A method for comprehensive identification of PFAS in the environment combining targeted analysis, suspect screening, and untargeted identification

Abstract

This invention discloses a method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification. The method includes the following steps: S1, performing full-can / DDA / DIA analysis on environmental samples using liquid chromatography-high-resolution mass spectrometry (LC-HDMS); S2, performing LC-HDMS analysis on several PFAS standards; S3, collecting the names and molecular formulas of several PFAS based on publicly available chemical databases and literature, calculating their precise mass numbers, and establishing a suspicious screening database in conjunction with an open-source MS2 spectral library; S4, establishing a non-targeted identification workflow by combining the mass number characteristics, characteristic MS2 fragmentation, characteristic neutral loss, and homologue characteristics of PFAS; S5, integrating targeted analysis compounds, candidate compounds from suspicious screening, and candidate compounds from non-targeted identification to comprehensively identify PFAS in environmental samples. This invention achieves comprehensive identification of known and unknown per- and polyfluoroalkyl compounds through three complementary analytical techniques.

Description

TECHNICAL FIELD

[0001] The present invention belongs to the field of environmental analytical chemistry, and in particular relates to a method for comprehensive identification of PFAS in the environment combining targeted analysis, suspect screening and untargeted identification. BACKGROUND

[0002] Perfluoroalkyl substances (PFAS) are a class of synthetic organic compounds that have been produced since around 1940. Due to their superior properties of high stability, surface activity, oil and stain repellency, and high temperature resistance, they have been widely used in various fields such as industrial (e.g. polymer processing aids, electroplating film, aviation fuel additives, water film foam extinguishing agent), commercial (e.g. building materials, cleaning products, medical equipment) and consumer products (household textiles, non-stick cookware, food packaging materials, stain-resistant clothing) etc. PFAS have a wide variety of structures, and the basic structural feature is to contain a perfluorinated carbon chain. C-F bond is highly stable and difficult to break under normal conditions, and the large number of fluorine atoms wrapped around the carbon chain makes it difficult to expose C-C bond, so PFAS substances are almost not degraded under natural conditions and in the body. The high stability also allows them to be transported over long distances by ocean currents or the atmosphere, causing global pollution, and PFAS substances have been detected in remote areas of the North and South Poles. PFAS can bind to biological proteins, and a large number of animal experiments and population survey data have shown that PFAS has high bioaccumulation and various toxic effects including carcinogenicity. Based on the above, PFAS pollutants have been the focus of widespread concern for many years.

[0003] With the increasing research on PFAS, some substances such as perfluorooctyl sulfonate (PFOS), perfluorooctyl carboxylic acid (PFOA), perfluorohexyl sulfonate (PFHxS) and their precursor substances have been listed in the Stockholm Convention in 2009, 2019 and 2022 respectively, and their production and use are restricted globally. Accordingly, the industry has begun to turn to the production of substitutes. Due to the excellent hydrophobic and oleophobic properties and high stability of PFAS, the search for substitutes is currently mainly focused on the structural modification of traditional PFAS, such as using shorter perfluorocarbon chains or modifying perfluorocarbon chains, including H substitution, insertion of ether bond, use of unsaturated structure, etc. A few studies have reported the environmental occurrence of several alternative PFAS (such as short-chain perfluoroalkyl carboxylic acid GenX, ether bond inserted sulfonic acid PFESA), however, a large number of new PFAS structures that are being produced and used are still largely unknown. In addition, the production and use of a large number of traditional PFAS in the past 80 years have also accumulated a large number of unknown precursors and by-products in the environment. Mass balance studies found that a large amount of unknown organofluorine compounds exist in various sample types by comparing the total extractable organofluorine with the sum of the concentrations of known PFAS. For example, the proportion of unknown ingredients in water or sediments is 50% to ≥99%; the proportion of unknown ingredients in biological samples (including worms, shrimps), wild mouse blood is 15% to ≥99%; even in human blood there is a similar proportion. These unknown PFAS are a major source of uncertainty in environmental and human health risk assessment, so it is of great significance to find and characterize these unknown PFAS in environmental media. For a long time, the occurrence of environmental pollutants including PFAS in the environment has been mainly studied by targeted analysis method, that is, by using standard samples to provide characteristic information (such as chromatographic retention time and MS / MS spectrum) to realize the detection of specific compounds. Therefore, targeted analysis relying on standard samples is difficult to identify unknown PFAS. With the development of full scan high resolution mass spectrometry (HRMS) in recent years, non-targeted identification, that is, identification and structural identification of unknown pollutants in the environment without standard samples, has become possible. Its ultra-high mass resolution and accuracy are the conditions for unknown identification, providing a technical means for comprehensive identification of PFAS in complex environmental matrix (TrAC Trends in Analytical Chemistry 2019, 121).

[0004] Currently, the identification of unknown PFAS based on high-resolution mass spectrometry mainly relies on two methods: suspected substance screening (i.e., comparing compound lists) and non-targeted identification. While the former greatly expands the range of pollutants that can be identified by targeted analysis, it can only identify a limited number of PFAS, and is powerless against currently unknown PFAS, those not included in databases, or those not previously reported. The latter, on the other hand, mostly relies on the characteristic quality defects of PFAS and the characteristics of their homologues. These characteristics are particularly suitable for highly polluted samples (such as samples near organic fluorine plants, environmental samples from fire drill areas, and Scotchgard carpet cleaner), but are often very limited when dealing with routine environmental and biological samples due to interference from a large number of highly responsive background ions. In recent years, various researchers have attempted to develop different non-targeted PFAS identification strategies, such as ion source fragmentation retention time indicators based on characteristic fragments generated during PFAS fragmentation and the characteristic loss of neutrality, and machine learning-based methods for predicting suspected PFAS. However, these methods either require manual data screening, which is inefficient and yields results that vary greatly depending on the operator's experience, easily leading to missed detections; or they require specific professional knowledge to use. Finally, looking at the different methods, the studies are relatively isolated and lack methodological integration, which results in most studies only being able to detect, quantify, and identify some PFAS.

[0005] Based on the current state of research, we propose to establish a comprehensive PFAS identification method that combines targeted analysis, suspicious screening, and non-targeted identification analysis. However, establishing a simple and convenient workflow for targeted, suspicious screening, and non-targeted identification, as well as integrating multiple research strategies to maximize PFAS identification, remain pressing issues to be addressed. Summary of the Invention

[0006] To address the shortcomings of existing technologies in identifying PFAS, such as high technical requirements, insufficient integration and systematicity, difficulty in in-depth data mining, and narrow PFAS identification range, the purpose of this invention is to provide a simple and easy-to-operate comprehensive identification method for per- and polyfluoroalkyl compounds in the environment. This method combines three complementary analytical techniques: precise targeted analysis, suspicious screening based on a large database of known PFAS, and non-targeted identification based on feature fragments, neutral loss of features, quality defect features, and homologue features. This enables the full identification of known and unknown per- and polyfluoroalkyl compounds in complex matrices.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] This invention provides a method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification techniques, comprising the following steps:

[0009] S1. Perform liquid chromatography-high resolution mass spectrometry analysis on environmental samples to obtain environmental sample chromatographic-high resolution mass spectrometry data;

[0010] S2. Perform liquid chromatography-high resolution mass spectrometry analysis on several PFAS standards to obtain chromatographic-high resolution mass spectrometry data of the standards.

[0011] The chromatographic-high-resolution mass spectrometry data of the standard and the environmental sample were matched and analyzed to obtain the compound for targeted analysis;

[0012] S3. Based on publicly available chemical databases and / or literature, collect the compound names and molecular formulas of several PFAS, calculate the precise mass numbers, and combine them with the open-source MS2 spectral library to establish a suspected screening analysis database.

[0013] Based on the aforementioned suspicious screening analysis database, the chromatographic-high-resolution mass spectrometry data of the environmental samples are subjected to suspicious screening analysis to obtain candidate compounds for suspicious screening analysis;

[0014] S4. Establish a non-targeted identification workflow by combining the mass number characteristics of PFAS, characteristic MS2 fragment ions, characteristic neutral loss, and homologue characteristics.

[0015] According to the non-targeted identification workflow, non-targeted identification is performed on the chromatographic-high-resolution mass spectrometry data of the environmental sample to obtain candidate compounds for non-targeted identification.

[0016] S5. Integrate the compounds identified by the targeted analysis, the candidate compounds identified by the suspicious screening analysis, and the candidate compounds identified by the non-targeted analysis to comprehensively identify PFAS in the environmental samples.

[0017] In the above-mentioned method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification, the environmental samples include water samples, solid samples, or biological samples; the water samples include industrial wastewater, wastewater treatment plant influent and effluent, river water, surface water, seawater, drinking water, or groundwater; the solid samples include wastewater treatment plant sediment, water body sludge, sediment, soil, indoor dust, or atmospheric particulate matter; the biological samples include human breast milk, urine, serum, follicular fluid, umbilical cord blood, saliva, sweat, animal tissues and organs, fish, birds, sharks, mollusks, or plants.

[0018] In the above-mentioned method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening and non-targeted identification, the method further includes a pretreatment step for environmental samples before liquid chromatography-high resolution mass spectrometry analysis;

[0019] When the environmental sample is a water sample, the pretreatment adopts WAX column solid-phase extraction, including the following steps: 1) Before extraction, the solid-phase extraction column is activated sequentially with a methanol solution of 0.5% ammonia water, methanol, and Milli-Q water; 2) The water sample is loaded into the solid-phase extraction column activated in step 1) at a flow rate of 5-10 mL / min; 3) After loading the water sample in step 2), the extraction column is washed sequentially with Milli-Q water and 25 mM CH3COONH4 / CH3COOH buffer solution at pH 4; 4) After washing in step 3), the extraction column is eluted with a methanol solution of 0.5% ammonia water, dried, and the eluent is collected. The eluent is evaporated to near dryness under a nitrogen flow and then reconstituted with methanol.

[0020] When the environmental sample is a solid sample, the pretreatment adopts ion-pair extraction combined with solid-phase extraction, including the following steps: 1) Add 0.4M NaOH solution, 0.1M Na2CO3 / NaHCO3 buffer solution with pH 10 and concentration to the environmental sample in sequence, and 0.5M tetrabutylammonium hydrogen sulfate (TBAHS) solution; 2) Add methyl tert-butyl ether (MTBE) solution to the mixture in step 1), repeat three times, shaking for 8 hours each time; 3) Combine the MTBE layers after the three liquid-liquid separations in step 2), dry them with nitrogen, and then redissolve them with methanol; 4) Add Milli-Q water to the solution obtained in step 3), and then perform solid-phase extraction, the solid-phase extraction steps are the same as those for the water sample;

[0021] When the environmental sample is plasma, breast milk, follicular fluid, or saliva, the pretreatment adopts an organic reagent protein precipitation combined with solid-phase extraction, including the following steps: 1) adding acetonitrile to the biological liquid sample for protein precipitation; 2) after sufficient precipitation, taking the supernatant and concentrating it with nitrogen; 3) adding Milli-Q water to the solution obtained in step 2), and then performing solid-phase extraction, the solid-phase extraction steps being the same as those for the water sample.

[0022] When the environmental sample is urine or sweat, the pretreatment method is the same as the pretreatment steps for the water sample.

