In this study, the estrogenicity of two major wastewater treatment plant (WWTP) effluents located in the central reaches of the Grand River watershed in southern Ontario was estimated using population demographics, excretion rates, and treatment plant-specific removals. Due to the lack of data on estrogen concentrations from direct measurements at WWTPs, the treatment efficiencies through the plants were estimated using the information obtained from an effects-directed analysis. The results show that this approach could effectively estimate the estrogenicity of WWTP effluents, both before and after major infrastructure upgrades were made at the Kitchener WWTP. The model was then applied to several possible future scenarios including population growth and river low flow conditions. The scenario analyses showed that post-upgrade operation of the Kitchener WWTP will not release highly estrogenic effluent under the 2041 projected population increase (36%) or summer low flows. Similarly, the Waterloo WWTP treatment operation is also expected to improve once the upgrades have been fully implemented and is expected to effectively treat estrogens even under extreme scenarios of population growth and river flows. The developed model may be employed to support decision making on wastewater management strategies designed for environmental protection, especially on reducing the endocrine effects in fish exposed to WWTP effluents.

The large mediatic coverage of recent massive wildfires across the world has emphasized the vulnerability of freshwater resources. The extensive hydrogeomorphic effects from a wildfire can impair the ability of watersheds to provide safe drinking water to downstream communities and high-quality water to maintain riverine ecosystem health. Safeguarding water use for human activities and ecosystems is required for sustainable development; however, no global assessment of wildfire impacts on water supply is currently available. Here, we provide the first global evaluation of wildfire risks to water security, in the form of a spatially explicit index. We adapted the Driving forces-Pressure-State-Impact-Response risk analysis framework to select a comprehensive set of indicators of fire activity and water availability, which we then aggregated to a single index of wildfire-water risk using a simple additive weighted model. Our results show that water security in many regions of the world is potentially vulnerable, regardless of socio-economic status. However, in developing countries, a critical component of the risk is the lack of socio-economic capability to respond to disasters. Our work highlights the importance of addressing wildfire-induced risks in the development of water security policies; the geographic differences in the components of the overall risk could help adapting those policies to different regional contexts.