Exploring the Evolution of Organofluorine-Containing Compounds during Simulated Photolithography Experiments.

One potential source of per- and polyfluoroalkyl substances (PFASs) in electronics fabrication wastewater are the organofluorine-containing compounds used in photolithography materials such as photoresists and top antireflective coatings (TARCs). However, the exact identities of these constituents are unknown and transformation reactions that may occur during photolithography may result in the formation of unknown or unexpected PFASs. To address this knowledge gap, we acquired five commercially relevant photolithography materials, characterized the occurrence of organofluorine-containing compounds in each material, and performed simulated photolithography experiments to stimulate any potential transformation reactions. We found that photoresists and TARCs have total fluorine (TF) concentrations in the g L-1 range, similar to the levels of other industrial and commercial products. However, the target and suspect PFASs present in these materials can only explain up to 20% of the TF in a material. We evaluated wastewater samples collected after simulated photolithography experiments and used a mass balance approach to assess the extent of transformations. Although a number of target, suspect, and nontarget PFASs were identified in the wastewater samples, the extent of transformation was limited and the fluorine contained in the PFASs could not explain more than an additional 1% of the TF in the photolithography materials.

Daily Monitoring at a Full-Scale Wastewater Treatment Plant Reveals Temporally Variable Micropollutant Biotransformations.

Despite decades of micropollutant (MP) monitoring at wastewater treatment plants (WWTPs), we lack a fundamental understanding of the time-varying metabolic processes driving MP biotransformations. To address this knowledge gap, we collected 24-h composite samples from the influent and effluent of the conventional activated sludge (CAS) process at a WWTP over 14 consecutive days. We used liquid chromatography and high-resolution mass spectrometry to (i) quantify 184 MPs in the influent and effluent of the CAS process; (ii) characterize temporal dynamics of MP removal and biotransformation rate constants; and (iii) discover biotransformations linked to temporally variable MP biotransformation rate constants. We measured 120 MPs in at least one sample and 66 MPs in every sample. There were 24 MPs exhibiting temporally variable removal throughout the sampling campaign. We used hierarchical clustering analysis to reveal four temporal trends in biotransformation rate constants and found MPs with specific structural features co-located in the four clusters. We screened our HRMS acquisitions for evidence of specific biotransformations linked to structural features among the 24 MPs. Our analyses reveal that alcohol oxidations, monohydroxylations at secondary or tertiary aliphatic carbons, dihydroxylations of vic-unsubstituted rings, and monohydroxylations at unsubstituted rings are biotransformations that exhibit variability on daily timescales.

Target and Suspect Screening Integrated with Machine Learning to Discover Per- and Polyfluoroalkyl Substance Source Fingerprints.

This study elucidates per- and polyfluoroalkyl substance (PFAS) fingerprints for specific PFAS source types. Ninety-two samples were collected from aqueous film-forming foam impacted groundwater (AFFF-GW), landfill leachate, biosolids leachate, municipal wastewater treatment plant effluent (WWTP), and wastewater effluent from the pulp and paper and power generation industries. High-resolution mass spectrometry operated with electrospray ionization in negative mode was used to quantify up to 50 target PFASs and screen and semi-quantify up to 2,266 suspect PFASs in each sample. Machine learning classifiers were used to identify PFASs that were diagnostic of each source type. Four C5-C7 perfluoroalkyl acids and one suspect PFAS (trihydrogen-substituted fluoroethernonanoic acid) were diagnostic of AFFF-GW. Two target PFASs (5:3 and 6:2 fluorotelomer carboxylic acids) and two suspect PFASs (4:2 fluorotelomer-thia-acetic acid and N-methylperfluoropropane sulfonamido acetic acid) were diagnostic of landfill leachate. Biosolids leachates were best classified along with landfill leachates and N-methyl and N-ethyl perfluorooctane sulfonamido acetic acid assisted in that classification. WWTP, pulp and paper, and power generation samples contained few target PFASs, but fipronil (a fluorinated insecticide) was diagnostic of WWTP samples. Our results provide PFAS fingerprints for known sources and identify target and suspect PFASs that can be used for source allocation.

Trace Organic Contaminant Removal from Municipal Wastewater by Styrenic ß-Cyclodextrin Polymers.

