Cited by 327Per- and polyfluoroalkyl substances researchPharmaceutical and Antibiotic Environmental ImpactsEnvironmental Chemistry and Analysis

The DOI matches its Crossref record; 59 of the 66 references it cites were found in a registry or an index; 2 of the 53 sources its claims cite were checked for support.

An investigation into per- and polyfluoroalkyl substances (PFAS) in nineteen Australian wastewater treatment plants (WWTPs)

Open access

Abstract

Quantifying the emissions of per- and polyfluoroalkyl substances (PFAS) from Australian wastewater treatment plants (WWTP) is of high importance due to potential impacts on receiving aquatic ecosystems. The new Australian PFAS National Environmental Management Plan recommends 0.23 ng L −1 of PFOS as the guideline value for 99% species protection for aquatic systems. In this study, 21 PFAS from four classes were measured in WWTP solid and aqueous samples from 19 Australian WWTPs. The mean ∑ 21 PFAS was 110 ng L −1 (median: 80 ng L −1 ; range: 9.3–520 ng L −1 ) in aqueous samples and 34 ng g −1 dw (median: 12 ng g −1 dw; range: 2.0–130 ng g −1 dw) in WWTP solids. Similar to WWTPs worldwide, perfluorocarboxylic acids were generally higher in effluent, compared to influent. Partitioning to solids within WWTPs increased with increasing fluoroalkyl chain length from 0.05 to 1.22 log units. Many PFAS were highly correlated, and PCA analysis showed strong associations between two groups: odd chained PFCAs, PFHxA and PFSAs; and 6:2 FTS with daily inflow volume and the proportion of trade waste accepted by WWTPs (as % of typical dry inflow). The compounds PFPeA, PFHxA, PFHpA, PFOA, PFNA, and PFDA increased significantly between influent and final effluent. The compounds 6:2 FTS and 8:2 FTS were quantified and F–53B detected and reported in Australian WWTP matrices. The compound 6:2 FTS was an important contributor to PFAS emissions in the studied Australian WWTPs, supporting the need for future research on its sources (including precursor degradation), environmental fate and impact in Australian aquatic environments receiving WWTP effluent.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Twenty-one PFAS from four classes were measured in aqueous and solid samples from 19 Australian wastewater treatment plants, with PFAS detected in every sample. The study reports widespread PFAS occurrence, significant increases of several PFCAs from influent to final effluent, and 6:2 FTS as an important contributor to estimated emissions.

Key findings

  • Mean ∑21PFAS was 110 ng L−1 (median 80 ng L−1; range 9.3–520 ng L−1) in aqueous samples and 34 ng g−1 dw (median 12 ng g−1 dw; range 2.0–130 ng g−1 dw) in solids; PFAS were detected in all samples from all matrices.
  • ∑21PFAS increased across treatment stages: influent 76, primary effluent 89, secondary effluent 140, final effluent 140, and recycled water 120 ng L−1; PFPeA, PFHxA, PFHpA, PFOA, PFNA, and PFDA increased significantly between influent and final effluent.
  • Partitioning to solids increased with fluoroalkyl chain length from 0.05 to 1.22 log units, and was higher for PFSAs than PFCAs of similar chain length, except 6:2 FTS, which had the lowest mean partitioning coefficient and primarily partitioned to the aqueous phase.
  • 6:2 FTS was detected in 99% of aqueous samples (mean 7.3 ng L−1) and 26% of solid samples (mean 0.26 ng g−1 dw); estimated annual discharge for PFBA, PFPeA, and 6:2 FTS was 25, 27, and 19 kg, respectively, similar to PFOS (26 kg), and total ∑21PFAS discharge was estimated at 339 kg using the same annual discharge volume of 3013 GL.

Methods

  • Three replicate aqueous and solid samples were collected from 19 Australian WWTPs throughout 2017, covering influent, primary effluent, secondary effluent, final effluent, recycled water, primary sludge, secondary sludge, and lagoon sludge; aqueous n = 201 and solid n = 51.
  • Twenty-one PFAS from PFCAs, PFSAs, FTSs, and Cl-PFESAs were quantified by LC-MS/MS with isotope dilution after solid-phase extraction for aqueous samples and solvent extraction with dispersive SPE cleanup for solids.
  • Analyses included descriptive statistics, Pearson correlations, linear mixed-effects models comparing influent and final effluent, PCA including daily inflow and percentage trade waste, and log Kd calculations for selected compounds where both aqueous and solid concentrations were above LOQ.

Limitations

  • The paper states that laboratory control samples using ultrapure water and acid-washed sand may not adequately represent WWTP matrices and associated interferences, creating some uncertainty in analytical results.
  • The paper states that annual discharge estimates from a single sampling campaign have high uncertainty due to daily and seasonal variation, and that log Kd calculations are only approximations because they assume equilibrium and do not consider differences in effluent and sludge retention times.
  • Evident from the design: each WWTP was sampled once during 2017, so within-plant temporal variability and seasonal trends are not fully resolved; several compounds were detected only below LOQ or at low frequency, limiting statistical analysis.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.heliyon.2019.e02316

