Gas Diffusion Coefficient of Undisturbed Peat Soils

Iiyama, Ippei; Hasegawa, Shuichi

doi:10.1111/j.1747-0765.2005.tb00049.x

Cited by 34 publications

(30 citation statements)

References 13 publications

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“…However, by changing the values of A and B, the model (Eq. (4)) was able to predict measured diffusion coefficients reported by Iiyama and Hasegawa [10] and Moldrup et al [11]. These results are presented in Fig.…”

Section: Development Of a New Empirical Relationshipsupporting

confidence: 63%

“…7. The low diffusion coefficients in undisturbed organic soil could be the result of the presence of more tortuous pathways as reported by Iiyama and Hasegawa [10]. However, by modifying the values of the coefficients A and B, the new model was able to predict the diffusion coefficient in undisturbed soil.…”

Section: Development Of a New Empirical Relationshipmentioning

confidence: 71%

“…Investigators have studied the diffusion properties of soil and undisturbed natural organic rich peat soil [10] and agricultural soil [11], but not re-compacted compost and compost-soil mixtures. The MBFs are constructed with loose soil and compost mixtures…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Methane diffusion coefficient in compost and soil–compost mixtures in gas phase biofilter

Pokhrel¹,

Hettiaratchi²,

Kumar³

2011

Chemical Engineering Journal

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Section: Development Of a New Empirical Relationshipsupporting

confidence: 63%

Section: Development Of a New Empirical Relationshipmentioning

confidence: 71%

See 1 more Smart Citation

Methane diffusion coefficient in compost and soil–compost mixtures in gas phase biofilter

Pokhrel¹,

Hettiaratchi²,

Kumar³

2011

Chemical Engineering Journal

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“…It is possible that the uncertainty in the soil CO 2 efflux calculation is attributed mostly to the model used to estimate ξ, as reported by Jassal et al (2005), who found that Penman (1940) and Marshall (1959) models overestimated diffusivities while the Millington and Quirk (1961) and Moldrup et al (1999) models underestimated them at very low air‐filled porosity. Iyamada and Hasegawa (2005) also showed that the Millington and Quirk (1961) model underestimated measured diffusivity for low air‐filled porosity and overestimated them for high air‐filled porosity. Sallam et al (1984) and Jin and Jury (1996) pointed out the same kind of erroneous estimation when the Millington and Quirk (1961) model was used.…”

Section: Resultsmentioning

confidence: 87%

Assessment of the soil CO<sub>2</sub> gradient method for soil CO<sub>2</sub> efflux measurements: comparison of six models in the calculation of the relative gas diffusion coefficient

Pingintha

Leclerc

Beasley

et al. 2010

Tellus B: Chemical and Physical Meteorology

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This paper uses a refined soil gradient method to estimate soil CO2 efflux. Six different models are used to determine the relative gas diffusion coefficient (ξ). A weighted harmonic averaging is used to estimate the soil CO2 diffusion coefficient, yielding a better estimate of soil CO2 efflux. The resulting soil CO2 efflux results are then compared to the soil CO2 efflux measured with a soil chamber. Depending on the choice of ξ model used, the estimated soil CO2 efflux using the gradient method reasonably approximates the efflux obtained using the soil chamber method. In addition, the estimated soil CO2 efflux obtained by this improved method is well described by an exponential function of soil temperature at a depth of 0.05 m with the temperature sensitivity (Q10) of 1.81 and a linear function of soil moisture at a depth of 0.12 m, in general agreement with previous findings. These results suggest that the gradient method is a practical cost‐effective means to measure soil CO2 emissions. Results from the present study suggest that the gradient method can be used successfully to measure soil CO2 efflux provided that proper attention is paid to the judicious use of the proper diffusion coefficient.

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“…Simulation of diffusion in the porous water-filled or air-filled peat takes into account the reduction in the diffusivity compared with pure water or air (see, e.g., Iiyama and Hasegawa, 2005). The diffusion coefficients used in this study are listed in Appendix A.…”

Section: Diffusion In the Peatmentioning

confidence: 99%

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

et al. 2017

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Abstract. Wetlands are one of the most significant natural sources of methane (CH 4 ) to the atmosphere. They emit CH 4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH 4 , in addition to carbon dioxide (CO 2 ). Production of CH 4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH 4 emissions are thus needed for upscaling observations to estimate present CH 4 emissions and for producing scenarios of future atmospheric CH 4 concentrations. Aiming at a CH 4 model that can be added to models describing peatland carbon cycling, we composed a model called HIMMELI that describes CH 4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation, and water table depth (WTD), it simulates the concentrations and transport of CH 4 , CO 2 , and oxygen (O 2 ) in a layered one-dimensional peat column. Here, we present the HIMMELI model structure and results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and demonstrate that HIMMELI outputs realistic fluxes by comparing modeled and measured fluxes at two peatland sites. As HIMMELI describes only the CH 4 -related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH 4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that (1) the model is flexible and robust and thus suitable for different environments; (2) the simulated CH 4 emissions largely depend on the prescribed rate of anoxic respiration; (3) the sensitivity of Published by Copernicus Publications on behalf of the European Geosciences Union. 4666M. Raivonen et al.: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands the total CH 4 emission to other input variables is mainly mediated via the concentrations of dissolved gases, in particular, the O 2 concentrations that affect the CH 4 production and oxidation rates; (4) with given input respiration, the peat column description does not significantly affect the simulated CH 4 emissions in this model version.

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Gas Diffusion Coefficient of Undisturbed Peat Soils

Cited by 34 publications

References 13 publications

Methane diffusion coefficient in compost and soil–compost mixtures in gas phase biofilter

Methane diffusion coefficient in compost and soil–compost mixtures in gas phase biofilter

Assessment of the soil CO<sub>2</sub> gradient method for soil CO<sub>2</sub> efflux measurements: comparison of six models in the calculation of the relative gas diffusion coefficient

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

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