A municipal pipe network overflow pollution tracing method based on DOM molecular group discrimination tracing

Abstract

The present application belongs to the field of ecological environment protection, and particularly relates to a municipal pipe network overflow pollution tracing method based on DOM molecular group discrimination tracing. The municipal overflow pollution tracing method provided by the present application mainly refers to obtaining the DOM molecular pool of main pollutants in municipal overflow and the molecular group composition characteristics thereof through FT-ICR-MS detection and calculation on a large number of pollution source samples of municipal overflow, and comprehensively and accurately completing the pollution source tracing of the end municipal overflow by using the analysis of the DOM molecules of various pollution sources of municipal overflow at the molecular level, so as to provide reliable data and technology for effective control of overflow pollution and optimization management and upgrading reconstruction of the drainage system.

Description

Technical Field

[0001] This invention belongs to the field of ecological and environmental protection, and specifically relates to a method for tracing the source of pollution from municipal pipeline overflows based on DOM molecular group discrimination tracing. Background Technology

[0002] Urban water pollution has always been a difficult environmental problem to eradicate. Since the "Action Plan for the Battle to Protect and Restore the Yangtze River" in 2018, the proportion of sections with excellent water quality in the Yangtze River Basin has reached nearly 97%, and the main stream has reached Class II water quality for the first time. However, the water environment problem in the basin remains severe, and the prevention and control of urban water pollution is still weak. Achieving the goal of basically eliminating black and odorous water bodies by 2025 is a pressing and arduous task. One of the difficulties in governance is urban overflow discharge. Urban overflows have complex and diverse sources and a high degree of mixing, which can carry pollutants into the basin, causing water quality degradation, increased concentrations of COD, ammonia nitrogen, and TP, and aggravated endogenous pollution, sometimes leading to black and odorous water. Therefore, reducing urban overflow pollution is crucial to promoting my country's water pollution prevention and control process.

[0003] Taking Shanghai as an example, with the effective control of direct sewage discharge, rainwater overflow from the drainage system has become a major source of pollution in the central urban area of ​​Shanghai. In terms of pollutant volume, nearly 30% of the pollutants generated in Shanghai's central urban area, although collected by the drainage network, are not sent to urban wastewater treatment plants but are directly discharged into rivers during rainwater overflow. Currently, Shanghai's drainage system is mainly a separate system, but some combined sewer systems still exist. In combined sewer systems, the flow rate in the network is small during dry weather, allowing sewage to enter wastewater treatment plants; however, during rainy days, the runoff from heavy rainfall exceeds the network's maximum design flow, causing overflow and becoming a major cause of urban overflow pollution. Because rainwater overflow includes pollutants from various sources such as domestic sewage, rainwater runoff, and pipe sediment, identifying the source of the pollution is currently very difficult. At present, pollution control measures mainly have two directions: the first is "combined to separate", but this is a very complex and large-scale system engineering project; the second is source control, but it can only adopt methods such as extensive emission reduction and pipeline bottom sludge removal, and cannot take targeted measures to deal with different pollution situations.

[0004] In addition, the mixing of rainwater and sewage in separate sewer systems is also a significant factor contributing to urban overflow pollution. The main causes of rainwater and sewage mixing include: (1) incomplete renovation of separate sewer systems; (2) illegal discharge of sewage by some enterprises; (3) industrial enterprises' wastewater discharge exceeding the sewage network's transport capacity; (4) some residential areas' combined sewer systems are unable to divert wastewater to the separate sewer systems of municipal roads; and (5) wastewater from road washing, roadside car washing, etc., flows into the rainwater network. However, it is currently difficult to accurately trace the source of rainwater and sewage mixing. If pollutants can be accurately traced by detecting wastewater discharged at the end of the line, it will help improve the efficiency of reducing pollution emissions at the source and take targeted measures to reduce urban overflow pollution to the watershed.

