Occurrence and toxicity of perfluoroalkyl acids along the estuarine and coastal regions under varied environmental factors
By Ricardo David Avellán-Llaguno, Xiaobo Liu, Sijun Dong, and Qiansheng Huang
Sci Total Environ
January 26, 2021
DOI: 10.1016/j.scitotenv.2020.144584
Due to the significant economic and ecological value, the increasing pollution threat to estuarine and coastal regions is of great concern. Perfluoroalkyl acids (PFAAs) are emerging pollutants which possess adverse ecological risk. In this review, we have compiled the data on the levels of PFAAs in environmental samples, mainly in estuarine and coastal zones. A worldwide map was generated to show the distribution of PFAAs. The experimental results have also been considered, which, together with those of environmental samples, has allowed us to infer about the factors that intervene in the behavior of PFAAs. The presence of PFAAs is determined primarily by the source of pollution. Salinity is as well shown as a significant condition, dependent too on the sampling environment. The analysis of PFAAs from environmental samples constitutes a fundamental tool for the surveillance of these pollutants, but the lack of homogeneity of protocols for sampling, as well as for the results presentation, limits the comparative capacity. Laboratory studies are also an essential tool in the analysis of particular aspects related to PFAAs, but many times the conditions tested are not environmentally significant. In this way, it would not be prudent to establish "paradigms" about the behavior of the PFAAs in certain areas or organisms, instead to suggest the points that can be considered fundamental for each issue addressed. The main variables that appear to intervene in estuarine and coastal regions are mainly the proximity to the source of pollution, salinity, pH, precipitation (rain) as well as types of PFAAs. All these can synergistically lead to different impacts on the ecosystem. Therefore, the particular risks of PFAAs in estuarine and coastal regions is a set of multiple variables, dependent on each sampling condition and according to the previously named parameters.
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