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首页> 外文期刊>International Journal of Integrated Engineering >The behavior of Particulate Matter (PM10) Concentrations at Industrial Sites in Malaysia
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The behavior of Particulate Matter (PM10) Concentrations at Industrial Sites in Malaysia

机译:马来西亚工业场所中颗粒物(PM10)浓度的行为

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Particulate Matter (PM 10 ) is one of the atmospheric pollutants that can cause significant effect to human health. Meteorological factors such as wind speed (WS), relative humidity (RH) and temperature (T), and gaseous pollutants namely surface layer ozone (O 3 ), nitrogen dioxide (NO 2 ), sulphur dioxide (SO 2 ) and carbon monoxide (CO) are reported as some of the main factors that influence the concentration of PM 10 . Therefore, the aim of this study is to investigate the pattern and behaviour of PM 10 concentration at three industrial sites which were Pasir Gudang in Johor, Perai in Penang and Nilai in Negeri Sembilan. In the current study, the descriptive statistics, correlation analysis and multiple linear regressions were used to analyse the hourly average data from 2010 to 2014. The maximum values of PM 10 concentration recorded at Pasir Gudang, Nilai and Perai stations were 995 μg/m3, 711 μg/m3 and 232 μg/m3, respectively. Positive correlation was found between PM10 concentration and all gaseous pollutants. While for meteorological parameters, only wind speed had negative relations at all monitoring stations. The values of R2 for Pasir Gudang, Perai and Nilai were 0.539, 0.628 and 0.634, respectively. Overall, this study proved that most of the selected meteorological parameters and gaseous pollutants positively influenced the concentration of PM 10 .
机译:颗粒物(PM 10)是可能对人类健康造成重大影响的大气污染物之一。气象因素,例如风速(WS),相对湿度(RH)和温度(T),以及气态污染物,即表层臭氧(O 3),二氧化氮(NO 2),二氧化硫(SO 2)和一氧化碳(据报道,CO 2是影响PM 10浓度的一些主要因素。因此,本研究的目的是调查柔佛州的Pasir Gudang,槟城的Perai和森美兰州的汝来三个工业基地的PM 10浓度模式和行为。在本研究中,使用描述性统计数据,相关分析和多元线性回归分析了2010年至2014年的每小时平均数据。巴西古当,汝来和北赖站的PM 10浓度最大值为995μg/ m3,分别为711μg/ m3和232μg/ m3。发现PM10浓度与所有气态污染物之间呈正相关。对于气象参数,在所有监测站中只有风速具有负相关。巴西古当,佩雷和汝来的R2值分别为0.539、0.628和0.634。总体而言,这项研究证明,大多数选定的气象参数和气态污染物均对PM 10的浓度产生积极影响。

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