Great Lakes tributary pharmaceutical water samples from water year 2018
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This data release provides water chemistry results and quality assurance data for samples collected from Great Lakes tributaries in the states of Minnesota, Wisconsin, Michigan, Indiana, Ohio, and New York. In total, 158 chemicals were analyzed which are primarily pharmaceuticals. Between one and four water samples were collected at 37 sampling locations between November 2017 and July 2018 resulting in a total of 87 environmental, 95 field replicate, and 15 field blank samples. Of the 158 chemicals analyzed, 23 chemicals were detected in at least one regular sample. Detections per site ranged from 0 to 12 chemicals at concentrations of 1.56 to 30900 nanograms per liter. Sample collection and analysis was performed by the U.S. Geological Survey and summarized in the associated journal article (https://doi.org/10.1002/etc.5403). More detailed method descriptions will be published in the future.
Identifying chemicals and mixtures of potential biological concern detected in passive samplers from Great Lakes tributaries using high-throughput data and biological pathways
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Water-borne contaminants were monitored in 69 tributaries of the Laurentian Great Lakes in 2010 and 2014 using semipermeable membrane devices (SPMDs), and polar organic chemical integrative samplers (POCIS). Analyses included 185 chemicals (143 detected) including 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). This dataset is associated with the following publication: Alvarez, D., S. Corsi, L. De Cicco, D. Villeneuve, and A. Baldwin. Identifying chemicals and mixtures of potential biological concern detected in passive samplers from Great Lakes tributaries using high-throughput data and biological pathways. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA,
Identifying chemicals and mixtures of potential biological concern detected in passive samplers from Great Lakes tributaries using high-throughput data and biological pathways
공공데이터포털
Water-borne contaminants were monitored in 69 tributaries of the Laurentian Great Lakes in 2010 and 2014 using semipermeable membrane devices (SPMDs), and polar organic chemical integrative samplers (POCIS). Analyses included 185 chemicals (143 detected) including 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). This dataset is associated with the following publication: Alvarez, D., S. Corsi, L. De Cicco, D. Villeneuve, and A. Baldwin. Identifying chemicals and mixtures of potential biological concern detected in passive samplers from Great Lakes tributaries using high-throughput data and biological pathways. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA,
Surface water and bottom sediment chemical data and landscape variable input datasets for predicting the occurrence of chemicals of emerging concern in 25 U.S. river basins in the Great Lakes basin
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This data release includes concentrations of contaminants of emerging concern (CEC), by chemical class, for sites sampled within 25 river basins in the U.S. portion of the Great Lakes basin and associated watershed characteristics. The CEC data include concentrations in surface water and sediment samples that were collected during 2010-2014. During the first 3 years, sample sites near mostly urban areas were chosen. The last two years of study focused on other point sources and few nominal reference sites. Water and sediment samples were analyzed for a diverse suite of CECs including, but not limited to, pharmaceuticals, industrial chemicals, flame retardants, pesticides, fragrances, and plasticizers. Statistical models were developed to define the relationships between watershed characteristics within a river basin and the occurrence of specific CEC classes using boosted regression tree models.
Concentrations of Pharmaceutical Contaminants and Their Predicted Effects from a Multi-Regional Assessment of Wadeable USA Streams, 2014-2017
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Human-use pharmaceutical compounds were analyzed at the U.S. Geological Survey, National Water Quality Laboratory, Denver, Colorado, in wadeable streams in 4 Regional Stream Quality Assessments: Northeast (NESQA), Southeast (SESQA), Pacific Northwest (PNSQA) and California (CSQA). Multiple (with few exceptions) samplings occurred at each site, during base flow, between 2014 and 2017. Sites were located in the headwaters of perennial, wadeable streams in urban and agricultural watersheds. Site selection and methodology for each assessment can be found in Van Meter and others (2015), Sheibley and others (2015), Van Meter and others (2017), Coles and others (2016), Van Meter and others (2016), Journey and others (2015), and Van Meter and others (2014).
Concentrations of Pharmaceutical Contaminants and Their Predicted Effects from a Multi-Regional Assessment of Wadeable USA Streams, 2014-2017
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Human-use pharmaceutical compounds were analyzed at the U.S. Geological Survey, National Water Quality Laboratory, Denver, Colorado, in wadeable streams in 4 Regional Stream Quality Assessments: Northeast (NESQA), Southeast (SESQA), Pacific Northwest (PNSQA) and California (CSQA). Multiple (with few exceptions) samplings occurred at each site, during base flow, between 2014 and 2017. Sites were located in the headwaters of perennial, wadeable streams in urban and agricultural watersheds. Site selection and methodology for each assessment can be found in Van Meter and others (2015), Sheibley and others (2015), Van Meter and others (2017), Coles and others (2016), Van Meter and others (2016), Journey and others (2015), and Van Meter and others (2014).
Water-quality data for a pharmaceutical study at Muddy Creek in North Liberty and Coralville, Iowa, 2017-2018
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Surface-water samples were collected, processed, and analyzed for organics, estrogen equivalents, and fecal indicator bacteria. Filtered organic samples were sent to the National Water Quality Laboratory in Denver, Colorado. Unfiltered estrogen equivalent samples were sent to the Organic Geochemistry Research Lab in Lawrence, Kansas, for extraction, after which they were sent to the National Fish Health Research Laboratory in Leetown, West Virginia. Bacteria samples were processed at the Central-Midwest Water Science Center Iowa City, Iowa, office. Staff collected field parameters in-situ.
Water-quality data for a pharmaceutical study at Muddy Creek in North Liberty and Coralville, Iowa, 2017-2018
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Surface-water samples were collected, processed, and analyzed for organics, estrogen equivalents, and fecal indicator bacteria. Filtered organic samples were sent to the National Water Quality Laboratory in Denver, Colorado. Unfiltered estrogen equivalent samples were sent to the Organic Geochemistry Research Lab in Lawrence, Kansas, for extraction, after which they were sent to the National Fish Health Research Laboratory in Leetown, West Virginia. Bacteria samples were processed at the Central-Midwest Water Science Center Iowa City, Iowa, office. Staff collected field parameters in-situ.