CN119355175B

CN119355175B - Method for non-targeted detection of 86 hormone interferents in aquatic ecosystem, hormone interferent ecological risk evaluation method and optimal control sequencing method

Info

Publication number: CN119355175B
Application number: CN202411898069.0A
Authority: CN
Inventors: 郭添荣; 蒲生彦; 悦清楠; 黄弋耘; 王心怡; 余东; 吴文林
Original assignee: Chengdu Institute Of Food Inspection; Chengdu Univeristy of Technology
Current assignee: Chengdu Institute Of Food Inspection; Chengdu Univeristy of Technology
Priority date: 2024-12-23
Filing date: 2024-12-23
Publication date: 2025-04-29
Anticipated expiration: 2044-12-23
Also published as: CN119355175A

Abstract

The invention provides a method for non-targeted detection of 86 hormone interferents in an aquatic ecosystem, a hormone interferent ecological risk evaluation method and a preferential control sequencing method, and belongs to the field of detection. The method comprises the following steps of a, preprocessing a sample in an aquatic ecosystem, and b, detecting by adopting ultra-high performance liquid chromatography-high resolution mass spectrum UHPLC-HRMS. The invention also provides a construction method of the 86 hormone interferents electronic identity information database, a hormone interferents ecological risk evaluation method and a hormone interferents optimal control ordering method. The invention reveals HDCs occurrence patterns, space-time evolution rules and main driving factors in the cross-interface aquatic ecosystem, carries out health risk assessment and priority control locking based on ecological risks, and fills the technical blank that only environment or food detection is involved but no system ecological risk tracking is carried out in the current literature.

Description

Method for non-targeted detection of 86 hormone interferents in aquatic ecosystem, hormone interferent ecological risk evaluation method and optimal control sequencing method

Technical Field

The invention relates to a method for non-targeted detection of 86 hormone interferents in an aquatic ecosystem, a hormone interferent ecological risk evaluation method and a priority ordering method, and belongs to the field of detection.

Background

Hormonal interferents (Hormone Disrupting Chemicals, HDCs), also known as endocrine interferents, are a class of hormonal interferents (Endocrine Disrupting Chemicals, EDCs) that have hormonal effects, and their overexposure may cause premature human sexual, breast cancer, and male semen failure toxicity and childhood leukemia. As the urban system continuously discharges medical sewage, cultivation wastewater and industrial wastewater, so that HDCs is continuously hidden, accumulated and migrated in the water environment, HDCs is often difficult to comprehensively remove by the traditional water purification process, and the residual HDCs can be accumulated in aquatic foods (such as fishes, shrimps and the like) and ingested by human beings through food chains, thereby seriously threatening the health of the human beings. However, since HDCs detects concentrations in water environments and aquatic animals at trace levels, with the continual advent of potential and unknown HDCs and the complexity of monitoring sample variability and data analysis, this presents a significant challenge for effective monitoring and targeted control of HDCs. The erosion degree of hormone interferents in the cross-interface aquatic ecosystem (water body-suspended matter-sediment-aquatic foods) of the ultra-large city is not clear at present, and the monitoring information of related researches is very limited. Therefore, we recognize that there is a need to fill this gap by building a universal HDCs rapid screening strategy and risk assessment method, which is critical to efficiently allocate limited resources to cope with erosion of HDCs in cross-interface aquatic ecosystems and to drive prospective risk perception.

CN201610466428.4, the name of the invention, a detection and analysis method of various endocrine disruptors in environment and food, relates to a detection and analysis method of various endocrine disruptors in environment and food, and the detection and analysis method utilizes 4' -carbonyl chloride-rhodamine as a derivative reagent, and performs analysis of various endocrine disruptors by combining ultrasonic assistance-in-situ derivative-dispersion liquid microextraction and ultra-high performance liquid chromatography triple quadrupole mass spectrometry detection. The invention uses 4' -carbonyl chloride-rhodamine with one permanent positive charge in the molecule as a derivatizing reagent for the first time to determine 23 endocrine disruptors.

CN201810345043.1, the name of the invention, a magnetic solid phase extraction-HPLC-ultraviolet detection method of an environmental secretion interfering substance in a water sample, discloses a magnetic solid phase extraction-HPLC-ultraviolet detection method of an environmental secretion interfering substance in a water sample, and belongs to the technical field of environmental monitoring. According to the detection method, the magnetic graphene oxide is used for carrying out adsorption extraction on the low-concentration EDCs in the water sample, and then the EDCs are eluted and fixed in volume, so that an enriched EDCs sample is obtained.

CN201810273248.3, a method for quantitatively detecting the contents of different occurrence forms of Endocrine Disruptors (EDCs) in water, relates to a method for separating and detecting different forms of organic pollutants in water in the field of environmental analysis chemistry, and particularly relates to a method for quantitatively detecting the contents of different occurrence forms of the Endocrine Disruptors (EDCs) in water. As the previous researches generally assume that the pollutants are in a dissolved state in the water body after being treated by the filter membrane, the combination of the pollutants and the colloid microparticles is ignored to show different forms. The invention detects the contents of particle phase, colloid binding phase and true soluble phase EDCs in water by adopting a pretreatment method of ceramic membrane filtration, ultrasonic auxiliary extraction and solid phase extraction and combining a high performance liquid chromatography-mass spectrometry (LC-MS/MS) analysis technology.

CN201110120299.0, the name of the invention is a method for measuring trace chlorophenol endocrine disruptors in water, which comprises the steps of firstly adding NaH2PO4 split-phase salt, then adding Na2HPO4-H3PO4 buffer solution to adjust the pH value of the solution, then adding [ Bmim ] BF4 hydrophilic ionic liquid to perform extraction separation, taking an ionic liquid phase after separation by a centrifuge, and finally measuring the content of the chlorophenol endocrine disruptors by a high performance liquid chromatography. In the invention, ionic liquid is used as an extractant, naH2PO4 is used as split-phase salt, and trace chlorophenol endocrine disruptors in water are measured by an ionic liquid aqueous two-phase extraction-High Performance Liquid Chromatography (HPLC) method.

Huang Wenping, etc., and simultaneously and rapidly detecting 31 endocrine disruptors in an environmental water body by using an ultra-high performance liquid chromatography-tandem mass spectrometry, environmental chemistry, 4 months in 2017 and 4 th period in 36 volumes, and establishing an analysis method for simultaneously determining 31 Endocrine Disruptors (EDCs) in the environmental water body by combining solid phase extraction with the ultra-high performance liquid chromatography-tandem mass spectrometry (SPE-UPLC-MS/MS).

The literature reported so far only detects endocrine disruptors for environmental samples (water, soil) or food samples, and no simultaneous detection and cross-interface collaborative risk study for coupled systems containing environmental and food samples is seen.

Disclosure of Invention

The invention provides a method for non-targeted detection of 86 hormone interferents in an aquatic ecosystem, a hormone interferent ecological risk evaluation method and a preferred control sequencing method.

