Geology topics

Natalia Vinas

Publications and source records attributed to Natalia Vinas.

2 recordsLinked to original sources

USGS2025

Leveraging invasive mussel contaminant survey data for stepwise prioritization of chemicals of potential concern in the Great Lakes basin

Historical and ongoing anthropogenic activities coupled with advancements in analytical techniques have led to the detection of large numbers of contaminants in the Laurentian Great Lakes. Consequently, identifying and prioritizing chemicals likely to cause ecological harm represents a challenge for natural resource managers. Previous prioritization efforts have focused on contaminants in sediment, water, and passive samplers, which may not be representative of compounds that bioaccumulate in aquatic organisms. Consequently, this study adopted a stepwise method to prioritize chemicals of potential concern detected in dreissenid mussels from samples collected across the Great Lakes from 2009–2018. The stepwise method considered environmental fate, detection frequency, and exceedance of toxicity quotients based on ecotoxicological effect concentrations. Overall, 153 compounds out of 267 analyzed were detected in dreissenid mussels, 47 of which had water quality effect concentrations, 56 had apical effect concentrations (Tier 1 ECOTOX or apical screening), 17 had nonapical effect concentrations (Tier 2 ECOTOX, Cytotoxic Burst, and ToxCast) and 33 had estimated effect concentrations (quantitative structure-activity relationship, estimated screening, and pharmacological potency). Of the compounds with water quality effect concentrations, nine were designated as high priority, including the herbicide atrazine and five polycyclic aromatic hydrocarbons that were previously identified as potentially hazardous within other matrices. Similar contaminants were identified as high priority in a related study of native unionid mussels in the Great Lakes. A total of 27 compounds were low priority, suggesting that these contaminants do not warrant further action based on this dataset. Overall, these findings will facilitate the development of management strategies to mitigate the effects of contaminants on aquatic organisms within the Great Lakes.

Great Lakes basin↗

USGS2025

Derivation and characterization of environmental hazard concentrations for chemical prioritization: A case study in the Great Lakes tributaries

Ongoing anthropogenic activities and analytical advancements yield continuously expanding lists of environmental contaminants. This represents a challenge to environmental managers, who must prioritize chemicals for management actions (e.g., restriction, regulation, remediation) but are often hindered by resource limitations. To help facilitate prioritization efforts, this study presents several strategies for deriving environmental hazard concentrations using publicly accessible data and open-source computational tools. Using a Great Lakes tributaries aquatic monitoring dataset as a case study, environmental hazard concentrations were obtained or derived for 334 organic chemicals. These concentrations were based on (1) current water quality guidelines; (2) apical screening values; (3) apical and (4) nonapical effect concentrations from the ECOTOXicology Knowledgebase; (5) in vitro effect concentrations from the ToxCast database; (6) cytotoxic burst concentrations collated from the Comptox Dashboard; (7) “estimated screening values” derived from modeled or estimated data and available from various regulatory and nonregulatory agencies; (8) pharmaceutical potency estimates from the MaPPFAST database; and (9) quantitative structure-activity relationship (QSAR)–derived acute toxicity estimates. Environmental fate data included aquatic half-lives and bioconcentration factors collated from the Comptox Dashboard or estimated using QSARs. To identify patterns that could be used for characterization, availability of ecotoxicological concentrations and environmental fate data were evaluated. Furthermore, exceedances of hazard concentrations were evaluated and compared across diverse ecotoxicological data types. Altogether, by providing detailed methodology and practical examples generated with real monitoring data, this study demonstrated that these hazard concentration derivation strategies can be efficiently and effectively used with large, complex datasets and identified critical considerations for future prioritization efforts.

Great Lakes region↗