A method for non-targeted detection of 86 hormone disruptors in aquatic ecosystems, as well as an ecological risk assessment method and a priority ranking method for hormone disruptors

Abstract

The present invention provides a method for non-targeted detection of 86 hormone disruptors in aquatic ecosystems, as well as an ecological risk assessment method and a priority control ranking method for hormone disruptors, and belongs to the field of detection. The method of the present invention comprises the following steps: a. Pretreatment of samples in aquatic ecosystems; b. Detection using ultra-high performance liquid chromatography-high resolution mass spectrometry UHPLC-HRMS. The present invention also provides a method for constructing an electronic identity information database of 86 hormone disruptors, as well as an ecological risk assessment method for hormone disruptors and a priority control ranking method for hormone disruptors. The present invention reveals the occurrence pattern, spatiotemporal evolution laws and main driving factors of HDCs in cross-interface aquatic ecosystems, conducts health risk assessment and priority control locking based on ecological risks, and fills the technical gap in the current literature that only involves environmental or food detection but no systematic ecological risk tracking.

Description

Technical Field

[0001] The present invention relates to a method for non-targeted detection of 86 hormone disruptors in aquatic ecosystems, as well as an ecological risk assessment method and a priority control ranking method for hormone disruptors, and belongs to the field of detection. Background Art

[0002] Hormone disrupting chemicals (HDCs), also known as endocrine disrupting chemicals, are a class of hormone disrupting chemicals (EDCs) with hormonal effects. Excessive exposure to them may cause human precocious puberty, breast cancer, male sperm failure toxicity and childhood leukemia. Megacities are cluster carriers of multiple factors such as population, technology, medical care and industry. With the continuous discharge of medical sewage, aquaculture wastewater and industrial wastewater in urban systems, HDCs in the water environment continue to accumulate and migrate. Traditional water purification processes are often difficult to completely remove HDCs. Residual HDCs may accumulate in aquatic foods (such as fish, shrimp, etc.) and be ingested by humans through the food chain, seriously threatening human health. However, since the detection concentration of HDCs in water environments and aquatic animals is at the trace level, coupled with the continuous emergence of potential and unknown HDCs, the differences in monitoring samples and the cumbersomeness of data analysis, this has brought huge challenges to the effective monitoring and targeted control of HDCs. At present, the extent of the erosion of hormone disruptors in the trans-interface aquatic ecosystems (water bodies-suspended matter-sediment-aquatic food) of megacities is still unclear, and the monitoring information of related studies is very limited. Therefore, we realize that it is urgent to fill this gap by constructing a universal HDCs rapid screening strategy and risk assessment method, which is crucial for effectively allocating limited resources to deal with the erosion of HDCs in trans-interface aquatic ecosystems and promoting forward-looking risk perception.

[0003] CN201610466428.4, invention name: A method for detecting and analyzing multiple endocrine disruptors in environment and food, relates to a method for detecting and analyzing multiple endocrine disruptors in environment and food, the detection and analysis method uses 4'-phosgene-rhodamine as a derivatization reagent, ultrasound-assisted-in-situ derivatization-dispersive liquid-liquid microextraction combined with ultra-high performance liquid chromatography triple quadrupole mass spectrometry to analyze multiple endocrine disruptors. The present invention uses 4'-phosgene-rhodamine containing a permanent positive charge in one molecule as a derivatization reagent for the first time to determine 23 endocrine disruptors.

[0004] CN201810345043.1, Invention Name: Magnetic solid phase extraction-HPLC-ultraviolet detection method for environmental endocrine disruptors in water samples, discloses a magnetic solid phase extraction-HPLC-ultraviolet detection method for environmental endocrine disruptors in water samples, belonging to the field of environmental monitoring technology. The detection method of the invention uses magnetic graphene oxide to adsorb and extract low-concentration EDCs in water samples, and then elutes and fixes the volume, thereby obtaining an enriched EDCs sample.

[0005] CN201810273248.3, invention name: A method for quantitatively detecting the content of different occurrence forms of endocrine disruptors in water, relates to a method for separating and detecting different forms of organic pollutants in water in the field of environmental analytical chemistry, and specifically to a method for quantitatively detecting the content of different occurrence forms of endocrine disruptors (EDCs) in water. Since previous studies generally assumed that pollutants are dissolved in water after being treated with a filtration membrane, the different forms exhibited by the combination of pollutants and colloidal microparticles were ignored. The present invention adopts a pre-treatment method of ceramic membrane filtration-ultrasound-assisted extraction-solid phase extraction for graded extraction, combined with high performance liquid chromatography-mass spectrometry (LC-MS / MS) analysis technology, to detect the content of EDCs in the particle phase, colloidal binding phase and true solution phase in water.

[0006] CN201110120299.0, invention name: a method for determining trace chlorophenol endocrine disruptors in water, the method is to first add NaH2PO4 phase separation salt to the measured water sample, then add Na2HPO4-H3PO4 buffer solution to adjust the pH value of the solution, then add [Bmim]BF4 hydrophilic ionic liquid for extraction and separation, take the ionic liquid phase after centrifuge separation, and finally determine the content of chlorophenol endocrine disruptors by high performance liquid chromatography. The present invention adopts ionic liquid as an extractant and NaH2PO4 as a phase separation salt, and utilizes ionic liquid two-phase extraction-high performance liquid chromatography (HPLC) to determine trace chlorophenol endocrine disruptors in water.

[0007] Huang Wenping, et al., Rapid simultaneous detection of 31 endocrine disrupting chemicals in environmental water by ultra-performance liquid chromatography-tandem mass spectrometry, Environmental Chemistry, April 2017, Vol. 36, No. 4. An analytical method for the simultaneous determination of 31 endocrine disrupting chemicals (EDCs) in environmental water by solid phase extraction combined with ultra-performance liquid chromatography-tandem mass spectrometry (SPE-UPLC-MS / MS) was established.

[0008] The literature reported so far only involves the detection of endocrine disruptors in environmental samples (water, soil) or food samples, and there is no research involving the simultaneous detection of coupled systems including environmental and food samples and conducting cross-interface collaborative risk studies. Summary of the invention

[0009] The present invention provides a method for non-targeted detection of 86 hormone disruptors in aquatic ecosystems, as well as an ecological risk assessment method and a priority control ranking method for hormone disruptors.

[0010] The present invention provides a method for non-targeted detection of 86 hormone disruptors in aquatic ecosystems, which comprises the following steps:

[0011] a. Pretreatment of samples in aquatic ecosystems;

[0012] b. Ultra high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) was used for detection. The chromatographic conditions were:

[0013] Column: Waters XBridge C18 (3.0 × 150 mm, 2.5 μm);

[0014] Column temperature: 40°C;

[0015] Flow rate: 0.2 mL / min;

[0016] Injection volume: 10 μL;

[0017] Mobile phase I: 1 mmol / L ammonium formate aqueous solution (containing 0.1% formic acid)-acetonitrile;

[0018] Mobile phase II: 0.01% aqueous ammonia solution-acetonitrile;

[0019] Firstly, the elution was carried out by gradient elution with mobile phase I, and then by gradient elution with mobile phase II. The elution procedure of mobile phase I was as follows:

[0020]

[0021] The elution program of mobile phase II is:

[0022]

[0023] HRMS conditions:

[0024] Ion source: HESI source; spray voltage: 3.0 kV in positive ion mode, 2.5 kV in negative ion mode; ion transfer tube temperature: 325°C; sheath gas N2 flow rate: 50 arb; auxiliary gas N2 flow rate: 10 arb; purge gas N2 flow rate: 1 arb; heating gas temperature: 350°C; RF-lens voltage: 35%; scan mode: simultaneous scanning of positive and negative ions; acquisition method: Full MS / dd-MS2; scan range: 100-1000 m / z; resolution: 60000 in primary and 15000 in secondary; automatic gain control: standard; maximum injection time: automatic; cycle count: 3 times in secondary; isolation window: 2 m / z; dynamic exclusion: 3.0 s; the energy was optimized to the best by using normalized collision energy to pump the standard solution into the needle;

[0025] The 86 hormone disruptors are:

[0026] Dehydrotestosterone, epitestosterone, fluoxymesterone, methyltestosterone, nandrolone propionate, nandrolone, testosterone propionate, trenbolone, mesandrosterone, nandrolone phenylpropionate, stanozolol, norandrostenedione, androstenedione, 17α-methylisotestosterone, mesandrosterone, epiandrosterone, 17β-hydroxyandrostan-3-one, mesandrosterone, danazol, dehydroandrostenone, allylgesterone, chlormadinone acetate, levonorgestrel, medroxyprogesterone acetate, megestrol acetate, melengestrol acetate, norethisterone, norethisterone acetate, 21-α-hydroxyprogesterone, norethindrone, 17-α-hydroxyprogesterone, beclomethasone dipropionate, betamethasone, cortisone acetate, hydrocortisone, methylprednisolone, prednisolone, triamcinolone acetonide, triamcinolone, cortisone, dexamethasone, hydrocortisone acetate beclomethasone, flumethasone, budesonide, fluocinolone acetate, fludrocortisone acetate, fluorometholone, clobetasol propionate, aldosterone, prednisone, estriol, estrone, diethylstilbestrol, diethylstilbestrol, hexestrol, estradiol, 17α-estradiol, 17β-estradiol, octylphenol, 4-nonylphenol, bisphenol A, ethinyl estradiol, α-zearalenol, β-zearalenol, zearalanone, α-zearalanol, β-zearalanol, clenbuterol, ractopamine, chlorprenaline, penbuterol, metaproterenol, formoterol, fenoterol, sebuterol, bambuterol, salbutamol, terbutaline, tolbuterol, cimaterol, mabuterol, mapentol, salmeterol, zilpaterol, bromobuterol.

