CN115201384A - Method for evaluating and detecting exposure risk of multiple pollutants in hair of large-scale crowd - Google Patents
Method for evaluating and detecting exposure risk of multiple pollutants in hair of large-scale crowd Download PDFInfo
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Abstract
The invention discloses an exposure risk assessment and detection method for multiple pollutants in large-range crowd hair, which comprises the following steps: s1: determining the pollutants and the exposure markers which have a correlation relationship as target detection objects; s2: establishing a correlation analysis model; s3: collecting and classifying samples; s4: detecting a sample to obtain data; s5: and (4) performing the health risk exposure evaluation of the large-scale population, and calculating and evaluating the exposure risk of the large-scale population on the basis of the data of the exposure marker mPAEs. By the collaborative optimization of the evaluation and detection method, the invention enables a plurality of target detection objects in the hair to be synchronously detected and analyzed, reduces the types of the target detection objects, simplifies the detection steps, reduces the detection cost, expands the application range of the detection data and the health exposure risk evaluation result, can greatly reduce the labor, instruments, consumables and time required by detection, and is beneficial to large-scale and large-scale popularization and application.
Description
Technical Field
The invention belongs to the technical field of organic pollutants and medical detection, and particularly relates to an exposure risk assessment and detection method for multiple pollutants in hair of large-range crowds based on correlation of exposure markers.
Background
Perfluorinated compounds (PFASs) are organic compounds with stable C-F bonds, which have excellent chemical stability and thermal stability, and are both hydrophilic and hydrophobic, and are widely applied in various fields such as chemical industry, leather, textile, daily detergents, fire fighting, cooking utensils manufacturing, etc., and closely related to people's daily life. There is increasing evidence that PFASs can be enriched in organisms and that some PFASs are dangerous to human health. PFASs can enter the human body via skin contact, respiratory inhalation and dietary intake, wherein perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) are found in the liver, kidneys and blood, even including some central nervous system. PFASs have attracted extensive attention as a class of environmental pollutants acting on multiple organs of the whole body due to various toxicities such as carcinogenicity, developmental toxicity, immunotoxicity and the like. Phthalates (PAEs) are considered to be environmental hormones ubiquitous in the living environment. PAEs are mainly used in hundreds of products such as toys, food packaging materials, medical blood bags and hoses, vinyl floors and wallpaper, detergents, lubricating oils, personal care products (such as nail polish, hair sprays, soaps, and shampoos). Excessive exposure of the human body to PAEs can cause acute poisoning, and even death can be caused seriously. Relevant research shows that PAEs can mutate human cells by changing human chromosomes; PAEs also cause damage to internal organs in the body, such as the liver, heart and lung, genitals, etc. With the deep understanding of pollution and harm of PAEs, the development of exposure monitoring on PAEs is very important. PAEs are metabolically converted into monoester metabolites, i.e. phthalate exposure markers (mPAEs), upon entry into the organism. In the exposure evaluation of PAEs, merely detecting the parent compound content is likely to greatly underestimate the health risk of such environmental pollutants, and therefore it is necessary to conduct the detection analysis of both PAEs and mPAEs.
Organic pollutants such as PFASs, PAEs and mPAEs coexist in human hair samples, but the concentrations of the organic pollutants are all in trace level, and synchronous detection is difficult. In the prior art, the treatment and detection of PFASs, PAEs and mPAEs in hair are usually carried out independently, for example, chinese patent application CN202110181360.6 discloses a detection method of PFASs in a serum sample, which comprises the following specific steps: s1, sample pretreatment: adding acetonitrile into a sample, performing vortex mixing, standing, centrifuging, drying supernatant A by using nitrogen, redissolving by using an extracting solution, and centrifuging again to obtain supernatant B; s2, sample detection: preparing a standard solution, drawing a calibration curve, setting detection conditions of liquid chromatography and mass spectrometry to detect a sample, and analyzing a detection result. However, this method uses a serum sample substrate containing a small amount of impurities and does not require the steps of washing, cleansing, etc., and thus it is difficult to apply this method to complicated sample treatments of substrates such as hair, etc., and this method fails to detect both perfluoro compounds and phthalic acid esters. The Chinese patent application CN 112229935A discloses an analysis and detection method for perfluorinated compounds, which firstly utilizes polypyrrole nano fibers to enrich the perfluorinated compounds, and then adopts liquid chromatography tandem mass spectrometry to detect the perfluorinated compounds in food contact materials, foods and the like, but the method has the defects of complex steps and incapability of simultaneously detecting the perfluorinated compounds and phthalic acid esters due to the fact that the polypyrrole nano fibers are adsorbed and purified by a solid-phase extraction column; the Chinese patent application CN 111474259B discloses a method for synchronously extracting and analyzing multiple flame retardants in hair, but most target compounds detected by the method are nonpolar compounds, the method is difficult to be applied to analysis of polar compounds such as perfluorinated compounds, phthalic acid esters and exposure markers thereof, and the method needs to adopt extraction and purification steps such as digestion and solid-phase extraction, and has long time consumption and high analysis cost. Obviously, the methods all have the defects of complicated sample treatment, detection and analysis steps, long time, more solvent consumption, high analysis cost and the like, and are difficult to be applied to the rapid detection and exposure evaluation of the perfluorinated compounds, the phthalic acid esters and the exposure markers thereof in the hair samples of large-batch crowds.
Therefore, the content detection of organic pollutants such as PFASs, PAEs and mPAEs in human hair samples disclosed at present cannot synchronously detect the PFASs, the PAEs and the mPAEs, quantitative detection data of the PFASs, the PAEs and the mPAEs can be respectively obtained only by analyzing the samples for multiple times, the treatment process is long in time, the solvent amount is large, the treatment cost and the analysis time are large, detection and analysis of a large number of samples in a large range in medicine and epidemiology cannot be carried out, and meanwhile, the method is not beneficial to environmental protection and is not beneficial to protecting the body health of detection and analysis operators. Meanwhile, synchronous detection of various detection objects such as PFASs, PAEs and mPAEs cannot be completed in one detection process, data obtained by three-time detection is difficult to obtain accurate and stable detection results due to the fact that influence and detection errors caused by sample change, various detection condition changes and the like in the detection process are increased, and the method is used for accurately analyzing the correlation among the PFASs, the PAEs and the mPAEs.
