Long-term spatiotemporal trends and health risk assessment of oyster arsenic levels in coastal waters of northern South China Sea

2017 ◽  
Vol 24 (25) ◽  
pp. 20673-20684 ◽  
Author(s):  
Xuefeng Wang ◽  
Lifei Wang ◽  
Xiaoping Jia ◽  
Donald A. Jackson
2021 ◽  
Author(s):  
Lifei Wang ◽  
Xuefeng Wang ◽  
Haigang Chen ◽  
Zenghuan Wang ◽  
Xiaoping Jia

Abstract Estuarine and coastal ecosystems are often considered vulnerable due to the complex biogeochemical processes and the human disturbances through a variety of pollution. Among environmental contaminants, heavy metals in estuarine and coastal ecosystems have been of increasing concern in environmental conservation. Long-term exposure to heavy metal contamination, mainly through food and water, could be harmful to human health. It is therefore critical to understand the quantitative comparisons and interacting effects of different heavy metals in common seafood species, such as oysters. This work studied the long-term spatiotemporal trends and health risk assessment of oyster arsenic (As), cadmium (Cd), copper (Cu), mercury (Hg), lead (Pb) and zinc (Zn) levels in the coastal waters of northern South China Sea. Cultured oysters (Crassostrea rivularis) from 23 estuaries and harbors in the coastal areas of northern South China Sea in 1989–2015 were analyzed for the spatiotemporal trends of the six heavy metal levels. Metal pollution index (MPI), target hazard quotient (THQ) and hazard index (HI) were used for quantifying the exposure of the six heavy metals to human health through oyster consumption. Principal component analysis (PCA) was used for assessing the relative importance of the six metals in oyster heavy metal distribution patterns in the northern South China Sea. Overall, the As, Cd, Cu, Hg, Pb and Zn levels in oysters from the northern South China Sea generally declined from 1989 to 2015, stayed relatively high (MPI = 2.42–3.68) during 1989–2000, gradually decreased since 2000, and slightly increased after 2010. Oyster heavy metal levels were highest in the Pearl River Estuary (MPI = 1.20–5.52), followed by west Guangdong and east Guangdong, Guangxi, and Hainan coastal waters. This pattern is probably because economics and industry around the Pearl River Estuary have been growing faster than the other areas of this work in the recent two decades, and it should be taken as a hotspot for the monitoring of seafood safety in southern China. Principal component analysis indicated that Cu, Zn and Cd were the most important metals in the long-term distributions of oyster heavy metal levels in the northern South China Sea. Health risk assessment suggested that the risk of the six heavy metals exposure through oyster consumption were relatively high during 1989–2005 (THQ = 1.01–5.82), significantly decreased since 2005 (THQ < 1), and slightly increased after 2010.


Author(s):  
Linbin Li ◽  
Ping Li ◽  
Yuan Liu

This paper presents a reliability based methodology to develop the design and assessment acceptance criteria for fixed offshore platforms in the northern South China Sea under extreme storm events. Firstly, the atmosphere, ocean and wave coupled numeric simulation model with site measurements verification is used to generate the time series directional waves, currents and winds for each refined grid point in the studied area during the past 40 years. Secondly, the storm and response based load statistics method is adopted to investigate the long term distribution of the extreme environmental load considering the joint occurrence of wave, current and wind. Thirdly a structural reliability method is proposed to quantify the probability of platform failure subjected to extreme storms. The environmental load factors for new design platforms in the northern South China Sea with different exposure categories are calibrated. Finally risk assessment is performed to develop the acceptance criteria for the exiting platforms in terms of reserve strength ratio based on the failure consequence and failure probability of platforms. Case studies are presented to illustrate the applications of the proposed method and how the reliability analysis results can be used in development of long term structural integrity management strategies.


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