to the remote monitoring terminal safely and efficiently; The power module drives the data acquisition and transmission module and the characteristic organic pollutant monitoring probe.

6. The groundwater outdoor in-situ characteristic organic pollutant monitoring system according to claim 5, It is characterized in that The characteristic organic pollutant monitoring probe consists of an outer shell, a characteristic organic pollutant sensor, a signal processing circuit and a data line; the outer shell is made of corrosion-resistant material, and a plurality of characteristic organic pollutant sensors are installed at the lower part thereof, which are used to detect the concentration of different types of characteristic organic pollutant molecules in groundwater. The original signal output by the characteristic organic pollutant sensor is amplified, filtered and processed by the signal processing circuit, and the digital data is obtained and then output through the data line.

7. The groundwater outdoor in-situ characteristic organic pollutant monitoring system according to claim 1, It is characterized in that The system may also include solar panels or batteries to provide continuous power to the system.

8. The groundwater outdoor in-situ characteristic organic pollutant monitoring system according to claim 5, It is characterized in that The power module is installed at the wellhead so that the existing solar panels or batteries can be used to power the entire system.

Images