scholarly journals Foam fractionation removal of multiple per‐ and polyfluoroalkyl substances from landfill leachate

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Philip McCleaf ◽  
Ylva Kjellgren ◽  
Lutz Ahrens
Keyword(s):  
Landfill Leachate ◽  
Foam Fractionation ◽  
Polyfluoroalkyl Substances

Per- and Polyfluoroalkyl Substances in Landfill Leachate: Patterns, Time Trends, and Sources

2012 ◽  
Vol 46 (21) ◽  
pp. 11532-11540 ◽  
Author(s):  
Jonathan P. Benskin ◽  
Belinda Li ◽  
Michael G. Ikonomou ◽  
John R. Grace ◽  
Loretta Y. Li
Keyword(s):  
Landfill Leachate ◽  
Time Trends ◽  
Polyfluoroalkyl Substances

Concentrating Per- and Polyfluoroalkyl Substances (PFAS) in Municipal Solid Waste Landfill Leachate Using Foam Separation

2020 ◽  
Vol 54 (19) ◽  
pp. 12550-12559 ◽  
Author(s):  
Nicole M. Robey ◽  
Bianca F. da Silva ◽  
Michael D. Annable ◽  
Timothy G. Townsend ◽  
John A. Bowden
Keyword(s):  
Municipal Solid Waste ◽  
Solid Waste ◽  
Landfill Leachate ◽  
Municipal Solid Waste Landfill ◽  
Waste Landfill ◽  
Foam Separation ◽  
Polyfluoroalkyl Substances

Treatment of per- and polyfluoroalkyl substances in landfill leachate: status, chemistry and prospects

2019 ◽  
Vol 5 (11) ◽  
pp. 1814-1835 ◽  
Author(s):  
Zongsu Wei ◽  
Tianyuan Xu ◽  
Dongye Zhao
Keyword(s):  
Landfill Leachate ◽  
Knowledge Gaps ◽  
Treatment Technologies ◽  
Polyfluoroalkyl Substances

This work critically reviews the occurrence, chemistry, treatment technologies and knowledge gaps for per- and polyfluoroalkyl substances in landfill leachate.

Structure-Based Virtual Screening of Perfluoroalkyl and Polyfluoroalkyl Substances (PFASs) as Endocrine Disruptors of Androgen Receptor Activity Using Molecular Docking and Machine Learning

2020 ◽  
Author(s):  
Azhagiya Singam Ettayapuram Ramaprasad ◽  
Phum Tachachartvanich ◽  
Denis Fourches ◽  
Anatoly Soshilov ◽  
Jennifer C.Y. Hsieh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Molecular Docking ◽  
Androgen Receptor ◽  
Endocrine Disruptors ◽  
Hormone Receptors ◽  
Steroid Hormone Receptors ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Polyfluoroalkyl Substances ◽  
Perfluoroalkyl And Polyfluoroalkyl Substances

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.

Chitosan ultilization in biocomposite adsorbent in Iron (Fe) removal from landfill leachate

2018 ◽  
Vol 10 (9) ◽  
Author(s):  
Zawawi Daud ◽  
◽  
Halizah Awang ◽  
Farah Nur Diyana Ibrahim ◽  
Nur Adila Ab Aziz ◽  
...  
Keyword(s):  
Landfill Leachate
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