• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Environmental Science and Technology >Multivariate Chemometric Approach on the Surface Water Quality in Langat Upstream Tributaries, Peninsular Malaysia
【24h】

Multivariate Chemometric Approach on the Surface Water Quality in Langat Upstream Tributaries, Peninsular Malaysia

机译：马来西亚半岛兰加特上游支流地表水水质的多元化学计量学方法

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The small tributaries to upstream Langat of Peninsular Malaysia play an important role to water quality in downstream. This study was carried out to investigate the indicator pollution and identify the potential sources of pollutants using multivariate chemometric techniques. Sampling campaign was conducted on monthly basis from January-June, 2015, duly interval dry and rainy seasons at six stations. Hierarchical cluster analysis (HACA) was employed on temporal and spatial dataset. Temporal dataset were grouped into two clusters on the basis of rainfall before collecting samples; the months of January, March and June formed one cluster and February, April and May appeared in the other. Spatial dataset were grouped into three clusters namely less polluted, medium polluted and polluted sites. Factor Analysis (FA) and Principal Component Analysis (PCA) were applied to identify the significant sources of pollutants, which resulted in five latent factors amounting to 73.0% of the total variance in data sets. Varifactors obtained from factor analysis indicate that the parameters responsible for water quality variations are related to physicochemical parameters and nutrients from both nonpoint and point sources. The nonpoint sources include plantation area, weathering of sedimentary rock and natural vegetation and point sources include mainly domestic wastewater. Thus, this study illustrates the water quality assessment, identification of pollution factors and temporal/spatial variations in water quality for the surface water of upstream tributaries to implement effective river water quality management with multivariate statistical techniques for analysis and interpretation of complex data sets.
机译：马来西亚半岛上游兰加特河的小支流对下游水质起着重要作用。进行这项研究以调查指示剂污染并使用多元化学计量学技术确定污染物的潜在来源。从2015年1月至6月，每月进行一次抽样活动，并在六个站按时间隔干旱和雨季。在时间和空间数据集上采用了层次聚类分析（HACA）。在收集样本之前，根据降雨将时间数据集分为两个聚类。 1月，3月和6月形成一个群集，而2月，4月和5月则出现在另一个群集中。空间数据集分为三个集群，即污染程度较低，中度污染和污染的地点。应用因子分析（FA）和主成分分析（PCA）来确定污染物的主要来源，这导致了五个潜在因子，总计占数据集总方差的73.0％。从因子分析获得的变量表明，负责水质变化的参数与非点源和点源的理化参数和养分有关。非点源包括人工林，沉积岩和自然植被的风化，点源主要包括生活污水。因此，本研究说明了上游支流地表水的水质评估，污染因素的识别以及水质的时空变化，从而利用多元统计技术对复杂数据集进行分析和解释，从而实现有效的河流水质管理。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号