Oxygen transfer from flowing water to microbes in an organic sediment bed

Higashino, Makoto; O’Connor, Ben L.; Hondzo, Miki; Stefan, Heinz G.

doi:10.1007/s10750-008-9508-8

Cited by 36 publications

(50 citation statements)

References 22 publications

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“…14 The DO absorption by organic matter is represented by the sink term,ċ s , which must be modeled. The parametrization for the non-linear sink term,ċ s , due to Higashino et al, 22 isċ…”

Section: Resulting Inmentioning

confidence: 99%

“…A thorough discussion on the effects of dispersion and advection in the sediment layer and the associated modelling problematics can be found in Scalo et al 19 and several works by Higashino and co-workers. [22][23][24][25][26] In the present work, we adopt the model developed by Scalo et al 19 to study the turbulencedriven small-scale transport processes involved in oxygen transfer to smooth and cohesive organic sediment layers (with no dispersion or advection effects) and their sensitivity to the governing parameters such as Re τ , Sc, and χ * (oxygen absorbing bacterial population density). The present work is the natural extension of previous experimental, 15 numerical, 22 and field-scale 27 studies to a numerical investigation based on an eddy resolving method.…”

Section: Introductionmentioning

confidence: 99%

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High-Schmidt-number mass transport mechanisms from a turbulent flow to absorbing sediments

2012

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We have investigated the mechanisms involved in dissolved oxygen (DO) transfer from a turbulent flow to an underlying organic sediment bed populated with DO-absorbing bacteria. Our numerical study relies on a previously developed and tested computational tool that couples a bio-geochemical model for the sediment layer and large-eddy simulation for transport on the water side. Simulations have been carried out in an open channel configuration for different Reynolds numbers (Reτ = 180–1000), Schmidt numbers (Sc = 400–1000), and bacterial populations (χ* = 100–700 mg l−1). We show that the average oxygen flux across the sediment-water interface (SWI) changes with Reτ and Sc, in good agreement with classic heat-and-mass-transfer parametrizations. Time correlations at the SWI show that intermittent peaks in the wall-shear stress initiate the mass transfer and modulate its distribution in space and time. The diffusive sublayer acts as a de-noising filter with respect to the overlying turbulence; the instantaneous mass flux is not affected by low-amplitude background fluctuations in the wall-shear stress but, on the other hand, it is receptive to energetic and coherent near-wall transport events, in agreement with the surface renewal theory. The three transport processes involved in DO depletion (turbulent transport, molecular transport across the diffusive sublayer, and absorption in the organic sediment layer) exhibit distinct temporal and spatial scales. The rapidly evolving near-wall high-speed streaks transport patches of fluid to the edge of the diffusive sublayer, leaving slowly regenerating elongated patches of positive DO concentration fluctuations and mass flux at the SWI. The sediment surface retains the signature of the overlying turbulent transport over long time scales, allowed by the slow bacterial absorption.

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Section: Resulting Inmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

High-Schmidt-number mass transport mechanisms from a turbulent flow to absorbing sediments

2012

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“…The flux variability predicted by the highly simplified model does not improve the predictive power in comparison to the relationship observed between the flux and variations under hydrodynamic forcing alone. While more detailed numerical models of DO dynamics at the sediment-water interface are capable of resolving the short-term dynamics of the fluxes accurately (Higashino et al 2008;Scalo et al 2012Scalo et al , 2013, the aim of the conceptual model applied here was to compare the range of variability of DO fluxes caused by hydrodynamic forcing and the flux variations caused by temperature. Based on a theoretical analysis, Glud et al (2007) concluded that short-term, hydrodynamically driven flux variability does not affect long-term carbon mineralization rates or DO sediment uptake rates (i.e., R).…”

Section: Discussionmentioning

confidence: 99%

“…Pronounced temporal variations of benthic DO fluxes have been observed on time scales from minutes to days Bryant et al 2010;Lorke et al 2012), where temperature changes are small. The observed hydrodynamic forcing of short-term fluxes can be explained by the modulation of the thickness diffusive boundary layer (DBL) overlaying the sediment surface (Lorke and Peeters 2006) and has been reproduced under laboratory conditions and in numerical models (e.g., Jørgensen and Des Marais 1990;Higashino et al 2008;Scalo et al 2012). Detailed models have been developed that couple hydrodynamic forcing of water-side DO fluxes with biogeochemicallycontrolled DO consumption rates within the sediment (Higashino et al 2008;Scalo et al 2013).…”

Section: Introductionmentioning

confidence: 91%

Short-term and seasonal variability of oxygen fluxes at the sediment–water interface in a riverine lake

