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Crumb rubber generated from end-of-life tires (ELTs) poses a threat to environmental and human health based on its widespread use. Of particular concern is the use of ELT crumb rubber as infill for artificial turf fields, as people are unknowingly exposed to complex mixtures of chemicals when playing on these fields. Additionally, there is concern regarding transport of rubber-related chemicals from artificial turf into the environment. However, existing knowledge does not fully elucidate the chemical profile, transformation products, and transport pathways of artificial turf crumb rubber across different ages. To address these knowledge gaps, we utilized a multi-faceted approach that consisted of targeted quantitation, chemical profiling, and suspect screening via ultra-high performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). We collected and processed 3 tire and 11 artificial turf crumb rubber samples via solvent extraction, leaching, and a bioaccessibility-based extraction. Nineteen rubber-derived chemicals were quantified using parallel reaction monitoring and isotope dilution techniques. In solvent extracts, the most abundant analytes were 1,3-diphenylguanidine (0.18-1200 μg g -1 ), N -(1,3-dimethylbutyl)- N '-phenyl- p -phenylenediamine (6PPD, 0.16-720 μg g -1 ), 2-mercaptobenzothiazole (0.47-140 μg g -1 ), and benzothiazole (0.84-150 μg g -1 ). Chemical profiling assessed changes in sample diversity, abundance, polarity, and molecular mass. Suspect screening identified 81 compounds with different confidence levels (16 at level 1, 53 with level 2, 7 at level 3, and 5 at level 4). The formation rate of transformation products and clustering analysis results identified time-based trends in artificial turf field samples. We found that the first two years of aging may be critical for the potential environmental impact of artificial turf fields. Our analysis provides insight into the chemical complexity of artificial turf crumb rubber samples ranging from 0-14 years in age.

In urban to peri-urban watersheds such as those surrounding San Francisco Bay, stormwater runoff is a major pathway by which contaminants enter aquatic ecosystems. We evaluated the occurrence of 154 organic contaminants via liquid chromatography coupled to tandem mass spectrometry, including organophosphate esters (OPEs), bisphenols, per- and polyfluoroalkyl substances (PFASs), and a suite of novel urban stormwater tracers (SWCECs; i.e. , vehicle-derived chemicals, pesticides, pharmaceuticals/personal care products, benzothiazoles/benzotriazoles). Time-averaged composite sampling focused on storms in highly developed watersheds over four wet seasons, with complementary sampling in less-urban reference watersheds, near-shore estuarine sites, and the open Bay. Of the targeted contaminants, 68 (21 SWCECs, 29 OPEs, 3 bisphenols, 15 PFASs) were detected in ≥10 of 26 urban stormwater samples. Median concentrations exceeded 500 ng L -1 for 1,3-diphenylguanidine, hexa(methoxymethyl)melamine, and caffeine, and exceeded 300 ng L -1 for 2-hydroxy-benzothiazole, 5-methyl-1 H -benzotriazole, pentachlorophenol, and tris(2-butoxyethyl) phosphate. Median individual PFAS concentrations were <10 ng L -1 , with highest concentrations for PFHxA (180 ng L -1 ), PFOA (110 ng L -1 ), and PFOS (81 ng L -1 ). In six of eight urban stormwater samples analyzed for 6PPD-quinone (a tire rubber-derived transformation product), concentrations exceeded coho salmon acute toxicity thresholds, suggesting (sub)lethal impacts for sensitive species. Observed concentrations were generally significantly higher in highly developed watersheds relative to reference watersheds, but not statistically different in near-shore estuarine sites, suggesting substantial transient exposure potential at stormwater outfalls or creek outflows. Results emphasized the role of stormwater in contaminant transport, the importance of vehicles/roadways as contaminant sources, and the value of monitoring broad multi-analyte contaminant suites to enable comprehensive source and toxicity evaluations.

