Risk assessment of down-the-drain chemicals at large spatial scales: Model development and application to contaminants originating from urban areas in the Saint Lawrence River Basin

Sci Total Environ. 2016 Jan 15:541:825-838. doi: 10.1016/j.scitotenv.2015.09.100. Epub 2015 Oct 2.

Abstract

Chemicals released into freshwater systems threaten ecological functioning and may put aquatic life and the health of humans at risk. We developed a new contaminant fate model (CFM) that follows simple, well-established methodologies and is unique in its cross-border, seamless hydrological and geospatial framework, including lake routing, a critical component in northern environments. We validated the model using the pharmaceutical Carbamazepine and predicted eco-toxicological risk for 15 pharmaceuticals in the Saint-Lawrence River Basin, Canada. The results indicated negligible to low environmental risk for the majority of tested chemicals, while two pharmaceuticals showed elevated risk in up to 13% of rivers affected by municipal effluents. As an integrated model, our CFM is designed for application at very large scales with the primary goal of detecting high risk zones. In regulatory frameworks, it can help screen existing or new chemicals entering the market regarding their potential impact on human and environmental health. Due to its high geospatial resolution, our CFM can also facilitate the prioritization of actions, such as identifying regions where reducing contamination sources or upgrading treatment plants is most pertinent to achieve targeted pollutant removal or to protect drinking water resources.

Keywords: Down-the-drain chemicals; Geo-spatial modeling; Large spatial scales; Pharmaceuticals; Risk assessment; Wastewater.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Canada
  • Cosmetics / analysis
  • Environmental Monitoring*
  • Household Products / analysis
  • Household Products / statistics & numerical data
  • Models, Theoretical
  • Rivers / chemistry*
  • Waste Disposal, Fluid / methods
  • Wastewater / analysis*
  • Wastewater / statistics & numerical data
  • Water Pollutants, Chemical / analysis*

Substances

  • Cosmetics
  • Waste Water
  • Water Pollutants, Chemical