2014

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In situ measurements of sediment-water oxygen fluxes conducted in a riverine lake during different seasons were analyzed with the aim of quantifying the combined effects of hydrodynamic forcing and seasonal changes in temperature on sediment oxygen uptake rate. Oxygen fluxes measured using the eddy correlation (EC) technique varied widely between -6.4 and -84 mmol m -2 day -1 , while variations observed on hourly time scales were of comparable magnitude to seasonal variations. Oxygen fluxes were most strongly correlated to current speed in the benthic boundary layer and water depth, which both co-varied with discharge, temperature, and oxygen concentration. A direct correlation of measured fluxes with temperature and corresponding seasonal flux variations could not be observed. To explore the potential effect of temperature on oxygen fluxes, we applied a simplified analytical model, which couples the effect of hydrodynamic forcing with a temperature-dependent oxygen consumption rate within the sediment. The results suggest that the flux is a non-linear function of both variables and both can have comparable effects on the magnitude of the oxygen fluxes. The model confirms our observation that short-term variations of oxygen fluxes in response to hydrodynamic forcing can mask longer-term seasonal variations driven by temperature. The model further indicates that the magnitude and form of the temperature dependence of oxygen uptake and mineralization rates in freshwater sediments obtained from laboratory incubations can be strongly affected by flow conditions during incubations. We conclude that predictions of oxygen uptake and mineralization rates under changing climatic conditions should also take potential changes of flow conditions into account.

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“…The DBL limits exchange between the sediment and overlying water, and therefore becomes a bottleneck of diffusive vertical flux at the sediment-water interface (SWI). Higashino et al [4][5][6] theoretically revealed that dynamic forcing in the BBL has a direct effect on DBL thickness and diffusion flux at the SWI. Under the influence of dynamics in the BBL, DBL thickness and flux vary significantly.…”

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confidence: 99%

Variable diffusion boundary layer and diffusion flux at sediment-water interface in response to dynamic forcing over an intertidal mudflat

2012

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The diffusion boundary layer (DBL) significantly limits the exchange between sediment and overlying water and therefore becomes a bottleneck of diffusive vertical flux at the sediment-water interface (SWI). Variable DBL thickness and diffusion flux in response to dynamic forcing may influence replenishment of nutrients and secondary pollution in coastal waters. In situ measurements of velocity in the bottom boundary layer (BBL) and oxygen concentration in the DBL were made over an intertidal mudflat, using an acoustic Doppler current and mini profiler. A linear distributed zone in the oxygen profile, the profile slope discontinuity and variance of concentration can be used to derive accurate DBL thickness. Diffusion fluxes calculated from the water column and sediment are identical, and their bias is less than 6%. A numerical model PROFILE is used to simulate the in situ dissolved oxygen profile, and layered dissolved oxygen consumption rates in the sediment are calculated. The DBL thickness (0.10-0.35 mm) and diffusion flux (15.4-53.6 mmol m) vary with a factor of 3.5 during a tidal period. Over an intertidal mudflat, DBL thickness is controlled by flow speed U in the BBL, according to δ DBL =1686.1DU −1 +0.1 (D is the molecular diffusion coefficient).That is, the DBL thickness δ DBL increases with decreasing flow speed U. Changes of diffusion flux at the SWI are caused by variations in the water above the sediment and the turbulent mixing intensity. The diffusion flux is positively related to the turbulent dissipation rate, friction velocity and turbulent energy. Under the influence of dynamics in the BBL, DBL thickness and flux vary significantly. diffusion boundary layer, diffusion flux, dynamic forcing, mini profiler, dissolved oxygen, intertidal mudflat Citation:Wang J N, Zhao L, Wei H. Variable diffusion boundary layer and diffusion flux at sediment-water interface in response to dynamic forcing over an intertidal mudflat. Chin Sci Bull, 2012Bull, , 57: 15681577, doi: 10.1007 The diffusion boundary layer (DBL) is a thin (less than 1 mm) film of water covering the sediment. When solutes and particles are transported from the bottom boundary layer (BBL) to the DBL, molecular diffusion instead of turbulent eddy diffusion dominates the vertical transport [1][2][3]. The DBL limits exchange between the sediment and overlying water, and therefore becomes a bottleneck of diffusive vertical flux at the sediment-water interface (SWI). theoretically revealed that dynamic forcing in the BBL has a direct effect on DBL thickness and diffusion flux at the SWI. Under the influence of dynamics in the BBL, DBL thickness and flux vary significantly. Understanding how the DBL and diffusion transport responds to dynamic forcing is therefore crucial for accurately quantifying diffusion flux, and for estimating the replenishment of nutrients and secondary pollution in coastal waters. Modeling also requires numerical parameterization of diffusion flux as a function of BBL dynamics. The diffusive vertical flux of dissolved oxy...

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Oxygen transfer from flowing water to microbes in an organic sediment bed

Cited by 36 publications

References 22 publications

High-Schmidt-number mass transport mechanisms from a turbulent flow to absorbing sediments

High-Schmidt-number mass transport mechanisms from a turbulent flow to absorbing sediments

Short-term and seasonal variability of oxygen fluxes at the sediment–water interface in a riverine lake

Variable diffusion boundary layer and diffusion flux at sediment-water interface in response to dynamic forcing over an intertidal mudflat

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