A method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy

Abstract

The present invention proposes a method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy, specifically collecting water samples from inspection wells before and after possible mixing points, filtering with a filter membrane, detecting with an ultraviolet-visible spectrophotometer, and obtaining an EEM matrix by fluorescence spectrophotometer detection. The EEM matrix is ​​corrected for the fluorescence inner filter effect using ultraviolet-visible absorption spectrum data, and the primary and secondary Raman scattering and Rayleigh scattering signals are deducted from the EEM matrix. The EEM matrix is ​​peak-picked and numerically normalized. The EEM matrix of the inspection well water sample after the possible mixing point is subtracted from the EEM matrix before the possible mixing point to obtain a spectral residual matrix, which is compared with the spectral library to determine whether it is an actual mixing point, and the mixed water is traced. The present invention can better adapt to the characteristics of rainwater and sewage mixing in industrial areas, such as complex water quality, large differences in the position and intensity of fluorescence characteristic peaks, intermittent and sudden emission of pollution sources, etc., and improve the accuracy of diagnosis.

Description

Technical Field

[0001] The present invention belongs to the field of municipal drainage pipe network engineering, and relates to a method for diagnosing industrial wastewater mixing points, and in particular to a method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy. The characteristic information of the fluorescence spectrum is used to quickly and accurately identify and trace the industrial wastewater. Background Art

[0002] In my country's urban separate drainage system, rainwater and sewage mixing is common, that is, sewage is mixed into the rainwater pipes and discharged into urban water bodies without treatment, or pollutants are silted in the rainwater pipe network and discharged into the receiving water body on rainy days, causing most water bodies to be black and smelly for a long time or repeatedly black and smelly on rainy days. The main reasons are that the urban drainage system is not planned reasonably and the operation is unstable, resulting in the failure to separate the rainwater and sewage pipe networks or the failure to deal with pipe network damage and defects in a timely manner.

[0003] The problem of rainwater and sewage mixing not only affects the normal operation of urban drainage systems, but also poses a serious threat to urban water environment, destroys the balance of water ecosystems, and reduces the quality of life of urban residents. At a time when my country's environmental infrastructure construction is becoming increasingly perfect and pollution prevention and control has entered a critical stage, rainwater and sewage mixing is the main reason for the black and smelly problems in most water bodies. It can be seen that the root cause of the black and smelly problem is on the shore, and the core lies in the pipe network. "Source control and pollution interception" is the fundamental measure to control the black and smelly problem, and the key to achieving this goal lies in the identification of the mixing points of the rainwater and sewage pipe network and the tracing of the pollution source.

[0004] Manual inspection is a common method in the practice of rainwater-sewage mixing engineering. By observing whether there is water flow in the rainwater inspection well on dry days, it is judged whether there is external water mixing in the rainwater pipe; further technologies include geophysical detection technology based on CCTV and QV detection and water quality characteristic factor method based on ammonia nitrogen and conductivity. However, these methods are difficult to balance workload, cost and accuracy. Therefore, exploring more efficient, accurate and economical methods for diagnosing rainwater-sewage mixing points and tracing pollution sources has great engineering application value.

[0005] In recent years, three-dimensional fluorescence has been widely used in academic research such as water supply and sewage treatment processes, and characterization of dissolved organic matter (DOM) migration and transformation in surface water and soil due to its simple measurement and large amount of information. In the early warning and tracing of surface water pollution, the application of three-dimensional fluorescence spectroscopy as a water quality fingerprint has also appeared, indicating that it also has application prospects in engineering. It is feasible to use three-dimensional fluorescence for the diagnosis of rainwater and sewage mixing problems in drainage networks. Summary of the invention

[0006] The purpose of the present invention is to provide a method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy.

[0007] The present invention provides a method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy, comprising the following steps:

[0008] (1) Collect water samples from inspection wells before and after possible mixing points;

[0009] (2) filtering through a filter membrane, detecting with a UV-visible spectrophotometer, and detecting with a fluorescence spectrophotometer to obtain an EEM matrix;

[0010] (3) Use the UV-visible absorption spectrum data to correct the fluorescence inner filter effect of the EEM matrix and subtract the first and second order Raman scattering and Rayleigh scattering signals from the EEM matrix;

[0011] (4) Peak picking is performed on the EEM matrix. The EEM matrix is ​​processed using a numerical normalization method to eliminate the dilution effect of the mixed water. A characteristic peak position Ex / Em of the EEM A water sample before mixing is selected. The two spectral matrices are divided by their respective values ​​at this position so that the fluorescence signal of each spectral matrix at this Ex / Em is 1;

[0012] (5) Subtract the EEM matrix of the inspection well water sample after the possible mixing point from the EEM matrix before the possible mixing point to obtain the spectral residual matrix;

[0013] (6) Compare with the spectrum library to determine whether it is an actual mixing point and trace the source of the mixed water.

