A pollution source tracing method based on three-dimensional fluorescence spectroscopy

Abstract

The present invention discloses a pollution source tracing method based on three-dimensional fluorescence spectroscopy, which relates to the field of water quality monitoring technology. By collecting water samples from specific upstream pollution discharge units as pollution sources, configuring mixed water samples of water samples from different pollution sources mixed in different volumes or proportions, establishing a pollution source database suitable for parallel factor analysis, establishing a good linear model between the pollution source and the three-dimensional fluorescence spectrum characteristic value, and proposing a shortest path algorithm to quantitatively solve the volume or proportion of the pollution source in the monitored water sample, a pollution source tracing method is performed to trace the pollution source back to the specific pollution discharge unit. The present invention improves the application scope of parallel factor analysis by establishing a three-dimensional fluorescence spectrum database of sewage discharged from mixed upstream pollution sources, so that the three-dimensional fluorescence spectra of sewage from different industrial systems can be effectively parallel factor analyzed together. Compared with the parallel factor analysis-Tucker congruence coefficient method, the pollution source can be traced to a more specific level.

Description

Technical Field

[0001] The present invention relates to the technical field of water quality monitoring, and in particular to a pollution source tracing method based on three-dimensional fluorescence spectroscopy. Background Art

[0002] As a crucial component of environmental issues, the water environment is closely linked to other environmental issues, such as the soil environment. Therefore, the importance of water pollution control is self-evident. Centralized sewage treatment will become the primary task of water pollution control. Whether sewage dischargers adhere to centralized treatment standards and discharge within standard quotas directly impacts the success of this task. Therefore, water quality monitoring and pollution source tracing are currently key research areas, providing crucial tools and insights for water pollution control.

[0003] Currently, the main approaches to addressing different wastewater discharge scenarios include hydrodynamic modeling, behavioral programming algorithms, and concentration gradient algorithms. However, due to the complex composition of real-world wastewater, variations in a particular water quality monitoring indicator can be caused by a variety of factors. These methods require extensive collection of various traditional water quality monitoring indicators, and the development and adjustment of models or algorithms also rely on experience. Consequently, a single model cannot be effectively generalized to other watersheds requiring monitoring. Compared to traditional water quality monitoring indicators, three-dimensional fluorescence spectroscopy offers unique advantages in analyzing complex real-world wastewater due to its high sensitivity, multidimensional information, and comprehensive chemical composition. It has attracted increasing attention in recent years. When molecules are irradiated with short-wavelength excitation light, the absorption of photon energy causes electrons in the molecules to transition from the ground state to an excited state. This excited state is unstable, and the molecules return to the ground state via radiative transitions, emitting long-wavelength fluorescence that reflects the substance's properties. The light absorbed by the analyte molecules when they reach the excited state is called excitation light, while the light emitted when the excited state molecules return to the ground state is called emission light. The excitation and emission spectra of different molecules are different. Therefore, the spectrum obtained by recording the excitation and emission wavelength and intensity information by the instrument is called the three-dimensional fluorescence spectrum (EEM). It can reflect the type and content of organic matter in the sample and has the characteristic of a one-to-one correspondence with the sample.

[0004] Currently, the main analytical methods for water quality monitoring or pollution source tracing based on three-dimensional fluorescence spectroscopy are:

[0005] 1. Single wavelength or multi-wavelength spectroscopy: A method that selects the excitation or emission spectrum at one or more wavelengths and establishes a linear relationship between the fluorescence intensity in the spectrum and the information of the substance to be detected.

[0006] 2. Fluorescence area integration method: Based on experience, the three-dimensional fluorescence spectrum is divided into different regions, the fluorescence intensity in different regions is integrated, and the integral is used to represent the cumulative fluorescence response of water-soluble organic matter (DOM) with similar characteristics.

[0007] 3. Feature extraction and matching method for two-dimensional single-shot surface data: After normalizing the three-dimensional fluorescence spectrum, the area is divided according to the intuitive contour convexity and concavity in the form of a contour map. The maximum difference in fluorescence intensity and the center position in the area are extracted as feature values, and a Reeb diagram is drawn for matching.

[0008] 4. Parallel Factor Analysis - Tucker Congruence Coefficient Method: After performing parallel factor analysis on the three-dimensional fluorescence spectrum, the parallel factor analysis - Tucker Congruence Coefficient Method obtains several component graphs that are split according to the original three-dimensional fluorescence spectrum. The Tucker Congruence Coefficient Method is used to calculate the similarity between different component graphs and the three-dimensional fluorescence spectra of one or several types of pollutants that may have similar characteristics.