In addition, the existing method for evaluating the exposure risk of various pollutants can be carried out only by acquiring concentration data of more components through detection; in the process of detecting PFASs, PAEs and mPAEs in hair in a large range and high flux, all components capable of being detected in the prior art are detected, and the components are applied to health exposure risk assessment, so that the detection and analysis assessment process is complex, the labor cost, the instrument cost, the consumable material cost and the time cost of detection and analysis are greatly increased, the requirements of exposure risk assessment and detection of various pollutants in the hair of a large-range high-flux crowd are difficult to meet by adopting the existing detection technology and analysis assessment technology, and the large-range popularization and the popularization of the pollutants are limited.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides the exposure risk assessment method for multiple pollutants in the hair of a large-range crowd, which can support the exposure risk assessment and analysis based on less key component detection data related to exposure markers and obtain a result with high reliability, thereby greatly simplifying two links of detection and analysis; while enabling the acquisition of exposure marker data for medical or clinical analysis of individuals and populations;
the invention also aims to provide a method for detecting multiple pollutants in hair of a large-scale population by implementing the exposure risk assessment method, which can synchronously detect and analyze PFASs, PAEs and mPAEs and obtain data of multiple components (especially exposure markers) in one detection process; on the other hand, the method can greatly reduce the types of target detection objects according to the requirements of analysis and evaluation, and can support the exposure risk evaluation method only by detecting the concentration of one component in the paired target detection objects serving as the exposure markers, so that the labor, instruments, consumables and time required by detection are greatly reduced, and the method is favorable for large-scale and large-scale popularization and application.
The technical scheme provided by the invention for solving the problems is as follows:
a method for assessing exposure risks of multiple pollutants in hair of a large-scale crowd is characterized by comprising the following steps:
s1: determining the pollutants and the exposure markers with the correlation relationship as target detection objects: finding out various pollutant types in the hair of the crowd, screening various exposure marker types with medical research value according to a large-scale crowd exposure evaluation model, and further screening at least one group of relative pollutants PAEs and exposure markers mPAEs thereof with correlation as paired target detection objects;
s2: establishing a correlation analysis model: establishing a correlation analysis model of pollutants PAEs in a paired target detection object and exposure markers mPAEs, wherein Y = aX + b (formula 1), wherein X is PAEs concentration, Y is mPAEs concentration, a is a proportionality coefficient, and b is a correction coefficient;
s3: collecting and classifying samples: collecting hair samples of people in a large range, recording sample source information, processing the hair samples into a plurality of samples to be detected, taking information data of sex, age and exposure source contact condition of a sampling object as classification variables, and taking concentration data of PAEs and mPAEs in the hair obtained through detection as variables;
s4: detecting sample acquisition data: respectively detecting target detection objects in collected samples to be detected of a large-range crowd, and at least acquiring concentration data of one of PAEs and mPAEs;
s5: and (3) carrying out large-range crowd health risk exposure assessment: substituting one of the known PAEs and mPAEs concentration data into formula 1, fitting the undetected compound concentration in the hair sample under the same categorical variable group, completing the concentration data, and further calculating and evaluating the exposure risk of a large-range crowd on the basis of the data of the exposure marker mPAEs.
A method for detecting multiple contaminants in hair of a wide range of people implementing the aforementioned exposure assessment method, comprising the steps of:
A. cleaning the sample to remove exogenous contaminants;
B. sample pretreatment: pretreating a sample, extracting supernate from a unit sample and an internal standard substance by adopting a solid-liquid extraction method, and concentrating the supernate to obtain a sample extracting solution to be detected;
C. sample detection: synchronously pretreating the extracting solution by adopting ultra performance liquid chromatography-tandem mass spectrometry to synchronously obtain the whole chromatograms and mass spectrograms of PFASs, PAEs and mPAEs of the sample;
D. obtaining quantitative detection data: and (3) respectively calculating the component contents of PFASs, PAEs and mPAEs in the sample according to the detection of an internal standard method, and at least calculating the component content of one of the paired target detection objects.
Compared with the prior art, the method for evaluating and detecting the exposure risk of various pollutants in the hair of large-scale crowd has the following beneficial effects:
1. according to the method, based on the correlation between pollutants and exposure markers, the evaluation and analysis steps of perfluorinated compounds, phthalic acid esters and the exposure markers in the hair are simplified synchronously and greatly, so that a small amount of core exposure marker component concentration data are obtained through detection, and the exposure risk evaluation of various pollutants in the hair of people can be completed through data fitting, so that the labor, instruments, consumables and time required by detection are greatly reduced, and the method is favorable for large-scale and large-scale popularization and application.
2. Based on the correlation between pollutants and exposed markers, PFASs, PAEs and mPAEs components in a hair sample with large range, long period and high flux are synchronously detected and analyzed, or key detection and analysis are carried out, so that the limitation of the prior art is greatly broken through. The invention utilizes the physical and chemical property difference of PFASs, PAEs and mPAEs and the characteristic that PAEs are partially metabolized and converted into mPAEs in human bodies, optimizes the steps of sample treatment, detection and analysis, does not need to carry out solid phase extraction, enrichment and purification on samples, synchronously detects PFASs, PAEs and mPAEs to obtain accurate data, and further analyzes the relation between PAEs and corresponding exposure markers mPAEs in hair samples, on one hand, the invention can effectively solve the problems of complicated pretreatment process and high cost in the prior art, and the method can be effectively applied to the screening and detection work of large-scale crowd hair samples; on the other hand, the types of the crowd exposed compounds capable of being synchronously processed, detected and analyzed are greatly improved, the system error formed by independent detection is reduced, a more accurate result is obtained, and more accurate data support is provided for sensitive crowds such as occupational exponentials to take accurate health protection measures; and finally, acquiring an empirical coefficient by establishing a correlation between the PAEs and the exposure marker thereof, and providing a theoretical basis for simplifying the analyzed target compound under the condition of limited conditions.