[0014] In the present invention, whether industrial wastewater is mixed is determined based on the change in the fluorescent fingerprint of the inspection well before and after the "branch pipe access point" on a sunny day, and the source is traced by spectral comparison.

[0015] In the present invention, 24 hours after rainfall, water samples are collected from the two inspection wells in front and behind which are close to the "branch access point" of the rainwater pipe or the point where there is obvious external water input; industrial wastewater from the surrounding factory areas is sampled, and a spectral database is subsequently formed, which is recorded as the pollution source spectral library.

[0016] In the present invention, the collected water samples are refrigerated at 0-10° C. and stored for no more than 7 days.

[0017] In the present invention, the purpose of using a filter membrane is to remove suspended particles and microorganisms, including but not limited to fungi, bacteria, etc. The filter membrane that can be used is 0.22-0.45 μm.

[0018] In the present invention, a UV-visible spectrophotometer is used to detect water samples, and the measurement band is 200-550nm; a fluorescence spectrophotometer is used to perform three-dimensional fluorescence spectrum detection on the water samples, and the excitation wavelength range is 200-450nm, and the emission wavelength range is 250-550nm.

[0019] In the present invention, Ex is the excitation wavelength, Em is the emission wavelength, and Ex / Em refers to the coordinate positions of the specified excitation wavelength and emission wavelength in the EEM matrix.

[0020] In the present invention, if the residual fluorescence peak and the industrial wastewater EEM in the spectral library show a high degree of consistency in certain areas, it means that the mixed wastewater has the same or similar fluorescence characteristics as the wastewater of the industrial enterprise, and it is preliminarily considered that the industrial enterprise has discharged wastewater. If the residual peak intensity is less than 20% of the peak before subtraction, it means that the degree of mixing is low, or it belongs to the normal fluctuation range of water quality.

[0021] In a preferred embodiment of the present invention, the specific steps of the method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy are as follows:

[0022] (1) Collect 50 mL of water samples from the inspection wells before and after the possible mixing point, label them separately, and transport them to the laboratory in a refrigerated manner;

[0023] (2) filtering the water sample obtained in step (1) using a 0.45 μm filter membrane and storing it in a refrigerator at 4° C.;

[0024] (3) using an ultraviolet-visible spectrophotometer to detect the water sample obtained in step (2), with a measurement band of 200-550 nm and a step length of 1 nm, to obtain ultraviolet-visible absorption spectrum data of the inspection well water sample before and after the possible mixing point;

[0025] (4) Perform three-dimensional fluorescence spectrum detection on the water sample obtained in step (2) using a fluorescence spectrophotometer, using a quartz cuvette, setting the voltage to 400 V to avoid generating too much background noise at low excitation wavelengths, setting the excitation wavelength range to 200-450 nm, the emission wavelength range to 250-550 nm, the slit width to 2 nm, and the scanning speed to 12000 nm / s, to obtain three-dimensional fluorescence data of the inspection well water samples before and after the possible mixing points, namely, the EEM matrix.

[0026] The slit width can be 2nm or 5nm. When the local spectral library is relatively complete and can reflect the fluorescence characteristic fluctuations of the same industrial wastewater, changing the slit width to 5nm can further shorten the detection time. In a preferred embodiment of the present invention, the slit width used is 5nm.

[0027] (5) using the UV-visible absorption spectrum data obtained in step (3) to correct the fluorescence inner filter effect of the EEM matrix obtained in step (4) to eliminate the attenuation and distortion of the fluorescence signal;

[0028] (6) subtracting the primary and secondary Raman scattering and Rayleigh scattering signals from the EEM matrix obtained in step (5), specifically, removing the values ​​of the regions with high fluorescence response and steep changes in the matrix, and then performing interpolation filling according to the triangular interpolation method to achieve the goal of eliminating the interference of the scattered signals;

[0029] (7) Peak picking is performed on the EEM matrix obtained in step (6), and numerical normalization is performed to obtain the EEM matrix of the inspection well water sample before and after the possible mixing point after preprocessing;

[0030] (8) Subtract the EEM matrix of the inspection well water sample after the possible mixing point from the EEM matrix of the inspection well water sample before the possible mixing point to obtain the spectral residual matrix, analyze the position and intensity changes of the fluorescence peak, and determine whether there is any external pollution or wastewater mixing;

[0031] (9) Compare the spectral residual matrix obtained in step (8) with the spectral library According to the number and position of the residual peaks, the spectrum of the pollution source that meets the characteristics is matched in the regional spectrum database. If the fluorescence peak and the industrial wastewater EEM in the spectrum library are highly consistent in certain areas, it means that the mixed wastewater has the same or similar fluorescence characteristics as the wastewater of the industrial enterprise. We can focus on investigating whether the industrial enterprise has illegal or wrong discharge of wastewater, narrow the scope of investigation, and provide an investigation direction for tracing the source. Combined with the direction of the pipeline network and GIS or GPS, the specific industrial enterprise that caused the mixing can be further determined.

