CN113051844B - Method for identifying and accurately tracing environmental pollution events of ocean and open water areas - Google Patents

Method for identifying and accurately tracing environmental pollution events of ocean and open water areas Download PDF

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CN113051844B
CN113051844B CN202110267189.0A CN202110267189A CN113051844B CN 113051844 B CN113051844 B CN 113051844B CN 202110267189 A CN202110267189 A CN 202110267189A CN 113051844 B CN113051844 B CN 113051844B
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盛彦清
姜明
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Coastal Ecological Environment Industry Development Yantai Co ltd
Yantai Institute of Coastal Zone Research of CAS
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Abstract

The invention discloses a method for identifying and accurately tracing the pollution events of oceans and open water areas, which analyzes the fluorescence characteristics of polluted water areas and potential sewage sources by utilizing a three-dimensional fluorescence spectrum and combining a parallel factor analysis model, comprehensively contrasts and analyzes the homology of soluble organic matter components, and accurately traces the pollution of the water areas and identifies the pollution of the water areas on the basis of qualitative and quantitative analysis through the simulation prediction of the sewage discharge from the sea and the deduction of the environmental behavior of characteristic pollutants. The invention can purposefully control and treat the pollution source in the marine pollution event.

Description

Method for identifying and accurately tracing environmental pollution events of ocean and open water areas
Technical Field
The invention belongs to the technical field of environmental emergency management, and relates to a method for identifying and accurately tracing an environmental pollution event in ocean and open water.
Background
Accurate pollution source identification is the first step in pollution control in environmental emergency management, especially in marine and open water area emergency pollution events. Near shore input and its mixing with the ocean is the main factor controlling the distribution and composition of dissolved organic matter. The soluble organic matter mainly comprises humic substances, carbohydrates and protein substances. In a body of water, it can be divided into two distinct sources: offsite (e.g., industrial wastewater and residential sewage) and onsite (e.g., in situ phytoplankton and bacterial production). In sediment, dissolved organic matter analysis can be used to determine its chemistry and durability. The input of exogenous load may increase dissolved organic matter humification in offshore waters while introducing substantial primary productivity, resulting in the production of endogenous dissolved organic matter. Therefore, the dissolved organic matter contains information from various sources, can be used as a tracing factor for tracing analysis of the pollutants in the marine ecosystem, and reflects the source and change conditions of the water body.
The current water pollution tracing and identifying method comprises a deterministic method and a probabilistic method. The deterministic method adopts a determined mathematical physical equation to carry out simulation analysis on the motion of the pollutants, and the probabilistic method carries out evaluation according to the occurrence probability of a specific event. The method has the limitations that the tracing of the source sea area pollution event needs a large number of high-precision numerical values (such as tide level, wave, submarine topography and the like) for data simulation, the pollution source cannot be quickly and effectively locked on the basis of qualitative and quantitative, and the accurate tracing of the sudden water area pollution event cannot be realized.
Disclosure of Invention
In order to solve the above technical problems, the present invention provides a method for identifying and tracing to the source of environmental pollution events in oceans and open waters.
The invention provides a method for identifying and accurately tracing environmental pollution events of oceans and open water areas, which comprises the following steps:
step 1: obtaining a potential sewage discharge source according to the hydrological and geological profile of water quality of a water area, the current municipal sewage discharge situation and the sewage discharge situation of potential enterprises in a drainage basin;
and 2, step: sampling data of selected sampling points of a polluted water area, and simultaneously sampling data of a drain outlet of a potential drain source;
and step 3: measuring the overlying water and the sediment on a fluorescence spectrum analyzer;
And 4, step 4: carrying out homology analysis on dissolved organic matters in the polluted water area and the potential pollution discharge source by combining a parallel factor model;
and 5: building a tracing model based on the internal relation between the fluorescence characteristics of the polluted water area and the potential sewage source, and verifying the accuracy of tracing the pollution of the water area by combining the three-dimensional fluorescence spectrum with the parallel factor method through comparison of numerical simulation results.