3. The team discovers that PFASs, PAEs and mPAEs exist in a human hair sample at the same time through earlier researches, but the three substances have different components and characteristics, and certain technical difficulties exist when the three substances are treated and analyzed, so that no report on synchronous detection and analysis of PFASs, PAEs and mPAEs in the hair sample exists at present. However, the metabolic conversion of PAEs into mPAEs after entering the human body results in an underestimation of the internal exposure load of PAEs in humans. Therefore, the concentration data of PFASs, PAEs and mPAEs in the hair sample can be synchronously analyzed, so that the exposure condition in the human body can be accurately evaluated, and data support is provided for formulating measures for effectively protecting the exposed human body. In addition, the existing detection method needs to respectively carry out pretreatment and instrument analysis on three types of pollutants to obtain an accurate detection result, and needs to record, count and analyze the detection results of respective instruments, so that the defects of long analysis and detection time, overhigh consumption cost of manpower, machine time and consumables and the like exist. The invention better overcomes the defect.
4. The simplified evaluation method and the simplified detection method are combined with each other, PFASs, PAEs and mPAEs in the crowd hair sample can be synchronously detected and analyzed aiming at the requirement of high-throughput detection and analysis of large-scale crowd samples such as exposure of professional workers, the problems of complicated sample processing process and high cost are effectively solved, more importantly, the simultaneous detection of various biological exposure marker compounds is realized, the system error formed by independent detection is reduced, and more accurate results can be obtained, so that the exposure load in a human body is more accurately evaluated, and effective data support is provided for sensitive crowds to take targeted health protection measures.
5. According to the detection method provided by the invention, through optimizing the pretreatment step of the sample, the sample does not need to be subjected to solid phase extraction and purification, the problems of complex pretreatment process, complexity and high cost in the prior art can be effectively solved, and the method can be effectively applied to the screening and detection work of hair samples of large-scale crowds;
6. the detection method provided by the invention can synchronously detect PFASs, PAEs and mPAEs compounds in the hair, reduces the system error formed by independently detecting the PFASs, PAEs and mPAEs compounds respectively in the prior art, and can obtain more accurate results;
7. according to the detection method provided by the invention, through the improvement of a plurality of steps and methods, the complicated processes of respective extraction are avoided, the experimental steps are simplified, and the influence of the solid phase extraction process on the recovery rate of the target compound is effectively reduced under the condition of obtaining reliable method accuracy and precision. The method can be used for pertinently and synchronously detecting more than 29 perfluorinated compound (PFASs) components, more than 21 Phthalate (PAEs) components and more than 9 phthalate exposure marker (mPAEs) components in the hair in a synchronous analysis manner, or only detecting a plurality of the PFASs components, the PAEs components and the mPAEs components according to the evaluation requirement, so that the pretreatment, detection and analysis efficiencies of the hair sample are greatly improved;
8. the evaluation method and the detection method provided by the invention carry out mathematical modeling on the correlation relationship between the PAEs and the mPAEs by analyzing and revealing the relationship between the PAEs in the same hair sample and the specific components of the exposure markers. By the model, the detection quantity of the target compounds can be greatly reduced, and the data of another type of target compounds can be accurately calculated and obtained according to the detection data of one type of target compounds, so that complete data is provided for population exposure evaluation, the quantity of target detection objects is further simplified, the detection and analysis efficiency and accuracy are improved, a new way is provided, and the model has important significance for comprehensively evaluating the exposure characteristics and health risks of the three types of pollutants ubiquitous in the environment in the population.
9. According to the evaluation method and the detection method provided by the invention, the perfluorinated compounds, the phthalic acid esters and the exposure markers thereof in the hair sample are synchronously detected, and the correlation analysis model (difference and correlation) of the PAEs and the exposure markers thereof is established, so that the evaluation method and the detection method can be effectively applied to screening and detection of individuals, exposure evaluation and epidemiological investigation of large-scale crowds and the like, and have wide application prospects in aspects of health risk evaluation, public health and the like.
10. The evaluation method and the detection method provided by the invention further aim at the defects that PFASs, PAEs and mPAEs required by the current medical research and clinical diagnosis need to be detected by using a kit or preparing a sample separately, and the detection is completed in the same detection process of the same sample, so that the detection data of three target detection objects (multiple exposure markers) is obtained by using one sample, a mathematical model is constructed to analyze the relationship among the detection data of the three target detection objects, the relationship between the PAEs and mPAEs exposure is researched, and the relationship is further used for revealing the data such as the rising contribution value and the main influence factors of mPAEs, and the like, thereby providing support for the analysis and prediction of the health exposure risk of related groups and individual personnel, and the clinical diagnosis, treatment and epidemiological analysis and prevention of diseases. Therefore, the method has wide medical application prospect and expands the application range of the detection data and the health exposure risk assessment result.