[0032] In the present invention, EEM refers to three-dimensional fluorescence or excitation emission matrix, which obtains a spectrum of excitation wavelength-emission wavelength-fluorescence intensity through 3D scanning. This method is used in various applications requiring multivariate analysis, and is usually used to provide fingerprints for samples of many different components.

[0033] In the present invention, in step (6), if the water samples come from different test batches, before subtracting the primary and secondary Raman scattering and Rayleigh scattering signals from the EEM matrix, Raman normalization is performed to eliminate the influence of instrument state factors and test condition factors. Raman normalization is to divide each value of the matrix by the same value, which has little effect before and after. For convenience, it can be uniformly performed before subtracting scattering.

[0034] In the present invention, the spectral library in step (9) is obtained by collecting industrial wastewater samples and repeating steps (2) to (7).

[0035] The method for locating and tracing the mixed connection of rainwater pipes in industrial areas based on fluorescence spectroscopy of the present invention can diagnose the mixing point of industrial wastewater by monitoring the water conditions in the rainwater pipes, thereby judging whether there is external sewage and wastewater mixing, and tracing the pollution source by combining the fluorescence spectral characteristics of industrial wastewater. The water conditions include but are not limited to: complex water quality, variable positions of fluorescence characteristic peaks, intermittent pollution sources, and sudden rainwater and sewage mixing.

[0036] The method of the present invention can timely discover the discharge or exceeding of industrial wastewater, effectively control the problem of rainwater and sewage mixing in industrial areas, reduce the pollution of urban water environment by industrial wastewater, improve the water quality of receiving water bodies, restore the balance of water ecosystems, and improve the quality of life of urban residents; effectively save the cost of investigating and controlling the problem of rainwater and sewage mixing in industrial areas, reduce the operating pressure of urban drainage systems, and improve the operating efficiency and safety of urban drainage systems.

[0037] For the mixed rainwater and sewage in residential areas, the rainwater pipes are mainly mixed with domestic sewage, the incoming water is characterized by continuity and regularity, the water quality is relatively simple, the shape of the three-dimensional fluorescence spectrum changes little, and the position of the fluorescence characteristic peak is fixed. It is possible to try to quickly determine whether there is domestic sewage mixed in the rainwater pipe section through the direct reading of the three-dimensional fluorescence spectrum of the front and rear inspection wells, the changes in the fluorescence peak and regional integral. Compared with the mixed rainwater and sewage in residential areas, the mixed rainwater and sewage in industrial areas are obviously different. The mixed rainwater and sewage phenomenon is mainly caused by industrial wastewater mixing into the rainwater pipes. Due to the large water consumption in industrial areas and the large differences in the quality of wastewater from different industrial types, when mixed water occurs in the rainwater pipes in industrial areas, the water quality is more complicated and the conventional indicators fluctuate greatly. In addition, the illegal discharge of wastewater and non-point source pollution in the factory area occur from time to time in industrial areas, and are often intermittent, sudden, and complex in pollution sources, so that water can be observed in the inspection wells of the rainwater pipes, but there is no continuous water flow. These characteristics make the method of using fluorescence peak and regional integral to assist in distinguishing mixing points have great limitations in the diagnosis and tracing of rainwater and sewage mixing in industrial areas, and do not fully utilize the differences in fluorescence spectra of different industrial wastewaters. Therefore, the present invention proposes a more applicable and targeted spectral analysis method for the problem of rainwater and sewage mixing in industrial areas.

[0038] The beneficial effects of the present invention are:

[0039] (1) The water sample collection, pretreatment and measurement of the present invention are simple and easy to operate. The method is not affected by factors such as the inner diameter of the pipe network and pipeline defects. The cost is reduced by more than 70% compared with CCTV, and it is highly efficient and has fewer constraints.

[0040] (2) The present invention uses fluorescence fingerprint comparison, which can reflect more information about organic pollutants in water samples than indicators such as ammonia nitrogen, has strong anti-interference ability, and has great engineering application prospects. It is expected that portable fluorescence fingerprint analysis and comparison equipment will be developed based on this to achieve rapid diagnosis of mixed connection of rainwater pipe networks on sunny days.

[0041] (3) Compared with the mixed connection of rainwater and sewage in residential areas, the present invention can better adapt to the characteristics of mixed connection of rainwater and sewage in industrial areas, such as complex water quality, variable positions of fluorescence characteristic peaks, intermittent and sudden pollution sources, etc., thereby improving the accuracy of diagnosis.

[0042] (4) The present invention can quickly and accurately identify the mixing points and sources of industrial wastewater in rainwater pipes in industrial areas without the need to use CCTV, QV, sonar and other methods, avoiding interference with pipeline structures and urban roads, saving manpower, material and time costs, and improving engineering efficiency and environmental protection levels.

