CN116297936A - Method, system, device and medium for tracing pollutant - Google Patents
Method, system, device and medium for tracing pollutant Download PDFInfo
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Abstract
The invention discloses a method, a system, a device and a medium for tracing a pollutant. According to the tracing method, a first water sample at a river section is obtained and detected, and a water quality fingerprint spectrum at the river section is constructed according to a detection result of the first water sample, wherein the water quality fingerprint spectrum comprises pollutant information at the river section; determining suspicious pollution sources at the river cross section according to industrial data information in the river flow field; acquiring and detecting a second water sample of the suspicious pollution source, and obtaining characteristic pollutant information of the suspicious pollution source according to a detection result of the second water sample; and analyzing the water quality fingerprint spectrum and the characteristic pollutant information through the pollution source identification model, and determining a tracing result. The tracing method can realize the identification and tracing of multi-component complex pollutants, has multiple types and accurate types of the identified and traced pollutants, and also improves the pertinence of the tracing of the pollutants and the accuracy of tracing results. The invention can be widely applied to the technical field of water environment.
Description
Technical Field
The invention relates to the technical field of water environment, in particular to a method, a system, a device and a medium for tracing a pollutant.
Background
In recent years, the amount of wastewater discharged to rivers by key pollution discharge units such as papermaking, chemical industry, printing and dyeing is increased year by year, and certain pollution is caused to the water body environment in the river flow field, wherein the pollution problem of organic pollutants in industrial wastewater is particularly remarkable, and a great threat is caused to the water environment in the river basin.
At present, the water quality detection of river basins is mainly carried out by conventional detection items such as COD, ammonia nitrogen, heavy metals and the like, but the detection items can only determine whether the water environment is polluted by wastewater, and the detection items lack organic pollutant detection indexes, so that the pollution condition of the water quality can not be accurately determined, and the identification and tracing work of organic pollution sources in the water quality can not be well realized. In addition, in water quality detection, although the existing detection technology aiming at organic pollutants exists, due to the fact that the components of the organic pollutants are complex, concentration differences in detection are large, and the like, the existing detection technology only can give out a plurality of large emission sources with large receptor contribution, identification and tracing of the emission sources beyond the large emission sources cannot be achieved, identification and tracing of specific emission sources cannot be achieved, and the detection technology is not strong in pertinence and not high in accuracy.
Accordingly, there is a need for solving and optimizing the problems associated with the prior art.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the related art to a certain extent.
Therefore, an object of the embodiments of the present invention is to provide a tracing method for a pollutant, which not only can identify and trace a multi-component complex pollutant, but also can improve the pertinence of tracing the pollutant and the accuracy of tracing results, wherein the type of the identified and traced pollutant is multiple.
It is another object of an embodiment of the present application to provide a system for tracing a contaminant.
In order to achieve the technical purpose, the technical scheme adopted by the embodiment of the application comprises the following steps:
in a first aspect, an embodiment of the present application provides a method for tracing a contaminant, including:
acquiring and detecting a first water sample at a river cross section, and constructing a water quality fingerprint spectrum at the river cross section according to a detection result of the first water sample, wherein the water quality fingerprint spectrum comprises pollutant information at the river cross section;
determining a suspected pollution source at the river section according to industrial data information in the river flow field;
acquiring and detecting a second water sample of the suspicious pollution source, and obtaining characteristic pollutant information of the suspicious pollution source according to a detection result of the second water sample;
Analyzing the water quality fingerprint spectrum and the characteristic pollutant information through a pollution source identification model, and determining a tracing result, wherein the tracing result comprises an actual pollution source at the river section.
In addition, according to the tracing method of the above embodiment of the present application, the following additional technical features may be further provided:
further, in an embodiment of the present application, the tracing method further includes: verifying the tracing result;
the verifying the tracing result comprises the following steps:
analyzing the characteristic pollutant information by a quantitative analysis method to obtain analysis results of all characteristic pollutants in the characteristic pollutant information;
performing inversion of pollutant concentration and inversion of pollutant types on pollutants in the first water sample to obtain an analysis result of inversion pollutants;
and verifying the tracing result according to the analysis result of the inversion pollutant and the analysis result of each characteristic pollutant.
Further, in one embodiment of the present application, the acquiring and detecting the first water sample at the river cross section, and constructing the water quality fingerprint spectrum at the river cross section includes:
acquiring a first water sample at the river section, and sequentially carrying out solid phase extraction and concentration treatment on the first water sample;
Detecting the first water sample through a non-targeted semi-quantitative analysis technology to obtain pollutant information at the river section, wherein the pollutant information comprises a pollutant name, a peak area response value, a matching factor, a chemical formula and retention time;
and constructing the water quality fingerprint spectrum according to the pollutant information.
