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Substrate Flux into Biofilms of any Thickness
Abstract
A kinetic model is developed for determining substrate flux into biofilms with known thicknesses, even though the thickness may be of nonsteady state. The critical contribution of this model is that mass transport resistance is explicity included in order that the flux becomes a direct function of the bulk substrate concentration. Laboratory-scale, column reactors were utilized to culture steady-state biofilms of known thicknesses. Subsequently, the influent flow rate or substrate concentration was changed to determine the short-term kinetics of substrate utilization of biofilms of known thicknesses. The model successfully predicted the column performance, except for cases in which oxygen depletion caused dual-substrate limitation. Removal of substrate to very low levels was only possible during short-term experiments when the biofilm was in net decay.
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Citations
Cited by
Model of steady‐state‐biofilm kinetics
Rittmann, B. E., & McCarty, P. L. (1980) · Biotechnology and Bioengineering · doi:10.1002/bit.260221110 · Cited by 425
Self-citationHexavalent Chromium Reduction by Bacillus sp. in a Packed-Bed Bioreactor
Chirwa, E. M. N., & Wang, Y.-T. (1997) · Environmental Science & Technology · doi:10.1021/es9606900 · Cited by 117
Metadata
- Authors
- Rittmann, B. E., & McCarty, P. L.
- Venue
- Journal of the Environmental Engineering Division
- Published
- 1981-08
- Volume
- 107
- Issue
- 4
- Pages
- 831-849
- ISSN
- 0090-3914 (ISSN-L)
- 2690-2435
- OpenAlex
- W2201483199
- Cited by
- 175
- References
- 0
- FWCI
- 7.60
- Type
- journal article
- Language
- en
- Open access
- closed
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- Rittmann, B. E., & McCarty, P. L. (1981). Substrate Flux into Biofilms of any Thickness. Journal of the Environmental Engineering Division. https://doi.org/10.1061/jeegav.0001202
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
