Search

Suspect screening is a valuable tool for characterizing per- and polyfluoroalkyl substances (PFASs) in environmental media. Although a variety of data mining tools have been developed and applied for suspect screening of PFAS, few suspect screening workflows have undergone a comprehensive performance evaluation or optimization. The goals of this research were to: (1) evaluate and optimize three independent suspect screening workflows for the detection of PFASs in water samples; and (2) apply the optimized suspect screening workflows to an environmental sample to determine the extent to which suspect screening results converge. We evaluated and optimized suspect screening workflows using Compound Discoverer v3.2, enviMass v4.2, and FluoroMatch v2.4 using test samples containing 33 target PFASs. The average sensitivity (Sen) and selectivity (Sel) for each workflow across the test samples was: Compound Discoverer Sen = 71%, Sel = 85%; enviMass Sen = 89%, Sel = 80%; FluoroMatch Sen = 51%, Sel = 82%. We then applied the optimized workflows to a contaminated groundwater sample containing an unknown number of PFASs. Each workflow managed to annotate unique PFASs that were not annotated by the other workflows including 2 by Compound Discoverer and 19 each by enviMass and FluoroMatch. Thirty-two enviMass hits and 28 of the Compound Discoverer and FluoroMatch hits were annotated by at least one of the other workflows. Sixteen PFASs were annotated by all three of the optimized workflows. This work provides a basis for conducting suspect screening for PFASs that will lead to more consistent reporting of suspect screening data. [ABSTRACT FROM AUTHOR]

The contamination of surface water and ground water by human activities, such as fossil fuel extraction and agriculture, can be difficult to assess due to incomplete knowledge of the chemicals and chemistry involved. This is particularly true for the potential contamination of drinking water by nearby extraction of oil and/or gas from wells completed by hydraulic fracturing. A case that has attracted considerable attention is unconventional natural gas extraction in Susquehanna County, Pennsylvania, particularly around Dimock, Pennsylvania. We analyzed surface water and groundwater samples collected throughout Susquehanna County with complementary biological assays and high-resolution mass spectrometry. We found that Ah receptor activity was associated with proximity to impaired gas wells. We also identified certain chemicals, including disclosed hydraulic fracturing fluid additives, in samples that were either in close proximity to impaired gas wells or that exhibited a biological effect. In addition to correlations with drilling activity, the biological assays and high-resolution mass spectrometry detected substances that arose from other anthropogenic sources. Our complementary approach provides a more comprehensive picture of water quality by considering both biological effects and a broad screening for chemical contaminants. [ABSTRACT FROM AUTHOR]