[0023] When the environmental sample is a tissue sample, the pretreatment adopts a combination of grinding or homogenization, organic reagent precipitation to remove proteins, and solid-phase extraction, including the following steps: 1) grinding or homogenizing the tissue sample; 2) adding acetonitrile to the sample obtained in step 1) for protein precipitation; 3) after sufficient precipitation, taking the supernatant and concentrating it with nitrogen blowing; 4) adding Milli-Q water to the solution obtained in step 3) and proceeding to solid-phase extraction, the solid-phase extraction steps being the same as those for the water sample; the tissue sample includes animal tissues and organs, fish, birds, sharks, and mollusks;

[0024] When the environmental sample is a plant, the pretreatment method is grinding or homogenization, organic reagent extraction, centrifugation, and solid-phase extraction, including the following steps: 1) grinding or homogenizing the plant sample; 2) adding methanol to the sample obtained in step 1) for extraction, wherein the extraction is performed sequentially by high-speed vortexing for 2 min, sonication for 30 min, and shaking on a shaker for 1 h; 3) centrifuging the sample obtained in step 2) at 5000 rpm for 30 min, and transferring the supernatant to a clean centrifuge tube; 4) repeating the extraction process three times; 5) combining the supernatants from the three extractions in step 4), concentrating them, then adding Milli-Q water and proceeding to solid-phase extraction, the solid-phase extraction steps being the same as those for the water sample; the plant includes leaves or stems.

[0025] In the above-described method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification, the conditions for the liquid chromatography-high resolution mass spectrometry analysis in steps S1 and S2 are as follows:

[0026] Liquid chromatography conditions: injection volume 5 μL; flow rate 0.3 mL / min; column temperature 25 °C; mobile phase consisted of an aqueous solution A containing 2 mM ammonium acetate and 2 mM 1-methylpiperidine, and a methanol solution B containing 2 mM ammonium acetate and 2 mM 1-methylpiperidine; the gradient elution program, by volume fraction, was as follows: 0 min 70% solution A and 30% solution B; 1 min 50% solution A and 50% solution B; 6 min 40% solution A and 60% solution B; 20 min 25% solution A and 75% solution B; 23 min 15% solution A and 85% solution B; 23.5 min 0% solution A and 100% solution B; 28.5 min 0% solution A and 100% solution B; 28.6 min 70% solution A and 30% solution B; 33.6 min 70% solution A and 30% solution B.

[0027] Mass spectrometry conditions: The ion source was an electrospray ionization source in negative ion mode; the spray voltage was 3500V; the ion source temperature was 300℃; Full MS / ddMS2 and Full MS / DIA modes were selected; in both modes, the MS1 resolution was set to 70000; the scan range was set to m / z = 100-1000; the MS2 resolution was set to 17500; the normalized collision energy was set to 20, 35, and 50; in ddMS2, the top 7 ions were set to perform MS2 scans (Loop count set to 7); in DIA, five mass ranges were set to perform MS2 scans, with mass ranges of m / z = 200-350, 350-500, 500-650, 650-800, and 800-950.

[0028] The chromatographic-high-resolution mass spectrometry data of the environmental samples and the chromatographic-high-resolution mass spectrometry data of the standards include chromatographic peak retention time, chromatographic peak area, primary mass spectrometry information (MS1), secondary mass spectrometry fragmentation information (MS2), and related signal intensity.

[0029] In the above-mentioned method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening and non-targeted identification techniques, the PFAS standards mentioned are 31 PFAS standards, and the purity of each standard is ≥98%.

[0030] The targeted matching analysis includes comparing the consistency of chromatographic peak retention time and mass spectrometry fragment ion information.

[0031] In the above-mentioned method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening and non-targeted identification techniques, the publicly available chemical database is the publicly available PFAS chemical database in the NORMAN Suspect List Exchange;

[0032] The number of PFAS is 4777 PFAS;

[0033] The MS2 spectral library consists of the mzCloud library and the massBank library;

[0034] The establishment of the suspected data screening analysis database was performed using Thermo Fisher's Compound Discoverer and Fluoromatch software. In Compound Discoverer, the Masslist module was used to generate an MS database for 4777 PFAS, and the mzValut module was used to load the MassBank Europe Mass Spectral Database (98525 spectra) and the MassBank of North America database (2079804 spectra). The mzCloud module also includes the mzCloud database. In Fluormatch software, the PFAS database loaded within the software was used.

[0035] In the aforementioned method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification, the suspicious screening analysis is performed on Compound Discoverer and FluoroMatch software. The Compound Discoverer workflow is as follows: In the spectrum selection module, the retention time interval is set to the default 0, and all spectra are analyzed; in the retention time alignment module, the mass deviation is set to 5 ppm; in the compound detection module, the mass deviation is set to 5 ppm, and the minimum peak intensity is set to 10000; all default negative addition ions are selected for adduct ions; in the compound classification module, the mass deviation is set to 5 ppm, the retention time deviation is set to 0.1 min, and the peak shape scoring threshold is set to 4; in the blank filling module, the mass deviation is set to 5 ppm, and the signal-to-noise ratio threshold is set to 3; in the background compound labeling module, the maximum ratio of the sample peak area to the blank peak area is set to 5, and the maximum ratio of the blank peak area to the sample peak area is set to 0; then, database comparison modules are added: “Search Masslists”, “Search mzCloud”, and “Search mzVault”; Search In the Masslists module, the retention time deviation is set to 0.1 min and the quality deviation to 5 ppm; in the Search mzCloud module, the database is set to "Autoprocessed" and "Reference". nFor the search tree (i.e., the fragment tree), select "No". For the Search DDA (i.e., DDA search) mode, select "confidence reverse". For both Match Ion Activation Mode and Match Ion Activity Energy, select "No". For the Match Factor Threshold, set it to 70. For the Search mzVault module, select "Europe Mass Spectral Database (98525spectra)" and "MassBank of North America". For Compound Class, select "All". For both Match Ion Activation Mode and Match Ion Activity Energy, select "No". For Precursor Mass To Match, set it to 5 ppm. For the Search Algorithm, set it to HighChem HihRes. For the Match Factor Threshold, set it to 70. For Use Retention, select "No". The retention time setting is set to No. For Fluoromatch software, the workflow is as follows: Select the data of pure methanol solution as the blank file; select the data of standard solution as the secondary information file, target file, and sample file; set the MS / MS and Full scan intensity thresholds to 1000; set the MS1 mass deviation to 0.005 Da; and set the MS / MS deviation to 10 ppm.

[0036] More preferably, the results of the Compound Discoverer are initially screened, with the screening criteria set as follows: "Background is fake"; in the "Masslist Matches" module, "has at least status" AND "single match found" AND "in massfile X", where X is the name of the established suspicious screening database, and "Formular" is set to "contains F"; both "mzCloud Best Match" and "mzVault Best Match" are set to "≥70", and "mzCloud Best Match Cofidence" is set to "7-10" OR "70-100"; chromatographic examination is performed on the candidate compounds obtained from the suspicious screening analysis, and the original chromatographic and mass spectrometric data are manually checked to remove candidates with poor peak shape and signal intensity comparable to the blank sample. Then, a preliminary PFAS structure type, i.e., class, is determined based on the mass number and structure type.

[0037] The results of the FluoroMatch run are initially screened. For all results rated A, B, and C, the original chromatographic and mass spectrometric data are manually checked to remove candidates with poor peak shape and signal intensity comparable to the blank sample. Then, the PFAS structure type is initially determined based on mass number and structure type, i.e., class, and classified (e.g., CF3-).

[0038] The above-mentioned method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening and non-targeted identification techniques is characterized in that: the mass number characteristic of the PFAS is negative mass defects or small positive mass defects, typically ranging from -0.15 to 0.1;

[0039] The characteristic MS2 fragment ions include CF3-, C2F5-, C3F7-, C4F9-, and C5F4-. 11 -、C6F 13 -, C3F5-, C4F7-, C5F9-, C6F 11 -, C3F3-, C4F5-, C5F7-, C6F9-, SO2F-, SO3F-, COF3-, C2F5O-, C3F7O-, C4F9O-, C3F5O-, C4F7O-, C3F3O-, C4F5O-, C5F7O-, C2F5SO2-, C3F7SO2-, C4F9SO2-, C2F6N-, C3F8N-, C4F 10 N-, C5F 12 N-, C6F 14 N-, C7F16 N-, C2F4N-, C3F6N-, C4F8N-, C5F 10 N-, C6F 12 N-, C7F 14 N-, C2F6NO-, C3F8NO-, C4F 10 NO-, C5F 12 NO-, C6F 14 NO-, C7F 16 NO-, C2F4NO-, C3F6NO-, C4F8NO-, C5F 10 NO-, C6F 12 NO-, C7F 14 NO-, C2F5SO3-, C3F7SO3-, C4F9SO3-;

[0040] The neutral loss of the features includes HF (mass number 20), H2F2 (mass number 40), H3F3 (mass number 60), H4F4 (mass number 80), and HFCO2 (mass number 64);

[0041] The homologues include a series of compounds whose mass numbers differ from CF2, C2F4, CHF, or C2H2F2.

[0042] In the above-mentioned method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening and non-targeted identification techniques, the non-targeted identification is performed on Compound Discoverer and Fluoromatch software;

[0043] For Compound Discoverer software, the workflow is as follows: In the spectrum selection module, the retention time interval is set to the default 0, and all spectra are analyzed; in the retention time alignment module, the mass deviation is set to 5 ppm; in the compound detection module, the mass deviation is set to 5 ppm, and the minimum peak intensity is set to 10000; all default negative addition ions are selected for adduct ions; in the compound classification module, the mass deviation is set to 5 ppm, the retention time deviation is set to 0.1 min, and the peak shape scoring threshold is set to 4; in the blank filling module, the mass deviation is set to 5 ppm, and the signal-to-noise ratio threshold is set to 3; in the background compound labeling module, the maximum ratio of sample peak area to blank peak area is set to 5, and the maximum ratio of blank peak area to sample peak area is set to 0; in the compound class coverage module, an MS2 characteristic fragment ion list is created, containing all fragments listed above and neutral lost mass numbers (such as CF). 3-The configuration is as follows: Signal-to-noise ratio threshold (S / N threshold) is 5, High Acc.Mass Tolerance is 15ppm, Low Acc.Mass Tolerance is 2.5mmu, Use Full MS Tree is enabled, and Allow DIA Scoring is enabled.

[0044] For Fluoromatch software, the workflow is as follows: Select data from pure methanol solution as the blank file; select data from standard solution as the secondary information file, target file, and sample file; set the MS / MS and Full scan intensity thresholds to 1000; set the MS1 mass deviation to 0.005 Da; and set the MS / MS deviation to 10 ppm.

[0045] Further preferably, for the results of the Compound Discoverer run above, data with classcoverage > 0 are filtered: ① For DDA mode data, the corresponding structure is determined by manual mass spectrometry analysis combined with other information; ② For DIA mode data, the full scan data within the corresponding mass range is viewed, and the possible PFAS precursor ions are found using the mass defect features listed above; then, target MS2 analysis is performed on these precursor ions, and if the results do not contain the MS2 characteristic fragment ions listed above or other new F-containing fragments, they are excluded; if they contain the MS2 characteristic fragment ions listed above, their structures are analyzed; for the results of the FluoroMatch run above, a preliminary screening is performed. For all results rated A, B, and C, the original chromatographic and mass spectrometric data are manually checked, and candidates with poor peak shape and signal intensity comparable to blank samples are removed. Then, based on the homologue characteristics and mass number defect features listed above, the preliminary PFAS structure type, i.e., class, is determined and classified.