Further, in one embodiment of the present application, the detecting the first water sample by a non-targeted semi-quantitative analysis technology, to obtain the pollutant information at the river section, includes:
detecting the first water sample by a non-targeted semi-quantitative analysis technology to obtain first pollutant information, wherein the first pollutant information is used for representing information of all pollutants in the first water sample;
and processing the first pollutant information according to a reservation condition preset by a user to obtain the pollutant information, wherein the reservation condition is at least one of the matching factor being larger than a first threshold, the peak area response value being larger than a second threshold or the peak area response value being larger than or equal to a third threshold, and the third threshold is the peak area response value of the blank data of 3 times.
Further, in one embodiment of the present application, the determining the suspected pollution source at the river section according to the industrial data information in the river flow field includes:
acquiring industrial data information of enterprises in the river flow field, wherein the industrial data information comprises the industrial field, the geographic position, the wastewater discharge amount, the chemical oxygen demand, whether discharged wastewater enters a non-centralized sewage treatment plant, whether discharged wastewater enters an industrial wastewater centralized treatment plant, the production process, raw and auxiliary materials, the final product and the intermediate product;
and carrying out statistical analysis according to the industrial data information to obtain enterprises which are listed as suspicious pollution sources at the river section.
Further, in one embodiment of the present application, the obtaining and detecting the second water sample of the suspected pollution source, obtaining the characteristic pollutant information of the suspected pollution source, includes:
obtaining a second water sample of the suspected pollution source, and sequentially carrying out solid phase extraction and concentration treatment on the second water sample;
detecting the second water sample through a non-targeted semi-quantitative analysis technology to obtain second pollutant information of the suspicious pollution source, wherein the second pollutant information is used for representing information of all pollutants in the second water sample;
Analyzing and processing the second pollutant information according to the industrial data information and the water quality fingerprint spectrum to obtain third pollutant information, wherein the third pollutant information is used for representing all characteristic pollutants emitted by the suspected pollution sources determined by the industrial data information and the water quality fingerprint spectrum;
performing feature calculation on the second pollutant information through machine-learned feature engineering to obtain fourth pollutant information, wherein the fourth pollutant information is used for representing all feature pollutants emitted by the suspected pollution sources determined by the feature engineering;
and combining the third pollutant information and the fourth pollutant information to obtain the characteristic pollutant information of the suspicious pollution source.
Further, in an embodiment of the present application, the performing feature calculation on the second contaminant information through feature engineering of machine learning to obtain fourth contaminant information includes:
classifying and normalizing each second pollutant in the second pollutant information, wherein the second pollutant is one pollutant represented by the second pollutant information;
Calculating the feature importance of each second pollutant after the classification and normalization treatment through a machine learning model, wherein the feature importance is used for representing the influence degree of the second pollutant on a target variable;
and determining a second pollutant with the highest characteristic importance score as the fourth pollutant information, or determining a plurality of second pollutants with higher characteristic importance scores as the fourth pollutant information.
In a second aspect, embodiments of the present application provide a contaminant tracing system, including:
the first acquisition module is used for acquiring and detecting a first water sample at a river cross section and constructing a water quality fingerprint spectrum at the river cross section, wherein the water quality fingerprint spectrum comprises pollutant information at the river cross section;
the first determining module is used for determining suspected pollution sources at the river cross section according to industrial data information in the river flow field;
the second acquisition module is used for acquiring and detecting a second water sample of the suspicious pollution source to obtain characteristic pollutant information of the suspicious pollution source;
and the second determining module is used for analyzing the water quality fingerprint spectrum and the characteristic pollutant information of the suspicious pollution source through a pollution source identification model and determining a tracing result, wherein the tracing result comprises the actual pollution source at the river section.
In a third aspect, an embodiment of the present application further provides a tracing device for a contaminant, including:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement a method of tracing a contaminant of the first aspect described above.
In a fourth aspect, embodiments of the present application further provide a computer readable storage medium, in which a processor executable program is stored, where the processor executable program is configured to implement a method for tracing a contaminant according to the first aspect, when executed by the processor.
The advantages and benefits of the present application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the present application.
According to the tracing method, system, device and medium for the pollutants, disclosed by the embodiment of the application, a first water sample at a river section is obtained and detected, and a water quality fingerprint spectrum at the river section is constructed according to the detection result of the first water sample; determining a suspected pollution source at the river section according to industrial data information in the river flow field; acquiring and detecting a second water sample of the suspicious pollution source, and obtaining characteristic pollutant information of the suspicious pollution source according to a detection result of the second water sample; and analyzing the water quality fingerprint spectrum and the characteristic pollutant information through a pollution source identification model, and determining a tracing result. The tracing method can realize the identification and tracing of multi-component complex pollutants, has multiple types and accurate types of the identified and traced pollutants, and also improves the pertinence of the tracing of the pollutants and the accuracy of tracing results.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description is made with reference to the accompanying drawings of the embodiments of the present application or the related technical solutions in the prior art, and it should be understood that, in the following description, the drawings are only for convenience and clarity of expressing some of the embodiments in the technical solutions of the present application, and other drawings may be obtained according to the drawings without the need of inventive labor for those skilled in the art.
