A pollution tracing method, system, device, medium and product based on high-resolution mass spectrometry data of natural organic matter and small-molecule organic pollutants

Abstract

The application discloses a pollution tracing method, system, device, medium and product based on high-resolution mass spectrometry data of natural organic matter and small-molecule organic pollutants, relates to the technical field of environmental monitoring, and determines the peak area pair of the mass spectrum peak corresponding to the reference substance of each sample based on the high-resolution mass spectrometry data of the natural organic matter and the small-molecule organic pollutants of each sample; corrects the peak area of each mass spectrum peak in the high-resolution mass spectrometry data of the small-molecule organic pollutants of each sample based on the peak area pair of the mass spectrum peak corresponding to the reference substance of each sample to obtain the corrected peak area of the corresponding mass spectrum peak; determines the characteristic vector of each sample based on the corrected peak area of each mass spectrum peak corresponding to the natural organic matter and the small-molecule organic pollutants of each sample; and determines the final value of the contribution proportion of each pollution source to each pollution receptor based on the characteristic vectors of the samples of all pollution sources and the characteristic vectors of the samples of all pollution receptors. The application improves the accuracy of pollution tracing.

Description

Technical Field

[0001] This application relates to the field of environmental monitoring technology, and in particular to a pollution source tracing method, system, device, medium and product based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants. Background Technology

[0002] With the rapid development of global industrialization and urbanization, the emission of organic pollutants has continued to increase and is widely present in various environmental media. Organic pollutants in water bodies can be divided into large-molecule natural organic matter and small-molecule organic pollutants. Natural organic matter mainly originates from organic matter produced or formed during the metabolic processes of plants, animals, and microorganisms; it is predominantly dissolved in water and has a complex structure. Natural organic matter generally does not have direct toxicity, but it can affect water quality and may increase the risk of subsequent pollution treatment. Small-molecule organic pollutants are mainly emitted by humans and have a wide range of sources, including industrial, agricultural, and domestic sources. In actual environmental media, natural organic matter and small-molecule organic pollutants coexist. A comprehensive analysis of the sources of these organic substances can provide a scientific basis for pollution control.

[0003] Conventional pollution source tracing methods typically rely on a single category of organic matter, either using only natural organic matter or only small-molecule organic pollutants. However, the source information carried by a single category of organic pollutants is often incomplete, failing to comprehensively reflect complex pollution sources and leading to low accuracy in source tracing results. Theoretically, simultaneously utilizing both natural organic matter and small-molecule organic pollutant data for source tracing can significantly improve information completeness and accuracy. However, the analysis of natural organic matter and small-molecule organic pollutants requires different high-resolution mass spectrometry methods, and the two types of data originate from different detection platforms, resulting in significant differences in data dimensions and abundance ranges, and a lack of unified measurement standards. Specifically, Fourier transform ion cyclotron resonance mass spectrometry is generally used to analyze natural organic matter, and the results often only include mass-to-charge ratio and peak area; while for small-molecule organic pollutants, ultra-high performance liquid chromatography-high resolution mass spectrometry is generally used, and the results include multiple information such as mass-to-charge ratio, retention time, secondary mass spectrometry, and peak area. Because the two types of mass spectrometry datasets are not directly comparable, they cannot be effectively integrated for joint source tracing, which has become a key bottleneck restricting the improvement of source tracing accuracy.

[0004] Therefore, how to utilize high-resolution mass spectrometry data from two different sources and with different dimensions—natural organic matter and small molecule organic pollutants—to achieve high-precision pollution source tracing is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] The purpose of this application is to provide a pollution source tracing method, system, device, medium, and product based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants, in order to solve the problem of low accuracy in pollution source tracing.

[0006] To achieve the above objectives, this application provides the following solution.

