Spatial distribution and ecological risk assessment of heavy metals in sediment around the coastal oyster reefs in Guangdong, China

The distribution and sources of heavy metals in sediments near natural oyster habitats along the Guangdong coast were investigated from July 2022 to February 2023. Sediments were predominantly sandy (>55 % sand). Heavy metal concentrations followed the order: Zn > Pb > Cu > Cr > As > Cd > Hg. One-way ANOVA revealed significant spatial differences in six metals except Cu, with higher concentrations near estuarine, bay, urban, and harbor areas. Overall, 4.1 % of samples exceeded China's Class I standard for Cu, Pb, Zn, and Cd. Only stations G24 (Zhuhai) and G41 (Zhanjiang) had poor sediment quality; 94 % of stations were suitable for shellfish aquaculture. The geo-accumulation index indicated about 30 % of samples were slightly polluted, mainly by As and Pb. Over 90 % of samples exhibited low ecological risk; however, Hg, Cd, and Pb posed moderate to high risk at 5.5 %, 4.9 %, and 2.1 % of stations, respectively. Compared with historical data, most metal levels remained low, though Cu in western Guangdong and Pb in the Pearl River Estuary reached historically high levels. Key sources were riverine input, urban discharge, port activities and industries.

Authors

Institutions

Publication Details

Journal
Marine Pollution Bulletin
Published
2025-08-29
DOI
https://doi.org/10.1016/j.marpolbul.2025.118609
Primary Topic
Heavy metals in environment
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial distribution and ecological risk assessment of heavy metals in sediment around the coastal oyster reefs in Guangdong, China

Shengyong Li, Xinan Yue, Zihua Zhou, Xiaoshou Liu et al.
Marine Pollution Bulletin
Heavy metals in environment
article

Spatial distribution and ecological risk assessment of heavy metals in sediment around the coastal oyster reefs in Guangdong, China

Shengyong Li, Xinan Yue, Zihua Zhou, Xiaoshou Liu, Xiaomin Li, Jianping Ye, Hua Wang, Zhongyuan Wang, Jingxin Liu, Yaohui Chen, Jinghuai Zhang, Yang Gao, Qiu Hong
article en

Abstract

The distribution and sources of heavy metals in sediments near natural oyster habitats along the Guangdong coast were investigated from July 2022 to February 2023. Sediments were predominantly sandy (>55 % sand). Heavy metal concentrations followed the order: Zn > Pb > Cu > Cr > As > Cd > Hg. One-way ANOVA revealed significant spatial differences in six metals except Cu, with higher concentrations near estuarine, bay, urban, and harbor areas. Overall, 4.1 % of samples exceeded China's Class I standard for Cu, Pb, Zn, and Cd. Only stations G24 (Zhuhai) and G41 (Zhanjiang) had poor sediment quality; 94 % of stations were suitable for shellfish aquaculture. The geo-accumulation index indicated about 30 % of samples were slightly polluted, mainly by As and Pb. Over 90 % of samples exhibited low ecological risk; however, Hg, Cd, and Pb posed moderate to high risk at 5.5 %, 4.9 %, and 2.1 % of stations, respectively. Compared with historical data, most metal levels remained low, though Cu in western Guangdong and Pb in the Pearl River Estuary reached historically high levels. Key sources were riverine input, urban discharge, port activities and industries.

Marine Pollution BulletinVol. 222(Pt 1)
Ministry of Ecology and Environment (CN), Ministry of Natural Resources (RW), Ocean University of China (CN)
National Natural Science Foundation of China, Science and Technology Planning Project of Guangdong Province
Life below water
Openalex Percentile: Top 83%
Heavy metals in environment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.