A method for analyzing unknown pollution sources based on point source spectra and river water quality information

Abstract

The present invention relates to a method for analyzing unknown pollution sources based on point source spectra and river water quality information, and the steps are as follows: Step 1: In the target river section, use a water quality model to forward simulate and analyze the water pollution component spectra formed by known point source spectra in the target cross-section of the river section; Step 2: Substitute the water quality monitoring data of the target cross-section into the pollution source analysis algorithm to obtain the pollution sources and their component spectra of the target cross-section; Step 3: Compare the component spectra of each pollution source obtained in Step 2 with the component spectra of the point pollution source in the target cross-section obtained in Step 1 to find out the differences in pollution factors; Step 4: According to regional characteristics and prior knowledge of hydrochemistry, determine the sources of the differences in pollution factors, and summarize and name the unknown pollution sources; Step 5: Incorporate each water quality information into the local water quality information database. The present invention is based on point source spectra and river water quality data to obtain the spectra of unknown pollution sources, making it characterized by low cost, large amount of information, strong operability, high accuracy, etc.

Description

(1) Technical Field

[0001] The present invention relates to a method for analyzing unknown pollution sources based on point source spectra and river water quality information, belonging to the fields of ecological environment protection and water environment supervision, and is of great significance for water environment supervision and treatment, and the formulation of decision-making for water pollution emergencies. (2) Background Art

[0002] The industrial sewage, domestic sewage and agricultural non-point source pollution are directly discharged into surface runoff, resulting in a large amount of pollution of limited fresh water resources, triggering the problem of water quality-based water shortage. Activities such as industrial and agricultural development and urban expansion have also made the types and sources of pollutants in water bodies more complex, deepening the degree of water environment damage and increasing the difficulty of pollution control.

[0003] Therefore, it is particularly important to obtain unknown pollution information. Further establishing a database integrating water quality, point pollution sources and unknown pollution sources can effectively carry out pollution control according to the characteristics of each river section, and can also compare the water quality information of the receiving water body with the pollution source database to identify problems after a pollution accident. In theory, various species that can characterize water quality information can be used to construct the database, such as chromaticity, turbidity, pH value, conductivity, dissolved oxygen, chemical oxygen demand, biochemical oxygen demand, total nitrogen, total phosphorus, ammonia nitrogen, arsenic, fecal coliforms, characteristic pollutants, etc. The more indicators characterizing water quality, the more water quality information is included, which is more beneficial to the subsequent tracing work. The pollution information of point pollution sources that can directly collect samples is relatively easy to obtain, but the acquisition of information on unknown pollution is a major challenge and needs to be achieved through certain technical means. (3) Summary of the Invention

[0004] The present invention provides a method for obtaining unknown pollution information of river channels, which is based on known point source spectra and river water quality data to obtain unknown source spectra, having the characteristics of low cost, large amount of information, strong operability and high accuracy, and is of great significance for the subsequent establishment of a database, which is conducive to the long-term treatment of water pollution in this area.

[0005] The above technical object of the present invention is achieved by the following technical solutions:

[0006] A method for obtaining information on unknown pollution sources of river water quality based on point source spectra, characterized in that:

[0007] The acquisition of the unknown pollution information of the river channel depends on the point source pollution information and river water quality information of the river channels in this area. For the convenience of management and the subsequent development of water environment management work, a river water quality information database can be established.

[0008] The database includes a basic information database of river channel point pollution sources, a basic information database of unknown pollution sources, and a water quality database. The establishment of the basic information database of river channel point pollution sources requires on-site investigation of the river channel to obtain information such as the name of the river channel pollution source, pollution discharge volume and cycle, geographical location of the pollution discharge outlet, main products of the pollution source, etc. Wastewater samples near the pollution discharge outlet are collected and the pH value, turbidity, conductivity, dissolved oxygen, biochemical oxygen demand, total nitrogen, total phosphorus, ammonia nitrogen, copper, mercury, nickel, fluoride, and fecal coliform count of the water samples are detected using national standard methods, or characteristic pollutants are selectively detected according to the type of pollution source.

[0009] The method for establishing the basic information database of unknown pollution sources according to the present invention is characterized in that the method comprises the following steps:

[0010] 1) In the target river section, use a water quality model to forward simulate and analyze the water pollution component spectrum formed by the known point source spectra in the target section;

[0011] 2) Substitute the water quality monitoring data of the target section into the pollution source analysis algorithm to obtain the pollution sources and their component spectra of the target section;

[0012] 3) Compare the component spectra of each pollution source obtained in 2) with the component spectra of the point pollution sources in the target section obtained in 1) to find out the differences in pollution factors;

[0013] 4) According to regional characteristics and prior knowledge of hydrochemistry, determine the sources of the differences in pollution factors, and summarize and name the unknown pollution sources;

[0014] 5) Enter the information of the unknown pollution sources into the basic information database of unknown pollution sources.

