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首页> 外文期刊>Aerosol and Air Quality Research >Statistical Characteristics of Ambient PM2.5 Concentration at a Traffic Site in Delhi: Source Identification Using Persistence Analysis and Nonparametric Wind Regression
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Statistical Characteristics of Ambient PM2.5 Concentration at a Traffic Site in Delhi: Source Identification Using Persistence Analysis and Nonparametric Wind Regression

机译:德里交通站点周围PM2.5浓度的统计特征:基于持久性分析和非参数风向的源识别

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摘要

The source and origin of the ambient PM2.5 concentration at a traffic site in Delhi was studied using the persistence analysis and nonparametric wind regression (NWR) technique. The analysis was performed for the original PM2.5 data observed during 2007–2009, by removing seasonal and trend patterns (PM2.5-AR1), and for the exceedance time series. Detrended fluctuation analysis showed the strong persistence in the original and exceeded PM2.5 time series. This behavior was linked with the self-organized criticality of the process generating PM2.5 concentrations. NWR analysis was carried out to infer the sources of PM2.5 concentrations in the area. Power plants and medium scale industries along with the local transport emissions were found to be responsible for PM2.5 emissions at the site. Analysis of seasonal variations showed significant contributions from medium scale industries and power plants in winter, and dust storms and industrial contribution in summer. An analysis of the results obtained during calm conditions suggests the dominance of local transport emissions along with the above sources of PM2.5 concentrations at the site.
机译:使用持久性分析和非参数风向回归(NWR)技术研究了德里交通站点中PM2.5浓度的来源和来源。通过去除季节和趋势模式(PM2.5-AR1)以及超出时间序列,对2007-2009年期间观察到的原始PM2.5数据进行了分析。去趋势波动分析显示了原始和超过PM2.5时间序列的强烈持久性。这种行为与产生PM2.5浓度的过程的自组织临界性有关。进行了NWR分析以推断该地区PM2.5浓度的来源。发现发电厂和中型工业以及当地的运输排放是造成该地点PM2.5排放的原因。对季节变化的分析表明,冬季中型工业和发电厂的贡献很大,夏季沙尘暴和工业的贡献很大。对在平静条件下获得的结果进行的分析表明,当地交通运输的排放量占主导地位,以及上述现场PM2.5浓度的来源。

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