[0027] Wherein, the aquatic ecosystem includes water, sediment or suspended matter in the water, and aquatic food; the pretreatment methods are respectively:

[0028] a. Water sample pretreatment: 1 L of static water sample was filtered through a 0.45 μm ultrafine glass fiber microporous filter to remove visible suspended particles, then 0.25 g Na2EDTA was added, and the pH was adjusted to 3.0±0.5 with 1 mol / L hydrochloric acid. The sample was enriched by 6 cc 200 mg Oasis®PRiME HLB solid phase extraction column, then centrifuged and dried for extraction, and eluted with 12 mL methanol solution. The eluate was combined and concentrated to 1 mL, and the extract was filtered through a 0.22 μm nylon organic phase needle microporous filter. The chromatographic injection vial was stored at -18°C.

[0029] b. Pretreatment of sediment and suspended solids: The samples were freeze-dried in the dark for 24 h, ground and homogenized through a 100-mesh sieve, 5.00 g of homogenate sample was weighed and placed in a 50 mL polypropylene centrifuge tube, 0.25 g Na2EDTA was added, mixed with pH = 3 citric acid buffer and 5 mL acetonitrile, and the samples were rapidly and vigorously shaken and vortexed for 10 min at 2000 r / min to fully disperse the samples, ultrasonically extracted for 10 min, and centrifuged at 9500 r / min for 5 min. The supernatant was taken and placed in a 50 mL polypropylene PP centrifuge tube. The above extraction process was repeated for a second extraction, and the supernatants of the two extractions were mixed and then diluted to 300 mL with Milli-Q water. The samples were purified and enriched according to the water sample pretreatment method;

[0030] c. Pretreatment of aquatic food: After slaughtering the sample, retain the edible part and homogenize it. Accurately weigh 5.00 g of the homogenate sample and place it in a 50 mL PP centrifuge tube. Add 20 mL of 80% acetonitrile aqueous solution containing 0.2% formic acid. After standing for 10 min, add two ceramic homogenizers. Shake rapidly and vigorously and vortex oscillate for 10 min at 2000 r / min to fully disperse the sample. Ultrasonic extraction is performed for 10 min. Centrifuge at 9500 r / min for 5 min. Take the supernatant for purification. Take 5 mL of the accurately measured supernatant and pass it through a 6 cc 200 mg Oasis®PRiME HLB solid phase extraction column at a flow rate of 1 drop / s. Collect 3-5 mL of the second half of the effluent and accurately measure 2 mL. Blow dry to 1 mL under nitrogen. Make up to volume with the initial mobile phase and pass through a 0.22 μm nylon organic phase needle microporous filter membrane. The chromatographic injection vial is stored at -18°C.

[0031] The present invention provides a method for constructing an electronic identity information database of 86 hormone disruptors, wherein the information database includes Chinese and English names, molecular formulas, CAS numbers, retention times, accurate mass numbers of parent ions, isotope distributions, accurate mass numbers of secondary fragments, ion adduct states, optimal normalized collision energy (HCD collision energy), and spectrum library (mzVault Library) information; the database is composed of two sections: a compound primary fingerprint identification database (Database) and a secondary HCD fragment ion characteristic spectrum library (mzVault Library);

[0032] The construction method includes the following steps:

[0033] a. Collect full scan data of the prepared 500 ng / mL mixed standard solution using the detection method, obtain the primary accurate mass number and retention time, and determine the best addition state; wherein the addition state includes [M+H]+, [MH]-, and [M+HCOO]-;

[0034] b. Set the collision energy gradient value of 5-105% with a step size of 5% in the acquisition method, collect full scan data of the prepared 500 ng / mL mixed standard solution using liquid chromatography-high-resolution mass spectrometry, and perform qualitative analysis using FreeStyle software to obtain the corresponding stable fragment ions with a relative mass deviation of <10 ppm as secondary ions and write them into the database; at the same time, select the collision energy when the primary ion response is 1 / 3 of the highest response ion among the secondary ions as the optimal collision energy and write it into the acquisition method.

[0035] The present invention provides an ecological risk assessment method for hormone disruptors, which uses a risk quotient (RQ) algorithm to assess the health risks of HDCs in aquatic ecosystems in a study area;

[0036] It includes the following steps:

[0037] Aquatic ecosystem samples were used to detect the contents of 86 hormone disruptors in aquatic ecosystems according to the described detection method, and the health risk of HDCs in aquatic ecosystems in the study area was evaluated using the RQ calculation formula;

[0038] The calculation formula of RQ is as follows: ; MEC is the measured environmental concentration and PNEC is the predicted no-effect concentration, and their values ​​can be calculated as follows: ;

[0039] EC50 and LC50 refer to the half-maximal effective concentration and the median lethal concentration respectively; NOEC and LOEC represent the no-observed-effect concentration and the lowest-observed-effect concentration respectively; AF is the assessment factor, which depends on the toxicity data and has a value of 50, 100 or 1000 for chronic toxicity;

[0040] The RQ value for assessing the risk of hormone disruptors was calculated using the following equation;

[0041]

[0042] The Kd values of HDCs detected in sediments and suspended solids were all obtained through experiments:

[0043] ;

[0044] The risk quotient (RQ) is used to evaluate the ecological risk of HDCs to aquatic organisms and is divided into three levels: low risk (RQ < 0.1), medium risk (0.1 < RQ < 1) and high risk (RQ > 1).

[0045] The present invention provides a method for prioritizing the control of hormone disruptors, which uses an optimized RQ algorithm to rank the risks of potential high-risk HDCs in order to identify and lock in the HDCs that should be preferentially controlled; the high-risk HDCs are obtained by the ecological risk assessment method of the hormone disruptors;

[0046] The algorithm is as follows:

[0047] (1)

[0048]

[0049] n and N represent the number of samples with actual concentrations exceeding PNEC and the total number of detected samples respectively; using the samples of detected HDCs, the target compounds are divided into five categories according to the risk level: high risk (PI ≥ 1), medium risk (0.1 ≤ PI < 1), tolerable risk (0.01 ≤ PI < 0.1), negligible risk (0 < PI < 0.01) and safe (PI = 0).

[0050] The beneficial effects of the present invention are:

[0051] Based on the self-built electronic identity information database of 86 HDCs, this paper developed and verified a method for non-targeted identification of 86 HDCs in aquatic ecosystems (water bodies-suspended matter-sediment-aquatic food). Based on this strategy, oriented by pollution sources and health risks, the occurrence pattern, spatiotemporal evolution and main driving factors of HDCs in cross-interface aquatic ecosystems were fully revealed, and health risk assessment and priority control based on ecological risks were also carried out. This fills the gap in the current literature that only involves environmental or food testing but no systematic ecological risk tracking, and realizes the simultaneous detection and risk collaborative research of samples across the entire chain of environment and food in aquatic ecosystems.