The invention relates to a method for identifying and accurately tracing environmental pollution events in oceans and open water areas, which combines hydrological parameters of related areas to directionally screen pollution sources, adopts a three-dimensional fluorescence spectrum combined with a parallel factor model to decompose soluble organic matters into fluorescent components of different types, realizes spectrum resolution of the three-dimensional fluorescence spectrum, identifies water area homology by comparing fluorescence characteristics, combines pollution source pollution discharge values to build a tracing model, and verifies the accuracy of tracing the water area pollution of the three-dimensional fluorescence spectrum combined with the parallel factor analysis model. On the basis of qualitative and quantitative analysis, the method can quickly and effectively lock the water pollution source and can purposefully control and treat the pollution source in the marine pollution event.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2a is a graph of the sum of squared errors of excitation wavelength factors;
FIG. 2b is a graph of the sum of squares error of the emission wavelength factors;
FIG. 3 is a three-dimensional fluorescence spectrum analyzed by the parallel factor method;
FIG. 4 is a graph of the excitation/emission profile loading values of the components of the three-dimensional fluorescence spectrum;
FIG. 5 is a graph of relative content percentages of fluorescent components;
FIG. 6 is a graph representing relative fluorescence intensity;
FIG. 7 is a graph of diffusion simulation of chemical oxygen demand for potential blowdown source at different time periods.
Detailed Description
As shown in fig. 1, the present invention provides a method for identifying and accurately tracing the environmental pollution events of oceans and open water areas, comprising the following steps:
step 1: obtaining a potential sewage discharge source according to the hydrological and geological profile of water quality of a water area, the current municipal sewage discharge situation and the sewage discharge situation of potential enterprises in a drainage basin;
step 2: sampling data of selected sampling points of a polluted water area, and simultaneously sampling data of a drain outlet of a potential drain source;
and step 3: measuring the overlying water and the sediment on a fluorescence spectrum analyzer;
in specific implementation, the temperature of the deposit is between 50 ℃ below zero and 0 ℃, the pressure is between 13 and 100Pa, and the freeze drying time is 24 hours;
in specific implementation, the sediments are vibrated for 24 hours at 200r/min according to the water-soil mass ratio of 1:10, then the sediments are centrifuged for 15 minutes at 5000r/min, and the extracted supernatant and the upper coating are respectively filtered by 0.45 mu m glass fiber filter membranes;
During specific implementation, a water sample is put into a 1cm quartz fluorescent sample pool, relevant parameters are set, deionized ultrapure water is used as blank reference, the Raman scattering influence of a fluorescence spectrum is eliminated, and fluorescence spectrum detection is carried out.
In the specific implementation, parameters of the fluorescence spectrum analyzer are set, an excitation light source is a 150W xenon lamp, the voltage is set to 700V, the scanning range of the excitation wavelength is 250-800 nm, the scanning range of the emission wavelength is 240-800 nm, the wavelength interval is 2nm, the scanning speed is 1200nm/min, deionized ultrapure water is used as blank reference, and the Raman scattering influence of the fluorescence spectrum is eliminated.
And 4, step 4: carrying out homology analysis on dissolved organic matters of the polluted water area and a potential sewage source by combining three-dimensional fluorescence spectrum analysis and a parallel factor model to obtain the fluorescence component intensity distribution of the water area sample;
when in specific implementation, the method comprises the following steps:
(1) the fluorescence spectrum data obtained by measurement form an I multiplied by J multiplied by K matrix, the parallel factor model analysis is carried out on the three-dimensional data matrix by adopting an N-way and DOMFluor tool box in Matlab2014a software, the parallel factor model analysis is decomposed into a score matrix A and load matrices B and C by adopting an alternating least square method, and the decomposition model is expressed as:
Figure BDA0002972490580000041
wherein I is the number of samples, and J and K are the numbers of emission wavelengths and excitation wavelengths of the samples respectively; x is the number of ijkThe fluorescence intensity value of the ith sample at the position with the emission wavelength of j and the excitation wavelength of k; n is the number of factors; a isin,bjn,cknRespectively representing elements in the load matrixes A, B and C, and respectively representing component concentration, emission spectrum and excitation spectrum information; e.g. of the typeijkIs a constituent element of a residual matrix E (I × J × K);
(2) setting a plurality of N values, and constructing parallel factor models with different factor quantities;
(3) setting initial values of B and C, wherein the dimension of B is J multiplied by N, the dimension of C is K multiplied by N, and solving A according to the formula (2) and the formula (3);
Figure BDA0002972490580000042
A＝XZT(ZZT)-1 (3)
wherein z isnIs a column vector; bnThe column vector of the nth factor is represented in B; c. CnThe column vector of the nth factor is represented in C;
Figure BDA0002972490580000043
to solve for the tensor product; x is the expansion of a three-dimensional matrix, and the dimension of the matrix is I multiplied by JK; z is a matrix formed by column vectors Zn, and the dimension of the matrix is NxJK;
(4) based on the obtained estimated value of A and the initial value of C, estimating a matrix B by the same method; estimating a matrix C by using the estimated values of A and B; successively iterating and circulating until convergence;
(5) when the residual error E is minimum and the consistency of the kernel is highest, the parallel factor analysis model of the N value is an optimal model;
(6) determining the fluorescence characteristics of each component according to the fluorescence peak position of each component analyzed by a parallel factor method;
(7) and characterizing the distribution of each component in the sampling region by the relative proportion and the fluorescence intensity of each fluorescence component of the obtained sample component corresponding to the maximum fluorescence intensity, and performing water pollution homology analysis according to component similarity and color display degree.