[0005] Currently, there are few technological inventions specifically for tracing the source of urban overflow pollution. Methods for tracing the source of urban water pollution are typically used to analyze pipeline overflows. There are currently many methods for tracing the source of urban water pollution, primarily based on conventional water quality indicators, ultraviolet spectroscopy, fluorescence spectroscopy, and model algorithms. This approach largely ignores the problems and information reflected by the composition and structure of pollutants themselves, resulting in significant limitations. For example, a rapid water pollution source tracing method and system (CN113449956A) discloses a rapid water pollution source tracing method that combines water pollution monitoring technology with migration models to simulate the migration of pollutants, thereby identifying enterprises illegally discharging pollutants; a method for tracing pollution sources in urban drainage pipe networks (CN113420396A) establishes a tree-shaped topology based on GIS platform data and uses various search algorithms to determine abnormal nodes in the drainage pipe network and trace pollution sources; a water pollution source tracing method based on ultraviolet-visible spectral data (CN113376114A) achieves intelligent pollutant source tracing by establishing a normalized water pollution source tracing spectral library; and a water quality multi-feature early warning source tracing system and method (CN113588617A) combines a water pollution identification and early warning module, fluorescence spectroscopy, ultraviolet spectroscopy, automatic sample preparation module, and laboratory measurement module, and uses deep learning algorithms to realize an automatic water pollution source measurement system. A method for tracing and classifying polluted water bodies using three-dimensional fluorescence spectral feature information (CN111426668A) is proposed. This method completes the source tracing of pollutants by constructing a basic fluorescence spectral database and a feature fluorescence spectral database, combined with a model constructed using the K-means algorithm and a PNN neural network.

[0006] Therefore, current methods for tracing the source of urban water pollution mainly rely on pollutant concentration, neglecting the issues and information reflected by the composition and structure of the pollutants themselves. Characterization of DOM components also generally suffers from low structural resolution and unclear molecular origins. When these technologies are applied to pipeline pollution tracing, the diversity and complexity of pollutants lead to ambiguity and significant limitations in the tracing results, easily causing deviations from the actual situation and preventing truly accurate tracing. Furthermore, large-scale and frequent collection and monitoring of source and end-point water samples are required, consuming substantial human and material resources. To address these issues, this invention proposes a method for tracing the source of overflow pollution in municipal pipeline networks based on DOM molecular group discrimination tracing. Starting with the characterization and comparative analysis of DOM molecular components, it can accurately and efficiently trace pollutant sources. It can not only identify multiple types of pollution sources but also distinguish subcategories of pollution sources, reflecting the dynamic changes in pollution output. Therefore, this invention is applicable to urban overflow pollution tracing, providing reliable data and technology for the effective control of overflow pollution and the optimized management and upgrading of drainage systems, thus promoting the treatment of urban water pollution. Summary of the Invention

[0007] The purpose of this invention is to address the current situation where it is difficult to effectively trace the source of urban overflow pollution, leading to serious pollution of urban water bodies, and to provide a method for tracing the source of municipal pipeline overflow pollution based on DOM molecular group discrimination tracing.

[0008] This invention proposes a method for tracing the source of overflow pollution in municipal pipe networks based on DOM molecular group discrimination and tracing, including establishing a molecular pool of urban overflow pollution based on DOM molecular groups and establishing a method for tracing the source of overflow pollution in municipal pipe networks;

[0009] (1) Establishing a molecular pool for urban overflow pollution based on DOM molecular groups

[0010] The DOM molecular pools of major pollutants in urban overflows were obtained by FT-ICR-MS detection and calculation of a large number of pollution source samples, as follows:

[0011] (1.1) Collect samples from a wide range of overflow pollution input sources, including one or more of the following: domestic sewage, treated industrial wastewater discharged into the sewer system, surface runoff or pipeline sediment samples;

[0012] (1.2) After solid phase extraction pretreatment, the pollution input source samples collected in step (1.1) are subjected to FT-ICR-MS detection, and the DOM molecular group fingerprint spectrum of each pollution input source sample is obtained by DOM molecular group division and molecular formula matching analysis.