[0046] In any of the methods described above for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification techniques, the integration includes:

[0047] Based on the chromatographic MS1 ion information, MS2 fragment ion information, homologue information, and retention time information of the environmental samples, the structures of the candidate compounds were inferred and confirmed.

[0048] Based on the chromatographic and mass spectrometric data of candidate compounds from the environmental samples, the list information from targeted analysis, suspicious screening, and non-targeted identification is integrated and organized into different PFAS categories. The presence of homologues of other chain lengths for each category is manually screened to obtain the final mass numbers for each PFAS category. Subsequently, the presence of the corresponding PFAS is checked in blank samples; if the signal intensity exceeds three times that of the blank, the PFAS is considered to be present in the sample. Finally, for each class, an accurate structural confidence score is assigned to each candidate compound identified as a PFAS based on factors such as the presence of structurally confirmed compounds, high-resolution database matching, clear and reasonable homologue characteristics, and the presence of characteristic quality defects.

[0049] The present invention has the following beneficial effects:

[0050] (1) Clear and simple method to establish process: This invention follows a modular process design to achieve repeatability and standardization of analysis method establishment.

[0051] (2) Wide range of identification and application scenarios: Based on real standards, a targeted analysis method applicable to both low-resolution and high-resolution mass spectrometry data has been established; a suspicious screening analysis database combining MS1 and MS2 spectral libraries has been established, capable of suspicious screening analysis of 4777 PFAS; a workflow for non-targeted identification of PFAS has been established; and the methods of targeted, suspicious screening, and non-targeted identification have been integrated, which can be implemented even without relying on standards or lacking any reference compound information. In addition, it can be applied to a variety of complex environmental and biological media (such as water samples, soil samples, plasma, etc.), providing technical support for environmental monitoring and human pollution exposure assessment.

[0052] (3) Personalized database establishment: In this invention, the suspected screening analysis database can be customized, expanded and modified according to the progress of PFAS identification research, so as to realize personalized application; the feature fragments and neutral loss of PFAS used in Class Coverage in non-targeted analysis may also appear in more forms of fragments and neutral loss as the research on PFAS progresses, and can also be increased as the research progresses to achieve more comprehensive PFAS identification.

[0053] (4) This invention combines targeted analysis, suspicious screening and non-targeted identification to comprehensively identify PFAS in the environment. The three methods complement each other and can fully identify known and unknown polyfluoroalkyl compounds in complex matrices. The types of compounds identified are comprehensive and the accuracy is high. The method has universal applicability and broad application prospects. Attached Figure Description

[0054] Figure 1 This is a flowchart of a comprehensive PFAS identification method in the environment of this invention.

[0055] Figure 2 This is a Venn diagram showing the types of PFAS identified by targeted, suspicious screening, and non-targeted methods in Embodiment 3 of the present invention.

[0056] Figure 3 This is the chromatogram and mass spectrum of Flurtamone in the sample identified in Example 3 of the present invention.

[0057] Figure 4 These are the chromatograms and mass spectra of FOSAC in the sample identified in Example 3 of this invention. Detailed Implementation

[0058] As described in the background section, how to combine targeted analysis, suspicious screening, and non-targeted identification to comprehensively mine high-resolution data and identify PFAS remains a pressing technical problem. Based on this, the present invention provides a method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification techniques, comprising the following steps: S1, performing liquid chromatography-high-resolution mass spectrometry (LC-HMS) analysis on environmental samples to obtain environmental sample LC-HMS data; S2, performing LC-HMS analysis on several PFAS standards to obtain standard LC-HMS data; performing targeted matching analysis on the LC-HMS data of the standards and the environmental samples to obtain the compounds for targeted analysis; S3, collecting the compound names and molecular formulas of several PFAS based on publicly available chemical databases and / or literature, calculating the precise mass numbers, and combining them with the open-source MS2 spectral library. A joint suspicious screening analysis database is established; based on the suspicious screening analysis database, suspicious screening analysis is performed on the chromatographic-high-resolution mass spectrometry data of the environmental samples to obtain candidate compounds for suspicious screening analysis; S4, combining the mass number characteristics of PFAS, characteristic MS2 fragment ions, characteristic neutral loss, and homologue characteristics, a non-targeted identification workflow is established; based on the non-targeted identification workflow, non-targeted identification is performed on the chromatographic-high-resolution mass spectrometry data of the environmental samples to obtain candidate compounds for non-targeted identification; S5, the candidate compounds of the targeted analysis, the candidate compounds of the suspicious screening analysis, and the candidate compounds of the non-targeted identification are integrated to comprehensively identify PFAS in the environmental samples.

[0059] Based on the above technical solutions, the method of this invention first establishes a targeted analysis method using real standards to ensure the reliability of the identification technology. Further, by collecting open-source PFAS information, a database and workflow for suspicious screening analysis are established. Finally, combining the mass number characteristics of PFAS, characteristic MS2 fragment ion information, and homologue extraction, a non-targeted identification workflow is established using software. By combining the established targeted, suspicious screening, and non-targeted methods, the complementary nature of different analytical techniques can be achieved, thereby enabling comprehensive identification of PFAS in environmental samples.

[0060] Figure 1 This is a flowchart of the comprehensive PFAS identification method in the environment of the present invention. The following is a detailed description of the method of the present invention for comprehensively identifying PFAS in the environment using targeted, suspicious screening and non-targeted identification technologies, in conjunction with the flowchart.

[0061] According to the present invention, the environmental sample can be a sample of the PFAS to be identified existing in the environment in any form, including water samples, solid samples, or biological samples; the water sample includes industrial wastewater, wastewater treatment plant influent and effluent, river water, surface water, seawater, drinking water, or groundwater; the solid sample includes wastewater treatment plant sediment, water body sludge (such as river sediment), sediment, soil, indoor dust, or atmospheric particulate matter; the biological sample includes human breast milk, urine, serum, plasma, follicular fluid, umbilical cord blood, saliva, sweat, animal tissues and organs, fish, birds, sharks, mollusks, or plants.

[0062] like Figure 1 As shown, the method also includes a pretreatment step for environmental samples, and the pretreatment method can be adjusted according to the type of environmental sample. The pretreatment methods are described in detail below for water samples and solid samples, mainly including WAX column-based solid-phase extraction and nitrogen blowing redissolution.

[0063] When the environmental sample is a water sample, the pretreatment adopts WAX column solid-phase extraction, including the following steps: 1) Before extraction, the solid-phase extraction column is activated sequentially with a methanol solution of 0.5% ammonia water, methanol, and Milli-Q water; 2) The water sample is loaded into the WAX ​​solid-phase extraction column activated in step 1) at a flow rate of 5-10 mL / min; 3) After loading the water sample in step 2), the extraction column is washed sequentially with Milli-Q water and 25 mM CH3COONH4 / CH3COOH buffer solution at pH 4; 4) After washing in step 3), the extraction column is eluted with a methanol solution of 0.5% ammonia water, dried, and the eluent is collected. The eluent is evaporated to near dryness under a nitrogen flow and then reconstituted with methanol.

[0064] As an example, the extraction column was an Oasis WAX column, specification: 6cc, 150mg. The procedure was as follows: Before extraction, the solid-phase extraction column was activated sequentially with 4 mL of 0.5% ammonia in methanol, 4 mL of methanol, and 4 mL of Milli-Q water; then, the water sample was loaded at a flow rate of 5-10 mL / min; subsequently, the extraction column was washed with 4 mL of 25 mM ammonium acetate buffer (pH=4) and 6 mL of methanol; next, the extraction column was eluted with 6 mL of 0.5% ammonia in methanol; the eluent was evaporated to near dryness under a gentle nitrogen flow and reconstituted with methanol to 1 mL;

[0065] When the environmental sample is a solid sample, the pretreatment adopts ion-pair extraction combined with solid-phase extraction, including the following steps: 1) Add 0.4M NaOH solution, 0.1M Na2CO3 / NaHCO3 buffer solution with pH 10 and concentration to the environmental sample in sequence, and 0.5M tetrabutylammonium hydrogen sulfate (TBAHS) solution; 2) Add methyl tert-butyl ether (MTBE) solution to the mixture in step 1), repeat three times, shaking for 8 hours each time; 3) Combine the methyl tert-butyl ether (MTBE layers) after the three liquid-liquid separations in step 2), dry them with nitrogen, and redissolve them with methanol. As an example, redissolve them with 500μL to 1mL (e.g., 1mL) of methanol; 4) Add Milli-Q water to the solution obtained in step 3) and proceed with solid-phase extraction. The solid-phase extraction steps are the same as those for the water sample.

[0066] As an example, taking 0.5g of freeze-dried and ground sediment as an example, the extraction column is an Oasis WAX column with specifications of 6cc and 150mg. First, 1.5ml of 0.4M NaOH solution is added (mix for 30min), followed by 2ml of 0.1M Na2CO3 / NaHCO3 buffer solution at pH 10. After thorough mixing, 1ml of 0.5M TBAHS solution is added and mixed. Then, 5ml of MTBE solution is added (repeated three times, shaking for 8h each time). The MTBE layers after the three liquid-liquid separations are combined, dried under mild nitrogen, and redissolved with 1ml of MeOH. Then, 30ml of Milli-Q pure water is added and the solid-phase extraction process is started (similar to the water sample process).

[0067] When the environmental sample is a liquid biological sample such as plasma, breast milk, follicular fluid, or saliva, the pretreatment adopts an organic reagent precipitation protein combined with solid-phase extraction, including the following steps: 1) Add acetonitrile to the biological liquid sample for protein precipitation; 2) After sufficient precipitation, take the supernatant and concentrate it with nitrogen until the volume no longer decreases significantly (e.g., concentrate to 200 μL); 3) Add Milli-Q water to the solution obtained in step 2) and then perform solid-phase extraction, the solid-phase extraction steps are the same as those for the water sample.

[0068] When the environmental sample is a low-protein liquid biological sample such as urine or sweat, the pretreatment method is the same as the pretreatment steps for the water sample.

[0069] When the environmental sample is a tissue sample, the pretreatment method employs grinding or homogenization, organic reagent precipitation of proteins, and solid-phase extraction, including the following steps: 1) grinding or homogenizing the tissue sample; 2) adding acetonitrile to the sample obtained in step 1) for protein precipitation; 3) after sufficient precipitation, taking the supernatant and concentrating it under nitrogen until the volume no longer decreases significantly (e.g., concentrating to 200 μL); 4) adding Milli-Q water to the solution obtained in step 3), followed by solid-phase extraction, the solid-phase extraction steps being the same as those for the water sample; the tissue sample includes animal tissues and organs, fish, birds, sharks, and mollusks;

[0070] When the environmental sample is a plant, the pretreatment method is grinding or homogenization, organic reagent extraction, centrifugation, and solid-phase extraction, including the following steps: 1) Grinding or homogenizing the plant sample; 2) Adding methanol to the sample obtained in step 1) for extraction (high-speed vortexing for 2 min, sonication for 30 min, and shaking on a shaker for 1 h); 3) Centrifuging the sample obtained in step 2) at 5000 rpm for 30 min, and transferring the supernatant to a clean centrifuge tube; 4) Repeating the extraction process three times; 5) Combining the supernatants from the three extractions in step 4), concentrating them until the volume no longer decreases significantly, then adding Milli-Q water and proceeding to solid-phase extraction, the solid-phase extraction steps being the same as those for the water sample; the plant includes leaves or stems.

