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. Author manuscript; available in PMC: 2026 Sep 26.
Published in final edited form as: J Environ Eng (New York). 2026 Feb 24;152(5):04026013. doi: 10.1061/JOEEDU.EEENG-8452

Comparative Analysis of Influent and Effluent Measurements of Per- and Polyfluoroalkyl Substances (PFAS) at Wastewater Treatment Facilities

Carol J Miller 1,*, Gwendolyn Schmidt 2, Sydni Jordan 3, Ebissa Kedir 4, Brendan O’Leary 5, James Hartrick 6, Majid Khan 7, Stephen Kuplicki 8, Mallory J Llewellyn 9, John Norton 10, Karoline Tangen 11, Catherine Willey 12, Tracie Baker 13
PMCID: PMC13614102  NIHMSID: NIHMS2199459  PMID: 42799163

Abstract

Per- and polyfluoroalkyl substances (PFAS) are infamous for their persistence as emerging environmental contaminants. While new treatment technologies are evolving to reduce PFAS at known sites of environmental contamination, the efficacy of traditional wastewater treatment plants (WWTPs) to reduce the suite of PFAS congeners is relatively unknown. The present research used a mass balance approach to assess the apparent removal efficiency of PFAS at a major regional wastewater treatment facility in the Great Lakes region. Since the sewer sheds for this facility are primarily combined, the sampling and analysis considered both dry- and wet-weather events. Samples of influent and effluent were collected and analyzed using solid phase extraction (SPE) and ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). A significant feature of the present research is the comparison of removal characteristics observed at this facility compared to those presented in previous studies for the most common PFAS compounds found in domestic wastewater, i.e., PFOA, PFOS, PFHxS, PFHxA, PFNA, 6:2FTS, and PFBS. The comparison uses the “apparent removal efficiency” (ARE) which represents the difference between influent and effluent mass divided by the influent mass. While most all the examined WWTPs display a negative apparent removal efficiency for each congener (effluent mass exceeds the measured influent mass of the particular congener), the urban WWTP of the present study has a more positive removal profile. This research provides potential explanations for the measured AREs while noting that the complexity of PFAS transformations as well as the large number of known congeners makes current approaches of estimating removal efficiency fraught with errors.

PRACTICAL APPLICATIONS:

Many wastewater treatment facilities are scrambling to better understand how effectively their treatment processes are handling emerging contaminants, including those in the per- and polyfluoroalkyl substances (PFAS) family of analytes. While some of these analytes now have mandated limits for drinking water applications, there are only limited guidelines for PFAS discharges in wastewater effluent. Consultants and design engineers will likely be very interested in the PFAS influent and effluent data contained in this paper and the use of “apparent” removal efficiency to compare the relative treatment efficacy of various plants with contrasting tributary characteristics. New data from one of the largest operating regional wastewater treatment facilities in the US is compared to other plants throughout the US and the world.

Keywords: PFAS, Combined Sewer System, Influent, Effluent, Wastewater Treatment, Interceptor, Removal Efficiency

INTRODUCTION:

Per- and polyfluoroalkyl substances (PFASs) are a class of anthropogenically sourced chemicals that are characterized by having at least one fully fluorinated carbon atom (Buck et al. 2011). They are aliphatic substances made of carbon-fluorine backbones and functional moieties. The combination of these characteristics has resulted in strong, persistent, and bioaccumulating chemicals that resist environmental and thermal degradation (Bălan et al. 2024; Dewapriya et al. 2023; Lin et al. 2024; Nguyen et al. 2022; Pétré et al. 2022; Smith et al. 2024; Wang et al. 2021; Winchell et al. 2021; Xu et al. 2021). Their strength lies in this stability, and their moieties result in both hydrophobic and lipophobic natures. PFAS chemicals have been used in industrial, commercial, and residential settings as surfactants, stain repellents, fluoropolymers, flame retardants, food packaging, and as many other products (Glüge et al. 2020). Research into the human health impacts of PFAS is an ongoing area of discovery, but there is a general consensus that many of the congeners can be harmful, with attributed impacts of cancer, liver diseases, heart attacks, strokes, reduced immune systems, cholesterol, etc. (Haimbaugh et al. 2024).

The effluent from wastewater treatment plants (WWTPs) has been identified as a major source of PFAS (Müller et al. 2023; Schultz et al. 2006; Sinclair and Kannan 2006) to the environment. Moreover, sewage sludge is known to be a sink for perfluorooctane sulfonic acid (PFOS). It was shown previously that WWTPs do not remove PFAS efficiently from wastewater (Schultz et al. 2006), and concentration of some PFAS components were found at higher levels in effluent water than influent water (Blaine et al. 2013; Brendel et al. 2018; Schultz et al. 2006; Sinclair and Kannan 2006). This suggests the biotransformation of precursor chemicals into PFAS during the WWTP processes. Unstable organofluorine compounds are precursors that transform to perfluoroalkyl acids (PFAA), e.g., perfluorooctane sulfonic acid (PFOS) and perfluoro octanoic acid (PFOA) (Blaine et al. 2013; Brendel et al. 2018; Müller et al. 2023; Schultz et al. 2006; Sinclair and Kannan 2006). Some studies assessed PFAS removal efficiency to answer the question of how efficient wastewater treatment facilities are in removing PFAS from influent flows (Ateia et al. 2019; Belkouteb et al. 2020; Chen et al. 2018; Glüge et al. 2020; Higgins and Luthy 2006b; Kothawala et al. 2017; Lenka et al. 2021; Pan et al. 2016; Zaggia et al. 2016).

The presence of significant PFAS contamination in urban areas of the Great Lakes watershed has been documented by previous researchers (Llewellyn et al. 2024). To assess the impact of urbanization and wastewater treatment processes, these researchers collected surface water, sediment, and fish samples at 27 sites within the Huron to Erie Corridor (HEC), an international waterway including the highly urbanized Detroit and Rouge Rivers. The results indicate the need for expanding toxicological research and risk assessment focused on congeners such as PFHxA and PFAS mixtures.

