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Developing a new Bayesian Risk Index for risk evaluation of soil contamination.

M T D Albuquerque1, S Gerassis2, C Sierra3

  • 1Instituto Politécnico de Castelo Branco, 6001-909 Castelo Branco, Portugal; CERENA/FEUP Research Center, Portugal.

The Science of the Total Environment
|June 19, 2017
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Summary
This summary is machine-generated.

Soil contamination by Potentially Toxic Elements (PTEs) from industrial and agricultural activities is a major concern. This study identifies high-risk areas needing remediation using a Bayesian Risk Index, pinpointing agricultural zones as critical.

Keywords:
Bayesian networksLocal G clusteringPotentially toxic elementsSequential Gaussian simulation

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Area of Science:

  • Environmental Geochemistry
  • Soil Science
  • Risk Assessment

Background:

  • Industrial and agricultural activities significantly degrade soil quality.
  • Potentially Toxic Elements (PTEs) pose risks to public health and ecosystems.
  • Identifying contaminated sites for remediation is essential for environmental protection.

Purpose of the Study:

  • To assess soil quality and identify areas requiring remediation in the Avilés Estuary.
  • To characterize Potentially Toxic Elements (PTEs) contamination using geochemical data and advanced analytical techniques.
  • To develop a Bayesian Risk Index (BRI) for mapping and quantifying soil contamination risk.

Main Methods:

  • Geochemical analysis of 230 soil samples for 14 elements across eight activity-defined zones.
  • Stratified systematic sampling to capture spatial variability.
  • Bayesian network analysis to identify key PTEs (Pb, As, Mn) and their correlations.
  • Geostatistical modeling (Sequential Gaussian Simulations) and Local G clustering to map risk and uncertainty.

Main Results:

  • High-risk soil contamination clusters were identified, primarily in agricultural/livestock zones at higher altitudes.
  • Low spatial uncertainty associated with high-risk areas indicates a clear need for remediation.
  • Atmospheric emissions from metallurgical industries were identified as a significant source of PTE soil contamination.

Conclusions:

  • The Bayesian Risk Index effectively identifies and maps soil contamination hotspots.
  • Agricultural areas, influenced by industrial atmospheric emissions, require urgent remediation efforts.
  • Integrated geochemical and geostatistical approaches are crucial for effective environmental risk assessment and management.