Drawings
FIG. 1 is a schematic flow chart of a method and application for assessing exposure and simultaneously detecting hair sample according to an embodiment of the present invention;
FIG. 2 shows 200 ng mL of an example of the present invention -1 A total ion current chromatogram of target PFASs in the standard solution;
FIG. 3 shows 200 ng/mL of an example of the present invention -1 A total ion current chromatogram of target PAEs in the standard solution;
FIG. 4 shows 200 ng/mL of an example of the present invention -1 A total ion current chromatogram of the target mPAEs in the standard solution;
the present invention will be described in detail below with reference to the drawings and examples.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention are described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the respective embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The embodiment is as follows:
referring to the attached drawings 1-4, the method for evaluating the exposure risk of multiple pollutants in the hair of a large-scale crowd provided by the invention aims at the research of the occupational disease prevention and control project of multiple enterprise workers (including electronic garbage recycling stations and treatment plants) in the electronic garbage dismantling industry in the Huanan area, hundreds to thousands of samples need to be treated in a single batch, and comprises the following steps:
s1: determining the pollutants and the exposure markers with the correlation relationship as target detection objects: finding out various pollutant types in the hair of the population, including PFASs, PAEs and mPAEs, screening various exposure marker types with medical research value according to a large-scale population exposure evaluation model, and further screening at least one group of relative pollutant PAEs and exposure marker mPAEs with correlation therebetween as paired target detection objects;
s11: further screening pollutants with obvious correlation and exposure marker components thereof in PAEs and mPAEs to serve as specific paired target detection objects, wherein the paired target detection objects are respectively as follows: DEHP and MEHP, diBP and MiBP, DEP and MEP, DMP and MMP;
s2: establishing a correlation analysis model: establishing a correlation analysis model of pollutants PAEs in a paired target detection object and exposure markers mPAEs, wherein Y = aX + b formula 1, wherein X is PAEs concentration, Y is mPAEs concentration, a is a proportionality coefficient, and b is a correction coefficient;
s21: respectively establishing a specific correlation analysis model of the paired target detection objects, such as an analysis model of DEHP and MEHP;
s3: collecting and classifying samples: collecting a crowd hair sample in a large range, recording sample source information, processing the sample into a plurality of samples to be detected, taking information data of sex, age and exposure source contact condition of a sampling object as classification variables, and taking concentration data of PAEs and mPAEs in hair obtained through detection as variables;
s31: preparing a plurality of independent hair samples to be detected from the crowd hair samples collected in a large range;
s4: detecting sample acquisition data: respectively detecting target detection objects in collected samples to be detected of a large-range population, and acquiring concentration data of at least one of PAEs (polycyclic aromatic hydrocarbons) and mPAEs (Multi-molecular olefins);
s41: detecting sample acquisition data: respectively detecting target detection objects in samples of the collected large-range crowd, and acquiring concentration data of at least one component in the target detection objects;
s42: detecting a sample to obtain multiple sample data: according to the sampling time or space division of the samples, respectively detecting the target detection object in each sample of the collected large-range crowd for many times, and acquiring the concentration data of at least one component in each composition pair target detection object; after multiple detections, obtaining target detection object data of multiple samples;
s43: performing medical trend analysis: and comparing and analyzing the fitting result of the target detection object concentration data according to the step S41 to obtain the time or space dimension change trend of the exposed marker.
S5: and (3) carrying out large-range crowd health risk exposure assessment: and substituting one of the known PAEs and mPAEs concentration data into the formula 1, fitting the undetected compound concentration in the hair sample under the same classification variable group, complementing the concentration data, and further calculating and evaluating the exposure risk of a large-range population on the basis of the data of the exposure marker mPAEs.
S51: and (3) performing large-scale population health risk exposure assessment: substituting the known concentration data of one of the target detection objects into formula 1, fitting the concentration of undetected compound in hair sample under the same classification variable group, and compensating the concentration
The data, based on the data of exposure markers mPAEs, further calculate and assess the exposure risk of a large population.
S52: and (4) comparing and analyzing the concentration data of the target detection object in the single sample obtained in the steps S1-S4 to obtain the individual health exposure risk assessment and trend analysis results, or using the individual health exposure risk assessment and trend analysis results for clinical analysis.
S53: and (4) comparing and analyzing the concentration data of the target detection object in the plurality of samples of the crowd with large range and long period obtained in the steps S1-S4 to obtain the crowd health exposure risk assessment and trend analysis results with large range and long period or to be used for medical analysis.
A method for detecting multiple contaminants in hair of a wide range of people implementing the aforementioned exposure assessment method, comprising the steps of:
A. cleaning the sample to remove exogenous contaminants;
B. sample pretreatment: pretreating a sample, extracting supernate from a unit sample and an internal standard substance by adopting a solid-liquid extraction method, and concentrating the supernate to obtain a sample extracting solution to be detected;
C. sample detection: synchronously pretreating the extracting solution by adopting ultra performance liquid chromatography-tandem mass spectrometry to synchronously obtain the whole chromatograms and mass spectrograms of PFASs, PAEs and mPAEs of the sample;
D. obtaining quantitative detection data: according to the detection of an internal standard method, the component contents of PFASs, PAEs and mPAEs in the sample are respectively calculated, and at least one component content of the paired target detection objects is calculated; the content of each required specific component in PFASs, PAEs and mPAEs types is calibrated by adopting a standard curve without matrix matching.
The technical solution of the present invention is explained in detail by four specific examples below.
Specific example 1:
referring to fig. 1-4, embodiments of the present invention provide a method for assessing exposure risks of multiple pollutants in hair of a large population based on correlation of exposure markers, and a method for detecting the same, based on the foregoing embodiments, specifically to perform rapid, efficient, high-throughput, and low-cost synchronous detection and analysis of multiple organic pollutants in batch segmented hair samples of occupational exposure population, including three types of pollutants of PFASs, PAEs, and mPAEs, specifically including the following steps:
A. the method for cleaning the sample to remove the exogenous pollutants comprises the following steps:
a-1) weighing 0.1g of sample into a glass tube, and adding ultrapure water for ultrasonic cleaning for 10 min;
a-2) removing the ultrapure water in the A-1), adding a 0.1% sodium dodecyl sulfate solution, and carrying out ultrasonic cleaning for 10 min;
a-3) discarding the sodium dodecyl sulfate solution of 0.1 percent in the A-2), adding ultrapure water, and carrying out ultrasonic cleaning for 10 min;
a-4) discarding the ultrapure water in the A-3), adding the ultrapure water, and ultrasonically cleaning for 10 min;
a-5) discarding the ultrapure water in A-4), and drying for use.