The invention provides a method for non-targeted detection of 86 hormone interferents in an aquatic ecosystem, which comprises the following steps:

a. pretreatment of samples in the aquatic ecosystem;

b. Ultra-high performance liquid chromatography-high resolution mass spectrum UHPLC-HRMS detection is adopted, and the chromatographic conditions are as follows:

chromatographic column Waters XBidge C18 (3.0X105 mm,2.5 μm);

column temperature 40 ℃;

the flow rate is 0.2 mL/min;

sample injection amount is 10 mu L;

mobile phase I1 mmol/L ammonium formate aqueous solution (0.1% formic acid) -acetonitrile;

Mobile phase II is 0.01% ammonia water solution-acetonitrile;

the elution process of the mobile phase I elution comprises the following steps of:

the elution procedure for mobile phase II was:

HRMS conditions:

The ion source is HESI source, the spray voltage is positive ion mode 3.0 kV, negative ion mode 2.5 kV, the ion transmission tube temperature is 325 ℃, the sheath gas N ₂ flow rate is 50 arb, the auxiliary gas N ₂ flow rate is 10 arb, the purge gas N ₂ flow rate is 1 arb, the heating temperature is 350 ℃, the RF-lens voltage is 35%, the scanning mode is positive and negative ion simultaneous scanning, the acquisition mode is Full MS/dd-MS2, the scanning range is 100-1000 m/z, the resolution is first 60000, second 15000, the automatic gain control is standard, the maximum injection time is automatic, the cycle count is second 3 times, the isolation window is 2 m/z, the dynamic exclusion is 3.0 s, and the energy is optimized by pumping the standard solution through the needle by adopting the normalized collision energy to the best;

the 86 kinds of hormone interferents are as follows:

Dehydrotestosterone, epitestosterone, fluoxytestosterone, methyltestosterone, nandrolone propionate, nandrolone, testosterone propionate, trenbolone, mesterolone, nandrolone, settazolol, norandrostenedione, androstenedione, 17α -methylisotestosterone, mesterol, epiandrosterone, 17β -hydroxyandrostan-3-one, mesterone, danazol, dehydroandrosterone, allylprogestin, megestrol acetate, levonorgestrel, medroxyprogesterone acetate, megestrol acetate, norethindrone acetate, 21- α -hydroxyprogestrel, norgestrel, 17- α -hydroxyprogestrel, beclomethasone propionate, betamethasone, cortisone acetate, hydrocortisone, methylprednisolone, prednisolone, triamcinolone, cortisone, dexamethasone, hydrocortisone acetate, hydrocortisone beclomethasone, fluorometsone, budesonide, fluocinolone acetonide, fludrocortisone acetate, fluorometholone, clobetasol propionate, aldosterone, prednisone, estriol, estrone, hexadienestrol, diethylstilbestrol, estradiol, 17α -estradiol, 17β -estradiol, octylphenol, 4-nonylphenol, bisphenol A, ethinyl estradiol, α -zearalenol, β -zearalenol, zearalenol zearalenone, alpha-zearalanol, beta-zearalanol, clenbuterol, ractopamine, chlorpanacoline, salbutamol, oxacinnabar, formoterol, fenoterol, sabbuterol, salbutamol, terbutaline, tobuterol, cimaterol, marbuterol, ma Bente, salmeterol, zilpaterol, and bromobuterol.

Wherein the aquatic ecological system comprises water, sediment or suspended matters in the water and aquatic foods, and the pretreatment method comprises the following steps:

a. 1L, standing the water sample, filtering the water sample by a 0.45 mu m ultrafine glass fiber microporous filter membrane to remove visible suspended particles, adding 0.25 g Na2EDTA, adjusting the pH to 3.0+/-0.5 by using 1 mol/L hydrochloric acid, enriching by using a 6 cc 200 mg Oasis DEG PRiME HLB solid phase extraction column, centrifuging, drying and extracting, eluting by using a 12 mL methanol solution, merging and concentrating the eluates to 1 mL, filtering the extract by using a 0.22 mu m nylon organic phase needle type microporous filter membrane, and preserving the chromatographic sample injection vial at-18 ℃;

b. Pre-treating sediment and suspended matters, namely freeze-drying a sample in darkness for 24 h, grinding and homogenizing the sample through a 100-mesh aperture sieve, weighing a 5.00 g homogenized sample, placing the homogenized sample into a 50mL polypropylene centrifuge tube, adding 0.25 g Na2EDTA, mixing the solution with a citric acid buffer solution with pH value of 3 and 5 mL acetonitrile, rapidly and severely shaking and vortexing for 10min, 2000 r/min to fully scatter the sample, ultrasonically extracting for 10min, centrifuging for 5 min at a high speed of 9500 r/min, taking a supernatant, placing the supernatant into a 50mL polypropylene PP centrifuge tube, repeating the extraction process for the second time, mixing the supernatants extracted for the second time, diluting the supernatant to 300 mL by using Milli-Q water, and purifying and enriching the sample according to a water sample pretreatment method;

c. The preparation method comprises the steps of slaughtering a sample, preserving edible part homogenized homogenate, accurately weighing 5.00 g homogenate samples, placing the samples in a 50mL PP centrifuge tube, adding an 80% acetonitrile water solution 20mL containing 0.2% formic acid, standing for 10min, adding two ceramics to obtain protons, rapidly and severely shaking and vortexing for 10min, 2000 r/min to fully disperse the samples, ultrasonically extracting for 10min, centrifuging for 5min at a high speed of 9500 r/min, taking supernatant to be purified, taking supernatant accurately measured for 5mL, passing through a 6 cc 200 mg Oasis PRiME HLB solid phase extraction column at a flow rate of 1 drop/s, collecting effluent liquid at the latter half section of 3-5 mL, accurately weighing 2 mL, drying to 1mL under nitrogen, initially flowing for a specific volume, and preserving the chromatographic sample in a-18 ℃ through a 0.22 μm nylon organic phase needle type microporous filter membrane.

The invention provides a construction method of an 86 hormone interferent electronic identity information Database, wherein the information Database comprises Chinese and English names, molecular formulas, CAS numbers, retention time, parent ion accurate mass numbers, isotope distribution, secondary fragment accurate mass numbers, ion addition states, optimal normalized collision energy (HCD collision energy) and spectrogram library (mzVault Library) information, and consists of two plates of a compound primary fingerprint identification Database (Database) and a secondary HCD fragment ion characteristic spectrogram library (mzVault Library);

the construction method comprises the following steps:

a. collecting full scan data of the prepared 500 ng/mL mixed standard solution by the detection method, obtaining a first-stage accurate mass number and retention time, and determining an optimal addition state, wherein the addition state comprises [ M+H ] +, [ M-H ] -, and [ M+HCOO ] -;

b. Setting a collsion energy gradient value of 5-105% and a step length of 5% in an acquisition method, acquiring full-scan data of the prepared 500 ng/mL mixed standard solution by using liquid chromatography-high resolution mass spectrum, performing qualitative analysis by using FreeStyle software to obtain fragment ions with corresponding stability and relative mass deviation of <10 ppm as secondary ions, writing the fragment ions into a database, selecting collsion energy with a primary ion response of 1/3 of the highest response of the secondary ions as optimal collision energy, and writing the fragment ions into the acquisition method.

