CN111562242A - Method for quickly identifying source of overflowing sewage in rainy days of urban drainage system - Google Patents
Method for quickly identifying source of overflowing sewage in rainy days of urban drainage system Download PDFInfo
- Publication number
- CN111562242A CN111562242A CN202010386861.3A CN202010386861A CN111562242A CN 111562242 A CN111562242 A CN 111562242A CN 202010386861 A CN202010386861 A CN 202010386861A CN 111562242 A CN111562242 A CN 111562242A
- Authority
- CN
- China
- Prior art keywords
- sample
- analysis
- source
- soluble organic
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
- G06F18/2135—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Data Mining & Analysis (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Artificial Intelligence (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Evolutionary Computation (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
Abstract
The invention relates to a method for quickly identifying the source of overflow sewage of an urban drainage system in rainy days, which comprises the following steps: collecting overflow sewage of a drainage pipe network as an analysis sample, and recording corresponding collection time and place; adjusting the pH value and the concentration of the soluble organic carbon of the analysis sample; performing three-dimensional fluorescence spectrum analysis to obtain three-dimensional fluorescence spectrum data; correcting the three-dimensional fluorescence spectrum data by adopting a blank water sample deduction method and an interpolation method; determining the components of the soluble organic matters through a parallel factor analysis model; obtaining the maximum fluorescence intensity value corresponding to each dissolved organic matter component in an analysis sample; and (3) identifying the main contribution source of the overflowing sewage of the urban drainage system in rainy days by adopting a principal component analysis method according to the pre-established corresponding indication relationship between the fluorescence characteristics of the soluble organic matter components and the pollution source. Compared with the prior art, the method has the advantages of simple operation, high identification speed, accurate tracing result, economy and safety, suitability for large-scale popularization and use and the like.
Description
Technical Field
The invention relates to the field of environmental protection, in particular to a method for quickly identifying a source of overflowing sewage in rainy days of an urban drainage system.
Background
In recent years, China continuously strengthens the construction of urban drainage pipe networks, so that the sewage collection rate reaches a higher level, but the water environment quality of many cities is not obviously improved, and one of the main reasons is caused by the drainage system overflowing sewage in rainy days. The problem of water pollution caused by the discharge of overflow sewage in rainy days is one of the important contents of the comprehensive treatment work of urban water environment. The method has the advantages of quickly and accurately tracing the pollution characteristics and pollutants, and is an important precondition for realizing effective control of urban overflow sewage. However, the existing overflow sewage characterization and tracing research method mainly based on the conventional water quality index analysis has many problems, especially the conventional water quality index analysis is mainly concentration analysis, which largely neglects the dynamic change of the chemical structure and properties of the pollutants from source to sink in the whole drainage system. Therefore, many studies have considered that characterization of the overflow effluent with conventional water quality indicators or trace analysis of the source of the pollution is insufficient or even problematic. In addition, although the conventional water quality index-based chemical equilibrium method and the like can analyze the overflow sewage source to a certain extent, a large amount of sampling and analysis work needs to be carried out, and the method has the characteristics of large manpower and material resource consumption, complex data analysis, low water quality index detection limit and low sensitivity, and cannot be popularized and applied in a large range.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a quick, sensitive and effective method for quickly identifying the source of the overflowing sewage in the rainy day of the urban drainage system.
The purpose of the invention can be realized by the following technical scheme:
a method for quickly identifying the source of overflow sewage of an urban drainage system in rainy days comprises the following steps:
an analysis sample collection step: collecting overflow sewage of a drainage pipe network as an analysis sample, and simultaneously recording corresponding collection time and place;
pretreatment of an analytical sample: adjusting the pH value and the concentration of the soluble organic carbon of the analysis sample;
an analysis data acquisition step: carrying out three-dimensional fluorescence spectrum analysis on the analysis sample obtained in the sample pretreatment step to obtain three-dimensional fluorescence spectrum data;
and (3) analysis data correction: correcting the three-dimensional fluorescence spectrum data by adopting a blank water sample deduction method and an interpolation method;
analyzing data: determining the components of the soluble organic matters through a parallel factor analysis model; acquiring maximum fluorescence intensity values corresponding to all soluble organic matter components in the analysis sample based on the three-dimensional fluorescence spectrum data acquired in the data correction step;
identifying a main contribution source: and (3) identifying the main contribution source of the overflowing sewage of the urban drainage system in rainy days by using the maximum fluorescence intensity value ratio corresponding to each soluble organic matter component of the analysis sample as an index and adopting a principal component analysis method according to the pre-established corresponding indication relationship between the fluorescence characteristics of the soluble organic matter components and the pollution source.
Dissolved Organic Matter (DOM) is one of the most prominent contaminant classes in overflow sewage in urban drainage systems in rainy days, and it is of general significance to characterize overflow sewage. The source analysis of the soluble organic matters carried by the overflowing sewage in rainy days of the drainage system is an important premise for realizing the optimized management of the urban drainage system and finally achieving the reduction of the overflowing pollution load in rainy days.
The three-dimensional fluorescence Spectrum (EEMs) can perform spectrum identification and characterization on objects with overlapped fluorescence Spectra in a multi-component complex system, is an effective spectrum fingerprint technology, and is widely applied to identification of complex pollution sources. As a broad water quality characteristic Factor Analysis and tracer agent Analysis method, a three-dimensional Fluorescence spectrum coupling Parallel Factor Analysis method (Excitation-Emission Matrix Fluorescence spectrum with Parallel Factor Analysis, EEM-PARAFAC) has shown a great potential for analyzing the source of soluble organic matters in overflow sewage. The method is simple to operate, high in identification speed, accurate in source tracing result, environment-friendly, energy-saving, economical and safe, and suitable for large-scale popularization and use.
