A Comparative GIS tree‑pollution analysis between arsenic, chromium, mercury, and uranium contents in soils of urban and industrial regions in Qatar

This study compared the applicability of several geographic information systems (GIS) regression tree-based models (n = 136) to precisely define the most influencing environmental predictor parameters on arid soils. The study focused on the accumulation of arsenic, chromium, mercury, and uranium in the arid soils of Qatar using GIS tools. The rates of the built reference trees (based on environmental parameters) vary among chosen toxic metals as follows: Hg (80%), U (77%), As (72%), and Cr (70%); and this affects considerably the developed correlations (reflected as relative importance in %) between these toxic metals and the chosen environmental parameters. These parameters influence differently the investigated As/Cr/Hg/U, with higher quantitative impact (importance varying according to the metal into question) of anthropogenic parameters (distance to environmental hotspots 85–90%, land cover/use 78–82%, and proximity to roads 62–82%) than for the geopedological (soil type 30–76%, parent material 17–60%, and distance to geological structures 12–42%) and hydromorphological (elevation 7–53%, slope gradient 10–41%, distance to drainage line 15–30%, slope gradient 0–5%, and slope aspect 0–3%) parameters. The results can be used to prioritize the choice of remediation measures, and can be applied to other arid areas sharing analogous environmental/socio-economic conditions and pollution causes.