[0007] Firstly, this application provides a pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants, including: High-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants were acquired from multiple samples; the multiple samples included samples from multiple pollution sources and samples from multiple pollution receptors in the target area. Based on the high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants of each sample, the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample were determined. Based on the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample, the peak areas of each mass spectrometry peak in the high-resolution mass spectrometry data of small molecule organic pollutants of each sample are corrected to obtain the corrected peak areas of the corresponding mass spectrometry peaks. Based on the peak area and mass-to-charge ratio of each mass spectral peak in the high-resolution mass spectrometry data of natural organic matter of each sample, and the corrected peak area and mass-to-charge ratio of each mass spectral peak corresponding to small molecule organic pollutants, the feature vector of each sample is determined. Based on the feature vectors of samples from all pollution sources and the feature vectors of samples from all pollution receptors, the final value of the contribution ratio of each pollution source to each pollution receptor is determined, thus completing the pollution source tracing.

[0008] In one embodiment, high-resolution mass spectrometry data of natural organic matter and high-resolution mass spectrometry data of small molecule organic pollutants from multiple samples are acquired, including: The original spectra of natural organic matter in each sample were acquired using Fourier transform ion cyclotron resonance mass spectrometry. Based on the original spectra of natural organic matter in each sample, the high-resolution mass spectrometry data of natural organic matter in each sample were determined. The high-resolution mass spectrometry data of natural organic matter included the mass-to-charge ratio, molecular formula and peak area of ​​multiple mass spectrometry peaks. The original spectra of small molecule organic pollutants in each sample were acquired using ultra-high performance liquid chromatography-high resolution mass spectrometry. Based on the original spectra of small molecule organic pollutants in each sample, high-resolution mass spectrometry data of small molecule organic pollutants in each sample were determined. The high-resolution mass spectrometry data of small molecule organic pollutants include: mass-to-charge ratio, retention time, secondary mass spectra, and peak area of ​​multiple mass spectrometry peaks.

[0009] In one embodiment, the peak area of ​​the mass spectrometry peak corresponding to the reference substance for each sample is determined based on the high-resolution mass spectrometry data of the natural organic matter and the high-resolution mass spectrometry data of the small molecule organic pollutants, respectively, including: Any sample is identified as the sample to be analyzed; Structural analysis was performed on the high-resolution mass spectrometry data of the natural organic matter in the sample to be analyzed, and the superclass to which each mass spectrometry peak in the sample to be analyzed belongs was obtained. The high-resolution mass spectrometry data of small molecule organic pollutants in the sample to be analyzed are used to perform structural analysis, so as to obtain the molecular formula and superclass of each mass spectrometry peak corresponding to the small molecule organic pollutants in the sample to be analyzed. Substances corresponding to both natural organic matter and small molecule organic pollutants in the sample to be analyzed, belonging to the same superclass, and having the same molecular formula are all identified as reference substances for the sample to be analyzed. The peak areas of the reference substances in the high-resolution mass spectrometry data of natural organic matter and the peak areas of the reference substances in the high-resolution mass spectrometry data of small molecule organic pollutants are extracted to obtain the peak area pairs corresponding to each reference substance in the sample to be analyzed.

[0010] In one embodiment, based on the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample, the peak areas of each mass spectrometry peak in the high-resolution mass spectrometry data of small molecule organic pollutants of each sample are corrected to obtain the corrected peak areas of the corresponding mass spectrometry peaks, including: Any sample is designated as the current sample, any superclass corresponding to the current sample is designated as the current superclass, and any reference substance belonging to the current superclass is designated as the current reference substance; The peak area of ​​the mass spectrum peak corresponding to the current reference substance in the high-resolution mass spectrometry data of natural organic matter is determined as the first peak area corresponding to the current reference substance. The peak area of ​​the mass spectrometry peak corresponding to the current reference substance in the high-resolution mass spectrometry data of small molecule organic pollutants is determined as the second peak area corresponding to the current reference substance. Calculate the ratio of the area of ​​the first peak and the area of ​​the second peak corresponding to the current reference material to obtain the correction coefficient of the current reference material; The average of the correction coefficients of all reference substances belonging to the current superclass is used to obtain the correction coefficient of the current superclass. The peak area of ​​each mass spectrometry peak belonging to the current superclass in the high-resolution mass spectrometry data of small molecule organic pollutants in the current sample is multiplied by the correction coefficient of the current superclass to obtain the corrected peak area of ​​the corresponding mass spectrometry peak.

