Evaluating and utilizing biokinetic constants in activated sludge

Stoichiometric equations developed from biokinetic equations are presented for evaluating and utilizing biokinetic constants in the design and operation of the activated sludge process. Using biokinetic constants developed from non-nitrifying conditions or total system biokinetic constants rather than individual true biokinetic constants for the heterotrophic and autotrophic reactions will lead to incorrect estimates of the daily waste sludge production.     

The Impact of Rainfall on Flows and Loadings at Georgia’s Wastewater Treatment Plants

An assessment of influent and effluent data from 24 wastewater treatment plants (WWTPs) in the state of Georgia with design capacities of 37,850 m³/d (10-mgd) or greater was undertaken. Twelve months of operating data from the 2003 calendar year were evaluated. The objectives of the study were to determine the effect of rainfall intensity on the volumetric flow rate to each WWTP and to determine the relationship between flow rate and the influent five-day, biochemical oxygen demand (BOD₅) and total suspended solids (TSS) concentrations. The relationships between rainfall intensity and influent BOD concentration, rainfall intensity and influent TSS concentration, influent BOD loading and effluent BOD concentration, and influent TSS loading and effluent TSS concentration were also evaluated. Moderate to strong correlations were observed between rainfall intensity and volumetric flow rate, volumetric flow rate and influent BOD and TSS concentrations, average monthly rainfall intensity and influent BOD and TSS concentrations, and between influent BOD and TSS loadings and effluent BOD and TSS concentrations. Weak correlations were observed for some of the relationships when applied to the complete data set however, stronger correlations were achieved by performing statistical analyses of variance and pooling subsets of the data. Peaking factors for flows and loadings were similar to those reported in the literature.     

MODIFICATIONS OF THE McMASTER WORM EGG COUNTING METHOD

SUMMARY Modifications of the McMaster egg counting technique are presented and discussed including the breaking up of hard faecal pellets, removal of air bubbles prior to counting, avoidance of salt spillage on the counting microscope and the use of sodium azide for preventing development of nematode eggs in field samples.     

Bionutrient Removal with a Sequencing Batch Reactor

Removal of nitrogen and phosphorus from a domestic wastewater using a sequencing batch reactor (SBR) was evaluated at solid retention times (SRTs) of 9.3, 13.8, and 18.3 days respectively. Oxygen uptake rates (OURs) and sludge settling characteristics were determined at each SRT investigated. COD removal, nitrification, denitrification, and phosphorus removal were accomplished by using the following operating cycle: 15-min unmixed fill; 2-hr mixed anaerobic period; 3-hr mixed aerobic period; 3-hr mixed anoxic period; 0.5-hr reaeration period; 1-hr settling period; 1-hr decant period; and a 1.5-hr idle period. Advanced wastewater treatment (AWT) standards of 5/5/3/1 mg L^-1 for biochemical oxygen demand (BOD₅), suspended solids (SS), total nitrogen (TN), and total phosphorus (TP) could not be achieved with the bench-scale SBR.     

Design and Modeling of Post-Denitrification Single-Sludge Activated Sludge Processes

A step-by-step design approach for sizing oxic/anoxic single- sludge activated sludge systems is presented. A computer model utilizing a Lotus 1–2–3 spreadsheet was also developed which simulates the post- denitrification single-sludge activated sludge process. The biokinetic equations developed by Lawrence and McCarty are utilized in the model. The model was calibrated using data from a full-scale, modified pure oxygen activated sludge process operating in the oxic/anoxic mode. Two- tailed, paired comparison student ‘t-tests’ performed on effluent BOD₅, SS, TKN, NH₃-N, NO^- ₃-N, and TN indicated there was no significant difference between the actual effluent values and that predicted by the model at a 99 percent confidence level.