Fig. 1 is a schematic flow chart of a method for tracing a contaminant according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a contaminant tracing system according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a contaminant tracing device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application. The step numbers in the following embodiments are set for convenience of illustration only, and the order between the steps is not limited in any way, and the execution order of the steps in the embodiments may be adaptively adjusted according to the understanding of those skilled in the art.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the present application.
Before describing embodiments of the present application in further detail, some of the terms and expressions designed in the embodiments of the present application will be described, with the terms and expressions referred to in the embodiments of the present application being applicable to the following explanations.
Fingerprint spectrum of water quality: the traditional water quality fingerprint spectrum refers to a water quality fingerprint spectrum formed by fluorescence spectrums of organic matters with different components in a water body according to different components of the organic matters in the water body, wherein the fluorescence spectrums emitted by the organic matters in the water body are also different; in this application, the water quality fingerprint spectrum refers to a spectrum composed of contaminant types, peak area response values, industrial types, industrial use classifications, and the like.
Chemical Oxygen Demand (COD): refers to the amount of oxidizing agent consumed when treating a water sample with a strong oxidizing agent under certain conditions.
At present, the water quality detection of river basins is mainly carried out by conventional detection items such as COD, ammonia nitrogen, heavy metals and the like, but the detection items can only determine whether the water environment is polluted by wastewater, and the detection items lack organic pollutant detection indexes, so that the pollution condition of the water quality can not be accurately determined, and the identification and tracing work of organic pollution sources in the water quality can not be well realized. In addition, in water quality detection, although the existing detection technology aiming at organic pollutants exists, due to the fact that the components of the organic pollutants are complex, concentration differences in detection are large, and the like, the existing detection technology only can give out a plurality of large emission sources with large receptor contribution, identification and tracing of the emission sources beyond the large emission sources cannot be achieved, identification and tracing of specific emission sources cannot be achieved, and the detection technology is not strong in pertinence and not high in accuracy.
In view of the above, the embodiment of the invention provides a tracing method for pollutants, which not only can realize the identification and tracing of multi-component complex pollutants, but also can improve the pertinence of the tracing of the pollutants and the accuracy of tracing results, wherein the identification and tracing of the pollutants are multiple in types and precise in types.
Referring to fig. 1, in an embodiment of the present application, a method for tracing a contaminant includes:
step 110, acquiring and detecting a first water sample at a river cross section, and constructing a water quality fingerprint spectrum at the river cross section according to a detection result of the first water sample, wherein the water quality fingerprint spectrum comprises pollutant information at the river cross section;
in the step, the river section refers to a section of a river cut perpendicular to the ground, and the river section needs to fully consider factors such as a river water intake, a dead water and return water area, river topography and the like. The sampling mode of the first water sample can be instantaneous sampling or mixed sampling, and the mixed sampling can be divided into three sampling modes of time integration, depth integration and area integration; also, prior to detection of the first water sample, the first water sample needs to be filtered to remove suspended matter, sediment, algae and other microorganisms in the first water sample.
It can be understood that the step 110 of obtaining and detecting a first water sample at the river cross section, and constructing a water quality fingerprint spectrum at the river cross section according to the detection result of the first water sample, includes the following steps:
step 111, obtaining a first water sample at the river section, and sequentially carrying out solid phase extraction and concentration treatment on the first water sample;
step 112, detecting the first water sample through a non-targeted semi-quantitative analysis technology to obtain pollutant information at the river section, wherein the pollutant information comprises a pollutant name, a peak area response value, a matching factor, a chemical formula and retention time;
and 113, constructing the water quality fingerprint spectrum according to the pollutant information.
It can be understood that after the first water sample is filtered, the solid phase extraction and concentration treatment comprises liquid phase extraction and liquid phase chromatographic hormone, and the separation, purification and enrichment of the first water sample are realized by adopting the modes of selective adsorption and selective elution, so that the influence of other impurities in the first water sample can be reduced, and the detection sensitivity of the organic pollutants can be improved.
Specifically, after the first water sample is subjected to filtration treatment and solid phase extraction concentration treatment, complex pollutant information in the first water sample can be rapidly, comprehensively and conveniently detected through a non-targeted semi-quantitative analysis technology, the non-targeted quantitative analysis technology does not have detection bias, and in a qualitative aspect, no-difference identification can be realized on organic pollutants in the water body, so that peak table information of each pollutant in the first water sample is obtained.
