Exploring Soil Pollution Patterns Using Self-Organizing Maps.

Area of Science:

• Geochemistry
• Environmental Science
• Soil Science

Background:

• Bedrock geochemistry is the primary determinant of soil elemental concentrations.
• Anthropogenic factors, particularly in urban areas, can influence soil composition and pose risks to food chains.
• Understanding elemental sources is crucial for assessing soil quality and environmental health.

Purpose of the Study:

• To analyze topsoil elemental concentrations in Cosenza and Rende, southern Italy.
• To discriminate between natural geochemical sources and anthropogenic inputs affecting soil composition.
• To define the soil quality status based on elemental associations.

Main Methods:

• Inductively coupled plasma mass spectrometry (ICP-MS) was used to analyze 25 elements in topsoil samples.
• Statistical and geostatistical methods were applied for monitoring elemental concentrations.
• The Self-Organizing Maps (SOM) algorithm was employed for unsupervised classification of elemental data.

Main Results:

• Seven distinct clusters of elemental associations were identified in the topsoil.
• Elemental associations were predominantly controlled by parent material and soil-forming processes.
• Specific elemental clusters showed evidence of anthropogenic influence, particularly in urban-influenced areas.

Conclusions:

• Geochemical bedrock composition is the main driver of soil elemental patterns.
• While natural factors dominate, localized anthropogenic inputs can modify soil elemental concentrations.
• The study provides insights into soil quality and potential environmental risks in the surveyed urban and peri-urban areas.