[0043] (5) The present invention can utilize three-dimensional fluorescence spectroscopy and ultraviolet-visible absorption spectroscopy to perform multi-dimensional characterization of water samples in rainwater pipes, making full use of the spectral characteristics of organic matter and improving the accuracy and sensitivity of water quality analysis.

[0044] (6) The present invention can classify and quantitatively analyze water samples based on the parameters of the three-dimensional fluorescence spectrum and the ultraviolet-visible absorption spectrum, thereby achieving the technical effect of accurately distinguishing rainwater runoff from different types of industrial wastewater, accurately diagnosing rainwater and sewage mixing points, and tracing the source of pollution.

[0045] (7) The present invention can be combined with a geographic information system (GIS) or a global positioning system (GPS) to locate and trace the mixing points in the rainwater pipe, and formulate corresponding treatment measures based on the location of the mixing points and the source of industrial wastewater, thereby improving the pertinence and effectiveness of investigation and treatment.

[0046] (8) The present invention provides an innovative method and theoretical basis for the research and application of the problem of mixed connection of rainwater and sewage in industrial areas, filling the technical gap in this field at home and abroad, and has high academic and engineering value.

[0047] (9) The present invention can effectively control the problem of rainwater and sewage mixing in industrial areas, reduce the pollution of urban water environment by industrial wastewater, improve the water quality of receiving water bodies such as urban rivers and lakes, restore the balance of the water ecosystem, and improve the quality of life of urban residents.

[0048] (10) The present invention can effectively save the cost of investigating and treating the problem of mixed rainwater and sewage in industrial areas, reduce the operating pressure of urban drainage systems, and improve the operating efficiency and safety of urban drainage systems.

[0049] (11) The present invention can effectively promote the research and innovation of the problem of mixed rainwater and sewage in industrial areas, promote the application and development of spectral technology in the field of environmental monitoring, and enhance my country's technological competitiveness and international influence in this field. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, each drawing in the following description is for some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0051] Figure 1 . Schematic diagram of the fluorescent fingerprint comparison principle and technical route of the present invention;

[0052] Figure 2 .EEM matrix diagram of Example 1 of the present invention;

[0053] Figure 3 .EEM matrix diagram of Example 2 of the present invention;

[0054] Figure 4 . Three-dimensional fluorescence area integral map of the rainwater inspection well of Example 3 of the present invention;

[0055] Figure 5 .The three-dimensional fluorescence spectrum of some industrial wastewater from the spectral library of industrial pollution sources accumulated by the present invention. DETAILED DESCRIPTION

[0056] The technical solution will be clearly and completely described below through the embodiments of the present application. Obviously, the described embodiments are only part of the preferred embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0057] Example 1

[0058] This embodiment adopts a method for diagnosing industrial wastewater mixing points based on fluorescence fingerprint comparison, and performs mixing diagnosis and source tracing on the pipe section between numbers A and B. The collected water samples are subjected to three-dimensional fluorescence spectrum analysis, and the fluorescence spectra of the front and rear inspection wells are subtracted to determine whether there is any external sewage and wastewater mixing, and the pollution source is traced in combination with the fluorescence spectrum characteristics of industrial wastewater.

[0059] The specific steps are as follows:

[0060] (1) Step 1: Collect 50 mL of water samples from the inspection wells before and after the "branch access point" or possible mixing point of the rainwater pipe, and mark them as A and B, that is, A is the water sample that has not been contaminated by mixing, and B is the water sample that may have been mixed with sewage. The collected water samples are transported to the laboratory in a refrigerated manner.

[0061] (2) Step 2: Use a 0.45 μm filter membrane to filter the water sample in time to remove suspended particles and microorganisms and other interfering factors to ensure the clarity and stability of the water sample, and then store it in a refrigerator at 4°C, and try to complete the collection of spectral data within 7 days. The DOM of the filtered water sample is relatively stable. Due to the high toxicity of industrial wastewater and the absence of microbial effects, the storage time can even be as long as several months.

[0062] (3) Step 3: Use a UV-visible spectrophotometer to measure the UV-visible absorption spectrum of the filtered water sample, with the measurement band being 200-550 nm and the step length being 1 nm. Record the absorption spectrum data for subsequent fluorescence inner filter effect correction.

[0063] (4) Step 4: Use a fluorescence spectrophotometer to measure the three-dimensional fluorescence spectrum of the filtered water sample. Use a quartz cuvette and set the voltage to 400 V to avoid generating too much background noise at low excitation wavelengths. Set the excitation wavelength range to 200-450 nm, the emission wavelength range to 250-550 nm, the slit width to 2 nm, and the scanning speed to 12000 nm / s to obtain the three-dimensional fluorescence data of the water sample, namely the EEM matrix.