B. Sample pretreatment: pretreating a sample, extracting supernate from a unit sample and an internal standard substance by adopting a solid-liquid extraction method, and concentrating the supernate to obtain a sample extracting solution to be detected; the method specifically comprises the following steps:
b-1) adding the unit hair sample into an internal standard substance, standing for 30 min, adding acetonitrile, and performing ultrasonic extraction for 10 min; for each 0.1g sample 2 ng of internal perfluorochemical standard was added, including MPFBA, M5PFPeA, M5PFHxA, M4PFHpA, M8PFOA, M9PFNA, M6PFDA, M7PFUdA, MPFDoA, M2PFTeDA, M3PFBS, M3PFHxS, M8PFOS. 30 ng phthalate internal standards DPrP-d4, DHxP-d4, DEHP-d4, DBP-d4, diBP-d4, DEP-d4, DBzP-d4 were added for each 0.1g sample.
B-2) extracting the extract liquid in B-1) for 3500 r.min -1 Centrifuging for 10 min, and collecting supernatant;
and B-3) carrying out nitrogen-blowing concentration on the supernatant collected in the B-2) to be tested.
C. Sample detection: synchronously preprocessing the extracting solution by adopting ultra-high performance liquid chromatography-tandem mass spectrometry to synchronously obtain the whole chromatograms and mass spectrograms of PFASs, PAEs and mPAEs of the sample; the method specifically comprises the following steps:
c-1) PFASs Instrument operating conditions were as follows:
a chromatographic column: the PFASs selected chromatographic column Infinitylab poroshel 120 EC-C18 (4.6 x 100 mm,2.7 Micron); acetonitrile-5 mmol. L -1 The ammonium acetate solution and the methanol-5 mmoL ammonium acetate solution can achieve better separation effect, and the acetonitrile-5 mmol.L can be found -1 The response of the ammonium acetate solution was higher. Therefore, acetonitrile-5 mmol/L ammonium acetate solution was used as the mobile phase in this example. 200 Chromatogram of PFASs in ng/mL standard solution, see FIG. 2.
Mobile phase: mobile phase A is acetonitrile, mobile phase B is 5 mmol.L -1 An ammonium acetate solution; the flow rate was 400. Mu.L.min -1 The column temperature is 25 ℃, and the sample injection amount is 5 mu L.
Gradient elution: 0.5-1.5 min,40% A;1.5-2 min,40-90% A;2-8 min,90% A;8-13 min,90-10% A;13-18 min,10% A, as shown in Table 1 below:
TABLE 1 PFASs liquid chromatography gradient elution procedure
TABLE 2 PFASs ion conditions used by internal standard method of mass spectrometer
C-2) PAEs and mPAEs the following instrument operating conditions:
the PAEs use a chromatographic Column of Kinet Biphenyl 100A Column (100 x 2.1 mm,2.6 Micron), and a methanol-0.1% formic acid solution and a methanol-0.1% acetic acid solution are selected to achieve a good separation effect, while a methanol-0.1% formic acid solution is used as a mobile phase, so that the target substance has a high response. Therefore, methanol-0.1% formic acid solution was used as the mobile phase in this example. 200 ng.mL -1 Chromatogram of PAEs in standard solution is shown in figure 3.
The chromatographic columns used for mPAEs were Kinete Biphenyl 100A Column (100 x 2.1 mm,2.6 Micron), and 0.1% acetic acid in methanol-water (95, 5V/V) and 0.1% acetic acid in methanol-water (1, 99, V/V) gave better separation and higher response. 200 Chromatogram of mPAEs in ng mL-1 standard solution is shown in figure 4.
Mobile phase: the mobile phase A of PAEs is methanol, the mobile phase B is 0.1% formic acid aqueous solution, and the flow rate is 350 muL.min -1 (ii) a mobile phase a of mPAEs was 0.1% acetic acid methanol-water (95, 5, V/V) and mobile phase B was 0.1% acetic acid methanol-water (1 -1 . The column temperature was 47 ℃ and the sample size was 5 μ L.
PAEs gradient elution: 0-0.5 min,10% A;0.5-5 min,10-95% A;5-13 min,95% A;13-13.5 min,95-10% A;13.5-18 min,10% A, as shown in Table 3 below:
TABLE 3 PAEs liquid chromatography gradient elution procedure
mPAEs gradient elution: 0-14.5 min, 5-100%; 14.5-17 min,100% A;17-17.1 min,100-5% A;17.1-21 min,5% A, as shown in Table 4 below:
table 4 mPAEs liquid chromatography gradient elution procedure
TABLE 5 ion conditions of PAEs and mPAEs by internal standard method of mass spectrometer
D. Obtaining a quantitative detection result: according to an internal standard method, calculating the contents of PFASs, PAEs and mPAEs in the sample; specifically, a standard curve without matrix matching is adopted to calibrate the contents of PFASs, PAEs and mPAEs.
The results of the blank normalized recovery of PFASs, PAEs and mPAEs are given in Table 6 below:
TABLE 6 detection results of blank standard addition recovery rates of PFASs, PAEs and mPAEs
Specific example 2:
the method for evaluating exposure risks and detecting exposure risks of multiple pollutants in hair of a large range of people based on correlation of exposure markers provided by the embodiment is based on the embodiment and the specific embodiment 1, and further provides a method for detecting PFASs, PAEs and mPAEs in hair, which is basically the same as the previous embodiments, and is different in that the embodiment detects a part of collected hair samples to observe effects of detection linear range, detection limit and recovery rate, and specifically comprises the following steps:
under optimized experimental conditions, the standard solvent is used for preparing 0.5, 1, 2, 5, 10, 20, 50, 100 and 200 ng.mL -1 A series of standard solutions of perfluorinated compounds. The mass concentration of the target substance (X, ng. ML) -1 ) The ratio (Y) of the peak area of the response to the peak area of the corresponding internal standard is plotted as the abscissa and the standard curve is plotted as the ordinate. The results showed that the concentration of the surfactant was 0.5 to 200 ng/mL -1 Good range linear dependence (r)>0.992). The standard solvent is used for preparing 2, 5, 10, 20, 50, 100, 200 and 500 ng/mL -1 Series of PAEs standard solutions. The mass concentration of the target substance (X, ng. ML) -1 ) Is shown as the abscissa of the graph,the ratio (Y) of the peak area of the response to the peak area of the corresponding internal standard is plotted as the ordinate of a standard curve. The results showed that the concentration of the organic solvent was 2 to 500 ng/mL -1 Good range linear dependence (r)> 0.991）。
In this example, PFASs were subjected to a standard recovery test using a portion of the hair sample at 10, 20 ng/mL levels -1 Each addition level was determined in duplicate 1 time, quantified by internal standard method. As a result, the concentration of the additive was 10 ng g -1 The accuracy of the sample is 70.66-145.5%, the recovery rate is 56.98-116.9%, and the RSD is<20 percent. The addition concentration is 20 ng g -1 The accuracy of the sample is 75.75-126.01%, the recovery rate is 86.38-122.94%, and the RSD is<20 percent. PAEs were subjected to a spiking recovery test at an add level of 20 ng-mL -1 Each addition level was determined in duplicate 1 time, quantified by internal standard method. The results show that the recovery rate is 65-275 percent, and most of the compounds RSD<20%。
The results of the recovery of PFASs at different loading levels are shown in Table 7 below.