Cites

59 of 59 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Fig. 1 Mean PFAS concentration (n = 3 replicates) in 19 WWTPs from influent (top panel) and final effluent (bottom panel) sampling points. PFUdA, PFTrA, 6:2 Cl-PFESA and 8:2 Cl-PFESA are not plotted as all values were <LOQ.
Fig. 1 Mean PFAS concentration (n = 3 replicates) in 19 WWTPs from influent (top panel) and final effluent (bottom panel) sampling points. PFUdA, PFTrA, 6:2 Cl-PFESA and 8:2 Cl-PFESA are not plotted as all values were <LOQ.CC BY · PubMed Central
Fig. 2 Boxplots of pooled data from 19 WWTPs for A) PFCAs (perfluorocarboxylic acids); B) PFSAs (perfluorosulfonates) and FTSs (fluorotelomer sulfonates) in aqueous samples; C) selected PFAS in solid samples. Aqueous sample locations were influent (n = 57), primary effluent (n = 39), secondary effluent (n = 24), final effluent (n = 57) and recycled water (n = 24). Solid sample locations were primary sludge (n = 15) and secondary sludge (n = 15). # indicates concentration outside y-axis range for PFBA. Asterisk (*) indicates significant difference (<0.01 = **; <0.001 = ***) between influent and final effluent concentrations when tested using linear mixed effects analysis.
Fig. 2 Boxplots of pooled data from 19 WWTPs for A) PFCAs (perfluorocarboxylic acids); B) PFSAs (perfluorosulfonates) and FTSs (fluorotelomer sulfonates) in aqueous samples; C) selected PFAS in solid samples. Aqueous sample locations were influent (n = 57), primary effluent (n = 39), secondary effluent (n = 24), final effluent (n = 57) and recycled water (n = 24). Solid sample locations were primary sludge (n = 15) and secondary sludge (n = 15). # indicates concentration outside y-axis range for PFBA. Asterisk (*) indicates significant difference (<0.01 = **; <0.001 = ***) between influent and final effluent concentrations when tested using linear mixed effects analysis.CC BY · PubMed Central
Fig. 3 Heatmap of PCA results for principal components computed using the correlation matrix (scaled) and including average daily inflow and proportion of trade waste in inflow. Components with eigenvalues above 1 from influent (A) and final effluent (B) are displayed.
Fig. 3 Heatmap of PCA results for principal components computed using the correlation matrix (scaled) and including average daily inflow and proportion of trade waste in inflow. Components with eigenvalues above 1 from influent (A) and final effluent (B) are displayed.CC BY · PubMed Central
Fig. 4 Comparison of estimated annual discharge (kg) of PFAS from Australian WWTPs in this study and from Gallen, Eaglesham [37].
Fig. 4 Comparison of estimated annual discharge (kg) of PFAS from Australian WWTPs in this study and from Gallen, Eaglesham [37].CC BY · PubMed Central

Verification

Claims the paper makes

74 Own result · 33 Not checked yet · 19 Own interpretation · 7 Own method · 2 Partly supported · 2 No basis given · accuracy not yet measured

Verify all 51 references — free account

Show all 82 claims

  • It may state two separate claims as one. 43
  • Probably not a substantial claim. 20
55 of 55
  • The authors state this as an assumption.

    For the log Kd calculation, PFAS concentrations in solids and liquids at the sampled location were in equilibrium.

    “This calculation method is only an approximation as it assumed that the concentration of PFAS in solids and liquids at the sampled location were in equilibrium and does not consider the differences in effluent and sludge retention times.”
  • The paper relies on this without support.

    Typical wastewater treatment processes are unable to remove PFAS from the final effluent.

    “Typical wastewater treatment processes are unable to remove PFAS from the final effluent.”
  • The paper relies on this without support.

    In Australian cities, sewer systems are closed, with separate stormwater sewers and low infiltration rates, so rainfall has limited effect on influent PFAS composition as opposed to pulse events from industrial effluent discharge.

    “Furthermore, unlike many parts of the world, in Australian cities, sewer systems are closed, with separate stormwater sewers and low infiltration rates, this means rainfall has limited effect on influent PFAS composition as opposed to pulse events from industrial effluent discharge.”
  • The authors state this as an assumption.

    The same annual discharge volume of 3013 GL applies to the 19 WWTPs in this study.

    “Assuming the same annual discharge volume of 3013 GL and using mean annual discharge rates from the 19 WWTPs in this study, we calculated an estimated discharge of ∑21PFAS of 339 kg.”
4 of 4

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

2 of 2

Citations

Cites

Show all 66 references

Cited by

Sorted by citations

Items 201–300 of 326

Metadata

Authors
Coggan, T. L., Moodie, D., Kolobaric, A., Szabo, D., Shimeta, J., Crosbie, N. D., Lee, E., Fernandes, M., & Clarke, B. O.
Affiliations
  • RMIT University (AU)
  • Melbourne Water (AU)
  • Water Corporation of Western Australia (Australia) (AU)
  • Flinders University (AU)
Corresponding author
Coggan, Timothy L.
Venue
Heliyon
Publisher
Elsevier BV
Published
2019-08
Volume
5
Issue
8
Pages
e02316
ISSN
2405-8440 (ISSN-L)
OpenAlex
W2969674960
Cited by
327
References
66
Citations by year
2026: 43 · 2025: 62 · 2024: 61 · 2023: 50 · 2022: 47 · 2021: 41 · 2020: 23
FWCI
12.07
Type
journal article
Language
en
Open access
Locations
  • Heliyon (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RMIT Research Repository (RMIT University Library) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
Funders
  • Department of Education, Employment and Workplace Relations, Australian Government
  • Water Research Australia
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, PFAS, wastewater treatment plants, PFAS emissions, perfluorocarboxylic acids, perfluorinated sulfonic acids, fluorotelomer sulfonates, trade waste, influent and effluent concentrations, aquatic ecosystems

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-10-07, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-10-07 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Cited sources are checked with a language model’s help (gpt-6-sol).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review