[0064] (5) Step 5: Use Matlab, Python, R language and other software to preprocess the EEM matrix into three-dimensional fluorescence data, including the following operations:

[0065] -Use UV-visible absorption spectrum data to correct the fluorescence inner filter effect of the EEM matrix to eliminate the attenuation and distortion of the fluorescence signal.

[0066] -Subtract the primary and secondary Raman scattering and Rayleigh scattering signals from the EEM matrix, specifically by cutting out the values ​​of the areas with high fluorescence response and steep changes in the matrix, and then interpolating and filling according to the triangular interpolation method to achieve the goal of eliminating the interference of scattered signals.

[0067] -(Optional operation) If the water samples come from different test batches, it is necessary to use Raman normalization or quinine sulfate correction to normalize the EEM matrix to eliminate the influence of instrument status factors and test condition factors. The water samples in this embodiment are measured from the same batch, so Raman normalization operation is not performed.

[0068] -Perform peak picking on the EEM data after the above processing, such as Figure 2As shown in the figure, EEM A has three fluorescence peaks #1-#3, which are located at Ex / Em=242 / 424, 282 / 412 and 332 / 412 nm respectively; EEM B also has three fluorescence peaks #1-#3, which are located at Ex / Em=240 / 416, 232 / 346 and 298 / 394 nm respectively.

[0069] -Use the numerical normalization method to process the matrices EEM A and EEM B to eliminate the dilution effect of mixed water. The specific operation is to select a characteristic peak position of EEM A, Ex / Em=282 / 412nm, and divide the two spectral matrices by their respective values ​​at this position, so that the fluorescence signal of each spectral matrix at this Ex / Em is 1. This processing will not change the position of the fluorescence peak, and due to the additivity of the spectrum, it can weaken the change in fluorescence peak intensity caused by the dilution of mixed water, which is convenient for subsequent spectrum calculation and comparison, and can better reflect the fluorescence characteristics of mixed pollutants.

[0070] (6) Step 6: Perform a subtraction operation on the preprocessed spectral matrices EEM A and EEM B, that is, subtract EEM A from EEM B to obtain a new spectral residual matrix EEM D.

[0071] (7) Step 7: Observe EEM D, analyze the position and intensity changes of its fluorescence peak, and determine whether there is industrial wastewater mixed in. In this example, Figure 2 As shown, EEM D has three obvious fluorescence peaks, namely #1 (Ex / Em=232 / 346nm), #2 (Ex / Em=222 / 310nm) and #3 (Ex / Em=276 / 310nm). The relative intensities of the three fluorescence peaks correspond to 0.7, 0.4 and 0.4, respectively, which exceed 20% of the peak value of EEM A, indicating that sewage and wastewater are mixed in this pipe section with a high mixing ratio, and the mixed pollutants have a strong fluorescence signal in this fluorescence area.

[0072] The basis for judging whether there is mixing: When there is no mixing in the residual spectrum, the water quality before and after is not much different, and there is no obvious fluorescence peak in the subtracted residual graph. As long as there is a large area of ​​fluorescence response, or the fluorescence peak is small and strong, it can be preliminarily considered that sewage is mixed in. Here, 20% of the peak value of EEM A is taken as a reference for judgment. It can be considered that when it is less than 20%, the degree of mixing is low or the water quality fluctuates. When it is greater than 20%, the greater the deviation, the higher the degree of mixing.

[0073] (8) Step 8: Collect industrial wastewater samples from nearby industrial enterprises and perform the same processing as steps 2-5 to obtain three-dimensional fluorescence data of industrial wastewater for source tracing and comparison. This data can form a spectral library for long-term application and can be continuously updated and expanded to adapt to more complex situations and wider areas.

[0074] (9) Step 9: Compare EEM D with the fluorescence spectrum in the library, analyze whether the position and intensity of the fluorescence peaks are similar, and determine the type of industrial wastewater mixed in. If the fluorescence peaks are highly consistent with the industrial wastewater EEM in the library in certain areas, it means that the mixed wastewater has the same or similar fluorescence characteristics as the wastewater of the industrial enterprise, and it can be preliminarily considered that the industrial enterprise has discharged wastewater. Combined with the direction of the pipeline network and GIS or GPS, the specific industrial enterprise can be further traced. According to the number and position of the residual peaks, EEM D matches the wastewater spectrum EEMC that meets the characteristics in the regional spectral database. After comparison, EEM C in the spectral library has two fluorescence peaks, namely #1 (Ex / Em=234 / 342nm) and #2 (Ex / Em=278 / 324nm), which are basically consistent with the positions of peaks #1 (Ex / Em=232 / 346nm) and #3 (Ex / Em=276 / 310nm) of the residual spectrum EEM D. Therefore, the source of the mixing can be traced back to the factory enterprise whose wastewater fluorescence characteristic is EEM C.