And 5: building a tracing model based on the internal relation between the fluorescence characteristics of the polluted water area and the potential sewage source, and verifying the accuracy of tracing the pollution of the water area by combining the three-dimensional fluorescence spectrum with a parallel factor method.
When the method is implemented, the method specifically comprises the following steps:
(1) and (3) carrying out pollution diffusion simulation by adopting a two-dimensional modeling system MIKE21, wherein a two-dimensional pollutant convection diffusion control equation is expressed as follows:
Figure BDA0002972490580000051
c in formula (4) is the concentration of the contaminant; u and v are flow velocity components in the x direction and the y direction respectively; dx and Dy are the dispersion coefficients in the x and y directions; QsCs is a pollution emission source, Qs is point source emission in a unit area, and Cs is pollutant emission concentration; f is an attenuation coefficient;
(2) setting a boundary condition;
bank boundary conditions: the concentration flux is zero;
opening boundary conditions: the inflow equation is expressed as:
cΓ＝c0 (5)
in the formula (5), r is a water boundary; c. C0For boundary concentration, model only, calculating incremental influence, and taking c0＝0。
The outflow equation is expressed as:
Figure BDA0002972490580000052
v in the formula (6) is boundary normal flow velocity; n is the normal direction;
(3) taking chemical oxygen demand of a potential pollution discharge source in different time periods as a simulation substance, and inputting data to carry out numerical simulation;
(4) and (4) comparing the numerical simulation diagram with the fluorescence component intensity distribution of the water area sample in the step (4), and verifying the accuracy of the three-dimensional fluorescence spectrum combined with the parallel factor method for tracing the source water area pollution.
The present invention will be described in detail below with reference to the drawings and examples, but the scope of the present invention is not limited to the drawings and examples described below.
In a certain offshore area of Shandong tobacco terrace, the chemical oxygen demand in the water body is far higher than 40mg/L due to serious industrial non-point source pollution in recent years. The geological overview of the water area, the current situation of municipal pollution discharge and potential enterprises in the drainage basin are integrated, and the potential discharge source is determined to be a chemical enterprise, but direct evidence of pollution discharge is not found. In order to determine the correlation between the potential sewage discharge source and the pollution of the water area, partial sampling points including overburden water and sediment are selected for the polluted water area, and meanwhile, sampling investigation is conducted on the sewage discharge outlet of the enterprise.
And (3) introducing the three-dimensional fluorescence spectrum data into Matlab 2014a software, and performing parallel factor model analysis on the three-dimensional data matrix by adopting an N-way and DOMFluor tool box, wherein as shown in the attached figures 2a and 2b, in the process of increasing the factor number N from 2 to 7, the fluctuation is smaller and smaller, the fitting effect is better and better, and when N is 4, the kernel consistency is highest, the error is minimum, and the model is optimal.
Resolving 4 components C1, C2, C3 and C4 according to a parallel factor method, wherein the component C1 represents a land-derived fulvic acid substance in a diagram of figure 3 a; component C2 represents a tryptophan-like substance in panel b of fig. 3; component C3 in panel C of fig. 3 represents a mixed land-and sea-derived fulvic acid-like substance; component C4 represents a tyrosine-like substance in panel d of fig. 3.
