Abstract
The U.S. E.P.A. Water9 air emissions model can be used to estimate air emissions, biological removal and adsorption of organic compounds in wastewater treatment and collection systems. Although the model contains an extensive database of physical property data and biological treatment kinetic constants for organic compounds, the Water9 documentation recommends that site-specific biotreatment kinetic data be used whenever available. The Water9 model uses a zero-order substrate removal constant (Kmax) and a first-order substrate removal constant (K1). While these appear similar to, and have the similar units as, the Monod maximum substrate removal constant qmax and the quotient of the Monod qmax divided by the half-saturation factor (Ks), the procedures given for determining the Water9 kinetic factors by batch testing (40CFR Part 63 Appendix C) indicate that there are important differences. The Water9 factors are based on the entire biomass population as measured by the mixed liquor suspended solids, while the intrinsic Monod kinetics are based on the active biological population only. In addition, an effective K1 is determined at the substrate concentration of interest, rather than being a more generally applicable intrinsic constant. Water9 modeling of styrene emissions from an industrial biological wastewater treatment system using the default physical property and kinetic data gave estimated effluent concentrations and air emissions considerably greater than indicated by effluent analytical data, and as indicated by the lack of any styrene odor at the treatment plant. Batch respirometry testing using biomass from the industrial plant and pure styrene as the substrate was used to generate a styrene removal profile based on Monod kinetics. The substrate removal profile was used in place of substrate analytical data in a modification of one of the recommended procedures for determining the Water9 kinetic constants. Using the site-specific biorate constants resulted in estimates of the styrene effluent concentrations in much better agreement with measured concentrations in the plant effluent. The styrene air emissions estimated by the model decreased by several orders of magnitude.
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