TABLE 7 detection results of PFASs different loading standard recovery rates
TABLE 8 PFASs minimum detection and quantitation limits
The PAEs spiking recovery results are shown in table 9 below.
TABLE 9 PAEs and mPAEs recovery test results
TABLE 10 minimum detection and quantitation limits for PAEs and mPAEs
TABLE 11 concentration of PFASs, PAEs and mPAEs in Hair
Specific example 3
The method for assessing and detecting the exposure risk of multiple pollutants in hair of a large-scale population based on the correlation of the exposure marker is basically the same as that in the specific embodiments 1 and 2, and the difference is that the correlation between the PAEs and the exposure marker is fitted through large-scale population detection data, and the obtained correlation coefficient is applied to further simplify the detection process. On the basis of the steps 1) -3), the method also comprises a step 4): establishing a correlation analysis model of PAEs and exposure markers mPAEs thereof: and Y = aX + b, when the analysis conditions are limited and only PAEs or mPAEs can be detected, substituting partial measured target compound data into the correlation analysis model, and calculating the concentration of an undetected target compound to obtain complete data, thereby obtaining a more accurate health risk assessment result on the basis of further simplifying the population exposure detection process.
As a specific application of the synchronous detection method, the embodiment uses the detected concentration data of PAEs and mPAEs in the hair sample and the correlation thereof to construct a correlation analysis model, and specifically includes the following steps:
(1) Information collection and classification: collecting hair samples of more than 100 persons of a plurality of enterprises in the south China area, taking the recorded information of the sex, the age, the exposure source contact condition and the like of a sampling object as classification variables, taking the concentrations of PAEs and mPAEs in the detected hair as variables, correspondingly classifying and carrying out comprehensive analysis, and screening and determining that the significance level between target compounds in a certain classification variable group is higher;
(2) And (3) correlation analysis: performing correlation analysis on PAEs and mPAEs in the classified variable group with high significance level by adopting Graphpad analysis software to obtain a correlation p value among corresponding compounds of each group;
(3) And (5) judging a result: when p is less than 0.05, the method indicates that significant correlation exists between target compounds, namely, corresponding compounds may have the same exposure source or metabolic conversion relationship, and in this case, the conversion relationship between corresponding compounds can be established through a mathematical model; when p is greater than 0.05, no significant correlation exists, which indicates that the corresponding compound has a complex source and a conversion relation cannot be established through a mathematical model;
(4) Data screening and sorting: the compounds in this example that have significant correlation between PAEs and mPAEs are DEHP and MEHP, etc. (see table 12). Regression analysis was performed according to Graphpad software, and the analysis model of this example was obtained by fitting: y = a is 0.0841 for the proportionality coefficient a and 1.30161 for the correction coefficient b in aX + b;
(5) And (3) model verification: and substituting the values of the coefficients a and b into a correlation analysis model: y = aX + b, yielding Y = 0.0841X + 1.30161. In this example, according to the detection data in table 8, the concentration of DEHP in hair is 819.748, and MEHP = 70.243 can be calculated according to the model and is close to the measured value (75.732), which indicates that the model prediction effect is better;
(6) Population exposure assessment: for Y = 0.0841X + 1.30161 2 Analysis of = 0.42 shows that there is a strong correlation between DEHP and MEHP under this categorical variable grouping, i.e., the concentration of MEHP in hair samples with high concentrations of DEHP is also high, with a consequent increased risk of exposing people to both PAEs and mPAEs. When the experiment conditions of the detection personnel are limited and only PAEs or mPAEs can be detected, the correlation analysis model can be used for detecting a few key stormsAnd detecting the concentration of the exposed marker, fitting the concentration of the undetected compound in the hair sample under the same classification variable group according to the concentration data and the correlation relationship to obtain complete concentration data of the exposed marker, and applying the complete concentration data to exposure risk assessment, thereby providing data support for accurately mastering the human exposure of various target compounds, systematically assessing the change trend of the exposure risk of a large-scale crowd and the like.
TABLE 12 correlation of PAEs with their corresponding exposure markers
Note: -represents a value below the detection limit
Specific example 4
The method for evaluating and detecting the exposure risk of multiple pollutants in hair of a large-scale population based on the correlation of the exposure marker, provided by the embodiment, is based on embodiments 1, 2 and 3, and further reduces the number of components of a target detection object calculated by detection and analysis through a correlation analysis model of PAEs and the exposure marker mPAEs thereof established in the embodiment 3, and performs trend analysis according to known detection data, undetected data or missing data under the condition of limited supplementary analysis conditions, and specifically comprises the following steps:
(1) Data collection: collecting historical detection data of the target compound in the hair sample, as shown in table 10, detecting results of PAEs and corresponding exposure markers in the hair sample in 2014, 2018 and 2022 are limited by analysis conditions, the hair sample in 2014 only carries out detection of PAEs, detection of mPAEs is not carried out, and complete exposure evaluation and trend analysis cannot be carried out;
(2) Model fitting: substituting the data of DEHP in the hair sample in 2014 into the correlation analysis model Y = 0.0841X + 1.30161 established in example 3, and calculating to obtain MEHP = 2736.55;
(3) And (3) trend analysis: according to model fitting results, MEHP = 2736.55 in the 2014 hair samples, higher than the concentrations in 2018 and 2022, indicates that mPAEs concentrations decrease during 2014, 2018 and 2022 (see table 13 in particular), and health risks of PAEs and mPAEs exposure in the population also decrease.