[0013] (1.3) Based on step (1.2), the DOM molecular group fingerprint spectrum and molecular formula of each type of pollution input source sample are analyzed and classified; the DOM molecular formulas of the same type of urban overflow pollution source samples are accumulated to obtain all the molecular formulas appearing in several samples of this type of pollution source, and the peak values ​​are obtained after weight calculation, thereby constructing the corresponding urban overflow pollution source DOM molecular pool of domestic sewage, treated industrial wastewater discharged into the pipe, surface runoff or pipeline sediment samples;

[0014]

[0015] Where: n——the cumulative number of samples from the same type of urban overflow pollution source;

[0016] P i —The peak value corresponding to a single molecular formula in a single sample;

[0017] SP i —The total peak value of all molecular formulas in a single sample;

[0018] By combining the peak data corresponding to the molecular formula, the relative abundance ratio of each group component in the sample was obtained, and the molecular group distribution characteristics of each type of urban overflow pollution source DOM were obtained through comparative analysis.

[0019] (2) Establish a method for tracing the source of pollution from municipal pipeline overflows, which refers to obtaining the source of pollution in the sample through matching calculation of the DOM molecular pool of urban overflows and the characteristics of DOM molecular groups, as follows:

[0020] (2.1) First, the collected unknown mixed pollution source samples were pretreated by solid phase extraction and then detected by FT-ICR-MS. The DOM molecular formula and group composition characteristics of the samples were obtained by analysis and calculation through DOM molecular group division and molecular formula matching.

[0021] (2.2) On the one hand, based on step (2.1), the DOM molecular formula in the sample is compared with the DOM molecular pool of urban overflow pollution. The molecular formula peak values ​​of each type of pollution source molecular pool that is successfully matched are accumulated to obtain the contribution of each type of pollution source to the sample. The type of pollution source with the largest cumulative peak value is taken as the main pollution source.

[0022]

[0023] In the formula: m — the number of molecular formulas that were successfully matched;

[0024] Pi – the peak value corresponding to a single molecular formula in a single sample;

[0025] (2.3) On the other hand, based on step (2.1), the proportion of DOM molecular group components in the sample is compared with the distribution characteristics of DOM molecular groups of various pollution sources in urban overflow. If the proportion of several types of components in the sample DOM is within the distribution characteristic range of the molecular group of the same pollution source, the acceptable error range is 2%, then the pollution source of this type is the main pollution source in this sample.

[0026] (2.4) Use the results of steps (2.2) and (2.3) to verify each other to complete the pollution source tracing; when the two results are the same, output the source tracing result directly; when the output result of step (2.3) is 0, the source tracing result of step (2.2) shall prevail; in a few cases, when the results of steps (2.2) and (2.3) conflict, the source tracing result obtained in step (2.2) shall prevail.

[0027] In this invention, the FT-ICR-MS pretreatment described in step (1.2) specifically involves: first, passing the sample through a 0.45 μm mixed fiber filter membrane to remove suspended particles, insoluble organic matter, and most microorganisms (the interstitial water of the pipe sediment sample is collected after centrifugation and then passed through the membrane); then, adding analytical grade hydrochloric acid to the sample after membrane passing and acidifying it to pH=2 to improve the extraction efficiency of phenolic and carboxyl organic matter; performing solid-phase extraction using a PPL column (500 mg, Agilent Technologies, USA) to remove salts and limit artifacts generated during the FT-ICR-MS process. The amount of sample passing through the PPL column is determined based on the sample's DOC concentration, and the DOC concentration of the eluent is controlled at approximately 100 mg / L. Before extraction, the PPL column is activated with 10 mL of chromatographic grade methanol and 10 mL of 0.01 M HCl (flow rate controlled at 2 mL·min). -1 After activation, the acidified sample (pH=2) was passed through a PPL column (flow rate controlled at 5 mL / min). -1 Then rinse the column with 10 mL of 0.01 M HCl (flow rate controlled at 2 mL / min). -1 The column was then completely dried with high-purity nitrogen. The DOM enriched on the dried column was eluted into a test tube using 5 mL of chromatographic-grade methanol and stored at -20 °C in the dark until analysis.