The invention provides a hormone interferent ecological risk evaluation method, which adopts a Risk Quotient (RQ) algorithm to evaluate the health risk of HDCs in an aquatic ecosystem of a research area;

it comprises the following steps:

Detecting the content of 86 hormone interferents in the aquatic ecosystem by adopting an aquatic ecosystem sample according to the detection method, and evaluating the health risk of HDCs in the aquatic ecosystem in a research area by adopting a RQ calculation formula;

The formula for RQ is shown below: MEC is the measured ambient concentration, PNEC is the predicted refractory concentration, and its value can be calculated by: ;

EC50 and LC50 refer to the half maximum effective and half lethal concentrations, respectively, NOEC and LOEC represent the no observed and minimum observed effect concentrations, respectively, AF is an evaluation factor that depends on toxicity data, with values of 50, 100 or 1000 for chronic toxicity;

RQ values for assessing risk of hormonal interferents were calculated using the following equations;

the Kd values of HDCs detected in the sediment and suspension were all obtained experimentally:

;

risk Quotient (RQ) is used to evaluate HDCs ecological risk to aquatic organisms and is divided into three classes, low risk (RQ < 0.1), medium risk (0.1 < RQ < 1) and high risk (RQ > 1).

The invention provides a method for optimally controlling and sequencing hormone interferents, which adopts an optimized RQ algorithm to perform risk sequencing on potential high risks HDCs so as to identify and lock HDCs which should be preferentially controlled, wherein the high risks HDCs are obtained by the method for evaluating the ecological risks of the hormone interferents;

The algorithm is as follows:

(1)

N and N represent the number of samples with actual concentration exceeding PNEC and the total number of samples detected respectively, and the target compounds are classified into five classes according to risk level, namely high risk (PI.gtoreq.1), medium risk (PI.gtoreq.0.1), bearable risk (PI.gtoreq.0.01), negligible risk (PI.gtoreq.0.01) and safety (PI=0) by adopting samples detected HDCs.

The beneficial effects of the invention are as follows:

the invention develops and verifies a method for non-targeted identification of 86 species HDCs in an aquatic ecosystem (water body-suspended matter-sediment-aquatic foods) based on a self-built 86 species HDCs electronic identity information database, comprehensively reveals the occurrence pattern, space-time evolution rule and main driving factors of HDCs in the cross-interface aquatic ecosystem based on the strategy by taking pollution sources and health risks as guidance, and also carries out health risk assessment and preferential control locking based on ecological risks. Fills the gap that only environment or food detection is related but no system ecological risk tracking is performed in the current literature, and realizes simultaneous detection and risk collaborative research of a cross-environment and food full-chain sample in an aquatic ecological system.

According to the invention, cities are selected as research areas, and a non-targeting screening strategy based on 86 types HDCs of electronic identity information characteristic databases (a primary fingerprint identification database and a secondary fragment ion characteristic spectrum library) is constructed by developing a multi-target sample high-throughput pretreatment method by adopting an ultra-high performance liquid chromatography-four-level rod/electrostatic field orbit trap ultra-high resolution mass spectrum (UHPLC-Q-Orbitrap HRMS) combined technology with the remarkable advantages of high separation capability, high quality resolution, high quality precision and the like. The method is a cross-interface HDCs high-throughput non-targeted screening and risk comprehensive characterization research which is developed in a cross-interface aquatic ecosystem (water body, sediment, suspended matters and aquatic foods) of a very large city for the first time. Through large-scale sample analysis of a year period, the occurrence pattern, the time-space evolution rule and the main driving factors of HDCs in the aquatic ecosystem are comprehensively revealed by taking pollution sources and health risks as guidance, health risk assessment and priority control locking based on ecological risks are also carried out, and the findings have important significance for formulating targeted HDCs control measures and risk management strategies.

Drawings

FIG. 1 is a partial exemplary HDCs-feature ion flow chromatogram;

FIG. 2 is a workflow diagram of HDCs high-throughput non-targeted screening;

FIG. 3 is a graph showing the effect of different extraction columns (a) and packing amounts (b) on the recovery of 86 HDCs species in different matrices;

FIG. 4 is a graph showing the effect of chromatography of the beta-receptor agonist Simaroubrol in Thermo Accucore Vanquish C ₁₈ (a) and Waters XBiridge C ₁₈ (b);

FIG. 5 is a graph comparing chromatographic peaks of estradiol in an acidic mobile phase (a) and a basic mobile phase (b);

FIG. 6 is a graph comparing the chromatographic peaks of isomers 17α -estradiol and 17β -estradiol (a), betamethasone and dexamethasone (b) in the organic phases methanol (1) and acetonitrile (2);

Fig. 7 is a secondary fragment mass spectrum of albuterol at optimal collision energy (nce=30%);

FIG. 8 is an ion flow diagram of the isomer extraction of 3 zearalanol compounds;

FIG. 9 is a graph of the detected number (a) of four classes HDCs in different environmental media, and concentration levels of GCs _all（b）、ERs_all（c）、SABAs_all (d) and ARs _all (e) in different environmental media;

FIG. 10 is a bar graph of HDCs detected concentration groupings in surface water (a), sediment (b), suspended matter (c), aquatic food (d) over different seasons, spatial variation of total HDCs concentration in surface water (e), sediment (f), suspended matter (g);

FIG. 11 is a graph showing the contribution of each factor to the PMF model for surface water (a), sediment (d), and suspended matter (g), the relative abundance of each factor for each HDCs index for surface water (b), sediment (e), and suspended matter (h), the contribution of each factor for HDCs detected for surface water (c), sediment (f), and suspended matter (i), and the Pearson correlation analysis;

FIG. 12 is a graph of RQ values for various point targets HDCs in surface water (a), sediment (b), and suspension (c).

Detailed Description

Test example 1 method for non-targeted detection of 86 hormone interferents in aquatic ecosystem according to the present invention

Experimental materials and reagents:

Acetonitrile (mass spectrum grade), methanol (mass spectrum grade), orbitrap Exploris,480 ultra-high resolution mass spectrum special mass axis correction liquid PierceTMFlexMixTM Calibration (positive and negative ion mixed liquid), thermo Accucore Vanquish C ₁₈ (2.1×100 mm,1.5 μm) chromatographic column Thermo FISHER SCIENTIFIC company in us; formic acid (mass spectrum grade), ammonia water (mass spectrum grade), ammonium acetate (chromatographic purity) U.S. SIGMA ALDRICH company, ceramic proton (100/pk), nylon organic phase needle type microporous filter of 0.22 μm, AGILENT ECLIPSE plus C ₁₈ (3.0 mm ×150 mm,1.8 μm) chromatographic column, CAPTIVA EMR LIPID solid phase extraction column Agilent company, oasis's HLB, oasis's PRiME HLB solid phase extraction column, waters Xbridge C ₁₈ (3.0×150 mm,3.5 μm) chromatographic column, waters Acquity BEH C ₁₈ (2.1 mm ×100 mm,1.7 μm) chromatographic column U.S. Waters company, AGELA CLEANERT S C ₁₈ solid phase extraction column Tianjin Bona Ai Jieer Co., ultra pure water (resistivity 18.2M Ω/cm,25 ℃) U.S. Millipore company, 0.45 μm ultra fine glass fiber microporous U.S. Pall sieve (Endecotts company), 100 mesh pore size filter).