Further, in the step of pretreating the analysis sample, the step of adjusting the pH value and the concentration of the soluble organic carbon of the analysis sample specifically comprises the following steps:
s201: the analysis sample was filtered through a 0.45 μm PVDF filter and diluted with ultrapure water so that the concentration of soluble organic carbon was less than 5mg C/L and the UV absorbance at 254nm was less than 0.05cm-1；
S202: adjusting the pH of the diluted sample to 2 ± 0.2 using 0.1M HCl and 0.1NaOH solution;
s203: the ionic strength of the assay sample was further adjusted to 10mM with 0.1M KCl.
Further, in the analysis data acquisition step, the three-dimensional fluorescence spectrum analysis is specifically performed on the analysis sample by using a fluorescence spectrometer at a temperature of 20 ± 2 ℃.
Further, the excitation wavelength scanning range of the fluorescence spectrometer is as follows: 250-450 nm, and the step length is 5 nm; the emission wavelength scan range is: 300-550 nm, and the step length is 2 nm.
Further, in the analysis data correction step, the blank water sample subtraction method specifically is to subtract the three-dimensional fluorescence spectrum data of the high purity water from the three-dimensional fluorescence spectrum data acquired in the data acquisition step, thereby correcting the three-dimensional fluorescence spectrum data acquired in the data acquisition step.
Further, in the step of analyzing data correction, the interpolation method specifically is to subtract a first-order rayleigh scattering effect and a second-order rayleigh scattering effect of the three-dimensional fluorescence spectrum data by using a Delaunay triangulation interpolation algorithm.
Further, in the analyzing data analyzing step, the expression of the parallel factor analysis model is as follows:
in the formula, xi,j,kThe fluorescence intensity, x, of the ith sample at the emission wavelength j and the excitation wavelength ki,j,kIs a constituent element of cubic array X (I × J × K), ai,nRepresenting elements of a composition matrix A of size I × N, bj,nRepresenting elements of a composition matrix B of size J × N, ck,nRepresenting elements of a composition matrix C of size K × NElement, ai,nUnder ideal conditions representing the concentration of latent fluorophore, bj,nEmission spectra representing latent fluorophores under ideal conditions, ck,nAn excitation spectrum representing a latent fluorophore under ideal conditions; e.g. of the typei,j,kIs a constituent element of a residual error cubic matrix E (I × J × K) and contains a noise variable, and N is a constituent number required for correctly fitting the parallel factor analysis model, wherein ai,nProportional to the substance concentration of the nth analytical component of the ith sample, bj,nLinear with the fluorescence quantum yield of the nth analytical component at the emission wavelength j, ck,nProportional to the specific absorption factor of the nth analytical component at the excitation wavelength k.
Further, in the analysis data analysis step, the determination of the soluble organic matter component is specifically: and determining the soluble organic matter component through nuclear consistency inspection and actual demand based on a parallel factor analysis model.
Further, in the step of identifying the main contribution source, the process of establishing the corresponding indication relationship between the fluorescence characteristics of the soluble organic components and the pollution source comprises the following steps:
and (3) indicating a sample collection step: collecting sediment filtrate of urban surface runoff rainwater, urban domestic sewage and/or drainage system sediment as an indication sample, and simultaneously recording corresponding collection time and place;
indicating a sample pretreatment step: adjusting the pH and the dissolved organic carbon concentration of the indicator sample;
an instruction data acquisition step: performing three-dimensional fluorescence spectrum analysis on the indication sample obtained in the indication sample pretreatment step to obtain three-dimensional fluorescence spectrum data;
and an indication data correction step: correcting the three-dimensional fluorescence spectrum data by adopting a blank water sample deduction method and an interpolation method;
and an indication relation establishing step: and acquiring the maximum fluorescence intensity value corresponding to each soluble organic matter component in the indication sample based on the three-dimensional fluorescence spectrum data acquired in the indication data correction step, and establishing the corresponding indication relation between the fluorescence characteristics of the soluble organic matter components and the pollution source.
Further, in the main contribution source identification step, the principal component analysis method reserves two principal components, and the characteristic value is larger than 1.
Further, in the main contribution source identification step, a load distribution map of the generalized data points is drawn by a principal component analysis method and a correspondence indicating relationship between the fluorescence characteristics of the soluble organic matter components and the contamination source, and the main contribution source is identified for the analysis sample.
The overflow sewage of the drainage pipe network is a mixed system formed by mixing a plurality of pollution sources, and the pollution sources occupying more than one proportion are main contribution sources of the mixed system.
Compared with the prior art, the invention has the following advantages:
(1) the method comprises the steps of extracting three-dimensional fluorescence spectrum data of an indication sample, obtaining maximum fluorescence intensity values corresponding to all soluble organic matter components in the indication sample by combining a parallel factor analysis method, and establishing a corresponding indication relation between fluorescence characteristics of the soluble organic matter components and a pollution source; identifying the main contribution sources of the analysis samples by a principal component analysis method; the method is simple to operate, high in identification speed, accurate in tracing result, environment-friendly, energy-saving, economical and safe, suitable for large-scale popularization and application, and capable of providing reliable data and decision support for effective control of overflow pollution of the urban drainage system and optimal management and upgrading transformation of the system.