[0011] In one embodiment, the feature vector of each sample is determined based on the peak area and mass-to-charge ratio of each mass spectral peak in the high-resolution mass spectrometry data of the natural organic matter of each sample, and the corrected peak area and mass-to-charge ratio of each mass spectral peak corresponding to the small molecule organic pollutants, including: Select any one sample as the sample to be combined; The feature vector of the sample to be combined is obtained by combining the peak area of ​​each mass spectrum peak in the high-resolution mass spectrometry data of the natural organic matter of the sample to be combined, the mass-to-charge ratio of each mass spectrum peak in the high-resolution mass spectrometry data of the natural organic matter of the sample to be combined, the corrected peak area of ​​each mass spectrum peak corresponding to the small molecule organic pollutants of the sample to be combined, and the mass-to-charge ratio of each mass spectrum peak in the high-resolution mass spectrometry data of the small molecule organic pollutants of the sample to be combined.

[0012] In one embodiment, based on the feature vectors of samples from all pollution sources and the feature vectors of samples from all pollution receptors, the final value of the contribution ratio of each pollution source to each pollution receptor is determined, thus completing pollution source tracing, including: Identify any contaminant receptor as the current receptor; Based on the feature vector of the current receptor sample and the feature vectors of samples from all pollution sources, construct the feature matrix corresponding to the current receptor; The feature matrix corresponding to the current receptor is preprocessed to obtain the preprocessed feature matrix corresponding to the current receptor; the preprocessing includes missing value imputation and standardization. Randomly initialize the contribution ratio of each pollution source to the current receptor to obtain the initial value of the contribution ratio of each pollution source to the current receptor. Using the fast expectation-maximization algorithm or the Bayesian algorithm, based on the preprocessed feature matrix corresponding to the current receptor and the initial value of the contribution ratio of each pollution source to the current receptor, the contribution ratio of each pollution source to the current receptor is iteratively updated to obtain the final value of the contribution ratio of each pollution source to the current receptor.

[0013] Secondly, this application provides a pollution source tracing system based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants, to realize the pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants described above. The pollution source tracing system based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants includes: The high-resolution mass spectrometry data acquisition module is used to acquire high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants from multiple samples, including samples from multiple pollution sources and samples from multiple pollution receptors in the target area. The peak area pair determination module is used to determine the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample based on the high-resolution mass spectrometry data of natural organic matter and the high-resolution mass spectrometry data of small molecule organic pollutants, respectively. The peak area correction module is used to correct the peak area of ​​each mass spectrometry peak in the high-resolution mass spectrometry data of small molecule organic pollutants of each sample based on the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample, so as to obtain the corrected peak area of ​​the corresponding mass spectrometry peak. The feature vector determination module is used to determine the feature vector of each sample based on the peak area and mass-to-charge ratio of each mass spectral peak in the high-resolution mass spectrometry data of natural organic matter and the corrected peak area and mass-to-charge ratio of each mass spectral peak corresponding to small molecule organic pollutants. The pollution source tracing module is used to determine the final value of the contribution ratio of each pollution source to each pollution receptor based on the feature vectors of samples from all pollution sources and the feature vectors of samples from all pollution receptors, thus completing the pollution source tracing.

[0014] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants as described above.

[0015] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants as described above.

[0016] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants as described above.