[0009] Parallel factor analysis - Tucker congruence coefficient method is a pollution tracing method for tracing the industry of the pollution source. Based on the relationship between the flow direction of the monitored river and the main stream and direct current, this method sets up dozens of water sampling points in the monitoring area, and performs three-dimensional fluorescence scanning and other tests on the water samples for indicators to be tested. The three-dimensional fluorescence spectra of the water samples from all collection points are compiled into a data set and then subjected to parallel factor analysis to obtain several component maps separated by the three-dimensional fluorescence spectra. After empirically judging the type of dissolved organic matter that the high fluorescence intensity areas of the three-dimensional fluorescence spectra of different components may represent, the Tucker congruence coefficient method is used to calculate the similarity between the three-dimensional fluorescence spectrum of the component map and the three-dimensional fluorescence spectrum of the wastewater of the industry that discharges this type of dissolved organic matter. If the similarity reaches 0.85 or above, the water body is considered to be polluted by the wastewater of this industry.

[0010] Because the parallel factor analysis-Tucker congruence coefficient method stops tracing pollution sources at the industry level, technicians in this field are committed to developing a method to monitor pollution excess emissions in downstream areas with multiple sources and complex pollution and trace them back to specific emission units. Summary of the Invention

[0011] In view of the above-mentioned defects of the prior art, the technical problem to be solved by the present invention is to provide a method for monitoring pollution excess discharge in downstream areas with multiple sources and complex pollution and tracing it back to specific emission units.

[0012] To achieve the above objectives, the present invention provides a pollution source tracing method based on three-dimensional fluorescence spectroscopy, which comprises the following steps:

[0013] Step 1: Collect the independent drainage from n pollution sources upstream within the monitoring basin, as well as one portion of the mixed drainage from the pollution sources when they merge downstream and are discharged normally, and record this as the "standard". Use the independent drainage collected upstream to prepare i portions of mixed sewage according to different volume ratios. Together with the "standard", a total of i+1 mixed sewage samples are formed. Record the drainage configuration information of the pollution sources contained in each portion of mixed sewage, and scan the three-dimensional fluorescence spectrum of the mixed sewage to form a database with a one-to-one correspondence with the configuration information;

[0014] Step 2: Collect actual water samples at the downstream end of the confluence of all sewage discharge units in the monitoring basin, scan their 3D fluorescence spectra, and perform parallel factor analysis on them together with the 3D fluorescence spectra in the database to obtain m components. The peak fluorescence value of each component is extracted as the characteristic value.

[0015] Step 3: Arrange the configuration information of the mixed sewage into a matrix I of size (i+1)×n. Add a column of unit column vectors to the left of matrix I, denoted as matrix IN. Arrange the eigenvalues ​​of the mixed sewage into a matrix C of size (i+1)×m. Solve the linear model matrix M so that IN·M=C.

[0016] Step 4: Arrange the eigenvalues ​​of the actual water sample into an m-dimensional column vector c, and record the quantified information of the drainage composition of the n sewage discharge units contained in the actual water sample as an n-dimensional column vector x. Through the matrix equation M T [1; x] = c finds the relationship between the elements of x;

[0017] Step 5: When n is less than or equal to m, x has a unique solution; when n is greater than m, the specific composition of the elements in the column vector x is [x1, x2, ..., x m ,x m+1 ,…,x n-1 ,x n ] T , the specific elements of the discharge information column vector of the conventional discharge water sample "standard" are [s1, s2, ..., s n ] T , construct the Euclidean distance function f(x1,x2,…,x n )=(x1-s1) 2 +(x2-s2) 2 +…+(x n -s n ) 2 , using the matrix equation M T ·[1;x]=c eliminates the function f and obtains f(x1,x2,…,x m ,x m+1 ,…x n )=g(x1,x2,…,xm ), find the unique solution x that minimizes the function g;

[0018] Step 6: By comparing the configuration information of the mixed water sample with the standard discharge situation, it is possible to determine whether there is excessive discharge upstream and to determine the scope of possible sewage discharge units that may cause excessive discharge.

[0019] In a preferred embodiment of the present invention, the number i of the mixed sewage is not less than 20.