(2) The method is used for identifying the main contribution source of the rainy-day overflow sewage based on the soluble organic matters, the soluble organic matters are one of the most main pollutant categories in the rainy-day overflow sewage of the urban drainage system, and compared with the conventional water quality index, the method has universal significance for representing the overflow sewage by using the soluble organic matters.
(3) The method obtains the maximum fluorescence intensity value corresponding to each soluble organic matter component in an analysis sample by a three-dimensional fluorescence spectrum coupling parallel factor analysis method, can perform spectrum identification and characterization on objects with overlapped fluorescence spectra in a multi-component complex system, is an effective spectrum fingerprint traceability analysis technology, has the characteristics of simple operation, high identification speed, accurate traceability result, environmental protection, energy conservation, economy, safety and the like, and is suitable for large-scale popularization and use.
(4) The invention considers the dynamic change of the chemical structure and the property of the pollutant from source to sink in the whole drainage system, and adjusts the pH value and the concentration of the soluble organic carbon of the analysis sample through the sample pretreatment step; and through the data correction step, a blank water sample deduction method is adopted, the Raman scattering effect is deducted, an interpolation method is adopted, the first-order and second-order Rayleigh scattering effects are deducted, the defect that the overflow pollution of the drainage system is represented or the pollution source is traced and analyzed through the conventional water quality index is overcome, and reliable data and decision support can be provided for the effective control of the overflow pollution of the urban drainage system and the optimization management and upgrading reconstruction of the system.
Drawings
FIG. 1 is a schematic flow chart of a method for rapidly identifying the source of overflow sewage in a rainy day in an urban drainage system according to the invention;
FIG. 2 is a schematic diagram of the geographical location of a sampling point and the land type of an underlying surface according to an embodiment of the present invention;
FIG. 3 is an original EEMs map of the overflow sewage in rainy days according to the embodiment of the present invention;
FIG. 4 is a graph of raw EEMs of high purity water according to an example of the present invention;
FIG. 5 is an EEMs map of an embodiment of the present invention minus the effect of Raman scattering;
FIG. 6 is a fully modified EEMs map of an embodiment of the present invention;
FIG. 7 shows a fitting component F of soluble organics in the example of the inventionmaxA PCA statistical analysis plot of the value proportion distribution;
FIG. 8 is a generalized data point loading profile according to an embodiment of the present invention;
in the figure, fluorescence intensity is fluorescence intensity, emission wavelength is emission wavelength, excitation wavelength is excitation wavelength, 1st Order Rayleigh Scatter Signal is first Order Rayleigh Scatter Signal, DOM signals are DOM signals, 2nd Order Rayleigh Scatter Signal is second Order Rayleigh Scatter Signal, and Raman Scatter Signal is Raman Scatter Signal.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Example 1
As shown in fig. 1, the embodiment provides a method for quickly identifying a source of overflow sewage in a rainy day in a municipal drainage system, which includes the following steps:
sample collection step S1: collecting overflow sewage of a drainage pipe network as an analysis sample; collecting sediment filtrate of urban surface runoff rainwater, urban domestic sewage and/or drainage system sediment as an indication sample; simultaneously recording corresponding acquisition time and location;
sample pretreatment step S1: adjusting the pH and the dissolved organic carbon concentration of the analytical sample and the indicator sample;
data acquisition step S2: carrying out three-dimensional fluorescence spectrum analysis on the analysis sample and the indication sample obtained in the sample pretreatment step to obtain three-dimensional fluorescence spectrum data;
data correction step S3: correcting the three-dimensional fluorescence spectrum data by adopting a blank water sample deduction method and an interpolation method;
data analysis step S4: determining the components of the soluble organic matters through a parallel factor analysis model; acquiring maximum fluorescence intensity values corresponding to all soluble organic matter components in the analysis sample and the indication sample based on the three-dimensional fluorescence spectrum data acquired in the data correction step; establishing a corresponding indication relation between the fluorescence characteristics of the soluble organic matter components and the pollution source according to the maximum fluorescence intensity value corresponding to each soluble organic matter component in the indication sample;
major contribution source identification step S5: and (3) identifying the main contribution source of the overflowing sewage of the urban drainage system in rainy days by using the maximum fluorescence intensity value ratio corresponding to each soluble organic matter component of the analysis sample as an index and adopting a principal component analysis method according to the corresponding indication relation between the fluorescence characteristics of the soluble organic matter components and the pollution source.
And (3) overflow pollution treatment: and according to the identification result of the main contribution source, the main source of the urban drainage system overflow pollution in rainy days is determined, and data and decision support are provided for the engineering practice of the urban drainage system optimization and reconstruction.
Each step is described in detail below.
1. Analysis sample collecting step S1
The sample sources of the embodiment include urban surface runoff rainwater, urban domestic sewage, drainage system sediments and overflow sewage, the main types, detailed collection places, system systems, batch numbers and total number of samples of the samples are shown in table 1, and the spatial geographic positions and the types of underlying surface land of sampling points are shown in fig. 2.
TABLE 1 basic information on samples collected
The following is a detailed description of the collection methods for each analytical sample and the indication of the source of the sample.
