Search

Rates of 14C-phenanthrene mineralization in contaminated, undisturbed marine sediments were measured using the whole core injection method to assess microbial natural attenuation activity as a function of sediment depth. Submerged sediments were sampled from Eagle Harbor, a marine superfund site in Puget Sound. Experiments show significant biodegradation activities (0.0012-0.0036 day(-1)) in the sediment horizons from 0 to 10 cm. The purpose and scope of this paper is to evaluate the range of experimental conditions giving valid results; a mathematical simulation described competing contaminant 14C-phenanthrene diffusion and simultaneous biodegradation (Monod kinetics), both retarded by sorption. The effect of aging was examined with two sorption models in presumed pseudo-homogenous sediments having effective properties. The simulation predictions provide quantitative guidelines for the successful use of the whole core injection method. (1) The effective Monod constant KS' in sediment is increased by a large partition coefficient KP between sediment and water and makes the apparent 14C-phenanthrene biodegradation approach first-order kinetics. (2) When KS'>1 mg(-1) l(-1), the measured 14C-phenanthrene biodegradation extent is biased by inadequately distributed injected tracer only when less than 7% of the sediment horizon is initially probed and mixed with injected tracer. (3) A short incubation time (<20 days) is necessary when a mobile indicator, e.g., gaseous 14CO2, is used. For longer incubation times, predictions show that a 14CO2 indicator diffuses to adjacent horizons, thus smearing the depth profile of biodegradation. (4) This method employing a radiolabeled tracer provides accurate biodegradation rates for freshly contaminated sediments, and represents an upper limit to the natural phenanthrene biodegradation extents if the contaminant is aged over 50 days.

To advance the accuracy of bioremediation measurements, it is useful before specific experiments to attribute or estimate the influence of both experimental as well as field conditions on the expected magnitudes of microbial degradation rate coefficients. This paper analyzes the numerical contribution, or influence, of categories of conditions, such as bacterial adaptive state, electron acceptor type, mixing, generalized sorption conditions, and biodegradation temperature, on published phenanthrene biodegradation rates as an example of our regression approach. A fundamental microbial degradation rate equation is transformed to an additive model, then using multiple linear regression on published data, coefficients (of categorical variables) and a linear model are presented that estimate first-order biodegradation rate coefficients to within a factor of 3. Numerical estimates of how much bacterial adaptive state and presence of a sorption phase, the two most statistically significant factors, alter the phenanthrene biodegradation rate are presented. The influence of some measurement or field conditions, for example, the influence of oxygen reduction versus optimal nitrate reduction, cannot be distinguished statistically given the available data and range. The regression model is tested using conditions from newly published papers to estimate a priori the expected rate, which compares very favorably to measurements reported in the papers. Due to limited published data and range for extreme cases, the current coefficients do not apply to degradation of very aged phenanthrene nor very low concentrations of electron acceptors. As estimating tools, however, the coefficients themselves and the regression approach have very beneficial roles in design of experiments for both laboratory and field settings. Our method can be applied to other PAHs as sufficient data become available.