1. Sample collection and pretreatment

Comprehensively considering urban functional division conditions, collecting water, sediment, suspended matters and aquatic foods at 15 points of a poplar (FHR), jian river (JR), jiang'an river (JAR), min river (MJR), lu Jiang beach (LJTL), qinglong lake (QLL), and Sanqi lake (SCL) in 2023 autumn, winter and 2024 spring and summer respectively.

The pretreatment of the water sample, namely, after a 1L static water sample is filtered by a 0.45 mu m superfine glass fiber microporous filter membrane to remove visible suspended particles, 0.25 g Na2EDTA is added, the pH is adjusted to 3.0+/-0.5 by 1 mol/L hydrochloric acid, the water sample is enriched by a 6 cc 200 mg Oasis DEG PRiME HLB solid phase extraction column, and then centrifugal drying extraction is carried out, 12 mL methanol solution is used for elution, eluent is combined and concentrated to 1 mL, 0.22 mu m nylon organic phase needle type microporous filter membrane is used for filtering the extract, and a chromatographic sample injection vial is stored at-18 ℃.

(2) Sediment and suspension pretreatment, freeze-drying the sample in darkness for 24 h, grinding and homogenizing the sample by a 100-mesh pore size sieve, weighing a homogenized sample of 5.00 g (accurate to 0.01 g), placing the homogenized sample in a 50 mL polypropylene centrifuge tube, adding 0.25 g Na2EDTA, mixing with a citric acid buffer (pH=3) and 5 mL acetonitrile, rapidly and vigorously shaking and vortexing for 10 min (2000 r/min) to fully disperse the sample, ultrasonically extracting for 10 min, centrifuging for 5 min at 9500 r/min at a high speed, placing the supernatant in a 50 mL polypropylene (PP) centrifuge tube, repeating the extraction process for the second time, mixing the supernatants extracted twice, diluting the supernatant to 300 mL by Milli-Q water, and purifying and enriching the sample according to a water sample pretreatment method.

(3) Pre-treating aquatic food, namely, after slaughtering a sample, preserving edible part for homogenizing and homogenizing, accurately weighing a homogenized sample of 5.00 g (accurate to 0.01 g), placing the homogenized sample in a 50 mL PP centrifuge tube, adding an 80% acetonitrile water solution (containing 0.2% formic acid) of 20 mL, standing for 10min, adding two ceramics for proton homogenization, rapidly and severely shaking and vortexing for 10min (2000 r/min) to fully scatter the sample, ultrasonically extracting for 10min, and centrifuging for 5min at a high speed of 9500 r/min, and taking supernatant to be purified. Taking 5mL to accurately measure supernatant, passing through 6 cc 200 mg Oasis PRiME HLB solid phase extraction column with the flow rate of 1 drop/s, collecting effluent liquid at the second half of 3-5 mL sections, accurately measuring 2 mL, drying to 1mL under nitrogen, performing initial mobile phase constant volume, passing through 0.22 μm nylon organic phase needle type microporous filter membrane, and preserving the chromatographic sample injection vial at-18 ℃.

The hormone-interfering chemical information is shown in Table 1:

TABLE 1 basic information of 86 HDCs standard substances

2.2 Instrument analysis method

UHPLC conditions, column temperature: 40 ℃ for column XBridge C ₁₈ (3.0X105 mm,2.5 μm), flow rate: 0.2 mL/min, sample injection amount: 10. Mu.L, mobile phase I:1 mmol/L ammonium formate aqueous solution (containing 0.1% formic acid) -acetonitrile, mobile phase II:0.01% aqueous ammonia solution-acetonitrile, liquid chromatography gradient elution procedure details are shown in Table 2, typical hormone interferent characteristic ion flow chromatograms are shown in FIG. 1.

TABLE 2 gradient elution procedure for liquid chromatography acidity and basicity HDCs

HRMS conditions of ion source HESI source, spray voltage of positive ion mode 3.0 kV, negative ion mode 2.5 kV, ion transmission tube temperature of 325 ℃, sheath gas (N ₂) flow rate of 50 arb, auxiliary gas (N ₂) flow rate of 10 arb, purge gas (N ₂) flow rate of 1 arb, heating temperature of 350 ℃, RF-lens voltage of 35%, scanning mode of positive and negative ions simultaneous scanning, acquisition mode of Full MS/dd-MS2, scanning range of 100-1000 m/z, resolution of first stage 60000, second stage 15000;Automatic gain control:standard;Maximum injection time:Auto;Loop count second stage 3 times, MSX number of 1;Isolation window:2 m/z, dynamic exclusion:3.0 s, energy using normalized collision energy HCD Collision energy normalized (NCE,%) and optimizing energy by needle pumping standard solution to the best.

2.3 Database construction and non-targeted authentication

The basic information of 86 types HDCs of standard substances is collected, the retention time, the accurate mass number and the like of the mass spectrum information are obtained through a Full MS Full scanning mode (table 3), and the information is imported into a Database to obtain a first-level accurate mass number fingerprint identification Database (Database). And in dd-MS2 mode, a secondary fragment ion characteristic spectrum chart library (mzVault Library) is obtained through cracking under different collision energies. The database construction detailed method comprises the following steps:

Establishing an electronic identity information database of 86 hormone interferents, wherein the electronic identity information database comprises information such as Chinese and English names, molecular formulas, CAS numbers, retention time, parent ion accurate mass numbers, isotope distribution, secondary fragment accurate mass numbers, ion addition states, optimal normalized collision energy (HCD collision energy), spectrogram library (mzVault Library) and the like. The method consists of two plates of a compound primary fingerprint identification Database (Database) and a secondary HCD fragment ion characteristic spectrum library (mzVault Library), and comprises the following construction methods:

Basic chemical information such as Chinese and English names, molecular formulas, CAS numbers and the like of 86 hormone interferents is collected, the information is imported into a database, and TRACEFINDER software automatically calculates the accurate molecular weight of the compound which is filled to five positions after decimal places according to the molecular formulas.

(1) And acquiring full-scan data of the prepared 500 ng/mL mixed standard solution by using ultra-high performance liquid chromatography-high resolution mass spectrum, obtaining a first-stage accurate mass number and retention time, and determining an optimal addition state. Wherein the addition state includes [ M+H ] +, [ M-H ] -, [ M+HCOO ] -. The information is input into a database and a collection method.

(2) Setting a collsion energy gradient value of 5-105% and a step length of 5% in an acquisition method, acquiring full-scan data of the prepared 500 ng/mL mixed standard solution by using liquid chromatography-high resolution mass spectrum, performing qualitative analysis by using FreeStyle software to obtain fragment ions with corresponding stability and relative mass deviation of <10 ppm as secondary ions, writing the fragment ions into a database, selecting collsion energy with a primary ion response of 1/3 of the highest response of the secondary ions as optimal collision energy, and writing the fragment ions into the acquisition method.

And (3) based on the automatic deconvolution function of the high-resolution mass spectrometry software, searching and matching the acquired data by using a self-built Database. The suspected compound is judged that ① retention time deviation is +/-0.5 min, ② accurate mass number deviation is +/-5 ppm, ③ isotope distribution error is less than 20%, ④ fragment ions are more than or equal to 2, mzVault Library is used for further confirmation of the suspected compound, and a matrix matching standard curve external standard method is used for quantitative analysis. The workflow of HDCs high throughput non-targeted screening is shown in figure 2.