[0052] This paper selects Chengdu as the research area, and adopts the ultra-high performance liquid chromatography-quadrupole / electrostatic field orbital trap ultra-high resolution mass spectrometry (UHPLC-Q-OrbitrapHRMS) coupling technology with significant advantages such as high separation ability, high mass resolution and high mass accuracy. By developing a high-throughput pretreatment method for multi-target samples, a non-targeted screening strategy based on 86 HDCs electronic identity information feature databases (primary fingerprint recognition database and secondary fragment ion feature spectrum library) is constructed. This is the first high-throughput non-targeted screening and comprehensive risk characterization study of cross-interface HDCs in cross-interface aquatic ecosystems (water bodies, sediments, suspended matter and aquatic food) in megacities. Through large-scale sample analysis over a one-year period, the occurrence pattern, spatiotemporal evolution laws and main driving factors of HDCs in aquatic ecosystems are fully revealed with pollution sources and health risks as the guide. Health risk assessment and priority control based on ecological risks are also carried out. These findings are of great significance for the formulation of targeted HDCs control measures and risk management strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 The characteristic ion chromatograms of some typical HDCs are shown;

[0054] Figure 2 Workflow diagram for high-throughput non-targeted screening of HDCs;

[0055] Figure 3 The effect of different extraction columns (a) and filler amounts (b) on the recovery of 86 HDCs in different matrices;

[0056] Figure 4 For the beta-agonist cimaterol in the Thermo Accucore Vanquish C 18 (a) and WatersXBridge C 18 (b) Chromatographic analysis effect diagram;

[0057] Figure 5The chromatographic peak comparison diagram of estradiol in the acidic mobile phase (a) and the alkaline mobile phase (b);

[0058] Figure 6 Comparison of chromatographic peaks of isomers 17α-estradiol and 17β-estradiol (a), betamethasone and dexamethasone (b) in organic phase methanol (1) and acetonitrile (2);

[0059] Figure 7 It is the secondary fragmentation mass spectrum of salbutamol at the optimal collision energy (NCE=30%);

[0060] Figure 8 The extracted ion chromatograms of the isomers of three zearalanol compounds;

[0061] Fig. 9 The number of detected HDCs of four types in different environmental media (a), and GCs all (b) ERs all (c) SABAs all (d) and ARs all (e) Concentration level diagram in different environmental media;

[0062] Fig.10 The grouped bar graphs of HDCs concentrations detected in surface water (a), sediments (b), suspended solids (c), and aquatic food (d) in different seasons, and the spatial variation of total HDCs concentrations in surface water (e), sediments (f), and suspended solids (g);

[0063] Fig.11 Contribution of each factor in the PMF model of surface water (a), sediment (d) and suspended matter (g), relative abundance of each HDCs index in surface water (b), sediment (e) and suspended matter (h) to each factor, contribution of HDCs detected in surface water (c), sediment (f) and suspended matter (i) to each factor and Pearson correlation analysis;

[0064] Fig.12 Figure 2 shows the RQ values ​​of target HDCs at different locations in surface water (a), sediment (b), and suspended matter (c). DETAILED DESCRIPTION

[0065] Experimental Example 1 Method for non-targeted detection of 86 hormone disruptors in aquatic ecosystems

[0066] Experimental materials and reagents:

[0067] Acetonitrile (mass spectrometry grade), methanol (mass spectrometry grade), Orbitrap Exploris 480 ultra-high resolution mass spectrometer dedicated mass axis calibration liquid PierceTMFlexMixTM Calibration (positive and negative ion mixture), Thermo Accucore VanquishC 18 (2.1×100 mm,1.5 μm) chromatographic column, Thermo Fisher Scientific, USA; formic acid (mass spectrometry grade), ammonia (mass spectrometry grade), ammonium acetate (chromatographic grade), Sigma Aldrich, USA; ceramic homogenizer (100 / pk), 0.22 μm nylon organic phase needle microporous filter membrane, Agilent Eclipse plus C 18 (3.0 mm × 150 mm, 1.8 μm) chromatographic columns, Captiva EMR Lipid solid phase extraction columns from Agilent, USA; Oasis® HLB, Oasis® PRiME HLB solid phase extraction columns, Waters XBridge C 18 (3.0 × 150 mm, 3.5 μm) column, Waters Acquity BEH C 18 (2.1 mm × 100 mm, 1.7 μm) Chromatographic column Waters, USA; Agela Cleanert SC 18 Solid phase extraction column Tianjin Bona Aiger Technology Co., Ltd.; ultrapure water (resistivity 18.2MΩ / cm, 25℃) Millipore Corporation, USA; 0.45 μm ultrafine glass fiber microporous filter membrane Pall Corporation, USA; 100 mesh sieve (Endecotts Company, UK).

[0068] 1. Sample collection and pretreatment

[0069] Taking into account the urban functional zoning, water, sediments, suspended matter and aquatic food were collected at 15 locations including Fuhe River (FHR), Jianjiang River (JR), Jiang'an River (JAR), Minjiang River (MJR), Lujiatan (LJTL), Qinglong Lake (QLL) and Sancha Lake (SCL) in the autumn and winter of 2023 and the spring and summer of 2024.

[0070] Water sample pretreatment: 1 L of static water sample was filtered through a 0.45 μm ultrafine glass fiber microporous filter to remove visible suspended particles, then 0.25 g Na2EDTA was added, and the pH was adjusted to 3.0±0.5 with 1 mol / L hydrochloric acid. The sample was enriched by 6 cc 200 mg Oasis®PRiME HLB solid phase extraction column, then centrifuged and dried, and eluted with 12 mL of methanol solution. The eluate was combined and concentrated to 1 mL, and the extract was filtered through a 0.22 μm nylon organic phase needle microporous filter membrane. The chromatographic injection vial was stored at -18°C.

[0071] (2) Pretreatment of sediment and suspended matter: The samples were freeze-dried in the dark for 24 h, ground and homogenized through a 100-mesh sieve, and 5.00 g (accurate to 0.01 g) of the homogenate sample was weighed and placed in a 50-mL polypropylene centrifuge tube. 0.25 g Na2EDTA was added, mixed with citric acid buffer (pH = 3) and 5 mL acetonitrile, and the sample was rapidly and vigorously shaken and vortexed for 10 min (2000 r / min) to fully disperse the sample. Ultrasonic extraction was performed for 10 min, and high-speed centrifugation was performed at 9500 r / min for 5 min. The supernatant was placed in a 50-mL polypropylene (PP) centrifuge tube. The above extraction process was repeated for a second time, and the supernatants of the two extractions were mixed and then diluted to 300 mL with Milli-Q water. The sample was then purified and enriched according to the water sample pretreatment method.

[0072] (3) Pretreatment of aquatic food: After slaughtering, retain the edible part of the sample and homogenize it. Accurately weigh 5.00 g (accurate to 0.01 g) of the homogenate sample and place it in a 50 mL PP centrifuge tube. Add 20 mL of 80% acetonitrile aqueous solution (containing 0.2% formic acid). After standing for 10 min, add two ceramic homogenizers. Shake rapidly and vigorously and vortex for 10 min (2000 r / min) to fully disperse the sample. Ultrasonic extraction is performed for 10 min. Centrifuge at 9500 r / min for 5 min and the supernatant is collected for purification. Take 5 mL of accurately measured supernatant and pass it through 6 cc 200 mg Oasis®PRiME HLB solid phase extraction column at a flow rate of 1 drop / s. Collect 3-5 mL of the second half of the effluent and accurately measure 2 mL. Blow dry to 1 mL under nitrogen, make up to volume with the initial mobile phase, pass it through a 0.22 μm nylon organic phase needle microporous filter membrane, and store the chromatographic injection vial at -18°C.

[0073] The chemical information of hormone disruptors is shown in Table 1:

[0074] Table 1 Basic information of 86 HDCs reference materials

[0075]

[0076] 2.2 Instrumental analysis method

[0077] UHPLC conditions: Column: Waters XBridge C 18 (3.0 × 150 mm, 2.5 μm). Column temperature: 40°C, flow rate: 0.2 mL / min, injection volume: 10 μL; mobile phase I: 1 mmol / L ammonium formate aqueous solution (containing 0.1% formic acid)-acetonitrile, mobile phase II: 0.01% ammonia aqueous solution-acetonitrile, detailed information of the HPLC gradient elution program is shown in Table 2, and characteristic ion current chromatograms of typical hormone disruptors are shown in Figure 1 .

[0078] Table 2 Liquid chromatography gradient elution procedures for acidic and basic HDCs

[0079]

[0080] HRMS conditions: ion source: HESI source; spray voltage: 3.0 kV in positive ion mode, 2.5 kV in negative ion mode; ion transfer tube temperature: 325°C; sheath gas (N2) flow rate: 50 arb; auxiliary gas (N2) flow rate: 10 arb; sweep gas (N2) flow rate: 1 arb; heating gas temperature: 350°C; RF-lens voltage: 35%; scanning mode: simultaneous scanning of positive and negative ions; acquisition method: FullMS / dd-MS2; scanning range: 100-1000 m / z; resolution: 60000 for the first level and 15000 for the second level; Automatic gain control: standard; Maximum injection time: Auto; Loop count: 3 times for the second level; MSX number: 1; Isolation window: 2 m / z; Dynamic exclusion: 3.0 s; energy used normalized collision energy HCDCollision energy normalized (NCE, %), and the energy was optimized to the best by injecting the standard solution through a needle pump.