[0028] In this invention, the FT-ICR-MS determination in step (1.3) specifically involves using a Fourier transform ion cyclotron resonance mass spectrometer (Bruker SolariX, Germany) equipped with a 15.0 T superconducting magnet and an electrospray ionization (ESI) source; after DOM sample pretreatment, 200 μL is taken for characterization using FT-ICR-MS in negative ion mode: at a concentration of 120 μl·h-1 The sample was injected at a rate of -4.0 kV using an ESI source capillary voltage. After 300 scans with an ion accumulation time of 0.06 s and an m / z scan range of 100–1600, the samples were superimposed. Peaks with a signal-to-noise ratio greater than 6 were considered valid mass spectrometry peaks. The instrument was calibrated with 10 mmol / L sodium formate before sample detection, and calibrated with a known soluble organic compound as an internal standard after sample detection. After calibration, the mass error was less than 1 ppm.

[0029] In this invention, the FT-ICR-MS analysis in step (1.4) specifically involves: calculating the elemental composition of each mass spectrum peak according to pre-set chemical constraints; ensuring that the elemental ratios in the molecular formula conform to 0≤H / C≤2.25 and 0≤O / C≤1.2; that the double bond equivalence (DBE) is less than 30; and that the number of elements in the molecular formula ranges from C. 1~100 H 1~100 O 0~50 N 0~ 3S 0~1 P 0-1 Then, based on the elemental composition and mass-to-charge ratio, the corresponding molecular formula information is calculated and matched. DOM molecular formulas were matched and grouped as follows: lipids (0 ≤ O / C < 0.3, 1.5 < H / C ≤ 2.0), proteins (0.3 ≤ O / C < 0.67, 1.5 < H / C ≤ 2.2, N / C ≥ 0.05), carbohydrates (0.67 ≤ O / C ≤ 1.2, 1.5 < H / C ≤ 2.0), unsaturated hydrocarbons (0 ≤ O / C < 0.1, 0.7 ≤ H / C ≤ 1), lignins (0.1 ≤ O / C < 0.67, 0.7 ≤ H / C ≤ 1.5, AImod < 0.67), and polycyclic aromatic hydrocarbons (0 ≤ O / C ≤ 0.67, 0.2 ≤ H / C < 0.7, AImod ≥ 0.05). The DOM molecular group fingerprint was finally obtained by combining 0.67 ≤ O / C ≤ 1.2, 0.5 ≤ H / C ≤ 1.5, AImod < 0.67.

[0030] In this invention, each type of urban overflow pollution source DOM molecular pool contains thousands of molecular formulas and has its own unique molecular group distribution characteristics. The DOM molecular formulas of samples from the same type of urban overflow pollution source are accumulated, with newly appearing molecular formulas directly accumulated, while repeated molecular formulas have their peak values ​​weighted and then accumulated, thus obtaining the corresponding DOM molecular pool. The relative abundance percentage of each group component in the sample is obtained by combining the peak data corresponding to the molecular formulas, and the molecular group distribution characteristics of the DOM for each type of urban overflow pollution source are obtained through comparative analysis.

[0031] In this invention, the domestic sewage source is one or more of kitchen wastewater, bathing wastewater, washing wastewater and black water, and the industrial wastewater discharged into the pipeline after treatment is mainly organic pollutant, specifically food industry, light industry or heavy industry wastewater.

[0032] The beneficial effects of this invention are as follows:

[0033] (1) Through extensive sampling and FT-ICR-MS detection, a more comprehensive, accurate and representative DOM molecular group fingerprint spectrum of urban overflow can be obtained, and based on this, a DOM molecular pool of the main pollution sources of urban overflow can be constructed.