[0071] According to the present invention, the conditions for the liquid chromatography-high resolution mass spectrometry analysis are as follows:

[0072] Liquid chromatography conditions: injection volume 5 μL; flow rate 0.3 mL / min; column temperature 25 °C; mobile phase consisted of an aqueous solution A containing 2 mM ammonium acetate and 2 mM 1-methylpiperidine, and a methanol solution B containing 2 mM ammonium acetate and 2 mM 1-methylpiperidine; the gradient elution program, by volume fraction, was as follows: 0 min 70% solution A and 30% solution B; 1 min 50% solution A and 50% solution B; 6 min 40% solution A and 60% solution B; 20 min 25% solution A and 75% solution B; 23 min 15% solution A and 85% solution B; 23.5 min 0% solution A and 100% solution B; 28.5 min 0% solution A and 100% solution B; 28.6 min 70% solution A and 30% solution B; 33.6 min 70% solution A and 30% solution B.

[0073] Mass spectrometry conditions: The ion source was an electrospray ionization source in negative ion mode; the spray voltage was 3500V; the ion source temperature was 300℃; Full MS / ddMS2 and Full MS / DIA modes were selected; in both modes, the MS1 resolution was set to 70000; the scan range was set to m / z = 100-1000; the MS2 resolution was set to 17500; the normalized collision energy was set to 20, 35, and 50; in ddMS2, the top 7 ions were set to perform MS2 scans (Loop count set to 7); in DIA, five mass ranges were set to perform MS2 scans, with mass ranges of m / z = 200-350, 350-500, 500-650, 650-800, and 800-950.

[0074] The chromatographic-high-resolution mass spectrometry data of the environmental samples and the chromatographic-high-resolution mass spectrometry data of the standards include chromatographic peak retention time, chromatographic peak area, primary mass spectrometry information (MS1), secondary mass spectrometry fragmentation information (MS2), and related signal intensity.

[0075] In the process of realizing this invention, it was discovered that the limitation in the targeted analysis process lies in the types, quantities, and purity of the available standards. Preferably, the PFAS standards described in this invention are 31 PFAS standards (perfluoropropionic acid, perfluorobutyric acid, perfluorovalerate, perfluorohexanoic acid, perfluoroheptanoic acid, perfluorooctanoic acid, perfluorononanoic acid, perfluorodecanoic acid, perfluoroundecanoic acid, perfluorododecanic acid, perfluorotridecanoic acid, perfluorotetradecanoic acid, perfluorohexadecanoic acid, perfluorooctadecanic acid, perfluorobutanesulfonic acid, perfluorohexylsulfonic acid, perfluoroheptanesulfonic acid, perfluorooctylsulfonic acid, perfluorodecylsulfonic acid, 4:2 fluoropolymer sulfonamide, 6:2 fluoropolymer sulfonamide, 8:2 fluoropolymer sulfonamide, 10:2 fluoropolymer sulfonamide, F53-B(2-[(6-chloro-1,1,2,2,3,3,4,4,5,5,6,6-dodecanohexyl)). The following standards were selected: potassium perfluoroethanesulfonate ([Oxy ...

[0076] According to the present invention, the targeted matching analysis includes comparing the consistency of chromatographic peak retention time and mass spectrometry fragment ion information. In a specific embodiment of the present invention, Xcalibur software is used to extract peaks of real standards from the collected chromatographic-high-resolution mass spectrometry data of the sample to obtain candidate compounds for targeted analysis.

[0077] In this invention, it should be noted beforehand that the suspected screening database refers to a database containing known PFAS that may exist in the environment, and these known PFAS that may exist in the environment are the suspected screening compounds. Optionally, the publicly available chemical database is a publicly available PFAS chemical database from the NORMAN Suspect List Exchange. During the implementation of this invention, it was found that the limitation in suspected screening analysis lies in the database capacity. In a specific embodiment of this invention, the plurality of PFAS refers to 4777 PFAS, which are listed below:

[0078] NS00011091 6:3Fluorotelomer carboxylic acid CAS_RN:27854-30-4;

[0079] NS00110133(2Z)-4,4,5,5,6,6,6-Heptafluoro-2-iodohex-2-en-1-ol CAS_RN:92835-92-2;

[0080] NS00109142 4,4,5,5,6,6,6-heptafluoro-2-iodohex-2-en-1-ol CAS_RN:92835-82-0;

[0081] NS00110679 Perfluoro-N,N,N',N'-tetrakis(heptafluoropropyl)-1,6-hexanediamine CAS_RN:143356-32-5; NS00110590 Ammonium perfluoro-9-(methyl)decanoate CAS_RN:3658-63-7;

[0082] NS00003821 2,3,3,3-Tetrafluoro-2-(trifluoromethyl)propanenitrile CAS_RN:42532-60-5;

[0083] NS00110675 6:2Fluorotelomer thiohydroxy ammonium chloride CAS_RN:88992-45-4;

[0084] NS00111905 5,6-dibromo-1,1,1,2,2,3,3,4,4-nonafluorohexane CAS_RN:236736-19-9;

[0085] NS00011090 2H,2H,3H,3H-Perfluorooctanoic acid CAS_RN:914637-49-3;

[0086] NS00109139 Octadecyl 2,2,3,3,4,4,4-heptafluorobutanoate CAS_RN:400-57-7;

[0087] Due to space limitations, PFAS will not be listed one by one.

[0088] The specific types of PFAS can be selected based on the chosen publicly available chemical database. The MS2 spectral library consists of the mzcloud and massbank libraries. The establishment of the suspected screening analysis database uses Thermo Fisher's Compound Discoverer and Fluoromatch software for analysis. The Masslist module generates an MS database for 4777 PFAS, and the mzValut module loads the MassBank Europe Mass Spectral Database (98525 spectra) and the MassBank of North America database (2079804 spectra). The mzCloud module includes its own mzCloud database. In Fluormatch software, the PFAS database loaded within the software is used.

[0089] According to the present invention, the suspicious screening analysis is performed on Compound Discoverer software and FluoroMatch software. The Compound Discoverer workflow is as follows: In the spectrum selection module, the retention time interval is set to the default 0, and all spectra are analyzed; in the alignment retention time module, the mass deviation is set to 5 ppm; in the compound detection module, the mass deviation is set to 5 ppm, and the minimum peak intensity is set to 10000; all default negative addition ions are selected for adduct ions; in the compound classification module, the mass deviation is set to 5 ppm, the retention time deviation is set to 0.1 min, and the peak shape scoring threshold is set to 3; in the background compound labeling module, the maximum ratio of the sample peak area to the blank peak area is set to 5, and the maximum ratio of the blank peak area to the sample peak area is set to 0; in the Search Masslists module, the retention time deviation is set to 0.1 min, and the mass deviation is set to 5 ppm; in the Search mzCloud module, the database is selected as "Autoprocessed" and "Reference", the Search MSn tree is selected as "No", the Search DDA mode is selected as "confidence reverse", and the Match Ion Activation Mode and Match Ion Activity are selected. Energy is set to No, Match FactorThreshold is set to 70; in the Search mzVault module, the databases are selected as "Europe Mass Spectral Database (98525spectra)" and "MassBank of North America", Compound Class is selected as All, Match Ion Activation Mode and Match Ion Activity Energy are set to No, Precursor MassTo Match is set to 5ppm, Search Algorithm is set to HighChem HihRes, Match FactorThreshold is set to 70, and Use Retention Time is set to No; for Fluoromatch software, the workflow is as follows: select pure methanol solution data as blank file; select standard solution data as secondary information file, target file and sample file; MS / MS and Full scan intensity thresholds are both set to 1000; MS1 mass deviation is set to 0.005Da; MS / MS deviation is set to 10ppm.

[0090] In a further preferred embodiment of the above suspicious screening analysis, the results of the Compound Discoverer are initially screened, with the following screening criteria: Background is "is fake"; "MasslistMatches" is "has at least status" AND "single match found" AND "in massfile X", where X is the name of the established suspicious screening database; "Formular" is set to "contains F"; both "mzCloud Best Match" and "mzVault Best Match" are set to "≥70", and "mzCloud Best Match" is set to "≥70". The "Cofidence" setting is set to "7-10" OR "70-100". For candidate compounds obtained from the suspicious screening analysis, chromatographic examination is performed. The original chromatographic and mass spectrometric data are manually checked, and candidates with poor peak shape and signal intensity comparable to the blank sample are eliminated. Then, a preliminary PFAS structure type (class) is determined based on mass number and structure type. The results of the FluoroMatch run are initially screened. For all results rated A, B, and C, the original chromatographic and mass spectrometric data are manually checked, and candidates with poor peak shape and signal intensity comparable to the blank sample are eliminated. Then, a preliminary PFAS structure type (class) is determined based on mass number and structure type. Taking CF3- as an example, the process is as follows: The parent ion containing CF3- fragments (or other PFAS characteristic MS2 fragment ions) is manually checked, and then its structure is analyzed by combining all MS2 fragment information of the parent ion. After structure analysis, it is classified according to mass number and structure type.

[0091] In the process of realizing this invention, it was found that non-targeted identification has no information on any reference compounds, and the difficulty in its application lies in screening and structural analysis of the acquired raw chromatographic-high-resolution mass spectrometry data.

[0092] According to the present invention, preferably, the characteristic MS2 fragment ions include CF3. - C2F5-, C3F7 - C4F9 - C5F 11 - C6F 13 - C3F5 - C4F7 - C5F9 - C6F 11 - C3F3 - C4F5 -、C5F7 - 、C6F9 - 、SO2F - 、SO3F - 、COF3 - 、C2F5O - 、C3F7O - 、C4F9O - 、C3F5O - 、C4F7O - 、C3F3O - 、C4F5O - 、C5F7O - 、C2F5SO2 - 、C3F7SO2 - 、C4F9SO2 - 、C2F6N - 、C3F8N - 、C4F 10 N - 、C5F 12 N - 、C6F 14 N - 、C7F 16 N - 、C2F4N - 、C3F6N - 、C4F8N - 、C5F 10 N - 、C6F 12 N - 、C7F 14 N - 、C2F6NO - 、C3F8NO - 、C4F 10 NO - 、C5F 12 NO - 、C6F 14 NO - 、C7F 16 NO - 、C2F4NO - 、C3F6NO - 、C4F8NO - 、C5F 10 NO - 、C6F 12 NO - 、C7F 14 NO - 、C2F5SO3 - 、C3F7SO3 - 、C4F9SO3- The neutral loss feature includes HF (mass number 20), H2F2 (mass number 40), H3F3 (mass number 60), H4F4 (mass number 80), and HFCO2 (mass number 64); the homologues include a series of compounds with mass numbers differing from CF2, C2F4, CHF, or C2H2F2; the mass number feature of the PFAS is a negative mass defect or a small positive mass defect ranging from -0.15 to 0.1; the non-targeted identification workflow is established using software CompoundDiscover or Fluoromatch.