Trace organic contaminants (TrOCs) present major removal challenges for wastewater treatment. TrOCs, such as perfluoroalkyl and polyfluoroalkyl substances (PFAS), are associated with chronic toxicity at ng L-1 exposure levels and should be removed from wastewater to enable safe reuse and release of treated effluents. Established adsorbents, such as granular activated carbon (GAC), exhibit variable TrOC removal and fouling by wastewater constituents. These shortcomings motivate the development of selective novel adsorbents that also maintain robust performance in wastewater. Cross-linked ß-cyclodextrin (ß-CD) polymers are promising adsorbents with demonstrated TrOC removal efficacy. Here, we report a simplified and potentially scalable synthesis of a porous polymer composed of styrene-linked ß-CD and cationic ammonium groups. Batch adsorption experiments demonstrate that the polymer is a selective adsorbent exhibiting complete removal for six out of 13 contaminants with less adsorption inhibition than GAC in wastewater. The polymer also exhibits faster adsorption kinetics than GAC and ion exchange (IX) resin, higher adsorption affinity for PFAS than GAC, and is regenerable by solvent wash. Rapid small-scale column tests show that the polymer exhibits later breakthrough times compared to GAC and IX resin. These results demonstrate the potential for ß-CD polymers to remediate TrOCs from complex water matrices.

More movement with manure: increased mobility of erythromycin through agricultural soil in the presence of manure.

Antibiotic residues in the environment threaten soil and aquatic organisms and human and livestock health through the building of antimicrobial resistance. Manure spreading associated with animal agriculture is one source of environmental antibiotic residues. To better understand the risk of contamination, we studied the adsorption of erythromycin, a model macrolide antibiotic used across human and animal medicine. We conducted a series of equilibrium batch experiments to determine the kinetics and extent of adsorption and a continuous-flow column adsorption experiment to observe non-equilibrium adsorption patterns. We determined that the adsorption equilibration time to soil was approximately 72 h in our batch experiments. Erythromycin adsorbed to soil relatively strongly (K = 8.01 × 10-2 L/mg; qmax = 1.53 × 10-3 mg/mg), adsorbed to the soil in the presence of manure with less affinity (K = 1.99 × 10-4 L/mg) at a soil: manure ratio of 10:1 by mass, and did not adsorb to manure across the solid ratios tested. We observed multi-phased adsorption of erythromycin to the soil during the non-equilibrium column experiment, which was largely absent from the treatments with both soil and manure present. These results suggest that erythromycin is more mobile in the environment when introduced with manure, which is likely the largest source of agriculturally sourced environmental antibiotics.

Identifying Functional Groups that Determine Rates of Micropollutant Biotransformations Performed by Wastewater Microbial Communities.

The goal of this research was to identify functional groups that determine rates of micropollutant (MP) biotransformations performed by wastewater microbial communities. To meet this goal, we performed a series of incubation experiments seeded with four independent wastewater microbial communities and spiked them with a mixture of 40 structurally diverse MPs. We collected samples over time and used high-resolution mass spectrometry to estimate biotransformation rate constants for each MP in each experiment and to propose structures of 46 biotransformation products. We then developed random forest models to classify the biotransformation rate constants based on the presence of specific functional groups or observed biotransformations. We extracted classification importance metrics from each random forest model and compared them across wastewater microbial communities. Our analysis revealed 30 functional groups that we define as either biotransformation promoters, biotransformation inhibitors, structural features that can be biotransformed based on uncharacterized features of the wastewater microbial community, or structural features that are not rate-determining. Our experimental data and analysis provide novel insights into MP biotransformations that can be used to more accurately predict MP biotransformations or to inform the design of new chemical products that may be more readily biodegradable during wastewater treatment.

Rapid removal of organic micropollutants from water by a porous ß-cyclodextrin polymer.

