Optimising sampling methods and understanding their uncertainties in the monitoring and assessment of micropollutants in water

Presenter: Andrew Novic, QAEHS PhD student

Abstract: PhD Thesis Review

Water monitoring networks are often established as a means to characterise and evaluate water quality or make inferences about usage. The estimation of average concentration and total loads of micropollutants over defined periods of time are parameters that can help evaluate spatial or temporal trends and in the success or failure of intervention strategies. Uncertainty and error in the estimation of concentration or loads can arise from discharge measurement, sampling, storage/preservation of samples and analytical results.

The aim of this thesis is to improve our capability to monitor the concentrations and loads of micropollutants in dynamic water bodies. This is to be achieved by (1) advancing our understanding in the uncertainties surrounding the sampling of micropollutants in dynamic waterbodies and (2) better defining the role of passive sampling in such monitoring networks. To achieve this, the approach of this thesis involved intensive sampling efforts in three field studies: riverine floodwaters in north Queensland (chapters 2 and 3), estuarine and marine waters in southeast Queensland (chapters 4 and 5), and a wastewater treatment plant in Zurich, Switzerland (chapter 6). The project aims to illuminate the uncertainties within both grab sampling (chapter 2) and passive sampling (chapters 3, 5 and 6) and aims to offer comparisons between the sampling methods in each environment (chapters 3, 4 and 6).