After decades of widespread PFAS use, the emerging understanding of adverse human health effects resulted in the phase-out of some of the long-chain PFAS in European countries (Brendel et al. 2018). While May 2025 final guidelines in the U.S. no longer include phase-out language, monitoring regulations and maximum contaminant levels (MCLs) are proposed (US EPA, 2025). Production of PFOA and PFOS, the two most well-known compounds, has significantly stalled (Buck et al. 2011; Higgins and Luthy 2006; Lakshminarasimman et al. 2021). Subsequent shifts to similarly structured but shorter-chained alternatives, such as perfluorohexanoic acid (PFHxA) and perfluorobutane sulfonic acid (PFBS), commenced (Buck et al. 2011; Lenka et al. 2021). The stability of the chemicals and their continued use left them ever-present in many environmental matrices, often being transported by air and water or settled into soils and sediments.

The major objectives of the present study are to (1) characterize the PFAS profile of the influent and effluent flows at a large urban regional WWTP, (2) compare the differences in PFAS composition at these sampling points for conditions associated with dry weather and wet weather, and (3) compare the findings of this and earlier investigations with respect to mass loading to and removal characteristics of the investigated treatment plants.

MATERIALS AND METHODS:

Site Description

This study is centered around a midwestern wastewater treatment facility served by a combined sewer system that delivers a daily mix of residential, commercial, and industrial waste from over 840 square miles. Trunk sewers lead the flows to three interceptors: Detroit River Interceptor (DRI (J)), North Interceptor-East Arm (N), and Oakwood-Northwest-Wayne County Interceptor (O) as shown in Figure 1. This same region was considered in a recent study focused on the quantification of human viruses, such as SARS-CoV-2, in wastewater (Miyani et al. 2021). In that case, the samples collected from the three interceptors exhibited SARS-CoV-2 in 100% of samples with concentrations in the range of 104–105 genomic copies/L. The present study evaluates PFAS loading in the same tributary area serviced by the three interceptors. Due to some infrastructure design changes that occurred between 2021 and the present sampling, there are slight differences between the WWTP drainage area delineation in the Miyani et al. (2021) paper (previously referenced) and the present. The current drainage alignment appears in Figure 1.

Fig. 1. Study Area Geography and Drainage Areas (Source: GLWA Master Plan Document).

Fig. 1.

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The drainage areas tributary to interceptor J, N, and O contribute approximately 36%, 29%, and 35% to the total influent flow to the WWTP, respectively. From there the facility employs influent screening, primary clarification, aeration, secondary clarification, and chlorination to treat the wastewater prior to discharge. Primary and return-activated sludges are collected from their respective clarification processes, and a portion of the return sludge gets separated off and designated as waste activated sludge. Wasted and primary sludges undergo gravity thickening, dewatering, and either drying, offloading, or incineration.

Under typical dry weather operation, all incoming flows up to a 930 Million Gallons per Day (MGD) are treated with both primary and secondary processes. In these scenarios the effluent is discharged through a single, primary outfall – Outfall No. 1. Circumstances where influent flows exceed the 930 MGD capacity, are herein referred to as wet weather conditions. When occurring, the excess skips aeration and secondary treatment altogether, and buffer flows are rediverted to follow the normal flow path. Flows greater than 1,150 MGD are then discharged through a second, nearby outfall – Outfall No. 2 – in addition to the primary outfall.

Sample Collection and Experimental Setup

The present investigation consisted of two field sampling events: one for dry weather which occurred on June 21, 2022, and another for wet weather which occurred on July 2, 2023. Samples were taken from the interceptors, primary effluent, secondary effluent, final effluent, primary sludge, and waste activated sludge. All liquid stream samples were collected as composites, where peristaltic pumps operated in 9- to 11-minute intervals to retrieve equal volumes over each 24-hour period. Sludges were collected as grab samples during the same time frames. Wet weather conditions prompted the use of Outfall No. 2, resulting in the collection of the corresponding sample. All samples were initially obtained by the plant operators and laboratory staff at the end of the 24-hour period. For the dry weather event, wastewater was collected in large carboys, thoroughly shaken, then portioned and transferred into duplicate 250-ml High Density Polyethylene (HDPE) bottles. Sludges were collected in singular, 1-liter HDPE bottles. All were immediately placed on ice and shipped overnight to the University of Florida analysis laboratory, where they were stored at approximately −20°C until analyzed using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The same procedures and UHPLC-MS/MS analysis method were implemented for the wet weather event; however, the samples were taken directly to Ann Arbor Technical Services (ATS), where they were stored and processed the next day. The present manuscript relates only to the samples obtained from the interceptor inflow (three interceptors) and outflow (one or two depending on dry or wet weather operation).

Dry Weather SPE Protocol

Analysis of dry weather samples was completed at the University of Florida using a method similar to EPA 1633 Method (US EPA, 2021); there were slight variations from the EPA method only because the method used was developed before 1633 existed. The solid phase extraction (SPE) protocol aligned with the methods described by Griffin et al. 2022. Before the analyses commenced, wastewater samples were thawed overnight at room temperature, which ranged from 20°C – 22°C. On the following day, samples underwent gravimetric weighing and pH adjustments. Glacial acetic acid was added to lower each pH value to 3, and an internal standard mixture containing 19 isotopically-labeled PFAS dissolved in methanol was incorporated as well. Strata-XL-AW 100 μm Polymeric Weak Anion 500 mg/6 mL cartridges were conditioned, and a vacuum manifold facilitated the sample filtration process. All buffers were prepared on the day of extraction. Cartridges were washed, dried, then eluted into clean test tubes. The weighing of each empty sample bottle allowed the final volume measurements to be normalized. Sample evaporation was achieved with ultra-high purity nitrogen gas, followed by the transfer into PP autosampler vials, storage at 4 °C, and concentration analysis.

