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
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
Received: 03 May 2022 – Discussion started: 30 May 2022
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.
Soil gas diffusivity and its controls are important issues in understanding greenhouse-gas dynamics of ecosystems. Knowledge gaps in this area are more obvious for organic soils than for mineral soils. Therefore the study of Kiuru et al. covers a relevant topic and principally aims and scopes of Biogeosciences. Although the study touches many several relevant aspects of the research area, nowhere a really satisfactory scientific depth is achieved. Therefore I suggest a complete revision of the manuscript with a stronger scientific focus on aspects that are well covered by the measurements and can be amended by a sufficient theoretical base.
Introduction: Here I miss any review about specific soil-physical features of peats in contrast to mineral soils. The state of the art, especially considering water retention but in parts also for gas diffusion would allow to formulate specific hypotheses for the application of diffusion models.
line 36: Consumption of O2 higher than the supply is not precise, you mean that diffusion cannot maintain O2 concentration above a critical level (which can be even zero in extreme cases).
line 52: This applies only when gas diffusion through the water is disregarded.
Material and methods: Description of standard methods can be substantially shortened (by 50%)
line 87: Reference soil group Histosol, is it order from UsSoilTax or reference soil group from WRB? Anyway, classification should be done somewhat deeper (WRB principal qualifiers).
line 104: Shrinkage has been measured, but not reported.
line 119: I wonder about the extremely long closing times (60 and 120 minutes). With the very high Ds values this could let to high measuring errors.
line 130: What was the exact criterion to discard measurements? How do you know that the other measurements were correct?
line 133: Why specific models have been chosen? The Millington-Kirk models have a mechanistic base with randomly disrupted capillary systems. The TPM-model is mostly empirical. Do you have ideas, which of these models are more sound to organic material?
Is there a reason why CO2 has been measured?
line 175 following, pore network:
It is an impressive mathematical toolbox that has been used. However, I miss any critical view (this could be also in the discussion) about the validity of the completely artifical pore network model. Peats consist of fibres, clusters with a possibly strong anisotropy due to the good compressibility. Why the throat-bubble model should reflect the pore network? Are these assumptions robust or do they easily create biases in estimations? This can be checked by simulations (sensitivity analysis) of exemplary datasets.
Results part:
line 251 following: The database is weak and results do not contain surprising or interesting patterns, so strongly shorten!
Shrinkage is a very critical issue but is completely disregarded in the measurements. I would suggest to correct epsilon for the reduced total volume.
Table 1: two digits are sufficient
Table 2: “significant differences” between what?
line 295: Hysteresis has been only modeled with a non-checked pore model with swelling-shrinkage disregarded. This is no relevant scientific contribution.
Discussion:
I would expect a critical view on the scientific progress including some theoretical thoughts that support the rather weak empirical base.
line 315 to 354: Is completely trivial and can be omitted, better is to check for critical issues in measurement quality.
line 363: The problem is, that the pore network model does have a real theoretical foundation.
line 393: See above, hysteresis problem/shrinkage swelling
Citation: https://doi.org/10.5194/bg-2022-112-RC2
Share
Petri Kiuru et al.
Petri Kiuru et al.
Viewed
Total article views: 256 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
195
52
9
256
1
2
HTML: 195
PDF: 52
XML: 9
Total: 256
BibTeX: 1
EndNote: 2
Views and downloads (calculated since 30 May 2022)
Cumulative views and downloads
(calculated since 30 May 2022)
Viewed (geographical distribution)
Total article views: 235 (including HTML, PDF, and XML)
Thereof 235 with geography defined
and 0 with unknown origin.
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.
Peatlands are large carbon stocks. Emissions of carbon dioxide and methane from peatlands may...