4.7 Article

Predicting the impact of salt mixtures on the air-water interfacial behavior of PFAS

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 819, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2021.151987

关键词

PFAS; Salt concentration; Salt valency; Interfacial partitioning; Adsorption; Environmental fate

资金

  1. UNSW

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This study develops a mass-action model to predict the interfacial behavior of PFAS in the presence of different salts. The results highlight the significant impact of multivalent salts on interfacial adsorption and the potential underestimation of PFAS interfacial adsorption when considering only monovalent salts.
Salts are known to have strong impacts on environmental behavior of per- and polyfluoroalkyl substances (PFAS) including air-water interfacial adsorption. Multivalent salts impact interfacial adsorption to a greater extent than monovalent salts. Models to make a priori predictions of PFAS interfacial adsorption in the presence of multiple salts with different ionic charges are needed given the need to predict PFAS environmental fate. This study fur-ther develops a mass-action model to predict the interfacial behavior of PFAS as a function of both salt valency and concentration. The model is validated using surface tension data for a series of monovalent and divalent salt mixtures over a wide range of ionic strengths (i.e., from no added salt to 0.5 M) as well as comparison to data from literature. This model highlights the disproportionate impact of multivalent salts on interfacial adsorption and the practical utility of the model for predicting interfacial adsorption in the presence of multiple monovalent and multivalent inorganic salts. Results suggest that failure to account for divalent salt, even when concentra-tions are much smaller than monovalent salt, under most environmentally relevant aqueous phase conditions will result in significant underpredictions of PFAS interfacial adsorption. Simple examples of PFAS distribution in a range of salt conditions in the vadose zone and in aerated-water treatment reactors highlight the predictive utility of the model.

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