[0017] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application discloses a pollution source tracing method, system, device, medium, and product based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants. It acquires high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants from multiple pollution sources and multiple pollutant receptors in a target area, respectively. Based on these two types of data, it determines the peak area pairs corresponding to reference substances in each sample, using the reference substances as a common reference between the two detection platforms. The peak area ratio is used to correct the peak area of ​​small molecule organic pollutants, eliminating the dimensional and abundance range differences caused by different detection platforms. This achieves standardization and unified measurement of the two types of high-resolution mass spectrometry data. Furthermore, the corrected small molecule organic pollutant data is fused with the natural organic matter data to construct a feature vector. Based on the feature vectors of all pollution sources and pollutant receptors, the contribution ratio of each pollution source to each pollutant receptor is determined. This allows for effective fusion and complementary source information of the two types of data during joint source tracing, avoiding the problem of incomplete source information caused by relying on only a single type of organic matter in traditional methods, thus significantly improving the accuracy of pollution source tracing. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart of a pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants provided in an embodiment of this application; Figure 2 This is a schematic diagram showing the relative positions of the sampling points of the sample; Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] The purpose of this application is to provide a pollution source tracing method, system, device, medium, and product based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants, aiming to improve the accuracy of pollution source tracing.

[0022] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] In one exemplary embodiment, such as Figure 1 As shown, a pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants is provided, including the following steps.

[0024] Step 1: Obtain high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants from multiple samples respectively.

[0025] The samples included multiple pollution sources and multiple pollution receptors in the target area.

[0026] As an optional implementation, step 1 includes the following steps.

[0027] Step 11: Use Fourier transform ion cyclotron resonance mass spectrometry to acquire the original spectra of natural organic matter in each sample.

[0028] Step 12: Based on the original spectra of natural organic matter in each sample, determine the high-resolution mass spectrometry data of natural organic matter in each sample; the high-resolution mass spectrometry data of natural organic matter includes: mass-to-charge ratio, molecular formula and peak area of ​​multiple mass spectrometry peaks.

[0029] Step 13: Use ultra-high performance liquid chromatography-high resolution mass spectrometry to acquire the original spectra of small molecule organic pollutants in each sample.

[0030] Step 14: Based on the original spectra of small molecule organic pollutants in each sample, determine the high-resolution mass spectrometry data of small molecule organic pollutants in each sample; the high-resolution mass spectrometry data of small molecule organic pollutants include: mass-to-charge ratio, retention time, secondary mass spectra and peak area of ​​multiple mass spectrometry peaks.

[0031] Step 2: Based on the high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants of each sample, determine the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample.

[0032] As an optional implementation, step 2 includes the following steps.

[0033] Step 21: Identify any sample as the sample to be analyzed.

[0034] Step 22: Perform structural analysis on the high-resolution mass spectrometry data of the natural organic matter in the sample to be analyzed, and obtain the superclass to which each mass spectrometry peak in the sample to be analyzed belongs.

[0035] Specifically, there are 26 superclasses: organic acids and their derivatives, organic oxygen compounds, organic halides, phenylpropanoids and polyketides, isopentenyl alcohol lipids, fatty acyls, glycerides, glycerophospholipids, sphingolipids, sugars, steroids and their derivatives, benzenes, azobenzenes, diazobenzenes, stilbenes, diphenylmethanes, triphenylmethanes, hydrocarbons, heterocyclic compounds, alkaloids and their derivatives, lignans, terpenes, organosulfur compounds, organonitrogen compounds, organophosphorus compounds, and organometallic compounds.

[0036] Step 23: Perform structural analysis on the high-resolution mass spectrometry data of small molecule organic pollutants in the sample to be analyzed, and obtain the molecular formula and superclass of each mass spectrometry peak corresponding to the small molecule organic pollutants in the sample to be analyzed.

[0037] Step 24: The substances corresponding to the mass spectrometry peaks of both natural organic matter and small molecule organic pollutants in the sample to be analyzed, which belong to the same superclass and have the same molecular formula, are identified as the reference substances of the sample to be analyzed.

