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Experimental and modeling study demonstrates non-monotonic moisture effects on organic vapor flux in soils, highlighting optimal environmental conditions for subsurface detection.
Molecular transport of low-volatility organic vapors through unsaturated porous media is governed by the coupled effects of diffusion, sorption, and pore structure, yet the relative roles of these processes remain insufficiently quantified. In this work, we develop a physics-based model describing vapor migration from a subsurface source to the soil surface by explicitly accounting for moisture-dependent sorption, air-filled porosity, and pore clogging by fine particles. The model predicts that soil moisture affects vapor transport through two competing mechanisms: thin water films progressively suppress gas–solid sorption, thereby increasing the effective diffusion coefficient, whereas further wetting reduces the connectivity of air-filled pores and ultimately blocks gas-phase transport. As a consequence, vapor migration exhibits a non-monotonic dependence on soil moisture, with a distinct optimum for surface vapor flux. The model further predicts that fine particles substantially decrease vapor transport by reducing pore connectivity, while lower temperatures suppress migration through both reduced molecular diffusivity and enhanced sorption. Laboratory experiments using representative low-volatility energetic compounds through sand with controlled moisture content and particle composition confirmed all major qualitative predictions of the model, including enhanced transport at intermediate moisture, suppression under dry, dusty and highly saturated conditions, and strong temperature dependence. Although energetic compounds were used as representative low-volatility substances, the proposed framework is generally applicable to molecular transport of trace organic vapors in unsaturated porous media and provides a quantitative basis for predicting environmental conditions under which subsurface sources can be detected by surface vapor measurements.
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Kudryashova et al. (2026) studied this question.
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