A Model Framework to Describe Growth-Linked Biodegradation of Trace-Level Pollutants in the Presence of Coincidental Carbon Substrates and Microbes

详细信息    查看全文

• 作者：Li Liu ; Damian E. Helbling ; Hans-Peter E. Kohler ; Barth F. Smets
• 刊名：Environmental Science & Technology
• 出版年：2014
• 出版时间：November 18, 2014
• 年：2014
• 卷：48
• 期：22
• 页码：13358-13366
• 全文大小：470K
• ISSN：1520-5851

文摘

Pollutants such as pesticides and their degradation products occur ubiquitously in natural aquatic environments at trace concentrations (渭g L^鈥? and lower). Microbial biodegradation processes have long been known to contribute to the attenuation of pesticides in contaminated environments. However, challenges remain in developing engineered remediation strategies for pesticide-contaminated environments because the fundamental processes that regulate growth-linked biodegradation of pesticides in natural environments remain poorly understood. In this research, we developed a model framework to describe growth-linked biodegradation of pesticides at trace concentrations. We used experimental data reported in the literature or novel simulations to explore three fundamental kinetic processes in isolation. We then combine these kinetic processes into a unified model framework. The three kinetic processes described were: the growth-linked biodegradation of micropollutant at environmentally relevant concentrations; the effect of coincidental assimilable organic carbon substrates; and the effect of coincidental microbes that compete for assimilable organic carbon substrates. We used Monod kinetic models to describe substrate utilization and microbial growth rates for specific pesticide and degrader pairs. We then extended the model to include terms for utilization of assimilable organic carbon substrates by the specific degrader and coincidental microbes, growth on assimilable organic carbon substrates by the specific degrader and coincidental microbes, and endogenous metabolism. The proposed model framework enables interpretation and description of a range of experimental observations on micropollutant biodegradation. The model provides a useful tool to identify environmental conditions with respect to the occurrence of assimilable organic carbon and coincidental microbes that may result in enhanced or reduced micropollutant biodegradation.