Six quality control water samples were prepared for the dry weather analysis. Optima-grade methanol was poured into clean 250-mL HDPE containers prior to being spiked with the internal standard solution. Half of the QC samples were also spiked with the quality control mix. Original and QC samples were then processed and analyzed at the same time, screening each sample for the presence of 44 PFAS analytes. The methodology for the dry weather samples is more fully described in our earlier publication (Llewellyn et al. 2024).

Wet Weather SPE Protocol

The wet weather analysis was completed at ATS Laboratory in Ann Arbor, MI. Similar to the approach for the dry weather analysis, ATS utilizes a modified version of EPA Method 1633 that incorporates all the quality assurance elements of 1633. ATS refers to this as the PFAS FIDM (“Full Isotope Dilution Method”). It incorporates radiolabeled internals for extraction and injection. It currently has 44 target PFAS analytes, and is flexible enough that additional PFAS analytes can be added in the future as the need arises. Some portions of the ATS PFAS FIDM method are proprietary to the laboratory and can not be fully described here. However, in the Supplementary Material, we have added several tables (S1-S5) that specifically detail this method in relation to QC, MDLs, Internal Standards, and Transition Ions.

Post-Analysis Quality Control

Dry weather processing screened the samples for 44 congeners while wet weather processing screened for 34. Only the PFAS chemicals that were measured in both events were considered for the comparative analysis, narrowing the list to 24 congeners identified (along with their abbreviations) in Table 1. Of the 24 congeners, only 13 had values above ND between the two sampling efforts. Clarification of how the screened analytes were narrowed down to 24 is depicted in Fig 2. According to O’Connor et al. 2023 and Thompson et al. 2022, PFOA, PFOS, PFHxS, PFHxA, PFNA, 6:2 FTS, and PFBS are the 7 most common analytes found in domestic wastewater. This paper will compare the concentrations of the 7 common analytes between the current sampling at the urban WWTP and other reported values from WWTPs reported within previous literature.

Table 1.

PFAS analytes and abbreviations, present study

Analyte Abbreviation
perfluorobutanoic acid PFBA
perfluoropentanoic acid PFPeA
perfluorohexanoic acid PFHXA
perfluoroheptanoic acid PFHpA
perfluorooctanoic acid PFOA
perfluorononanoic acid PFNA
perfluorodecanoic acid PFDA
perfluoroundecanoic acid PFUnA
perfluorododecanoic acid PFDoA
perfluorotridecanoic acid PFTrDA
perfluorotetradecanoic acid PFTeDA
perfluorobutane sulfonic acid PFBS
perfluoropentane sulfonic acid PFPeS
perfluorohexane sulfonic acid PFHXS
perfluoroheptane sulfonic acid PFHpS
perfluorooctane sulfonic acid PFOS
perfluorononane sulfonic acid PFNS
perfluorodecane sulfonic acid PFDS
perfluorododecane sulfonic acid PFDoS
4:2 fluorotelomer sulfonic acid 4:2 FTS
6:2 fluorotelomer sulfonic acid 6:2 FTS
8:2 fluorotelomer sulfonic acid 8:2 FTS
5:3 fluorotelomer carboxylic acid 5:3 FTCA
perfluorooctanesulfonamide PFOSA
perfluoroalkyl acids PFAA
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Fig. 2. Conceptual Diagram of the Assignment of the 24 Common Analytes from the Combined Dry Weather and Wet Weather Analyses.

Fig. 2.

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Measures were also taken to maintain quality and consistency throughout the analysis phases. Field blanks for both the dry and wet weather events were analyzed alongside the other liquid phase samples. The protocol for analyte detection included subtracting the highest field blank concentrations from those of the other samples. If the difference yielded any negative values, the analyte was excluded from both dry and wet weather reporting. In all cases but one, the field blank concentration was non-detect (ND).

RESULTS:

Hourly influent and effluent flow values were measured at the facility and shared with the researchers after each conditional event. The flow values for the corresponding 24-hour period were averaged and converted to volumetric measurements. The product of flow volumes and concentration measurements resulted in the PFAS mass values, which were assessed and compared for each event.

Influent and Effluent Flows

Dry weather influent flows to the WWTP from the three interceptors (combined) ranged from 313 to 644 MGD with a time-averaged inflow of 456 MGD. The metered effluent rate varied from 296 to 623 MGD during this same time period, resulting in a time-averaged effluent value of 435 MGD.

The wet weather inflows ranged from 501 to 1658 MGD over the 24 hours of the sampling period, with a resulting time-averaged influent flow of 917 MGD. The combined effluent flow rate from Outfall No. 1 and Outfall No. 2 peaked at 1658 MGD, and the time-averaged discharge was 917 MGD. Thus, the 24-hour effluent flow volume is 917 million gallons (matching the influent volume).

Measured PFAS Concentrations

Selected results of the sample processing and UHPLC-MS/MS analyses are displayed in Table 2. Weighted influent values account for each interceptor’s contribution to the influent flow by factoring their flow proportions (36%, 29%, and 35% for Interceptors J, N, and O, respectively) into a weighted concentration average. Individual interceptor concentrations allow for future correlations between PFAS quantities, tributary sewers, and their geographic locations. The weighted averages reduce the information into a standalone inflow value. The list of PFAS concentrations was also set to include PFOS, however, high levels of detection in wet weather field blanks caused the analyte to be excluded from the wet weather analysis but included in dry weather analysis. The field blank issue is indicated in Table 2 with NS*.

Table 2.

