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Application of positive matrix factorization receptor model and elemental analysis for the assessment of sediment contamination and their source apportionment of Deepor Beel, Assam, India
Ecological Indicators ( IF 6.9 ) Pub Date : 2020-03-21 , DOI: 10.1016/j.ecolind.2020.106291
Siddhant Dash , Smitom Swapna Borah , Ajay S. Kalamdhad

The present study is a first of its kind on the sediment contamination in Deepor Beel, which makes use of source apportionment receptor modelling technique {positive matrix factorization (PMF)} for determining and quantifying the sources’ contribution to the pollution of the sediment column of Deepor Beel, Assam. Sediment samples were collected and analysed for seven different heavy metals from 23 sampling locations for a period from October 2017 to February 2019. Polling the entire dataset to a single matrix and carrying out multiple iterations revealed that four factors were optimum and thus, was applied for the simulation of the model. It was observed that the factors 1, 2, 3 and 4 corresponded to the soil parent material, leaching from the Boragaon landfill, discharge of agricultural and domestic wastes, and effluents from the industries and traffic emissions respectively. The sediment samples were further subjected to elemental analysis; X-ray powder diffraction (XRD) followed by Scanning electron microscope - Energy Dispersive X-Ray Spectroscopy (SEM – EDS), to determine the elemental composition and forms of heavy metals present in the sediment columns from various parts of the wetland. Sediment sample collected from the proximity of the landfill site was observed to be affected the most, probably due to leaching effects, especially during the monsoon. The central zone, however, was found to be devoid of any anthropogenic contaminations, while the sediment column near the industrial complex was found to be contaminated to a moderate extent. The study indicates the quantum of sediment contamination in the wetland and the causative parameters responsible, thus proving to be of immense help to the various governmental bodies in the planning and management of resources for sediment remediation of Deepor Beel.



中文翻译:

正矩阵分解受体模型和元素分析在评估印度阿萨姆邦Deepor Beel沉积物污染及其来源分配中的应用

本研究是有关Deepor Beel中沉积物污染的同类研究中的第一个,它利用源分配受体建模技术{positive matrix factorization(PMF)}来确定和量化源对沉积物污染的贡献。 Deepor Beel,阿萨姆邦。从2017年10月到2019年2月,从23个采样点收集了沉积物样品并分析了7种不同的重金属。将整个数据集轮询到一个矩阵中并进行多次迭代表明,四个因素是最佳的,因此将其应用于模型的仿真。观察到,因子1、2、3和4对应于土壤母体材料,这些材料是从长滩岛垃圾填埋场浸出的,农业和生活垃圾的排放,分别来自工业和交通排放。沉积物样品进一步进行元素分析。X射线粉末衍射(XRD),然后是扫描电子显微镜-能量色散X射线光谱法(SEM-EDS),以确定湿地各部分沉积物中存在的重金属的元素组成和形式。观察到从填埋场附近收集的沉积物样品受到的影响最大,这可能是由于浸出作用所致,特别是在季风期间。然而,发现中部地区没有任何人为污染,而发现工业园区附近的沉积物柱受到了中等程度的污染。

更新日期:2020-03-22
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