1.1, the sampling method of runoff rainwater comprises the following steps: collecting from the moment when runoff is formed after rainfall and ending when no runoff exists, wherein the sampling interval is 15min, and averaging and mixing samples;
1.2, the sampling method of newly added domestic sewage comprises the following steps: collecting the rainfall at a main discharge outlet of a sewage main pipe in a residential area 48 hours after the rainfall event is finished;
1.3, the sampling method of the residual domestic sewage comprises the following steps: collecting the mixture at a main discharge outlet of a sewage main pipe in a residential area after the rainfall event is finished for 10 days, wherein the sampling interval is 3 hours, the sampling time is 24 hours, and a flow weight mixed sample is taken;
1.4, the method for sampling the sediment of the drainage system comprises the following steps: collecting in a front pool and a pipeline of a drainage pump station after the rainfall event is finished for 10 days;
1.5, the method for sampling the overflow in rainy days and dry days comprises the following steps: collecting when the rainwater pump starts to operate until the rainwater pump stops operating, and taking a flow weight mixed sample.
All samples for analysis were collected using previously pickled high density polyethylene and numbered in detail according to time and place of collection. The samples were stored at 4 ℃ and the testing work required to be completed within 1 week.
2. Sample preprocessing step S1
Before the detection of the fluorescence signal of the sample is carried out, the fluorescence quenching effect of EEMs data needs to be suppressed experimentally and the internal filtering effect needs to be corrected.
The specific operation content comprises the following steps: the analysis sample and the indication sample were each filtered through a 0.45 μm PVDF filter membrane and diluted with ultrapure water so that the solution-soluble organic carbon concentration was less than 5mg C/L and the ultraviolet absorbance at 254nm was less than 0.05cm-1The requirements of (1); the pH of the diluted sample was adjusted to pH 2 ± 0.2 using 0.1M HCl and 0.1NaOH solution, and the ionic strength of the sample was continued to be adjusted to 10mM with 0.1M KCl. It is required that the volume of the acid-base buffer added per 10mL of the sample solution should be not more than 100. mu.L.
3. Data acquisition step S2
EEMs spectral data for the analytical and indicator samples were determined separately at 20. + -. 2 ℃ using a Horiba Fluoro Max4 fluorescence spectrometer, with 3 replicates per sample. Wherein, the excitation wavelength scanning range is as follows: 250-450 nm, and the step length is 5 nm; the emission wavelength scan range is: 300-550 nm, and the step length is 2 nm.
4. Data correction step S3
As shown in FIG. 3, three peaks of Raman scattering (Raman Scatter) and Second-Order Rayleigh Scatter (First and Second Order Rayleigh Scatter) are present in addition to the peaks of the soluble organic signal in the three-dimensional fluorescence Spectroscopy (EEMs) data.
As shown in fig. 4, the first-order rayleigh scattering has a very high fluorescence intensity, and the raman scattering peak intensity is generally low and can be seen more clearly in the original EEMs spectrum of high purity water. The presence of three scattered peaks seriously interferes with the correct fitting of the PARAFAC to the signal peaks of the soluble organics, so the three peaks are subtracted and interpolated accordingly before the PARAFAC model is calculated.
As shown in fig. 5, the raman scattering effect was subtracted by subtracting the high purity water EEMs data from the raw EEMs data of the analyzed sample. The subtraction of the first and second order rayleigh scattering effects is realized by a Delaunay triangulation interpolation algorithm, and corresponding differences are required after the scattering effects are subtracted. The Delaunay triangulation interpolation algorithm uses data points in the scattering peak area of the EEMs map to construct an optimal Delaunay triangulation network during calculation, original data points are kept unchanged after interpolation, and other points to be interpolated are only related to three vertexes of a triangle where the original data points are located. As shown in fig. 6, after the Delaunay triangulation interpolation algorithm is used, a complete signal peak of soluble organic substances appears in the EEMs spectrum.
5. Data analysis step S4
Decomposing the complete corrected EEMs data matrix into a set of cubic terms and residual arrays by adopting a PARAFAC method (parallel factor analysis method), namely a parallel factor analysis model:
in the formula, xi,j,kThe fluorescence intensity, x, of the ith sample at the emission wavelength j and the excitation wavelength ki,j,kIs a constituent element of cubic array X (I × J × K), ai,nRepresenting elements of a composition matrix A of size I × N, bj,nRepresenting elements of a composition matrix B of size J × N, ck,nRepresenting elements of a composition matrix C of size K × N, ai,nUnder ideal conditions representing the concentration of latent fluorophore, bj,nEmission spectra representing latent fluorophores under ideal conditions, ck,nAn excitation spectrum representing a latent fluorophore under ideal conditions; e.g. of the typei,j,kIs a constituent element of a residual error cubic matrix E (I × J × K) and contains a noise variable, and N is a constituent number required for correctly fitting the parallel factor analysis model, wherein ai,nProportional to the substance concentration of the nth analytical component of the ith sample, bj,nLinear with the fluorescence quantum yield of the nth analytical component at the emission wavelength j, ck,nProportional to the specific absorption factor of the nth analytical component at the excitation wavelength k.
Determination of the number of fitting components by three-dimensional fluorescence spectrum coupling Parallel Factor Analysis (Excitation-Emission matrix fluorescence spectrum with Parallel Factor Analysis, EEM-PARAFAC) is based on the nuclear consistency test and the actual research requirements. In this example, the nuclear consistency test scores and associated explanatory variances for the samples are shown in table 2.