The global occurrence in water resources of organic micropollutants, such as pesticides and pharmaceuticals, has raised concerns about potential negative effects on aquatic ecosystems and human health. Activated carbons are the most widespread adsorbent materials used to remove organic pollutants from water but they have several deficiencies, including slow pollutant uptake (of the order of hours) and poor removal of many relatively hydrophilic micropollutants. Furthermore, regenerating spent activated carbon is energy intensive (requiring heating to 500-900 degrees Celsius) and does not fully restore performance. Insoluble polymers of ß-cyclodextrin, an inexpensive, sustainably produced macrocycle of glucose, are likewise of interest for removing micropollutants from water by means of adsorption. ß-cyclodextrin is known to encapsulate pollutants to form well-defined host-guest complexes, but until now cross-linked ß-cyclodextrin polymers have had low surface areas and poor removal performance compared to conventional activated carbons. Here we crosslink ß-cyclodextrin with rigid aromatic groups, providing a high-surface-area, mesoporous polymer of ß-cyclodextrin. It rapidly sequesters a variety of organic micropollutants with adsorption rate constants 15 to 200 times greater than those of activated carbons and non-porous ß-cyclodextrin adsorbent materials. In addition, the polymer can be regenerated several times using a mild washing procedure with no loss in performance. Finally, the polymer outperformed a leading activated carbon for the rapid removal of a complex mixture of organic micropollutants at environmentally relevant concentrations. These findings demonstrate the promise of porous cyclodextrin-based polymers for rapid, flow-through water treatment.

Polymerized Molecular Receptors as Adsorbents to Remove Micropollutants from Water.

Organic micropollutants (MPs) are increasing in number and concentration in water systems as a result of human activities. Often from human origin, these micropollutants build up in the environment because organisms lack the mechanisms to metabolize these substances, which cause negative health, ecological, and economic effects. Adsorption-based remediation processes for these compounds often rely on activated carbon materials. However, activated carbons are ineffective against certain MPs, exhibit low removal efficiencies in the presence of common aqueous matrix constituents, and require energy-intensive activation and regeneration processes. To overcome the deficiencies of traditional technologies, novel adsorbents based on molecular receptors offer promising alternative solutions. This Account describes the recent development of polymer adsorbents based on molecular receptors for removing trace organic chemicals from water. Polymer networks based on molecular receptors have high binding affinities for many MPs but, unlike activated carbons, have a specific molecule-binding mechanism that prevents these polymers from being fouled by matrix constituents such as natural organic matter. The size and hydrophobic pocket of the ß-cyclodextrin receptor preferentially adsorbs target molecules such as organic micropollutants in the presence of matrix constituents, and the nature of the cross-linker tunes the binding affinity and selectivity of the adsorbent for specific classes of MPs, including those of varying charge and hydrophobicity. ß-cyclodextrin polymers also exhibit rapid adsorption kinetics and are easily regenerated. This Account details ß-cyclodextrin polymers made with three different cross-linkers, including a polymer that is postsynthetically transformed from a negatively charged polymer to a positively charged polymer to invert the polymer's micropollutant adsorption profile. Morphological constraints have so far limited these cross-linked polymers' ability to be used in commercial applications, but two methods to create larger and more uniformly sized particles for use in flow-through applications are described here. ß-Cyclodextrin polymers are useful for trapping organic micropollutants such as bisphenol A, perfluorooctanoic acid, and many kinds of pharmaceuticals and pesticides, but their binding pockets are too large to capture micropollutants that are small or of high polarity. Other molecular receptors such as resorcinarene cavitands can target lower-molecular-weight MPs, including halomethane disinfection byproducts and industrial solvents, that are not bound strongly by ß-cyclodextrins. These materials demonstrate the potential of expanding the library of polymers based on molecular receptors. Overall, these emerging adsorbents show promise for the removal of legacy and emerging MPs from water, as well as the ability to rationally tune the adsorbent's structure to target the most persistent and toxic MPs.

Target and Nontarget Analysis of Per- and Polyfluoralkyl Substances in Wastewater from Electronics Fabrication Facilities.

The goals of this study were to improve our understanding of the types of per- and polyfluoroalkyl substances (PFASs) that occur in wastewater from electronics fabrication facilities (fabs) and to assess the relative concentrations of PFAS species. We collected wastewater samples from three fabs in the United States, analyzed the samples by means of high-resolution mass spectrometry, and implemented complementary target and nontarget analyses. Twelve of 25 target PFASs were quantified in at least one sample, and five perfluorocarboxylates and perfluorobutane sulfonate (PFBS) were quantified in all samples. PFBS was quantified at the highest concentration among the samples (8040 ng L-1) and we expect that its presence is related to the use of photoacid generators during photolithography. The sum concentrations of the target PFASs in the diluted discharge samples from each fab were 623, 394, and 376 ng L-1. Nontarget analysis revealed the presence of 41 homologous series of PFASs comprising 133 homologues. We proposed structures for 15 homologous series of nontarget PFASs, six of which are reported here for the first time. Using an approach for semiquantification of nontarget PFASs, we estimated that the sum concentrations of target and nontarget PFASs in the diluted discharge samples from each fab were 1490, 78 700, and 2170 ng L-1. Our findings are essential for developing alternative photolithography chemicals or informing the implementation of advanced wastewater treatment technologies at fabs.

