The influence of macrofaunal burrow spacing and diffusive scaling on sedimentary nitrification and denitrification: An experimental simulation and model approach

The influence of burrow spacing on nitrification and denitrification was simulated experimentally using sediment plugs of different thicknesses immersed in aerated seawater reservoirs. Different plug thicknesses mimic different distances between oxygenated burrow centers and produce similar changes in aerobic–anaerobic reaction balances as a function of diffusive transport scaling. The thicknesses used were roughly equivalent to transport scales (interburrow spacing) that could be produced by burrow abundances of ~400 to 50,000 m-2, depending on burrow lumen radii (e.g., 0.05–1 cm). Following the exposure of anoxic sediment plugs to aerated water, an efficient aerobic nitrification zone was established within the first ~2–3 millimeters of sediment. At pseudo-steady state, the thinnest plug (2 mm) simulating highest burrow density, was entirely oxic and the denitrification rate nil. Denitrification was stimulated in anoxic regions of the thicker plugs (5, 10, and 20 mm) compared to the initial value in experimental sediment. Maximum nitrification rates and the highest denitrification/nitrification ratio between oxic nitrification and adjacent denitrification zones occurred for the intermediate plug thickness of 5 mm. Of the oxic/anoxic composites, the thickest plug showed the least efficient coupling between nitrification/denitrification zones (lowest denitrification/nitrification ratio). Both the thickness of the oxic layer and the total net remineralization of dissolved inorganic N varied inversely with plug thickness. A set of diffusion–reaction models was formulated assuming a range of possible nitrification kinetic functions. All model forms predicted optimal nitrification–denitrification and ammonification–denitrification coupling with relative oxic–anoxic zonation scales comparable to intermediate plug thicknesses (5–6 mm). However, none of the commonly assumed kinetic forms for nitrification could produce the observed NO-3 profiles in detail, implying that natural sediment populations of nitrifiers may be less sensitive to O2 than laboratory strains. Our experimental and model results clearly show that rates of N remineralization and the balance between stimulation/inhibition of denitrification are highly dependent on sedimentary biogenic structure and the particular geometries of irrigated burrow distributions

Extended Smoothed Boundary Method for Solving Partial Differential Equations with General Boundary Conditions on Complex Boundaries

In this article, we describe an approach for solving partial differential equations with general boundary conditions imposed on arbitrarily shaped boundaries. A continuous function, the domain parameter, is used to modify the original differential equations such that the equations are solved in the region where a domain parameter takes a specified value while boundary conditions are imposed on the region where the value of the domain parameter varies smoothly across a short distance. The mathematical derivations are straightforward and generically applicable to a wide variety of partial differential equations. To demonstrate the general applicability of the approach, we provide four examples herein: (1) the diffusion equation with both Neumann and Dirichlet boundary conditions; (2) the diffusion equation with both surface diffusion and reaction; (3) the mechanical equilibrium equation; and (4) the equation for phase transformation with the presence of additional boundaries. The solutions for several of these cases are validated against corresponding analytical and semi-analytical solutions. The potential of the approach is demonstrated with five applications: surface-reaction-diffusion kinetics with a complex geometry, Kirkendall-effect-induced deformation, thermal stress in a complex geometry, phase transformations affected by substrate surfaces, and a self-propelled droplet.Comment: This document is the revised version of arXiv:0912.1288v

Modeling desorption kinetics of a persistent organic pollutant from field aged sediment using a bi-disperse particle size distribution

