Accurate predic on of gas diff usivity (D p /D o ) and air permeability (k a ) and their variaons with air-fi lled porosity (ε) in soil is cri cal for simula ng subsurface migra on and emission of climate gases and organic vapors. Gas diff usivity and air permeability measurements from Danish soil profi le data (total of 150 undisturbed soil samples) were used to inves gate soil type and density eff ects on the gas transport parameters and for model development. The measurements were within a given range of matric poten als (−10 to −500 cm H 2 O) typically represen ng natural fi eld condi ons in subsurface soil. The data were regrouped into four categories based on compac on (total porosity Φ <0.4 or >0.4 m 3 m −3 ) and soil texture (volume-based content of clay, silt, and organic ma er <15 or >15%). The results suggested that soil compac on more than soil type was the major control on gas diff usivity and to some extent also on air permeability. We developed a density-corrected (D-C) D p (ε)/D o model as a generalized form of a previous model for D p / D o at −100 cm H 2 O of matric poten al (D p , 100 /D o ). The D-C model performed well across soil types and density levels compared with exis ng models. Also, a power-law k a model with exponent 1.5 (derived from analogy with a previous gas diff usivity model) used in combina on with the D-C approach for k a,100 (reference point) seemed promising for k a (ε) predic ons, with good accuracy and minimum parameter requirements. Finally, the new D-C model concept for gas diff usivity was extended to bimodal (aggregated) media and performed well against data for uncompacted and compacted volcanic ash soil.Abbrevia ons: D-C, density-corrected; GMP, generalized macroporosity; MQ, Millington and Quirk; OM, organic ma er; WLR, water-induced linear reduc on.
The soil‐gas diffusion is a primary driver of transport, reactions, emissions, and uptake of vadose zone gases, including oxygen, greenhouse gases, fumigants, and spilled volatile organics. The soil‐gas diffusion coefficient, Dp, depends not only on soil moisture content, texture, and compaction but also on the local‐scale variability of these. Different predictive models have been developed to estimate Dp in intact and repacked soil, but clear guidelines for model choice at a given soil state are lacking. In this study, the water‐induced linear reduction (WLR) model for repacked soil is made adaptive for different soil structure conditions (repacked, intact) by introducing a media complexity factor (Cm) in the dry media term of the model. With Cm = 1, the new structure‐dependent WLR (SWLR) model accurately predicted soil‐gas diffusivity (Dp/Do, where Do is the gas diffusion coefficient in free air) in repacked soils containing between 0 and 54% clay. With Cm = 2.1, the SWLR model on average gave excellent predictions for 290 intact soils, performing well across soil depths, textures, and compactions (dry bulk densities). The SWLR model generally outperformed similar, simple Dp/Do models also depending solely on total and air‐filled porosity. With Cm = 3, the SWLR performed well as a lower‐limit Dp/Do model, which is useful in terms of predicting critical air‐filled porosity for adequate soil aeration. Because the SWLR model distinguishes between and well represents both repacked and intact soil conditions, this model is recommended for use in simulations of gas diffusion and fate in the soil vadose zone, for example, as a key element in developing more accurate climate change models.
Soil heterogeneity has a distinct effect on surface methane concentrations. Methane transport can be adequately represented with a Fickian model framework. Saturation has a dominant effect over soil texture on gas migration through soil.
Grazed pastures are recognized as a dominant source of nitrous oxide (N2O), a highly potent greenhouse gas. Studies have examined soil physical controls on N2O emissions, including soil moisture status. Limited attempts to link N2O emissions with soil‐diffusivity (Dp/Do), using repacked soil cores, have shown peak N2O emissions to align with a relatively narrow window of Dp/Do, despite a relatively wide range in water‐filled pore space (WFPS), across a range of soil bulk densities. Such detailed studies have not been performed with intact soil cores. We investigated the effects of soil‐water characteristic (SWC) and Dp/Do on N2O emissions from intact soil samples, retrieved at three depths (0–5, 5–10, 10–15 cm) from three perennial pasture sites that received a KNO3 solution (1800 mg, N mL−1). We observed distinct fingerprints of SWC and Dp/Do, which showed clear effects of soil structure on diffusion‐controlled gas emissions. Depth‐wise variation in soil moisture diminished as the soil was subjected to higher matric potential (> ∼ ‐100 kPa). Variation in Dp/Do, was more pronounced in the dry soil (> ∼ ‐1000 kPa), being largely constrained by soil moisture in wet soil (∼ ‐100 kPa) with little depth‐wise variation. Measured N2O fluxes peaked within narrow ranges of WFPS and Dp/Do, 0.90–0.95 and 0.005–0.01, respectively. The value of Dp/Do can be determined using parametric models and presents a pasture management (e.g., irrigation, soil physical disturbance such as pasture renovation and animal treading)) tool to minimize N2O emissions: soil Dp/Do should be maintained above a range of 0.005–0.01 to minimize N2O emissions. Core Ideas Peak N2O fluxes from intact soil cores occurred when diffusivity ranged from 0.005–0.01 This peak N2O flux diffusivity range was 0.005–0.01 regardless of soil or depth (0–15 cm) The diffusivity range for peak N2O flux equalled that observed in repacked soil cores Diffusivity values are readily determined and add to the suite of soil management tools
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.