2.3.1 Non-targeted screening scale:

The European Union (SANCO/12495/2011) requirement for validation of drug analysis results is that the mass accuracy deviation of at least two validated ions is less than 5 ppm. The parameter setting of the screening method can directly influence the screening result, and false positive and false negative detection results are easy to generate. Therefore, in the experiment, blank matrix standard solution and solvent standard solution are used for pre-screening, and screening parameters are adjusted until all compounds in the mixed label are screened out.

The recommended value for the ion peak intensity threshold (Threshold Override) is 5000, since the environmental impurity response is typically below 5000, but the response may be less than 5000 when the sample is found to be low in hormonal interferent or when the matrix effect is strong during sample screening, so this threshold is not set to avoid missed detection during screening. But this threshold can be set to exclude impurity interference during fragment ion screening.

The retention time Window (Window over) was set to 30 sec, which is an important index for identifying compounds, and the peak time of the 65 hormone interferents in the ultra-high performance liquid phase was concentrated in the first 20: 20 min, which was set to 30 sec according to the experimental accumulation, and the positive and negative expansion of the retention time of 15: 15 sec was optimal.

The accurate mass-to-charge ratio of the compound can be measured by the mass spectrum of the electrostatic field orbitrap in the mass-to-charge ratio deviation range (Mass Tolerance), and according to experimental results, the theoretical mass-to-charge ratio and the actually measured mass-to-charge ratio are found to be often not different by more than 5 ppm, so that the mass accuracy window of the parent ion is set to be 5 ppm. The accuracy window for the secondary ion fragments is properly enlarged to 10 ppm because in actual sample screening, secondary fragment formation interference may occur due to collision due to sample matrix, concentration, etc., the fragment strength may be low but the deviation will not generally exceed 10 ppm.

The non-targeted qualitative screening mainly uses the created parent ion accurate mass-charge ratio database and the high-resolution fragment ion mass spectrogram database as reference basis, and assists in screening under four conditions of retention time and isotope distribution characteristics, wherein key parameters are set as follows:

Parent ion as screening condition is Threshold Override peak intensity threshold, S/N Ratio Threshold signal-to-noise threshold, 5.0;Mass Tolerance mass-to-charge ratio deviation allowable range, 5 ppm.

The retention time was used as a screening condition, window Override: retention time deviation Window threshold 30 sec.

The sub-ions are used as screening conditions, namely the matched minimum fragment number 2;Intensity Threshold, the peak intensity threshold 5000;Mass Tolerance and the mass-to-charge ratio deviation allowable range 10 ppm.

Isotope peak mode as screening conditions, fit Threshold (%) similarity 80%, allowed Mass Deviation (ppm) allowed mass to charge ratio deviation 5 ppm;Allowed Intensity Deviation (%) allowed intensity deviation 20%.

If all four conditions can be met, the existence of the target compound in the sample to be detected can be determined, and if all the conditions are not met, the detection can be determined. If partial items are not satisfied, manual analysis is performed according to specific conditions.

In order to verify the scientificity and accuracy of the screening parameter setting, three blank matrixes of water, sediment and shrimps are selected in an experiment, mixed standard stock solutions of 86 hormone interferents are respectively added, the machine is used for detection according to experimental conditions, and an established database is utilized for pre-screening. Experiments have found that 86 hormone interferents are all able to be automatically screened for perfect matches by TRACE FINDER general 5.1.

2.3.2 Theoretical exact mass number and secondary mass spectrometry conditions:

The theoretical accurate mass number is that 49 compounds respond in positive ion mode, parent ions are [ M+H ] ⁺, 37 compounds respond in negative ion mode, wherein parent ions of 22 compounds are [ M+HCOO ] ^-, and parent ions of 15 compounds are [ M-H ] ^-. The theoretical exact mass numbers of 86 hormonal interferents are listed in table 3 and verified by comparing the data of the first full scan of the standard substance. The table shows that the relative mass deviation of 86 kinds of hormone interferents is lower than 5 ppm, which proves that the mass accuracy of the target compound is good, and the qualitative requirement is met.

And (3) secondary mass spectrometry conditions, namely obtaining the accurate mass number of the parent ions of the target compound through full scanning, setting a target object list according to the obtained accurate mass number, and automatically acquiring the secondary mass spectrometry scanning only when the parent ions in the list are found during primary mass spectrometry scanning and the intensity reaches a set threshold value (1 multiplied by 10 ⁵). However, in the experimental process, the number of secondary mass spectrum acquisition points of some substances is too small, and some isomer substances can only acquire the secondary mass spectrum of one of the substances, which may be related to factors such as poor dynamic exclusion (Dynamic exclusion) parameter setting range or Apex excitation (Apex trigger). Better fragment ion information is obtained by optimizing parameters such as dynamic exclusion, vertex triggering, topN and the like. Firstly, the dynamic elimination is adjusted by adjusting, optimizing and adjusting to find that the dynamic elimination time is optimal to be half-peak width and is optimal to 6 s and 3 s, but the dynamic elimination time is finally determined to be 3 s according to most peaks due to different width effects of 86 hormone interferents. Secondly, the Apex excitation (Apex trigger) also affects the acquisition effect of the secondary mass spectrum, and the principle is that a time range is set according to the peak width of the chromatographic peak, and the secondary mass spectrum is acquired after a period of time delay after the peak is generated, so that the time for triggering MS ₂ is as far as possible at the peak top position of the chromatographic peak, and a high-quality MS ₂ spectrogram is obtained. However, since the compounds detected in the experiment are numerous, the peak widths are not completely consistent, and the set period of time cannot ensure that all the compounds excite the secondary at the peak top point, so that the effect is better instead of starting the function. The analysis result has the accurate mass number of the parent ions and the secondary fragment ion information, so that the qualitative accuracy is improved, and the occurrence probability of false positive is greatly reduced. Information on parent ion, fragment ion, etc. of 86 hormone interferents is shown in Table 3.

2.3.3 Isotopic characteristic abundance analysis:

in the screening analysis, in addition to differentiating by means of parameters such as the exact mass-to-charge ratio, retention time, etc. of the target compound, isotope characteristic distribution can also be utilized to enhance the performance of the screening method. For compounds having an isotopic pattern, each peak abundance of the mass spectrum is related to the number of atoms of the isotopic element present in the ion and the natural abundance of each isotope, and thus the presence or absence of a certain element in the sample can be deduced. The isotopic peak intensities at which the excimer ion peaks occur can be calculated from the binomial expansion. Wherein a represents the relative abundance of light isotope, b represents the relative abundance of heavy isotope, and n represents the number of atoms of isotope element in the molecule.

The abundance ratio can be directly calculated by software in TRANCEFINDER systems. The hormone compounds screened in this way mostly contain C, H, O, N, cl and the like. The elements have various isotopes such as ¹⁶O（99.756%）、¹⁷O（0.039%）、¹⁸O（0.205%）、¹⁴N（99.64%）、¹⁵ N (0.36%), and the like, for example, the accurate mass number and abundance ratio of the isotope peaks in the sample are matched with the calculated data, so that the possibility of the sample in existence of the sample is high. The accurate mass numbers of isotope peaks of a certain substance in the object to be detected can be matched, but the abundance ratio of the second isotope peak is not matched, and further confirmation is needed according to the information such as fragment ions.

