Wipe sampling variables (such as wipe wetting solvent, pesticide concentration effects, commercial products, number of wipes per tested surface) were evaluated to determine their potential effects on method performance and how they may alter surface recoveries. This dataset is associated with the following publication: Willison, S., D. Stout, A. Mysz, J. Starr, D. Tabor, B. Wyrzykowska-Ceradini, J. Nardin, E. Morris, and E. Snyder. The impact of wipe sampling variables on method performance associate with indoor pesticide misuse and highly contaminated areas. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 655: 539-546, (2019).

Wipe sampling variables (such as wipe wetting solvent, pesticide concentration effects, commercial products, number of wipes per tested surface) were evaluated to determine their potential effects on method performance and how they may alter surface recoveries. This dataset is associated with the following publication: Willison, S., D. Stout, A. Mysz, J. Starr, D. Tabor, B. Wyrzykowska-Ceradini, J. Nardin, E. Morris, and E. Snyder. The impact of wipe sampling variables on method performance associate with indoor pesticide misuse and highly contaminated areas. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 655: 539-546, (2019).

Data files for "Oliver, S.K., Corsi, S.R., Baldwin, A.K., Nott, M.A., Ankley, G.T., Blackwell, B.R., Villeneuve, D.L., Hladik, M.L., Kolpin, D.W., Loken, L., DeCicco, L.A., Meyer, M.T. and Loftin, K.A. (2023), Pesticide Prioritization by Potential Biological Effects in Tributaries of the Laurentian Great Lakes. Environ Toxicol Chem, 42: 367-384. https://doi.org/10.1002/etc.5522". This dataset is associated with the following publication: Oliver, S., S. Corsi, A. Baldwin, M. Nott, G. Ankley, B. Blackwell, D. Villeneuve, M. Hladik, D. Kolpin, L. Loken, L. DeCicco, M. Meyer, and K. Loftin. Pesticide Prioritization by Potential Biological Effects in Tributaries of the Laurentian Great Lakes. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 42(2): 367-384, (2023).

Data files for "Oliver, S.K., Corsi, S.R., Baldwin, A.K., Nott, M.A., Ankley, G.T., Blackwell, B.R., Villeneuve, D.L., Hladik, M.L., Kolpin, D.W., Loken, L., DeCicco, L.A., Meyer, M.T. and Loftin, K.A. (2023), Pesticide Prioritization by Potential Biological Effects in Tributaries of the Laurentian Great Lakes. Environ Toxicol Chem, 42: 367-384. https://doi.org/10.1002/etc.5522". This dataset is associated with the following publication: Oliver, S., S. Corsi, A. Baldwin, M. Nott, G. Ankley, B. Blackwell, D. Villeneuve, M. Hladik, D. Kolpin, L. Loken, L. DeCicco, M. Meyer, and K. Loftin. Pesticide Prioritization by Potential Biological Effects in Tributaries of the Laurentian Great Lakes. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 42(2): 367-384, (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 "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).

The National Water-Quality Assessment (NAWQA) Program and National Stream Quality Accounting Network (NASQAN) are U.S. Geological Survey (USGS) monitoring programs that measure pesticide concentrations in the Nation’s streams and rivers, herein collectively referred to as streams. The NAWQA Program began monitoring pesticides in 1992 and the NASQAN Program began monitoring pesticides in 1995. The programs were recently merged to form the USGS National Water Quality Network for Rivers and Streams. Water samples are analyzed for pesticides by the USGS National Water Quality Laboratory (NWQL) using methods developed by the NWQL’s Methods Research and Development team. The NWQL extensively used two analytical methods, gas chromatography/mass spectrometry and liquid chromatography/mass spectrometry, to measure pesticides in filtered water samples during 1992–2012 (old method). In October 2012, the monitoring programs began using direct aqueous-injection liquid chromatography tandem mass spectrometry as a new analytical method for pesticides (new method). The change in analytical methods, however, has the potential to inadvertently introduce bias in analysis of datasets that span the change. The data sets provided in this report were used to document performance of the new method in a variety of stream-water matrices and help quantify potential changes in measurement bias or variability that could be attributed to changes in analytical methods (Martin and others, 2016). Users should consult the report by Martin and others (2016) to understand how these data were collected and used. Measured concentrations and calculated recoveries of 281 pesticides and degradates in paired environmental background water samples and matrix spiked water samples collected at 48 stream-water sites from June 11, 2012 to September 6, 2012 are provided in seven tab-delimited ASCII files with relational database (RDB) format header. A tab-delimited ASCII file (DataDictionaryList.txt) listing DataSet attributes and RDB column formats is also included in this data release. Martin, J.D., Norman, J.E., Sandstrom, M.W., and Rose, C.E., 2016, A field study of selected U.S. Geological Survey analytical methods for measuring pesticides in filtered stream water, June-September 2012: U.S. Geological Survey Scientific Investigations Report, 2017-5049

The National Water-Quality Assessment (NAWQA) Program and National Stream Quality Accounting Network (NASQAN) are U.S. Geological Survey (USGS) monitoring programs that measure pesticide concentrations in the Nation’s streams and rivers, herein collectively referred to as streams. The NAWQA Program began monitoring pesticides in 1992 and the NASQAN Program began monitoring pesticides in 1995. The programs were recently merged to form the USGS National Water Quality Network for Rivers and Streams. Water samples are analyzed for pesticides by the USGS National Water Quality Laboratory (NWQL) using methods developed by the NWQL’s Methods Research and Development team. The NWQL extensively used two analytical methods, gas chromatography/mass spectrometry and liquid chromatography/mass spectrometry, to measure pesticides in filtered water samples during 1992–2012 (old method). In October 2012, the monitoring programs began using direct aqueous-injection liquid chromatography tandem mass spectrometry as a new analytical method for pesticides (new method). The change in analytical methods, however, has the potential to inadvertently introduce bias in analysis of datasets that span the change. The data sets provided in this report were used to document performance of the new method in a variety of stream-water matrices and help quantify potential changes in measurement bias or variability that could be attributed to changes in analytical methods (Martin and others, 2016). Users should consult the report by Martin and others (2016) to understand how these data were collected and used. Measured concentrations and calculated recoveries of 281 pesticides and degradates in paired environmental background water samples and matrix spiked water samples collected at 48 stream-water sites from June 11, 2012 to September 6, 2012 are provided in seven tab-delimited ASCII files with relational database (RDB) format header. A tab-delimited ASCII file (DataDictionaryList.txt) listing DataSet attributes and RDB column formats is also included in this data release. Martin, J.D., Norman, J.E., Sandstrom, M.W., and Rose, C.E., 2016, A field study of selected U.S. Geological Survey analytical methods for measuring pesticides in filtered stream water, June-September 2012: U.S. Geological Survey Scientific Investigations Report, 2017-5049