[0081] 2.3 Database construction and non-targeted identification

[0082] The basic information of 86 HDCs standard substances was collected, and the retention time, accurate mass number and other chromatographic mass spectral information were obtained through the Full MS full scan mode (Table 3), and imported into the database to obtain the primary accurate mass number fingerprint identification database (Database). In the dd-MS2 mode, the secondary fragment ion characteristic spectrum library (mzVaultLibrary) was obtained by cleavage under different collision energies. The detailed method of database construction is as follows:

[0083] Establish an electronic identity information database of 86 hormone disruptors, including Chinese and English names, molecular formulas, CAS numbers, retention times, accurate mass numbers of parent ions, isotope distributions, accurate mass numbers of secondary fragments, ion adduct states, optimal normalized collision energy (HCD collision energy), and spectra library (mzVault Library). It consists of two sections: the primary fingerprint database (Database) of compounds and the secondary HCD fragment ion characteristic spectra library (mzVault Library). The construction method is as follows:

[0084] The basic chemical information of 86 hormone disruptors, including their Chinese and English names, molecular formulas, CAS numbers, etc., was collected and imported into the database. The TraceFinder software automatically calculated and filled in the precise molecular weight of the compound to five decimal places based on the molecular formula.

[0085] (1) Collect full scan data of the prepared 500 ng / mL mixed standard solution using ultra-high performance liquid chromatography-high-resolution mass spectrometry to obtain the primary accurate mass number, retention time, and determine the best adduct state. The adduct states include [M+H]+, [MH]-, and [M+HCOO]-. Enter the above information into the database and acquisition method.

[0086] (2) In the acquisition method, set the collision energy gradient value from 5 to 105% with a step size of 5%. Collect full scan data of the prepared 500 ng / mL mixed standard solution using liquid chromatography-high-resolution mass spectrometry. Perform qualitative analysis using FreeStyle software to obtain corresponding stable fragment ions with a relative mass deviation of less than 10 ppm as secondary ions and write them into the database. At the same time, select the collision energy when the primary ion response is 1 / 3 of the highest response ion among the secondary ions as the optimal collision energy and write it into the acquisition method.

[0087] Based on the automatic deconvolution function of high-resolution mass spectrometry software, the self-built database was used to search and match the collected data. Suspected compound determination: ① retention time deviation is between ±0.5 min, ② accurate mass deviation is between ±5 ppm, ③ isotope distribution error is less than 20%, ④ fragment ion ≥2. Suspected compounds were further confirmed using mzVault Library, and quantitative analysis was performed using matrix-matched standard curve external standard method. The workflow of HDCs high-throughput non-targeted screening is shown in Figure 2 .

[0088] 2.3.1 Non-targeted screening criteria:

[0089] The EU (SANCO / 12495 / 2011) requires that the mass accuracy deviation of at least two confirmation ions be less than 5 ppm for confirmation of drug analysis results. The parameter settings of the screening method will directly affect the screening results and easily produce false positive and false negative test results. Therefore, in the experiment, a blank matrix standard solution and a solvent standard solution are first used for pre-screening, and the screening parameters are adjusted until all compounds in the mixed standard are screened out.

[0090] The recommended value of the ion peak intensity threshold (Threshold Override) is 5000, because the response of environmental impurities is usually less than 5000. However, during the sample screening process, when the content of hormone disruptors in the sample is low or the matrix effect is strong, the response may be less than 5000, so this threshold is not set during screening to avoid missed detection. However, this threshold can be set during fragment ion screening to exclude impurity interference.

[0091] The retention time window (Window Override) was set to 30 sec. Retention time is an important indicator for identifying compounds. In this experiment, the peak times of 65 hormone disruptors using ultra-high performance liquid chromatography were concentrated in the first 20 min. Based on experimental accumulation, it was set to 30 sec, and the retention time was optimally expanded by 15 sec.

[0092] Mass Tolerance Electrostatic field orbital trap mass spectrometry can measure the precise mass to charge ratio of a compound. According to experimental results, the theoretical mass to charge ratio and the measured mass to charge ratio often do not differ by more than 5 ppm, so the mass accuracy window of the parent ion is set to 5 ppm. The accuracy window of the secondary ion fragments is appropriately enlarged to 10 ppm, because in actual sample screening, the sample matrix, concentration and other factors may interfere with the collision-generated secondary fragments, and the fragment intensity may be low, but the deviation generally does not exceed 10 ppm.

[0093] Non-targeted qualitative screening mainly uses the created parent ion accurate mass-to-charge ratio database and high-resolution fragment ion mass spectrum database as reference, assisted by retention time and isotope distribution characteristics, and four conditions are used for screening. The key parameters are set as follows:

[0094] The precursor ion is used as the screening condition: Threshold Override peak intensity threshold: not enabled; S / N RatioThreshold signal-to-noise ratio threshold: 5.0; Mass Tolerance mass-to-charge ratio deviation allowable range: 5 ppm.

[0095] Retention time as screening condition: Window Override: Retention time deviation window threshold 30 sec.

[0096] The screening conditions for product ions are as follows: the minimum number of matching fragments is 2; Intensity Threshold: peak intensity threshold is 5000; Mass Tolerance: the mass-to-charge ratio deviation is allowed to be 10 ppm.

[0097] Isotope peak pattern as screening condition: Fit Threshold (%) similarity: 80%; Allowed Mass Deviation (ppm): 5 ppm; Allowed Intensity Deviation (%): 20%.

[0098] If all four conditions are met, it can be determined that the target compound exists in the sample to be tested. If none of them are met, it can be determined that it is not detected. If some items are not met, manual analysis will be performed according to the specific situation.

[0099] In order to verify the scientificity and accuracy of the screening parameter setting, the experiment selected three blank matrices of water, sediment and shrimp, added 86 mixed standard stock solutions of hormone disruptors, tested them on the machine according to the experimental conditions, and pre-screened them using the established database. The experiment found that all 86 hormone disruptors can be fully matched through automatic screening by Trace Finder General 5.1.

[0100] 2.3.2 Theoretical accurate mass and secondary mass spectrometry conditions:

[0101] Theoretical accurate mass: 49 of the 86 hormone disruptors responded in positive ion mode, and the parent ions were all [M+H] + ; 37 compounds responded in negative ion mode, of which 22 compounds had parent ions of [M+HCOO] - , the parent ions of 15 compounds are [MH] -Table 3 lists the theoretical accurate mass numbers of 86 hormone disruptors, and verifies them by comparing the data of the first-level full scan of the standard substances. As can be seen from the table, the relative mass deviations of the 86 hormone disruptors are all less than 5 ppm, proving that the mass accuracy of the target compounds is very good and meets the qualitative requirements.

[0102] Secondary mass spectrometry conditions: The target compound parent ion accurate mass is obtained by full scan, and the target list is set according to the obtained accurate mass. The parent ions in the list are only found in the primary mass spectrometry scan and their intensity reaches the set threshold (1×10 5 ), the secondary mass spectrometry scan can be automatically collected. However, during the experiment, it was found that the number of secondary mass spectrometry collection points of some substances was too small, and some isomeric substances could only collect the secondary mass spectra of one of the substances. The possible reasons were related to the poor setting range of dynamic exclusion parameters or factors such as apex trigger. Better fragment ion information was obtained by optimizing parameters such as dynamic exclusion, apex trigger and TopN. First, by adjusting the dynamic exclusion, it was found that the best dynamic exclusion time was half peak width, and 6 s and 3 s were optimized. However, due to the different effects of the width of 86 hormone disruptors, the dynamic exclusion time was finally determined to be 3 s according to most peaks. Secondly, it was found that apex excitation (Apextrigger) would also affect the collection effect of secondary mass spectrometry. The principle is to set a time range according to the peak width of the chromatographic peak, delay a period of time after the peak, and then collect the secondary mass spectrum, so that the time of triggering MS2 is as close as possible to the top of the chromatographic peak to obtain high-quality MS2 spectra. However, since there are many compounds tested in this experiment, the peak widths are not completely consistent, so the set period of time cannot guarantee that all compounds will excite the secondary at the peak apex, so it is better not to enable this function. Therefore, the analysis results contain both the accurate mass number of the parent ion and the secondary fragment ion information, which improves the accuracy of qualitative analysis and greatly reduces the probability of false positives. The parent ion, fragment ion and other information of 86 hormone disruptors are shown in Table 3.

[0103] 2.3.3 Isotope characteristic abundance analysis:

[0104] In screening analysis, in addition to relying on the precise mass-to-charge ratio, retention time and other parameters of the target compound for differentiation, the isotope characteristic distribution can also be used to improve the performance of the screening method. For compounds with isotope patterns, the abundance of each peak in the mass spectrum is related to the number of atoms of the isotope element present in the ion and the natural abundance of each isotope, from which the presence or absence of a certain element in the sample can be inferred. The isotope peak intensity of the quasi-molecular ion peak can be calculated by the expansion of the binomial. In the formula, a represents the relative abundance of the light isotope; b represents the relative abundance of the heavy isotope; and n represents the number of atoms of the isotope element in the molecule.