[0015] The present invention has the following advantages and outstanding technical effects compared with the prior art:

[0016] (1) Use technical means rather than traditional instrument monitoring means to analyze the information of unknown pollution sources in the river channel, which has the advantages of ensuring the accuracy of the obtained information, small workload, low cost, and being conducive to large-scale promotion.

[0017] (2) In order to ensure the correctness of the comparison results between pollution source analysis and known pollution sources, considering that the pollutants discharged by each point source will change during the transmission process, a forward diffusion model is introduced. (IV) BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the method for obtaining information on unknown pollution sources in the river channel and establishing the subsequent water pollution database provided by the present invention.

[0019] Figure 2 It is a schematic diagram of the river channel generalization provided by the present invention. (V) SPECIFIC EMBODIMENTS

[0020] The method for obtaining information on unknown pollution sources in a river based on point source spectra and river water quality data provided by the present invention requires obtaining point source information of the river and river water quality data first. The river point pollution source information database includes the name of the pollution source, geographical location, main products, enterprise penalty records, contact person and legal representative; the water quality database includes the pH value, turbidity, conductivity, dissolved oxygen, biochemical oxygen demand, total nitrogen, total phosphorus, ammonia nitrogen, copper, mercury, nickel and fluoride of the water sample; the water quality data can also add pollutant indicators in the "National Comprehensive Sewage Discharge Standard (GB8978 - 1996)" and "National Surface Water Environment Quality Standard GB3838 - 2002" according to the actual situation; the unknown pollution source basic information database includes the name of the pollution source, geographical location range, and temporal characteristics.

[0021] The river point pollution source information database requires first conducting research on the sewage discharge outlets of enterprises around the river, as well as centralized domestic sewage and agricultural wastewater discharge outlets, and using a professional sampler to sample at the sampling points. At the same time, collecting basic information of the pollution sources such as geographical location and formation reasons can provide great convenience for the subsequent use of the database and can become an auxiliary tool for pollution source identification.

[0022] After collecting the water body samples, first use portable monitoring equipment to monitor the water quality at the sampling points, and the indicators include temperature, air pressure, pH value, dissolved oxygen content, conductivity; then use the ICP - MS method to extract metal elements in the sample, use the liquid - liquid extraction - GC - MS method to extract organic matter information, and use ion chromatography to extract anion information. The chemical fingerprints obtained from the sample detection are incorporated into the water quality database.

[0023] After establishing the basic information database of river point pollution sources and the water quality database of point pollution sources, then use technical means to obtain the basic information of unknown pollution sources and their water quality data.

[0024] For a river, the receptor for pollution source analysis is the target section of the receiving water body, the pollution sources are all pollution emissions upstream of the target section, and what is analyzed is the contribution of specific pollution sources rather than pollution source categories to the receptor. Considering the accuracy of unknown pollution source analysis in subsequent work, the present invention takes a certain upstream section at a certain distance from the target section as the initial input source, and all other pollution sources are all pollution emissions between this upstream section and the target section, that is, the point pollution sources obtained from the previous sampling.

[0025] For most inland rivers, the depth and width are very small relative to the length. The sewage discharged into the river can be evenly mixed in the cross-section within a very short distance. Therefore, the water quality calculation of the vast majority of rivers can be simplified to a one-dimensional water quality problem. The one-dimensional water quality model is applicable to general pollutants that conform to the one-dimensional kinetic degradation law, such as pollutants with single indicators such as cyanide, phenol, organic poisons, heavy metals, biochemical oxygen demand, and chemical oxygen demand. All substances in the water body are relatively conservative or all substances decay according to certain laws, ensuring that the diffusion rate of pollutants in the water body is proportional to the pollutant concentration. At the same time, it is assumed that the fluid is incompressible and homogeneous; the flow regime is one-dimensional; the riverbed slope is small and the longitudinal cross-section changes little; the hydrostatic pressure assumption is met.