[0034] (2) This technology has conducted source analysis on urban overflow from two aspects, ensuring the comprehensiveness of the source analysis results and improving the reliability of the results;

[0035] (3) This technology enables the source analysis of urban overflow pollution, and can efficiently and accurately determine the source of pollutants from the molecular level, thereby providing reliable data and technology for the effective control of overflow pollution and the optimization and upgrading of drainage systems. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the process of the present invention;

[0037] Figure 2 This is a schematic diagram of FT-ICR-MS data analysis in this invention;

[0038] Figure 3 This is a schematic diagram illustrating the classification of pollution sources and urban overflows in this invention;

[0039] Figure 4 This is a schematic diagram of the steps of the source tracing algorithm in this invention. Detailed Implementation

[0040] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0041] Example 1:

[0042] Samples of major pollution sources of urban overflow were collected in urban areas of Shanghai, including domestic sewage, industrial sewage, pipeline sediments, and surface runoff; samples were also collected at the end of the urban overflow.

[0043] Wastewater samples from domestic sources were collected from the first inspection well where the terminal branch pipes of kitchen wastewater, bathing wastewater, washing wastewater, and black water in the residential area were connected. During the period when each type of wastewater was generated most concentratedly, 2L water samples were collected using a stainless steel water sampler and stored in polyethylene sampling bottles to ensure that the wastewater source in the collected samples was as singular as possible.

[0044] Industrial wastewater was collected from the collection wells of wastewater that flowed into the municipal drainage network after treatment in industrial parks such as food industry, light industry, and heavy industry. The sampling time was during the later part of the peak period of wastewater treatment in the plant. A 2L water sample was collected using a stainless steel water sampler and stored in a polyethylene sampling bottle.

[0045] Pipeline samples were collected from municipal sewage pipes, stormwater pipes, and mixed pipes in the residential area, along with overlying water and sediment. Overlying water samples were collected using a stainless steel water sampler, and 1L of sample was stored in a polyethylene sampling bottle; sediment samples were collected using a sludge trap, and 1L of sample was also stored in a polyethylene sampling bottle.

[0046] Surface runoff samples were collected from storm drains along road surfaces during July and August, with an average rainfall intensity of 4.72–8.14 mm / h and at least 7 sunny days prior to sampling. Before sampling, the probe of a handheld ultrasonic open channel flow meter (YK-MS) was placed below the liquid surface in the storm drain to measure the flow rate. Based on the ultrasonically detected liquid depth, the cross-sectional area of ​​the pipe, and the flow velocity, the actual flow rate was calculated using the formula "flow rate = flow velocity * cross-sectional area". During sampling, a stainless steel bucket was used to collect samples at the inlet of each storm drain, with each sampling interval of 5 minutes, from the start of the heavy rainfall until its end. After collection, the samples were stored in rinsed polyethylene sampling bottles and quickly transferred to the laboratory.

[0047] Urban overflow samples were collected from the forebay of stormwater pumping stations during the initial rainfall phase, after a large amount of initial rainwater had flowed into the pumping stations. A stainless steel water sampler was used, and 1L of sample was stored in a polyethylene sampling bottle.

[0048] FT-ICR-MS Pretreatment (Solid-Phase Extraction): First, the sample was passed through a 0.45 μm mixed fiber filter membrane to remove suspended particles, insoluble organic matter, and most microorganisms. Then, after membrane filtration, analytical grade hydrochloric acid was added to the sample to acidify it to pH=2, thereby improving the extraction efficiency of phenolic and carboxyl-containing organic compounds. Solid-phase extraction was performed using a PPL column (500 mg, Agilent Technologies, USA) to remove salts and limit artifacts generated during FT-ICR-MS. The amount of sample passing through the PPL column was determined based on the sample's DOC concentration, and the DOC concentration of the eluent was controlled to be around 100 mg / L. Before extraction, the PPL column was activated with 10 mL of chromatographic grade methanol and 10 mL of 0.01 M HCl (flow rate controlled at 2 mL / min). -1 After activation, the acidified sample (pH=2) was passed through a PPL column (flow rate controlled at 5 mL / min). -1 Then rinse the column with 10 mL of 0.01 M HCl (flow rate controlled at 2 mL / min). -1 The column was then completely dried with high-purity nitrogen. The DOM enriched on the dried column was eluted into a test tube using 5 mL of chromatographic-grade methanol and stored at -20 °C in the dark until analysis.

