Ecological risk assessment and source apportionment of potentially toxic elements in an emerging mining zone region of northwestern Ghana

  • Samuel Dzidefo Sagoe
  • , Daniel Kwayisi
  • , Seidu Alidu
  • , Ebenezer Ebo Yahans Amuah
  • , Millicent Obeng Addai
  • , Obed Fiifi Fynn
  • , Raymond Webrah Kazapoe

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The expansion of artisanal and small-scale gold mining (ASGM) in northern Ghana, driven by rising global gold prices, has raised concerns over soil contamination by potentially toxic elements (PTEs). This study aimed to assess the spatial distribution, pollution levels, and ecological risks associated with PTEs in an emerging mining area in northwestern Ghana. A total of 704 surface soil samples were collected and analysed using Energy Dispersive X-ray Fluorescence (ED-XRF) spectroscopy to quantify 8 PTEs: As, Pb, Cr, Zn, Ni, Cu, Co, and V. The results indicated elevated concentrations of Vanadium (V: 2.35–372.84 mg/kg; mean = 125.14 mg/kg), Chromium (Cr: 8.10–331.99 mg/kg; mean = 101.84 mg/kg), and Zinc (Zn: 4.15–231.43 mg/kg; mean = 77.45 mg/kg), which dominated the soil geochemistry. Arsenic and Lead showed lower mean concentrations (As: 11.82 mg/kg; Pb: 12.32 mg/kg) but presented higher ecological risks due to their toxicity. Multivariate analyses using Self-Organising Maps (SOM) and Spectral Clustering revealed two main elemental clusters; Cluster 1 (lithogenic origin) and Cluster 2 (anthropogenic influence). Pollution assessment through the geo-accumulation index (Igeo) and potential ecological risk index (RI) indicated moderate pollution levels, with hotspots around Chasea and Dagbori. Although the overall pollution risk remains moderate compared to Ghana's southern mining zones, the emergence of spatially concentrated contamination suggests an early warning signal. These highlight the need for preventive environmental monitoring and inclusive policy action to preserve soil health in Ghana's fragile northern ecosystems.

Original languageEnglish
Article number106840
JournalResults in Engineering
Volume27
DOIs
Publication statusPublished - Sep 2025

Keywords

  • Ecological risk indices
  • Galamsey
  • Heavy metal pollution
  • Machine learning
  • Pollution indices

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