文章基本信息

标题：Risk Assessment of Heavy Metal Concentrations in Sediments of Matang Mangrove Forest Reserve
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作者：Waseem Razzaq Khan ; Syaizwan Zahmir Zulkifli ; Mohamad Roslan bin Mohamad Kasim 等
期刊名称：Tropical Conservation Science
电子版ISSN：1940-0829
出版年度：2020
卷号：13
页码：1-12
DOI：10.1177/1940082920933122
出版社：SAGE Publications
摘要：Matang Mangrove Forest Reserve (MMFR) is one of the most productive and managed forests in the world. On the other hand, it has become a concern whether MMFR is being degraded as a result of exposure to industrial pollution. Industries located around MMFR dispose effluents contaminated by heavy metals. This study was conducted to analyze heavy metal contamination and risk assessment status in MMFR sediments. Sediment samples from six compartments were collected based on age and location of the mangrove plantation. Total metal digestion and modified sequential extraction were performed to estimate the concentration of heavy metals. Based on the estimation, risk assessment code, geo-accumulation index, pollution load index, and contamination factor were computed to classify the compartments according to their contamination and pollution levels. Organic matter and sediment texture (silt, clay, and sand content) were also analyzed to find its correlation with heavy metals. According to the results, high concentrations for Copper, Nickel, and Cadmium were observed in Compartment 42, while Compartment 18 and Compartment 74 showed higher concentrations for Zinc and Lead. Heavy metals showed weak positive correlation with clay and silt, but weak negative correlation with sand. For organic matter, only Zinc showed statistically significant but weak negative correlation. Risk assessment code, geo-accumulation index, pollution load index, and contamination factor categorized the compartments into unpolluted to moderately polluted. Based on the study outcomes, it can be concluded that MMFR, although acquiring industrial discharge, is not with a high risk of heavy metal contamination.
关键词：MMFR; heavy metals; risk assessment code; geo-accumulation index; contamination