Improved Understanding and Application of Hazardous Waste Biological Treatment Processes Using Microbial Systems Analysis Techniques

Abstract

A systems analysis technique known as the frequency response method was used to characterize the system structure, and the stability and robustness of naphthalene biotransformation in an activated sludge-type system. The continuous system was perturbed with a complex wastewater feed stream containing a sinusoidally-varying naphthalene concentration while all other reactor operating paramenters were held nearly constant. Time series offgas analysis for naphthalene provided a sensitive output parameter that was readily measured and related to the naphthalene reactor liquid concentration.The feed input perturbation period was varied in successive intervals from 64 to 1 hr, and intervening sequences of constant naphthalene feed concentration allowed the system to relax after each perturbation interval. Using an unsteady-state, difference equation-based naphthalene material balance with an assumed first-order naphthalene biotransformation rate equation, a first-order biotransformation rate parameter (or rate "constant") was calculated and was used as an indicator for interpretation of the unexpectedly complex, dynamic naphthalene biotransformation activity.Frequency response analysis of mixed microbial systems was found to be a feasible and useful tool with which to probe the dynamic behavior of biotransformation activity in an operating biological treatment system. This information can give rise to new hypotheses and hopefully new understanding regarding the nature of biotransformation in complex systems. The resulting knowledge should also improve the potential for process control, optimization, and scaleup. Dynamic testing and evaluation protocols for activities in natural and environmental microbial systems based on frequency response systems analysis methods are also feasible and could evolve into a process selection criterion to maximize the success of demonstrations and field-scale applications through early identification of the most stable and robust processes.