[0093] According to the present invention, preferably, the non-targeted identification is performed on Compound Discoverer and Fluoromatch software; in Compound Discoverer software, in the spectrum selection module, the retention time interval is set to the default 0, and all spectra are analyzed; in the alignment retention time module, the mass deviation is set to 5 ppm; in the compound detection module, the mass deviation is set to 5 ppm, and the minimum peak intensity is set to 10000; all default negative addition ions are selected for adduct ions; in the compound classification module, the mass deviation is set to 5 ppm, the retention time deviation is set to 0.1 min, and the peak shape scoring threshold is set to 4; in the blank filling module, the mass deviation is set to 5 ppm, and the signal-to-noise ratio threshold is set to 3; in the background compound labeling module, the maximum ratio of the sample peak area to the blank peak area is set to 5, and the maximum ratio of the blank peak area to the sample peak area is set to 0; in the compound type coverage module, an MS2 characteristic fragment ion list is established, containing all fragments and neutral loss mass numbers listed above, and the list is set to be used for comparison; other parameters are set as follows: signal-to-noise ratio threshold (S / N) The threshold is 5, the high-resolution mass number deviation is 15 ppm, the low-resolution mass number deviation is 2.5 mmu, the use of full MS tree is enabled, and the allow DIA scoring is enabled. For Fluoromatch software, the workflow is as follows: select the data of pure methanol solution as the blank file; select the data of standard solution as the secondary information file, target file, and sample file; set the MS / MS and Full scan intensity thresholds to 1000; set the MS1 mass deviation to 0.005 Da; and set the MS / MS deviation to 10 ppm.

[0094] In a further preferred embodiment of the above non-targeted identification, for the results of the Compound Discoverer run, data with class coverage > 0 are screened: ① For DDA mode data, the corresponding structure is determined by manual mass spectrometry analysis combined with other information; ② For DIA mode data, the full scan data within the corresponding mass range is viewed, and the possible PFAS precursor ions are found using the mass defect features listed above; then, target MS2 analysis is performed on these precursor ions, and if the results do not contain the MS2 characteristic fragment ions listed above or other new F-containing fragments, they are excluded; if they contain the MS2 characteristic fragment ions listed above, their structures are analyzed; the results of the FluoroMatch run are initially screened, and for all results rated A, B, and C, the original chromatographic and mass spectrometric data are manually checked, and candidates with poor peak shape and signal intensity comparable to blank samples are removed. Then, based on the homologue characteristics and mass number defect features listed above, the PFAS structure type, i.e., class, is initially determined and classified.

[0095] According to the present invention, the integration includes: inferring and confirming the structure of candidate compounds based on the chromatographic MS1 ion information, MS2 fragment ion information, homologue information, and retention time information of the environmental samples; integrating the list information of targeted analysis, suspicious screening, and non-targeted identification based on the chromatographic and mass spectrometric data of the candidate compounds in the environmental samples, and organizing them into different PFAS categories; manually screening for the existence of homologues of other chain lengths in each category to obtain the final mass numbers of each PFAS category; subsequently checking whether the corresponding PFAS exists in the blank sample, and considering the PFAS to be present in the sample if the signal intensity exceeds 3 times that of the blank; finally, assigning an accurate structural confidence level to each candidate compound identified as a PFAS based on whether there are structurally confirmed compounds in each class, whether it can be matched with a high-resolution database, whether there are clear and reasonable homologue characteristics, and whether it exhibits characteristic mass defects. For specific confidence levels, refer to the article by Joseph et al. (Charbonnet, JA; McDonough, CA; Xiao, F.; Schwichtenberg, T.; Cao, D.; Kaserzon, S.; Thomas, KV; Dewapriya, P.; Place, BJ; Schymanski, EL; Field, JA; Helbling, DE; Higgins, CP, Communicating Confidence of Per-and Polyfluoroalkyl Substance Identification via High-Resolution Mass Spectrometry. Environ Sci Technol Lett 2022, 9, (6), 473-481.). Understandably, at a confidence level of Level 4, only the specific molecular formula of the compound can be determined, but its structure cannot; at a confidence level of Level 3, its major functional groups can be determined, but its unique true structure cannot be determined, and multiple structural isomers are possible; at a confidence level of Level 2, its major functional groups can be determined, and only one possible structure can be inferred based on the information obtained; at a confidence level of Level 1, it is the unique structure determined with the help of standards (similar to targeted analysis).

[0096] The present invention will now be described in further detail with reference to specific embodiments. The given embodiments are merely illustrative of the invention and not intended to limit its scope. The embodiments provided below can serve as a guide for further improvements by those skilled in the art and do not constitute a limitation on the invention in any way.

[0097] Unless otherwise specified, the methods used in the following embodiments are conventional methods, performed according to the techniques or conditions described in the literature in this field or according to the product instructions. Unless otherwise specified, the materials and reagents used in the following embodiments are commercially available.

[0098] The reagents, detection instruments, and detection conditions used in the following examples are as follows:

[0099] Reagents: 31 real PFAS standards are listed in Table 1 below.

[0100] Liquid Chromatography-Mass Spectrometry (LC-QE): Ultra-High Performance Liquid Chromatography (UHPLC) and High Resolution Mass Spectrometry (HMS) System. TM Mass spectrometry system (Thermo Fisher Scientific, USA); Column: Thermo Fisher Hypersil Gold C18 (1.9um, 2.1×500mm).

[0101] Liquid chromatography conditions: injection volume was 5 μL; flow rate was 0.3 mL / min; column temperature was 25 °C; the mobile phase consisted of an aqueous solution (A) containing 2 mM ammonium acetate and 2 mM 1-methylpiperidine and a methanol solution (B) containing 2 mM ammonium acetate and 2 mM 1-methylpiperidine. The specific mobile phases are shown in Table 1 below.

[0102] Table 1. Elution Procedure

[0103]

[0104] Mass spectrometry conditions: The ion source was an electrospray ionization source in negative ion mode; the spray voltage was 3500V; the ion source temperature was 300℃; Full MS / ddMS2 and Full MS / DIA modes were selected; in both modes, the MS1 resolution was set to 70000; the scan range was set to m / z = 100-1000; the MS2 resolution was set to 17500; the normalized collision energy was set to 20, 35, and 50; in ddMS2, the top 7 ions were set to perform MS2 scans (Loop count set to 7); in DIA, five mass ranges were set to perform MS2 scans, with mass ranges of m / z = 200-350, 350-500, 500-650, 650-800, and 800-950.

[0105] Example 1: Comprehensive Identification of PFAS in Spiked Test Samples

[0106] This embodiment provides a comprehensive identification of PFAS in laboratory spiked samples, focusing on establishing a methodological system to identify PFAS present in spiked samples, including the following steps:

[0107] S1. Perform liquid chromatography-high resolution mass spectrometry analysis on several PFAS standards to obtain chromatographic-high resolution mass spectrometry data of the standards. The specific steps are as follows:

[0108] 1) Common PFAS discovered in the environment were summarized through text mining, and real standard samples were purchased. As shown in Table 2, there are a total of 31 types.

[0109] Table 2. Compound names, CAS numbers, Chinese names, purity, molecular formulas, and exact mass of primary ions for 31 PFAS standards.

[0110]

[0111]

[0112]

[0113] 2) Prepare a mixed solution of the 31 real standards selected in step one, with a concentration of 100 μg / L and methanol as the solvent.

[0114] 3) The PFAS mixed solution with 31 real standards obtained in step 2) was analyzed using liquid chromatography-high resolution mass spectrometry.

[0115] Based on information from real standards, targeted analysis was performed on the chromatographic-high-resolution mass spectrometry (HPLC-MS) data of 31 real standards in a PFAS mixture. Specifically, Xcalibur software was used to extract peaks from the collected HPLC-MS data of the spiked samples. The results showed that the 31 PFAS in the mixture obtained by targeted analysis were consistent with those in the standard mixture, confirming that the PFAS in the spiked samples could be targeted and identified.

[0116] S2. Based on publicly available chemical databases, collect the compound names and molecular formulas of PFAS, calculate their precise mass numbers, and combine them with the open-source MS2 spectral library to establish a suspected PFAS screening analysis database. The specific steps are as follows:

[0117] 1) Based on the publicly available chemical database containing the NORMAN Suspect ListExchange, we collected the names, structural formulas, and precise mass numbers of primary ions of 4777 PFAS, and combined them with open-source MS2 spectral libraries (such as mzCloud and massbank) to establish a suspected screening analysis database.

[0118] 2) Analysis was performed using Thermo Fisher's Compound Discoverer (version 3.3) and Fluoromatch software. In Compound Discoverer, the Masslist module was used to generate an MS database for 4777 PFAS, and the mzValut module was used to load the MassBank Europe Mass Spectral Database (98525 spectra) and the MassBank of North America database (2079804 spectra). The mzCloud module comes with its own mzCloud database. In Fluormatch software, the PFAS database loaded within the software was used.

[0119] The chromatographic-high-resolution mass spectrometry data of the spiked samples collected in step S1 were analyzed for suspicious activity using Compound Discoverer (version 3.3) software. The procedure was as follows: In the spectrum selection module, the retention time interval was set to the default value of 0, and all spectra were analyzed. In the retention time alignment module, the mass deviation was set to 5 ppm. In the compound detection module, the mass deviation was set to 5 ppm, and the minimum peak intensity was set to 10000 to filter out impurity peaks while acquiring as much data as possible. All default negative addition ions were selected for addition ions. In the compound classification module, the mass deviation was set to 5 ppm, the retention time deviation was set to 0.1 min, and the peak shape scoring threshold was set to 4. In the blank filling module, the mass deviation was set to 5 ppm, and the signal-to-noise ratio threshold was set to 3. This module was used to fill in peaks missing due to the detection threshold. In the background compound labeling module, the maximum ratio of the sample peak area to the blank peak area was set to 5, and the maximum ratio of the blank peak area to the sample peak area was set to 0. This module was used to label background ions. In the Search Masslists module, set the retention time deviation to 0.1 min and the quality deviation to 5 ppm; in the Search mzCloud module, select "Autoprocessed" and "Reference" for the database. nTree (i.e., search fragment tree) is selected as No; Search DDA (i.e., DDA search) mode is selected as "confidence reverse"; Match Ion Activation Mode and Match Ion Activity Energy are both selected as No; Match Factor Threshold is set to 70; In the Search mzVault module, the databases are selected as "Europe Mass Spectral Database (98525spectra)" and "MassBank of North America"; Compound Class is selected as All; Match Ion Activation Mode and Match Ion Activity Energy are both selected as No; Precursor MassTo Match is set to 5ppm; Search Algorithm is set to HighChem HihRes; Match Factor Threshold is set to 70; Use RetentionTime (i.e., whether to use retention time) is set to No. After the software runs, the screening criteria are set as follows: Background is "is fake"; "Masslist Matches" is "has at least status" AND "single match found" AND "in massfile X", where X is the name of the established suspicious screening database; "Formular" is set to "contains F". "mzCloud Best Match" and "mzVault Best Match" are both set to "≥70", and "mzCloud BestMatch Cofidence" is set to "7-10" OR "70-100". After screening, chromatographic checks are performed one by one, and the original chromatographic and mass spectrometric data are manually checked to remove candidates with poor peak shape and signal intensity comparable to blank samples.

[0120] For Fluoromatch software, the workflow is as follows: Select data from a pure methanol solution as the blank file; select data from a standard solution as the secondary information file, target file, and sample file; set the MS / MS and Full scan intensity thresholds to 1000; set the MS1 mass deviation to 0.005 Da; and set the MS / MS deviation to 10 ppm. Perform initial screening on the FluoroMatch results. For all results rated A, B, and C, manually check the original chromatographic and mass spectrometric data, removing candidates with poor peak shape and signal intensity comparable to the blank sample. Then, classify the PFAS structure based on mass number and structural type.

