Bitumen extraction in Alberta's oil sands region generates large volumes of oil sands process-affected waters (OSPW) that pose environmental and human health risks. Currently, few feasible options for managing these large and growing volumes of polluted waters exist. The primary objective of this research is to investigate the feasibility, effectiveness, and safety of treatment wetlands as a treatment option for the oil sands industry. To do this, a mechanistic model of the fate and toxicity of OSPW contaminants in treatments wetlands was developed and tested in field studies at the Kearl Treatment Wetland – a free water surface flow wetland in northern Alberta. Measuring concentrations of polycyclic aromatic hydrocarbons (PAHs) and naphthenic acids (NAs) in influent and effluent of the Kearl Treatment Wetland showed that the combined total mass of all detected PAHs and NA reduced by 54 to 83% and 7.5 to 69%, respectively, as a result of treatment. Concentrations of PAHs and NAs in the aqueous phase of the wetland were measured using polyethylene (PE) and Polar Organic Chemical Integrative Samplers (POCIS), respectively. The model is shown to be in good agreement with the experimental observations and required only minimal calibration. Application of the model shows that evapotranspiration is not likely to significantly contribute to the removal of OSPW contaminants. Chemical removal relies mainly on transformation in wetland rooting media due to high microbial activity in wetland biofilm. Higher rates of transformation result in greater removal efficiencies for most chemicals. However, highly hydrophobic substances experience low removal efficiencies and appear to be unaffected by changes in transformation rates in the wetland suggesting wetland treatment is not suitable for these substances. Treatment efficiency is sensitive to wetland surface area and flow rate of water through the wetland suggesting intentional wetland design and operation can improve treatment efficiency. Trade-offs in wetland design and operation can be informed by the model.
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Thesis advisor: Gobas, Frank
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