It may be understood that in step 113, the step of constructing a water quality fingerprint spectrum according to the pollutant information may be performed in a Chemical Book database and a Pubchem database to obtain classification information and degradation information corresponding to each organic pollutant in the pollutant information, where the specific classification may be classification according to industrial fields, classification according to specific applications, source classification, and the like, for example, classification according to source may be classified into urban sources, agricultural sources, industrial sources, and the like; the classification according to the industrial field can be divided into food field, printing and dyeing field, daily chemical industry field, pharmaceutical field and the like. In the construction of the water quality fingerprint spectrum, the water quality fingerprint spectrum comprises pollutant information and specific classification information of each organic pollutant in the pollutant information, and a key theory and traceable data basis can be provided for subsequent pollutant traceability.
It will be appreciated that the step 112 of detecting the first water sample by a non-targeted semi-quantitative analysis technique to obtain contaminant information at the river cross section includes the steps of:
step 1121, detecting the first water sample by a non-targeted semi-quantitative analysis technology to obtain first pollutant information, wherein the first pollutant information is used for representing information of all pollutants in the first water sample;
And 1122, processing the first pollutant information according to a preset reservation condition of a user to obtain the pollutant information, wherein the reservation condition is at least one of that the matching factor is greater than a first threshold, the peak area response value is greater than a second threshold, or the peak area response value is greater than or equal to a third threshold, and the third threshold is a peak area response value of 3 times blank data.
It can be understood that the first pollutant information comprises peak table information of all pollutants in the first water sample, certain interference impurities still exist after the first water sample is filtered and subjected to solid phase extraction concentration treatment, the influence of the interference impurities on the first pollutant information can be effectively removed according to the retention conditions, and the information of complex and various organic pollutants in the first water sample can be retained.
Specifically, in the embodiment of the application, the detection analysis can be performed on the first water sample by using an ultra-high resolution quadrupole combined electrostatic field track trap liquid chromatography-mass spectrometer, the organic pollutant information with the matching factor larger than 60, the peak area response value larger than 10000 and the peak area response value larger than or equal to 3 times of the peak area response value of blank data in the first pollutant information is reserved, and after the organic pollutant information which does not meet the reservation conditions is removed, the pollutant information containing all the organic pollutant information in the first water sample can be obtained. It may be further understood that the peak area response value of the blank data refers to a peak area response value of a blank sample without organic pollutants, the specific settings of the first threshold, the second threshold and the third threshold may be set according to actual requirements, and the retention conditions may also be set according to actual requirements, which are only illustrative and not limiting in any way.
Step 120, determining suspicious pollution sources at the river cross section according to industrial data information in the river flow field;
it is understood that the step 120 of determining a suspected pollution source at the river cross section according to the industrial data information in the river flow field includes the steps of:
step 121, acquiring industrial data information of enterprises in the river flow field, wherein the industrial data information comprises the industrial field, geographical position, wastewater discharge amount, chemical oxygen demand, whether discharged wastewater enters a non-centralized sewage treatment plant, whether discharged wastewater enters an industrial wastewater centralized treatment plant, a production process, raw and auxiliary materials, a final product and an intermediate product;
and 122, carrying out statistical analysis according to the industrial data information to obtain enterprises which are listed as suspicious pollution sources at the river sections.
It will be appreciated that in step 120, the suspected pollution sources at the river cross section may be initially determined according to the industrial data information in the river flow area and the water quality fingerprint spectrum, specifically, the suspected pollution sources corresponding to various organic pollutants in the pollutant information may be initially determined according to the organic pollutants in the water quality fingerprint spectrum and the corresponding classifications thereof, and the suspected pollution sources may be one or more specific enterprises.
Specifically, in this embodiment of the present application, according to the industrial field, the geographical location, whether the discharged wastewater enters the non-centralized sewage treatment plant, whether the discharged wastewater enters the industrial wastewater centralized treatment plant, and the preliminary screening is performed on each organic matter in the water quality fingerprint spectrum, then the wastewater discharge and the chemical oxygen demand of the preliminarily screened enterprises are counted, the enterprises with higher wastewater discharge and/or chemical oxygen demand are preferentially listed as the preliminary suspicious pollution sources, and then the production process, the raw auxiliary materials, the final products and the intermediate products listed as the preliminary suspicious pollution source enterprises are screened and analyzed to determine whether the corresponding organic pollutants exist in the water quality fingerprint spectrum, for example, whether the corresponding organic pollutants exist in the water quality fingerprint spectrum, and the enterprises which are identified as the preliminary suspicious pollution sources are indeed suspicious pollution sources. It will also be appreciated that after the statistical analysis in step 122, each organic contaminant in the water fingerprint spectrum will have a corresponding enterprise that is listed as a suspected source of contamination.