[0020] In a preferred embodiment of the present invention, the configuration information is any one of the volume, volume proportion or concentration ratio of the wastewater of each sewage discharge unit in the mixed sewage.

[0021] In a preferred embodiment of the present invention, the wavelength range of the excitation wavelength and the emission wavelength of the three-dimensional fluorescence spectrum is between 200 nm and 900 nm, and the scanning wavelength interval is between 1 nm and 5 nm.

[0022] In a preferred embodiment of the present invention, the components obtained by the parallel factor analysis should be cross-validated.

[0023] In a preferred embodiment of the present invention, the method for solving the linear model matrix is ​​any one of the least squares method, principal component analysis, partial least squares method or support vector machine, and its content format should be organized into the first line as the constant term of each component expression, and the next n lines are the coefficients of the drainage configuration information of n sewage discharge units in each component expression.

[0024] In a preferred embodiment of the present invention, the expression of the function f is (x1-s1) 2 +(x2-s2) 2 +…+(x n -s n ) 2 or |x1-s1|+|x2-s2|+…+|x n -s n |One of them.

[0025] In a preferred embodiment of the present invention, the sewage over-discharge situation in step 6 specifically involves determining whether there is over-discharge and determining the range of possible sewage discharge units that may cause over-discharge.

[0026] In a preferred embodiment of the present invention, the value of each element in the column vector x corresponds to the composition relationship of the wastewater from each upstream sewage discharge unit in the actual water sample collected downstream.

[0027] In a preferred embodiment of the present invention, when judging the actual over-discharge situation and the source of the over-discharged sewage, an increase of 10% to 20% in the configuration information value of the monitored water sample quantification compared with the configuration information value of the standard discharge quantification is considered to be a low confidence level for over-discharge.

[0028] The present invention uses the method of parallel factor analysis to reveal the fluorescence peak information in the three-dimensional fluorescence spectrum that is masked by the overlapping fluorescence areas of different substances. Compared with the existing technology, the feature extraction of the three-dimensional fluorescence spectrum has a more accurate fluorescence peak position. The present invention establishes a three-dimensional fluorescence spectrum database of sewage by mixing the drainage of upstream pollution sources, which improves the application scope of parallel factor analysis, so that the three-dimensional fluorescence spectra of sewage from different industrial systems can be effectively parallel factor analyzed together. Compared with the parallel factor analysis-Tucker congruence coefficient method, the pollution source can be traced to a more specific level. The method for establishing a model of pollution source information and three-dimensional fluorescence spectrum characteristics proposed by the present invention is universal and will not be restricted by different pipe networks or rivers. The pollution source tracing method using three-dimensional fluorescence spectrum proposed by the present invention has the advantages of fewer water quality indicators to be monitored, convenient database establishment, more reliable extraction of three-dimensional fluorescence spectrum feature information, the method of model establishment does not rely on experience, and the accuracy of pollution tracing. It has broad application prospects in the field of water quality monitoring.

[0029] The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings to fully understand the purpose, characteristics and effects of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of a pollution source tracing method using three-dimensional fluorescence spectroscopy according to a preferred embodiment of the present invention;

[0031] Figure 2 is a kernel consistency function diagram of embodiment 1 of the present invention;

[0032] Figure 3 3-component cross-validation diagram of Example 1 of the present invention;

[0033] Figure 4 This is a diagram showing the decomposition of the first component in Example 1 of the present invention;

[0034] Figure 5 This is a diagram showing the decomposition of the second component in Example 1 of the present invention;

[0035] Figure 6 This is a diagram of the third component decomposition of Example 1 of the present invention;

[0036] Figure 7 is the linear fitting result of the drainage volume ratio of the five factories in Example 1 of the present invention and the peak value of the fluorescence of the first component;

[0037] Figure 8 is the linear fitting result of the drainage volume ratio of the five factories in Example 1 of the present invention and the peak value of the fluorescence of the second component;

[0038] Figure 9 is the linear fitting result of the drainage volume ratio of the five factories in Example 1 of the present invention and the peak value of the fluorescence of the third component;

[0039] Figure 10 This is the increase in the drainage volume of the five factories in Example 1 of the present invention compared with the standard drainage volume. DETAILED DESCRIPTION

[0040] The following describes several preferred embodiments of the present invention with reference to the accompanying drawings to make its technical content clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the scope of protection of the present invention is not limited to the embodiments mentioned herein.

