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Updated: Oct 22, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Probabilistic framework for assessing ecological risk of Contaminants of Emerging Concern: Application to a Canadian
Gyan Chhipi-Shrestha1, Manuel Rodriguez2, Sonja Behmel2
1School of Engineering, University of British Columbia, Okanagan Campus, 1137 Alumni Ave, Kelowna, BC V1V 1V7, Canada; École Supérieure d'Aménagement du Territoire, Université Laval, 1628 Pavillon Savard, Université Laval, Québec City, QC, G1K 7P4, Canada.
Abstract:
Contaminants of Emerging Concern (CECs) in natural water pose risks to ecosystems. The concentration of CECs varies spatially and temporally, and their estimated ecotoxicities differ widely by toxicological studies. This study extensively reviewed literature on ecological risk assessment and proposed a probabilistic framework for assessing ecological risk and its uncertainties (aleatory and epistemic). The framework integrated Adverse Outcome Pathway in risk assessment and was applied to a Canadian lake system for seven CECs: salicylic acid, acetaminophen, caffeine, carbamazepine, ibuprofen, drospirenone, and sulfamethoxazole. Altogether 264 water samples were collected and analyzed from 15 sites May 2016 to September 2017. Phytoplankton, zooplankton, and fish were also sampled and analyzed. The results show ecological risk estimates (Risk Quotient, RQ) varied considerably indicating a range of uncertainty. Based on the conservative estimate, the central tendency estimate of the ecological risk of mixture compounds was medium (RQ = 0.6) including drospirenone. However, the reasonably maximum estimate of the risk was high (RQ = 1.4) for mixture compounds including drospirenone. The high risk is primarily due to drospirenone as its individual risk was high (RQ = 1.1) to fish. The specific site and time of high drospirenone exposure was identified for implementing control measures. Classification of ecotoxicity values based on environmental parameters such as climate and water quality, can reduce uncertainty in the risk estimate.
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