Measured PFAS concentrations for the WWTP influent and effluent flows, present study

Dry Weather Concentrations (ng/L)
 Wet Weather Concentrations (ng/L)
Interceptor
 Outfall
 Interceptor
 Outfall
Analytes J N O 1 J N O 1 2
PFBA ND ND ND ND ND 5.0 11.7 6.4 ND
PFPeA ND ND ND ND 4.3 5.6 9.0 6.5 6.4
PFHxA 6.1 7.8 24.6 13.8 ND 7.2 18 13 12
PFHpA 2.3 2.2 6.6 2.1 ND 2.2 3.8 2.3 2.4
PFOA 3.4 4.7 10.8 6.1 2.9 4.4 8.7 5.0 5.4
PFNA ND ND ND ND ND ND ND ND ND
PFDA ND 0.4 1.1 0.60 ND ND ND ND ND
PFUnA ND ND ND ND ND ND ND ND ND
PFDoA ND ND ND ND ND ND ND ND ND
PFTrDA ND ND ND ND ND ND ND ND ND
PFTeDA ND 8.3 ND ND ND ND ND ND ND
PFBS ND ND ND ND ND 11 16 9.7 10
PFPEs ND ND ND ND ND ND ND ND ND
PFHxS ND ND ND ND ND 2.3 3.5 2.3 ND
PFHpS ND ND ND ND ND ND ND ND ND
PFOS 5.1 3.6 9.4 5.14 * * * * *
PFNS ND ND ND ND ND ND ND ND ND
PFDS ND ND ND ND ND ND ND ND ND
PFDoS ND ND ND ND ND ND ND ND ND
4:2 FTS ND ND ND 0.02 ND ND ND ND ND
6:2 FTS 10. 64.4 12.5 45.8 ND 2.3 3.4 2.8 2.2
8:2 FTS ND ND ND ND ND ND ND ND ND
5:3 FTCA ND ND ND ND ND 10.8 38 7.5 8.5
PFOSA ND ND ND ND ND ND ND 3.2 4.9
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Note: ND= NonDetect,

*

= Sampled, but unable to use data due to quality control issues; Outfall 1 is the primary outfall, while outfall 2 is the secondary outfall used only for wet weather events

As shown conceptually in Figure 1, many of the 24 “common” PFAS congeners included in the sampling set were not detected in either the influent or effluent flows on the sampling days (i.e. PFNA, PFUnA, PFDoA, PFTrDA, PFPeS, PFHpS, PFNS, PFDS, PFDoS, and 8:2 FTS). It is also true that many PFAS congeners were not even in the list of sampled analytes, given that the total list contains more than 14,000 unique congeners (US EPA 2022). Therefore, it is critical to note that while the present results may inform estimations of PFAS contributions from the sewershed, the common list of congeners may represent only a small portion of the PFAS that may be present in the wastewater samples. This note also impacts the reliability of the removal efficiency calculations for each congener, as transformations may occur from congeners that were not in the influent/effluent sampling list. Nevertheless, the trends that are observable at this level are still worthy of exploration. For example, none of the PFAS detected in the wet weather sampling contained more than eight carbon atoms (8C) in their fluorinated chains. The trends observed are also on a comparable basis to previous work reported in the literature which has included only a subset of the total known PFAS analytes.

Table 2 provides only the measured PFAS concentrations in the influent and effluent flows, although the sampling exercise included other in-plant sampling locations. There were instances in which analytes identified in Table 2 as non-detect (ND) yielded measurable concentrations at other, intermediate sampling points throughout the plant. For example, the full suite of dry weather results showed that PFNA was detected at a point just before the secondary treatment process. However, the chemical was not detected in either the influent or effluent from the same day. Such results may not be reflected in a comparative end-to-end analysis, but they do provide a holistic characterization of the facility’s PFAS profile. An extensive report of these values may be found in the supplemental information.

PFAS mass distribution

The concentrations shown in Table 2 are converted into mass units to develop further insights regarding the data. Of the 24 PFAS chemicals on the common list, only eight analytes yielded detectable influent or effluent concentrations in the dry weather sampling event (Figure 1). The following analytes were uniquely detected in the dry weather sampling PFDA, PFTeDA, and 4:2 FTS; with 4:2 FTS noted only in the effluent as shown in Table S6 and Fig. 3. The total observed mass (∑PFAS) for the 24-hour influent flow was 98.9 grams, with 33% being 6:2 FTS from interceptor N which made up the majority of the mass that flowed through that interceptor.

Fig. 3. Dry weather mass contributions for the eight detected analytes.

Fig. 3.

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Interceptor O contained the most mass of each of the detected analytes, except for 6:2 FTS, with PFHxA having the second highest mass of the influent flow, making up 44% of the flow in Interceptor O. These findings do not correlate with the sewers’ contributions to influent flow. Interceptor N, which contributed the smallest proportion at 29%, delivered the most PFAS mass to the treatment facility, while Interceptor J, responsible for the largest proportion at 36%, delivered the least. The total mass observed in the effluent flow was 112.8g, with 6:2 FTS making up more than half of the observed mass.

Of the wet weather samples, only ten of the 24 common analytes were detected. The following analytes were uniquely noted in the wet weather samples: PFBA, PFPeA, PFBS, PFHxS, 5:3 FTCA, and PFOSA as shown in Table S7 and Fig. 4. Note that PFOSA is only detected in the effluent discharge. The influent flow volumes were much greater for the wet weather sampling than dry conditions, which contributes to the more than double PFAS mass loading for the wet over dry conditions. The largest contributor to the wet weather mass was the analyte 5:3 FTCA, which represented 29% of the accounted influent PFAS mass.

Fig. 4. Wet weather mass distribution for the ten detected analytes.

Fig. 4.

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Similar to the dry weather sampling, interceptor O contributed the greatest mass of each analyte for the influent flow. The observed trends for dry weather hold for the wet weather conditions. Though Interceptor J was responsible for 36% of the flow, 5% of PFAS were detected throughout the sampling period. PFPeA and PFOA made up the 5% of the mass found in Interceptor J, while the other analytes from the common list were not detected. On the effluent side, PFHxA contributed the greatest mass at 22% of total effluent flow, with PFBS having the second greatest mass at 17%. For all analytes, Outfall 1 exhibited greater mass loading of PFAS than Outfall 2. Large influent flows led to large effluent flows, and the resulting ∑PFAS mass was 1.75 times greater than that of the dry weather sampling.