130, acquiring and detecting a second water sample of the suspicious pollution source, and obtaining characteristic pollutant information of the suspicious pollution source according to a detection result of the second water sample;
It may be understood that step 130, obtaining and detecting a second water sample of the suspected pollution source, and obtaining the characteristic pollutant information of the suspected pollution source according to the detection result of the second water sample, includes the following steps:
step 131, obtaining a second water sample of the suspected pollution source, and sequentially carrying out solid-phase extraction concentration treatment on the second water sample;
step 132, detecting the second water sample by a non-targeted semi-quantitative analysis technology to obtain second pollutant information of the suspicious pollution source, wherein the second pollutant information is used for representing information of all pollutants in the second water sample;
step 133, analyzing and processing the second pollutant information according to the industrial data information and the water quality fingerprint spectrum to obtain third pollutant information, wherein the third pollutant information is used for representing all characteristic pollutants emitted by the suspected pollution sources determined by the industrial data information and the water quality fingerprint spectrum;
step 134, performing feature calculation on the second pollutant information through a feature project of machine learning to obtain fourth pollutant information, wherein the fourth pollutant information is used for representing all feature pollutants emitted by the suspected pollution sources determined by the feature project;
And step 135, merging the third pollutant information and the fourth pollutant information to obtain the characteristic pollutant information of the suspected pollution source.
It can be appreciated that the second water sample can be obtained from the drain of the suspected pollution source, and the second water sample also needs to be subjected to filtration treatment, solid phase extraction concentration treatment, and detection of the second water sample by the non-targeted semi-quantitative analysis technology, which are similar to the related content of the first water sample, and the redundant description of the present application is omitted.
It will be appreciated that since the constructed water quality fingerprint spectrum includes contaminant types, peak area response values, industry types, industry usage classifications, etc., the water quality fingerprint spectrum may indicate that certain specific organic contaminants are only potentially present in a particular industry or that certain specific organic contaminants are primarily present in that industry, it may be judged that certain specific organic contaminants are identified as characteristic contaminants in that industry; in step 132, the second pollutant information is organic pollutant information actually emitted by the suspected pollutant source, and in step 133, the third pollutant information is characteristic pollutant emitted by the suspected pollutant source determined after the second pollutant information is analyzed by the water quality fingerprint spectrum at the river cross section and the industrial data information.
It can be understood that, because there are often multiple suspected pollution sources in the river basin, the distances between the suspected pollution sources and the river cross section are different, the organic pollutant components discharged by the same suspected pollution source are different, the concentrations of the organic pollutants in the sewage discharged by different suspected pollution sources are different, and multiple organic pollutants discharged by different suspected pollution sources may generate a certain chemical reaction or degradation reaction and other complex reasons in the river basin, the second pollutant information is directly used as the input of the final traceability result of the suspected pollution source at the river cross section, the pertinence is not strong, the accuracy is not high, so that the feature calculation needs to be performed on the second pollutant information, so as to improve the accuracy and pertinence of the traceability result at the river cross section.
It can be understood that after the third pollutant information and the fourth pollutant information are combined, the obtained characteristic pollutant information of the suspicious pollutant source is various in variety and accurate in type, and the pertinence of pollutant tracing and the accuracy of tracing results can be improved.
It may be appreciated that step 134, performing feature calculation on the second contaminant information through feature engineering of machine learning to obtain fourth contaminant information, includes the following steps:
Step 1341, classifying and normalizing each second contaminant in the second contaminant information, where the second contaminant is one contaminant represented by the second contaminant information;
step 1342, calculating the feature importance of each second pollutant after the classification and normalization treatment through a machine learning model, wherein the feature importance is used for representing the influence degree of the second pollutant on a target variable;
step 1343, determining a second contaminant with the highest feature importance score as the fourth contaminant information, or determining a plurality of second contaminants with higher feature importance scores as the fourth contaminant information.
It will be appreciated that in the embodiment of the present application, the classification of the second contaminant information may be classified according to the foregoing industrial data information, and specifically, each second contaminant distribution in the second contaminant information may be classified according to the industrial type, and normalized so that each second contaminant has the same metric. And then inputting the classified and normalized third pollutants into a machine learning model, obtaining feature importance scores of the second pollutants according to the change conditions of performance indexes (such as accuracy, F1 values and the like) in the machine learning model, and sequencing the feature importance scores of all the second pollutants to determine that the second pollutant with the highest feature importance score is the fourth pollutant information of the suspicious pollutant source or determine that a plurality of second pollutants with higher feature importance scores are the fourth pollutant information of the suspicious pollutant source. It may be further understood that the target variable may be set according to an actual requirement, specifically, the target variable may be an industrial type of the second pollutant, or may be a performance index in the machine learning model, and specifically may be at least one of an accuracy rate, a recall rate, and an accuracy rate in the performance index.