[0049] FT-ICR-MS determination: This invention utilizes Fourier transform ion cyclotron resonance mass spectrometry (Bruker SolariX, Germany) equipped with a 15.0 T superconducting magnet and an electrospray ionization (ESI) source. After DOM sample pretreatment, 200 μL was taken for characterization using FT-ICR-MS in negative ion mode: at a concentration of 120 μl·h. -1 The sample was injected at a rate of [missing value], with an ESI source capillary voltage of -4.0 kV. After 300 scans with an ion accumulation time of 0.06 s and an m / z scan range of 100–1600, the samples were superimposed. Peaks with a signal-to-noise ratio greater than 6 were considered valid mass spectrometry peaks. The instrument was calibrated with 10 mmol / L sodium formate before sample detection, and calibrated with a known soluble organic compound as an internal standard after sample detection. After calibration, the mass error was less than 1 ppm.

[0050] FT-ICR-MS analysis: The elemental composition of each mass spectrum peak was calculated based on the pre-set chemical constraints. The element ratios in the molecular formula conform to 0≤H / C≤2.25 and 0≤O / C≤1.2, the double bond equivalence (DBE) is less than 30, and the number of elements in the molecular formula ranges from C. 1~100 H 1~100 O 0~50 N 0~3 S 0~1P 0-1 Then, based on the elemental composition and mass-to-charge ratio, the corresponding molecular formula information is calculated and matched. After matching, the DOM molecular formulas are grouped as follows: lipids (0 ≤ O / C < 0.3, 1.5 < H / C ≤ 2.0), proteins (0.3 ≤ O / C < 0.67, 1.5 < H / C ≤ 2.2, N / C ≥ 0.05), carbohydrates (0.67 ≤ O / C ≤ 1.2, 1.5 < H / C ≤ 2.0), unsaturated hydrocarbons (0 ≤ O / C < 0.1, 0.7 ≤ H / C ≤ 1), lignins (0.1 ≤ O / C < 0.67, 0.7 ≤ H / C ≤ 1.5, AI...). mod < 0.67), polycyclic aromatic hydrocarbons (0 ≤ O / C ≤ 0.67, 0.2 ≤ H / C < 0.7, AI) mod ≥ 0.67) and tannins (0.67 ≤ O / C ≤ 1.2, 0.5 ≤ H / C ≤ 1.5, AI) mod < 0.67).

[0051] A source tracing algorithm was established: the main sources of urban overflow pollution were divided into seven categories: kitchen wastewater, bathing wastewater, laundry wastewater, black water, industrial wastewater, pipeline sediments, and surface runoff. Molecular pools were constructed based on their corresponding molecular formulas (DOMs). The DOMs of samples from the same category of urban overflow pollution sources were accumulated to obtain all molecular formulas appearing in several samples of that category. The peak values ​​were weighted to obtain the DOM molecular pools for each pollution source type. Simultaneously, the DOM group characteristics under that pollution category were obtained based on the proportion of DOM group components in the samples from the same category of urban overflow pollution sources.

[0052] Source tracing method: The source tracing algorithm is calculated based on the FT-ICR-MS data of the sample to be judged. The molecular formula and peak value are matched with the molecular pools of 7 pollution sources. The contribution of each type of pollution source is ranked according to the cumulative peak value of the successfully matched molecular formulas, and the contribution of 7 types of pollution sources, namely kitchen wastewater, bathing wastewater, washing wastewater, black water, industrial wastewater, pipeline sediment and surface runoff, is obtained.

