Estimating persistent oil contamination in tropical region using vegetation indices and random forest regression.

The persistence of soil contamination after cessation of oil activities remains a major environmental issue in tropical regions. The assessment of the contamination is particularly difficult on vegetated sites, but promising advances in reflectance spectroscopy have recently emerged for this purpose. This study aimed to exploit vegetation reflectance for estimating low concentrations of Total Petroleum Hydrocarbons (TPH) in soils. A greenhouse experiment was carried out for 42 days on Cenchrus alopecuroides (L.) under realistic tropical conditions. The species was grown on oil-contaminated mud pit soils from industrial sites, with various concentrations of TPH. After 42 days, a significant decrease in plant growth and leaf chlorophyll and carotenoid contents was observed for plants exposed to 5-19 g kg-1 TPH in comparison to the controls (p < 0.05). Conversely, pigment contents were higher for plants exposed to 1 g kg-1 TPH (hormesis phenomenon). These modifications proportionally affected the reflectance of C. alopecuroides at leaf and plant scales, especially in the visible region around 550 and 700 nm. 33 vegetation indices were used for linking the biochemical and spectral responses of the species to oil using elastic net regressions. The established models indicated that chlorophylls a and b and ß-carotene were the main pigments involved in the modifications of reflectance (R2 > 0.7). The same indices also succeeded in estimating the concentrations of TPH using random forest regression, at leaf and plant scales (RMSE = 1.46 and 1.63 g kg-1 and RPD = 5.09 and 4.44, respectively). Four out of the 33 indices contributed the most to the models (>75%). This study opens up encouraging perspectives for monitoring the cessation of oil activities in tropical regions. Further researches will focus on the application of our approach at larger scale, on airborne and satellite imagery.

Application of PROSPECT for estimating total petroleum hydrocarbons in contaminated soils from leaf optical properties.

Recent advances in hyperspectral spectroscopy suggest making use of leaf optical properties for monitoring soil contamination in oil production regions by detecting pigment alterations induced by Total Petroleum Hydrocarbons (TPH). However, this provides no quantitative information about the level of contamination. To achieve this, we propose an approach based on the inversion of the PROSPECT model. 1620 leaves from five species were collected on a site contaminated by 16 to 77 g.kg-1 of TPH over a 14-month period. Their spectral signature was measured and used in PROSPECT model inversions to retrieve leaf biochemistry. The model performed well for simulating the spectral signatures (RMSE < 2%) and for estimating leaf pigment contents (RMSE ≤ 2.95 µg.cm-2 for chlorophylls). Four out of the five species exhibited alterations in pigment contents when exposed to TPH. A strong correlation was established between leaf chlorophyll content and soil TPH concentrations (R2 ≥ 0.74) for three of them, allowing accurate predictions of TPH (RMSE =3.20 g.kg-1 and RPD = 5.17). The accuracy of predictions varied by season and improved after the growing period. This study demonstrates the capacity of PROSPECT to estimate oil contamination and opens up promising perspectives for larger-scale applications.