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<p>Heavy metal (HMs) contamination of soil and its adverse impacts are a global concern. However, limited&#xa0;studies have investigated the spatial and seasonal variability of soil HMs in the Tasik Chini area. This study aimed to assess the distribution, source, and contamination of ten particular heavy metalic elements (Cr, Cu, Co, Ni, Cd, Ba, Pb, Mn, As, and Zn) in the surface soil of the Chini Lake. A total of 60 soil samples were collected from 10 sites during wet and dry seasons, and analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The degree of pollution was assessed using the CF and PLI, while PCA, CA, and correlation analysis provided insights into the prevalence and sources of HMs. Based on the findings, a notable mean concentration of HMs was measured in Ni (6.78 ± 8.37&#xa0;ppm), Mn (11.51 ± 21.08&#xa0;ppm), and Pb (3.23 ± 2.68&#xa0;ppm), compared to background values of 16&#xa0;μg/g, 460&#xa0;μg/g, and 31&#xa0;μg/g, respectively. Pollution indices revealed moderate contamination levels for Cd, Co, and Pb, especially in mining and agricultural areas.&#xa0;PCA indicates a variance of 50.27% with a strong relationship between As, Cu, Cd, Mn, Zn, Ba, and Pb, suggesting a common originating source of mining and agriculture activities. CA analysis highlights the higher contamination level in the mining area and downstream in the agricultural area among the sampling station groups. According to the results, human-made sources, including mining waste and agricultural chemicals, are the primary contributors of Cd, Pb, Cu, Zn, and As, whereas Ni, Cr, and Mn were mostly derived from natural geogenic backgrounds. This study concludes that seasonal inputs from mining and agriculture have a substantial impact on soil HMs contamination. Further studies are needed on ecological and socio-economic implications, including long-term monitoring, to support effective mitigation and management.</p>

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Assessment of spatial and seasonal variation in soil heavy metal contamination adjacent to Chini Lake, Malaysia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月16日

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  • Mir Sujaul Islam,
  • Faiz Ul Hassan,
  • Mohd Ekhwan Toriman,
  • Raheel Ahmad,
  • Muhammad Amjad Bashir,
  • Abdur Rehim,
  • Qurat-Ul-Ain Raza

摘要

Heavy metal (HMs) contamination of soil and its adverse impacts are a global concern. However, limited studies have investigated the spatial and seasonal variability of soil HMs in the Tasik Chini area. This study aimed to assess the distribution, source, and contamination of ten particular heavy metalic elements (Cr, Cu, Co, Ni, Cd, Ba, Pb, Mn, As, and Zn) in the surface soil of the Chini Lake. A total of 60 soil samples were collected from 10 sites during wet and dry seasons, and analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The degree of pollution was assessed using the CF and PLI, while PCA, CA, and correlation analysis provided insights into the prevalence and sources of HMs. Based on the findings, a notable mean concentration of HMs was measured in Ni (6.78 ± 8.37 ppm), Mn (11.51 ± 21.08 ppm), and Pb (3.23 ± 2.68 ppm), compared to background values of 16 μg/g, 460 μg/g, and 31 μg/g, respectively. Pollution indices revealed moderate contamination levels for Cd, Co, and Pb, especially in mining and agricultural areas. PCA indicates a variance of 50.27% with a strong relationship between As, Cu, Cd, Mn, Zn, Ba, and Pb, suggesting a common originating source of mining and agriculture activities. CA analysis highlights the higher contamination level in the mining area and downstream in the agricultural area among the sampling station groups. According to the results, human-made sources, including mining waste and agricultural chemicals, are the primary contributors of Cd, Pb, Cu, Zn, and As, whereas Ni, Cr, and Mn were mostly derived from natural geogenic backgrounds. This study concludes that seasonal inputs from mining and agriculture have a substantial impact on soil HMs contamination. Further studies are needed on ecological and socio-economic implications, including long-term monitoring, to support effective mitigation and management.