FIG. 4 a shows that component C1 has two distinct excitation wavelengths at 254nm and 359nm, the maximum emission wavelength is 457nm, and the corresponding fluorescence peaks are respectively an A peak and a C peak; FIG. 4 b is a graph showing that component C2 has a distinct excitation wavelength at 293nm, a maximum emission wavelength of 356nm, and a corresponding fluorescence peak of T peak; FIG. 4C is a graph showing that component C3 has two distinct excitation wavelengths at 251nm and 311nm, the maximum emission wavelength is 392nm, and the corresponding fluorescence peaks are respectively an A peak and an M peak; FIG. 4 d shows component C4 with a distinct excitation wavelength at 275nm, a maximum emission wavelength of 328nm, and a corresponding fluorescence peak as the B peak.
The obtained sample components corresponding to the maximum fluorescence intensity are characterized by the distribution of each component in the sampling area according to the relative fluorescence intensity, and the analysis is carried out according to the display degree of the water area color, which shows that the water area pollution has obvious land source input, as shown in figure 5.
And then comparing and analyzing the contribution rate of the fluorescence component of each sample, as shown in figure 6, it can be known that the sample points No. 1, No. 2 and No. 5 of the pollution discharge enterprise are matched with the samples C1 and C3 in the fluorescence components of the overlying water and the sediment, the samples No. 3 and No. 4 are matched with the component C4, the sample C2 only finds higher contribution rate near the sewage outlet, and the relative fluorescence intensity of the four components is gradually reduced from the sewage outlet to the open sea area as a whole corresponding to the sample points No. 1 and No. 2 of the pollution discharge enterprise, and the synthesis shows that the pollution of the water area comes from the chemical enterprise.
Based on the chemical oxygen demand discharge concentration of chemical enterprises, parameters such as water quality and water quantity are combined, the chemical oxygen demand sea-entering diffusion range of sewage in different time periods is simulated, the interval time is 24h, a pollution diffusion model of the chemical oxygen demand discharge enterprises and the three-dimensional fluorescence spectrum contrast analysis of water areas are integrated, and the simulated high-concentration shape is very similar to the shape of relative fluorescence intensity, as shown in fig. 7. In the figure, a is a 24h diffusion distribution diagram; in the figure, b is a 48h diffusion distribution diagram; in the figure, c is a 72h diffusion distribution diagram; in the figure, d is a 96h diffusion profile. The water pollution is fully shown to come from the emission of high-load pollutants of pollution discharge enterprises, and the three-dimensional fluorescence spectrum is further proved to be combined with a parallel factor method model to analyze dissolved organic matters so as to accurately trace the source and identify the environmental pollution of oceans and coastal water areas.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the scope of the present invention, which is defined by the appended claims.

Claims (5)

1. A method for identifying and accurately tracing environmental pollution events of oceans and open water areas is characterized by comprising the following steps:
step 1: obtaining a potential sewage discharge source according to the hydrological and geological profile of water quality of a water area, the current municipal sewage discharge situation and the sewage discharge situation of potential enterprises in a drainage basin;
Step 2: sampling data of selected sampling points of a polluted water area, and simultaneously sampling data of a drain outlet of a potential drain source;
and step 3: measuring the overlying water and the sediment on a fluorescence spectrum analyzer;
and 4, step 4: carrying out homology analysis on dissolved organic matters of the polluted water area and a potential sewage source by combining a three-dimensional fluorescence spectrum analysis model and a parallel factor analysis model to obtain the fluorescence component intensity distribution of the water area sample;
and 5: building a tracing model based on the internal relation between the fluorescence characteristics of the polluted water area and the potential sewage source, and verifying the accuracy of tracing the pollution of the water area by combining the three-dimensional fluorescence spectrum with the parallel factor analysis model through comparison of numerical simulation results;
the source tracing model is built in the step 5, namely sea-entering sewage discharge numerical simulation by utilizing a potential sewage discharge source is utilized, and the method specifically comprises the following steps:
(1) and (3) carrying out pollution diffusion simulation by adopting a two-dimensional modeling system MIKE21, wherein a two-dimensional pollutant convection diffusion control equation is expressed as follows:
Figure FDA0003629435320000011
c in formula (4) is the concentration of the contaminant; u and v are flow velocity components in the x direction and the y direction respectively; dx and Dy are the dispersion coefficients in the x and y directions; QsCs is a pollution emission source, Qs is point source emission in a unit area, and Cs is pollutant emission concentration; f is an attenuation coefficient;
(2) Setting a boundary condition;
and bank boundary conditions: the concentration flux is zero;
opening boundary conditions: the inflow equation is expressed as:
cΓ＝c0 (5)
in the formula (5), r is a water boundary; c. C0For boundary concentration, model only, calculating incremental influence, and taking c0＝0；
The outflow equation is expressed as:
Figure FDA0003629435320000021
v in the formula (6) is boundary normal flow velocity; n is the normal direction;
(3) inputting data to perform numerical simulation by taking chemical oxygen demand as a simulation substance;
(4) and (4) comparing the numerical simulation diagram with the fluorescence component intensity distribution of the water area sample in the step (4), and verifying the accuracy of the three-dimensional fluorescence spectrum combined with the parallel factor method for tracing the source water area pollution.
