首页> 外文会议>Proceedings of the 7th Asian aerosol conference >Particulate matter source apportionment based on a back trajectory model during episode days in central Taiwan
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Particulate matter source apportionment based on a back trajectory model during episode days in central Taiwan

机译:台湾中部情节期间基于回弹轨迹模型的颗粒物源分配

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摘要

It is important to realize the contribution of air pollutants emission sources to ambient concentrations to establish proper and effective strategies. We applied the Gaussian trajectory transfer-coefficient model (Tsuang, 2003; Tseng et al., 2003) to simulate the particulate matter (PM) concentrations and the source apportionments at Chungming Station in central Taiwan during PM episode days in 2008. The location of the receptor is shown in Figure 1. Two kinds of PM episode days are selected. One PM episode is during Asia dust storm period (2-4 March 2008) and the other PM episode is effected by ill-dispersion synoptic pattern (29 March 2008). The correlation coefficient (R) between the observed and calculated daily PM10 concentrations from 28 February to 5 March 2008 including Asia dust storm is 0.716 (Figure 2). The source apportionments results indicated that the primary sources for PM10 at Chungming Station were subsidence (31%) during dust storm period and upwind boundary concentration (26%) during non-dust storm period (Figure 3). The subsidence played an important role during the Asia dust storm. The subsidence increased 12% PM10 apportionment during dust storm period than that during non-dust storm period. On the other hand, the correlation coefficient (R) between the observed and calculated daily PM10 concentrations from 26 March to 1 April 2008 including one PM episode day is 0.965 (Figure 4). The primary sources for PM10 at Chungming Station were upwind boundary concentration (24%) and point sources (23%) on the PM episode day (Figure 5). The synoptic system was high pressure circulation effected Taiwan which often causes the ambient in relatively stable condition. Not like the PM10 source apportionment during dust storm period, the subsidence was less important and the long range secondary aerosol transport and local emissions seemed to have much influence on the PM10 contribution to a receptor.
机译:重要的是要认识到空气污染物排放源对环境浓度的影响,以建立适当而有效的策略。我们应用高斯轨迹转移系数模型(Tsuang,2003; Tseng等,2003)来模拟2008年PM发作期间台湾中部崇明站的颗粒物(PM)浓度和源分配。受体如图1所示。选择两种PM发作日。一次下午发作发生在亚洲沙尘暴时期(2008年3月2-4日),另一次发作发生在分布不均的天气模式下(2008年3月29日)。从2008年2月28日至3月5日(包括亚洲沙尘暴)观察到的每日PM10浓度与计算得出的每日PM10浓度之间的相关系数(R)为0.716(图2)。物源分配结果表明,中鸣站PM10的主要来源是沙尘暴时期的沉降(31%)和非沙尘暴时期的上风边界浓度(26%)(图3)。在亚洲沙尘暴期间,沉降起了重要作用。与非沙尘暴相比,沙尘暴期间的沉降PM10分配增加了12%。另一方面,从2008年3月26日至4月1日(包括一个PM发作日)观察到的每日PM10浓度与计算得出的每日PM10浓度之间的相关系数(R)为0.965(图4)。崇明站PM10的主要来源是下午发作日的上风边界浓度(24%)和点源(23%)(图5)。对流系统是受高压环流影响的台湾,常常造成周围环境处于相对稳定的状态。与沙尘暴期间的PM10来源分配不同,下沉作用不那么重要,远程二次气溶胶运输和局部排放似乎对PM10对受体的贡献有很大影响。

著录项

  • 来源
  • 会议地点 Xian(CN)
  • 作者单位

    Department of Industrial Engineering and Management,Fortune Institute of Technology,1-10,Nwongchang Rd.,Daliao,Kaohsiung 831,Taiwan;

    Department of Finance,Fortune Institute of Technology,1-10,Nwongchang Rd.,Daliao,Kaohsiung 831,Taiwan;

    Department of General Education Center,Fortune Institute of Technology,1-10,Nwongchang Rd.,Daliao,Kaohsiung 831,Taiwan;

    Department of Medicinal Chemistry,Chia Nan University of Pharmacy and Science,60,Sec. 1,Erh-Jen Rd.,Jen-Te,Tainan 717,Taiwan;

    Department of Environmental Engineering,National Chung-Hsing University,250,Kuokang Road,Taichung 402,Taiwan;

    Department of Environmental Engineering,National Chung-Hsing University,250,Kuokang Road,Taichung 402,Taiwan;

    Department of Chemistry,National Cheng Kung University,1,University Rd.,Tainan 701,Taiwan;

    Department of Environmental Engineering and Science,Chia Nan University of Pharmacy and Science,60,Sec. 1,Erh-Jen Rd.,Jen-Te,Tainan 717,Taiwan;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 气溶胶(烟、雾);
  • 关键词

    source apportionment; trajectory model; PM episode;

    机译:源分配;轨迹模型; PM发作;

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