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首页> 外文期刊>Fresenius environmental bulletin >A STUDY ON ROAD TRAFFIC EMISSIONS OF HEAVY METALS IN THE TIRANA- ELBASAN HIGHWAY TUNNEL EXPERIMENT IN ALBANIA BY USING THE DUST SAMPLES
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A STUDY ON ROAD TRAFFIC EMISSIONS OF HEAVY METALS IN THE TIRANA- ELBASAN HIGHWAY TUNNEL EXPERIMENT IN ALBANIA BY USING THE DUST SAMPLES

机译:利用粉尘样品研究阿尔巴尼亚地拉那-厄尔巴桑公路隧道实验中重金属的道路交通排放

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To identify the tracer emission from the diesel engines and to evaluate the environmental pollution caused by traffic emission inside the tunnel, fine particulate matter (PM) samples collected in the tunnel of Krraba (Tirana-Elbasan highway) were analyzed for heavy metals content (Cu, Fe, Hg, Pb, Mn, Ni, and Zn) in relation to different distances from the entrance portal to the exit portal of the tunnel. The horizontal ventilation systems of the tunnel, located next to the tunnel portals, were not permanently function during the both monitoring periods. Dust samples collected in front of the entrance portal show low metal content that is gradually increased as the distance from the entrance to the exit portal increased. High contents of metals in dust samples were found that indicates the dust samples are efficient to be used for the monitoring of heavy metal pollution caused by tunnel’s traffic exhausts over the time, even with low sensitivity analytical methods. The data onto two different monitoring periods shows different views of metal distributions. The first monitoring period (November 2013) is characterized by high Fe content in dust samples, by indicating the high effect of soil dust caused by construction activity during this monitoring period. The second monitoring period (March 2014) is characterized by higher content of Cu, Hg, Zn and Mn that are typical elements of the anthropogenic sources related mainly to traffic emissions. The multivariate analysis of dimensionality reduction technique, factor analysis (FA), was used to identify the most potential factors of these tracers. The FA and Cluster analysis of trace metal concentrations data show that the Hg and Pb onto PM samples, are probably linked with the diesel engine emissions.
机译:为了识别柴油发动机的示踪物排放并评估隧道内交通排放造成的环境污染,分析了在克拉拉巴(地拉那-埃尔巴桑高速公路)隧道中收集的细颗粒物(PM)样品中的重金属含量(Cu)。 ,Fe,Hg,Pb,Mn,Ni和Zn)与从隧道入口到出口的不同距离有关。在两个监测期内,位于隧道入口附近的隧道水平通风系统均未永久运行。在入口入口前面收集的灰尘样品显示出较低的金属含量,该金属含量随着从入口到出口入口的距离的增加而逐渐增加。灰尘样品中的金属含量很高,这表明即使采用低灵敏度分析方法,该灰尘样品也可有效地用于监测一段时间内因隧道交通尾气引起的重金属污染。两个不同监测周期的数据显示了金属分布的不同视图。第一个监测期(2013年11月)的特征是粉尘样品中的铁含量高,表明该监测期内施工活动对土壤粉尘的影响很大。第二个监测期(2014年3月)的特征是较高的Cu,Hg,Zn和Mn含量是人为来源的典型元素,主要与交通排放有关。降维技术的多元分析,因子分析(FA),用于识别这些示踪剂中最有潜力的因子。微量金属浓度数据的FA和簇分析表明,PM样品上的Hg和Pb可能与柴油机排放有关。

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