2. The method for identifying and tracing the environmental pollution events in the ocean and open water areas accurately according to claim 1, wherein the temperature of the sediment in step 3 is-50 ℃ to 0 ℃, the pressure is 13 Pa to 100Pa, and the freeze-drying time is 24 h.
3. The method for identifying and tracing the environmental pollution events in the ocean and open water areas accurately according to claim 1, wherein in the step 3, the sediments are vibrated for 24h at the water-soil mass ratio of 1:10 and 200r/min, then are centrifuged for 15min at 5000r/min, and the extracted supernatant and the overlying water are respectively filtered through 0.45 μm glass fiber filter membranes.
4. The method for identifying and accurately tracing the environmental pollution events in the ocean and open water areas according to claim 1, wherein in the step 3, the parameters of the fluorescence spectrum analyzer are set, an excitation light source is a 150W xenon lamp, the voltage is set to 700V, the scanning range of the excitation wavelength is 250-800 nm, the scanning range of the emission wavelength is 240-800 nm, the wavelength interval is 2nm, the scanning speed is 1200nm/min, and deionized ultrapure water is used as a blank reference to eliminate the Raman scattering influence of the fluorescence spectrum.
5. The method for identifying and accurately tracing environmental pollution events in ocean and open water areas according to claim 1, wherein the parallel factor analysis model in the step 4 specifically comprises the following steps:
(1) the fluorescence spectrum data obtained by measurement form an I multiplied by J multiplied by K matrix, the parallel factor model analysis is carried out on the three-dimensional data matrix by adopting an N-way and DOMFluor tool box in Matlab 2014a software, the parallel factor model analysis is decomposed into a score matrix A, load matrices B and C by adopting an alternating least square method, and the decomposition model is expressed as:
Figure FDA0003629435320000031
wherein I is the number of samples, and J and K are the numbers of emission wavelengths and excitation wavelengths of the samples respectively; x is a radical of a fluorine atomijkThe fluorescence intensity value of the ith sample at the position with the emission wavelength of j and the excitation wavelength of k; n is the number of factors; a isin,bjn,cknRespectively representing elements in the load matrixes A, B and C, and respectively representing component concentration, emission spectrum and excitation spectrum information; e.g. of the typeijkIs a constituent element of a residual matrix E (I × J × K);
(2) setting a plurality of N values, and constructing parallel factor models with different factor quantities;
(3) setting initial values of B and C, wherein the dimension of B is J multiplied by N, the dimension of C is K multiplied by N, and solving A according to the formula (2) and the formula (3);
Figure DEST_PATH_FDA0002972490570000022
A＝XZT(ZZT)-1 (3)
wherein z isnIs a column vector; bnThe column vector of the nth factor is represented in B; c. C nThe column vector of the nth factor is represented in C;
Figure FDA0003629435320000034
to solve for the tensor product; x is the expansion of a three-dimensional matrix, and the dimension of the matrix is I multiplied by JK; z is a matrix formed by column vectors Zn, and the dimension of the matrix is NxJK;
(4) based on the obtained estimated value of A and the initial value of C, estimating a matrix B by the same method, estimating a matrix C by the estimated values of A and B, and performing successive iteration circulation until convergence;
(5) when the residual error E is minimum and the consistency of the kernel is highest, the parallel factor analysis model of the N value is an optimal model;
(6) determining the fluorescence characteristics of each component according to the fluorescence peak position of each component analyzed by the parallel factor analysis model;
(7) and characterizing the distribution of each component in the sampling region by the relative proportion and the fluorescence intensity of each fluorescence component of the obtained sample component corresponding to the maximum fluorescence intensity, and performing water pollution homology analysis according to component similarity and color display degree.
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