[0105]

[0106] In the TranceFinder system, the abundance ratio can be directly calculated by software. Most of the hormone compounds screened this time contain C, H, O, N, Cl, etc. These elements have multiple isotopes such as: 16 O (99.756%), 17 O (0.039%), 18 O (0.205%), 14 N (99.64%), 15 N (0.36%), etc. If the exact mass and abundance ratio of the isotope peak in the analyte match the calculated data, it means that the analyte is likely to exist in the sample. If the exact mass of the isotope peak of a substance in the analyte can match but the abundance ratio of its second isotope peak does not match, further confirmation is required based on information such as fragment ions.

[0107] 2.3.4 Theoretical accurate mass and secondary mass spectrometry conditions

[0108] Theoretical accurate mass: 49 of the 86 hormone disruptors responded in positive ion mode, and the parent ions were all [M+H] + ; 37 compounds responded in negative ion mode, of which 22 compounds had parent ions of [M+HCOO] - , the parent ions of 15 compounds are [MH] - Table 3 lists the theoretical accurate mass numbers of 86 hormone disruptors, and verifies them by comparing the data of the first-level full scan of the standard substances. As can be seen from the table, the relative mass deviations of the 86 hormone disruptors are all less than 5 ppm, proving that the mass accuracy of the target compounds is very good and meets the qualitative requirements.

[0109] Secondary mass spectrometry conditions: The target compound parent ion accurate mass is obtained by full scan, and the target list is set according to the obtained accurate mass. The parent ions in the list are only found in the primary mass spectrometry scan and their intensity reaches the set threshold (1×10 5), the secondary mass spectrometry scan can be automatically collected. However, during the experiment, it was found that the number of secondary mass spectrometry collection points of some substances was too small, and some isomeric substances could only collect the secondary mass spectra of one of the substances. The possible reasons were related to the poor setting range of dynamic exclusion parameters or factors such as apex trigger. Better fragment ion information was obtained by optimizing parameters such as dynamic exclusion, apex trigger and TopN. First, by adjusting the dynamic exclusion, it was found that the best dynamic exclusion time was half peak width, and 6 s and 3 s were optimized. However, due to the different effects of the width of 86 hormone disruptors, the dynamic exclusion time was finally determined to be 3 s according to most peaks. Secondly, it was found that apex excitation (Apextrigger) would also affect the collection effect of secondary mass spectrometry. The principle is to set a time range according to the peak width of the chromatographic peak, delay a period of time after the peak, and then collect the secondary mass spectrum, so that the time of triggering MS2 is as close as possible to the top of the chromatographic peak to obtain high-quality MS2 spectra. However, since there are many compounds tested in this experiment, the peak widths are not completely consistent, so the set period of time cannot guarantee that all compounds will excite the secondary at the peak apex, so it is better not to enable this function. Therefore, the analysis results contain both the accurate mass number of the parent ion and the secondary fragment ion information, which improves the accuracy of qualitative analysis and greatly reduces the probability of false positives. The parent ion, fragment ion and other information of 86 hormone disruptors are shown in Table 3.

[0110] Table 3 Chromatographic mass spectrometric fingerprint identification and characteristic spectrum database of 86 HDCs

[0111]

[0112] X means there is no fragment or the fragment is not representative of the characteristics, and the primary precursor ion combined with the retention time and isotope distribution is used for qualitative analysis.

[0113] 2.4 Ecological risk assessment of HDCs

[0114] The risk quotient (RQ) algorithm was used to assess the health risks of HDCs in the aquatic ecosystem of the study area, and the derivation of predicted no-effect concentrations (PNECs) and their related toxicity data are shown in Table 4 .

[0115] Table 4 Derivation of predicted toxicity data from no-effect concentrations (PNECs)

[0116]

[0117] S8 Calculation of the Risk Quotient (RQ) for HDCs

[0118] The risk quotient (RQ) is used to assess the ecological risk of HDCs to aquatic organisms and is divided into three levels: low risk (RQ < 0.1), medium risk (0.1 < RQ < 1) and high risk (RQ > 1). The calculation formula for RQ is as follows:

[0119]

[0120] MEC is the measured environmental concentration and PNEC is the predicted no-effect concentration, and their values ​​can be calculated as follows:

[0121]

[0122] EC50 and LC50 refer to half maximal effective concentration and half lethal concentration, respectively. NOEC and LOEC stand for no observed effect concentration and lowest observed effect concentration, respectively. AF is an assessment factor that depends on toxicity data and has a value of 50, 100 or 1000 for chronic toxicity.

[0123] The RQ value for assessing the risk of hormone disruptors was calculated using the following equation.

[0124]

[0125] All toxicity data for HDCs were obtained from

[0126] 1. United States Environmental Protection Agency (US EPA) ECOTOX database (https: / / cfpub.epa.gov / ecotox / search.cfm)

[0127] 2. NORMAN Ecotoxicology Database (https: / / www.norman-network.com / nds / ecotox / lowestPnecsIndex.php)

[0128] 3. United States Environmental Protection Agency (US EPA) (ECOSAR) model (v2.0, USEPA)

[0129] The Kd values ​​of HDCs detected in sediments and suspended solids were obtained experimentally:

[0130]

[0131] 2.5 Priority control ranking of HDCs

[0132] The optimized RQ algorithm is used to rank the risks of potential high-risk HDCs to identify and lock in the HDCs that should be prioritized for control.

[0133] To identify the HDCs that should be prioritized for control, the present invention introduces an optimized risk quotient method based on the average RQ value (RQM) and the frequency (F) of the measured concentration of individual HDCs exceeding the PNEC, and systematically evaluates and ranks the potential high-risk HDCs to determine the compounds that need to be prioritized for management.

[0134]

[0135]

[0136] In the present invention, n and N represent the number of samples with actual concentrations exceeding the PNEC and the total number of detected samples, respectively. To more accurately reflect the actual risk situation of the samples and avoid diluting the risk assessment results, the present invention uses only the samples in which HDCs are detected. The target compounds are divided into five categories according to the risk level: high risk (PI ≥ 1), medium risk (0.1 ≤ PI < 1), tolerable risk (0.01 ≤ PI < 0.1), negligible risk (0 < PI < 0.01), and safe (PI = 0).

[0137] 2.6 Data analysis

[0138] Xcalibur 4.4, Freestyle 1.8, and TraceFinder 5.1 (Thermo Fisher Scientific) are used for data acquisition, qualitative screening, and confirmation and quantification, respectively; SPSS v25.0 (SPSS Inc., MA) and Origin 2018 (OriginLab Corporation, MA) are used for Spearman correlation and principal component analysis (PCA); the positive matrix factorization model (PMF5.0) of the US Environmental Protection Agency (USEPA) is used for source analysis of HDCs, and the spatial distribution of HDCs in water, sediment, and suspended solids is generated through ArcGIS 10.8.

[0139] 3 Results and discussion

[0140] 3.1 Selection of extraction columns for sample pretreatment

[0141] Using the collected aquatic ecosystem samples as the research matrix, Agela Cleanert SC 18 , Oasis HLB, Oasis PRiME HLB, and Captiva EMR Lipid four extraction columns 25–28Adsorption and purification effect of hormone disruptors in different matrices ( Figure 3 a) It was found that the average recovery rate of hormone disruptors in each matrix was the highest when Oasis PRIME HLB was used. The adsorption and purification effects of different filler dosages of Oasis PRIME HLB (1 cc 30 mg / 3 cc 60 mg / 3 cc 150 mg / 6cc 200 mg / 6 cc 500 mg) were further investigated ( Figure 3 b) It was found that the average recovery of hormone disruptors in each matrix was the highest when the filler amount was 6 cc 200 mg.

[0142] 3.2 Customization of instrument analysis conditions

[0143] 3.2.1 Selection of chromatographic columns

[0144] Thermo Accucore Vanquish C 18 (2.1×100 mm, 1.5 μm), AgilentEclipse plus C 18 (3.0 mm × 150 mm, 1.8 μm) and Waters Acquity BEH C 18 (2.1 mm × 100 mm, 1.7 μm) and Waters XBridge C 18 The separation effects of four different chromatographic columns (3.0 × 150 mm, 2.5 μm) on 86 hormone disruptors were compared. It was found that the first three columns had different degrees of peak tailing and poor sharpness, while the Waters XBridge C 18 The chromatographic peak shape has no obvious tailing and is sharp and symmetrical, which can maximize the effective separation of 86 hormone disruptors at the same time. For example, the peak shape of the typical hormone CMT is well improved ( Figure 4 ), which may be compatible with WatersXBridge C 18 The unique bonding method of the chromatographic column is related to the end-capping technology.

