Psychopharmaceuticals are a vital part of the modern medicinal arsenal. However, due to their unique mode of action, effecting the neural and nervous system in humans, they can have disproportionately strong adverse effects on the aquatic ecosystem compared to other pollutants. However, prior to the start of the project presented in this thesis, the risks of psychopharmaceuticals were unclear, owing to a lack of a dedicated analysis on the risks, and the lack of some psychopharmaceuticals from occurrence studies and monitoring lists. Furthermore, the removal efficiency from wastewater of many psychopharmaceuticals by conventional, advanced, and nature-based treatments was largely unknown.
To this end, the present thesis aimed to perform a comprehensive risk analysis to establish occurrence and ecotoxicity data gaps for psychopharmaceuticals. This analysis aimed to identify the high risk compounds, but also assess the quality and quantity of the data these risks were based on, in order to better inform future occurrence, monitoring, and ecotoxicity studies.
From the risk analysis, a shortlist of 50 compounds was produced and used to guide the development of an analytical method to quantify these compounds in wastewater. Using this novel method, three experiments were conducted to evaluate the risks and removal in difference scenarios:
Specifically, this thesis used a new metric called risk-based removal to provide a rough benchmark to qualify a specific treatment as successfully reducing the risk posed by psychopharmaceuticals. Here, the results indicated that current wastewater treatment is not sufficient to negate the risk caused by psychopharmaceuticals, and that advanced treatment provides the best opportunity to do so. The algal-mussel cascade was no able to reduce the risk, and due to a pH swing cause by the algal cultivation, many compounds unbound themselves from particulate mater to re-enter the water phase, providing a cautionary tale for the removal of micropollutants by nature-based solutions.