کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6358164 | 1315627 | 2014 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Assessing metal toxicity in sediments using the equilibrium partitioning model and empirical sediment quality guidelines: A case study in the nearshore zone of the Bohai Sea, China
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
اقیانوس شناسی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Assessing metal toxicity in sediments using the equilibrium partitioning model and empirical sediment quality guidelines: A case study in the nearshore zone of the Bohai Sea, China Assessing metal toxicity in sediments using the equilibrium partitioning model and empirical sediment quality guidelines: A case study in the nearshore zone of the Bohai Sea, China](/preview/png/6358164.png)
چکیده انگلیسی
Surface sediments were collected from five nearshore (wastewater discharges, aquaculture facilities and a seaport) sites in Bohai Bay and Laizhou Bay, China. The equilibrium partitioning (EqP) model and empirical sediment quality guidelines (SQGs) were applied to assess the potential metal toxicity in the collected sediments. The results show that, based on the EqP model, 35% of stations exhibited potential metal toxicity. Several metals (Cu, Ni and Cr) exceeded the empirical SQGs (9-93% of the time), however these guidelines may not be suitable for use in the Bohai Sea owing to the background concentrations. The EqP model is a more useful method for assessing potential metal toxicity in Bohai Sea sediment than the empirical SQGs. Additionally, we have provided new understanding about methods for assessing sediment metal toxicity in the Bohai Sea that may be useful in other coastal areas in China.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Marine Pollution Bulletin - Volume 85, Issue 1, 15 August 2014, Pages 114-122
Journal: Marine Pollution Bulletin - Volume 85, Issue 1, 15 August 2014, Pages 114-122
نویسندگان
Li Li, Wang Xiaojing, Liu Jihua, Shi Xuefa, Ma Deyi,