TABLE 2 EEM-PARAFAC fitting kernel consistency test scores and interpretation variance of overflow sewage soluble organics in rainy days
When 2-5 components are matched, the core consistency test scores are all higher, and the matching is accurate and reasonable. The test score of the 6-component fitting is less than 90 percent, and the test is not satisfactory. The EEM-PARAFAC study of this example therefore used a 5-component fit (c 1-c 5). The matched PARAFAC component data needs to be subjected to semiquantitative analysis for calibration, and the area where each group of sample components are located and the maximum fluorescence intensity F of the area are identifiedmaxThe value is obtained. Referring to the relationship between the type of fluorescent substance and the position of the wavelength of the excitation-emission fluorescence peak established in the prior study, as shown in table 3, the corresponding indicating relationship between the fitting component of the soluble organic matter in the overflow sewage in rainy days of the urban drainage system and the pollution source in the example is established, as shown in table 4.
TABLE 3 excited emission fluorescence peak wavelength position of various soluble organic matter components in water
TABLE 4 corresponding indication relationship between fitting components of soluble organics in overflow sewage in rainy days of drainage system and pollution source
6. Major contribution source identifying step S5
The fitted dissolved organic components (c 1-c 5) F of the corresponding batch analysis samples were monitoredmaxThe ratio is used as an index to perform PCA calculation and draw the load of the generalized data pointsAnd (4) a lotus distribution diagram. Table 5 shows the soluble organics as matching component FmaxKMO, Bartlett spherical detection parameters and the interpretation variance of each PCA component of the proportional PCA statistic. In fig. 7 and 8, PCA retains 2 Principal Components (PC), PC1 can account for 49.4% of the total variance, PC2 can account for 23.3% of the total variance, which together account for 72.7% of the data lumped variance, KMO 0.705.
TABLE 5 soluble organics fitting component FmaxProportional PCA analysis and component interpretation variance
As shown in fig. 7 and 8, the generalized data points for all the analyzed samples are distributed in 5 cluster sets:
in the cluster A, the distributed water sample is mainly the seepage runoff rainwater on the underlying surface, which shows that the cluster A is the drainage type of the overflow sewage in rainy days with the seepage runoff rainwater on the underlying surface as the main part;
in cluster B, the sample generalized data points exhibited similar loading on PC1 and PC2, indicating that the variables c1, c2, c3 together determine the main properties of these water samples. The water samples distributed in the cluster comprise non-permeable underlying surface runoff rainwater without a mixed rainwater pipe, degraded non-permeable underlying surface runoff rainwater and dry flow sewage of a batch pump station. The cluster B is shown to be an overflow sewage discharge type which takes non-permeable underlying surface runoff rainwater as a main factor;
in the cluster C, the fitting component C4 in the dry flow sewage of the front pool of the Shanghai Chengdu north pump station, the dry flow sewage of the Shanghai Gueldy ferry pump station and the rain sewage mixed water of 2 batches of the Shanghai Shibo garden in the north area accounts for 50-70 percent, which shows that the cluster C is an overflow sewage discharge type taking residual domestic sewage as a leading part;
cluster D, occurs in the opposite load distribution quadrant to cluster B. The generalized data point of cluster D showed significant negative correlation with both PC1 and PC2 and significant positive correlation with variables c4 and c 5. The samples in the cluster mainly comprise overflowing sewage in rainy days, most of drought sewage, newly-added domestic sewage and sediments. The cluster D is shown to be an overflow sewage discharge type which takes newly increased and residual domestic sewage as a leading factor;
in the cluster E, the fitting component c5 in 2 batches of Shanghai-Lu ferry pump stations dry-flow sewage and 1 batch of Shanghai forest pump stations dry-flow sewage accounts for 60-73%, which indicates that the cluster E is an overflow sewage discharge type which takes newly-added domestic sewage as a main part.
Further, in this embodiment, based on the monitoring data, the potential source of the soluble organic matter in the overflow sewage of the urban drainage system in rainy days is analyzed by developing and using the EEM-parafacc on the MATLAB2012a software platform (MathWorks), and the fluorescence intensity information of the main component of the soluble organic matter is obtained. On this basis, the SPSS (version 20, IBM) software was used to fit the F of the soluble organic fraction to all samples analyzedmaxThe PCA statistical analysis is carried out on the proportion, so that the main source of the overflow sewage of the drainage system under the current rainfall condition can be quickly and effectively identified.
Example 2
This example is substantially the same as example 1, except that the correspondence between the fluorescence characteristics of the soluble organic component and the source of contamination in this example is established in advance.
Specifically, the method for quickly identifying the source of the overflow sewage of the urban drainage system in rainy days provided by the embodiment comprises the following steps:
an analysis sample collection step: collecting overflow sewage of a drainage pipe network as an analysis sample, and simultaneously recording corresponding collection time and place;
pretreatment of an analytical sample: adjusting the pH value and the concentration of the soluble organic carbon of the analysis sample;
an analysis data acquisition step: carrying out three-dimensional fluorescence spectrum analysis on the analysis sample obtained in the sample pretreatment step to obtain three-dimensional fluorescence spectrum data;
and (3) analysis data correction: correcting the three-dimensional fluorescence spectrum data by adopting a blank water sample deduction method and an interpolation method;
analyzing data: determining the components of the soluble organic matters through a parallel factor analysis model; acquiring maximum fluorescence intensity values corresponding to all soluble organic matter components in the analysis sample based on the three-dimensional fluorescence spectrum data acquired in the data correction step;
identifying a main contribution source: and (3) identifying the main contribution source of the overflowing sewage of the urban drainage system in rainy days by using the maximum fluorescence intensity value ratio corresponding to each soluble organic matter component of the analysis sample as an index and adopting a principal component analysis method according to the pre-established corresponding indication relationship between the fluorescence characteristics of the soluble organic matter components and the pollution source.
