Incorporating effects of surface roughness and probing molecule size for estimation of soil specific surface area

TL;DR

This paper presents a theoretical method to estimate soil specific surface area by incorporating surface roughness and probe molecule size, using fractal concepts and soil data, improving accuracy over traditional methods.

Contribution

It introduces a novel approach combining fractal analysis and soil measurements to better estimate soil SSA considering surface roughness and probe size effects.

Findings

Estimated SSA with RMSE of 16.8 and 30.1 m2/g for two soil datasets.

Method captures effects of surface roughness and particle size distribution.

Provides a more accurate SSA estimation compared to traditional methods.

Abstract

The pore-solid interface and its characteristics play a key role in chemical interactions between minerals in the solid soil matrix and the liquid in pore space and, consequently, solute transport in soils. Specific surface area (SSA), typically measured to characterize the pore-solid interface, depends not only on the particles size distribution, but also particle shapes and surface roughness. In this note, we investigate the effects of surface roughness and probing molecule size on SSA estimation, employ concepts from fractals, and theoretically estimate specific surface area from particle size distribution and water retention curve (WRC). The former is used to characterize the particle sizes and the latter to approximately quantify the pore-solid interface roughness by determining the surface fractal dimension Ds. To evaluate our approach, we use five Washington and twenty one Arizona soils for which both particle size distributions and water retention curves were accurately measured over a wide range of particle sizes and matric potentials. Comparison with the experiments show that the proposed method estimates the SSA reasonably well with root mean square error RMSE = 16.8 and 30.1 m2/g for the Washington and Arizona datasets, respectively.