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
Dates
Publication Date
2018-12-20
Start Date
2010
End Date
2014
Citation
Elliott, S.M. and Kammel, L.E., 2018, 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: U.S. Geological Survey data release, https://doi.org/10.5066/F7ZK5FXJ.
Summary
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 [...]
Summary
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.
Kiesling, R.L., Elliott, S.M., Kammel, L.E., Choy, S.J., Hummel, S.L., 2019, Predicting the occurrence of chemicals of emerging concern in surface water and sediment across the U.S. portion of the Great Lakes Basin, Science of the Total Environment, v. 651, p. 838-850. doi:10.1016/j.scitotenv.2018.09.201