The establishment process of the corresponding indication relationship between the fluorescence characteristics of the soluble organic components and the pollution source comprises the following steps:
and (3) indicating a sample collection step: collecting sediment filtrate of urban surface runoff rainwater, urban domestic sewage and/or drainage system sediment as an indication sample, and simultaneously recording corresponding collection time and place;
indicating a sample pretreatment step: adjusting the pH and the dissolved organic carbon concentration of the indicator sample;
an instruction data acquisition step: performing three-dimensional fluorescence spectrum analysis on the indication sample obtained in the indication sample pretreatment step to obtain three-dimensional fluorescence spectrum data;
and an indication data correction step: correcting the three-dimensional fluorescence spectrum data by adopting a blank water sample deduction method and an interpolation method;
and an indication relation establishing step: and acquiring the maximum fluorescence intensity value corresponding to each soluble organic matter component in the indication sample based on the three-dimensional fluorescence spectrum data acquired in the indication data correction step, and establishing the corresponding indication relation between the fluorescence characteristics of the soluble organic matter components and the pollution source.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. A method for quickly identifying the source of overflow sewage of a municipal drainage system in rainy days is characterized by comprising the following steps:
an analysis sample collection step: collecting overflow sewage of a drainage pipe network as an analysis sample, and simultaneously recording corresponding collection time and place;
pretreatment of an analytical sample: adjusting the pH value and the concentration of the soluble organic carbon of the analysis sample;
an analysis data acquisition step: carrying out three-dimensional fluorescence spectrum analysis on the analysis sample obtained in the sample pretreatment step to obtain three-dimensional fluorescence spectrum data;
and (3) analysis data correction: correcting the three-dimensional fluorescence spectrum data by adopting a blank water sample deduction method and an interpolation method;
analyzing data: determining the components of the soluble organic matters through a parallel factor analysis model; acquiring maximum fluorescence intensity values corresponding to all soluble organic matter components in the analysis sample based on the three-dimensional fluorescence spectrum data acquired in the data correction step;
identifying a main contribution source: and (3) identifying the main contribution source of the overflowing sewage of the urban drainage system in rainy days by using the maximum fluorescence intensity value ratio corresponding to each soluble organic matter component of the analysis sample as an index and adopting a principal component analysis method according to the pre-established corresponding indication relationship between the fluorescence characteristics of the soluble organic matter components and the pollution source.
2. The method for rapidly identifying the source of the urban drainage system overflowing sewage in rainy days according to claim 1, wherein in the step of pretreating the analysis sample, the step of adjusting the pH value and the concentration of the soluble organic carbon of the analysis sample comprises the following steps:
s201: the analysis sample was filtered through a 0.45 μm PVDF filter and diluted with ultrapure water so that the concentration of soluble organic carbon was less than 5mg C/L and the UV absorbance at 254nm was less than 0.05cm-1；
S202: adjusting the pH of the diluted sample to 2 ± 0.2 using 0.1M HCl and 0.1NaOH solution;
s203: the ionic strength of the assay sample was further adjusted to 10mM with 0.1M KCl.
3. The method for rapidly identifying the source of the urban drainage system overflowing sewage in rainy days according to claim 1, wherein in the analysis data acquisition step, the three-dimensional fluorescence spectrum analysis is specifically performed on an analysis sample by using a fluorescence spectrometer at a temperature of 20 +/-2 ℃.
4. The method for rapidly identifying the source of the overflowing sewage in the rainy day in the urban drainage system according to claim 3, wherein the excitation wavelength scanning range of the fluorescence spectrometer is as follows: 250-450 nm, and the step length is 5 nm; the emission wavelength scan range is: 300-550 nm, and the step length is 2 nm.
5. The method according to claim 1, wherein in the step of analyzing data correction, the blank water sample deduction method is specifically that the three-dimensional fluorescence spectrum data obtained in the step of obtaining data is subtracted from the three-dimensional fluorescence spectrum data of the high purity water, so as to correct the three-dimensional fluorescence spectrum data obtained in the step of obtaining data.
6. The method as claimed in claim 1, wherein in the step of analyzing and correcting the data, the interpolation method is to subtract a first-order rayleigh scattering effect and a second-order rayleigh scattering effect of the three-dimensional fluorescence spectrum data by using a Delaunay triangulation interpolation algorithm.
7. The method for rapidly identifying the source of the overflowing sewage of the urban drainage system in the rainy day according to claim 1, wherein in the step of analyzing the data, the expression of the parallel factor analysis model is as follows:
in the formula, xi,j,kThe fluorescence intensity, x, of the ith sample at the emission wavelength j and the excitation wavelength ki,j,kIs a constituent element of cubic array X (I × J × K), ai,nRepresenting elements of a composition matrix A of size I × N, bj,nRepresenting elements of a composition matrix B of size J × N, ck,nRepresenting elements of a composition matrix C of size K × N, ai,nUnder ideal conditions representing the concentration of latent fluorophore, bj,nEmission spectra representing latent fluorophores under ideal conditions, ck,nAn excitation spectrum representing a latent fluorophore under ideal conditions; e.g. of the typei,j,kIs a constituent element of a residual error cubic matrix E (I × J × K) and contains a noise variable, and N is a constituent number required for correctly fitting the parallel factor analysis model, wherein ai,nProportional to the substance concentration of the nth analytical component of the ith sample, bj,nLinear with the fluorescence quantum yield of the nth analytical component at the emission wavelength j, ck,nProportional to the specific absorption factor of the nth analytical component at the excitation wavelength k.