[0041] In the drawings, components with identical structures are denoted by the same reference numerals, and components with similar structures or functions are denoted by similar reference numerals. The size and thickness of each component shown in the drawings are arbitrary and are not limited by the present invention. For clarity, the thickness of components in some places in the drawings is appropriately exaggerated.

[0042] The present invention provides a pollution source tracing method based on three-dimensional fluorescence spectroscopy. The method establishes a database capable of applying parallel factor analysis by mixing sewage with different components due to different industries and showing obvious differences in three-dimensional fluorescence spectra. The pollution source and the water samples of the monitored basin are subjected to parallel factor analysis as a whole, and the peak values ​​of the fluorescence peaks of different components are extracted as characteristic values. A linear model of the characteristic values ​​and the emission conditions is established for the purpose of solving actual tracing problems. The shortest path search algorithm is applied, and when over-emission is monitored, the specific pollution over-emission unit can be traced back.

[0043] The purpose of the present invention can be achieved by the following technical solutions, the complete process is shown in Figure 1 :

[0044] The method of monitoring pollution over-discharge and tracing the source in a downstream section with multiple sources and complex pollution according to the present invention comprises the following steps:

[0045] (1) Collect n independent drainages from pollution sources upstream within the monitoring basin, as well as one portion of mixed drainage from pollution sources when they merge downstream and are discharged normally, and record this as the "standard". Use the independent drainage collected upstream to configure i portions of mixed sewage according to different volume ratios, and together with the "standard", form a total of i+1 portions of mixed sewage samples. Record the drainage or configuration information of the pollution sources contained in each portion of mixed sewage, and scan the three-dimensional fluorescence spectrum of the mixed sewage to form a one-to-one corresponding database with the configuration information;

[0046] (2) Collect actual water samples at the downstream end of the confluence of all sewage discharge units in the monitoring basin, scan their three-dimensional fluorescence spectra, and perform parallel factor analysis together with the three-dimensional fluorescence spectra in the database to split them into m components, and extract the peak fluorescence value of each component as the characteristic value;

[0047] (3) Arrange the configuration information of the mixed sewage into a matrix I of size (i+1)×n, add a column of unit column vectors to the left of the matrix I, and record it as matrix IN; Arrange the eigenvalues ​​of the mixed sewage into a matrix C of size (i+1)×m, and solve the linear model matrix M so that IN·M=C;

[0048] (4) The eigenvalues ​​of the actual water sample are organized into an m-dimensional column vector c, and the quantified information of the drainage composition of the n sewage discharge units contained in the actual water sample is recorded as an n-dimensional column vector x. Through the matrix equation M T [1; x] = c finds the relationship between the elements of x;

[0049] (5) When n is less than or equal to m, x has a unique solution; when n is greater than m, the elements in the column vector x are specifically composed of [x1, x2,…, x m ,x m+1 ,…,x n-1 ,x n ] T , the specific elements of the discharge information column vector of the conventional discharge water sample "standard" are [s1, s2, ..., s n ] T , construct the Euclidean distance function f(x1,x2,…,x n )=(x1-s1) 2 +(x2-s2) 2 +…+(x n -s n ) 2 , using the matrix equation M T ·[1;x]=c eliminates the function f and obtains f(x1,x2,…,x m ,x m+1 ,…x n )=g(x1,x2,…,x m ), find the unique solution x that minimizes the function g;

[0050] (6) The values ​​of the elements in the column vector x correspond to the composition of the wastewater from each upstream sewage discharge unit in the actual water samples collected downstream. By comparing the configuration information of the mixed water sample with the standard discharge situation, it is possible to determine whether there is an over-discharge situation upstream and to determine the range of the possible sewage discharge units that may cause the over-discharge.

[0051] In the technical solution provided by the present invention, the number of mixed sewage portions i should be no less than 20;

[0052] Based on the technical solution provided by the present invention, the configuration information is any one of the volume, volume proportion or concentration ratio of the wastewater of each sewage discharge unit in the mixed sewage;

[0053] Based on the technical solution provided by the present invention, the wavelength range of the excitation wavelength and emission wavelength of the three-dimensional fluorescence spectrum is between 200nm and 900nm, and the scanning wavelength interval is 1nm to 5nm;

[0054] Based on the technical solution provided by the present invention, the components obtained by parallel factor analysis should be cross-validated;