The detected common analytes consisted of subsets of PFAS, including Perfluoroalkyl carboxylic acids (PFCA), perfluoroalkyl sulfonates (PFSA), Fluorotelomer Sulfonate (FTS), and Fluorotelomer Carboxylic Acid (FTCA). Long chain PFCAs and FTCAs have seven or more fluorinated carbons, and long chain PFSAs and FTS have six or more fluorinated carbons. Since the use of long-chain PFAS has been fading out, short-chain PFAS has been used in their place. Short-chain PFAS are more mobile in aqueous environments than long-chain PFAS, causing a wider spread of contamination. While short-chain PFAS are less likely to bioaccumulate, they have their own harmful effects, making them no better than long-chain (Brendel et al. 2018). In this study, wet weather conditions brought a wider spread of detectable PFAS analytes and higher masses to the treatment facility. The detected dry weather analytes consisted of three short-chain PFAS, and the detected wet weather analytes had four short-chain PFAS. Additionally, the dry weather samples only had one PFSA, with the rest being PFCA and FTS, while wet weather had two PFSAs, PFCA, FTS, and FTCA.

“Apparent” PFAS removal efficiency

Removal efficiency assessments are typically completed to document WWTPs’ ability to reduce a particular contaminant from the influent stream. For the case of PFAS, it is very difficult to compute an accurate estimate of this due to the multiple transformations in the carbon and fluorine bonds that occur during the various treatment processes, as well as the inability to accurately capture/measure all the potential PFAS precursors in the influent stream. Therefore, in the present analysis, the comparison between influent and effluent mass of a particular PFAS congener will be referred to as apparent removal efficiency (ARE). From this point on, this paper will consider only PFOA, PFOS, PFHxS, PFHxA, PFNA, 6:2FTS, and PFBS, as these seven analytes are commonly found in drinking water and are regulated under the EPA. In addition, these are the common PFAS that appear in much of the previously published literature that we are using for our comparative analysis. The ARE for the dry and wet weather events of the present investigation are presented in Table S8 and Fig. 5. Under dry weather conditions, the ARE was positive for PFOA and PFOS but negative for PFHXA and 6:2 FTS. In wet weather conditions, the ARE was positive for PFOA and PFHXS but negative for PFBS, PFHxA, and 6:2 FTS. The wet weather PFOS ARE could not be calculated, as there was the issue with the high concentration in the field blank for PFOS during the wet weather collections, as discussed earlier in this paper. While the calculation of negative ARE values is concerning, the subsequent section compares to other WWTPs in the literature, and suggests this occurrence is common – in fact, there are many cases of comparable or greater negative values of ARE than those calculated in the present analysis. This suggests that while ARE provides a basis for comparison, it should not be used as an indication of the holistic removal efficiency of PFAS as a whole. It is possible that the overall removal efficiency of combined PFAS congeners (more than 14,000 as noted earlier in this paper) is positive. The ARE metric can be used to evaluate the removal efficiency of an individual PFAS analyte. Even then, it is possible that reactions within the WWTP modify the PFAS bonds and lead to transformations within and among congeners. In that case, the ARE would not be an accurate reflection of removal efficiency.

Fig. 5. A comparison of the present study’s apparent removal efficiency (ARE) for dry and wet weather conditions.

Fig. 5.

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COMPARISON OF PRESENT OBSERVATIONS TO EXISTING LITERATURE:

Concentration comparisons

Existing literature on PFAS measurements at WWTPs was analyzed to better understand the variation of PFAS concentration profiles at the influent and effluent of WWTPs both within the United States and abroad. Each of the WWTPs serves a unique community in terms of surface area coverage, land use type, climate, and industry contributions. Tavasoli et al. (2021) studied six municipal WWTPs in southeastern New Hampshire, US, which discharge into the Great Bay Estuary. The authors note that while the sampled WWTPs accept primarily municipal waste, some also accept industrial waste, including septage and pretreated landfill leachate. Bossi et al. (2007) focused on a wide study area that includes 11 WWTPs across Denmark, seven of which accept municipal waste and four industrial wastes. In contrast, the Loganathan et al. (2007) study sampled two WWTPs located in western Kentucky and eastern coastal Georgia, US. Both WWTPs sampled accept waste from domestic and commercial districts and differ in that the Kentucky plant serves a rural area, while the Georgia plant serves an urban area. Gobelius et al. (2023) looked at the primary treatment plant in Uppsala, Sweden, which accepts primarily industrial and domestic wastewater as well as some storm runoff. The study by Lin et al. (2024) targeted 13 WWTPs that receive waste streams from primarily residential sources, categorized by neighborhood and housing type, although some light industry (retail stores, automotive, carpet cleaners) was present. In Desgens-Martin et al. (2023), a total of six WWTPs located across southern and central California, US were sampled 13 times over two years and divided into regions based on characteristics such as population size and land use of the surrounding area. Wastewater entering these plants comes from agricultural, urban, undeveloped, and biosolid-treated areas. Schultz et al. (2006), in contrast, sampled only one WWTP, located in the Pacific Northwest, which services 50,000 people and accepts municipal wastewater.

Figs. 6 and 7 show the number of times the concentration sum of the common PFAS analytes was detected within the given concentration range for influent and effluent, respectively. Most treatment plants had concentrations below 101 ng/L except for Desgens-Martin et al. (2023) and Loganathan et al. (2007).

Fig. 6. Comparison of occurrences # of plants vs range of concentration, Influent.

Fig. 6.

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Fig. 7. Comparison of occurrences # of plants vs range of concentration, Effluent.

Fig. 7.

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Comparison of apparent removal efficiency (ARE)

In this research, we have estimated the apparent removal efficiency (ARE) of PFAS of the present study, using the ARE definition provided earlier. In this section, we compare the ARE of present study to the ARE calculated using data from other WWTPs examined from the literature (Table S9 and Fig. 8). Note that the most negative ARE calculated was greater than −1000%, but the negative extent of the scale was limited to −700% to make the remainder of the data more readable. Of all the results shown in Figure 8, there are more positive AREs than negative. However, some of the negative values are very concerning. As shown in Fig. 8, the largest negative value for ARE is −1092.5% for PFNA, as calculated from the data in Lin et al. (2024).

Fig. 8. Comparison of ARE of PFAS analytes between the present study and existing literature. The present study is R1,

Fig. 8.