[0038] Step 25: Extract the peak area of ​​the reference substance in the high-resolution mass spectrometry data of natural organic matter and the peak area of ​​the reference substance in the high-resolution mass spectrometry data of small molecule organic pollutants for each sample to be analyzed, and obtain the peak area pairs corresponding to each reference substance in the sample to be analyzed.

[0039] Step 3: Based on the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample, correct the peak areas of each mass spectrometry peak in the high-resolution mass spectrometry data of small molecule organic pollutants of each sample to obtain the corrected peak areas of the corresponding mass spectrometry peaks.

[0040] As an optional implementation, step 3 includes the following steps.

[0041] Step 31: Determine any sample as the current sample, determine any superclass corresponding to the current sample as the current superclass, and determine any reference substance belonging to the current superclass as the current reference substance.

[0042] Step 32: Determine the peak area of ​​the mass spectrum peak corresponding to the current reference substance in the high-resolution mass spectrometry data of natural organic matter as the first peak area corresponding to the current reference substance.

[0043] Step 33: Determine the peak area of ​​the mass spectrometry peak corresponding to the current reference substance in the high-resolution mass spectrometry data of small molecule organic pollutants as the second peak area corresponding to the current reference substance.

[0044] Step 34: Calculate the ratio of the area of ​​the first peak and the area of ​​the second peak corresponding to the current reference material to obtain the correction coefficient of the current reference material.

[0045] Step 35: Calculate the average of the correction coefficients of all reference substances belonging to the current superclass to obtain the correction coefficient of the current superclass.

[0046] Step 36: Multiply the peak area of ​​each mass spectrometry peak belonging to the current superclass in the high-resolution mass spectrometry data of small molecule organic pollutants in the current sample by the correction coefficient of the current superclass to obtain the corrected peak area of ​​the corresponding mass spectrometry peak.

[0047] Step 4: Determine the feature vector of each sample based on the peak area and mass-to-charge ratio of each mass spectral peak in the high-resolution mass spectrometry data of natural organic matter and the corrected peak area and mass-to-charge ratio of each mass spectral peak corresponding to small molecule organic pollutants.

[0048] As an optional implementation, step 4 includes the following steps.

[0049] Step 41: Select any sample as the sample to be combined.

[0050] Step 42: Combine the peak areas of each mass spectrum peak in the high-resolution mass spectrometry data of the natural organic matter of the sample to be combined, the mass-to-charge ratio of each mass spectrum peak in the high-resolution mass spectrometry data of the natural organic matter of the sample to be combined, the corrected peak areas of each mass spectrum peak corresponding to the small molecule organic pollutants of the sample to be combined, and the mass-to-charge ratio of each mass spectrum peak in the high-resolution mass spectrometry data of the small molecule organic pollutants of the sample to be combined to obtain the feature vector of the sample to be combined.

[0051] Step 5: Based on the feature vectors of samples from all pollution sources and the feature vectors of samples from all pollution receptors, determine the final value of the contribution ratio of each pollution source to each pollution receptor, and complete the pollution source tracing.

[0052] As an optional implementation, step 5 includes the following steps.

[0053] Step 51: Identify any contamination receptor as the current receptor.

[0054] Step 52: Construct the feature matrix corresponding to the current receptor based on the feature vector of the current receptor sample and the feature vectors of all pollution source samples.

[0055] Step 53: Preprocess the feature matrix corresponding to the current receptor to obtain the preprocessed feature matrix corresponding to the current receptor; the preprocessing includes missing value imputation and standardization.

[0056] Step 54: Randomly initialize the contribution ratio of each pollution source to the current receptor to obtain the initial value of the contribution ratio of each pollution source to the current receptor.

[0057] Step 55: Using the fast expectation-maximization algorithm or the Bayesian algorithm, based on the preprocessed feature matrix corresponding to the current receptor and the initial value of the contribution ratio of each pollution source to the current receptor, iteratively update the contribution ratio of each pollution source to the current receptor to obtain the final value of the contribution ratio of each pollution source to the current receptor.