[0026] The forward water quality simulation algorithm consists of the unsteady flow Saint-Venant equations and the advection-diffusion equation. Among them, the control equations describing the one-dimensional unsteady water flow movement law are the Saint-Venant equations, which are composed of the continuity equation of mass conservation and the momentum equation of energy conservation. The algorithm is as follows:

[0027]

[0028] In the formula: Q is the flow rate (m 3 / s); A is the cross-sectional area of the water passage (m 2 ); q is the lateral inflow (m 3 / s); x is the distance coordinate (m); t is the time coordinate (s); h is the water level (m); R is the hydraulic radius (m); C is the Chezy coefficient; α is the momentum correction coefficient; g is the acceleration due to gravity (m / s 2 ).

[0029] The change of substances in the water body is described by the one-dimensional advection-diffusion equation:

[0030]

[0031] In the formula: Q is the flow rate (m 3 / s); A is the cross-sectional area of the water passage (m 2 ); C is the substance concentration (mg / l); D is the longitudinal diffusion coefficient of the river channel (m 2 / s); t is the time coordinate (s); x is the distance coordinate (m); K is the linear attenuation coefficient of pollutants; q is the lateral inflow (m 3 / s); C2 is the pollutant source-sink concentration (mg / l).

[0032] Thus, the pollution component spectrum of the point source at the target section is obtained through the forward simulation algorithm.

[0033] The component spectrum of the river channel point pollution source at the sewage outlet is converted into the component spectrum at the receptor section through the above one-dimensional water quality model. Samples of the river channel receptor section are collected for water quality detection, and the positive matrix factorization model is used for source tracing analysis of the water quality data. The positive matrix factorization model has the characteristics of not requiring source spectra, non-negativity of the elements in the decomposition matrix, and can be optimized using the data standard deviation, etc.

[0034] The positive matrix factorization model assumes that X is an n×m matrix, where n is the number of samples and m is the number of chemical components. Then X can be decomposed into X = GF + E, where G is an n×p matrix, F is a p×m matrix, p is the number of main pollution sources, and E is the residue matrix, defined as:

[0035]

[0036] In the formula, x ij is the concentration of the i-th sample and the j-th variable; e ij is the concentration residue of the i-th sample and the j-th variable; g ik is the contribution rate of the i-th sample and the k-th source; f kj is the score of the k-th source and the j-th variable; p is the number of main sources.

[0037] The positive matrix factorization model is based on the weighted least squares method for constraint and iterative calculation, continuously decomposing the matrix to obtain the optimal solution, and the optimization goal is to minimize the objective function Q. The objective function Q is defined as:

[0038]

[0039] In the formula, u ij is the measurement uncertainty of the j-th pollutant in the i-th sample.

[0040] When it is necessary to calculate the uncertainty based on the equation, the calculation method of the uncertainty is as follows:

[0041]

[0042] In the formula, U nc represents the uncertainty, MDL is the method detection limit of this water quality parameter, and U rel is the relative standard deviation of the monitoring item.

[0043] The positive matrix factorization model will weight the uncertainty of each data point. In actual application, if there is a data missing problem, the linear interpolation method can be used to complete the missing values, and a relatively large uncertainty is assigned to these values to weaken the influence of these data on the final result. The model does not depend on the pollution source component spectrum, but requires researchers to analyze and distinguish the number and type of pollution sources.

[0044] After using the model to complete the determination of pollution sources in the target section, compare it with the component spectra obtained from the previous point pollution sources through forward simulation, find unknown pollution sources, name them, divide their location areas, and classify the basic information into the basic information database of unknown pollution sources and their water quality information into the water quality information database.

[0045] The following further elaborates on the present invention in conjunction with specific embodiments and their accompanying drawings. The embodiments are only used to illustrate the present invention rather than limit it.

[0046] There are multiple textile enterprises along a certain river course. The enterprises will generate a large amount of wastewater during the production process; there are also villages and farmlands along the river course, and there is a possibility of the discharge of domestic sewage and soil sources distributed over a large area. Taking this river course as an example, the method for obtaining unknown pollution sources in the river course and establishing a water environment database is described in detail.

[0047] Pollution source investigation: Investigate the sewage sources, geographical locations, main components of the sewage outlets along the river course. If enterprises are involved, record the enterprise contacts, legal persons, and enterprise penalty records at the same time.

[0048] Sample collection: Collect wastewater samples from the sewage outlets.

[0049] Analysis and testing of conventional water quality indicators: Immediately conduct tests on conventional water quality indicators such as pH value, conductivity, chemical oxygen demand, biochemical oxygen demand, total nitrogen, and total phosphorus after transporting the samples to the laboratory. The test results can find that there are certain differences in the wastewater quality of different sewage outlets, indicating that the conventional indicators have a certain auxiliary function for wastewater identification.

