Spatial distribution and partitioning behavior of selected poly- and perfluoroalkyl substances in freshwater ecosystems: a French nationwide survey.
Spatial distribution and partitioning behavior of selected poly- and perfluoroalkyl substances in freshwater ecosystems: a French nationwide survey.
复制标题
DOI：
10.1016/j.scitotenv.2015.02.043
复制
发表时间：
2015-06
期刊：
影响因子：
--
通讯作者：
G. Munoz;J. Giraudel;Fabrizio Botta;F. Lestremau;M. Devier;H. Budzinski;P. Labadie
中科院分区：
文献类型：
--
作者：
G. Munoz;J. Giraudel;Fabrizio Botta;F. Lestremau;M. Devier;H. Budzinski;P. Labadie
在全国范围内对法国大陆133条河流和湖泊中22种多氟烷基物质(PFAS)的空间分布和分配进行了调查。溶解相的Σ全氟辛烷磺酸含量在-725 ng/L−-1之间(中位数：7.9g/L−)和沉积物中的全氟辛烷磺酸-25 mg/−/1干重(中位数：0.48g/−/1dw)；溶解的全氟辛烷磺酸水平显著低于城市、农村或工业现场。尽管全氟辛烷磺酸(全氟辛烷磺酸)被发现平均是最普遍的化合物，但基于神经网络的多变量分析显示，其他化合物在特定地点，在某些情况下，在分水岭尺度上有值得注意的趋势。例如，罗纳河沿岸的几个地点显示出特殊的全氟烷基羧酸盐(Σ)特征，全氟烷基羧酸盐(PFCA)往往是全氟烷基羧酸盐(PFCA)的主要成分(例如，沉积物中的全氟烷基羧酸盐和99%的PFAS可能是工业点源排放的结果)。对低于检测限(非检测)的数据进行了几种处理，以计算描述性统计、组间差异和同类之间的相关性以及logKd和logKoc分配系数；在这方面，用于描述性统计计算的首选顺序统计回归(Robust ROS)方法，而用于回归和相关性分析的Akritas-Theil-Sen估计量。多元回归结果表明，溶解相中的PFAS水平和沉积物特性(有机碳含量和粒度)可能是沉积物中PFAS水平的重要控制因素。
The spatial distribution and partitioning of 22 poly- and perfluoroalkyl substances (PFASs) in 133 selected rivers and lakes were investigated at a nationwide scale in mainland France. ΣPFASs was in the range < LOD–725 ng L− 1in the dissolved phase (median: 7.9 ng L− 1) and < LOD–25 ng g− 1dry weight (dw) in the sediment (median: 0.48 ng g− 1dw); dissolved PFAS levels were significantly lower at “reference” sites than at urban, rural or industrial sites. Although perfluorooctane sulfonate (PFOS) was found to be the prevalent compound on average, a multivariate analysis based on neural networks revealed noteworthy trends for other compounds at specific locations and, in some cases, at watershed scale. For instance, several sites along the Rhône River displayed a peculiar PFAS signature, perfluoroalkyl carboxylates (PFCAs) often dominating the PFAS profile (e.g., PFCAs > 99% of ΣPFASs in the sediment, likely as a consequence of industrial point source discharge). Several treatments for data below detection limits (non-detects) were used to compute descriptive statistics, differences among groups, and correlations between congeners, as well as logKdand logKocpartition coefficients; in that respect, the Regression on Order Statistics (robust ROS) method was preferred for descriptive statistics computation while the Akritas–Theil–Sen estimator was used for regression and correlation analyses. Multiple regression results suggest that PFAS levels in the dissolved phase and sediment characteristics (organic carbon fraction and grain size) may be significant controlling factors of PFAS levels in the sediment.