2.3.4 Theoretical exact mass number and secondary mass spectrometry conditions

Table 3 86 HDCs chromatographic mass spectrometry fingerprint identification and feature spectrogram database

X represents no fragments or fragments are not characteristic, and are characterized by adopting the primary parent ion binding retention time and isotope distribution.

2.4 HDCs ecological risk assessment

The Risk Quotient (RQ) algorithm was used to assess the health risk of HDCs in the aquatic ecosystem of the study area, and the derivation of the predicted ineffective stress concentration (PNECs) and its associated toxicity data are detailed in Table 4.

Table 4 concentration of null response (PNECs) to derive predicted toxicity data

S8 HDCs calculation of Risk Quotient (RQ)

Risk Quotient (RQ) is used to evaluate HDCs ecological risk to aquatic organisms and is divided into three classes, low risk (RQ < 0.1), medium risk (0.1 < RQ < 1) and high risk (RQ > 1). The formula for RQ is shown below:

MEC is the measured ambient concentration, PNEC is the predicted null-response concentration, the value of which can be calculated by:

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

RQ values for assessing risk of hormonal interferents were calculated using the following equations.

All toxicity data for HDCs were from

1. U.S. environmental protection agency (US EPA) ECOTOX database (https:// cfpub. EPA. Gov/ecotox/search. Cfm)

NORMAN ecotoxicology database (https:// www.norman-network. Com/nds/ecotox/lowestPnecsIndex. Php)

3. U.S. environmental protection agency (US EPA) (ECOSAR) model (v 2.0, U.S. EPA)

2.5HDCs priority ordering

The potentially high risk HDCs is risk ranked using an optimized RQ algorithm to identify and lock HDCs that should be prioritized.

To identify HDCs that should be preferentially controlled, the present invention introduces an optimized risk quotient based on average RQ values (RQM) and individual HDCs measured concentrations exceeding PNEC frequency (F), with systematic evaluation and ranking of potential high risk HDCs to determine compounds that should be preferentially managed.

In the present invention, N and N represent the number of samples whose actual concentration exceeds PNEC and the total number of samples detected, respectively. In order to more accurately reflect the actual sample condition with risk, and avoid dilution risk assessment results, the invention adopts a sample which only considers HDCs to be detected. The target compounds are classified into five classes according to risk level, high risk (PI. Gtoreq.1), medium risk (0.1. Gtoreq.pi < 1), affordable risk (0.01. Gtoreq.pi < 0.1), negligible risk (0 < PI < 0.01), and safe (pi=0).

2.6 Data analysis

Data acquisition, qualitative screening and confirmatory quantification were performed using Xcalibur 4.4, freestyle 1.8 and TRACEFINDER 5.1.1 (Thermo FISHER SCIENTIFIC company), respectively, spearman correlation and Principal Component Analysis (PCA) using SPSS v25.0 (SPSS inc., MA), origin 2018 (Origin lab company, MA), source resolution of HDCs using the positive definite matrix decomposition model (PMF 5.0) of the United States Environmental Protection Agency (USEPA), and spatial distribution of HDCs in water, sediment and suspension was generated by ArcGlS 10.8.

3. Results and discussion

3.1 Selection of extraction column for sample pretreatment

Using the collected aquatic ecosystem samples as research matrixes, the adsorption and purification effects of four extraction columns ^25–28 of AGELA CLEANERT S C ₁₈, oasis HLB, oasis PRiME HLB and CAPTIVA EMR LIPID on the hormone interferents in different matrixes are examined (figure 3 a), the average recovery rate of the hormone interferents in each matrix is highest when the Oasis PRIME HLB is adopted, the adsorption and purification effects of different filler amounts of the Oasis PRIME HLB (1 cc 30 mg/3 cc 60 mg/3 cc 150 mg/6 cc 200 mg/6 cc 500 mg) are further examined (figure 3 b), and the average recovery rate of the hormone interferents in each matrix is highest when the filler amount is 6 cc 200 mg.

3.2 Instrument analysis condition customization

3.2.1 Selection of chromatographic columns

The experiments examined the separation of 86 hormone interferents from Thermo Accucore Vanquish C₁₈（2.1×100 mm,1.5 μm）、Agilent Eclipse plus C₁₈（3.0 mm × 150 mm,1.8 μm） and Waters Acquity BEH C ₁₈ (2.1. 2.1 mm ×100 mm,1.7 μm) and Waters XBridge C ₁₈ (3.0×150 mm,2.5 μm) by four different chromatographic columns. The peak shape tailing and sharpness of the first three chromatographic columns are found to be poor in different degrees, while the peak shape of the Waters XB ridge C ₁₈ is free from obvious tailing and is sharply symmetrical, so that effective separation of 86 hormone interferents can be achieved at the same time, for example, the peak shape of a typical hormone CMT is well improved (figure 4), which is possibly related to the unique bonding mode and end capping technology of the Waters XB ridge C ₁₈ chromatographic column.

3.2.2 Selection of mobile phases

The composition and ratio of the mobile phase can affect the chromatographic effect. In the present invention, a part of the hormone interferents can only show a peak in an alkaline or acidic mobile phase, for example, E2 does not show a peak in an acidic mobile phase (0.1% formic acid water+acetonitrile) and a peak in an alkaline mobile phase (0.01% ammonia water+acetonitrile) (FIG. 5), so that both the acidic mobile phase and the alkaline mobile phase are used simultaneously, and furthermore, when acetonitrile is adopted as an organic phase, it is found that all isomers can achieve baseline separation, and peak shapes of typical isomers in different organic mobile phases are compared with each other, as shown in FIG. 6. When 0.1% formic acid water and acetonitrile are examined as an acidic mobile phase, it was found that a part of hormone interferents hardly peaked, and then 5, 2 and 1 mmol/L ammonium formate were added to 0.1% formic acid water, respectively, and it was found that the baseline separation and response effect were optimal when 0.1% formic acid water of 1 mmol/L ammonium formate was added.

3.2.3 Selection of HRMS parameters

According to the invention, through comparing three scanning modes of Full MS, full MS/dd-MS ² and Target-SIM/dd-MS ², false positive results are found to be easily caused by Full MS, partial non-targeting information is lack of Target-SIM/dd-MS ², a first-level Full-scanning mass spectrogram can be obtained by Full MS/dd-MS ², the accurate mass relative deviation of 86 types HDCs meets requirements, in order to ensure an optimal acquisition interval, 86 types HDCs are all subjected to baseline separation when resolution (R1=60000 and R2=15000) is optimally selected, the experimental requirements are met, the size of collision energy has a direct relation to acquiring characteristic fragment ions, and when NCE energy gradient data-dependent acquisition technology is used for fragmentation of HDCs, the optimal collision energy of compounds such as Estradiol (100%) is found to be far greater than 50%, and the optimal collision energy of compounds such as Triamcinolone (10%) can be cracked under lower collision energy, so that the invention can use different NCE energy gradients (10% -100%) to see the optimal mass spectrum of the SBE energy spectrum 7. 86 HDCs collisions are shown in Table 3.