[0121] The final suspicious case screening results showed that all added standards were in the compound list, confirming that PFAS in the spiked samples could be identified through suspicious case screening.

[0122] S3, combining PFAS mass number characteristics (negative mass defects) and characteristic MS2 fragment ion information (CF3). - C2F5-, C3F7 - C4F9 - C5F 11 - C6F 13 - C3F5 - C4F7 - C5F9 - C6F 11 - C3F3 - C4F5 - C5F7 - C6F9 - SO2F - SO3F - COF3 - C2F5O - C3F7O - C4F9O - C3F5O - C4F7O - C3F3O - C4F5O - C5F7O - C2F5SO2 - C3F7SO2 - C4F9SO2 - C2F6N - C3F8N - C4F 10 N - C5F12 N - C6F 14 N - C7F 16 N - C2F4N - C3F6N - C4F8N - C5F 10 N - C6F 12 N - C7F 14 N - C2F6NO - C3F8NO - C4F 10 NO - C5F 12 NO - C6F 14 NO - C7F 16 NO - C2F4NO - C3F6NO - C4F8NO - C5F 10 NO - C6F 12 NO - C7F 14 NO - C2F5SO3 - C3F7SO3 - C4F9SO3 - The system addresses the loss of neutral characteristics (including HF (mass number 20), H2F2 (mass number 40), H3F3 (mass number 60), H4F4 (mass number 80), HFCO2 (mass number 64)) and homologue characteristics (including a series of compounds with mass numbers differing from CF2, C2F4, CHF, or C2H2F2, and whose peak times conform to the correct retention time order). A workflow for non-targeted identification is established using algorithms or software (such as Compound Discover and Fluoromatch).

[0123] According to the non-targeted identification workflow, non-targeted identification is performed on the chromatographic-high-resolution mass spectrometry data of the spiked samples to obtain candidate compounds for non-targeted identification. This includes: running the chromatographic-high-resolution mass spectrometry data of the spiked samples collected in step S1 on Compound Discoverer and Fluoromatch software. The specific steps are as follows:

[0124] In Compound Discoverer software, in the spectrum selection module, the retention time interval is set to the default 0, and all spectra are analyzed; in the alignment retention time module, the mass deviation is set to 5 ppm; in the compound detection module, the mass deviation is set to 5 ppm, and the minimum peak intensity is set to 10000; all default negative addition ions are selected for adduct ions; in the compound classification module, the mass deviation is set to 5 ppm, the retention time deviation is set to 0.1 min, and the peak shape scoring threshold is set to 4; in the blank filling module, the mass deviation is set to 5 ppm, and the signal-to-noise ratio threshold is set to 3; in the background compound labeling module, the maximum ratio of sample peak area to blank peak area is set to 5, and the maximum ratio of blank peak area to sample peak area is set to 0; in the compound class coverage module, an MS2 characteristic fragment ion list is created, containing all fragments and neutral lost mass numbers listed above, and the list is set to be used for comparison; other parameters are set as follows: the signal-to-noise ratio threshold (S / N threshold) is 5, and the high-resolution mass number deviation (High The Acc. Mass Tolerance was 15 ppm, the Low Acc. Mass Tolerance was 2.5 mmu, Full MS Tree was enabled, and DIA Scoring was allowed. After the software ran, the results were reviewed as follows: ① For DDA mode data, the corresponding structure was determined through manual mass spectrometry analysis combined with other information; ② For DIA mode data, the full scan data within the corresponding mass range were reviewed, and the mass defect characteristics mentioned above were used to find possible PFAS precursor ions; then, target MS2 analysis was performed on these precursor ions. If the results did not contain the MS2 characteristic fragment ions mentioned above or other new F-containing fragments, they were excluded; if they contained the MS2 characteristic fragment ions mentioned above, their structures were analyzed. The results showed that all PFAS in the spiked sample were completely identified. This confirms that non-targeted identification of PFAS in the spiked sample is possible.

[0125] In Fluoromatch software, data from a pure methanol solution was selected as the blank file; data from the standard solution were selected as the secondary information file, target file, and sample file; the MS / MS and Full scan intensity thresholds were both set to 1000; the MS1 mass deviation was set to 0.005 Da; and the MS / MS deviation was set to 10 ppm. After the software run, the results were reviewed. All PFAS series in the spiked samples were classified as A, B, and C (potential PFAS compounds with clearly defined F-containing fragments or characteristic neutral loss, or with characteristic homologues), and all were completely identified. This confirms that non-targeted identification of PFAS in the spiked samples is achievable.

[0126] Through the above steps, this embodiment achieves the identification of all 31 PFAS in the standard solution, and can identify both targeted, suspicious screening and non-targeted compounds with a 100% accuracy rate. Specifically, step S2 (targeted analysis), step S3 (suspicious screening), and step S4 (non-targeted identification) can all correctly identify perfluorinated and polyfluorinated compounds in the sample. The three methods complement each other and can ensure the comprehensive identification of perfluorinated and polyfluorinated compounds in the environment to the greatest extent.

[0127] Example 2: Comprehensive Identification of PFAS in Water Samples

[0128] This embodiment provides a comprehensive method for identifying PFAS in groundwater samples. The purpose is to test the method's ability to identify PFAS in the aquatic environment, as well as to identify unknown PFAS.

[0129] The operating steps are basically the same as in Example 1. The difference is that in step S1, WAX column solid-phase extraction is used to pretreat the water sample. The specific operation is as follows:

[0130] S1. Pretreatment of the water sample: Before extraction, the solid-phase extraction column (Oasis WAX column, specification: 6cc, 150mg) was activated sequentially with 4 mL of 0.5% ammonia-methanol solution, 4 mL of methanol, and 4 mL of Milli-Q water. Then, the water sample was loaded at a flow rate of 5-10 mL / min. Next, the extraction column was washed sequentially with 4 mL of Milli-Q water and 25 mM CH3COONH4 / CH3COOH solution at pH 4. Then, the extraction column was eluted with 6 mL of 0.5% ammonia-methanol solution, dried under vacuum, and the eluent was collected. The eluent was evaporated to near dryness under a gentle nitrogen flow and redissolved in methanol to 1 mL.

[0131] The pretreated water sample was analyzed by liquid chromatography-high resolution mass spectrometry to obtain water sample chromatographic-high resolution mass spectrometry data, including the retention time of the chromatographic peak, the chromatographic peak area, the primary mass spectrometry information (MS1), the secondary mass spectrometry fragment information (MS2), and the relevant signal intensity.

[0132] S2. Same as steps 1)-3) in S1 of Example 1, prepare a PFAS mixed solution of 31 real standards, and perform liquid chromatography-high resolution mass spectrometry analysis on it to obtain the standard chromatographic-high resolution mass spectrometry data, including the chromatographic peak retention time, chromatographic peak area, primary mass spectrometry information (MS1), secondary mass spectrometry fragment information (MS2) and related signal intensity of each standard.

[0133] Matching analysis of chromatographic-high-resolution mass spectrometry data of standards and water samples was performed to obtain candidate compounds for targeted analysis. The specific steps are as follows: Xcalibur software was used to extract peaks of real standards from the collected chromatographic-high-resolution mass spectrometry data of water samples to obtain candidate compounds for targeted analysis.

[0134] S3. Same as step S2 in Example 1, except that the chromatographic-high resolution mass spectrometry data of the PFAS mixed solution of 31 real standards are replaced with the chromatographic-high resolution mass spectrometry data of the pretreated water sample to obtain candidate compounds for suspected screening analysis.

[0135] S4. Same as step S3 in Example 1, except that the chromatographic-high resolution mass spectrometry data of the PFAS mixed solution of 31 real standards are replaced with the chromatographic-high resolution mass spectrometry data of the pretreated water sample to obtain candidate compounds for non-target identification.

[0136] S5. Integrate the candidate compound information obtained in steps S2, S3, and S4. Combine the retention time information, MS1 ion information, MS2 fragment ion information, and homologue information of the spiked sample obtained in step S2 to infer and confirm the structure of the candidate compounds. Based on the chromatographic data (chromatographic peaks, retention times, etc.) and mass spectrometry data (MS1 ion information and MS2 fragment ion information) of the water sample, integrate the list information of the targeted analysis, suspicious screening, and non-targeted identification. Specifically, screen for repeated PFAS in the results of targeted analysis, suspicious screening, and non-targeted identification, and merge those of the same category into different PFAS types. Manually screen for the existence of homologues of other chain lengths for each type to obtain the final mass number of each PFAS type. Then check whether the corresponding PFAS exists in the blank sample. If the signal intensity is more than 3 times that of the blank, the PFAS is considered to be present in the sample. Finally, assign an accurate structural confidence score to each candidate compound identified as a PFAS based on whether there are compounds with confirmed structures in each class, whether they can be matched with a high-resolution database, whether there are clear and reasonable homologue characteristics, and whether they exhibit characteristic quality defects.

[0137] As shown in Table 3, the results indicate that a total of 34 PFAS were identified in the water samples in this embodiment, including traditional per / polyfluoroalkyl carboxylic acids (PFCAs), per / polyfluoroalkyl sulfonic acids (PFSAs), and emerging fluorinated telomeres (n:2FTSs), H-substituted perfluoroalkyl organic acids (H-PFCAs, H-PFSAs), and perfluoroalkyl organic acids with oxygen ether bond insertion (O-PFCAs, O-PFSAs), etc. (Table 3, targeted, suspected screening, and non-targeted identification are represented by T, S, and N, respectively). Among them, C 10 H 19 F6N2PO8S2 and C 10 H 15 F3O7 are both unknown PFAS without prior information. Both compounds are non-targeted recognitions, with scores of A- (Confident ID) and B+ (Tentative ID, highly likely PFAS), respectively.

[0138] Table 3. 34 PFAS identified in water samples

[0139]

[0140]

[0141] As shown in Table 3, the method of this invention can achieve comprehensive identification of PFAS in water samples. Among them, compounds with a confidence level of 4 have accurate molecular formulas; compounds with a confidence level of 2-3 have preliminarily inferred structures; and compounds with a confidence level of 1 have all passed the verification with real standards.

[0142] Example 3: Comprehensive Identification of PFAS in Dewatered Sludge Samples from Municipal Wastewater Treatment Plants

[0143] This embodiment provides a comprehensive method for identifying PFAS in dewatered sludge samples from municipal wastewater treatment plants. The purpose is to test the method's ability to identify PFAS in different environmental samples, as well as the overlap and complementarity of targeted, suspicious screening, and non-targeted identification methods.

[0144] The operating steps are basically the same as in Example 1. The difference is that in step S1, the dewatered sludge sample from the municipal wastewater treatment plant undergoes pretreatment, as follows:

[0145] S1. Pretreatment of dewatered sludge samples from municipal wastewater treatment plants: Take 0.5g of freeze-dried and ground powder (passed through a 100-mesh sieve). First, add 1.5ml of 0.4M NaOH solution (mix for 30min), then add 2ml of pH 10 0.1M Na2CO3 / NaHCO3 buffer solution. After thorough mixing, add 1ml of 0.5M TBAHS solution and mix. Then add 5ml of MTBE solution (repeat three times, shaking for 8h each time). Combine the MTBE layers after the three liquid-liquid separations, then dry with gentle nitrogen gas and redissolve with 1ml of MeOH. Then add 30mL of Milli-Q pure water and proceed to the solid-phase extraction process (similar to the water sample process).

