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Identifying pollutant source directions using multiple analysis methods at a rural location in New York

机译:在纽约农村地区使用多种分析方法识别污染物源方向

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摘要

We identify the directionality of sources contributing to observed pollutant concentrations at a rural site through the use of the analysis methods of Conditional Probability Function (CPF) and the Source Direction Probability (SDP). Input data consists of hourly averaged PM2.5 mass, Organic Mass (OM) from Organic Carbon (OC), optical Elemental Carbon (optical EC), SO2, CO, NOy, O3 concentrations and metrological data from Pinnacle State Park site in rural New York State for the period of Dec 2004 to Dec 2008. These measured pollutants are coupled with on-site wind data to identify the directionality of the sources; which are then compared to known stationary source locations from the EPA Air Data web site. Although the CPF plot of the O-3 showed no distinct directionality source area, the Pinnacle State Park site was frequently impacted by plumes of relatively high PM2.5 mass, SO_2, CO, NOy, optical EC and OM concentrations. Further analysis of the enhanced pollution occurrence frequency from the eastern sector revealed two peaks in the time-of-day distribution of elevated CO, NOy, and optical EC, which provides additional information on the sources. This contrasts with the enhanced pollution occurrence frequency from the south for CO, OM, and optical EC, which shows a single morning peak in its time-of-day distribution and indicates a somewhat more distant, but common source for these carbon-containing pollutants. PM2.5 mass corresponds to the source areas related to emission facilities listed in the EPA Emissions Inventory, which is further confirmed by correlation and analysis of aerosol optical depth (AOD) data from Moderate-resolution Imaging Spectrometer (MODIS) on board Terra and Aqua satellites. We present evidence that most of the high pollution episodes likely arise from emission sources located several hundred kilometers from the site, indicating mid-long range transport of pollutants to this location.
机译:通过使用条件概率函数(CPF)和源方向概率(SDP)的分析方法,我们确定了导致农村地区观测到的污染物浓度的源的方向性。输入数据包括每小时平均PM2.5质量,来自有机碳(OC)的有机质量(OM),光学元素碳(光学EC),SO2,CO,NOy,O3浓度以及新农村地区Pinnacle State Park站点的计量数据纽约州从2004年12月至2008年12月。这些测得的污染物与现场风况数据相结合,可确定排放源的方向性;然后将其与EPA Air Data网站上已知的固定源位置进行比较。尽管O-3的CPF图未显示明显的方向性源区域,但Pinnacle国家公园遗址经常受到PM2.5质量较高,SO_2,CO,NOy,光学EC和OM浓度较高的羽流的影响。进一步分析了东部地区增加的污染发生频率,发现在CO,NOy和光学EC升高的时间分布中有两个峰值,这提供了有关来源的更多信息。这与从南部开始的CO,OM和光学EC的污染发生频率增加形成鲜明对比,后者在一天中的时间分布中显示一个早晨高峰,并表明这些含碳污染物的排放源距离稍远,但是常见的。 PM2.5质量对应于EPA排放清单中列出的与排放设施有关的源区域,通过对Terra和Aqua船上中等分辨率成像光谱仪(MODIS)的气溶胶光学深度(AOD)数据进行关联和分析,可以进一步确认PM2.5质量卫星。我们提供的证据表明,大多数高污染事件可能来自距该站点数百公里的排放源,这表明污染物向该位置的中长期传输。

著录项

  • 来源
    《Atmospheric environment》 |2011年第15期|p.2531-2540|共10页
  • 作者单位

    Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, New York, USA,Department of Environmental Engineering, Mokpo National University, South Korea;

    Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, New York, USA;

    Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, New York, USA,Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan;

    Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan;

    New York State Department of Environmental Conservation, Division of Air Resources, Albany, New York, USA;

    Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, New York, USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    source; direction; CPF; SDP; AOD;

    机译:源;方向;CPF;SDP;AOD;

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