Deciphering Heavy Metals Adsorption on Soil by Physicochemical Property Diversity Using Machine Learning Method DOI

Jianle Wang,

Xueming Liu,

Yuliang Tu

и другие.

Опубликована: Янв. 1, 2023

The soil physicochemical properties play a key role in heavy metals (HMs) geochemical processes environment. However, how the of affect metal binding ability remains unclear, which limits our for predicting environmental behavior HMs. In this study, 22 types samples collected from different regions China, and we developed 12 machine learning (ML) models to predict adsorption HMs by soils, utilising 2112 experimental data points these samples, investigated master control factors on capacity (Cr, Pb, Cd, As) using best ML model. Based feature analysis, reactive oxides organic matter contents crucial determining oxyanion (Cr soil. Meanwhile, pH, particle size can account majority differences cation (Pb Cd) It is noteworthy that bulk density exchangeable potassium content played relative HMs, has been studied less extensively. This study provides fresh perspectives impact HM adsorption.

Язык: Английский

New PFASs Identified in AFFF Impacted Groundwater by Passive Sampling and Nontarget Analysis DOI
Sara Ghorbani Gorji, María José Gómez, Pradeep Dewapriya

и другие.

Environmental Science & Technology, Год журнала: 2024, Номер 58(3), С. 1690 - 1699

Опубликована: Янв. 8, 2024

Monitoring contamination from per- and polyfluoroalkyl substances (PFASs) in water systems impacted by aqueous film-forming foams (AFFFs) typically addresses a few known PFAS groups. Given the diversity of PFASs present AFFFs, current analytical approaches do not comprehensively address range these systems. A suspect-screening nontarget analysis (NTA) approach was developed applied to identify novel groundwater samples contaminated historic AFFF use. total 88 were identified both passive samplers grab samples, dominated sulfonate derivatives sulfonamide-derived precursors. Several ultrashort-chain (USC) (≤C3) detected, 11 reported for first time Australian groundwater. transformation products identified, including perfluoroalkane sulfonamides (FASAs) sulfinates (PFASis). Two new (((perfluorohexyl)sulfonyl)sulfamic acid; m/z 477.9068 (E)-1,1,2,2,3,3,4,5,6,7,8,8,8-tridecafluorooct-6-ene-1-sulfonic 424.9482). This study highlights that several are overlooked using standard target analysis, therefore, potential risk all is likely be underestimated.

Язык: Английский

Процитировано

15

Characterizing the Areal Extent of PFAS Contamination in Fish Species Downgradient of AFFF Source Zones DOI Creative Commons
Heidi M. Pickard, Bridger J. Ruyle,

Faiz Haque

и другие.

Environmental Science & Technology, Год журнала: 2024, Номер 58(43), С. 19440 - 19453

Опубликована: Окт. 16, 2024

Most monitoring programs next to large per- and polyfluoroalkyl substances (PFAS) sources focus on drinking water contamination near source zones. However, less is understood about how these affect downgradient hydrological systems food webs. Here, we report paired PFAS measurements in water, sediment, aquatic biota along a gradient away from zones contaminated by the use of legacy aqueous film-forming foam (AFFF) manufactured using electrochemical fluorination. Clustering analysis indicates that composition characteristic AFFF detectable fishes >8 km source. Concentrations 38 targeted extractable organofluorine (EOF) decreased AFFF-contaminated concentrations remained above consumption limits at all locations within affected watershed. Perfluoroalkyl sulfonamide precursors accounted for approximately half fish tissues, which explain >90% EOF across sampling locations. Suspect screening analyses revealed presence polyfluoroketone pharmaceutical species, fluorinated agrochemical likely does not accumulate biological suggesting diffuse such as septic system inputs throughout watershed addition contamination. Based results, consider hydrologically connected regions watersheds would help ensure public health protection.

Язык: Английский

Процитировано

8

Transforming PFAS management: A critical review of machine learning applications for enhanced monitoring and treatment DOI
Md Hasan-Ur Rahman,

Rabbi Sikder,

Tanvir Ahamed Tonmoy

и другие.

Journal of Water Process Engineering, Год журнала: 2025, Номер 70, С. 106941 - 106941

Опубликована: Янв. 15, 2025

Язык: Английский

Процитировано

1

Deciphering heavy metal adsorption capacity of soil based on its physicochemical properties and adsorption reaction time using machine learning DOI

Jianle Wang,

Xueming Liu, Weijie Li

и другие.

Journal of environmental chemical engineering, Год журнала: 2025, Номер unknown, С. 116913 - 116913

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

1

Interactions between biofilms and PFASs in aquatic ecosystems: Literature exploration DOI
Bin Ji, Yaqian Zhao

The Science of The Total Environment, Год журнала: 2023, Номер 906, С. 167469 - 167469

Опубликована: Сен. 29, 2023

Язык: Английский

Процитировано

12

Deciphering Heavy Metal Adsorption Capacity of Soil Based on its Physicochemical Properties and Adsorption Reaction Time Using Machine Learning DOI

Jianle Wang,

Xueming Liu, Weijie Li

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

A Critical Review of Sensors for Detecting Per- and Polyfluoroalkyl Substances: Focusing on Diverse Molecular Probes DOI

Jiancheng Zha,

Muyuan Ma,

Yue Shen

и другие.

Environmental Research, Год журнала: 2025, Номер unknown, С. 121669 - 121669

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Multi-class machine learning classification of PFAS in environmental water samples: a blinded test of performance on unknowns DOI Creative Commons
Tohren C. G. Kibbey, D. M. O’Carroll, Andrew Safulko

и другие.

Environmental Science Advances, Год журнала: 2024, Номер 3(3), С. 366 - 382

Опубликована: Янв. 1, 2024

A multi-class method was developed to identify PFAS origin based on chemical composition, and performance of the evaluated in a blinded test against unknowns. The showed great promise its ability recognize sample origin.

Язык: Английский

Процитировано

2

A comprehensive review on the distribution of per- and poly-fluoroalkyl substances in the environment across Sub-Saharan Africa revealed significant variation in their concentrations DOI Creative Commons
Hildegard R. Kasambala, Mwemezi J. Rwiza, Nelson Mpumi

и другие.

Environmental Challenges, Год журнала: 2024, Номер 16, С. 100975 - 100975

Опубликована: Июль 6, 2024

Per- and polyfluoroalkyl substances (PFAS) are a group of synthetic chemicals known for their widespread use in various industrial consumer products. They enter the food chain via contaminated water, air, soil, resulting bioaccumulation plants, fishes, foods, human milk, blood serum. Here, we critically reviewed literature published from 2005 to 2021 on occurrence distribution Perfluorooctanoic acid (PFOA) perfluoro-octane sulfonate (PFOS) as most occurring PFAS aquatic environment sub-Saharan Africa (SSA). To our knowledge, this is first paper review status SSA environment. This found that almost all matrices studied regions have been polluted by with varying concentrations. information suggests levels deserve immediate attention. Furthermore, faces unique challenges understanding managing contamination due scarcity data specific need more administrative guidelines monitoring water. provides vital baseline occurrences, contributing factors better protect public health, develop sustainable solutions growing concern.

Язык: Английский

Процитировано

2

First insights into per-and polyfluoroalkyl substance contamination in edible fish species of the Indus water system of Pakistan DOI
Rahat Riaz, Muhammad Yasir Abdur Rehman, Muhammad Junaid

и другие.

Chemosphere, Год журнала: 2023, Номер 349, С. 140970 - 140970

Опубликована: Дек. 17, 2023

Язык: Английский

Процитировано

5