30 May 2022
30 May 2022
Status: this preprint is currently under review for the journal BG.

Pore network modeling as a new tool for determining gas diffusivity in peat

Petri Kiuru1, Marjo Palviainen2, Arianna Marchionne3, Tiia Grönholm4, Maarit Raivonen5, Lukas Kohl6,7, and Annamari Laurén1 Petri Kiuru et al.
  • 1School of Forest Sciences, Faculty of Science and Forestry, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland
  • 2Department of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 Helsinki, Finland
  • 3Department of Mathematics and Statistics, University of Helsinki, P.O. Box 68, 00014 Helsinki, Finland
  • 4Finnish Meteorological Institute (FMI), Erik Palménin aukio 1, 00560 Helsinki, Finland
  • 5Institute for Atmospheric and Earth System Research (INAR)/Physics, Faculty of Science, University of Helsinki, P.O. Box 68, 00014 Helsinki, Finland
  • 6Department of Agricultural Sciences, University of Helsinki, P.O. Box 56, 00014 Helsinki, Finland
  • 7Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, Faculty of Agriculture and Forestry, University of Helsinki, P.O. Box 56, 00014 Helsinki, Finland

Abstract. Peatlands are globally significant carbon stocks and may become major sources of greenhouse gasses (GHG) carbon dioxide and methane in changing climate and under anthropogenic management pressure. Diffusion is the dominant gas transport mechanism in peat, and therefore, a proper knowledge of the soil gas diffusion coefficient is important for the estimation of GHG emissions from peatlands. Pore network modeling (PNM) is a potential tool for the determination of gas diffusivity in peat, as it explicitly connects the peat microstructure and the characteristics of the peat pore network to macroscopic gas transport properties. In the present work, we extracted macropore networks from three-dimensional X-ray micro-computed tomography (µCT) images of peat samples and simulated gas diffusion along the networks using PNM. These results were compared to soil gas diffusion coefficients determined from the same samples in the laboratory using the diffusion chamber method. The measurements and simulations were conducted for peat samples from three depths. The soil gas diffusion coefficients were determined under varying water contents adjusted in a pressure plate apparatus. We also assessed the applicability of commonly used gas diffusivity models to peat. The laboratory measurements showed a decrease in gas diffusivity with depth due to a decrease in air-filled porosity and pore space connectivity. However, gas diffusivity remained relatively high close to saturation, which may indicate that the structure of the macropore network is such that it enables the presence of connected diffusion pathways through the peat matrix even in wet conditions. The gas diffusivity models were not very successful in predicting the soil gas diffusion coefficient. This may indicate that the microstructure of peat differs considerably from the structure of mineral soils and other kinds of porous materials, for which the models have been constructed and calibrated. By contrast, the pore network simulations reproduced the laboratory-determined soil gas diffusion coefficients rather well. Thus, the combination of the µCT and PNM methods may offer a promising alternative to the traditional estimation of soil gas diffusivity through laboratory measurements.

Petri Kiuru et al.

Status: open (until 27 Jul 2022)

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  • RC1: 'Comment on bg-2022-112', Haojie Liu, 30 Jun 2022 reply

Petri Kiuru et al.

Petri Kiuru et al.


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Short summary
Peatlands are large carbon stocks. Emissions of carbon dioxide and methane from peatlands may increase due to changes in management and climate. We studied the variation in the gas diffusivity of peat with depth using pore network simulations and laboratory experiments. Gas diffusivity was found to be lower in deeper peat with smaller pores and lower pore connectivity. However, gas diffusivity remained fairly high in wet conditions, which may reflect the distinctive structure of peat.