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Tavasoli et al. 2021 is R2, Schultz et al. 2006 is R3, Loganathan et al. 2007 is R4, Lin et al 2024 is R5, Bossi et al 2007 is R6, and Gobelius et al 2023 is R7. The “P” value included with the reference citation indicates the plant number from that citation (several references examined more than one WWTP).

Other studies have shown mass change trends over unit processes that have driven similar influent-to-effluent evaluations. These mass changes are most often ascribed to the relationship between flow phase, organic matter content, and analyte hydrophobicity (Higgins and Luthy 2006; Lenka et al. 2021). PFAS chemicals, being largely hydrophobic due to the number and positioning of carbon-fluorine bonds, sorb to the organic matter present in most wastewater sludges and solids-heavy aqueous flows. The larger the carbon-fluorine chain, the more hydrophobic the analyte is and the higher the propensity is for these surface-level interactions to occur. Neither the dry nor wet weather removal efficiency results conform to any trendline that would imply this phenomenon took place on the days of sampling. However, expanding the study and increasing sampling points for each condition may provide a reliable suite of information that shows otherwise.

CONCLUSIONS:

The major objectives of the present study are to (1) characterize the PFAS profile of the influent and effluent flows at a large urban regional wastewater treatment plant (WWTP), and (2) compare the findings of this and earlier investigations concerning mass loading to and removal characteristics of the investigated treatment plants. The dry weather results for this study showed the wastewater had high values of PFCAs and FTS with a mix of short-chain and long-chain analytes. The wet weather results consisted of a wider spread of analytes, including an additional PFSA as well as a FTCA, more short-chain analytes, as well as a higher mass of analytes overall. The apparent removal efficiency for the seven analytes commonly found in drinking water was calculated for the present study. PFHxA, PFOA, and 6:2 FTS were detected in both sampling events, where dry weather had less mass than wet weather for the analytes, except for 6:2 FTS.

The concentration of the seven analytes commonly found in drinking water from the present study was compared with existing literature of PFAS concentrations in different climates, influent categories, and populations. Figures 6 and 7 show the number of treatment facilities or times the sum of the analytes was detected within a concentration range. For most of the references, the summation of the influent PFAS concentrations was calculated below 120 ng/L, and the values for the sewershed added to this literature review exhibited inputs below 80 ng/L. The inflow concentrations from Desgens-Martin et al. (2023), were significantly larger.

The results of this study will form the foundation of a multi-year assessment. Efforts will be made to expand sampling events, coordinate influent PFAS quantities with the geographic locations of tributary sewers, and incorporate statistical analyses related to differing demographics and land use.

Supplementary Material

Supplemental

ACKNOWLEDGEMENTS:

The authors sincerely acknowledge the research funding support from the Fred and Barbara Erb Family Foundation [Award No. 2399] for the completion of this work. A portion of this work was also supported by a grant from the National Institute of Environmental Health Sciences, National Institutes of Health [ P42 ES030991]. In addition, the authors acknowledge the cooperation and technical support from the Great Lakes Water Authority (GLWA), Detroit, USA in completion of this research, especially individuals from the GLWA Water Resource Recovery Facility (WRRF).

DATA AVAILABILITY STATEMENT:

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. Some or all data, models, or code generated or used during the study are available in a repository online.

REFERENCES:

