Abbas Alkarkhi F M, Ismail Norli, Easa Azhar Mat
School of Industrial Technology, Environmental Technology Division, Universiti Sains Malaysia, 11800 Penang, Malaysia.
J Hazard Mater. 2008 Feb 11;150(3):783-9. doi: 10.1016/j.jhazmat.2007.05.035. Epub 2007 May 16.
Cockles (Anadara granosa) sample obtained from two rivers in the Penang State of Malaysia were analyzed for the content of arsenic (As) and heavy metals (Cr, Cd, Zn, Cu, Pb, and Hg) using a graphite flame atomic absorption spectrometer (GF-AAS) for Cr, Cd, Zn, Cu, Pb, As and cold vapor atomic absorption spectrometer (CV-AAS) for Hg. The two locations of interest with 20 sampling points of each location were Kuala Juru (Juru River) and Bukit Tambun (Jejawi River). Multivariate statistical techniques such as multivariate analysis of variance (MANOVA) and discriminant analysis (DA) were applied for analyzing the data. MANOVA showed a strong significant difference between the two rivers in term of As and heavy metals contents in cockles. DA gave the best result to identify the relative contribution for all parameters in discriminating (distinguishing) the two rivers. It provided an important data reduction as it used only two parameters (Zn and Cd) affording more than 72% correct assignations. Results indicated that the two rivers were different in terms of As and heavy metal contents in cockle, and the major difference was due to the contribution of Zn and Cd. A positive correlation was found between discriminate functions (DF) and Zn, Cd and Cr, whereas negative correlation was exhibited with other heavy metals. Therefore, DA allowed a reduction in the dimensionality of the data set, delineating a few indicator parameters responsible for large variations in heavy metals and arsenic content. Taking into account of these results, it can be suggested that a continuous monitoring of As and heavy metals in cockles be performed in these two rivers.
从马来西亚槟城州的两条河流采集了蚶（泥蚶）样本，使用石墨炉原子吸收光谱仪（GF-AAS）测定铬（Cr）、镉（Cd）、锌（Zn）、铜（Cu）、铅（Pb）、砷（As）含量，使用冷蒸气原子吸收光谱仪（CV-AAS）测定汞（Hg）含量。两个感兴趣的地点，每个地点有20个采样点，分别是瓜拉朱律（朱律河）和武吉丹汶（杰贾维河）。采用多变量方差分析（MANOVA）和判别分析（DA）等多元统计技术对数据进行分析。MANOVA结果表明，两条河流蚶的砷和重金属含量存在显著差异。DA在区分两条河流时，对所有参数的相对贡献给出了最佳结果。它仅使用两个参数（锌和镉）就提供了超过72%的正确分类，实现了重要的数据降维。结果表明，两条河流蚶的砷和重金属含量不同，主要差异在于锌和镉的贡献。判别函数（DF）与锌、镉和铬呈正相关，与其他重金属呈负相关。因此，DA降低了数据集的维度，确定了导致重金属和砷含量大幅变化的几个指示参数。考虑到这些结果，建议对这两条河流的蚶中的砷和重金属进行持续监测。