[0058] Specifically, when using the fast expectation-maximization algorithm to iteratively update the contribution ratio of each pollution source to the current receptor, the expectation step and the maximization step are executed alternately in an iterative manner. In the expectation step, the posterior probability of each mass spectrum peak belonging to each pollution source is calculated based on the contribution ratio of each pollution source to the current receptor in the current iteration. In the maximization step, the likelihood function is maximized to update the contribution ratio of each pollution source to the current receptor.

[0059] The Bayesian algorithm is based on Bayes' theorem. It iteratively calculates the posterior distribution of the contribution ratio parameter by setting the prior distribution of the contribution ratio parameter and combining it with the likelihood function of the observed data. During the iteration process, it continuously updates the posterior probability of each feature vector belonging to each pollution source.

[0060] Furthermore, the method described in this application was used to determine the contribution ratio of wastewater discharge from a production workshop to the flowing river. Five samples were collected: one unaffected background sample from the river upstream of the production workshop (Sample 1), one sample from a tributary of the river flowing through a forest park (Sample 2), one sample from the process wastewater discharge outlet of the production workshop (Sample 3), and two affected cross-section samples set along the river's flow direction (Samples 4 and 5). The relative locations of the sampling points for each sample are shown below. Figure 2 As shown. Samples 2 and 3 are from two sources, natural and polluted, respectively. No other pollution sources flow into the area downstream of Sample 1 and upstream of Sample 2. Sample 4 is located between downstream of Sample 2 and upstream of Sample 3, serving as a confluence of Samples 1 and 2; Sample 5 is located downstream of Sample 3, serving as a confluence of Samples 1, 2, and 3. Sample 1 is the background sample, Samples 2 and 3 are the two source samples, and Samples 4 and 5 are samples from confluences along the riverbank. Ultimately, it was determined that Sample 4 is influenced by both upstream (Sample 1) and natural sources. Due to its proximity to a river tributary, it is significantly influenced by the natural source (Sample 2), contributing 51.8%; Sample 5 is influenced by both natural sources and wastewater from the production workshop, contributing 21.6% and 58.3%, respectively.

[0061] In an exemplary embodiment, a pollution source tracing system based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants is provided to implement the above-mentioned pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants. The pollution source tracing system based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants includes: The high-resolution mass spectrometry data acquisition module is used to acquire high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants from multiple samples, including samples from multiple pollution sources and samples from multiple pollution receptors in the target area. The peak area pair determination module is used to determine the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample based on the high-resolution mass spectrometry data of natural organic matter and the high-resolution mass spectrometry data of small molecule organic pollutants, respectively. The peak area correction module is used to correct the peak area of ​​each mass spectrometry peak in the high-resolution mass spectrometry data of small molecule organic pollutants of each sample based on the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample, so as to obtain the corrected peak area of ​​the corresponding mass spectrometry peak. The feature vector determination module is used to determine the feature vector of each sample based on the peak area and mass-to-charge ratio of each mass spectral peak in the high-resolution mass spectrometry data of natural organic matter and the corrected peak area and mass-to-charge ratio of each mass spectral peak corresponding to small molecule organic pollutants. The pollution source tracing module is used to determine the final value of the contribution ratio of each pollution source to each pollution receptor based on the feature vectors of samples from all pollution sources and the feature vectors of samples from all pollution receptors, thus completing the pollution source tracing.

[0062] In one exemplary embodiment, a computer device is provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants.

[0063] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements a pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants.

[0064] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements a pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants.

[0065] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 3As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants.