[0145] 3.2.2 Selection of mobile phase

[0146] The composition and ratio of the mobile phase will affect the chromatographic results. Some hormone disruptors in the present invention can only elute in alkaline or acidic mobile phases. For example, E2 does not elute in an acidic mobile phase (0.1% formic acid water + acetonitrile), but elutes in an alkaline mobile phase (0.01% ammonia water + acetonitrile). Figure 5), so both acidic and alkaline mobile phases were used simultaneously; in addition, it was found that when acetonitrile was used as the organic phase, all isomers could achieve baseline separation. The peak shapes of typical isomers in different organic mobile phases are shown in Figure 6 When investigating 0.1% formic acid water + acetonitrile as the acidic mobile phase, it was found that some hormone disruptors were difficult to peak, so 5, 2 and 1 mmol / L ammonium formate were added to 0.1% formic acid water, and it was found that the baseline separation and response effects were best when 1 mmol / L ammonium formate was added to 0.1% formic acid water.

[0147] 3.2.3 Selection of HRMS parameters

[0148] The present invention compares Full MS, Full MS / dd-MS 2 and Target-SIM / dd-MS 2 Three scanning modes: Full MS is prone to false positive results; Target-SIM / dd-MS 2 Lack of some non-targeted information; Full MS / dd-MS 2 A first-level full-scan mass spectrum can be obtained, and the relative deviations of the accurate masses of 86 HDCs meet the requirements. To ensure the best acquisition interval, when the resolution (R1=60000, R2=15000) is optimized and selected, all 86 HDCs are baseline separated, meeting the experimental requirements. The size of the collision energy has a direct relationship with the acquisition of characteristic fragment ions. When the HDCs are fragmented using the NCE energy gradient data-dependent acquisition technology, it is found that the optimal collision energy of compounds such as Estradiol (100%) is much greater than 50%, and compounds such as Triamcinolone (10%) will be cracked at lower collision energies. Therefore, the present invention uses different NCE energy gradients (10%-100%), and the SBT fragment mass spectrum at the optimal collision energy is shown in FIG. Figure 7 The collision energies of 86 HDCs are shown in Table 3.

[0149] 3.3 Identification of isomers and methodological evaluation

[0150] 3.3.1 Identification of isomers

[0151] Effective identification of isomeric components with the same molecular formula and mass number and similar structure is an important guarantee for rapid screening. 13 groups of isomeric substances were found in the database, including 1 group of quaternary isomeric substances, 4 groups of ternary isomeric substances, and 8 groups of binary isomeric substances. The established UHPLC-Q / Orbitrap HRMS instrumental analysis method was used for chromatographic separation, and isomeric substances were identified based on the retention time. Under this method, the 13 groups of isomeric substances can be baseline separated and can be effectively distinguished by retention time. The extracted ion chromatograms of isomeric substances of three typical zearalanol compounds are shown in Figure 1. Figure 8 .

[0152] 3.3.2 Methodological evaluation

[0153] In order to ensure the accuracy and reliability of the screening method, the quality of the method was verified and evaluated. The verification results showed that the 86 HDCs had a good linear relationship in the concentration range of 0.05-250 ng / mL, and the correlation coefficient (r) was ≥0.9809; the limit of detection (LOD) of water samples was 0.05-5 ng / L, and the limit of quantification (LOQ) was 0.15-15 ng / L; the limit of detection (LOD) of other samples was 0.05-5 ng / g, and the limit of quantification (LOQ) was 0.15-15 ng / g; at the addition level of 1 times LOQ-10 times LOQ, the overall recovery of 86 HDCs was 68.7%-111.5%, and the RSD was 2.3%-11.0%, indicating that the accuracy and precision of the method established in this invention met the experimental requirements. The matrix effect evaluation showed that the matrix effects of 86 HDCs in water, suspended matter, and crabs were all in the range of 80%-120%, that is, the matrix effect was not obvious; while CMA in sediments showed a matrix inhibition effect (MIE), M1T in freshwater fish showed a matrix enhancement effect (MEE), TRB, DAN, and BM showed MIE, EpiA in shrimps showed MEE, and TRB, MD, and β-ZOL showed MIE.

[0154] 3.4 Distribution pattern of HDCs

[0155] Four types of HDCs were identified in this study. ERs were detected in all studied media, while ARs were mostly detected only in surface water ( Fig. 9 a), HDCs show different occurrence patterns in different media (biological and abiotic) ( Fig. 9 b, c, d, e), and the results showed that HDCs were widely distributed in the aquatic ecosystem of Chengdu (Tables 5-7).

[0156] Table 5 Detection rate, concentration range and average value of HDCs in aquatic environment (water, sediment and suspended matter) in Chengdu

[0157]

[0158] Table 6 Detection rate, concentration range and average value of hormone disruptors in aquatic food (grass carp, crucian carp and eel) in Chengdu

[0159]

[0160] Table 7 Detection rate, concentration range and average value of hormone disruptors in aquatic foods (shrimp, crab and frog) in Chengdu

[0161]

[0162] From the perspective of HDCs categories, GCs were most significant in shrimp, suspended matter and frog samples. In addition, GCs were present in significant concentrations in surface water, sediments and suspended matter, which may be related to their special physical and chemical properties (Kow value, solubility and adsorption tendency, etc.). ERs were mainly enriched in shrimps, with a concentration as high as 392.9 ng / g, which may be related to endogenous hormones in organisms. SABAs were detected more evenly, but the detection frequency in water and suspended matter was low. ARs had a low detection rate and were mainly concentrated in water bodies, with the highest concentration of 12.2 ng / L, indicating that their occurrence level in the environment was low.

[0163] From the perspective of sample types, the detection rates of GCs and ARs in surface water were high, especially DXM, which had a detection rate of 10% and a concentration range of 17.8-45.6 ng / L, which is similar to the concentration level of DXM in European urban waters (12ng / L-45.6ng / L). The detection rate of RCP was 4%, and its concentration range was 0.5-10.7 ng / L. The detection rate of ERs was lower, but its concentration may still pose a potential risk. In sediments, the detection rate of DXM was 7%, and its concentration range was 12.3-29.0 ng / g, with an average concentration of 18.9 ng / g. This enrichment phenomenon highlights the key role of sediments as a long-term storage reservoir for HDCs. The concentration of HDCs in suspended solids was higher than that in surface water and sediments, especially affecting the migration of GCs and SABAs. For example, the concentration of DXM was 35.6-50.2 ng / g, indicating that suspended solids are the main carrier of HDCs migration in water bodies. The overall detection rate of HDCs in aquatic foods was low, and most of them were not detected in organisms, which may be related to the strong metabolic degradation ability of organisms. It is worth noting that the detection rate of E1 in shrimps (57%) and frogs (24%) was higher, which may be related to the endogenous hormones of these organisms.

[0164] 3.5 Temporal and spatial distribution characteristics of HDCs

[0165] The HDCs in the present invention show obvious spatiotemporal heterogeneity. Fig.10a, b, c, d), the seasonal variation trends of different environmental samples are similar. Spring and winter are the peak seasons for HDCs concentrations, which may be related to the increase in agricultural and animal husbandry activities in spring. In winter, the diffusion capacity of water bodies decreases, the temperature drops, and the degradation rate of pollutants slows down, resulting in an increase in HDCs concentrations. HDCs in aquatic foods show seasonal changes that are significantly different from those of environmental media. HDCs concentrations are higher in spring and summer, especially ERs, reaching 399.5 ng / g and 159.4 ng / g in spring and summer, respectively. This may be related to the biological reproduction period and environmental conditions such as changes in Henry coefficients caused by high temperatures in summer and low water levels. In comparison, the concentrations of HDCs in aquatic foods are lower in autumn and winter, indicating that the degradation rate of these seasonal pollutants is accelerated or biological absorption is reduced. From a spatial perspective ( Fig.10e, f and g), the concentration of pollutants in the southern region is higher, and the river shows an increasing trend from upstream to downstream, which is affected by seasonal changes and biological processes. Sediment pollution is more prominent in the eastern region, while suspended matter is seriously polluted in the southern region. Among them, the spatial differences of HDCs in surface water are significant, especially in the downstream areas of FHR, JAR and MJR. GCs are mainly found in surface water, such as DXM, which has a high concentration in the downstream of FHR (45.6 ng / L), MJR (31 ng / L) and JAR (22.8 ng / L), which may be related to the discharge of upstream pharmaceutical and domestic wastewater. DES (4.2 ng / L) and DET (0.2 ng / L) in ERs are mainly in the downstream of JAR and MJR, and their source may be domestic sewage. The concentration of RCP in SABAs was higher in the downstream of FHR (12.3 ng / L) and JR (5.2 ng / L), while ORC was concentrated in the downstream of JAR (6.6 ng / L) and JR (1.8 ng / L), which may be discharged from livestock. The spatial distribution of HDCs in sediments was similar to that in surface water, but the concentration levels were significantly different. ERs showed a high accumulation trend in sediments, which was similar to the phenomenon in the Danube River in Europe and the Great Lakes in North America. The concentrations of HTS in ERs were higher in the downstream of FHR (9.6 ng / g), QLL (13.2 ng / g) and downstream of MJR (16.8 ng / g), and the concentrations of ORC were higher in QLL (9.4 ng / g) and upstream of JR (17.8 ng / g), indicating that these areas were seriously polluted by ERs, and the main sources may be animal husbandry, agriculture and domestic sewage. GCs were widely distributed in sediments of waters such as JAR, FHR, QLL, MJR and JR, with concentrations ranging from 0.6 to 29.0 ng / g. DXM was more prominent in sediments of waters such as upstream JAR (18.2 ng / g), downstream FHR (19 ng / g) and QLL (12.3 ng / g). All four types of HDCs were detected in suspended matter, with concentrations ranging from 0.2 ng / g to 50.2 ng / g. ng / g, showing significant differences in different pollutants in water bodies. The concentration of DXM was highest in the downstream of JAR and FHR, reaching 35.6-50.2 ng / g. Among SABAs, the concentrations of CLB, CPR, and PBT were relatively high in the downstream of JAR and FHR, ranging from 0.7-21.9 ng / g.

