Arnob Ghosh , Md. Kamal Hossain , Kowshik Das Karmaker , Md. Zuel Rana , Md. Jobaer Alam , Abu Hena Muhammad Yousuf , Shamiha Shafinaz Shreya , Mahfujur Rahman , Afsana Hamid , Afroza Parvin , Mohammad Moniruzzaman , Mohammad Abdul Momin Siddique , Mahmudul Hasan
{"title":"Heavy metal pollution in the sundarbans mangrove ecosystem: a growing environmental concern","authors":"Arnob Ghosh , Md. Kamal Hossain , Kowshik Das Karmaker , Md. Zuel Rana , Md. Jobaer Alam , Abu Hena Muhammad Yousuf , Shamiha Shafinaz Shreya , Mahfujur Rahman , Afsana Hamid , Afroza Parvin , Mohammad Moniruzzaman , Mohammad Abdul Momin Siddique , Mahmudul Hasan","doi":"10.1016/j.hazadv.2025.100887","DOIUrl":null,"url":null,"abstract":"<div><div>The Sundarbans, the world's largest mangrove forest, hosts a diverse ecosystem with numerous plant and wildlife species. Nevertheless, this vibrant ecosystem is facing a severe threat from heavy metal pollution. To address the ecological and socioeconomic importance of the study area, this research investigated the dynamics of nine trace metals: arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb), and zinc (Zn) in water and sediment samples. The water and sediment samples were collected from 12 distinct sites in Sundarbans in the pre-monsoon, post-monsoon, and winter seasons. Seasonal and spatial patterns highlighted the concentration fluctuation, which was attributed to contamination levels, and identified the hotspot of the metals. The study found higher levels of As and Hg in all sites across all seasons in the water samples. The highest concentration of water was observed in the Pasur River during the pre-monsoon season. Seasonal dynamics also indicated that pre- and post-monsoon seasons are the most critical for ecosystem vulnerability. The contamination levels indicated by pollution indices such as the Degree of Contamination (C<sub>d</sub>), Heavy Metal Pollution Index (HPI), Nemerow Pollution Index (NPI), Geo-accumulation Index (I<sub>geo</sub>), and Pollution Load Index (PLI) show that the water is significantly polluted, predominantly by As and Hg. Ecological risk evaluation indicated more ecological risks in water than in sediment. The combined statistical analysis, including Principal Component Analysis (PCA), Hierarchical Cluster analysis (HCA), and Correlation Analysis, identified the prime sources of heavy metals in the water and sediment samples that are mixed geogenic–anthropogenic origins with seasonal variation. Industrial discharge, agriculture and port-related activities were identified as key anthropogenic sources, whereas natural weathering and sediment transport were also significant contributors of metals. The results of the study offer a broad overview of the present heavy metal configuration in water and sediment, which can be regarded as a benchmark for future monitoring programs. Policy frameworks may integrate the findings to adopt an effective mitigation policy to achieve conservation goals of the Sundarbans Mangrove.</div></div>","PeriodicalId":73763,"journal":{"name":"Journal of hazardous materials advances","volume":"20 ","pages":"Article 100887"},"PeriodicalIF":7.7000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of hazardous materials advances","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772416625002980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
The Sundarbans, the world's largest mangrove forest, hosts a diverse ecosystem with numerous plant and wildlife species. Nevertheless, this vibrant ecosystem is facing a severe threat from heavy metal pollution. To address the ecological and socioeconomic importance of the study area, this research investigated the dynamics of nine trace metals: arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb), and zinc (Zn) in water and sediment samples. The water and sediment samples were collected from 12 distinct sites in Sundarbans in the pre-monsoon, post-monsoon, and winter seasons. Seasonal and spatial patterns highlighted the concentration fluctuation, which was attributed to contamination levels, and identified the hotspot of the metals. The study found higher levels of As and Hg in all sites across all seasons in the water samples. The highest concentration of water was observed in the Pasur River during the pre-monsoon season. Seasonal dynamics also indicated that pre- and post-monsoon seasons are the most critical for ecosystem vulnerability. The contamination levels indicated by pollution indices such as the Degree of Contamination (Cd), Heavy Metal Pollution Index (HPI), Nemerow Pollution Index (NPI), Geo-accumulation Index (Igeo), and Pollution Load Index (PLI) show that the water is significantly polluted, predominantly by As and Hg. Ecological risk evaluation indicated more ecological risks in water than in sediment. The combined statistical analysis, including Principal Component Analysis (PCA), Hierarchical Cluster analysis (HCA), and Correlation Analysis, identified the prime sources of heavy metals in the water and sediment samples that are mixed geogenic–anthropogenic origins with seasonal variation. Industrial discharge, agriculture and port-related activities were identified as key anthropogenic sources, whereas natural weathering and sediment transport were also significant contributors of metals. The results of the study offer a broad overview of the present heavy metal configuration in water and sediment, which can be regarded as a benchmark for future monitoring programs. Policy frameworks may integrate the findings to adopt an effective mitigation policy to achieve conservation goals of the Sundarbans Mangrove.