Table 13 PAEs and their exposure marker concentrations in hair samples of 2014, 2018 and 2022
Note: indicates no detection
According to the embodiment of the invention, through the cooperative optimization of the evaluation and detection method, multiple target detection objects in the hair can be synchronously detected and analyzed, the types of the target detection objects are reduced, the detection steps are simplified, the detection cost is reduced, the application range of detection data and health exposure evaluation results is expanded, the manpower, instruments, consumables and time required by detection can be greatly reduced, and the large-scale and large-scale popularization and application are facilitated.
The invention can simultaneously carry out detection and analysis of PAEs and mPAEs through one hair sample, and the obtained concentration data, change trend data and the like can also be applied to clinical diagnosis and treatment of reasons and harm degrees of diseases such as liver, heart lung, genital organs and the like, thereby providing a basis for effective treatment. Meanwhile, effective support is provided for the prevention and treatment of occupational diseases of related enterprises and worker groups (cross-regional and long-term).
It should be noted that, in other embodiments of the present invention, different schemes obtained by specifically selecting steps, components, ratios, process parameters and conditions within the scope of the steps, components, ratios, process parameters and conditions described in the present invention can achieve the technical effects described in the present invention, and therefore, the present invention is not listed one by one.
The foregoing is merely a preferred embodiment of the invention and is not intended to limit the invention in any manner. Those skilled in the art can make numerous possible variations and modifications to the present invention, or modify equivalent embodiments, using the means and techniques disclosed above, without departing from the scope of the invention. All equivalent changes in the components, proportions and processes according to the present invention are intended to be covered by the scope of the present invention.
Claims (10)
1. A method for assessing exposure risks of multiple pollutants in hair of a large-scale crowd is characterized by comprising the following steps:
s1: determining the pollutants and the exposure markers with the correlation relationship as the target detection objects: finding out various pollutant species in the hair of the population, screening various exposure marker types with medical research value according to a large-scale population exposure evaluation model, and further screening at least one group of relative pollutants PAEs and exposure markers mPAEs thereof with relevant relationship to serve as paired target detection objects;
s2: establishing a correlation analysis model: establishing a correlation analysis model of pollutants PAEs in a paired target detection object and exposure markers mPAEs thereof, wherein Y = aX + b formula 1, X is PAEs concentration, Y is mPAEs concentration, a is a proportionality coefficient, and b is a correction coefficient;
s3: collecting and classifying samples: collecting a crowd hair sample in a large range, recording sample source information, processing the sample into a plurality of samples to be detected, taking information data of sex, age and exposure source contact condition of a sampling object as classification variables, and taking concentration data of PAEs and mPAEs in hair obtained through detection as variables;
s4: detecting sample acquisition data: respectively detecting target detection objects in collected samples to be detected of a large-range population, and acquiring concentration data of at least one of PAEs (polycyclic aromatic hydrocarbons) and mPAEs (Multi-molecular olefins);
s5: and (3) performing large-scale population health risk exposure assessment: substituting one of the known PAEs and mPAEs concentration data into formula 1, fitting the undetected compound concentration in the hair sample under the same categorical variable group, completing the concentration data, and further calculating and evaluating the exposure risk of a large-range crowd on the basis of the data of the exposure marker mPAEs.
2. The method of claim 1, comprising the steps of:
s11: further screening pollutants with obvious correlation and exposure marker components thereof in PAEs and mPAEs to serve as specific paired target detection objects, wherein the paired target detection objects are respectively as follows: DEHP and MEHP, diBP and MiBP, DEP and MEP, DMP and MMP;
s21: respectively establishing a specific correlation analysis model of paired target detection objects;
s31: preparing a plurality of independent hair samples to be detected from the crowd hair samples collected in a large range;
s41: detecting sample acquisition data: respectively detecting target detection objects in the collected samples of the large-range crowd, and acquiring concentration data of at least one component in the target detection objects;
s51: and (3) performing large-scale population health risk exposure assessment: and substituting the known concentration data of one of the target detection objects into the formula 1, fitting the concentration data of the undetected compounds in the hair samples under the same classification variable group, complementing the concentration data, and further calculating and evaluating the exposure risk of a large-range population on the basis of the data of the exposure marker mPAEs.
3. The method of claim 1, comprising the steps of:
s42: detecting a sample to obtain multiple sample data: according to sampling time or space division of samples, detecting target detection objects in the samples of the collected large-range crowd for multiple times and respectively, and acquiring concentration data of at least one component in the target detection objects of all the components; after multiple detections, obtaining target detection object data of multiple samples;
s43: performing medical trend analysis: and according to the fitting result of the target detection object concentration data in the step S42, comparing and analyzing to obtain the change trend of the time or space dimension of the exposed marker.
4. The method according to claim 1, wherein the step S5 comprises the steps of:
s52: and (4) comparing and analyzing the concentration data of the target detection object in the single sample obtained in the steps S1-S4 to obtain the individual health exposure risk assessment and trend analysis results, or using the individual health exposure risk assessment and trend analysis results for clinical analysis.
5. The method of claim 4, wherein the step S5 comprises the steps of:
s53: and (4) comparing and analyzing the concentration data of the target detection object in the plurality of samples of the crowd with large range and long period obtained in the steps S1-S4 to obtain the crowd health exposure risk assessment and trend analysis results with large range and long period or to be used for medical analysis.
