Spatial Distribution, Risk Index, and Correlation of Heavy Metals in the Chuhe River (Yangtze Tributary): Preliminary Research Analysis of Surface Water and Sediment Contamination

支流 污染 环境化学 环境科学 沉积物 污染 水质 Mercury(编程语言) 地表水 地表径流 水文学(农业) 环境工程 化学 地质学 生态学 地理 生物 地图学 古生物学 有机化学 岩土工程 程序设计语言 计算机科学
作者
Adharsh Rajasekar,Raphinos Tackmore Murava,Eyram Norgbey,Xiwen Zhu
出处
期刊:Applied sciences [MDPI AG]
卷期号:14 (2): 904-904
标识
DOI:10.3390/app14020904
摘要

This comprehensive study aimed to evaluate the water quality and sediment contamination in the Chuhe River in Nanjing. The spatial assessment of 10 samples collected in September highlighted that, in surface water, Copper (Cu) > Nickel (Ni) > Zinc (Zn) > Chromium (Cr) > Lead (Pb) > Arsenic (As) > Cadmium (Cd) > Mercury (Hg), whereas in sediments, Zn > Cr > Cu > Pb > Ni > As > Cd > Hg. The coefficient of variation (CV) for Ni and Zn in surface water was >15, whereas As, Cu, Pb, and Ni had a CV that was higher than 15 in sediments, indicating variability in contamination sources. The Pollution Load Index values ranged between 2.16 and 3.05, reflecting varying contamination levels across samples. The Geoaccumulation Index data also showed moderate-to-considerable contamination, especially for elements such as Cd and Cu. Correlation analyses in water and sediments unearthed significant relationships, with notable links between Cu and Pb in the water and strong correlations between As and Cu and between Cr and Ni in sediments. In sediments, Total Nitrogen and Phosphorus were significantly correlated with As, Cu, Pb, and Ni. The Potential Ecological Response Index for sediments indicated that they are at medium to high risk (307.47 ± 33.17) and could be potentially detrimental to aquatic life in the tributary. The tributary, influenced by agricultural runoff, residential areas, and other anthropogenic activities, showed that despite Nemerow pollution index values for water samples being below 1, sediment analysis indicated areas of concern. Principal Component Analysis (PCA) was conducted to identify the potential sources of heavy metal contamination. In surface water, shared negative loadings on PC 1 (60.11%) indicated a unified influence, likely from agricultural runoff, while PC 2 (14.26%) revealed additional complexities. Sediments exhibited a unique signature on PC 1 (67.05%), associated with cumulative agricultural impacts, with PC 2 (18.08%) providing insights into nuanced factors, such as sediment composition and dynamic interactions. These findings offer a complete insight into the Chuhe River tributary’s condition, underlining the urgency for ongoing monitoring and potential remediation measures.

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