8. The method for rapidly identifying the source of the overflowing sewage of the urban drainage system in the rainy day according to claim 1, wherein in the step of analyzing data, the determination of the soluble organic components is specifically as follows: and determining the soluble organic matter component through nuclear consistency inspection and actual demand based on a parallel factor analysis model.
9. The method for rapidly identifying the source of the overflowing sewage in the rainy day in the urban drainage system according to claim 1, wherein in the step of identifying the main contribution source, the establishment of the corresponding indication relationship between the fluorescence characteristics of the soluble organic components and the pollution source comprises the following steps:
and (3) indicating a sample collection step: collecting sediment filtrate of urban surface runoff rainwater, urban domestic sewage and/or drainage system sediment as an indication sample, and simultaneously recording corresponding collection time and place;
indicating a sample pretreatment step: adjusting the pH and the dissolved organic carbon concentration of the indicator sample;
an instruction data acquisition step: performing three-dimensional fluorescence spectrum analysis on the indication sample obtained in the indication sample pretreatment step to obtain three-dimensional fluorescence spectrum data;
and an indication data correction step: correcting the three-dimensional fluorescence spectrum data by adopting a blank water sample deduction method and an interpolation method;
and an indication relation establishing step: and acquiring the maximum fluorescence intensity value corresponding to each soluble organic matter component in the indication sample based on the three-dimensional fluorescence spectrum data acquired in the indication data correction step, and establishing the corresponding indication relation between the fluorescence characteristics of the soluble organic matter components and the pollution source.
10. The method for rapidly identifying the source of the sewage overflowing in the rainy day in the urban drainage system according to claim 1, wherein in the identifying step of the main contribution source, the load distribution map of the generalized data points is drawn by the principal component analysis method and the corresponding indication relationship between the fluorescence characteristics of the soluble organic components and the pollution source, and the identification of the main contribution source is performed on the analysis sample.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010386861.3A CN111562242A (en) | 2020-05-09 | 2020-05-09 | Method for quickly identifying source of overflowing sewage in rainy days of urban drainage system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010386861.3A CN111562242A (en) | 2020-05-09 | 2020-05-09 | Method for quickly identifying source of overflowing sewage in rainy days of urban drainage system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111562242A true CN111562242A (en) | 2020-08-21 |
Family
ID=72068006
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010386861.3A Pending CN111562242A (en) | 2020-05-09 | 2020-05-09 | Method for quickly identifying source of overflowing sewage in rainy days of urban drainage system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111562242A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112630202A (en) * | 2020-12-10 | 2021-04-09 | 湖南大学 | Method for identifying source of overflowing sewage in rainy days of urban drainage system |
| CN113075181A (en) * | 2021-03-25 | 2021-07-06 | 昆明市生态环境局安宁分局生态环境监测站 | Linear transformation gain method for water pollution tracing three-dimensional fluorescent digital signal |
| CN113514436A (en) * | 2021-06-17 | 2021-10-19 | 上海勘测设计研究院有限公司 | Method for rapidly judging rainwater connection into sewage inspection well |
| CN113834800A (en) * | 2021-08-25 | 2021-12-24 | 昆山市污水处理有限公司 | Method for testing carbon-containing disinfection byproducts based on fluorescence spectrum |
| CN114594055A (en) * | 2022-03-25 | 2022-06-07 | 同济大学 | Spectral-based rainwater pipeline mixed junction non-excavation diagnosis method |
| CN114878528A (en) * | 2022-04-21 | 2022-08-09 | 宁波大学 | Method for quickly tracing surface water surface floating oil based on three-dimensional fluorescence spectroscopy |
| CN115081594A (en) * | 2022-07-01 | 2022-09-20 | 上海城市水资源开发利用国家工程中心有限公司 | Drainage pipeline sediment source quantitative calculation method |
| CN116858817A (en) * | 2023-07-24 | 2023-10-10 | 同济大学 | Industrial wastewater mixed contact point position diagnosis method based on fluorescence spectrum |
| CN117522653A (en) * | 2024-01-05 | 2024-02-06 | 同济大学 | Rain and sewage hybrid joint traceability analysis method based on three-dimensional fluorescence and municipal pipe network BIM model |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102890075A (en) * | 2012-10-17 | 2013-01-23 | 中国环境科学研究院 | Quickly judging method for underground water polluted by organic matter |
-
2020
- 2020-05-09 CN CN202010386861.3A patent/CN111562242A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102890075A (en) * | 2012-10-17 | 2013-01-23 | 中国环境科学研究院 | Quickly judging method for underground water polluted by organic matter |
Non-Patent Citations (4)
| Title |
|---|
| 上海斯迈欧分析仪器有限公司: "使用三维荧光光谱的多变量分析法评价水中有机物", 《化工仪器网 WWW.CHEM17.COM/TECHNOLOGY/DETAIL/390581.HTML》 * |