  1. Ateia M, Alsbaiee A, Karanfil T, and Dichtel W 2019. “Efficient PFAS Removal by Amine-Functionalized Sorbents: Critical Review of the Current Literature.” Environ Sci Technol Lett, 6 (12): 688–695. American Chemical Society. 10.1021/acs.estlett.9b00659. [DOI] [Google Scholar]
  2. Bălan SA, Bruton TA, Harris K, Hayes L, Leonetti CP, Mathrani VC, Noble AE, and Phelps DSC 2024. “The Total Mass of Per- and Polyfluoroalkyl Substances (PFASs) in California Cosmetics.” Environ Sci Technol, 58 (27): 12101–12112. 10.1021/acs.est.3c06539. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Belkouteb N, Franke V, McCleaf P, Köhler S, and Ahrens L 2020. “Removal of per- and polyfluoroalkyl substances (PFASs) in a full-scale drinking water treatment plant: Long-term performance of granular activated carbon (GAC) and influence of flow-rate.” Water Res, 182. 10.1016/j.watres.2020.115913. [DOI] [PubMed] [Google Scholar]
  4. Blaine AC, Rich CD, Hundal LS, Lau C, Mills MA, Harris KM, and Higgins CP 2013. “Uptake of perfluoroalkyl acids into edible crops via land applied biosolids: Field and greenhouse studies.” Environ Sci Technol, 47 (24): 14062–14069. 10.1021/es403094q. [DOI] [PubMed] [Google Scholar]
  5. Bossi R, Strand J, Sortkjær O, & Larsen MM 2008. “Perfluoroalkyl compounds in Danish wastewater treatment plants and aquatic environments”. Environment International, 34(4), 443–450. 10.1016/j.envint.2007.10.002 [DOI] [PubMed] [Google Scholar]
  6. Brendel S, Fetter É, Staude C, Vierke L, and Biegel-Engler A 2018. “Short-chain perfluoroalkyl acids: environmental concerns and a regulatory strategy under REACH.” Environ Sci Eur, 30. 10.1186/s12302-018-0134-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Buck RC, Franklin J, Berger U, Conder JM, Cousins IT, De Voogt P, Jensen AA, Kannan K, Mabury SA, and van Leeuwen SPJ 2011. “Perfluoroalkyl and polyfluoroalkyl substances in the environment: Terminology, classification, and origins.” Integr Environ Assess Manag, 7 (4): 513–541. 10.1002/ieam.258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chen S, Zhou Y, Meng J, and Wang T 2018. “Seasonal and annual variations in removal efficiency of perfluoroalkyl substances by different wastewater treatment processes.” Environmental Pollution, 242: 2059–2067. 10.1016/j.envpol.2018.06.078. [DOI] [PubMed] [Google Scholar]
  9. Dewapriya P, Chadwick L, Gorji SG, Schulze B, Valsecchi S, Samanipour S, Thomas KV, and Kaserzon SL 2023. “Per- and polyfluoroalkyl substances (PFAS) in consumer products: Current knowledge and research gaps.” Journal of Hazardous Materials Letters, 4: 100086. 10.1016/J.HAZL.2023.100086. [DOI] [Google Scholar]
  10. Desgens-Martin V, Li W, Medina T, and Keller AA 2023. ”Estimated Influent PFAS Loads to Wastewater Treatment Plants and Ambient Concentrations in Downstream Waterbodies: Case Study in Southern and Central California.” ACS ES&T Water, 3(8), 2219–2228. 10.1021/acsestwater.3c00022 [DOI] [Google Scholar]
  11. Glüge J, Scheringer M, Cousins IT, Dewitt JC, Goldenman G, Herzke D, Lohmann R, Ng CA, Trier X, and Wang Z 2020. “An overview of the uses of per- And polyfluoroalkyl substances (PFAS).” Environ Sci Process Impacts, 22 (12): 2345–2373. 10.1039/d0em00291g. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Gobelius L, Glimstedt L, Olsson J, Wiberg K, & Ahrens L 2023. “Mass flow of per- and polyfluoroalkyl substances (PFAS) in a Swedish municipal wastewater network and wastewater treatment plant.” Chemosphere, 336, 139182–139182. 10.1016/j.chemosphere.2023.139182 [DOI] [PubMed] [Google Scholar]
  13. Griffin EK, Aristizabal-Henao J, Timshina A, Ditz HL, Camacho CG, da Silva BF, Coker ES, Deliz Quiñones KY, Aufmuth J, & Bowden JA 2022. “Assessment of per- and polyfluoroalkyl substances (PFAS) in the Indian River Lagoon and Atlantic coast of Brevard County, FL, reveals distinct spatial clusters.” Chemosphere, 301, 134478. 10.1016/j.chemosphere.2022.134478 [DOI] [PubMed] [Google Scholar]
  14. Haimbaugh A, Meyer NM, Connell ML, Blount-Pacheco J., Tolofari D, Gonzalez G, Banerjee D, Norton J, Miller CJ, and Baker TR. 2024. “Environmental Exposure to Per- and Polyfluoroalkyl Substances (PFASs) and Reproductive Outcomes in the General Population: A Systematic Review of Epidemiological Studies.” Int. J. Environ. Res. Public Health, 24, 21(12), 1615; 10.3390/ijerph21121615 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Higgins CP, and Luthy RG 2006. “Sorption of perfluorinated surfactants on sediments.” Environ Sci Technol, 40 (23): 7251–7256. 10.1021/es061000n. [DOI] [PubMed] [Google Scholar]
  16. Kothawala DN, Köhler SJ, Östlund A, Wiberg K, and Ahrens L 2017. “Influence of dissolved organic matter concentration and composition on the removal efficiency of perfluoroalkyl substances (PFASs) during drinking water treatment.” Water Res, 121: 320–328. 10.1016/j.watres.2017.05.047. [DOI] [PubMed] [Google Scholar]
  17. Lakshminarasimman N, Gewurtz SB, Parker WJ, and Smyth SA 2021. “Removal and formation of perfluoroalkyl substances in Canadian sludge treatment systems – A mass balance approach.” Science of the Total Environment, 754. 10.1016/j.scitotenv.2020.142431. [DOI] [PubMed] [Google Scholar]
  18. Lenka SP, Kah M, and Padhye LP 2021. “A review of the occurrence, transformation, and removal of poly- and perfluoroalkyl substances (PFAS) in wastewater treatment plants.” Water Res. 199. 10.1016/j.watres.2021.117187 [DOI] [PubMed] [Google Scholar]
  19. Lin D, Méndez M, Paterson K, Wong A, Yee D, Sutton R, Houtz E, Cousins M, and Fono L 2024. “Residential Wastewater as a Major Source of Per- and Polyfluoroalkyl Substances to Municipal Wastewater.” ACS ES and T Water. American Chemical Society. 4.(11): 4847–4857. 10.1021/acsestwater.4c00507. [DOI] [Google Scholar]
  20. Llewellyn MJ, Griffin EK, Caspar RJ, Timshina AS, Bowden JA, Miller CJ, Baker BB, and Baker TR 2024. “Identification and quantification of novel per- and polyfluoroalkyl substances (PFAS) contamination in a Great Lakes urban-dominated watershed.” Science of the Total Environment, 941. 10.1016/j.scitotenv.2024.173325. [DOI] [PubMed] [Google Scholar]