3.3 Isomer identification and methodological evaluation

3.3.1 Identification of isomers

The effective distinguishing identification of the isomer components with the same molecular and mass numbers and similar structures is an important guarantee for realizing rapid screening, 13 groups of isomer substances are found in a database, wherein the four elements are equally divided into 1 group, the three elements are equally divided into 4 groups and the two elements are equally divided into 8 groups, chromatographic separation is carried out by using an established UHPLC-Q/Orbitrap HRMS instrument analysis method, and the isomer substances are identified according to the difference of the retention time. Under the method, all 13 groups of isomers can realize baseline separation and can be effectively distinguished through retention time, and an isomer extraction ion flow diagram of 3 typical zearalanol compounds is shown in figure 8.

3.3.2 Methodology evaluation

In order to ensure the accuracy and reliability of the screening method, the quality of the method is particularly verified and evaluated. The verification result shows that 86 samples HDCs have good linear relation within the concentration range of 0.05- ‒ -ng/mL, the correlation coefficient (r) is not less than 0.9809, the water sample detection Limit (LOD) is 0.05-5 ng/L, the quantitative Limit (LOQ) is 0.15-15 ng/L, the other sample detection Limit (LOD) is 0.05-5 ng/g, the quantitative Limit (LOQ) is 0.15-15 ng/g, the total recovery rate of 86 samples HDCs is 68.7% ‒ 111.5.5% and the RSD is 2.3% ‒ 11.0.0% under the condition of 1-time LOQ ‒ -time LOQ addition level, and the accuracy and precision of the established method of the invention are proved to meet the experimental requirements. Matrix effect evaluation shows that 86 kinds of HDCs matrix effects in water, suspended matters and crabs are in the range of 80% -120%, namely matrix effect is not obvious, CMA in sediment is expressed as Matrix Inhibition Effect (MIE), M1T in freshwater fish is expressed as Matrix Enhancement Effect (MEE), TRB, DAN and BM are expressed as MIE, epiA in shrimps is expressed as MEE, and TRB, MD and beta-ZOL are expressed as MIE.

3.4 HDCs occurrence pattern

The present invention identified class 4 HDCs, ERs detected in all study media, whereas ARs was mostly detected only in surface water (fig. 9 a), HDCs exhibited different patterns of occurrence in different media (biological versus non-biological) (fig. 9b, c, d, e), indicating a broader distribution of HDCs in the aquatic ecosystem in the adult city (tables 5-7).

TABLE 5 HDCs detection rate, concentration Range and mean in Chengdu aquatic Environment (Water, sediment and suspended matter)

TABLE 6 detection rate, concentration Range and average value of hormone disruptors in Chengdu aquatic foods (grass carp, carassius auratus and eel)

TABLE 7 detection rate, concentration Range and average value of hormone disruptors in Chengdu aquatic foods (shrimps, crabs and frogs)

GCs, from the HDCs category, appears most pronounced in shrimp, suspension and frog samples, and in addition, there is a significant concentration of GCs in surface water, sediment and suspension, possibly related to its specific physicochemical properties (Kow value, solubility and adsorption propensity etc.). ERs are then mainly enriched in shrimps, up to 392.9 ng/g, which may be related to endogenous hormones of the organism. SABAs detection is more uniform, but less frequently in water and suspended matter. The ARs detection rate is lower, the ARs detection rate is mainly concentrated in water, and the concentration is 12.2 ng/L at the highest, which indicates that the occurrence level in the environment is lower.

From the sample category, the detection rate of GCs and ARs in surface water is higher, particularly the detection rate of DXM reaches 10%, and the concentration range is 17.8-45.6 ng/L, which is similar to the concentration level of DXM (12 ng/L-45.6 ng/L) in European urban water. RCP detection rate is 4% and its concentration range is 0.5-10.7 ng/L.ERs detection rate is lower, but its concentration may still be potentially risky. In the sediment, the detection rate of DXM is 7%, the concentration range is 12.3-29.0 ng/g, the average concentration is 18.9 ng/g, and the enrichment phenomenon highlights the key role of the sediment as a HDCs long-term storage pool. The HDCs concentration levels in suspension are higher than surface water and sediment, especially the migration effects on GCs and SABAs are significant, e.g. DXM concentrations of 35.6-50.2 ng/g, indicating that the suspension is the main carrier of HDCs migration in the body of water, that the overall detection rate of HDCs in aquatic foods is low and that most are not detected in organisms, which may be related to the strong metabolic degradation capacity of organisms. Notably, E1 was detected at a higher rate in shrimp (57%) and frog (24%), which may be related to endogenous hormones of these organisms.

3.5 HDCs spatiotemporal distribution characteristics

HDCs in the present invention exhibited significant spatiotemporal heterogeneity, with similar trends in seasonal variation of different environmental samples from time to time (fig. 10a, b, c, d), spring and winter being peak periods of HDCs concentration, which may be associated with increased spring agriculture and livestock activity. And in winter, the water diffusion capacity is reduced, the air temperature is reduced, the pollutant degradation rate is slowed down, and the HDCs concentration is increased. HDCs in aquatic foods exhibit a seasonal variation that is significantly different from the environmental medium. The higher concentrations of HDCs in spring and summer, especially ERs, reached 399.5 ng/g and 159.4. 159.4 ng/g in spring and summer, respectively, which may be related to changes in henry coefficients, low water levels, etc. due to high temperatures in the biological growth phase and summer. In comparison, lower concentrations of HDCs in autumn and winter aquatics indicate faster degradation of these seasonal contaminants, or reduced bioabsorption. Spatially (fig. 10 e, f, and g), the concentration of contaminants in the south area is high, and the river tends to increase from upstream to downstream and is affected by seasonal variations and biological processes. The sediment is more contaminated in the eastern area, while the suspended matter is severely contaminated in the southern area. Wherein the spatial differences in surface water HDCs are significant, especially in the downstream regions of FHR, JAR and MJR. The concentration of mainly GCs in surface waters, such as DXM is higher downstream of FHR (45.6 ng/L), MJR (31 ng/L) and JAR (22.8 ng/L), which may be related to upstream medical and domestic wastewater discharge. RCP in SABAs is higher in concentration downstream of FHR (12.3 ng/L) and downstream of JR (5.2 ng/L), while ORC is concentrated downstream of JAR (6.6 ng/L) and downstream (1.8 ng/L), possibly for animal husbandry emissions. The HDCs spatial distribution in the sediment was similar to surface water, but there was a significant difference in concentration levels. ERs showed a higher tendency to accumulate in sediments, similar to the phenomenon of the European Agate and North America great lakes, where HTS had a higher concentration downstream of FHR (9.6 ng/g), QLL (13.2 ng/g) and MJR (16.8 ng/g), ORC had a higher concentration upstream of QLL (9.4 ng/g) and JR (17.8 ng/g), indicating that these areas were severely contaminated with ERs, the major sources of which may be animal husbandry, agriculture and domestic sewage GCs were widely distributed in water sediments such as JAR, FHR, QLL, MJR and JR, in the range of 0.6 to 29.0 ng/g.DXM (18.2 ng/g) upstream of JAR, The sediment in the water areas such as FHR downstream (19 ng/g) and QLL (12.3 ng/g) is more prominent, four types HDCs of suspended substances are detected, the concentration is different from 0.2 ng/g to 50.2 ng/g, the obvious difference of different pollutants in the water body is shown, the concentration of DXM in the JAR and the FHR downstream is the highest, and the concentration of CLB, CPR, PBT in SABAs in the JAR and the FHR downstream is higher and is between 0.7 and 21.9 ng/g.