[0166] 3.6 Source analysis of HDCs

[0167] In surface water ( Fig.11a, b, c) identified three factors as the optimal solution, with R² ranging from 0.621 to 0.999. In factor 1, BM had the highest contribution rate (97.1%), followed by RCP (95.1%), DXM (71%) and FMT (57.1%); BM and DXM are often used to treat inflammation and may come from pharmaceutical factories or medical waste. RCP may come from livestock wastewater, and FMT may come from gyms and pharmaceutical factories. Therefore, factor 1 is mainly attributed to pharmaceutical wastewater. In factor 2, DES had the highest contribution rate (92.1%), followed by BDN (87.7%), which may enter the environment as a drug abuse in the gym. Therefore, factor 2 is mainly attributed to the gym. In factor 3, ORC had a contribution rate of up to 98.3%, which is widely used in livestock and aquaculture. FMT (19.1%) was the second, and ORC concentrations as high as 3.5 ppm were detected in Vietnamese aquaculture wastewater. Therefore, factor 3 is mainly attributed to livestock and aquaculture. In sediments ( Fig.11 d, e, f) Three factors were determined to be the optimal solution, with R² ranging from 0.956 to 0.999. In factor 1, HTS contributed significantly (98.5%). HTS is widely present in daily necessities and enters the environment through domestic sewage discharge. Therefore, factor 1 is mainly attributed to domestic sewage. Factor 2 is closely related to DXM (97.8%), E1 (71.2%), and TC (54.1%). DXM and TC are mainly discharged into the environment through hospital wastewater. DXM concentrations as high as 117-545 ng / L and TC concentrations of 14-41 ng / L were found in hospital wastewater in the Netherlands. E1 is an endogenous hormone that mainly enters the sewage system through human and animal metabolites. Therefore, factor 2 can be attributed to the combined pollution source of pharmaceutical wastewater and domestic sewage. ORC (98.7%) contributed the most to factor 3, followed by PL (87.4%). ORC is mainly used to prevent and treat bacterial infections, and PL is often used to treat immune diseases. Pharmaceutical factories may produce wastewater containing ORC and PL during production. Therefore, factor 2 is mainly related to pharmaceutical wastewater discharge. Fig.11g, h, i) determined that the three factors were the optimal solution, with R² ranging from 0.727 to 0.999. In factor 1, E2 had the highest contribution rate (96.7%), followed by DXM (68.5%) and HC (41.6%). E2 is a human metabolite and is widely present in urban sewage. DXM is often used to treat skin diseases and is mainly enriched in suspended solids in water bodies through excrement. HC is an anti-inflammatory drug and may be enriched in suspended solids through domestic sewage. In factor 2, BEN had the highest contribution rate (96.2%), followed by BDP (99.3%), PBT (98.7%) and DXM (31%). They are all mainly used to treat male hormone-related diseases and are enriched in suspended solids through pharmaceutical wastewater. Therefore, factor 2 mainly comes from pharmaceutical wastewater. Factor 3 mainly involves livestock wastewater, with CLB contributing as much as 99.2%. Farms that illegally use CLB as a growth promoter are the main source of pollution for this factor. The contribution of HC (34.1%) was relatively low, but still cannot be ignored due to its widespread use in livestock.

[0168] 3.7 Ecological risk assessment and priority ranking of HDCs

[0169] Analysis of the RQ values ​​of HDCs in surface water, sediment and suspended solids according to risk levels ( Fig.12 a, b and c). The results show that the RQ values ​​of surface water are all below 0.1, which is a low risk. The RQ values ​​of PL and DXM in sediments vary between 0.13-0.64 and 0.06-0.15, respectively, and most of them are at medium risk; while the RQ value of HTS varies between 1.09-15.27, with high ecological risk. HC, DXM and E2 in suspended matter samples are at medium risk, and the highest RQ values ​​of CA, CLB and PBT are 7.56, 3.40 and 14.22, respectively, with extremely high ecological risk. It is worth noting that the RQ values ​​of some points in sediments and suspended matter are much higher than those in surface water. This may be due to the adsorption, accumulation effect and biomagnification effect of some HDCs, which makes sediments and suspended matter with high adsorbed particulate organic carbon content become "sinks" for HDCs.

[0170] The present invention further adopts the optimized RQ algorithm, calculates the priority index (PI) based on the PNEC frequency, and performs comprehensive risk ranking (Table 8). The results show that the risk levels of HDCs in surface water are all safe, and HDCs in sediments are divided into medium risk and safe. Among them, HTS, PL and DXM constitute high risk or medium risk in the traditional RQ method, but they are identified as medium risk and safe pollutants due to their low frequency of exceeding the standard. CA, PBT and CLB in suspended matter samples are medium risk and tolerable risk. The PI value of other HDCs is 0, indicating that the current concentration does not pose an ecological risk. Among the medium HDCs that are of focus, HTS is included in the regulatory list of the World Health Organization (WHO) and the Food and Agriculture Organization of the United Nations (FAO), and PBT and CA are both included in the EU Water Framework Directive (WFD) observation list. Therefore, HTS, PBT and CA are locked as the priority control objects of Chengdu's aquatic ecosystem.

[0171] Table 8 Priority index of target HDCs in aquatic ecosystems

[0172]

[0173] 4 Discussion:

[0174] Based on the construction of a high-throughput pretreatment method for multi-target samples and UHPLC-Q-Orbitrap HRMS instrument analysis technology, the present invention has developed a high-throughput non-targeted identification strategy for HDCs with satisfactory methodological evaluation results by building a database of electronic identity characteristics of 86 HDCs and combining the mass spectrometry fragmentation law. Through large-scale sample analysis over a one-year period, 17.85% of the 409 samples collected from 4 rivers and 3 lakes in the study area tested positive, and 24 HDCs were identified, mainly GCs, ERs and SABAs. ERs were detected in all research media, and GCs were more significant in shrimp, suspended matter and frog samples; HDCs concentrations were higher in spring and summer, and the degree of pollution from upstream to downstream showed an increasing trend. The source-sink relationship found that domestic sewage, medical wastewater and aquaculture wastewater were the main sources of pollution, and the priority index of HDCs locked HTS, PBT and CA as priority prevention and control targets.

[0175] In conclusion, the high-throughput non-targeted screening and risk assessment strategy constructed by the present invention comprehensively revealed for the first time the occurrence, seasonal distribution patterns, main carriers and risk levels of HDCs in aquatic ecosystems of megacities, and locked in priority prevention and control targets. This strategy not only has broad global applicability, but also provides valuable insights for management to formulate targeted prevention and control measures. Future research should focus on the migration and transformation process of HDCs in aquatic ecosystems and their complex impact on the food chain, and evaluate the long-term effects of HDCs pollution on the environment and human health, which will help to more comprehensively address the HDCs pollution problem and provide strong protection for environmental sustainability and public health.

