scholarly journals Occurrence of perfluoroalkyl and polyfluoroalkyl substances in the water environment and their removal in a water treatment process

2014 ◽  
Vol 5 (2) ◽  
pp. 196-210 ◽  
Author(s):  
Biplob Kumar Pramanik

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) such as perfluorooctanoic acid (PFOA), and perfluorooctane sulfonate (PFOS) are found in aquatic environments worldwide. The presence of these compounds in the water environment is still unclear, even though direct or indirect discharges of these compounds from industries to the aquatic environment are the potential routes. In this paper, PFOA and PFOS contamination of aquatic ecosystems, and their removal efficiency by different water treatment processes are reviewed. Typically, PFOS and PFOA contamination levels are higher in industrialized countries than in non-industrial countries. Coagulation, sand filtration, sedimentation, oxidation and disinfection are mostly ineffective in removing PFASs from drinking and wastewater. Granular activated carbon demonstrated the removal of PFASs and the extent of removal depends on operational conditions, such as temperature, operational life period and empty bed contact time. High-pressure membrane systems are the most suitable processes for removing the PFOS and PFOA in water sources. In the high-pressure membrane, removal of those chemicals occurs through rejection via electrostatic interaction. The extent of the reduction efficiency depends on the solution chemistry of the sample; lower pH and higher calcium ion addition in the water sample enhance the reduction efficiency in the high-pressure membrane application.

2020 ◽  
Author(s):  
Azhagiya Singam Ettayapuram Ramaprasad ◽  
Phum Tachachartvanich ◽  
Denis Fourches ◽  
Anatoly Soshilov ◽  
Jennifer C.Y. Hsieh ◽  
...  

Perfluoroalkyl and Polyfluoroalkyl Substances (PFASs) pose a substantial threat as endocrine disruptors, and thus early identification of those that may interact with steroid hormone receptors, such as the androgen receptor (AR), is critical. In this study we screened 5,206 PFASs from the CompTox database against the different binding sites on the AR using both molecular docking and machine learning techniques. We developed support vector machine models trained on Tox21 data to classify the active and inactive PFASs for AR using different chemical fingerprints as features. The maximum accuracy was 95.01% and Matthew’s correlation coefficient (MCC) was 0.76 respectively, based on MACCS fingerprints (MACCSFP). The combination of docking-based screening and machine learning models identified 29 PFASs that have strong potential for activity against the AR and should be considered priority chemicals for biological toxicity testing.


2016 ◽  
Vol 15 (8) ◽  
pp. 1867-1872
Author(s):  
Florina Fabian ◽  
Silvia Fiore ◽  
Giuseppe Genon ◽  
Deborah Panepinto ◽  
Valentin Nedeff ◽  
...  

2021 ◽  
Vol 188 ◽  
pp. 116546
Author(s):  
Charlie J. Liu ◽  
Timothy J. Strathmann ◽  
Christopher Bellona

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