Tunneling Electron Transport in ZnO Nanograins Prepared by Electrospinning Method: An Ethyl Acetate Vapour Sensor by Chemiresistive Method

Journal of Porous Materials - In this work, Polyvinyl alcohol (PVA) based ZnO nanofibers were deposited by the electrospinning method. ZnO nanofibers obtained through this method have an average...     

Impact of bioavailability restrictions on microbially induced stable isotope fractionation. 1. Theoretical calculation

The microbial degradation of organic substrates often exhibits a fractionation of stable isotopes which leads to an enrichment of the heavier isotope in the remaining substrate. The use of this effect to quantify the amount of biodegraded substrate in contaminated aquifers requires that the isotope fractionation factor is constant in time and space. In many natural and engineered systems the bioavailable concentration at the location of the enzymes differs from the average bulk concentration of the substrate. When enzymatically driven substrate degradation is coupled to a preceding transport step controlling the bioavailability of the substrate, the observed isotope fractionation becomes a function of the bulk substrate concentration. The sensitivity of the observed isotope fractionation factor toward such substrate concentration changes depends on the ratio of bulk substrate concentration and Michaelis-Menten constant and on the ratio between the specific affinity of the microorganisms toward the substrate and the first order rate constant of the bioavailability limiting transport process. Highest sensitivities toward substrate concentration were found for combinations of high substrate concentration with low substrate bioavailability (i.e., high ratios of substrate concentration and Michaelis-Menten constant, and high ratios of specific affinity and transport rate constant). As a consequence, changes in concentration and isotopic composition of a bioavailability limited substrate in batch experiments should not exhibit a linear relation in a Rayleigh plot, and the slope of the Rayleigh plot should show a decreasing trend with concentration decrease. When using isotope fractionation to quantify biodegradation along groundwater flow paths, changes in observed isotope fractionation might occur while contaminant concentration decreases along a flow path.     

Impact of bioavailability restrictions on microbially induced stable isotope fractionation. 2. Experimental evidence

Stable isotope fractionation analysis (SIFA) of contaminants is an emerging technique to characterize in situ microbial activity. The kinetic isotope effect in microbial degradation reactions, or enzyme catalysis, is caused by the preferential cleavage of bonds containing light rather than heavy isotopes. This leads to a relative enrichment of the heavier isotopes in the residual substrate pool. However, a number of nonisotopically sensitive steps preceding the isotopically sensitive bond cleavage may affect the reaction kinetics of a degradation process, thus reducing the observed (i.e., the macroscopically detectable) isotope fractionation. Low bioavailability of contaminants poses kinetic limitations on the biodegradation process and can significantly reduce the observed kinetic isotope fractionation. Here we present experimental evidence for the influence of bioavailability-limited pollutant biodegradation on observed stable isotope fractionation. Batch laboratory experiments were performed to quantify the toluene hydrogen isotope fractionation of Pseudomonas putida mt-2 (pWWO) subjected to different small concentrations of toluene with and without deuterium label, which corresponded to realistic environmental mass transfer scenarios. Detected isotope fractionations depended significantly on the toluene concentration, hence confirming the influence of substrate mass transfer limitation on observed isotope fractionation, hypothesized by Thullner et al. (Environ. Sci. Technol. 2008, 42,6544-6551). Our results indicate that the bioavailability of a substrate should be considered during quantitative analysis of microbial degradation based on SIFA.