[0075] Example 2

[0076] This embodiment adopts a method for diagnosing industrial wastewater mixing points based on fluorescence fingerprint comparison, and performs mixing diagnosis and tracing on the pipe section between numbers A2 and B2. The collected water samples are subjected to three-dimensional fluorescence spectral analysis, and the fluorescence spectra of the front and rear inspection wells are subtracted to determine whether there is any external sewage and wastewater mixing, and the pollution is traced in combination with the fluorescence spectral characteristics of industrial wastewater. The specific steps are as follows:

[0077] (1) Step 1: Collect 50 mL of water samples from two inspection wells upstream and downstream of a rainwater pipe. Note that A2 is the water sample upstream of the rainwater pipe that has not been contaminated by mixing, and B2 is the water sample downstream of the rainwater pipe that may be mixed with sewage. The collected water samples are transported to the laboratory in a refrigerated manner.

[0078] (2) Step 2: Use a 0.45 μm filter membrane to filter the water sample in time to remove interfering factors such as suspended particles and microorganisms to ensure the clarity and stability of the water sample. Store it in a refrigerator at 4°C before measurement, and try to complete the spectral data collection within 7 days.

[0079] (3) Step 3: Use a UV-visible spectrophotometer to measure the UV-visible absorption spectrum of the filtered water sample, with the measurement band being 200-550 nm and the step length being 1 nm. Record the absorption spectrum data for subsequent fluorescence inner filter effect correction.

[0080] (4) Step 4: Use a fluorescence spectrophotometer to measure the three-dimensional fluorescence spectrum of the filtered water sample. Use a quartz cuvette, set the voltage to 400 V, the excitation wavelength range to 200-450 nm, the emission wavelength range to 250-550 nm, the slit width to 5 nm, and the scanning speed to 12000 nm / s to obtain the three-dimensional fluorescence data of the water sample, namely the EEM matrix.

[0081] (5) Step 5: Use Matlab, Python, R language and other software to preprocess the EEM matrix into three-dimensional fluorescence data, including the following operations:

[0082] -Use UV-visible absorption spectrum data to correct the fluorescence inner filter effect of the EEM matrix to eliminate the attenuation and distortion of the fluorescence signal.

[0083] -Subtract the primary and secondary Raman scattering and Rayleigh scattering signals from the EEM matrix, specifically by cutting out the values ​​of the areas with high fluorescence response and steep changes in the matrix, and then interpolating and filling according to the triangular interpolation method to achieve the goal of eliminating the interference of scattered signals.

[0084] -(Optional operation) If the water samples come from different test batches, it is necessary to use Raman normalization or quinine sulfate correction to normalize the EEM matrix to eliminate the influence of instrument status factors and test condition factors. The Raman integration of the water sample in this embodiment is basically the same as before, so there is no need to perform Raman normalization operation.

[0085] -Perform peak picking on the EEM data after the above processing, such as Figure 3 As shown in the figure, EEM A2 has three fluorescence peaks, namely #1 (Ex / Em=232 / 342nm), #2 (Ex / Em=280 / 350nm) and #3 (Ex / Em=224 / 286nm), and #1:#2:#3≈10:5:2; EEM B2 has two fluorescence peaks, namely #1 (Ex / Em=232 / 344nm) and #2 (Ex / Em=282 / 344nm), and #1:#2=2:1.

[0086] -Process the matrices EEM A2 and EEM B2 with the fluorescence intensity at a specific Ex / Em position to eliminate the dilution effect of mixed water. The specific operation is to select a characteristic peak position of EEM A2, Ex / Em=232 / 342nm, and divide the two spectral matrices by their respective values ​​at this position, which is called a numerical normalization operation, so that the fluorescence signal of each spectral matrix at this Ex / Em is 1. This processing will not change the position of the fluorescence peak, and due to the additivity of the spectrum, it can weaken the influence of the deviation of the fluorescence intensity ratio of A2 in water sample B2 from the actual due to the dilution of mixed water, which is convenient for subsequent spectrum calculation and comparison, and can better reflect the fluorescence characteristics of mixed pollutants.

[0087] (6) Step 6: Perform a subtraction operation on the preprocessed spectral matrices EEM A2 and EEM B2, that is, subtract EEM A2 from EEM B2 to obtain a new spectral residual matrix EEM D2.

[0088] (7) Step 7: Observe EEM D2, analyze the number, position and intensity changes of its fluorescence peaks, and determine whether there is industrial wastewater mixing. In this example, the two main fluorescence peaks of the residual spectrum D2 are #1 (Ex / Em=224 / 310nm) and #2 (Ex / Em=278 / 308nm). The fluorescence range is small and the response is strong, indicating that sewage is mixed in this pipe section, and the mixed pollutants have a strong fluorescence signal in this fluorescence area. The residual peak intensity is less than 20% of the peak before subtraction, indicating that the degree of mixing is low.