[0066] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0067] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0068] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0069] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0070] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0071] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants, characterized in that, The pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants includes: High-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants were acquired from multiple samples; the multiple samples included samples from multiple pollution sources and samples from multiple pollution receptors in the target area. Based on the high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants of each sample, the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample were determined. Based on the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample, the peak areas of each mass spectrometry peak in the high-resolution mass spectrometry data of small molecule organic pollutants of each sample are corrected to obtain the corrected peak areas of the corresponding mass spectrometry peaks. Based on the peak area and mass-to-charge ratio of each mass spectral peak in the high-resolution mass spectrometry data of natural organic matter of each sample, and the corrected peak area and mass-to-charge ratio of each mass spectral peak corresponding to small molecule organic pollutants, the feature vector of each sample is determined. Based on the feature vectors of samples from all pollution sources and the feature vectors of samples from all pollution receptors, the final value of the contribution ratio of each pollution source to each pollution receptor is determined, thus completing the pollution source tracing.

2. The pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants according to claim 1, characterized in that, High-resolution mass spectrometry (HMS) data of natural organic matter and small molecule organic pollutants from multiple samples were acquired, including: The original spectra of natural organic matter in each sample were acquired using Fourier transform ion cyclotron resonance mass spectrometry. Based on the original spectra of natural organic matter in each sample, the high-resolution mass spectrometry data of natural organic matter in each sample were determined. The high-resolution mass spectrometry data of natural organic matter included the mass-to-charge ratio, molecular formula and peak area of ​​multiple mass spectrometry peaks. The original spectra of small molecule organic pollutants in each sample were acquired using ultra-high performance liquid chromatography-high resolution mass spectrometry. Based on the original spectra of small molecule organic pollutants in each sample, high-resolution mass spectrometry data of small molecule organic pollutants in each sample were determined. The high-resolution mass spectrometry data of small molecule organic pollutants include: mass-to-charge ratio, retention time, secondary mass spectra, and peak area of ​​multiple mass spectrometry peaks.

3. The pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants according to claim 2, characterized in that, Based on the high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants of each sample, the peak areas of the mass spectrometry peaks corresponding to the reference substances of each sample were determined, including: Any sample is identified as the sample to be analyzed; Structural analysis was performed on the high-resolution mass spectrometry data of the natural organic matter in the sample to be analyzed, and the superclass to which each mass spectrometry peak in the sample to be analyzed belongs was obtained. The high-resolution mass spectrometry data of small molecule organic pollutants in the sample to be analyzed are used to perform structural analysis, so as to obtain the molecular formula and superclass of each mass spectrometry peak corresponding to the small molecule organic pollutants in the sample to be analyzed. Substances corresponding to both natural organic matter and small molecule organic pollutants in the sample to be analyzed, belonging to the same superclass, and having the same molecular formula are all identified as reference substances for the sample to be analyzed. The peak areas of the reference substances in the high-resolution mass spectrometry data of natural organic matter and the peak areas of the reference substances in the high-resolution mass spectrometry data of small molecule organic pollutants are extracted to obtain the peak area pairs corresponding to each reference substance in the sample to be analyzed.

4. The pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants according to claim 3, characterized in that, Based on the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample, the peak areas of each mass spectrometry peak in the high-resolution mass spectrometry data of small molecule organic pollutants of each sample are corrected to obtain the corrected peak areas of the corresponding mass spectrometry peaks, including: Any sample is designated as the current sample, any superclass corresponding to the current sample is designated as the current superclass, and any reference substance belonging to the current superclass is designated as the current reference substance; The peak area of ​​the mass spectrum peak corresponding to the current reference substance in the high-resolution mass spectrometry data of natural organic matter is determined as the first peak area corresponding to the current reference substance. The peak area of ​​the mass spectrometry peak corresponding to the current reference substance in the high-resolution mass spectrometry data of small molecule organic pollutants is determined as the second peak area corresponding to the current reference substance. Calculate the ratio of the area of ​​the first peak and the area of ​​the second peak corresponding to the current reference material to obtain the correction coefficient of the current reference material; The average of the correction coefficients of all reference substances belonging to the current superclass is used to obtain the correction coefficient of the current superclass. The peak area of ​​each mass spectrometry peak belonging to the current superclass in the high-resolution mass spectrometry data of small molecule organic pollutants in the current sample is multiplied by the correction coefficient of the current superclass to obtain the corrected peak area of ​​the corresponding mass spectrometry peak.

