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Modified Monod and linear substrate utilization rate equations for activated sludge biodegradation processes.

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University of Ottawa (Canada)

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Substrate removal is most commonly modelled with a Monod or a linear rate equation. In these expressions the removal rate is most often assumed to be first order with respect to volatile suspended solids, which are used as an approximation of the active biomass in the reactor. Wastewater treatment systems are typically operated at sludge ages at which the biomass is in the condition of advanced endogenous decay. This results in the accumulation of dead biomass and other organic debris which reduces the accuracy of volatile suspended solids as a measure of active biomass. The active biomass percentage of volatile suspended solids decreases as sludge age increases. To account for the those conditions, a modified substrate removal expression with volatile mass concentration $\rm(X\sb{v})$ replaced with active biomass concentration $\rm(X\sb{a})$ represented as $\rm AX\sb{v}\sp{n}$ (A - constant, n between 0 and 1) was hypothesized as an improved model. Theoretically the expression $\rm AX\sb{v}\sp{n}$ can represent accurately the actual active biomass concentration. Activated sludge from sequencing batch reactors at steady state conditions was studied for substrate removal kinetics in batch utilization tests. Those tests were conducted on different initial substrate concentrations and different sludge dilutions. The best fitting exponent n, found from the experimental data from those tests, was equal to 0 in both equations. The fitting error (residual mean square) computed from modified equations with n equal to 0 was much lower then fitting error from unmodified equations in which n was equal to 1. The kinetic coefficients computed from modified equations were a better representation of the intrinsic kinetic coefficients (substrate and bacterial population specific) than coefficients computed from unmodified equations. The modified Monod equation provided better fit to the experimental data than the modified linear equation. (Abstract shortened by UMI.)

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Source: Masters Abstracts International, Volume: 34-02, page: 0870.

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