[0089] (8) Step 8: Collect industrial wastewater samples from nearby industrial enterprises and perform the same processing as steps 2-5 to obtain three-dimensional fluorescence data of industrial wastewater for source tracing and comparison. This data can form a spectral library for long-term application and can be continuously updated and expanded to adapt to more complex situations and wider areas.

[0090] (9) Step 9: Compare EEM D2 with the fluorescence spectra in the regional spectral library, analyze whether the positions and intensities of the fluorescence peaks are similar, and determine the type of industrial wastewater mixed in. If the fluorescence peaks are highly consistent with the industrial wastewater EEM in the spectral library in certain areas, it means that the mixed wastewater has the same or similar fluorescence characteristics as the wastewater of the industrial enterprise, and it can be preliminarily considered that the industrial enterprise has discharged wastewater. Combined with the pipeline network direction and GIS or GPS, the specific industrial enterprise can be further traced. According to the number and position of the residual peaks, EEM D2 matches the sewage wastewater spectrum EEM C2 that meets the characteristics in the regional spectral database. After comparison, the two fluorescence peaks #1 (Ex / Em=276 / 310nm) and #2 (Ex / Em=220 / 310nm) of the domestic sewage EEM C2 in the spectral library are consistent with the positions of peaks #2 and #1 of the residual spectrum EEM D, respectively. Find the branch pipe between the A2-B2 pipe section, and finally trace the source of the mixing to the domestic sewage of the factory employees upstream of the surrounding branch pipes.

[0091] Example 3

[0092] Matlab was used to further perform regional integration analysis on the three-dimensional fluorescence spectrum data of A2 and B2 obtained in Example 2 (after deducting scattering and before numerical normalization). The results are as follows: Figure 4 As shown, the total regional integral value of A2 is 5.92×10 3 au, the total regional integral value of B2 is 6.19×10 3au, the difference between the two is within 5%, and the integral values ​​of each sub-region are similar. It is difficult to conclude whether there is mixing, let alone trace the source of mixing pollution.

[0093] The subtraction result of the present invention can determine whether there is mixing, assess the severity of the mixing, and narrow the target range of pollution tracing.

[0094] Example 4

[0095] Collect a variety of industrial wastewater samples from inside or at the outlet of each factory enterprise, repeat the same processing as steps 2-5 in Example 1 to obtain industrial wastewater three-dimensional fluorescence matrix data and fluorescence peak position and intensity information. The three-dimensional fluorescence spectra of some industrial wastewater are as follows: Figure 5 As shown in the figure, it can be seen that the three-dimensional fluorescence spectra of different industrial wastewaters are quite different, and the positions of the fluorescence peaks are obviously different. It is feasible to trace the pollution source by using the residual fluorescence peak after subtraction.

[0096] The data can form a pollution source spectral library for pollution source tracing and comparison. The library can be used for a long time and can be continuously updated and expanded to adapt to more complex situations such as seasonal and process changes, as well as wider areas.

[0097] The above-described embodiments are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be thought of by any technician familiar with the art within the technical scope disclosed in the present application without creative work should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims in the present application.

Claims

1. A method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy, characterized in that: The following steps are involved: Step (1) collecting water samples from inspection wells before and after possible mixing points; Step (2) filtering with a filter membrane, detecting with a UV-visible spectrophotometer, and detecting with a fluorescence spectrophotometer to obtain an EEM matrix; Step (3) using the UV-visible absorption spectrum data to correct the fluorescence inner filter effect of the EEM matrix, and subtracting the primary and secondary Raman scattering and Rayleigh scattering signals from the EEM matrix; Step (4) peak picking is performed on the EEM matrix, and the EEM matrix is ​​processed using a numerical normalization method to eliminate the dilution effect of the mixed water, and a characteristic peak position Ex / Em of the EEM A of the water sample before mixing is selected, and the two spectral matrices are respectively divided by their respective values ​​at the position, so that the fluorescence signal of each spectral matrix at the Ex / Em is 1; Step (5) subtracting the EEM matrix of the inspection well water sample after the possible mixing point from the EEM matrix before the possible mixing point to obtain a spectral residual matrix; Step (6) compares with the spectral library to determine whether it is an actual mixing point and trace the source of the mixed water.

2. The method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy according to claim 1 is characterized in that: On sunny days, we can judge whether industrial wastewater has been mixed in based on the changes in the fluorescent fingerprint of the inspection wells before and after the "branch pipe access point", and use spectral comparison to trace the source.

3. The method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy according to claim 1 is characterized in that: 24 hours after rainfall, collect water samples from the two inspection wells near the "branch access point" of the rainwater pipe or the point with obvious external water input; Sampling of industrial wastewater from surrounding factories and subsequent spectral database formation, recorded as the pollution source spectral database; Refrigerate the collected water samples at 0-10℃ for no more than 7 days; Use membrane filtration to remove suspended particles and microorganisms; The water samples were tested using a UV-visible spectrophotometer with a measurement range of 200-550nm; The water samples were subjected to three-dimensional fluorescence spectrum detection using a fluorescence spectrophotometer, with an excitation wavelength range of 200-450 nm and an emission wavelength range of 250-550 nm.

