水生植物
生物累积
生物浓缩
中观
环境化学
水生植物
化学
氢化物
吸附
金鱼藻
凤眼莲
植物修复
植物
生态学
生物
吸附
营养物
重金属
有机化学
作者
Na Pi,J.Z. Ng,Barry C. Kelly
出处
期刊:Water Research
[Elsevier BV]
日期:2017-06-01
卷期号:117: 167-174
被引量:62
标识
DOI:10.1016/j.watres.2017.04.003
摘要
Studies investigating the bioaccumulation behavior of perfluoroalkyl substances (PFASs) in aquatic macrophytes are limited. The present study involved controlled mesocosm experiments to assess uptake and elimination rate constants (ku,ke), bioconcentration factors (BCFs) and translocation factors (TFs) of several perfluoroalkyl carboxylic acids (PFCAs) and perfluoroalkane sulfonic acids (PFSAs) in two aquatic plant species, including one submerged species (Echinodorus horemanii) and one free-floating species (Eichhornia crassipes). The results indicated all PFASs were readily accumulated in these aquatic macrophytes. ku and BCFs increased with increasing perfluoroalkyl chain length. For PFCAs and PFSAs with identical perfluoroalkyl chain length, the corresponding PFSA exhibited higher bioaccumulation potential. On a whole-plant basis, the bioaccumulation potential of PFASs in submerged and free-floating macrophytes were comparable, indicating sorption to plant biomass is similar in the different species. Conversely, when considering accumulation in foliage, BCFs in the free-floating macrophyte were substantially lower compared to submerged species, especially for longer-chain PFASs. Compounds with shorter perfluoroalkyl chain length (PFBS, PFPeA and PFHxA) exhibited preferential translocation to leaf tissue (TFs >1). BCFs exhibited a sigmoidal relationship with pefluoroalkyl chain length, membrane-water distribution coefficients (Dmw), protein-water distribution coefficients (Dpw) and organic-water partition coefficients (Koc). For these trends, maximum BCF values were exhibited by long-chain PFCAs, with a log Dmw, log Dpw and log Koc of 6.47, 5.72 and 5.04, respectively. These findings are useful for future design and implementation of phytoremediation systems, as well for future develop of mechanistic models for predicting the environmental fate and distribution of these contaminants of concern.
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