| 周双玉等: "城市排水泵站溢流沉积物释放溶解性有机物的动态荧光特征", 《广东化工》 * |
| 陈方等: "饮用水有机污染物的三维荧光光谱检测与分析方法", 《浙江大学学报（农业与生命科学版）》 * |
| 黄廷林等: "荧光光谱结合平行因子分析研究夏季周村水库溶解性有机物的分布与来源", 《环境科学》 * |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112630202A (en) * | 2020-12-10 | 2021-04-09 | 湖南大学 | Method for identifying source of overflowing sewage in rainy days of urban drainage system |
| CN113075181A (en) * | 2021-03-25 | 2021-07-06 | 昆明市生态环境局安宁分局生态环境监测站 | Linear transformation gain method for water pollution tracing three-dimensional fluorescent digital signal |
| CN113075181B (en) * | 2021-03-25 | 2024-05-24 | 昆明市生态环境局安宁分局生态环境监测站 | Linear transformation gain method for water pollution traceability three-dimensional fluorescent digital signal |
| CN113514436A (en) * | 2021-06-17 | 2021-10-19 | 上海勘测设计研究院有限公司 | Method for rapidly judging rainwater connection into sewage inspection well |
| CN113834800A (en) * | 2021-08-25 | 2021-12-24 | 昆山市污水处理有限公司 | Method for testing carbon-containing disinfection byproducts based on fluorescence spectrum |
| CN114594055A (en) * | 2022-03-25 | 2022-06-07 | 同济大学 | Spectral-based rainwater pipeline mixed junction non-excavation diagnosis method |
| CN114878528A (en) * | 2022-04-21 | 2022-08-09 | 宁波大学 | Method for quickly tracing surface water surface floating oil based on three-dimensional fluorescence spectroscopy |
| CN115081594A (en) * | 2022-07-01 | 2022-09-20 | 上海城市水资源开发利用国家工程中心有限公司 | Drainage pipeline sediment source quantitative calculation method |
| CN115081594B (en) * | 2022-07-01 | 2024-05-14 | 上海城市水资源开发利用国家工程中心有限公司 | Quantitative calculation method for sediment source of drainage pipeline |
| CN116858817A (en) * | 2023-07-24 | 2023-10-10 | 同济大学 | Industrial wastewater mixed contact point position diagnosis method based on fluorescence spectrum |
| CN117522653A (en) * | 2024-01-05 | 2024-02-06 | 同济大学 | Rain and sewage hybrid joint traceability analysis method based on three-dimensional fluorescence and municipal pipe network BIM model |
| CN117522653B (en) * | 2024-01-05 | 2024-03-26 | 同济大学 | Rain and sewage hybrid joint traceability analysis method based on three-dimensional fluorescence and municipal pipe network BIM model |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111562242A (en) | Method for quickly identifying source of overflowing sewage in rainy days of urban drainage system | |
| Ma et al. | Identification of nitrate sources in groundwater using a stable isotope and 3DEEM in a landfill in Northeast China | |
| CN109470667A (en) | A kind of combination water quality parameter and three-dimensional fluorescence spectrum carry out the method that pollutant is traced to the source | |
| CN107677614B (en) | Online early warning system and method for risk of heavy metal pollution in water | |
| CN110083585B (en) | Water pollution discharge source database and establishing method thereof | |
| Angello et al. | Spatio-temporal evaluation and quantification of pollutant source contribution in little akaki river, Ethiopia: conjunctive application of factor analysis and multivariate receptor model | |
| CN111678969A (en) | Method for analyzing heavy metal pollution source by using soil profile surface layer heavy metal accumulation proportion | |
| CN114594055B (en) | Rain water pipeline mixed contact point non-excavation diagnosis method based on spectrum | |
| CN105675838B (en) | A based on data-driven2/ O flow water outlet total phosphorus intelligent detecting methods | |
| CN112630202A (en) | Method for identifying source of overflowing sewage in rainy days of urban drainage system | |
| Yin et al. | Tryptophan-like fluorescence as a fingerprint of dry-weather misconnections into storm drainage system | |
| Zhu et al. | Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm | |
| CN108507955A (en) | The device and method of multispectral synchronous detection chemical oxygen demand of water body | |
| Bai et al. | Ecological water replenishment to the Yongding River, China: effects of different water sources on inorganic ions and organic matter characteristics | |
| CN116858817A (en) | Industrial wastewater mixed contact point position diagnosis method based on fluorescence spectrum | |
| CN114663783B (en) | Remote sensing identification method for water body pollution of river entering sea based on machine learning | |
| CN116612380A (en) | Urban water pollution tracing remote sensing method based on hyperspectral data | |
| CN111523799A (en) | Method for analyzing rain and sewage mixing degree of shunt system pipe network | |
| CN113075181B (en) | Linear transformation gain method for water pollution traceability three-dimensional fluorescent digital signal | |
| CN111007220B (en) | Method for agile monitoring of water quality of live pig breeding sewage | |
| Minutolo et al. | Sedimentary mud and phaeophytin-a are reliable predictors of oxygen consumption and nitrogen turnover in the southern North Sea | |
| Zhao et al. | Development of water basin pollution emission inventory: a preliminary literature review and Its implication for China | |
| CN117974404B (en) | Land-land cooperative land-domain pollution source analysis method and system | |
| CN118071370A (en) | Method and system for tracing soluble organic matters in water body discharged from drainage pipeline network | |
| CN115168446B (en) | Pollutant tracing method and device and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200821 |
|
| RJ01 | Rejection of invention patent application after publication |