And 140, analyzing the water quality fingerprint spectrum and the characteristic pollutant information through a pollution source identification model, and determining a tracing result, wherein the tracing result comprises an actual pollution source at the river section.
It can be appreciated that the feature contaminants and the feature importance scores of the feature contaminants can help training the pollution source identification model to a certain extent, and can avoid the occurrence of the overfitting phenomenon. In addition, in the analysis process of the pollution source identification model on the water quality fingerprint spectrum and the characteristic pollutant information, the characteristic importance can also enhance the interpretability of the pollution source identification model.
It can be understood that the pollution source identification model determines the tracing result by measuring the difference between the water quality fingerprint spectrum at the river section and the characteristic pollutant information of the suspicious pollution source in the direction by applying an included angle cosine formula, and visualizes the tracing result through a clustering algorithm. In particular, the characteristic pollutant information of different suspected pollution sources can form different profiles on the mass spectrum, and the mass spectrum profile of the characteristic pollutant information at the river section is similar to the mass spectrum profile of the suspected pollution sources although the pollutant discharged by the suspected pollution sources can be degraded, diluted and the like in the migration process of the water body.
The following is an included angle cosine formula provided in the embodiment of the present application, which is:
wherein θ refers to the angle between the response line segment of the mass spectrum profile of the characteristic contaminant information at the suspected contaminant source and the response line segment of the mass spectrum profile at the river section; k refers to a dimension in the characteristic pollution source information, wherein the dimension is used for representing the types of organic pollutants contained in the characteristic pollution source information; n refers to the largest dimension of the characteristic pollution source information; x is X 1k A characteristic contaminant in the characteristic contaminant information that characterizes a suspected contaminant source; x is X 2k Characteristic contaminant information characterizing a suspected source of contamination flows through a corresponding characteristic contaminant at a river cross-section.
It will be appreciated that with an included angle cosine cos (θ) ranging from-1 to 1, a larger value of cos (θ) indicates that the mass spectrum profile of the characteristic contaminant information at the river cross-section is more similar to the mass spectrum profile at the suspected contaminant source, and a smaller value of cos (θ) indicates that the mass spectrum profile of the characteristic contaminant information at the river cross-section is more dissimilar to the mass spectrum profile at the suspected contaminant source. When cos (θ) = 1, the mass spectrum profile of the characteristic pollutant information at the river cross section is completely similar to the mass spectrum profile at the suspected pollution source, and when cos (θ) = -1, the mass spectrum profile of the characteristic pollutant information at the river cross section is completely dissimilar to the mass spectrum profile at the suspected pollution source.
It can be understood that the included angle cosine cos (theta) can judge the directivity of the overall outline of the characteristic pollutant information, can better identify and trace the source of the multi-component complex pollutant, and avoids the tracing interference caused by degradation, dilution and other processes of the pollutant discharged by the suspicious pollution source in the migration process of the water body, and has strong tracing pertinence and high accuracy.
In some embodiments, the tracing method further comprises: step 150, verifying the tracing result;
step 150, verifying the tracing result, including:
step 151, analyzing the characteristic pollutant information by a quantitative analysis method to obtain analysis results of all characteristic pollutants in the characteristic pollutant information;
step 152, inverting the concentration of the pollutants in the first water sample and inverting the types of the pollutants to obtain an analysis result of inverted pollutants;
and step 153, verifying the tracing result according to the analysis result of the inversion pollutant and the analysis result of each characteristic pollutant.
It can be understood that the tracing result includes an actual pollution source at the river section, in the embodiment of the application, quantitative analysis can be performed on each characteristic pollutant by using an ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometer to obtain an analysis result of each characteristic pollutant, then concentration inversion and type inversion are performed on the pollutant in the first water sample to obtain an analysis result of inversion pollutant, and the analysis result of inversion pollutant is compared with the analysis result of each characteristic pollutant, if the comparison results are equal or similar, the tracing result can be considered to be correct.
Specifically, the concentration inversion formula may be:
c＝c 0 -kt
wherein c is the actual pollution of the pollutant with a certain characteristicInversion concentration of characteristic contaminants at the dye source, c 0 K is a reaction constant, and t is a distance between an actual pollution source and a river section or a time required for the characteristic pollutant discharged by the actual pollution source to reach the river section, wherein the concentration of the characteristic pollutant at the river section corresponds to the characteristic pollutant.
