首页> 外文期刊>Journal of Biodiversity, Bioprospecting and Development >Pollution control 2020Investigation of emissions sources and characterization at Mamelodi Township, Gauteng, South Africa using conditional probability function modelling-Shonisani Norman Singonideria
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Pollution control 2020Investigation of emissions sources and characterization at Mamelodi Township, Gauteng, South Africa using conditional probability function modelling-Shonisani Norman Singonideria

机译:使用条件概率函数型号 - Shonisani normanInderia,南非Mamelodi Township,Gautengi Township,豪登岛镇蒙登市排放来源及其表征

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This paper investigates pollution sources affecting Mamelodi Township within the City ofTshwane in Gauteng province, South Africa. Gauteng province has also the largestpopulation in South Africa. The ambient pollution concentration at the vicinity of Mamelodidepends upon their output of gases from various activities emanates from biogenic andanthropogenic. Anthropogenic activities are the main made sources of emissions such asdomestic fuel burning, industrial activities and transport emissions.It is therefore an objectiveof this study to assess and determine significant sources of emission which are affecting theMamelodi Ambient Monitoring Station by investigating ambient concentration correlationparameters, pollution roses and probability functions modelling. Investigations will be focuson the following pollutants Sulphur dioxide, Nitrogen dioxide, Ozone and Particulate Matterof less than ten micro diameter. In this study k-means clustering techniques has been appliedto bivariate polar plot to identify and group similar features.
机译:本文研究了南非豪登省市乌兰省曼德利乡的污染源。豪登省也是南非的最大值。 Mamelodidepend附近的环境污染浓度在各种活性的气体输出时从生物生物和蒽产生。作为各种燃料燃烧,工业活动和运输排放的主要排放来源是这项研究的主要原因。因此,这项研究是通过研究环境浓度相关参数,污染玫瑰来评估和确定影响HOMELODI环境监测站的重要排放来源的目标。和概率函数建模。调查将重点占据以下污染物二氧化硫,二氧化氮,臭氧和颗粒物质小于10微直径。在本研究中,K-Means聚类技术已应用于双变量极性图来识别和组的特征。

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