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Developing a Standardized Protocol for Assessing the Biodegradability of Trace Organic Contaminants

9781780405162
100 pages
IWA Publishing
Overview
This work was performed to better understand the factors that impact trace organic compound (TOrC) biodegradation kinetics in mixed microbial cultures. To accomplish this goal, optimized short-term batch tests using TOrC and identified TOrC surrogates were conducted using lab-scale activated sludge cultures. In these optimization experiments, the initial TOrC/surrogate concentration, readily biodegradable carbon concentration (rbCOD) and dissolved oxygen (DO) concentrations were varied. Once developed, these batch tests were deployed at three full-scale wastewater treatment facilities to estimate in-situ biotransformation kinetics. 

This work confirms that TOrC biotransformation is best described using pseudo-first order kinetics. In contrast, results from surrogate experiments indicate that the current approach to aerobic respirometry is not sufficiently sensitive for resolving TOrC biotransformation versus endogenous respiration. Results from short-term batch test optimization also indicate that parameters estimated from depletion tests performed at artificially high TOrC concentrations are statistically similar to parameters estimated at low TOrC concentrations. This suggests that interrogation of the biomass can be performed at high TOrC concentrations, which would reduce the cost of sample processes associated with working at lower concentrations. 

It was also found that the presence of excess readily biodegradable substrates suppress biotransformation rates for specific TOrC under aerobic and anoxic conditions. These results indicate that accurate estimation of biotransformation parameters requires careful design of the batch test to match the in-situ carbon conditions. An initial attempt to incorporate existing biotransformation and sorption parameters into current activated sludge process models was also performed. Results from this simulation indicate that modeling results are highly sensitive to the processes of sorption and desorption.