It will be appreciated that the concentration analysis results of the inverted contaminants can be obtained from the concentration inversion formula. The inversion of the pollutant types can be to reversely push the pollutants before degradation corresponding to the pollutants at the river cross section according to the pollutants at the river cross section and the degradation and other processes occurring in the water migration process, so as to obtain the analysis result of the inverted pollutant types. And then combining the concentration analysis result and the type analysis result, comparing and analyzing with the analysis result of each characteristic pollutant in the actual pollution source, and verifying the traceability result.
A detailed description of a contaminant tracing system according to an embodiment of the present application is provided below with reference to the accompanying drawings.
Referring to fig. 2, a contaminant tracing system according to an embodiment of the present application includes:
a first acquisition module 101, configured to acquire and detect a first water sample at a river cross section, and construct a water quality fingerprint spectrum at the river cross section, where the water quality fingerprint spectrum includes pollutant information at the river cross section;
A first determining module 102, configured to determine a suspected pollution source at a river section according to industrial data information in a river flow field;
a second obtaining module 103, configured to obtain and detect a second water sample of the suspected pollution source, so as to obtain characteristic pollutant information of the suspected pollution source;
and the second determining module 104 is configured to analyze the water quality fingerprint spectrum and the characteristic pollutant information of the suspected pollution source through a pollution source identification model, and determine a tracing result, where the tracing result includes an actual pollution source at the river section.
It can be understood that the content in the above method embodiment is applicable to the system embodiment, and the functions specifically implemented by the system embodiment are the same as those of the above method embodiment, and the achieved beneficial effects are the same as those of the above method embodiment.
Referring to fig. 3, an embodiment of the present application further provides a tracing device for a contaminant, including:
at least one processor 201;
at least one memory 202 for storing at least one program;
the at least one program, when executed by the at least one processor 201, causes the at least one processor 201 to implement one of the contaminant tracing method embodiments described above.
Similarly, it can be understood that the content in the above method embodiment is applicable to the embodiment of the present apparatus, and the functions specifically implemented by the embodiment of the present apparatus are the same as those of the embodiment of the foregoing method, and the achieved beneficial effects are the same as those achieved by the embodiment of the foregoing method.
The embodiment of the present application further provides a computer readable storage medium, in which a program executable by the processor 201 is stored, where the program executable by the processor 201 is configured to implement the above-mentioned embodiment of a method for tracing a contaminant when executed by the processor 201.
Similarly, the content in the above method embodiment is applicable to the present computer-readable storage medium embodiment, and the functions specifically implemented by the present computer-readable storage medium embodiment are the same as those of the above method embodiment, and the beneficial effects achieved by the above method embodiment are the same as those achieved by the above method embodiment.
In some alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of this application are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed, and in which sub-operations described as part of a larger operation are performed independently.
Furthermore, while the present application is described in the context of functional modules, it should be appreciated that, unless otherwise indicated, one or more of the functions and/or features may be integrated in a single physical device and/or software module or one or more of the functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary to an understanding of the present application. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be apparent to those skilled in the art from consideration of their attributes, functions and internal relationships. Thus, those of ordinary skill in the art will be able to implement the present application as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative and are not intended to be limiting upon the scope of the application, which is to be defined by the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium may even be paper or other suitable medium upon which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
In the foregoing description of the present specification, descriptions of the terms "one embodiment/example", "another embodiment/example", "certain embodiments/examples", and the like, are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the application, the scope of which is defined by the claims and their equivalents.
While the preferred embodiments of the present application have been described in detail, the present application is not limited to the embodiments, and various equivalent modifications and substitutions can be made by those skilled in the art without departing from the spirit of the present application, and these equivalent modifications and substitutions are intended to be included in the scope of the present application as defined in the appended claims.
Claims (10)
1. A method for tracing a contaminant, comprising:
acquiring and detecting a first water sample at a river cross section, and constructing a water quality fingerprint spectrum at the river cross section according to a detection result of the first water sample, wherein the water quality fingerprint spectrum comprises pollutant information at the river cross section;
determining a suspected pollution source at the river section according to industrial data information in the river flow field;
acquiring and detecting a second water sample of the suspicious pollution source, and obtaining characteristic pollutant information of the suspicious pollution source according to a detection result of the second water sample;
Analyzing the water quality fingerprint spectrum and the characteristic pollutant information through a pollution source identification model, and determining a tracing result, wherein the tracing result comprises an actual pollution source at the river section.
2. The method of claim 1, further comprising: verifying the tracing result;
the verifying the tracing result comprises the following steps:
analyzing the characteristic pollutant information by a quantitative analysis method to obtain analysis results of all characteristic pollutants in the characteristic pollutant information;
performing inversion of pollutant concentration and inversion of pollutant types on pollutants in the first water sample to obtain an analysis result of inversion pollutants;
and verifying the tracing result according to the analysis result of the inversion pollutant and the analysis result of each characteristic pollutant.