[0055] Based on the technical solution provided by the present invention, the method for solving the linear model matrix is ​​any one of the least squares method, principal component analysis, partial least squares method or support vector machine, and its content format should be organized into the first line as the constant term of each component expression, and the following n lines are the coefficients of the drainage configuration information of n sewage discharge units in each component expression;

[0056] Based on the technical solution provided by the present invention, the expression of function f is (x1-s1) 2 +(x2-s2) 2 +…+(x n -s n ) 2 or |x1-s1|+|x2-s2|+…+|x n -s n |One of;

[0057] Based on the technical solution provided by the present invention, when judging the actual over-discharge situation and the source of the over-discharged sewage, it is considered that the confidence level of over-discharge is very low if the value of the configuration information of the quantified monitoring water sample increases by 10% to 20% compared with the value of the configuration information of the quantified standard discharge.

[0058] Example 1:

[0059] A method for monitoring pollution over-discharge and tracing the source of over-discharge at a downstream end with multiple sources and complex pollution based on three-dimensional fluorescence is applied, specifically comprising the following steps:

[0060] (1) Wastewater discharged from five factories (A, B, C, D, and E) in an industrial park was collected. According to the emission quotas of the five factories and the average flow rate of non-industrial polluted water from other sources, mixed sewage samples with a standard discharge situation of 3:3:3:3:3:3:10 were prepared, and 20 additional mixed sewage samples were prepared to simulate various non-standard discharge situations as much as possible. All the configuration information was recorded in the form of volume ratio. Then, the excitation wavelength range was set to 200nm~500nm, the emission wavelength was set to 250nm~550nm, and the wavelength interval was 5nm for scanning. The 21 three-dimensional fluorescence spectra obtained were used to establish a database corresponding to the configuration information.

[0061] (2) A water sample of the day when the discharge volume of factory A exceeded the quota by 50% was collected from the downstream pipeline after the rainwater and sewage were combined in the industrial park. The actual water sample was set to the excitation wavelength range of 200nm to 500nm, the emission wavelength of 250nm to 550nm, and the wavelength interval of 5nm for scanning. A three-dimensional fluorescence spectrum was obtained. The parallel factor analysis was performed together with the other 21 three-dimensional fluorescence spectra in the database of step (1). The kernel consistency function was used to confirm that the number of components was 3. Figure 2 After further cross-validation, the three-dimensional fluorescence spectrum of each sample was split into three components with uniform form. Figure 3 , the three components are shown in Figure 4-6 Extract the peak value of fluorescence in the three-dimensional fluorescence spectrum of each component as the characteristic value;

[0062] (3) Arrange the configuration information of each mixed sewage in (1) into matrix IN, and arrange the characteristic values ​​of each mixed sewage in (2) into matrix C. Use the data in matrix IN and matrix C as dependent variables and independent variables to perform partial least squares fitting with 5 principal components, and obtain the fitting results of the three component characteristic values ​​and the linear model matrix M. The fitting results are shown in Figure 7-9 ;

[0063] (4) The eigenvalues ​​of the actual water sample are sorted into a 3D column vector c, and the matrix equation M T [1; x] = c to obtain the column vector x of the drainage volume ratios of the five sewage discharge units in the actual water sample;

[0064] (5) Because the number of pollution sources (5) is greater than the number of components (3), the specific values ​​of each element in x cannot be directly obtained. Therefore, the Euclidean distance function f(x1, x2, ..., x5) = (x1-3) is constructed between the volume ratio of wastewater discharged by each factory in the actual water sample and the volume ratio of wastewater discharged by each factory in the mixed wastewater under standard discharge conditions. 2 +(x2-3) 2 +(x3-3) 2 +(x4-3)2 +(x5-3) 2 , using the quantitative relationship between the drainage volume ratios of each sewage discharge unit reflected in the column vector x, the function f is eliminated and simplified to a binary function g(x4,x5). In MATLAB, x4=3.2872 and x5=3.3313 are obtained to minimize the function g. Therefore, x1=4.7790, x2=3.3312, and x3=3.0317. Therefore, the actual samples come from the sewage discharged by the five factories A, B, C, D, and E, and the volume ratio is 4.7790:3.3312:3.0317:3.2872:3.3313. Compared with the volume ratio of the standard discharge, it is judged that there is over-discharge, and the factory A has obvious over-discharge. The volume of the factories B, C, D, and E increases by less than 15% compared with the standard situation. It is within the allowable fluctuation range and is not considered to be over-discharged, which is consistent with the actual situation of the actual water samples collected. Figure 10 .