4. The method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy according to claim 1 is characterized in that: If the residual fluorescence peak and the industrial wastewater EEM in the spectral library show a high degree of consistency in certain areas, it means that the mixed wastewater has the same or similar fluorescence characteristics as the wastewater of the industrial enterprise, and it is preliminarily believed that the industrial enterprise has discharged wastewater; or, If the residual peak intensity is less than 20% of the peak before subtraction, it means that the degree of mixing is low or it is a normal fluctuation in water quality.

5. An application of the method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy according to claim 1, characterized in that: By monitoring the water conditions in the rainwater pipes, the industrial wastewater mixing points can be diagnosed to determine whether there is any external sewage or wastewater mixing, and the pollution source can be traced by combining the fluorescence spectrum characteristics of industrial wastewater; The water conditions include but are not limited to: complex water quality, The position of the characteristic fluorescence peak is variable, and the pollution source is intermittent and sudden mixing of rain and sewage.

6. The use of the method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy according to claim 5 is characterized in that: Timely discover the discharge or exceeding of industrial wastewater standards, effectively control the problem of rainwater and sewage mixing in industrial areas, reduce the pollution of urban water environment by industrial wastewater, improve the water quality of receiving water bodies, restore the balance of water ecosystems, and improve the quality of life of urban residents; effectively save the cost of investigation and treatment of rainwater and sewage mixing in industrial areas, reduce the operating pressure of urban drainage systems, and improve the operating efficiency and safety of urban drainage systems.

7. A method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy, characterized in that: The steps include: In step (1), water samples from the inspection wells before and after the possible mixing point are collected, marked and refrigerated; Step (2) filtering with a filter membrane, detecting with a UV-visible spectrophotometer, and detecting with a fluorescence spectrophotometer to obtain an EEM matrix; The water sample obtained in step (1) is filtered using a 0.45 μm filter membrane and then stored in a refrigerator at 4° C. The water sample obtained in step (2) is subjected to three-dimensional fluorescence spectrum detection by using a fluorescence spectrophotometer, using a quartz cuvette, setting the voltage to 400 V, setting the excitation wavelength range to 200-450 nm, the emission wavelength range to 250-550 nm, the slit width to 2 nm, and the scanning speed to 12000 nm / s, to obtain three-dimensional fluorescence data of the inspection well water sample before and after the possible mixing point, i.e., the EEM matrix; Step (3) using an ultraviolet-visible spectrophotometer to detect the water sample obtained in step (2), with a measurement band of 200-550nm and a step length of 1nm, to obtain ultraviolet-visible absorption spectrum data of the inspection well water sample before and after the possible mixing point, respectively; using the ultraviolet-visible absorption spectrum data to correct the fluorescence inner filter effect of the EEM matrix, and subtracting the primary and secondary Raman scattering and Rayleigh scattering signals from the EEM matrix; The obtained EEM matrix is ​​corrected for the fluorescence inner filter effect by using the obtained UV-visible absorption spectrum data; The obtained EEM matrix is ​​subjected to subtraction of primary and secondary Raman scattering and Rayleigh scattering signals, specifically, the values ​​of the areas with high fluorescence response and steep changes in the matrix are cut off, and then interpolation and filling are performed according to the triangular interpolation method; Step (4) peak picking is performed on the EEM matrix, and the EEM matrix is ​​processed using a numerical normalization method to eliminate the dilution effect of the mixed water, thereby obtaining the EEM matrix of the pre-processed inspection well water sample before and after the possible mixing point; a characteristic peak position Ex / Em of the EEM A of the water sample before mixing is selected, and the two spectral matrices are respectively divided by their respective values ​​at the position, so that the fluorescence signal of each spectral matrix at the Ex / Em is 1; Step (5) subtracting the EEM matrix of the inspection well water sample before the possible mixing point from the EEM matrix of the inspection well water sample after the possible mixing point to obtain a spectral residual matrix, analyzing the position and intensity changes of the residual fluorescence peak to determine whether there is any external pollution or wastewater mixing; In step (6), the spectral residual matrix is ​​compared with the spectral library to determine whether it is an actual mixing point, and the mixed water is traced to the source to determine the type of sewage and wastewater mixed in.

8. The method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy according to claim 7 is characterized in that: In the step (3), if the water samples come from different test batches, Raman normalization processing is performed before subtracting the primary and secondary Raman scattering and Rayleigh scattering signals from the EEM matrix.

9. The method for diagnosing industrial wastewater mixing points based on fluorescence spectroscopy according to claim 8, characterized in that: The spectral library in step (6) is obtained by collecting industrial wastewater samples and repeating steps (2) to (4).

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