Assessing the impact of chemical contaminants on aquatic ecosystem health remains challenging due to complex exposure scenarios and the myriad of impact metrics to consider. To expand the breadth of compounds monitored and evaluate the potential hazard of environmental mixtures, cell-based bioassays (estrogen receptor alpha (ERα) and aryl hydrocarbon receptor (AhR)) and non-targeted chemical analyses with high resolution mass spectrometry (NTA-HRMS) were used to assess the quality of ∼70 marine sediment samples collected from 5 distinct coastal and offshore habitats of the Southern California Bight. AhR responses (<0.12-4.5 ng TCDD/g dry weight) were more frequently detectable and more variable than for ERα (<0.1-0.5 ng E2/g dry weight). The range of AhR and ERα responses increased by habitat as follows: Channel Islands < Mid-shelf < Marinas < Ports < Estuaries. The narrow range and magnitude of ERα screening response suggested limited potential for estrogenic impacts across sediments from all 5 habitats. The AhR response was positively correlated with total PAH and PCB concentrations and corresponded with a chemical score index representing the severity of metal and organic contamination. NTA-HRMS fingerprints generated in positive electrospray ionization mode were clearly distinguishable among coastal vs. offshore samples, with the greatest chemical complexity (n = 982 features detected) observed in estuarine sediment from a highly urbanized watershed (Los Angeles River). The concordance and complementary nature of bioscreening and NTA-HRMS results indicates their utility as holistic proxies for sediment quality, and when analyzed in conjunction with routine targeted chemical monitoring, show promise in identifying unexpected contaminants and novel toxicants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

High resolution mass spectrometry (HRMS) analyses provide expansive chemical characterizations of environmental samples. To date, most research efforts have developed tools to expedite labor- and time-intensive contaminant identification efforts. However, even without chemical identity, the richness of nontarget HRMS data sets represents a significant opportunity to chemically differentiate samples and delineate source contributions. To develop this potential, we evaluated the use of unidentified HRMS detections to define sample uniqueness and provide additional statistical resolution for quantitative source apportionment, overcoming a critical limitation of existing approaches based on targeted contaminants. By creating a series of sample mixtures that mimic pollution sources in a representative watershed, we assessed the fidelity of HRMS source fingerprints during dilution and mixing. This approach isolated 8-447 nontarget compounds per sample for source apportionment and yielded accurate source concentration estimates (between 0.82 and 1.4-fold of actual values), even in multisource systems with <1% source contributions. Furthermore, we mined the nontarget data to identify five source-specific chemical end-members amenable to apportionment. While additional development studies are needed to fully evaluate the myriad factors affecting method accuracy and capabilities, this study provides a conceptual foundation for novel applications of nontarget HRMS data to confidently distinguish and quantify source impacts in complex systems.

Azaarenes are N-heterocyclic polyaromatic pollutants that co-occur with polycyclic aromatic hydrocarbons (PAHs) in contaminated soils. Despite the known toxicity of some high-molecular-weight azaarenes, their diversity, abundance, and fate in contaminated soils remain to be elucidated. We applied high-resolution mass spectrometry and mass-defect filtering to four PAH-contaminated samples from geographically distant sites and detected 232 azaarene congeners distributed in eight homologous series, including alkylated derivatives and two hitherto unknown series. Four- and five-ring azaarenes were detected among these series, and the most abundant nonalkylated congeners groups (C 13 H 9 N, C 15 H 9 N, C 17 H 11 N, C 19 H 11 N, and C 21 H 13 N) were quantified. The profiles of congener groups varied among different sites. Three-ring azaarenes presented higher concentrations in unweathered sites, while four- and five-ring azaarenes predominated in weathered sites. Known toxic and carcinogenic azaarenes, such as benzo[c]acridine and dibenzo[a,h]acridine, were detected along with their multiple isomers. Our results highlight a previously unrecognized diversity and abundance of azaarenes in PAH-contaminated sites, with corresponding implications for environmental monitoring and risk assessment.

The impact of a typical municipal solid waste incinerator (MSWI) on polychlorinated naphthalene (PCN) concentrations in surrounding soil was studied. We collected 6 stack gas samples from the MSWI and 21 soil samples from sampling sites at distances of between 300 and 1,700 m from the MSWI stack. Total dl-PCN (dioxin-like PCN) concentrations in the stack gas samples ranged from 6898 and 89,032 pg m(-3), with a mean value of 36,241 pg m(-3). The total dl-PCN concentrations in the soil samples ranged from 30.35 to 280.9 pg g(-1), with a mean value of 87.03 and a median value of 70.32 pg g(-1), while the TEQ values were between 7.7 and 130.2 fg TEQ g(-1), with a mean value of 41.12 fg TEQ g(-1) and a median value of 31.52fg TEQ g(-1). The PCN homologue patterns and the results of Principal Component Analysis suggested that the MSWI may be a source of PCNs in the soils. A contour map, created using an ordinary Kriging interpolation technique, showed that a limited area (≤ 1,000 m radius) surrounding the MSWI was influenced by the emissions from the MSWI. Furthermore, an exponential function equation was proposed to quantify the relationship between TEQs of PCNs and the distance from the stack., (Copyright © 2014 Elsevier B.V. All rights reserved.)