[0065] The preferred embodiments of the present invention have been described in detail above. It should be understood that numerous modifications and variations based on the concepts of the present invention are possible without inventive effort by those skilled in the art. Therefore, any technical solution that can be derived by one skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A pollution source tracing method based on three-dimensional fluorescence spectroscopy, characterized in that: The method comprises the following steps: Step 1: Collect n independent upstream drainages from pollution sources within the monitored watershed, as well as one portion of mixed drainage from the downstream confluence of pollution sources for conventional discharge, recorded as the "standard." Use the independent upstream drainage to prepare i portions of mixed sewage at different volume ratios, and combine this with the "standard" to form a total of i+1 mixed sewage samples. Record the drainage configuration information of each pollution source contained in each mixed sewage portion, and scan the three-dimensional fluorescence spectrum of the mixed sewage to form a database with a one-to-one correspondence with the configuration information. Step 2: Collect actual water samples at the downstream end of the confluence of all sewage discharge units in the monitoring basin, scan their 3D fluorescence spectra, and perform parallel factor analysis on them together with the 3D fluorescence spectra in the database to obtain m components. The peak fluorescence value of each component is extracted as the characteristic value. Step 3: Arrange the configuration information of the mixed sewage into a matrix I of size (i+1)×n. Add a column of unit column vectors to the left of matrix I, denoted as matrix IN. Arrange the eigenvalues ​​of the mixed sewage into a matrix C of size (i+1)×m. Solve the linear model matrix M so that IN·M=C. Step 4: Arrange the eigenvalues ​​of the actual water sample into an m-dimensional column vector c, and record the quantified information of the drainage composition of the n sewage discharge units contained in the actual water sample as an n-dimensional column vector x. T [1; x] = c finds the relationship between the elements of x; Step 5: When n is less than or equal to m, x has a unique solution; when n is greater than m, the specific composition of the elements in the column vector x is [x1, x2, ..., x m ,x m+1 ,…,x n-1 ,x n ] T , the specific elements of the discharge information column vector of the conventional discharge water sample "standard" are [s1, s2, ..., s n ] T , construct the Euclidean distance function f(x1,x2,…,x n )=(x1-s1) 2 +(x2-s2) 2 +…+(x n -s n ) 2 , using the matrix equation M T ·[1;x]=c eliminates the function f and obtains f(x1,x2,…,x m ,x m+1 ,…x n )=g(x1,x2,…,x m ), find the unique solution x that minimizes the function g; Step 6: Determine the sewage over-discharge situation by comparing the configuration information of the mixed water sample with the standard discharge situation.

2. The method according to claim 1, wherein The number i of the mixed sewage is not less than 20.

3. The method according to claim 1, wherein The configuration information is any one of the volume, volume proportion or concentration ratio of the wastewater of each sewage discharge unit in the mixed sewage.

4. The method according to claim 1, wherein The wavelength range of the excitation wavelength and the emission wavelength of the three-dimensional fluorescence spectrum is between 200nm and 900nm, and the scanning wavelength interval is between 1nm and 5nm.

5. The method according to claim 1, wherein The components obtained by the parallel factor analysis should be cross-validated.

6. The method according to claim 1, wherein The method for solving the linear model matrix is ​​any one of the least squares method, principal component analysis, partial least squares method or support vector machine. Its content format should be organized into the first line as the constant term of each component expression, and the next n lines are the coefficients of the drainage configuration information of n sewage discharge units in each component expression.

7. The method according to claim 1, wherein The expression of the function f is (x1-s1) 2 +(x2-s2) 2 +…+(x n -s n ) 2 or |x1-s1|+|x2-s2|+…+|x n -s n |One of them.

8. The method according to claim 1, wherein The sewage over-discharge situation in step 6 specifically involves determining whether there is over-discharge and determining the scope of possible sewage discharge units that may cause over-discharge.

9. The method according to claim 1, wherein The value of each element in the column vector x corresponds to the composition relationship of the wastewater from each upstream sewage discharge unit in the actual water sample collected downstream.

10. The method according to claim 1, wherein When judging the actual over-discharge situation and the source of the over-discharged sewage, an increase of 10% to 20% in the quantitative configuration information value of the monitoring water sample compared with the quantitative configuration information value of the standard discharge indicates a low confidence level of over-discharge.

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