3. The method for tracing a contaminant according to claim 1, wherein said obtaining and detecting a first water sample at a river cross section, constructing a water quality fingerprint at said river cross section, comprises:
acquiring a first water sample at the river section, and sequentially carrying out solid phase extraction and concentration treatment on the first water sample;
Detecting the first water sample through a non-targeted semi-quantitative analysis technology to obtain pollutant information at the river section, wherein the pollutant information comprises a pollutant name, a peak area response value, a matching factor, a chemical formula and retention time;
and constructing the water quality fingerprint spectrum according to the pollutant information.
4. A method of tracing a contaminant according to claim 3, wherein said detecting said first water sample by a non-targeted semi-quantitative analysis technique to obtain contaminant information at said river cross section comprises:
detecting the first water sample by a non-targeted semi-quantitative analysis technology to obtain first pollutant information, wherein the first pollutant information is used for representing information of all pollutants in the first water sample;
and processing the first pollutant information according to a reservation condition preset by a user to obtain the pollutant information, wherein the reservation condition is at least one of the matching factor being larger than a first threshold, the peak area response value being larger than a second threshold or the peak area response value being larger than or equal to a third threshold, and the third threshold is the peak area response value of the blank data of 3 times.
5. The method of claim 1, wherein determining suspected pollution sources at the river cross section based on industrial data information within the river flow comprises:
acquiring industrial data information of enterprises in the river flow field, wherein the industrial data information comprises the industrial field, the geographic position, the wastewater discharge amount, the chemical oxygen demand, whether discharged wastewater enters a non-centralized sewage treatment plant, whether discharged wastewater enters an industrial wastewater centralized treatment plant, the production process, raw and auxiliary materials, the final product and the intermediate product;
and carrying out statistical analysis according to the industrial data information to obtain enterprises which are listed as suspicious pollution sources at the river section.
6. The method for tracing a contaminant according to claim 5, wherein said obtaining and detecting a second sample of water from said suspected contaminant source, obtaining information about a characteristic contaminant of said suspected contaminant source, comprises:
obtaining a second water sample of the suspected pollution source, and sequentially carrying out solid phase extraction and concentration treatment on the second water sample;
detecting the second water sample through a non-targeted semi-quantitative analysis technology to obtain second pollutant information of the suspicious pollution source, wherein the second pollutant information is used for representing information of all pollutants in the second water sample;
Analyzing and processing the second pollutant information according to the industrial data information and the water quality fingerprint spectrum to obtain third pollutant information, wherein the third pollutant information is used for representing all characteristic pollutants emitted by the suspected pollution sources determined by the industrial data information and the water quality fingerprint spectrum;
performing feature calculation on the second pollutant information through machine-learned feature engineering to obtain fourth pollutant information, wherein the fourth pollutant information is used for representing all feature pollutants emitted by the suspected pollution sources determined by the feature engineering;
and combining the third pollutant information and the fourth pollutant information to obtain the characteristic pollutant information of the suspicious pollution source.
7. The method for tracing a contaminant according to claim 6, wherein said performing feature computation on said second contaminant information by machine-learned feature engineering to obtain fourth contaminant information comprises:
classifying and normalizing each second pollutant in the second pollutant information, wherein the second pollutant is one pollutant represented by the second pollutant information;
Calculating the feature importance of each second pollutant after the classification and normalization treatment through a machine learning model, wherein the feature importance is used for representing the influence degree of the second pollutant on a target variable;
and determining a second pollutant with the highest characteristic importance score as the fourth pollutant information, or determining a plurality of second pollutants with higher characteristic importance scores as the fourth pollutant information.
8. A system for tracing a contaminant, comprising:
the first acquisition module is used for acquiring and detecting a first water sample at a river cross section and constructing a water quality fingerprint spectrum at the river cross section, wherein the water quality fingerprint spectrum comprises pollutant information at the river cross section;
the first determining module is used for determining suspected pollution sources at the river cross section according to industrial data information in the river flow field;
the second acquisition module is used for acquiring and detecting a second water sample of the suspicious pollution source to obtain characteristic pollutant information of the suspicious pollution source;
and the second determining module is used for analyzing the water quality fingerprint spectrum and the characteristic pollutant information of the suspicious pollution source through a pollution source identification model and determining a tracing result, wherein the tracing result comprises an actual pollution source at the river section.
9. A contaminant traceability device, comprising:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement the method of tracing of contaminants of any one of claims 1-7.
10. A computer readable storage medium, in which a processor executable program is stored, characterized in that the processor executable program is for implementing the method of tracing a contaminant according to any one of claims 1-7 when being executed by the processor.
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| CN117383768B (en) * | 2023-12-08 | 2024-03-12 | 中国林业科学研究院林产化学工业研究所 | Sewage circulation treatment control system and method |
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