5. The pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants according to claim 2, characterized in that, Based on the peak area and mass-to-charge ratio of each mass spectral peak in the high-resolution mass spectrometry data of natural organic matter for each sample, and the corrected peak area and mass-to-charge ratio of each mass spectral peak corresponding to small molecule organic pollutants, the characteristic vectors of each sample are determined, including: Select any one sample as the sample to be combined; The feature vector of the sample to be combined is obtained by combining the peak area of ​​each mass spectrum peak in the high-resolution mass spectrometry data of the natural organic matter of the sample to be combined, the mass-to-charge ratio of each mass spectrum peak in the high-resolution mass spectrometry data of the natural organic matter of the sample to be combined, the corrected peak area of ​​each mass spectrum peak corresponding to the small molecule organic pollutants of the sample to be combined, and the mass-to-charge ratio of each mass spectrum peak in the high-resolution mass spectrometry data of the small molecule organic pollutants of the sample to be combined.

6. The pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants according to claim 1, characterized in that, Based on the feature vectors of samples from all pollution sources and the feature vectors of samples from all pollution receptors, the final value of the contribution ratio of each pollution source to each pollution receptor is determined, thus completing the pollution source tracing, including: Identify any contaminant receptor as the current receptor; Based on the feature vector of the current receptor sample and the feature vectors of samples from all pollution sources, construct the feature matrix corresponding to the current receptor; The feature matrix corresponding to the current receptor is preprocessed to obtain the preprocessed feature matrix corresponding to the current receptor; the preprocessing includes missing value imputation and standardization. Randomly initialize the contribution ratio of each pollution source to the current receptor to obtain the initial value of the contribution ratio of each pollution source to the current receptor. Using the fast expectation-maximization algorithm or the Bayesian algorithm, based on the preprocessed feature matrix corresponding to the current receptor and the initial value of the contribution ratio of each pollution source to the current receptor, the contribution ratio of each pollution source to the current receptor is iteratively updated to obtain the final value of the contribution ratio of each pollution source to the current receptor.

7. A pollution source tracing system based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants, to implement the pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants as described in any one of claims 1-6, characterized in that, The pollution source tracing system based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants includes: The high-resolution mass spectrometry data acquisition module is used to acquire high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants from multiple samples, including samples from multiple pollution sources and samples from multiple pollution receptors in the target area. The peak area pair determination module is used to determine the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample based on the high-resolution mass spectrometry data of natural organic matter and the high-resolution mass spectrometry data of small molecule organic pollutants, respectively. The peak area correction module is used to correct the peak area of ​​each mass spectrometry peak in the high-resolution mass spectrometry data of small molecule organic pollutants of each sample based on the peak area pairs of the mass spectrometry peaks corresponding to the reference substances of each sample, so as to obtain the corrected peak area of ​​the corresponding mass spectrometry peak. The feature vector determination module is used to determine the feature vector of each sample based on the peak area and mass-to-charge ratio of each mass spectral peak in the high-resolution mass spectrometry data of natural organic matter and the corrected peak area and mass-to-charge ratio of each mass spectral peak corresponding to small molecule organic pollutants. The pollution source tracing module is used to determine the final value of the contribution ratio of each pollution source to each pollution receptor based on the feature vectors of samples from all pollution sources and the feature vectors of samples from all pollution receptors, thus completing the pollution source tracing.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the pollution source tracing method based on high-resolution mass spectrometry data of natural organic matter and small molecule organic pollutants as described in any one of claims 1-6.

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