Sabrina Cipullo

TL;DR: The resultant groundwater pollution risk indicated that the central regions of the plain have high and very high risk of nitrate pollution further confirmed by the exiting landuse map.

TL;DR: Three state-of-the-art ML models including support vector machine, random forest, and k-nearest neighbor were selected and it is highlighted that the kNN model is the best model because it has the lowest uncertainty based on the PICP statistic in both the QR and UNEEC methods.

TL;DR: This review focuses on the role of biotic and abiotic factors affecting bioavailability along with soil physicochemical properties and contaminant composition and the advantages and disadvantages of different extraction techniques.

TL;DR: The use of ML models could improve the understanding of rate-limiting processes affecting the freely available fraction (bioavailable) of contaminants in soil, therefore contributing to mitigate potential risks and to inform appropriate response and recovery methods.

TL;DR: How oral bioaccessibility, solid phase distribution and mineralogical analysis can provide insights into the distribution, fate and behaviour of PTE in waste streams from abandoned mine sites and inform human health risk posed by such sites is demonstrated.