Identifying Chemicals and Mixtures of Potential Biological Concern Detected in Passive Samplers from Great Lakes Tributaries Using High‐Throughput Data and Biological Pathways

Abstract

Water-borne contaminants were monitored in 69 tributaries of the Laurentian Great Lakes in 2010 and 2014 using semipermeable membrane devices (SPMDs), and This article is protected by copyright. All rights reserved. Accepted Articlepolar organic chemical integrative samplers (POCIS). A risk-based screening approach was used to prioritize chemicals and chemical mixtures, identify sites at greatest risk for biological impacts, and identify potential hazards to monitor at those sites. Analyses included 185 chemicals (143 detected) including polycyclic aromatic hydrocarbons (PAHs), legacy and current-use pesticides, fire retardants, pharmaceuticals, fragrances, and others. Hazard quotients were calculated by dividing detected concentrations by biological effect concentrations reported in the ECOTOX Knowledgebase (Toxicity quotients, TQs) or ToxCast database (Exposure Activity Ratios, EARs). Mixture effects were estimated by summation of EAR values for chemicals that influence ToxCast assays with common gene targets. Nineteen chemicals, including atrazine, DEET, di(2ethylhexyl)phthalate, dl-menthol, galaxolide, p-tert-octylphenol, three organochlorine pesticides, three PAHs, four pharmaceuticals, and three phosphate flame retardants, had TQs greater than 0.1 or EARs for individual chemicals (EAR chem ) greater than 10 -3 at 10% or more of the sites monitored. An additional four chemicals (tributyl phosphate, triethyl citrate, benz(a)anthracene, and benzo(b)fluoranthene) were present in mixtures with EAR (EAR mixture ) greater than 10 -3 . To evaluate potential apical effects and biological endpoints to monitor in exposed wildlife, in vitro bioactivity data were compared to adverse outcome pathway (AOP) and gene ontology information. Endpoints and effects associated with endocrine disruption, alterations in xenobiotic metabolism, and potentially neuronal development would be relevant to monitor at the priority sites.The EAR threshold exceedance for many chemical classes was correlated with urban land cover and wastewater effluent influence, while herbicides and fire retardants were also correlated to agricultural land cover.

Prioritizing Pharmaceutical Contaminants in Great Lakes Tributaries Using Risk‐Based Screening Techniques

“…Both ToxCast and ECOTOX provide distinct types of information with differing biological coverage and would not always be expected to agree; therefore, prioritization thresholds were established independently for these two sets of screening values. An EAR Chem value >10 −3 was considered to have exceeded a prioritization threshold, consistent with previous similar analyses (Alvarez et al, 2021; Corsi et al, 2019) which found that using an EAR threshold of 10 −3 resulted in a list of prioritized chemicals similar to that of traditional water‐quality benchmarks. A TQ value >0.1 was considered to have exceeded a prioritization threshold, similar to previous analyses (Corsi et al, 2019).…”

“…Several summary metrics are modeled from chemical dose–assay response curves in the ToxCast data analysis pipeline. For the present study, the ACC was chosen for comparison with observed water concentrations, consistent with previous efforts (Alvarez et al, 2021; Blackwell et al, 2017; Corsi et al, 2019; Fay et al, 2018). The ACC is determined as a multiplier of the baseline median absolute deviation of measured activity in the assay that provides an indication of the concentration at which the bioactivity measured first exceeds the baseline response.…”

“…This process reduced the original 717 assays with measurable responses (i.e., hit calls) for the detected chemicals to 394 assays considered to be appropriate for use in this analysis; additional details are provided in Supporting Information, Tables SI-2, SI-7, and SI-8. Several summary metrics are modeled from chemical dose-assay response curves in the ToxCast data analysis pipeline. For the present study, the ACC was chosen for comparison with observed water concentrations, consistent with previous efforts (Alvarez et al, 2021;Blackwell et al, 2017;Corsi et al, 2019;Fay et al, 2018). The ACC is determined as a multiplier of the baseline median absolute deviation of measured activity in the assay that provides an indication of the concentration at which the bioactivity measured first exceeds the baseline response.…”

Combining Passive Sampling with Suspect and Nontarget Screening to Characterize Organic Micropollutants in Streams Draining Mixed-Use Watersheds

“…Diheptyl phthalate and tributyl citrate are two high production volume plastic additives that were first identified via suspect and nontarget screening of fine particulate matter and stormwater runoffs, respectively. TBEP is a plasticizer and flame retardant that may possess the potential for endocrine disrupting effects and has been found to accumulate in POCIS deployed in the Great Lakes tributaries . With the exception of TBEP, none of the level 1 nontarget compounds was captured by grab samples despite their widespread detection in streams.…”

Risk‐Based Prioritization of Organic Chemicals and Locations of Ecological Concern in Sediment From Great Lakes Tributaries

“…ToxCast provides several summary metrics derived from dose-response curves to indicate chemical potency. Following previous studies (Alvarez et al, 2021;Blackwell et al, 2017;Bradley et al, 2019;Corsi et al, 2019), the present study used the ACC as an indicator of the chemical concentration that may be required for bioactivity to begin occurring in the assay. The ACC is an assay-specific metric determined as a multiplier of the baseline median absolute deviation of measured activity in the assay that provides an indication of the concentration at which the bioactivity measured first exceeds the baseline The sum of the EAR values for all chemicals associated with a common ToxCast assay endpoint concentration.…”