Comprehensive profiles of per- and polyfluoroalkyl substances in Chinese and African municipal wastewater treatment plants: new implications for removal efficiency
Abstract
Municipal wastewater treatment plants (WWTPs) can reflect the pollution status of per- and polyfluoroalkyl substances (PFASs) pollution. Here, matched influent, effluent, and sludge samples were collected from 58 municipal WWTPs in China, South Sudan, Tanzania, and Kenya. Target and suspect screening of PFASs was performed to explore their profiles in WWTPs and assess removal efficiency and environmental emissions. In total, 155 and 58 PFASs were identified in WWTPs in China and Africa, respectively; 146 and 126 PFASs were identified in wastewater and sludge, respectively. Novel compounds belonging to per- and polyfluoroalkyl ether carboxylic acids (PFECAs) and sulfonic acids (PFESAs), hydrogen-substituted polyfluorocarboxylic acids (H-PFCAs), and perfluoroalkyl sulfonamides (PFSMs) accounted for a considerable proportion of total PFASs (ΣPFASs) in Chinese WWTPs and were also widely detected in African samples. In China, estimated national emissions of ΣPFASs in WWTPs exceeded 16.8 t in 2015, with >60 % originating from emerging PFASs. Notably, current treatment processes are not effective at removing PFASs, with 35 of the 54 WWTPs showing emissions higher than mass loads. PFAS removal was also structure dependent. Based on machine learning models, we found that molecular descriptors (e.g., LogP and molecular weight) may affect adsorption behavior by increasing hydrophobicity, while other factors (e.g., polar surface area and molar refractivity) may play critical roles in PFAS removal and provide novel insights into PFAS pollution control. In conclusion, this study comprehensively screened PFASs in municipal WWTPs and determined the drivers affecting PFAS behavior in WWTPs based on machine learning models.
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Chinese municipal WWTPs showed PFAS concentrations much lower than those found in this study in both influent and effluent, with PFBA often predominant.
“Chinese municipal WWTPs showed PFAS concentrations much lower than those found in our study in both in fl uent and ef fl uent, with PFBA often predominant (Jiang et al., 2023; Mu et al., 2022).”
From Occurrence of per- and polyfluorinated alkyl substances in wastewater treatment plants in Northern Italy (2023) · cites this paper as Jiang et al., 2023
Comparable values of PFOA contamination were found in sludge from African WWTPs (South Sudan, Tanzania, and Kenya) during 2015-2016.
“Comparable values of PFOA contamination were found in sludge from African WWTPs (South Sudan, Tanzania, and Kenya) during 2015 -2016 (Jiang et al., 2023).”
From Occurrence of per- and polyfluorinated alkyl substances in wastewater treatment plants in Northern Italy (2023) · cites this paper as Jiang et al., 2023
PFAS contamination in African WWTPs was much lower than those found in this study, with PFBA and PFHxS the most abundant in influent and PFBA the most abundant in effluent.
“PFAS contamination in African WWTPs was much lower than those found in our study, with PFBA and PFHxS the most abundant in in fl uent and PFBA the most abundant in ef fl uent (Jiang et al., 2023).”
From Occurrence of per- and polyfluorinated alkyl substances in wastewater treatment plants in Northern Italy (2023) · cites this paper as Jiang et al., 2023
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- Authors
- Jiang, L., Yao, J., Ren, G., Sheng, N., Guo, Y., Dai, J., & Pan, Y.
- Affiliations
- Shanghai Jiao Tong University (CN)
- National Institute of Metrology (CN)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Pan, Yitao
- Venue
- Science of The Total Environment
- Publisher
- Elsevier BV
- Published
- 2023-01
- Volume
- 857
- Issue
- Pt 3
- Pages
- 159638
- ISSN
- 0048-9697 (ISSN-L)
- OpenAlex
- W4306974908
- Cited by
- 51
- References
- 61
- Citations by year
- 2026: 6 · 2025: 19 · 2024: 20 · 2023: 6
- FWCI
- 4.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- The Science of The Total Environment (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Shanghai Rising-Star Program (22QA1404800)
- National Natural Science Foundation of China (21906160, 41907272, 41977326)
- Topics
- Physical Sciences › Environmental Science › Environmental Chemistry › Per- and polyfluoroalkyl substances research
- Physical Sciences › Environmental Science › Pollution › Pharmaceutical and Antibiotic Environmental Impacts
- Physical Sciences › Environmental Science › Environmental Chemistry › Environmental Chemistry and Analysis
- Keywords
- per- and polyfluoroalkyl substances, municipal wastewater treatment plants, wastewater sludge, PFAS emissions, emerging PFASs, molecular descriptors, adsorption behavior, machine learning, China, Africa
- MeSH terms
- China, Environmental Monitoring, Fluorocarbons, Kenya, Sewage, Water Pollutants, Chemical, Water Purification, Wastewater
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