Key Takeaways & Executive Findings
- •• • Mean Cu and Cr concentrations in Xiangshan Harbor sediments exceeded the Class I marine sediment quality standard (GB 18668-2002) by 1.03× and 1.1×, respectively, indicating localized contamination that may threaten benthic organisms and necessitate targeted remediation. • • In Sanmen Bay, mean Cr exceeded the standard by 1.1×, while Cu did not; this differential accumulation suggests distinct sources and requires source-specific management strategies. • • Coefficients of variation for five heavy metals in Hangzhou Bay exceeded 30%, signifying strong anthropogenic influence; spatial analysis traced contamination to a chemical industrial park, with concentrations decreasing westward, directly implicating industrial discharge as the primary driver. • • The potential ecological risk indices (RI) for Xiangshan Harbor, Sanmen Bay, and Hangzhou Bay were 38.5, 36.7, and 31.1, respectively, all below the low-risk threshold (RI < 150), confirming overall low ecological risk but warranting continued monitoring due to localized hotspots.
Abstract
Surface sediment samples were collected from 28 stations in the intertidal zones of Xiangshan Harbor, Sanmen Bay, and the southern coast of Hangzhou Bay, major fishery waters in Ningbo, to assess heavy metal pollution and ecological risk. Concentrations of Cu, Pb, Zn, Cd, Cr, Hg, and As were determined. Results showed that Cu and Cr were the primary超标 factors, with mean concentrations exceeding the Class I standard (GB 18668-2002) by factors of 1.03 and 1.1, respectively, in Xiangshan Harbor; in Sanmen Bay, Cr exceeded by 1.1 times, while Cu did not. In Hangzhou Bay, Cu and Cr were elevated but below the standard. Coefficients of variation (CV) for five metals in Hangzhou Bay exceeded 30%, indicating strong external influence. In Xiangshan Harbor, As showed strong variation, and in Sanmen Bay, Hg showed strong variation. The potential ecological risk indices (RI) were 38.5, 36.7, and 31.1 for Xiangshan Harbor, Sanmen Bay, and Hangzhou Bay, respectively, all indicating low ecological risk. Spatial distribution in Hangzhou Bay revealed a decreasing gradient from a chemical industrial park, suggesting industrial discharge as a primary source. The study provides baseline data for environmental management and recommends source control and bioremediation in high-risk areas.
1. Introduction
Heavy metal contamination in coastal sediments poses a persistent threat to marine ecosystems and human health through food chain accumulation. In Ningbo's major fishery waters—Xiangshan Harbor, Sanmen Bay, and Hangzhou Bay—the lack of systematic data on sediment quality has hindered effective environmental management. Previous assessments often relied on total metal concentrations without integrating spatial variability or source apportionment, limiting their utility for targeted intervention.
This study addresses that gap by conducting a comprehensive survey of seven heavy metals across 28 intertidal stations, employing single-factor and Nemerow pollution indices alongside Hakanson's potential ecological risk index. By quantifying contamination levels, spatial distribution, and potential sources, the research provides actionable insights for regulatory bodies, enabling prioritization of pollution control measures in areas with elevated risk, such as the chemical industrial zone in Hangzhou Bay.
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ZHENG Dan, JIAO Haifeng, WANG Jianping, JIANG Hai, WU Beili, LIU Youyu, SUN Yuan, LIN Shan (2026). Risk Assessment of Heavy Metals in Sediments from Xiangshan Harbor, Sanmen Bay and Hangzhou Bay. Environmental Chemistry. https://doi.org/10.0000/202605-2
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Frequently Asked Questions
What are the specific contamination levels of Cu and Cr in the three bays, and how do they compare to regulatory standards?
In Xiangshan Harbor, mean Cu and Cr concentrations were 1.03 and 1.1 times the Class I standard (GB 18668-2002), respectively. In Sanmen Bay, Cr exceeded the standard by 1.1 times, while Cu did not exceed. In Hangzhou Bay, both Cu and Cr were elevated but below the standard. These values indicate localized contamination, particularly in Xiangshan Harbor, requiring attention.
How do the coefficients of variation (CV) inform about external influences on heavy metal distribution?
CV values exceeding 30% indicate strong variability, suggesting significant external inputs. In Hangzhou Bay, five metals showed CV >30%, reflecting substantial anthropogenic influence. In Xiangshan Harbor, As showed strong variation, and in Sanmen Bay, Hg showed strong variation, pointing to site-specific sources such as industrial discharge or historical contamination.
What is the overall ecological risk level in these areas, and what are the implications for fishery management?
The potential ecological risk indices (RI) were 38.5, 36.7, and 31.1 for Xiangshan Harbor, Sanmen Bay, and Hangzhou Bay, respectively, all below the low-risk threshold (RI < 150). This indicates low ecological risk, but localized hotspots and strong variability warrant continuous monitoring to prevent future degradation and ensure the safety of fishery products.
What are the likely sources of heavy metal contamination, and how can this inform mitigation strategies?
Spatial analysis in Hangzhou Bay revealed a decreasing concentration gradient from a chemical industrial park, directly implicating industrial discharge as a primary source. In other areas, sources may include agricultural runoff, atmospheric deposition, or natural geological enrichment. Mitigation should focus on source control, particularly enforcing discharge regulations near industrial zones, and implementing bioremediation or sediment capping in affected areas.
How do the findings compare with previous studies in similar coastal environments, and what are the limitations?
The RI values are consistent with other studies in Chinese coastal bays, which often report low to moderate risk. However, this study is limited by a single sampling campaign (August 2021) and does not assess bioavailability or seasonal variations. Future research should incorporate bioassays and repeated sampling to capture temporal dynamics and better assess ecological impacts.
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