Sorption modelling of crude oil-contaminated soils using a derived spectral index

Theoretical models to describe and evaluate sorption of hydrocarbons on soil particles are well documented but experimental results in the literature are scarce. This study describes the use of a spectral index to evaluate sorption phenomena in oil-contaminated soils at micro and macro levels. Experiments involved oil-dosing from 0.25 mL to 4 mL and the application of a spectral index to estimate the sorption capacity of different soils based on change in statistically derived Critical Point (CP). Results show that sorption of oil varies with soil type, specifically the proportion of clay in a soil/sediment and the clay species, in the order smectite > illite > kaolinite. In support of theoretical models, this work proposes a model from experimental data that explains observed phenomena of soil-oil interaction with changing soil composition. The location and prominence of the CP is also strongly affected by soil moisture, particularly in coarse-grained soils, potentially providing insight to soil-oil–water interaction. The methods developed using a simple synthetic crude provide potential to explore other contamination scenarios including different soil compositions, types of petroleum products and different environmental controls.