Environmental Source Tracking of Per- and Polyfluoroalkyl Substances within a Forensic Context: Current and Future Techniques.

The source tracking of per- and polyfluoroalkyl substances (PFASs) is a new and increasingly necessary subfield within environmental forensics. We define PFAS source tracking as the accurate characterization and differentiation of multiple sources contributing to PFAS contamination in the environment. PFAS source tracking should employ analytical measurements, multivariate analyses, and an understanding of PFAS fate and transport within the framework of a conceptual site model. Converging lines of evidence used to differentiate PFAS sources include: identification of PFASs strongly associated with unique sources; the ratios of PFAS homologues, classes, and isomers at a contaminated site; and a site's hydrogeochemical conditions. As the field of PFAS source tracking progresses, the development of new PFAS analytical standards and the wider availability of high-resolution mass spectral data will enhance currently available analytical capabilities. In addition, multivariate computational tools, including unsupervised (i.e., exploratory) and supervised (i.e., predictive) machine learning techniques, may lead to novel insights that define a targeted list of PFASs that will be useful for environmental PFAS source tracking. In this Perspective, we identify the current tools available and principal developments necessary to enable greater confidence in environmental source tracking to identify and apportion PFAS sources.

Exploring the Specificity of Extracellular Wastewater Peptidases to Improve the Design of Sustainable Peptide-Based Antibiotics.

New antimicrobial peptides are emerging as promising alternatives to conventional antibiotics because of their specificity for target pathogens and their potential to be rapidly hydrolyzed (i.e., inactivated) by extracellular peptidases during biological wastewater treatment, thereby limiting the emergence and propagation of antibiotic resistance in the environment. However, little is known about the specificity of extracellular peptidases derived from wastewater microbial communities, which is a major impediment for the design of sustainable peptide-based antibiotics that can be hydrolyzed by wastewater peptidases. We used a set of natural peptides to explore the specificity of dissolved extracellular wastewater peptidases. We found that enzyme-catalyzed hydrolysis occurred at specific sites and that a subset of these hydrolyses was conserved across enzyme pools derived from three independent wastewater microbial communities. An analysis of the amino-acid residues flanking the hydrolyzed bonds revealed a set of residue motifs that were linked to enzyme-catalyzed hydrolysis and are therefore candidates for incorporation into new and sustainable peptide-based antibiotics.

ß-Cyclodextrin Polymers with Different Cross-Linkers and Ion-Exchange Resins Exhibit Variable Adsorption of Anionic, Zwitterionic, and Nonionic PFASs.

Per- and polyfluoroalkyl substances (PFASs) occur in groundwater as mixtures of anionic, cationic, zwitterionic, and nonionic species, although few remediation technologies have been evaluated to assess the removal of different types of PFASs. In this study, we evaluated the performance of three ß-cyclodextrin polymers (CDPs), an anion-exchange (AE) resin, and a cation-exchange (CE) resin for the removal of anionic, zwitterionic, and nonionic PFASs from water. We found that a CDP with a negative surface charge rapidly removes all zwitterionic PFASs with log KD values ranging between 2.4 and 3.1, and the CE resin rapidly removes two zwitterionic PFASs with log KD values of 1.8 and 1.9. The CDPs with a positive surface charge rapidly remove all anionic PFASs with log KD values between 2.7 and 4.1, and the AE resin removes all anionic PFASs relatively slowly with log KD values between 2.0 and 2.3. All adsorbents exhibited variable removal of the nonionic PFASs and some adsorption inhibition at higher pH values and in the presence of groundwater matrix constituents. Our findings provide insight into how adsorbents can be combined to remediate groundwater contaminated with complex mixtures of different types of PFASs.

Impact of Hurricane Maria on Drinking Water Quality in Puerto Rico.

