Geoaccumulation and distribution of heavy metals in the urban river sediment
Geoaccumulation and distribution of heavy metals in the urban river sediment作者机构：Environmental Forensics Research CentreFaculty of Environmental StudiesUniversiti Putra Malaysia43400 UPM SerdangSelangorMalaysia
出 版 物：《International Journal of Sediment Research》 (国际泥沙研究(英文版))
年 卷 期：2014年第29卷第3期
页 面：368-377页
核心收录：
基 金：the Research University Grant Scheme(RUGS)Project Number 03-01-10-0890RUVot 91895 from Universiti Putra Malaysia the Ministry of Higher Education and World Federation of Scientist for the financial support
主 题：Heavy metals Principal Component Analysis Cluster Analysis River Sediment
摘 要：Current study presents the application of chemometric techniques to comprehend the interrelations among sediment variables whilst identifying the possible pollution source at Langat River,*** sediment samples（0-10 cm）were collected at 22 sampling stations and analyzed for total metals(48Cd,29Cu,30Zn,82Pb),pH,redox potential（Eh）,salinity,electrical conductivity（EC）,loss on ignition（LOI）and cation exchange capacity（CEC）.The principal component analysis（PCA）scrutinized the origin of environmental pollution by various anthropogenic and natural activities:four principal components were obtained with 86.34%（5 cm）and88.34%（10 cm）.Standard,forward and backward stepwise discriminant analysis effectively discriminate 2variables（84.06%）indicating high variation of heavy metals accumulation at both *** cluster analysis accounted for high input of Zn and Pb at LA8,LA 10,LA 11 and LA 12 that mergers three（5 cm）and four（10cm）into *** is consistent with the contamination factor（C1）that shows high Cd（LA 1）and Pb（LA 7,LA 8,LA 10,LA 11 and LA 12）contaminations at *** indicate that Pb and Zn are the most bioavailable metals in the sediment with significant positive linear relationship at both sediment ***,this approach is a good indication of environmental pollution status that transfers new findings on the assessment of heavy metals by interpreting large complex datasets and predicting the fate of heavy metals in the sediment.
同方期刊数据库