[0053] Simultaneously, based on the sample grouping results and peak data, the proportion of DOM group components is obtained and compared with the molecular group distribution characteristics of the pollution source DOM. If the proportions of several types of components in the sample DOM are all within the molecular group distribution characteristic range of the same pollution source (acceptable error range is 2%), then this type of pollution source is the main pollution source in this sample. Accurate tracing is achieved by combining the two comparison results. When the contribution of multiple pollution sources in the sample is similar, it is easy for the group component matching result to contradict the molecular formula matching result. In this case, the molecular formula matching result shall prevail.

Claims

1. A method for tracing the source of pollution from municipal pipeline overflows based on DOM molecular group discrimination tracing, characterized in that... This includes establishing a molecular pool for urban overflow pollution based on DOM molecular groups and establishing a source tracing method for municipal pipeline overflow pollution; (1) Establish a molecular pool of urban overflow pollution based on DOM molecular groups. The DOM molecular pool of major pollutants in urban overflow is obtained by FT-ICR-MS detection and calculation of a large number of pollution source samples of urban overflow, as follows: (1.1) Collect samples from a wide range of overflow pollution input sources, including one or more of the following: domestic sewage, treated industrial wastewater discharged into the sewer system, surface runoff or pipeline sediment samples; (1.2) After solid-phase extraction pretreatment, the pollution input source samples collected in step (1.1) are subjected to FT-ICR-MS detection, and the DOM molecular group fingerprint spectrum of each pollution input source sample is calculated by DOM molecular group division and molecular formula matching analysis. The FT-ICR-MS pretreatment is as follows: First, the sample is passed through a 0.45 μm mixed fiber filter membrane to remove suspended particles, insoluble organic matter and most microorganisms; then, after passing through the membrane, high-purity hydrochloric acid is added to the sample and acidified to pH=2 to improve the extraction efficiency of phenolic and carboxyl organic matter; solid-phase extraction is performed using a PPL column to remove salt and limit artifacts generated during the FT-ICR-MS process; the amount of sample passing through the PPL column is determined according to the DOC concentration of the sample, and the DOC concentration of the eluent is controlled at about 100 mg / L; before extraction, the PPL column is activated with 10 mL of chromatographic grade methanol and 10 mL of 0.01 M HCl, and the flow rate is controlled at 2 mL·min. -1 After activation, the acidified sample (pH=2) was passed through a PPL column at a flow rate controlled at 5 mL / min. -1 The column was then rinsed with 10 mL of 0.01 M HCl at a flow rate of 2 mL / min. -1 The column was completely dried with high-purity nitrogen. The DOM enriched on the dried column was eluted into a test tube using 5 mL of chromatographic grade methanol and stored at -20℃ in the dark until analysis. (1.3) Based on step (1.2), the DOM molecular group fingerprint spectrum and molecular formula of each type of pollution input source sample are analyzed and classified; The DOM molecular formulas of samples of the same type of urban overflow pollution source are accumulated to obtain all molecular formulas appearing in several samples of this type of pollution source. The peak values ​​are obtained after weight calculation, thereby constructing the corresponding DOM molecular pool of urban overflow pollution sources of domestic sewage, treated industrial wastewater discharged into the pipe, surface runoff or pipeline sediment samples. ； Where: n——the cumulative number of samples from the same type of urban overflow pollution source; P i —The peak value corresponding to a single molecular formula in a single sample; SP i —The total peak value of all molecular formulas in a single sample; By combining the peak data corresponding to the molecular formula, the relative abundance ratio of each group component in the sample was obtained, and the molecular group distribution characteristics of each type of urban overflow pollution source DOM were obtained through comparative analysis. (2) Establish a method for tracing the source of pollution from municipal pipeline overflows, which refers to obtaining the source of pollution in the sample through matching calculation of the DOM molecular pool of urban overflows and the characteristics of DOM molecular groups, as follows: (2.1) First, the collected unknown mixed pollution source samples were pretreated by solid phase extraction and then detected by FT-ICR-MS. The DOM molecular formula and group composition characteristics of the samples were calculated by DOM molecular group division and molecular formula matching analysis. (2.2) On the one hand, based on step (2.1), the DOM molecular formula in the sample is compared with the DOM molecular pool of urban overflow pollution. The molecular formula peak values ​​of each type of pollution source molecular pool that is successfully matched are accumulated to obtain the contribution of each type of pollution source to the sample. The type of pollution source with the largest cumulative peak value is taken as the main pollution source. ； In the formula: m — the number of molecular formulas that were successfully matched; Pi – the peak value corresponding to a single molecular formula in a single sample; (2.3) On the other hand, based on step (2.1), the proportion of DOM molecular group components in the sample is compared with the distribution characteristics of DOM molecular groups of various pollution sources in urban overflow. If the proportion of several types of components in the sample DOM is within the distribution characteristic range of the molecular group of the same pollution source, the acceptable error range is 2%, then the pollution source of this type is the main pollution source in this sample. (2.4) Use the results of steps (2.2) and (2.3) to verify each other to complete the pollution source tracing; when the two results are the same, output the source tracing result directly; when the output result of step (2.3) is 0, the source tracing result of step (2.2) shall prevail; in a few cases, when the results of steps (2.2) and (2.3) conflict, the source tracing result obtained in step (2.2) shall prevail.

