Monitoring Lead Contamination by Integrating Environmental Indices and Random Forest-Based Digital Soil Mapping in Shiraz Urban Watershed, Iran

Mousavi, Amin; Enjavinezhad, Sayyed Mahmoud; Naghibi, Seyed Javad; Alavipanah, Seyed Kazem; Baghernejad, Majid; Malekian, Ashraf

doi:10.22059/poll.2025.394624.2911

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	Monitoring Lead Contamination by Integrating Environmental Indices and Random Forest-Based Digital Soil Mapping in Shiraz Urban Watershed, Iran
Pollution
دوره 11، شماره 4، دی 2025، صفحه 1462-1472 اصل مقاله (2.11 M)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22059/poll.2025.394624.2911
نویسندگان
Amin Mousavi^* ¹؛ Sayyed Mahmoud Enjavinezhad²؛ Seyed Javad Naghibi²^{، 3}؛ Seyed Kazem Alavipanah⁴؛ Majid Baghernejad²؛ Ashraf Malekian⁵
¹Department of Soil Science, Ferdowsi University of Mashhad, P.O. Box 9177948978, Mashhad, Iran
²Department of Soil Sciences, Shiraz University, P.O. Box 71441-13131 Shiraz, Iran
³Head of Research & Extension Office, Landscape & Green Spaces Organization of Shiraz Municipality, P.O. Box 45366-78 Shiraz, Iran
⁴Department of Remote Sensing & GIS, University of Tehran, P.O. Box 14155-6465, Tehran, Iran
⁵Department of Agriculture, Payame Noor University, P.O. Box 19395-4697, Tehran, Iran
چکیده
The rapid increase in population and economic expansion has resulted in the infiltration of environmental pollutants, particularly heavy metals, into the soil, presenting a substantial threat to public well-being and reliability of food security. Consequently, awareness and evaluation of these elements are key to assessing soil quality and related risks. In this study, machine learning modeling (random forest model) and digital mapping were employed to quantify and model lead (Pb) contamination using various environmental indices in a section of the urban watershed of Shiraz. For this purpose, 148 soil samples were systematically gathered from a depth of 0 to 20 cm utilizing a randomized sampling approach. After sample preparation, the total Pb content in the soil was determined applying standard analytical methods. Pb contamination risk assessment was conducted using three environmental indices: Geo-Accumulation Index (Igeo), Enrichment Factor (EF), and Contamination Factor (Cƒ). The results indicated that all analyzed samples exhibited total Pb concentrations (mean: 7.78 mg/kg) below the recommended standard levels for Iran. Based on the Igeo (range: 1.54–4.72), the samples were categorized as moderately to severely contaminated. The EF (range: 4.35–39.65) classified the samples as moderately, highly, and extremely enriched, while the Cƒ (range: 3.37–29.63) placed the samples in the high to very high contamination category. The interpretation of environmental indices confirmed low to moderate levels of Pb contamination, primarily influenced by anthropogenic activities. Therefore, to ensure sustainable food security, continuous monitoring of Pb concentration variations in the studied soils is essential.
کلیدواژه‌ها
Environmental pollutants؛ Machine Learning (ML)؛ Digital mapping؛ Contamination risk

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Monitoring Lead Contamination by Integrating Environmental Indices and Random Forest-Based Digital Soil Mapping in Shiraz Urban Watershed, Iran