Claims

1. A method for non-targeted detection of 86 hormone disruptors in aquatic ecosystems, characterized in that: It includes the following steps: a. Pretreatment of samples in aquatic ecosystems; b. Ultra high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) was used for detection. The chromatographic conditions were: Column: Waters XBridge C18 3.0 × 150 mm, 2.5 μm; Column temperature: 40°C; Flow rate: 0.2 mL / min; Injection volume: 10 μL; Mobile phase I: 1 mmol / L aqueous ammonium formate solution containing 0.1% formic acid-acetonitrile; Mobile phase II: 0.01% aqueous ammonia solution-acetonitrile; Firstly, the elution was carried out by gradient elution with mobile phase I, and then by gradient elution with mobile phase II. The elution procedure of mobile phase I was as follows: ； The elution program of mobile phase II is: ； HRMS conditions: Ion source: HESI source; spray voltage: 3.0 kV in positive ion mode, 2.5 kV in negative ion mode; ion transfer tube temperature: 325°C; sheath gas N2 flow rate: 50 arb; auxiliary gas N2 flow rate: 10 arb; purge gas N2 flow rate: 1 arb; heating gas temperature: 350°C; RF-lens voltage: 35%; scan mode: simultaneous positive and negative ion scan; acquisition method: Full MS / dd-MS2; scan range: 100-1000 m / z; Resolution: 60000 for primary and 15000 for secondary; Automatic gain control: Standard; Maximum injection time: Automatic; Cycle count: 3 times for secondary; Isolation window: 2 m / z; Dynamic exclusion: 3.0 s; Use normalized collision energy to optimize the energy by injecting the standard solution through a needle pump; The 86 hormone disruptors are: Dehydrotestosterone, epitestosterone, fluoxymesterone, methyltestosterone, nandrolone propionate, nandrolone, testosterone propionate, trenbolone, mesandrosterone, nandrolone phenylpropionate, stanozolol, norandrostenedione, androstenedione, 17α-methylisotestosterone, mesandrosterone, epiandrosterone, 17β-hydroxyandrostan-3-one, mesandrosterone, danazol, dehydroandrostenone, allylgesterone, chlormadinone acetate, levonorgestrel, medroxyprogesterone acetate, megestrol acetate, melengestrol acetate, norethisterone, norethisterone acetate, 21-α-hydroxyprogesterone, norethindrone, 17-α-hydroxyprogesterone, beclomethasone dipropionate, betamethasone, cortisone acetate, hydrocortisone, methylprednisolone, prednisolone, triamcinolone acetonide, triamcinolone, cortisone, dexamethasone, hydrocortisone acetate beclomethasone, flumethasone, budesonide, fluocinolone acetate, fludrocortisone acetate, fluorometholone, clobetasol propionate, aldosterone, prednisone, estriol, estrone, dienestrol, diethylstilbestrol, hexestrol, estradiol, 17α-estradiol, 17β-estradiol, octylphenol, 4-nonylphenol, bisphenol A, ethinyl estradiol, α-zearalenol, β-zearalenol, zearalanone, α-zearalanol, β-zearalanol, clenbuterol, ractopamine, chlorprenaline, penbuterol, orproline, formoterol, fenoterol, sebuterol, bambuterol, salbutamol, terbutaline, tolbuterol, cimaterol, mabuterol, mapentol, salmeterol, zilpaterol, bromobuterol; The aquatic ecosystem includes water, sediment or suspended matter in the water, and aquatic food; the pre-treatment methods are: a. Water sample pretreatment: 1 L of static water sample was filtered through a 0.45 μm ultrafine glass fiber microporous filter to remove visible suspended particles, then 0.25 g Na2EDTA was added, and the pH was adjusted to 3.0±0.5 with 1 mol / L hydrochloric acid. The sample was enriched by 6 cc 200 mg Oasis®PRiME HLB solid phase extraction column, then centrifuged and dried for extraction, and eluted with 12 mL methanol solution. The eluate was combined and concentrated to 1 mL, and the extract was filtered through a 0.22 μm nylon organic phase needle microporous filter. The chromatographic injection vial was stored at -18°C; b. Pretreatment of sediment and suspended solids: The samples were freeze-dried in the dark for 24 h, ground and homogenized through a 100-mesh sieve, 5.00 g of homogenate sample was weighed and placed in a 50 mL polypropylene centrifuge tube, 0.25 g Na2EDTA was added, mixed with pH = 3 citric acid buffer and 5 mL acetonitrile, and the samples were rapidly and vigorously shaken and vortexed for 10 min at 2000 r / min to fully disperse the samples, ultrasonically extracted for 10 min, and centrifuged at 9500 r / min for 5 min. The supernatant was taken and placed in a 50 mL polypropylene PP centrifuge tube. The above extraction process was repeated for a second extraction, and the supernatants of the two extractions were mixed and then diluted to 300 mL with Milli-Q water. The samples were purified and enriched according to the water sample pretreatment method; c. Pretreatment of aquatic food: After slaughtering the sample, retain the edible part and homogenize it. Accurately weigh 5.00 g of the homogenate sample and place it in a 50 mL PP centrifuge tube. Add 20 mL of 80% acetonitrile aqueous solution containing 0.2% formic acid. After standing for 10 min, add two ceramic homogenizers. Shake rapidly and vigorously and vortex oscillate for 10 min at 2000 r / min to fully disperse the sample. Ultrasonic extraction is performed for 10 min. Centrifuge at 9500 r / min for 5 min. Take the supernatant for purification. Take 5 mL of the accurately measured supernatant and pass it through a 6cc 200 mg Oasis®PRiME HLB solid phase extraction column at a flow rate of 1 drop / s. Collect 3-5 mL of the second half of the effluent and accurately measure 2 mL. Blow dry to 1 mL under nitrogen. Make up to volume with the initial mobile phase and pass through a 0.22 μm nylon organic phase needle microporous filter membrane. The chromatographic injection vial is stored at -18°C.

2. A method for constructing an electronic identity information database of 86 hormone disruptors, characterized in that: The information database includes Chinese and English names, molecular formula, CAS number, retention time, accurate mass of parent ion, isotope distribution, accurate mass of secondary fragments, ion adduct state, optimal normalized collision energy, and spectrum library information; It consists of two sections: the primary compound fingerprint identification data Database and the secondary HCD fragment ion characteristic spectrum library mzVault Library; The construction method includes the following steps: a. Collect full scan data of the prepared 500 ng / mL mixed standard solution using the detection method described in claim 1, obtain the primary accurate mass number and retention time, and determine the best additive state; wherein the additive state includes [M+H]+, [MH]-, and [M+HCOO]-; b. Set the collision energy gradient value of 5-105% with a step size of 5% in the acquisition method, collect full scan data of the prepared 500 ng / mL mixed standard solution using liquid chromatography-high-resolution mass spectrometry, and perform qualitative analysis using FreeStyle software to obtain the corresponding stable fragment ions with a relative mass deviation of <10 ppm as secondary ions and write them into the database; at the same time, select the collision energy when the primary ion response is 1 / 3 of the highest response ion among the secondary ions as the optimal collision energy and write it into the acquisition method.

3. A method for ecological risk assessment of hormone disruptors, characterized in that: It adopts the risk quotient RQ algorithm to assess the health risk of HDCs in the aquatic ecosystem of the study area; It includes the following steps: Using aquatic ecosystem samples, detecting the contents of 86 hormone disruptors in the aquatic ecosystem according to the detection method of claim 1, and using the RQ calculation formula to evaluate the health risks of HDCs in the aquatic ecosystem of the study area; The calculation formula of RQ is as follows: ; MEC is the measured environmental concentration and PNEC is the predicted no-effect concentration, and their values ​​can be calculated as follows: ; EC50 and LC50 refer to half-maximal effective concentration and half-lethal concentration, respectively; NOEC and LOEC stand for no observed effect concentration and lowest observed effect concentration, respectively; AF is the assessment factor, which depends on the toxicity data and has a value of 50, 100 or 1000 for chronic toxicity; The RQ value for assessing the risk of hormone disruptors was calculated using the following equation; ; The Kd values ​​of HDCs detected in sediments and suspended solids were obtained through experiments: ; The risk quotient RQ is used to assess the ecological risk of HDCs to aquatic organisms and is divided into three levels: low risk: RQ < 0.1, medium risk: 0.1 < RQ < 1 and high risk: RQ > 1.

4. A method for prioritizing hormone disruptors, characterized in that: The optimized RQ algorithm is used to rank the potential high-risk HDCs to identify and lock the HDCs that should be controlled first; the high-risk HDCs are obtained by the method for ecological risk assessment of hormone disruptors as described in claim 3; The algorithm is: （1）； ； n and N represent the number of samples with actual concentrations exceeding PNEC and the total number of detected samples, respectively; using samples with detected HDCs, the target compounds were divided into five categories according to their risk levels: high risk: PI ≥ 1, medium risk: 0.1 ≤ PI < 1, tolerable risk: 0.01 ≤ PI < 0.1, negligible risk: 0 < PI < 0.01, and safe: PI = 0.

Images