MODELING THE IMPACT OF MICROBIAL ACTIVITY ON REDOX DYNAMICS IN POROUS MEDIA

Abstract

The present study investigates the interaction between microbial growth and activity and the redox dynamics in natural porous media. The impact the transport regime has on this interaction is also addressed. Expressions for microbial growth are incorporated into a geochemical reaction network linking redox reaction rates to the activity of the microorganisms. A flexible simulation environment, the Biogeochemical Reaction Network Simulator (BRNS) is used for this purpose. Two reactive transport applications relevant to fields of contaminant hydrology and early diagenesis are simulated with the BRNS. Model results are evaluated based on a comparison with comprehensive datasets on the biodegradation of lactate in a sand column experiment and on the distribution of redox-sensitive chemical species in marine sediments of the Skagerrak, Denmark. It is shown that, despite quite different transport regimes, the geomicrobiological model performs equally well in the reproduction of measured chemical species distribution for both applications. This result emphasizes the broad applicability of the proposed approach. Our simulations support that the competitive behavior between various microbial groups is a process controlling the development of redox stratified environments. Furthermore, it is also shown that the transport regime is a key controlling factor for the degree of spatial correlation between microbial biomass distributions and redox reaction rates. Although all our simulations yield a pronounced stratification of the redox processes in the system, the biomass distribution is related to the associated reaction rates only in case of the advection controlled column experiment. In the early diagenetic application, mixing due to bioturbation is the dominant transport process for particulate matter, hence leading to fairly homogeneous distribution of bacterial biomasses which are unrelated to the spatial distribution of redox reaction rates. This homogeneous biomass distribution combined with the 1G carbon degradation model approach might explain why the steady state concentration profiles in such systems can be reproduced by diagenetic models without explicit representation of microbial growth.