Spatial Distribution and Mobility Assessment of Carcinogenic Heavy Metals in Soil Profiles Using Geostatistics and Random Forest, Boruta Algorithm

摘要: In third world countries, industries mainly cause environmental contamination due to lack of policies or oversight during their implementation. The Sheikhupura industrial zone, which includes such as tanneries, leather, chemical, textiles, and colour dyes, contributes massive amounts untreated effluents that are released directly into drains used for the irrigation crops vegetables. This practice causes not only soil with an excessive amount heavy metals, but is also considered a source toxicity in food chain, i.e., bioaccumulation plants ultimately human body organs. objective this research study was assess spatial distribution metals chromium (Cr), cadmium (Cd), lead (Pb), at three depths using geostatistics selection significant contributing variables Random Forest (RF) function Boruta Algorithm. A total 60 sampling locations were selected area collect samples (180 samples) (0–15 cm, 15–30 60–90 cm). analysed physico-chemical properties, saturation, electrical conductivity (EC), organic matter (OM), pH, phosphorus (P), potassium (K), Cr, Cd, Pb standard laboratory procedures. data comprehensive statistics geostatistical techniques. correlation coefficient matrix between properties revealed (EC) had (p ≤ 0.05) negative Pb. RF Algorithm employed depth classifier ranked parameters (Cr, Pb, EC, P) relation depth. mobility factor indicated leachate percentage different vertical soil. pattern variability regarding subsoil horizons. Significant discovered near Deg drain Bed Nallah irrigated high Cr topsoil contamination, homogenous Cd < 0.05). Consequently, management strategies can be adopted reduce load