3.6 HDCs Source resolution

In surface waters (fig. 11a, b, c) 3 factors were determined as optimal solutions, R2 was between 0.621 and 0.999, with factor 1 the contribution rate of BM being highest (97.1%), followed by RCP (95.1%), DXM (71%) and FMT (57.1%), BM and DXM were commonly used to treat inflammation, possibly from pharmaceutical factories or medical waste. RCP may originate from animal husbandry waste water and FMT may originate from gymnasium, pharmaceutical factories, so factor 1 is mainly due to medical waste water of factor 2, DES's contribution is highest (92.1%), and BDN (87.7%), may be the source of gymnasium drug abuse into the environment. In factor 3, the contribution rate of ORC is as high as 98.3%, which is widely used in livestock and aquaculture. Next to FMT (19.1%), ORC concentrations as high as 3.5 ppm have been detected in Vietnam aquaculture wastewater, thus factor 3 is mainly attributed to the livestock aquaculture industry. In the sediment (fig. 11d, e, f) 3 factors were determined as optimal solutions, R2 was between 0.956 and 0.999, and in factor 1, HTS contribution rate was significant (98.5%). HTS was widely present in daily necessities and discharged into the environment through 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, where DXM concentrations as high as 117-545 ng/L, TC concentrations of 14-41 ng/L, E1 are endogenous hormones, mainly through human and animal metabolites into the sewage system have been found in the hospital wastewater in the netherlands. Thus, factor 2 can be attributed to a source of combined contamination of medical wastewater and domestic sewage. The factor 3 contribution was highest with ORC (98.7%), followed by PL (87.4%). ORC is mainly used for preventing and treating bacterial infection, PL is often used for treating immune diseases, and waste water containing ORC and PL may be generated in the production process of pharmaceutical factories. Thus, factor 2 is mainly associated with medical wastewater discharge. In the suspensions (fig. 11 g, h, i) 3 factors were determined as optimal solutions, R2 was between 0.727 and 0.999, with factor 1 the highest E2 contribution rate (96.7%), followed by DXM (68.5%) and HC (41.6%), and E2 was a human metabolite, widely present in urban sewage. DXM is commonly used to treat skin disorders, mainly by being enriched in aqueous suspensions by fecal matter. HC is an anti-inflammatory agent that may be enriched in suspended matter by domestic sewage. Of the factors 2, the BEN contribution rate is highest (96.2%), followed by BDP (99.3%), PBT (98.7%) and DXM (31%). They are all mainly used for the treatment of male hormone related diseases, enriched in suspension by medical waste water, and therefore factor 2 is mainly derived from medical waste water. Factor 3 mainly relates to animal husbandry wastewater, the contribution rate of CLB is up to 99.2%, and a farm using the CLB as a growth promoter illegally is a main pollution source of the factor. The contribution rate of HC (34.1%) is relatively low, but it is not negligible because of its wide use in livestock.

3.7 HDCs ecological risk evaluation and optimal control sequencing

RQ values in surface water, sediment and suspended matter were analyzed HDCs according to risk class (fig. 12a, b and c). The results show that the RQ values of the surface water are all below 0.1, and the risk is low. The RQ values of PL and DXM in the sediment varied between 0.13-0.64 and 0.06-0.15 respectively, mostly at moderate risk, whereas the RQ value of HTS varied between 1.09-15.27, with high ecological risk. HC, DXM and E2 in the suspension samples are at moderate risk, the highest RQ values for CA, CLB and PBT are 7.56, 3.40 and 14.22 respectively, and the ecological risk is extremely high. Notably, the partial point RQ values in the sediment and suspension are much higher than in surface water, probably due to the adsorption, accumulation and bio-amplification effects of the fraction HDCs, making the sediment and suspension with higher adsorbed particulate organic carbon content a "sink" of HDCs.

The invention further employs an optimized RQ algorithm to calculate a Priority Index (PI) based on PNEC frequency for comprehensive risk ranking (Table 8). The results show that HDCs risk grades in surface water are all safe, and HDCs in sediment is classified into medium risk and safe. Among them, HTS, PL and DXM constitute a high or medium risk in the traditional RQ method, but are identified as medium and safe contaminants due to their low superscalar frequency, CA, PBT and CLB in the suspension samples are medium and affordable. Other HDCs have PI values of 0, indicating that the current concentration does not constitute an ecological risk, and in medium HDCs of great concern, HTS are listed in the World Health Organization (WHO) and the federal grain and farming organization (FAO) regulatory lists, and PBT and CA are listed in the european Water Frame Directive (WFD) observation list, thus locking HTS, PBT and CA as the aquatic ecosystem optimization targets in the capital.

TABLE 8 priority index of targets HDCs in aquatic ecosystem

4. Discussion:

On the basis of constructing a multi-target sample high-throughput pretreatment method and an UHPLC-Q-Orbitrap HRMS instrument analysis technology, a HDCs high-throughput non-targeted identification strategy with satisfactory methodology evaluation results is developed by combining a mass spectrum fragmentation rule through a self-built electronic identity characteristic database of 86 seeds HDCs. Through large-scale sample analysis of a year period, 17.85% of 409 samples collected from 4 rivers and 3 lakes in a research area are positive, 24 HDCs samples are identified, mainly GCs, ERs and SABAs.ers are detected in all research media, the GCs is obviously expressed in shrimp, suspended matters and frog samples, the concentration of HDCs in spring and summer is higher, and the pollution degree from upstream to downstream is increased. The source-sink relationship finds that domestic sewage, medical wastewater and aquaculture wastewater are main pollution sources, and HDCs's priority index locks HTS, PBT and CA as priority prevention and control objects.

In a word, the high-throughput non-targeted screening and risk assessment strategy constructed by the application of the invention comprehensively reveals the occurrence, season distribution law, main carrier and risk level of HDCs in the aquatic ecosystem of the oversized city for the first time, and locks the priority prevention and control object. The strategy not only has wide global applicability, but also provides valuable insight for the management layer to formulate targeted prevention and control measures, future researches should be focused on focusing on the migration and transformation process HDCs in the aquatic ecosystem and the complex influence of the migration and transformation process on the food chain, and evaluation of the long-term effect of HDCs pollution on the environment and human health, so that the method is helpful for more comprehensively coping with HDCs pollution problems and providing powerful guarantee 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 comprises 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 N ₂ flow rate: 50 arb; auxiliary gas N ₂ flow rate: 10 arb; purge gas N ₂ 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;

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 compound primary fingerprint recognition 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 to obtain the primary accurate mass number and retention time, and determine the best additive state; wherein the additive state includes [M+H]+, [M-H]-, 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 uses the risk quotient RQ algorithm to assess the health risks 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 for 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: an optimized RQ algorithm is used to perform risk ranking on potential high-risk HDCs to identify and lock in HDCs that should be controlled with priority; 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.