[0146] Liquid chromatography-high resolution mass spectrometry (LC-HMS) was performed on the pretreated dewatered sludge samples to obtain water sample LC-HMS data, including chromatographic peak retention time, chromatographic peak area, primary mass spectrometry information (MS1), secondary mass spectrometry fragment information (MS2), and related signal intensity.

[0147] S2. Same as steps 1)-3) in S1 of Example 1, prepare a PFAS mixed solution of 31 real standards, and perform liquid chromatography-high resolution mass spectrometry analysis on it to obtain the standard chromatographic-high resolution mass spectrometry data, including the chromatographic peak retention time, chromatographic peak area, primary mass spectrometry information (MS1), secondary mass spectrometry fragment information (MS2) and related signal intensity of each standard.

[0148] Matching analysis was performed on the chromatographic-high-resolution mass spectrometry data of the standard and the dewatered sludge sample to obtain candidate compounds for targeted analysis. The specific steps are as follows: Xcalibur software was used to extract the peaks of the real standard from the chromatographic-high-resolution mass spectrometry data of the collected dewatered sludge sample to obtain candidate compounds for targeted analysis.

[0149] S3. Same as step S2 in Example 1, except that the chromatographic-high resolution mass spectrometry data of the PFAS mixed solution of 31 real standards are replaced with the chromatographic-high resolution mass spectrometry data of the pretreated dewatered sludge sample to obtain candidate compounds for suspected screening analysis.

[0150] S4. Same as step S3 in Example 1, except that the chromatographic-high resolution mass spectrometry data of the PFAS mixed solution of 31 real standards are replaced with the chromatographic-high resolution mass spectrometry data of the pretreated dewatered sludge sample to obtain candidate compounds for non-target identification.

[0151] S5. Integrate the candidate compound information obtained in steps S2, S3, and S4. Combine the retention time information, MS1 ion information, MS2 fragment ion information, and homologue information of the spiked sample obtained in step S2 to infer and confirm the structure of the candidate compounds. Based on the chromatographic data (chromatographic peaks, retention times, etc.) and mass spectrometry data (MS1 ion information and MS2 fragment ion information) of the water sample, integrate the list information of the targeted analysis, suspicious screening, and non-targeted identification. Specifically, screen for repeated PFAS in the results of targeted analysis, suspicious screening, and non-targeted identification, and merge those of the same category into different PFAS types. Manually screen for the existence of homologues of other chain lengths for each type to obtain the final mass number of each PFAS type. Then check whether the corresponding PFAS exists in the blank sample. If the signal intensity is more than 3 times that of the blank, the PFAS is considered to be present in the sample. Finally, assign an accurate structural confidence score to each candidate compound identified as a PFAS based on whether there are compounds with confirmed structures in each class, whether they can be matched with a high-resolution database, whether there are clear and reasonable homologue characteristics, and whether they exhibit characteristic quality defects.

[0152] As shown in Table 4, the results indicate that a total of 32 classes and 54 types of PFAS were identified (Table 4, with targeted, suspected screening, and non-targeted identification represented by T, S, and N, respectively); targeted, suspected screening, and non-targeted identification identified 14, 36, and 26 types of PFAS, respectively. The distribution of compounds identified by targeted, suspected screening, and non-targeted identification is shown in the figure below. Figure 2 As shown, targeted analysis identified 4 compounds, suspicious screening analysis identified 18 compounds, and non-targeted identification identified 18 compounds. Targeted and suspicious screening analyses jointly identified 9 compounds. Targeted and non-targeted identification jointly identified 6 compounds. Suspicious screening and non-targeted identification jointly identified 9 compounds. Five PFAS compounds were jointly identified by the three analytical methods. This demonstrates the complementarity and indispensability of the three methods in this comprehensive identification method, as well as its applicability in real-world environments.

[0153] The following detailed explanation of the identification process for suspicious screening and non-targeted identification, using specific cases, is provided:

[0154] Suspicious screening analysis and identification cases:

[0155] The exact mass number of the primary ion is 332.09055. Flurtamone was matched to the database through a suspicious screening analysis. Eight MS2 fragment ions (m / z 101.03960, 145.02696, 169.02676, 183.03055, 185.02219, 240.02913, 247.07439, 316.05911) conformed to the secondary spectrum of flurtamone.Figure 3 Its confidence level is classified as 2a.

[0156] Non-targeted identification case:

[0157] The precise mass number of the primary ion is 655.05689. Through non-targeted identification, typical MS2 fragment ions of PFAS, such as [O2FS]- and [C2F5]-, were found in the spectrum at this mass number. A second MS2 fragmentation of the parent ion at this mass number was performed, and further spectral examination revealed a total of four MS2 fragment ions. Figure 4 ): [C3F7]-(m / z=168.98953, mass deviation is 0.942ppm), [C4F9]-(m / z=218.98640, mass deviation is 1.107ppm), [C5F 11 ]-(m / z=268.98343, mass deviation is 1.660ppm)and[C8F 17 [-(m / z = 418.97447, mass deviation 2.547 ppm). Its chemical formula is presumed to be [C]. 16 H 16 F 17 [N2O4S]- (mass error 0.641ppm), chromatogram, MS2 mass spectra of the first and second fragmentation are as follows. Figure 4 As shown. Since isomerism cannot be ruled out, the confidence level of this structure is assigned as 3a. The name of this structure is perfluoroalkyl sulfonamido amino carboxylic acid (abbreviated FOSAC).

[0158] Table 4. 54 PFAS species identified in sediment

[0159]

[0160]

[0161] As can be seen from Table 4, the method of the present invention can achieve comprehensive identification of PFAS in solid samples, and the confidence level is all at level 3 and above, indicating that it has accurate molecular formula and preliminary inferred structure.

[0162] In summary, the results of the above embodiments collectively demonstrate that the comprehensive identification method for perfluorinated and polyfluorinated pollutants in the environment involved in this invention has high accuracy, and the targeted, suspicious screening, and non-targeted identification methods are complementary; it can be applied in complex environmental media; and it identifies a comprehensive range of compounds. Therefore, the method of this invention has universal applicability and broad application prospects.

[0163] The present invention has been described in detail above. Those skilled in the art will recognize that the invention can be practiced in a wide range of ways with equivalent parameters, concentrations, and conditions without departing from its spirit and scope. While specific embodiments have been provided, it should be understood that further modifications can be made to the invention. In summary, according to the principles of the invention, this application is intended to include any changes, uses, or improvements to the invention, including modifications made using conventional techniques known in the art that depart from the scope disclosed herein.