This study performed a comprehensive assessment of the impact of Hurricane Maria (HM) on drinking water quality in Puerto Rico (PR) by integrating targeted chemical analysis of both inorganic (18 trace elements) and organic trace pollutants (200 micropollutants) with high-throughput quantitative toxicogenomics and in vitro biomarkers-based toxicity assays. Average concentrations of 14 detected trace elements and 20 organic micropollutants showed elevation after HM. Arsenic, sucralose, perfluorooctanoic acid (PFOA), atrazine-2-hydroxy, benzotriazole, acesulfame, and prometon were at significantly (p < 0.05) higher levels in the post-HM than in the pre-HM samples. Thirteen micropollutants, including four pesticides, were only detected in posthurricane samples. Spatial comparison showed higher pollutant and toxicity levels in the samples from northern PR (where eight Superfund sites are located) than in those from southern PR. Distinctive pathway-specific molecular toxicity fingerprints for water extracts before and after HM and at different locations revealed changes in toxicity nature that likely resulted from the impact of HM on drinking water composition. Correlation analysis and Maximum Cumulative Ratio assessment suggested that metals (i.e., arsenic) and PFOA were the top ranked pollutants that have the potential to cause increased risk after HM, providing a possible direction for future water resource management and epidemiological studies.

Fall Creek Monitoring Station: Using Environmental Covariates To Predict Micropollutant Dynamics and Peak Events in Surface Water Systems.

This research aimed to further our understanding of how environmental processes control micropollutant dynamics in surface water systems as a means to predict peak concentration events and inform intermittent sampling strategies. We characterized micropollutant concentrations in daily composite samples from the Fall Creek Monitoring Station over 18 months. These data were compiled alongside environmental covariates, including daily measurements of weather, hydrology, and water quality parameters, to generate a novel data set with high temporal resolution. We evaluated the temporal trends of several representative micropollutants, along with cumulative metrics of overall micropollutant contamination, by means of multivariable analyses to determine which combination of covariates best predicts micropollutant dynamics and peak events. Peak events of agriculture-derived micropollutants were best predicted by positive associations with turbidity and UV254 absorbance and negative associations with baseflow index. Peak events of wastewater-derived micropollutants were best predicted by positive associations with alkalinity and negative associations with streamflow rate. We demonstrate that these predictors can be used to inform intermittent sampling strategies aimed at capturing peak events, and we generalize the approach so that it could be applied in other watersheds. Finally, we demonstrate how our approach can be used to contextualize micropollutant data derived from infrequent grab samples.

Fall Creek Monitoring Station: Highly Resolved Temporal Sampling to Prioritize the Identification of Nontarget Micropollutants in a Small Stream.

The goal of this research was to comprehensively characterize the occurrence and temporal dynamics of target and nontarget micropollutants in a small stream. We established the Fall Creek Monitoring Station in March 2017 and collected daily composite samples for one year. We measured water samples by means of high-resolution mass spectrometry and developed and optimized a postacquisition data processing workflow to screen for 162 target micropollutants and group all mass spectral (MS) features into temporal profiles. We used hierarchical clustering analysis to prioritize nontarget MS features based their similarity to target micropollutant profiles and developed a high-throughput pipeline to elucidate the structures of prioritized nontarget MS features. Our analyses resulted in the identification of 31 target micropollutants and 59 nontarget micropollutants with varying levels of confidence. Temporal profiles of the 90 identified micropollutants revealed unexpected concentration-discharge relationships that depended on the source of the micropollutant and hydrological features of the watershed. Several of the nontarget micropollutants have not been previously reported including pharmaceutical metabolites, rubber vulcanization accelerators, plasticizers, and flame retardants. Our data provide novel insights on the temporal dynamics of micropollutant occurrence in small streams. Further, our approach to nontarget analysis is general and not restricted to highly resolved temporal data acquisitions or samples collected from surface water systems.

Reduction of a Tetrafluoroterephthalonitrile-ß-Cyclodextrin Polymer to Remove Anionic Micropollutants and Perfluorinated Alkyl Substances from Water.

