Dataset for "Loken LC, Corsi SR, Alvarez DA, Ankley GT, Baldwin AK, Blackwell BR, De Cicco LA, Nott MA, Oliver SK, Villeneuve DL. Prioritizing Pesticides of Potential Concern and Identifying Potential Mixture Effects in Great Lakes Tributaries Using Passive Samplers. Environ Toxicol Chem. 2023 Feb;42(2):340-366. doi: 10.1002/etc.5491. Epub 2022 Dec 23. PMID: 36165576; PMCID: PMC10107608.". This dataset is associated with the following publication: Loken, L., S. Corsi, D. Alvarez, G. Ankley, A. Baldwin, B. Blackwell, L. DeCicco, M. Nott, S. Oliver, and D. Villeneuve. Prioritizing Pesticides of Potential Concern and Identifying Potential Mixture Effects in Great Lakes Tributaries Using Passive Samplers. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 42(2): 340-366, (2023).

Dataset for "Loken LC, Corsi SR, Alvarez DA, Ankley GT, Baldwin AK, Blackwell BR, De Cicco LA, Nott MA, Oliver SK, Villeneuve DL. Prioritizing Pesticides of Potential Concern and Identifying Potential Mixture Effects in Great Lakes Tributaries Using Passive Samplers. Environ Toxicol Chem. 2023 Feb;42(2):340-366. doi: 10.1002/etc.5491. Epub 2022 Dec 23. PMID: 36165576; PMCID: PMC10107608.". This dataset is associated with the following publication: Loken, L., S. Corsi, D. Alvarez, G. Ankley, A. Baldwin, B. Blackwell, L. DeCicco, M. Nott, S. Oliver, and D. Villeneuve. Prioritizing Pesticides of Potential Concern and Identifying Potential Mixture Effects in Great Lakes Tributaries Using Passive Samplers. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 42(2): 340-366, (2023).

Dataset for "Pronschinske, M.A., Corsi, S.R., DeCicco, L.A., Furlong, E.T., Ankley, G.T., Blackwell, B.R., Villeneuve, D.L., Lenaker, P.L. and Nott, M.A. (2022), Prioritizing Pharmaceutical Contaminants in Great Lakes Tributaries Using Risk-Based Screening Techniques. Environ Toxicol Chem, 41: 2221-2239. https://doi.org/10.1002/etc.5403". This dataset is associated with the following publication: Pronschinske, M., S. Corsi, L. DeCicco, E. Furlong, G. Ankley, B. Blackwell, D. Villeneuve, P. Lenaker, and M. Nott. Prioritizing Pharmaceutical Contaminants in Great Lakes Tributaries Using Risk-Based Screening Techniques.. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 41(9): 2221-2239, (2022).

Dataset for "Pronschinske, M.A., Corsi, S.R., DeCicco, L.A., Furlong, E.T., Ankley, G.T., Blackwell, B.R., Villeneuve, D.L., Lenaker, P.L. and Nott, M.A. (2022), Prioritizing Pharmaceutical Contaminants in Great Lakes Tributaries Using Risk-Based Screening Techniques. Environ Toxicol Chem, 41: 2221-2239. https://doi.org/10.1002/etc.5403". This dataset is associated with the following publication: Pronschinske, M., S. Corsi, L. DeCicco, E. Furlong, G. Ankley, B. Blackwell, D. Villeneuve, P. Lenaker, and M. Nott. Prioritizing Pharmaceutical Contaminants in Great Lakes Tributaries Using Risk-Based Screening Techniques.. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 41(9): 2221-2239, (2022).

To better understand the transport of neonicotinoid insecticides into the Great Lakes, monthly samples (October 2015-September 2016) were collected from 10 tributaries to the Great Lakes, USA. At least one neonicotinoid was detected in 74% of the monthly samples with up to three neonicotinoids detected in an individual sample (10% of all samples). The most frequently detected neonicotinoid was imidacloprid (53%) followed by clothianidin (44%), thiamethoxam (22%), acetamiprid (2%), and dinotefuran (1%). Thiacloprid was not detected in any samples. More spatially intensive samples from were collected in an agriculturally dominated area (Maumee River, Ohio) twice during spring 2016. Three neonicotinoids were ubiquitously detected (clothiandin, imidacloprid, thiamethoxam) in all water samples collected within this basin. This dataset is associated with the following publication: Hladik, M., S. Corsi, D. Kolpin, A. Baldwin, B. Blackwell, and J. Cavallin. Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes, USA. ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 235: 102-1029, (2018).

To better understand the transport of neonicotinoid insecticides into the Great Lakes, monthly samples (October 2015-September 2016) were collected from 10 tributaries to the Great Lakes, USA. At least one neonicotinoid was detected in 74% of the monthly samples with up to three neonicotinoids detected in an individual sample (10% of all samples). The most frequently detected neonicotinoid was imidacloprid (53%) followed by clothianidin (44%), thiamethoxam (22%), acetamiprid (2%), and dinotefuran (1%). Thiacloprid was not detected in any samples. More spatially intensive samples from were collected in an agriculturally dominated area (Maumee River, Ohio) twice during spring 2016. Three neonicotinoids were ubiquitously detected (clothiandin, imidacloprid, thiamethoxam) in all water samples collected within this basin. This dataset is associated with the following publication: Hladik, M., S. Corsi, D. Kolpin, A. Baldwin, B. Blackwell, and J. Cavallin. Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes, USA. ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 235: 102-1029, (2018).

This dataset includes pesticides and pesticide transformation products in 15 tributaries of the Great Lakes. Pesticides were monitored using polar organic chemical integrative samplers (POCIS) to estimate concentrations in water following standard protocols (Alvarez, 2010) in June and July 2016. POCIS extracts were analyzed for 225 chemicals (USGS National Water Quality Laboratory schedule 5437, Sandstrom and others, 2016), for which 129 chemicals also have POCIS uptake rates, allowing calculations of time-weighted mean concentration over the approximately 30 day deployment (Alvarez and others, 2008). Collectively, there were 97 chemicals detected, and time-weighted mean concentrations could be calculated for 95 chemicals. The data support the findings in the associated journal article (https://doi.org/TBD).

This dataset includes pesticides and pesticide transformation products in 15 tributaries of the Great Lakes. Pesticides were monitored using polar organic chemical integrative samplers (POCIS) to estimate concentrations in water following standard protocols (Alvarez, 2010) in June and July 2016. POCIS extracts were analyzed for 225 chemicals (USGS National Water Quality Laboratory schedule 5437, Sandstrom and others, 2016), for which 129 chemicals also have POCIS uptake rates, allowing calculations of time-weighted mean concentration over the approximately 30 day deployment (Alvarez and others, 2008). Collectively, there were 97 chemicals detected, and time-weighted mean concentrations could be calculated for 95 chemicals. The data support the findings in the associated journal article (https://doi.org/TBD).