Purpose With the predicted climate change, it is expected that the chances of river flooding increase. During flood events, sediments will resuspend and when sediments are polluted, contaminants can be transferred to the surrounding water. In this paper we discuss a numerical intraparticle diffusion model that simulates desorption of dieldrin from a suspension of contaminated porous sediment particles with a well-characterized particle size distribution. The objective of this study was to understand the desorption rate (flux) of dieldrin from a suspension of field-aged sediment at different hydraulic retention times (HRT) of the aqueous phase and to elaborate the effect of particle-size distribution on mass transfer. Materials and methods Desorption kinetics of dieldrin, a persistent organic pollutant (POP), were experimentally measured and described in a separate paper using field-contaminated sediment. A radial diffusion model, accommodating intraparticle reversible sorption kinetics, aqueous phase pore diffusion, and a sink term for bulk aqueous phase refreshment was used to describe the experimental data. Results and discussion We observed rapid equilibrium of contaminants between small particles (10 µm) and the surrounding water even though the sorption affinity of dieldrin towards organic matter was high. On the contrary, for the larger particles (84 µm), calculations show that desorption was limited by intraparticle diffusion. Combining small and larger particles in our radial diffusion model resulted in the biphasic desorption behavior often observed even when using a linear isotherm. Conclusions Flood events will result in an increase of desorption rate of POPs from sediments to the surrounding water. HRT and the particle-size distribution determine the desorption rate. We conclude that nonstationary diffusion within organic matter is the main process of mass transfer. Particle size distributions are very valuable to understand the phenomenology related to mass transfer limitations often described as limited bioavailability and can be used as basis to develop engineering options to limit contaminant mass fluxes into the environmen

Performance loss of proton exchange membrane fuel cell due to hydrophobicity loss in gas diffusion layer: Analysis by multiscale approach combining pore network and performance modelling

Loss of hydrophobicity in the gas diffusion layers (GDL) is sometimes suggested as a potential mechanism to explain in part the performance loss of PEMFC. The present study proposes a numerical methodology to analyse this effect by combining pore network modelling (PNM) and performance modelling (PM): the PNM/PM approach. PNM allows simulating the decrease of through-plane gas diffusion coefficient in the GDL as a function of the hydrophobicity loss, which is taken into account through the increase in the fraction of hydrophilic pores in GDL. Then PM based on Darcy equations allows simulating performance loss of PEMFC as a function of gas diffusion decay. This coupling shows that the loss of hydrophobic treatment increases flooding, decreases performance, and increases current density heterogeneities between inlet and outlet of the cell. Interestingly, this degradation is found to be highly non-linear, mainly because of the non-linear influence of the fraction of hydrophilic pores on gas diffusion (this is due to the existence of a percolation threshold associated with the hydrophilic pore sub-network) as well as the non-linear behaviour of electrochemistry with gas diffusion. This study also shows that the loss of hydrophobicity in a GDL is a very suitable candidate to explain performance loss rates that are classically observed during long-term tests. The proposed methodology may also help linking other local properties of components to fuel cell global performance

Combination of techniques to quantify the distribution of bacteria in their soil microhabitats at different spatial scales

To address a number of issues of great societal concern at the moment, like the sequestration of carbon, information is direly needed about interactions between soil architecture and microbial dynamics. Unfortunately, soils are extremely complex, heterogeneous systems comprising highly variable and dynamic micro-habitats that have significant impacts on the growth and activity of inhabiting microbiota. Data remain scarce on the influence of soil physical parameters characterizing the pore space on the distribution and diversity of bacteria. In this context, the objective of the research described in this article was to develop a method where X-ray microtomography, to characterize the soil architecture, is combined with fluorescence microscopy to visualize and quantify bacterial distributions in resin-impregnated soil sections. The influence of pore geometry (at a resolution of 13.4 μm) on the distribution of Pseudomonas fluorescens was analysed at macro- (5.2 mm × 5.2 mm), meso- (1 mm × 1 mm) and microscales (0.2 mm × 0.2 mm) based on an experimental setup simulating different soil architectures. The cell density of P. fluorescens was 5.59 x 107(SE 2.6 x 106) cells g−1 soil in 1–2 mm and 5.84 x 107(SE 2.4 x 106) cells g−1 in 2–4 mm size aggregates soil. Solid-pore interfaces influenced bacterial distribution at micro- and macroscale, whereas the effect of soil porosity on bacterial distribution varied according to three observation scales in different soil architectures. The influence of soil porosity on the distribution of bacteria in different soil architectures was observed mainly at the macroscale, relative to micro- and mesoscales. Experimental data suggest that the effect of pore geometry on the distribution of bacteria varied with the spatial scale, thus highlighting the need to consider an “appropriate spatial scale” to understand the factors that regulate the distribution of microbial communities in soils. The results obtained to date also indicate that the proposed method is a significant step towards a full mechanistic understanding of microbial dynamics in structured soils