[0050] At the same time, generalize the river course based on the pollution source information obtained from the investigation. For the generalization example, see Figure 2 .

[0051] Conduct forward simulation on point pollution sources and upstream sections to obtain the water quality component spectra of each source at the target section after physical, chemical, and biological degradation. Monitor the water quality of the target section, and use the positive matrix factorization model to trace the water quality information of the water body to obtain the water quality information of other pollution sources except the known point sources.

[0052] According to the prior knowledge of hydrochemistry, divide and name the different pollution sources, determine the basic information of the unknown pollution sources, and at the same time, abnormal pollution sources can also be detected and included in the water quality information database, which is convenient to be used as the basis for enterprises' illegal illegal discharges.

[0053] Enter the basic information of pollution sources to build a basic information database of pollution sources. Considering that the basic information of point pollution sources is obtained from sample analysis and that of unknown pollution sources is obtained from model speculation, two information databases are divided for convenient subsequent regular adjustment. The water quality information of pollution sources obtained from sampling and analysis at each section and each sewage outlet and from model speculation is classified into the water quality database. Finally, the basic information database of river point pollution sources, the basic information database of unknown pollution sources, and the water quality database are merged to build a river pollution source database.

[0054] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications made without departing from the spirit and principle of the present invention shall be equivalent replacement methods and are all included in the protection scope of the present invention.

Claims

1. A method for analyzing unknown pollution sources based on point source spectra and river water quality information, characterized in that The method includes the following steps: Step 1: Conduct on-site investigations along the river course to determine the names of pollution sources, pollution discharge amounts and cycles, geographical locations of pollution discharge outlets, and main products of pollution sources. Collect wastewater samples near the discharge outlets and use national standard methods to detect the pH value, turbidity, conductivity, dissolved oxygen, biochemical oxygen demand, total nitrogen, total phosphorus, ammonia nitrogen, copper, mercury, nickel, fluoride, and fecal coliform count of the water samples, or selectively detect characteristic pollutants according to the types of pollution sources. Step 2: Use a water quality model to conduct forward simulation analysis of the variation laws of known point pollution sources, set degradation factors, and simulate the formation of the pollution source composition spectra at the target section after physical, chemical, and biological degradation and diffusion of each point source. The forward simulation algorithm of the water quality model consists of the unsteady flow Saint-Venant equations and the convection-diffusion equation. The algorithm is as follows: Where: Q is the flow rate (m 3 / s); A is the cross-sectional area of flow (m 2 ); q is the lateral inflow (m 3 / s); x is the distance coordinate (m); t is the time coordinate (s); h is the water level (m); R is the hydraulic radius (m); C is the Chezy coefficient; α is the momentum correction coefficient; g is the acceleration due to gravity (m / s 2 ); The change of substances in the water body is represented by the one-dimensional convection-diffusion equation: Where: Q is the flow rate (m 3 / s); A is the cross-sectional area of flow (m 2 ); q is the lateral inflow (m 3 / s); x is the distance coordinate (m); t is the time coordinate (s); C is the substance concentration (mg / l); D is the longitudinal dispersion coefficient of the river channel (m 2 / s); K is the linear attenuation coefficient of pollutants; C2 is the source-sink concentration of pollutants (mg / l); Step 3: Substitute the receptor composition spectrum of the target section into the pollution source analysis algorithm for calculation. Use the positive matrix factorization method to achieve the pollution source analysis of the target section. The method is as follows: where: x ij is the concentration of the i-th sample and the j-th variable; e ij is the concentration residual of the i-th sample and the j-th variable; g ik is the contribution rate of the i-th sample and the k-th source; f kj is the score of the k-th source and the j-th variable; p is the number of main sources; The positive matrix factorization algorithm is based on the weighted least squares method for limitation and iterative calculation, continuously decomposing the matrix to obtain the optimal result. The optimization goal is to minimize the objective function Q. The definition of the objective function Q is: where u ij is the measurement uncertainty of the j-th pollutant in the i-th sample; The calculation method of uncertainty is as follows: Where: U nc is the uncertainty; MDL is the method detection limit of the water quality parameter; U rel is the relative standard deviation of the monitoring item; Step 4: Compare the pollution analysis result composition spectrum in Step 3 with the forward simulation composition spectrum of the known point pollution sources in Step 2 to find out the differences in pollution factors. Step 5: According to the regional characteristics and prior knowledge of water chemistry, determine the sources of differences in pollution factors, summarize and name the unknown pollution sources, and record the names of pollution sources, occurrence time periods, upstream and downstream stake numbers and coordinates of the river section.

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