Claims

1. A method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification, characterized in that, Includes the following steps: S1. Perform liquid chromatography-high resolution mass spectrometry analysis on environmental samples to obtain environmental sample chromatographic-high resolution mass spectrometry data; The method further includes a pretreatment step for environmental samples before liquid chromatography-high resolution mass spectrometry analysis. When the environmental sample is a water sample, the pretreatment adopts WAX column solid-phase extraction, including the following steps: 1) Before extraction, the solid-phase extraction column is activated sequentially with a methanol solution of 0.5% ammonia water, methanol, and Milli-Q water; 2) The water sample is loaded into the WAX ​​solid-phase extraction column activated in step 1) at a flow rate of 5-10 mL / min; 3) After loading the water sample in step 2), the extraction column is washed sequentially with Milli-Q water and 25 mM CH3COONH4 / CH3COOH buffer solution at pH 4; 4) After washing in step 3), the extraction column is eluted with a methanol solution of 0.5% ammonia water, dried, and the eluent is collected. The eluent is evaporated to near dryness under a nitrogen flow and then reconstituted with methanol. When the environmental sample is a solid sample, the pretreatment adopts ion-pair extraction combined with solid-phase extraction, including the following steps: 1) Add 0.4M NaOH solution, 0.1M Na2CO3 / NaHCO3 buffer solution with pH 10 and concentration to the environmental sample in sequence, and 0.5M tetrabutylammonium hydrogen sulfate solution; 2) Add methyl tert-butyl ether solution to the mixture in step 1), repeat three times, shaking for 8 hours each time; 3) Combine the methyl tert-butyl ether layers after the three liquid-liquid separations in step 2), dry them with nitrogen, and then redissolve them with methanol; 4) Add Milli-Q water to the solution obtained in step 3), and then perform solid-phase extraction, the solid-phase extraction steps are the same as those for the water sample; When the environmental sample is plasma, breast milk, follicular fluid, or saliva, the pretreatment adopts an organic reagent protein precipitation combined with solid-phase extraction, including the following steps: 1) adding acetonitrile to the biological liquid sample for protein precipitation; 2) after sufficient precipitation, taking the supernatant and concentrating it with nitrogen; 3) adding Milli-Q water to the solution obtained in step 2) and then performing solid-phase extraction, the solid-phase extraction steps being the same as those for the water sample. When the environmental sample is urine or sweat, the pretreatment method is the same as the pretreatment steps for the water sample. When the environmental sample is a tissue sample, the pretreatment method employs grinding or homogenization, organic reagent precipitation of proteins, and solid-phase extraction, including the following steps: 1) grinding or homogenizing the tissue sample; 2) adding acetonitrile to the sample obtained in step 1) for protein precipitation; 3) after sufficient precipitation, taking the supernatant and concentrating it under nitrogen; 4) adding Milli-Q water to the solution obtained in step 3), followed by solid-phase extraction, the solid-phase extraction steps being the same as those for the water sample; the tissue sample includes animal tissues and organs, fish, birds, sharks, and mollusks; When the environmental sample is a plant, the pretreatment method employs grinding or homogenization, organic reagent extraction, centrifugation, and solid-phase extraction, including the following steps: 1) Grinding or homogenizing the plant sample; 2) Adding methanol to the sample obtained in step 1) for extraction, wherein the extraction is performed sequentially by high-speed vortexing for 2 min, sonication for 30 min, and shaking on a shaker for 1 h; 3) Centrifuging the sample obtained in step 2) at 5000 rpm for 30 min, and transferring the supernatant to a clean centrifuge tube; 4) Repeating the extraction process three times; 5) Combining the supernatants from the three extractions in step 4), concentrating them, then adding Milli-Q water and proceeding to solid-phase extraction, the solid-phase extraction steps being the same as those for the water sample; the plant includes leaves or stems. S2. Perform liquid chromatography-high resolution mass spectrometry analysis on several PFAS standards to obtain chromatographic-high resolution mass spectrometry data of the standards. Targeted matching analysis was performed on the chromatographic-high-resolution mass spectrometry data of the standard and the environmental sample to obtain the target compound. S3. Based on publicly available chemical databases and / or literature, collect the compound names and molecular formulas of several PFAS, calculate the precise mass numbers, and combine them with the open-source MS2 spectral library to establish a suspected screening analysis database. Based on the aforementioned suspicious screening analysis database, the chromatographic-high-resolution mass spectrometry data of the environmental samples are subjected to suspicious screening analysis to obtain candidate compounds for suspicious screening analysis; The publicly available chemical database is the publicly available PFAS chemical database in the NORMAN Suspect List Exchange; The number of PFAS is 4777 PFAS; The MS2 spectrum library consists of the mzCloud library and the massbank library; The establishment of the suspected screening analysis database was performed using Compound Discoverer and Fluoromatch software. In Compound Discoverer, the Masslist module was used to generate an MS database for 4777 PFAS, and the mzValut module was used to load the MassBankEuropeMass SpectralDataBase (98525 spectra) and MassBankofNorthAmerica database (2079804 spectra). The mzCloud module comes with its own mzCloud database. In Fluormatch software, the PFAS database loaded within the software was used. The suspicious screening analysis was performed using CompoundDiscoverer and FluoroMatch software. The CompoundDiscoverer workflow was as follows: In the spectrum selection module, the retention time interval was set to the default 0, and all spectra were analyzed; in the retention time alignment module, the mass deviation was set to 5 ppm; in the compound detection module, the mass deviation was set to 5 ppm, and the minimum peak intensity was set to 10000; all default negative adduct ions were selected for adduct ions; in the compound classification module, the mass deviation was set to 5 ppm, the retention time deviation was set to 0.1 min, and the peak shape scoring threshold was set to 4; in the blank filling module, the mass deviation was set to 5 ppm. m, the signal-to-noise ratio threshold is set to 3; in the background compound labeling module, the maximum ratio of sample peak area to blank peak area is set to 5, and the maximum ratio of blank peak area to sample peak area is set to 0; in the SearchMasslists module, the retention time deviation is set to 0.1 min, and the mass deviation is set to 5 ppm; in the SearchmzCloud module, the database is set to "Autoprocessed" and "Reference", SearchMSntree is set to no, SearchDDA mode is set to "confidence reverse", and MatchIonActivationMode and MatchIonActivity are selected. Energy is set to No for all options; Match Factor Threshold is set to 70. In the SearchmzVault module, the databases are "Europe Mass Spectral Database (98525 spectra)" and "MassBank of North America". Compound Class is set to All. Match Ion Activation Mode and Match Ion Activity Energy are both set to No. PrecursorMassToMatch is set to 5ppm. SearchAlgorithm is set to HighChemHihRes. MatchFactorThreshold is set to 70. UseRetentionTime is set to No. For Fluoromatch software, the workflow is as follows: Select pure methanol solution data as the blank file; select standard solution data as the secondary information file, target file, and sample file; MS / MS and Fullscan intensity thresholds are both set to 1000; MS1 mass deviation is set to 0.005Da; MS / MS deviation is set to 10ppm. S4. Establish a non-targeted identification workflow by combining the mass number characteristics of PFAS, characteristic MS2 fragment ions, characteristic neutral loss, and homologue characteristics. According to the non-targeted identification workflow, non-targeted identification is performed on the chromatographic-high-resolution mass spectrometry data of the environmental sample to obtain candidate compounds for non-targeted identification. The characteristic MS2 fragment ions include CF3-, C2F5-, C3F7-, C4F9-, C5F11-, C6F13-, C3F5-, C4F7-, C5F9-, C6F11-, C3F3-, C4F5-, C5F7-, C6F9-, SO2F-, SO3F-, COF3-, C2F5O-, C3F7O-, C4F9O-, C3F5O-, C4F7O-, C3F3O-, C4F5O-, C5F7O-, C2F5SO2-, C3F7SO2-, C4F9SO2-, C2F 6N-, C3F8N-, C4F10N-, C5F12N-, C6F14N-, C7F16N-, C2F4N-, C3F6N-, C4F8N-, C5F10N-, C 6F12N-, C7F14N-, C2F6NO-, C3F8NO-, C4F10NO-, C5F12NO-, C6F14NO-, C7F16NO-, C2F4N O-, C3F6NO-, C4F8NO-, C5F10NO-, C6F12NO-, C7F14NO-, C2F5SO3-, C3F7SO3-, C4F9SO3-; The neutral loss of the features includes HF (mass number 20), H2F2 (mass number 40), H3F3 (mass number 60), H4F4 (mass number 80), and HFCO2 (mass number 64); The homologues include a series of compounds whose mass numbers differ from CF2, C2F4, CHF, or C2H2F2; The mass number characteristic of the PFAS is a negative mass defect or a small positive mass defect with a mass defect range of -0.15 to 0.1; S5. Integrate the compounds identified by the targeted analysis, the candidate compounds identified by the suspicious screening analysis, and the candidate compounds identified by the non-targeted analysis to comprehensively identify PFAS in the environmental samples; The integration includes: Based on the chromatographic MS1 ion information, MS2 fragment ion information, homologue information, and retention time information of the environmental samples, the structures of the candidate compounds were inferred and confirmed. Based on the chromatographic and mass spectrometric data of candidate compounds from the environmental samples, the list information from targeted analysis, suspicious screening, and non-targeted identification is integrated and organized into different PFAS categories. The presence of homologues of other chain lengths for each category is manually screened to obtain the final mass numbers for each PFAS category. Subsequently, the presence of the corresponding PFAS is checked in blank samples; a signal intensity exceeding three times that of the blank is considered to indicate the presence of the PFAS in the sample. Finally, for each class, an accurate structural confidence score is assigned to each candidate compound identified as a PFAS based on the presence of structurally confirmed compounds, whether it can be matched to a high-resolution database, whether it has clear and reasonable homologue characteristics, whether it exhibits characteristic mass defects, and whether it contains characteristic MS2 fragment ions.

2. The method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification according to claim 1, characterized in that: The environmental samples include water samples, solid samples, or biological samples; the water samples include industrial wastewater, wastewater treatment plant influent and effluent, river water, surface water, seawater, drinking water, or groundwater; the solid samples include wastewater treatment plant sediment, water body sludge, sediment, soil, indoor dust, or atmospheric particulate matter; the biological samples include human breast milk, urine, serum, follicular fluid, umbilical cord blood, saliva, sweat, animal tissues and organs, fish, birds, sharks, mollusks, or plants.

3. The method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification according to claim 1 or 2, characterized in that: In steps S1 and S2, the conditions for the liquid chromatography-high resolution mass spectrometry analysis are as follows: Liquid chromatography conditions: injection volume 5 μL; flow rate 0.3 mL / min; column temperature 25 °C; mobile phase consisted of an aqueous solution A containing 2 mM ammonium acetate and 2 mM 1-methylpiperidine, and a methanol solution B containing 2 mM ammonium acetate and 2 mM 1-methylpiperidine; gradient elution program by volume fraction was as follows: 0 min 70% solution A and 30% solution B; 1 min 50% solution A and 50% solution B; 6 min 40% solution A and 60% solution B; 20 min 25% solution A and 75% solution B; 23 min 15% solution A and 85% solution B. 23.5 min 0% solution A and 100% solution B; 28.5 min 0% solution A and 100% solution B; 28.6 min 70% solution A and 30% solution B; 33.6 min 70% solution A and 30% solution B; Mass spectrometry conditions: The ion source was an electrospray ionization source in negative ion mode; the spray voltage was 3500 V; the ion source temperature was 300℃; Full MS / ddMS2 and Full MS / DIA modes were selected; the MS1 resolution was set to 70000 in both modes; the scan range was set to m / z=100-1000. The MS2 resolution was set to 17500; the normalized collision energy was set to 20, 35, and 50; in ddMS2, the top 7 ions were set to be scanned using MS2, and the loop count was set to 7; in DIA, the five mass ranges were set to be scanned using MS2, with the mass ranges being m / z = 200-350, 350-500, 500-650, 650-800, and 800-950. The chromatographic-high-resolution mass spectrometry data of the environmental samples and the chromatographic-high-resolution mass spectrometry data of the standards include chromatographic peak retention time, chromatographic peak area, primary mass spectrometry information (MS1), secondary mass spectrometry fragmentation information (MS2), and related signal intensity.

4. The method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification according to claim 1 or 2, characterized in that: The PFAS standards mentioned are 31 PFAS standards, and the purity of each standard is ≥98%. The targeted matching analysis includes comparing the consistency of chromatographic peak retention time and mass spectrometry fragment ion information.

5. The method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification according to claim 1, characterized in that: The results of the CompoundDiscoverer run were initially screened, with the following screening criteria: Background was set to "isfake"; "MasslistMatches" was set to "hasatleaststatus" AND "singlematch found" AND "in massfile X", where X is the name of the established suspicious screening database; "Formular" was set to "containsF"; "mzCloudBestMatch" and "mzVaultBestMatch" were both set to "≥ 70", and "mzCloudBestMatchCofidence" was set to "7-10" OR "70-100". Candidate compounds obtained from the suspicious screening analysis were subjected to chromatographic examination. The original chromatographic and mass spectrometric data were manually checked, and candidates with poor peak shape and signal intensity comparable to blank samples were removed. Then, preliminary PFAS structure type classification (i.e., class) was performed based on mass number and structure type. The results of the FluoroMatch run are initially screened. For all results rated A, B, and C, the original chromatographic and mass spectrometric data are manually checked to remove candidates with poor peak shape and signal intensity comparable to the blank sample. Then, the PFAS structure type is initially classified according to mass number and structure type.

6. The method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification according to claim 1 or 2, characterized in that: The non-target identification was performed using Compound Discoverer and Fluoromatch software: For CompoundDiscoverer software, the workflow is as follows: In the spectrum selection module, the retention time interval is set to the default 0, and all spectra are analyzed; in the retention time alignment module, the mass deviation is set to 5 ppm; in the compound detection module, the mass deviation is set to 5 ppm, and the minimum peak intensity is set to 10000; all default negative addition ions are selected for adduct ions; in the compound classification module, the mass deviation is set to 5 ppm, the retention time deviation is set to 0.1 min, and the peak shape scoring threshold is set to 4; in the blank filling module, the mass deviation is set to 5 ppm, and the signal-to-noise ratio threshold is set to 3; in the background compound labeling module, the maximum ratio of sample peak area to blank peak area is set to 5, and the maximum ratio of blank peak area to sample peak area is set to 0; in the compound type coverage module, an MS2 characteristic fragment ion list is created, containing all fragments and neutral lost mass numbers listed in claim 1, and the list is set to be used for comparison; other parameters are set as follows: the signal-to-noise ratio threshold (S / N threshold) is 5, and the high-resolution mass number deviation (High Acc. MassTolerance) is 15. ppm, Low Acc. Mass Tolerance is 2.5 mmu, Use Full MS Tree is Yes, Allow DIA Scoring is Yes; For Fluoromatch software, the workflow is as follows: Select data from pure methanol solution as the blank file; select data from standard solution as the secondary information file, target file, and sample file; set the MS / MS and Full scan intensity thresholds to 1000; set the MS1 mass deviation to 0.005 Da; and set the MS / MS deviation to 10 ppm.

7. The method for comprehensively identifying PFAS in the environment by combining targeted analysis, suspicious screening, and non-targeted identification according to claim 6, characterized in that: For the results of the Compound Discoverer run described in claim 6, data with class coverage > 0 are filtered: ① For DDA mode data, the corresponding structure is determined by manual mass spectrometry analysis combined with other information; ② For DIA mode data, the full scan data within the corresponding mass range is examined, and the mass defect features in claim 1 are used to find possible PFAS precursor ions; then, target MS2 analysis is performed on these precursor ions, and if the results do not contain MS2 characteristic fragment ions as described in claim 1 or other new F-containing fragments, they are excluded; if they contain MS2 characteristic fragment ions as described in claim 1, their structures are analyzed. The results of the FluoroMatch run described in claim 6 are initially screened. For all results rated A, B, and C, the original chromatographic and mass spectrometric data are manually checked to remove candidates with poor peak shape and signal intensity comparable to the blank sample. Then, based on the homologue characteristics and mass number characteristic defects in claim 1, the PFAS structure type is initially determined, i.e., classified.

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