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Comparison Between Model Simulations and Field Results for In‐Situ Biorestoration of Chlorinated Aliphatics: Part 1. Biostimulation of Methanotrophic Bacteria
Author(s) -
Semprini Lewis,
McCarty Perry L.
Publication year - 1991
Publication title -
groundwater
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 94
eISSN - 1745-6584
pISSN - 0017-467X
DOI - 10.1111/j.1745-6584.1991.tb00527.x
Subject(s) - biostimulation , methane , population , bacterial growth , electron acceptor , chemistry , porous medium , methanogenesis , environmental science , environmental chemistry , bacteria , porosity , bioremediation , ecology , contamination , photochemistry , organic chemistry , geology , biology , paleontology , demography , sociology
A nonsteady‐state model is presented for the in‐situ biostimulation of a microbial population in saturated porous media. The model includes basic processes of microbial growth, utilization of electron donor and acceptor, advective transport, dispersion, and sorption in porous media. Model simulations are compared with results from a series of controlled field experiments at the Moffett Naval Air Station, where the growth of an indigenous population of methane‐utilizing bacteria (methanotrophs) was stimulated by the controlled addition of dissolved methane and oxygen (DO) into a semiconfined aquifer. Simulations provide good matches to the observed transient uptake of methane and DO, demonstrating that the observed response resulted from the growth of methanotrophs in the test zone. Simulations duplicate results from alternate pulsed addition of methane (electron donor) and oxygen (electron acceptor), used as a means for distributing microbial growth throughout the test zone. The model permits estimation of changes in microbial population distribution at various stages of the two‐year experiment. Temporal changes in model‐fitted kinetic parameters indicate that the microbial population evolved to one that more effectively utilized the methane at lower concentrations. These analyses demonstrate that a relatively simple model, which includes basic microbial and transport processes, can be of use in the design and evaluation of in‐situ biotreatment processes. The model user, however, must provide judgment in the selection of appropriate input parameters, as well as being aware of model limitations.