2. The method according to claim 1, characterized in that... In step (1.3), the FT-ICR-MS determination was specifically performed using Fourier transform ion cyclotron resonance mass spectrometry equipped with a 15.0 T superconducting magnet and an electrospray ionization source. After DOM sample pretreatment, 200 μL was taken for characterization using FT-ICR-MS in negative ion mode: at a concentration of 120 μl·h. -1 The sample was injected at a rate of -4.0 kV from the ESI source capillary. After 300 scans with an ion accumulation time of 0.06 s and an m / z scan range of 100–1600, the samples were superimposed. A signal-to-noise ratio greater than 6 was considered an effective mass spectrometry peak. The instrument was calibrated with 10 mmol / L sodium formate before sample detection, and calibrated with a known soluble organic compound as an internal standard after sample detection. After calibration, the mass error was less than 1 ppm.

3. The method according to claim 1, characterized in that... In step (1.4), the FT-ICR-MS analysis specifically involves calculating the elemental composition of each mass spectrum peak based on pre-set chemical constraints. The elemental ratios in the molecular formula must conform to 0≤H / C≤2.25 and 0≤O / C≤1.2, the double bond value must be less than 30, and the number of elements in the molecular formula must be within the range of C. 1~100 H 1~100 O 0~50 N 0~3 S 0~1 P 0-1 Then, based on the elemental composition and mass-to-charge ratio, the corresponding molecular formula information is calculated and matched. After matching, the DOM molecular formulas are grouped as follows: lipids 0 ≤ O / C < 0.3, 1.5 < H / C ≤ 2.0; proteins 0.3 ≤ O / C < 0.67, 1.5 < H / C ≤ 2.2, N / C ≥ 0.05; carbohydrates 0.67 ≤ O / C ≤ 1.2, 1.5 < H / C ≤ 2.0; unsaturated hydrocarbons 0 ≤ O / C < 0.1, 0.7 ≤ H / C ≤ 1; lignins 0.1 ≤ O / C < 0.67, 0.7 ≤ H / C ≤ 1.5, AImod < 0.67; polycyclic aromatic hydrocarbons 0 ≤ O / C ≤ 0.67, 0.2 ≤ H / C < 0.7, AImod < 0.

67. The molecular group fingerprint spectrum of DOM was finally obtained by considering the following parameters: ≥ 0.67 for tannins, 0.67 ≤ O / C ≤ 1.2, 0.5 ≤ H / C ≤ 1.5, and AImod < 0.

67.

4. The method according to claim 1, characterized in that... The domestic sewage source includes one or more of the following: kitchen wastewater, bathing wastewater, washing wastewater, and black water. The industrial wastewater that is treated and discharged into the pipeline is mainly composed of organic pollutants, specifically wastewater from the food industry, light industry, or heavy industry.

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