  21. Loganathan BG, Sajwan KS, Sinclair E, Senthil Kumar K, & Kannan K 2007. ”Perfluoroalkyl sulfonates and perfluorocarboxylates in two wastewater treatment facilities in Kentucky and Georgia.” Water Research, 41(20), 4611–4620. 10.1016/j.watres.2007.06.045 [DOI] [PubMed] [Google Scholar]
  22. Miyani B,; Xavier Fonoll, Norton J, Asce M, Mehrotra A, and Xagoraraki I n.d. “SARS-CoV-2 in Detroit Wastewater.” Journal of Environmental Engineering,146(11). 10.1061/(ASCE)EE.1943. [DOI] [Google Scholar]
  23. Müller V, Kindness A, and Feldmann J 2023. “Fluorine mass balance analysis of PFAS in communal waters at a wastewater plant from Austria.” Water Res, 244: 120501. 10.1016/j.watres.2023.120501. [DOI] [PubMed] [Google Scholar]
  24. Nguyen HT, McLachlan MS, Tscharke B, Thai P, Braeunig J, Kaserzon S, O’Brien JW, and Mueller JF 2022. “Background release and potential point sources of per- and polyfluoroalkyl substances to municipal wastewater treatment plants across Australia.” Chemosphere, 293. 10.1016/j.chemosphere.2022.133657. [DOI] [PubMed] [Google Scholar]
  25. O’Connor N, Patch D, Noble D, Scott J, Koch I, Mumford KG, and Weber K 2023. “Forever no more: Complete mineralization of per- and polyfluoroalkyl substances (PFAS) using an optimized UV/sulfite/iodide system.” Science of the Total Environment, 888. 10.1016/j.scitotenv.2023.164137. [DOI] [PubMed] [Google Scholar]
  26. Pan CG, Liu YS, and Ying GG 2016. “Perfluoroalkyl substances (PFASs) in wastewater treatment plants and drinking water treatment plants: Removal efficiency and exposure risk.” Water Res, 106: 562–570. 10.1016/j.watres.2016.10.045. [DOI] [PubMed] [Google Scholar]
  27. Pétré MA, Salk KR, Stapleton HM, Ferguson PL, Tait G, Obenour DR, Knappe DRU, and Genereux DP 2022. “Per- and polyfluoroalkyl substances (PFAS) in river discharge: Modeling loads upstream and downstream of a PFAS manufacturing plant in the Cape Fear watershed, North Carolina.” Science of the Total Environment, 831. 10.1016/j.scitotenv.2022.154763. [DOI] [PubMed] [Google Scholar]
  28. Schultz MM, Higgins CP, Huset CA, Luthy RG, Barofsky DF, and Field JA 2006. “Fluorochemical mass flows in a municipal wastewater treatment facility.” Environ Sci Technol, 40 (23): 7350–7357. 10.1021/es061025m. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Sinclair E, and Kannan K 2006. “Mass loading and fate of perfluoroalkyl surfactants in wastewater treatment plants.” Environ Sci Technol, 40 (5): 1408–1414. 10.1021/es051798v. [DOI] [PubMed] [Google Scholar]
  30. Smith SJ, Lauria M, Higgins CP, Pennell KD, Blotevogel J, and Arp HPH 2024. “The Need to Include a Fluorine Mass Balance in the Development of Effective Technologies for PFAS Destruction.” Environ Sci Technol. American Chemical Society. 58(6): 2587–2590. 10.1021/acs.est.3c10617 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Tavasoli E, Luek JL, Malley JP, & Mouser PJ 2021. “Distribution and fate of per- and polyfluoroalkyl substances (PFAS) in wastewater treatment facilities”. Environmental Science: Processes & Impacts.23(6): 903–913 10.1039/d1em00032b [DOI] [PubMed] [Google Scholar]
  32. Thompson KA, Mortazavian S, Gonzalez DJ, Bott C, Hooper J, Schaefer CE, and Dickenson ERV 2022. “Poly- and Perfluoroalkyl Substances in Municipal Wastewater Treatment Plants in the United States: Seasonal Patterns and Meta-Analysis of Long-Term Trends and Average Concentrations.” ACS Environmental Science and Technology Water. 2(5):690–700. 10.1021/acsestwater.1c00377 [DOI] [Google Scholar]
  33. US EPA. 2021. “Draft Method 1633 Analysis of Per- and Polyfluoroalkyl Substances (PFAS) in Aqueous, Solid, Biosolids, and Tissue Samples by LC-MS/MS; DRAFT - August 2021”. Accessed September 18, 2025, https://www.epa.gov/system/files/documents/2021-09/method_1633_draft_aug-2021.pdf
  34. US EPA. 2022. “PFAS structures in DSSTox (updated August 2022)”. Accessed September 10, 2025, https://comptox.epa.gov/dashboard/chemical-lists/PFASSTRUCTV5
  35. US EPA. 2024. “Method 1633, Revision A Analysis of Per- and Polyfluoroalkyl Substances (PFAS) in Aqueous, Solid, Biosolids, and Tissue Samples by LC-MS/MS”. Accessed September 15, 2025, https://www.epa.gov/system/files/documents/2024-12/method-1633a-december-5-2024-508-compliant.pdf
  36. US EPA. 2025. “Per- and Polyfluoroalkyl Substances (PFAS) Final PFAS National Primary Drinking Water Regulation”. Accessed August 14, 2025, https://www.epa.gov/sdwa/and-polyfluoroalkyl-substances-pfas.
  37. Wang Z, Buser AM, Cousins IT, Demattio S, Drost W, Johansson O, Ohno K, Patlewicz G, Richard AM, Walker GW, White GS, and Leinala E 2021. “A New OECD Definition for Per- And Polyfluoroalkyl Substances.” Environ Sci Technol, 55(23): 15575–15578. 10.1021/acs.est.1c06896 [DOI] [PubMed] [Google Scholar]
  38. Winchell LJ, Ross JJ, Wells MJM, Fonoll X, Norton JW, and Bell KY 2021. “Per- and polyfluoroalkyl substances thermal destruction at water resource recovery facilities: A state of the science review.” Water Environment Research, 93(6):826–843. 10.1002/wer.1483 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Xia C, Capozzi SL, Romanak KA, Lehman DC, Dove A, Richardson V, Greenberg T, McGoldrick D, and Venier M 2024. “The Ins and Outs of Per- and Polyfluoroalkyl Substances in the Great Lakes: The Role of Atmospheric Deposition.” Environ Sci Technol, 58 (21): 9303–9313. 10.1021/acs.est.3c10098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Xu B, Liu S, Zhou JL, Zheng C, Weifeng J, Chen B, Zhang T, and Qiu W 2021. “PFAS and their substitutes in groundwater: Occurrence, transformation and remediation.” J Hazard Mater, 412. 10.1016/J.JHAZMAT.2021.125159. [DOI] [PubMed] [Google Scholar]
  41. Zaggia A, Conte L, Falletti L, Fant M, and Chiorboli A 2016. “Use of strong anion exchange resins for the removal of perfluoroalkylated substances from contaminated drinking water in batch and continuous pilot plants.” Water Res, 91: 137–146. 10.1016/j.watres.2015.12.039. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental
NIHMS2199459-supplement-Supplemental.docx (66KB, docx)

Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. Some or all data, models, or code generated or used during the study are available in a repository online.

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