Organic micropollutants (MPs) are anthropogenic substances that contaminate water resources at trace concentrations. Many MPs, including per- and polyfluorinated alkyl substances (PFASs), have come under increased scrutiny because of their environmental persistence and association with various health problems. A ß-cyclodextrin polymer linked with tetrafluoroterephthalonitrile (TFN-CDP) has high affinity for cationic and many neutral MPs from contaminated water because of anionic groups incorporated during the polymerization. But TFN-CDP does not bind many anionic MPs strongly, including anionic PFASs. To address this shortcoming, we reduced the nitrile groups in TFN-CDP to primary amines, which reverses its affinity towards charged MPs. TFN-CDP exhibits adsorption distribution coefficients (log KD values) of 2-3 for cationic MPs and -0.5-1.5 for anionic MPs, whereas the reduced TFN-CDP exhibits log KD values of -0.5-1.5 for cationic MPs and 2-4 for anionic MPs, with especially high affinity towards anionic PFASs. Kinetic studies of the removal of 10 anionic PFASs at environmentally relevant concentrations showed 80-98 % removal of all contaminants after 30 min and was superior to commercial granular activated carbon. These findings demonstrate the scope and tunability of CD-based adsorbents derived from a single polymerization and the promise of novel adsorbents constructed from molecular receptors.

Removal of GenX and Perfluorinated Alkyl Substances from Water by Amine-Functionalized Covalent Organic Frameworks.

Per- and polyfluorinated alkyl substances (PFAS), such as perfluorooctanoic acid (PFOA), perfluorooctanesulfonate (PFOS), and ammonium perfluoro-2-propoxypropionate (GenX), contaminate ground and surface waters throughout the world. The cost and performance limitations of current PFAS removal technologies motivate efforts to develop selective and high-affinity adsorbents. Covalent organic frameworks (COFs) are unexplored yet promising adsorbents because of their high surface area and tunable pore sizes. Here we show that imine-linked two-dimensional (2D) COFs bearing primary amines adsorb GenX rapidly at environmentally relevant concentrations. COFs with partial amine incorporation showed the highest capacity and fastest removal, suggesting that the synergistic combination of the polar group and hydrophobic surfaces are responsible for GenX binding. A COF with 28% amine loading also removed more than 90% of 12 out of 13 PFAS. These results demonstrate the promise of COFs for PFAS removal and suggest design criteria for maximizing adsorbent performance.

Widespread Micropollutant Monitoring in the Hudson River Estuary Reveals Spatiotemporal Micropollutant Clusters and Their Sources.

The objective of this study was to identify sources of micropollutants in the Hudson River Estuary (HRE). We collected 127 grab samples at 17 sites along the HRE over 2 years and screened for up to 200 micropollutants. We quantified 168 of the micropollutants in at least one of the samples. Atrazine, gabapentin, metolachlor, and sucralose were measured in every sample. We used data-driven unsupervised methods to cluster the micropollutants on the basis of their spatiotemporal occurrence and normalized-concentration patterns. Three major clusters of micropollutants were identified: ubiquitous and mixed-use (core micropollutants), sourced from sewage treatment plant outfalls (STP micropollutants), and derived from diffuse upstream sources (diffuse micropollutants). Each of these clusters was further refined into subclusters that were linked to specific sources on the basis of relationships identified through geospatial analysis of watershed features. Evaluation of cumulative loadings of each subcluster revealed that the Mohawk River and Rondout Creek are major contributors of most core micropollutants and STP micropollutants and the upper HRE is a major contributor of diffuse micropollutants. These data provide the first comprehensive evaluation of micropollutants in the HRE and define distinct spatiotemporal micropollutant clusters that are linked to sources and conserved across surface water systems around the world.

ß-Cyclodextrin Polymer Network Sequesters Perfluorooctanoic Acid at Environmentally Relevant Concentrations.

Per- and poly fluorinated alkyl substances (PFASs), notably perfluorooctanoic acid (PFOA), contaminate many ground and surface waters and are environmentally persistent. The performance limitations of existing remediation methods motivate efforts to develop effective adsorbents. Here we report a ß-cyclodextrin (ß-CD)-based polymer network with higher affinity for PFOA compared to powdered activated carbon, along with comparable capacity and kinetics. The ß-CD polymer reduces PFOA concentrations from 1 µg L-1 to <10 ng L-1, at least 7 times lower than the 2016 U.S. EPA advisory level (70 ng L-1), and was regenerated and reused multiple times by washing with MeOH. The performance of the polymer is unaffected by humic acid, a component of natural organic matter that fouls activated carbons. These results are promising for treating PFOA-contaminated water and demonstrate the versatility of ß-CD-based adsorbents.