6. A method for detecting multiple contaminants in hair of a broad population for carrying out the exposure assessment method of any one of claims 1-5, comprising the steps of:
A. cleaning the sample to remove exogenous contaminants;
B. sample pretreatment: pretreating a sample, extracting supernate from a unit sample and an internal standard substance by adopting a solid-liquid extraction method, and concentrating the supernate to obtain a sample extracting solution to be detected;
C. sample detection: synchronously preprocessing the extracting solution by adopting ultra-high performance liquid chromatography-tandem mass spectrometry to synchronously obtain the whole chromatograms and mass spectrograms of PFASs, PAEs and mPAEs of the sample;
D. obtaining quantitative detection data: and (3) detecting according to an internal standard method, respectively calculating the component contents of PFASs, PAEs and mPAEs in the sample, and at least calculating the component content of one of the paired target detection objects.
7. The detection method according to claim 6, wherein the step A of washing the sample specifically comprises the steps of:
a-1) weighing 0.1g of sample into a glass tube, and adding ultrapure water for ultrasonic cleaning for 10 min;
a-2) discarding ultrapure water in the A-1), adding 0.1% sodium dodecyl sulfate solution, and ultrasonically cleaning for 10 min;
a-3) discarding the sodium dodecyl sulfate solution of 0.1 percent in the A-2), adding ultrapure water, and carrying out ultrasonic cleaning for 10 min;
a-4) removing the ultrapure water in the A-3), adding the ultrapure water, and ultrasonically cleaning for 10 min;
a-5) discarding the ultrapure water in A-4), and drying for use.
8. The detection method according to claim 6, wherein the sample pretreatment of the step B specifically comprises the following steps:
b-1) adding the unit hair sample into an internal standard substance, standing for 30 min, adding acetonitrile, and performing ultrasonic extraction for 10 min; adding 2 ng of a perfluorinated internal standard substance for every 0.1g of sample, wherein the internal standard substance comprises MPFBA, M5PFPeA, M5PFHxA, M4PFHpA, M8PFOA, M9PFNA, M6PFDA, M7PFUdA, MPFDoA, M2PFTeDA, M3PFBS, M3PFHxS and M8PFOS; 30 ng of phthalate internal standard substances DPrP-d4, DHxP-d4, DEHP-d4, DBP-d4, diBP-d4, DEP-d4 and DBzP-d4 are added to each 0.1g of sample;
b-2) extracting the extract liquid in B-1) for 3500 r.min -1 Centrifuging for 10 min, and collecting supernatant;
and B-3) carrying out nitrogen-blowing concentration on the supernatant collected in the B-2) to be tested.
9. The detection method according to claim 6, wherein the step C of detecting the sample specifically comprises the following steps:
c-1) PFASs apparatus operating conditions were as follows:
a chromatographic column: PFASs select chromatographic column Infinitylab Poroshell 120 EC-C18; using acetonitrile and ammonium acetate solution as mobile phase to obtain a chromatogram of PFASs in the standard solution of 200 ng/mL;
mobile phase: mobile phase A is 5 mmol/L acetonitrile, and mobile phase B is5 mmol·L -1 Ammonium acetate solution of (a); the flow rate was 400. Mu.L.min -1 The column temperature is 25 ℃, and the sample injection amount is 5 mu L;
gradient elution: 0.5-1.5 min, 40%; 1.5-2 min,40-90% by weight A;2-8 min,90% A;8-13 min,90-10% A;13-18 min,10% A;
c-2) PAEs and mPAEs the following instrument operating conditions:
PAEs uses a Kinete Biphenyl 100A Column as a chromatographic Column, and uses 0.1% formic acid solution as a mobile phase; obtaining 200 ng.mL -1 Chromatogram of PAEs in standard solution;
the mPAEs use a Kinete Biphenyl 100A Column as a chromatographic Column, and a 0.1% acetic acid and methanol aqueous solution are used to obtain 200 ng/mL -1 Chromatogram of mPAEs in standard solution;
mobile phase: the mobile phase A of PAEs is methanol, the mobile phase B is 0.1% formic acid aqueous solution, and the flow rate is 350 muL.min -1 (ii) a mobile phase a of mPAEs was 0.1% aqueous acetic acid and methanol, mobile phase B was 0.1% aqueous acetic acid and methanol at 300 μ l.min -1 (ii) a The column temperature is 47 ℃, and the sample injection amount is 5 mu L;
PAEs gradient elution: 0-0.5 min,10% A;0.5-5 min,10-95% A;5-13 min,95% A;13-13.5 min,95-10% A;13.5-18 min,10% A;
mPAEs gradient elution: 0-14.5 min, 5-100%; 14.5-17 min,100% A;17-17.1 min, 100-5%; 17.1-21 min,5% A.
10. The detection method according to claim 6, wherein the step C of detecting the sample specifically comprises the following steps:
and D, calibrating the content of each required specific component in PFASs, PAEs and mPAEs types by adopting a standard curve without matrix matching.
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| CN116165121A (en) * | 2023-04-25 | 2023-05-26 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Method for detecting penetration of organic pollutants in cross section of human hair |
| CN116183802A (en) * | 2023-04-25 | 2023-05-30 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Rapid detection method and application of multiple semi-volatile organic compounds in atmospheric particulate matter PM2.5 |
| CN116165121B (en) * | 2023-04-25 | 2023-07-07 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Method for detecting penetration of organic pollutants in cross section of human hair |
| CN116183802B (en) * | 2023-04-25 | 2023-10-13 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Rapid detection method and application of multiple semi-volatile organic compounds in atmospheric particulate matter PM2.5 |
| CN117388412A (en) * | 2023-12-13 | 2024-01-12 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Crowd TBBPA exposure biological monitoring method based on hair detection and application |
| CN117388412B (en) * | 2023-12-13 | 2024-02-13 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Crowd TBBPA exposure biological monitoring method based on hair detection and application |
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