Evaluation of the information content of long-term wastewater characteristics data in relation to activated sludge model parameters.

A parameter estimation framework was used to evaluate the ability of observed data from a full-scale nitrification-denitrification bioreactor to reduce the uncertainty associated with the bio-kinetic and stoichiometric parameters of an activated sludge model (ASM). Samples collected over a period of 150 days from the effluent as well as from the reactor tanks were used. A hybrid genetic algorithm and Bayesian inference were used to perform deterministic and parameter estimations, respectively. The main goal was to assess the ability of the data to obtain reliable parameter estimates for a modified version of the ASM. The modified ASM model includes methylotrophic processes which play the main role in methanol-fed denitrification. Sensitivity analysis was also used to explain the ability of the data to provide information about each of the parameters. The results showed that the uncertainty in the estimates of the most sensitive parameters (including growth rate, decay rate, and yield coefficients) decreased with respect to the prior information.

Assessment of the endogenous respiration rate and the observed biomass yield for methanol-fed denitrifying bacteria under anoxic and aerobic conditions.

In this study, the endogenous respiration rate and the observed biomass yield of denitrifying methylotrophic biomass were estimated through measuring changes in denitrification rates (DNR) as a result of maintaining the biomass under methanol deprived conditions. For this purpose, activated sludge biomass from a full-scale wastewater treatment plant was kept in 10-L batch reactors for 8 days under fully aerobic and anoxic conditions at 20 °C without methanol addition. To investigate temperature effects, another biomass sample was placed under starvation conditions over a period of 10 days under aerobic conditions at 25 °C. A series of secondary batch tests were conducted to measure DNR and observed biomass yields. The decline in DNR over the starvation period was used as a surrogate to biomass decay rate in order to infer the endogenous respiration rates of the methylotrophs. The regression analysis on the declining DNR data shows 95% confidence intervals of 0.130 ± 0.017 day-1 for endogenous respiration rate under aerobic conditions at 20 °C, 0.102 ± 0.013 day-1 under anoxic conditions at 20 °C, and 0.214 ± 0.044 day-1 under aerobic conditions at 25 °C. Results indicated that the endogenous respiration rate of methylotrophs is 20% slower under anoxic conditions than under aerobic conditions, and there is a significant temperature dependency, with an Arrhenius coefficient of 1.10. The observed biomass yield value showed an increasing trend from approximately 0.2 to 0.6 when the starvation time increased from 0 to 10 days.