Complex mixtures of low concentrations of organic micropollutants are commonly found in rivers and streams, but their relationship to the structure of native bacterial communities that underlie critical ecological goods and services in these systems is poorly understood. To address this knowledge gap, we used correlation-based network analysis to explore co-occurrence patterns between measured micropollutant concentrations and the associated surface water and sediment bacterial communities in a restored riparian zone of the Des Plaines River (DPR) in Illinois that is impacted by both wastewater treatment plant (WWTP) effluent and agricultural runoff. Over a two year period, we collected 55 grab samples at 11 sites along the DPR and one of its tributaries (48 surface water samples) and from WWTP effluent (7 samples), and screened for 126 organic micropollutants. In parallel, we used high-throughput 16S rRNA gene amplicon sequencing to characterize the bacterial community in sediment and surface water. Our results revealed quantifiable levels of 102 micropollutants in at least one surface water or WWTP effluent sample, 85 of which were detected in at least one surface water sample. While micropollutants were temporally and spatially variable in terms of both presence and concentration, 21 micropollutants were measured in over 75% of the 48 surface water samples. 16S rRNA gene sequencing documented diverse bacterial communities along the DPR transect, with highly distinct community structures observed in sediment and water. Bacterial community structure in surface water, but not in sediment, was significantly associated with concentrations of micropollutants, based on a Mantel test. Correlation-based network analyses revealed diverse strong and significant co-occurrence and co-exclusion patterns between specific bacterial OTUs and both micropollutant groups (defined based on k-means clustering on chemical substructure) and individual micropollutants. Significantly more associations were documented between micropollutants and bacterial taxa in the water compared to the sediment microbiomes. Taken together, our results document a significant link between complex mixtures of micropollutants commonly found in aquatic systems and associated bacterial community structure. Furthermore, our results suggest that micropollutants may exert a more significant impact on water-associated than on sediment-associated bacterial taxa. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing (HF) operations utilize millions of gallons of water amended with chemical additives including biocides, corrosion inhibitors, and surfactants. Fluids injected into the subsurface return to the surface as wastewaters, which contain a complex mixture of additives, transformation products, and geogenic chemical constituents. Quantitative analytical methods are needed to evaluate wastewater disposal alternatives or to conduct adequate exposure assessments. However, our narrow understanding of how matrix effects change the ionization efficiency of target analytes limits the quantitative analysis of polar to semi-polar HF additives by means of liquid chromatography electrospray ionization mass spectrometry (LC-ESI-MS). To address this limitation, we explored the ways in which matrix chemistry influences the ionization of seventeen priority HF additives with a modified standard addition approach. We then used the data to quantify HF additives in HF-associated fluids. Our results demonstrate that HF additives generally exhibit suppressed ionization in HF-associated fluids, though HF additives that predominantly form sodiated adducts exhibit significantly enhanced ionization in produced water samples, which is largely the result of adduct shifting. In a preliminary screening, we identified glutaraldehyde and 2-butoxyethanol along with homologues of benzalkonium chloride (ADBAC), polyethylene glycol (PEG), and polypropylene glycol (PPG) in HF-associated fluids. We then used matrix recovery factors to provide the first quantitative measurements of individual homologues of ADBAC, PEG, and PPG in HF-associated fluids ranging from mg L−1 levels in hydraulic fracturing fluid to low μg L−1 levels in PW samples. Our approach is generalizable across sample types and shale formations and yields important data to evaluate wastewater disposal alternatives or implement exposure assessments. [ABSTRACT FROM AUTHOR]

Upon partial degradation of polar organic micropollutants during activated sludge treatment, transformation products (TPs) may be formed that enter the aquatic environment in the treated effluent. However, TPs are rarely considered in prospective environmental risk assessments of wastewater-relevant compound classes such as pharmaceuticals and biocides. Here, we suggest and evaluate a tiered procedure, which includes a fast initial screening step based on high resolution tandem mass spectrometry (HR-MS/MS) and a subsequent confirmatory quantitative analysis, that should facilitate consideration of TPs formed during activated sludge treatment in the exposure assessment of micropollutants. At the first tier, potential biotransformation product structures of seven pharmaceuticals (atenolol, bezafibrate, ketoprofen, metoprolol, ranitidine, valsartan, and venlafaxine) and one biocide (carbendazim) were assembled using computer-based biotransformation pathway prediction and known human metabolites. These target structures were screened for in sludge-seeded batch reactors using HR-MS/MS. The 12 TPs found to form in the batch experiments were then searched for in the effluents of two full-scale, municipal wastewater treatment plants (WWTPs) to confirm the environmental representativeness of this first tier. At the second tier, experiments with the same sludge-seeded batch reactors were carried out to acquire kinetic data for major TPs that were then used as input parameters into a cascaded steady-state completely-stirred tank reactor (CSTR) model for predicting TP effluent concentrations. Predicted effluent concentrations of four parent compounds and their three major TPs were corroborated by comparison to 3-day average influent and secondary effluent mass flows from one municipal WWTP. CSTR model-predicted secondary effluent mass flows agreed within a factor of two with measured mass flows and confidence intervals of predicted and measured mass flows overlapped in all cases. The observed agreement suggests that the combination of batch-determined transformation kinetics with a simple WWTP model may be suitable for estimating aquatic exposure to TPs formed during activated sludge treatment. Overall, we recommend the tiered procedure as a realistic and cost-effective approach to include consideration of TPs of wastewater-relevant compounds into exposure assessment in the context of prospective chemical risk assessment.