No abstract

Very few tools are available for assessing the impact of combined sewer overflows (CSOs) on receiving aquatic environments. The main goal of the study was to assess the ecotoxicological risk of CSOs for a surface aquatic ecosystem using a coupled "substance and bioassay" approach. Wastewater samples from the city of Longueuil, Canada CSO were collected for various rainfall events during one summer season and analyzed for a large panel of substances (n = 116). Four bioassays were also conducted on representative organisms of surface aquatic systems (Pimephales promelas, Ceriodaphnia dubia, Daphnia magna, and Oncorhynchus mykiss). The analytical data did not reveal any ecotoxicological risk for St. Lawrence River organisms, mainly due to strong effluent dilution. However, the substance approach showed that, because of their contribution to the ecotoxicological hazard posed by the effluent, total phosphorus (Ptot), aluminum (Al), total residual chlorine, chromium (Cr), copper (Cu), pyrene, ammonia (N-NH4 (+)), lead (Pb), and zinc (Zn) require more targeted monitoring. While chronic ecotoxicity tests revealed a potential impact of CSO discharges on P. promelas and C. dubia, acute toxicity tests did not show any effect on D. magna or O. mykiss, thus underscoring the importance of chronic toxicity tests as part of efforts aimed at characterizing effluent toxicity. Ultimately, the study leads to the conclusion that the coupled "substance and bioassay" approach is a reliable and robust method for assessing the ecotoxicological risk associated with complex discharges such as CSOs.

Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern.