{"title":"三种全氟烷烃酸的非生物和生物群样品的多变量分析","authors":"H. Fiedler, Abeer Baabish, Mohammad Sadia","doi":"10.3389/frans.2022.954915","DOIUrl":null,"url":null,"abstract":"Perfluoroalkane substances (PFAS) comprise a large family of chemicals of environmental concern and are subject to chemical analyses, international regulation, and risk assessments. Environmental samples including air, water, sediment, and soil as abiotic matrices, food samples comprising fish, meat (beef, sheep, chicken), egg, butter, and milk as well as human milk samples were assessed using uni- and multivariate methods. Participating countries were asked to provide baseline samples and not target potential hotspots. Chemometric analysis was possible for only three of the 15 PFAS monitored, namely perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHxS). The assessments showed that PFAS contamination in developing countries and in all matrices considered was almost equally attributed to PFOS and PFOA; PFHxS did not play a role. Subsequently, across all samples, PFOS and PFOA were strongly negatively correlated (spearman correlation coefficient r = −0.94). The measured values showed moderate positive correlation between PFOS and PFOA (r = 0.76) indicating common sources or environmental behavior. No clear pattern could be observed for geographic locations nor for transfers between matrices. Whereas the abiotic samples—soil, sediment, air—gave a very heterogenous picture (very small p-values) and had wide ranges and outliers, the measured values of the biota samples were not significantly different between matrices.","PeriodicalId":73063,"journal":{"name":"Frontiers in analytical science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multivariate analysis of abiotic and biota samples for three perfluoroalkane acids\",\"authors\":\"H. Fiedler, Abeer Baabish, Mohammad Sadia\",\"doi\":\"10.3389/frans.2022.954915\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Perfluoroalkane substances (PFAS) comprise a large family of chemicals of environmental concern and are subject to chemical analyses, international regulation, and risk assessments. Environmental samples including air, water, sediment, and soil as abiotic matrices, food samples comprising fish, meat (beef, sheep, chicken), egg, butter, and milk as well as human milk samples were assessed using uni- and multivariate methods. Participating countries were asked to provide baseline samples and not target potential hotspots. Chemometric analysis was possible for only three of the 15 PFAS monitored, namely perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHxS). The assessments showed that PFAS contamination in developing countries and in all matrices considered was almost equally attributed to PFOS and PFOA; PFHxS did not play a role. Subsequently, across all samples, PFOS and PFOA were strongly negatively correlated (spearman correlation coefficient r = −0.94). The measured values showed moderate positive correlation between PFOS and PFOA (r = 0.76) indicating common sources or environmental behavior. No clear pattern could be observed for geographic locations nor for transfers between matrices. Whereas the abiotic samples—soil, sediment, air—gave a very heterogenous picture (very small p-values) and had wide ranges and outliers, the measured values of the biota samples were not significantly different between matrices.\",\"PeriodicalId\":73063,\"journal\":{\"name\":\"Frontiers in analytical science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in analytical science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3389/frans.2022.954915\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in analytical science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frans.2022.954915","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multivariate analysis of abiotic and biota samples for three perfluoroalkane acids
Perfluoroalkane substances (PFAS) comprise a large family of chemicals of environmental concern and are subject to chemical analyses, international regulation, and risk assessments. Environmental samples including air, water, sediment, and soil as abiotic matrices, food samples comprising fish, meat (beef, sheep, chicken), egg, butter, and milk as well as human milk samples were assessed using uni- and multivariate methods. Participating countries were asked to provide baseline samples and not target potential hotspots. Chemometric analysis was possible for only three of the 15 PFAS monitored, namely perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHxS). The assessments showed that PFAS contamination in developing countries and in all matrices considered was almost equally attributed to PFOS and PFOA; PFHxS did not play a role. Subsequently, across all samples, PFOS and PFOA were strongly negatively correlated (spearman correlation coefficient r = −0.94). The measured values showed moderate positive correlation between PFOS and PFOA (r = 0.76) indicating common sources or environmental behavior. No clear pattern could be observed for geographic locations nor for transfers between matrices. Whereas the abiotic samples—soil, sediment, air—gave a very heterogenous picture (very small p-values) and had wide ranges and outliers, the measured values of the biota samples were not significantly different between matrices.