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首页> 外文期刊>Atmospheric environment >Modelling VOC source impacts on high ozone episode days observed at a mountain summit in Hong Kong under the influence of mountain-valley breezes
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Modelling VOC source impacts on high ozone episode days observed at a mountain summit in Hong Kong under the influence of mountain-valley breezes

机译:模拟VOC来源对山峰谷微风影响下香港山峰上高臭氧发作日的影响

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摘要

A top-down approach to evaluate high ozone (O_3) formation, attributed to different emission sources, is developed for anti-cyclonic conditions in a region of Hong Kong influenced by meso-scale circulations. A near-explicit photochemical model coupled with the Master Chemical Mechanism (MCMv3.2) is used to investigate the chemical characteristics in the region. Important features have been enhanced in this model including the photolysis rates, simulated by the National Center for Atmospheric Research (NCAR) Tropospheric Ultraviolet and Visible (TUV) Radiation Model, as well as hourly variation of Volatile Organic Compound (VOC) concentration input from on-site sampling. In general, the combined model gives a reasonably good representation of high O_3 levels in the region. The model successfully captured a multi-day O_3 event in the autumn of 2010. Source apportionment via Positive Matrix Factorization (PMF) was carried out on the sampled VOC data, to determine the major sources in the region. Based on the outcomes of the PMF source apportionment, a sensitivity analysis using the developed photochemical model was conducted and used to estimate O_3 reduction under different source removal regimes. Results indicate that vehicular emissions are the dominant VOC source contributing to O_3 formation. This study has demonstrated a potentially efficient secondary pollutants control methodology, using a combined field measurements and modelling approach.
机译:针对香港受中尺度环流影响的地区的反气旋条件,开发了一种自上而下的方法来评估高臭氧(O_3)的形成,这归因于不同的排放源。使用近乎明确的光化学模型和主化学机理(MCMv3.2)来研究该地区的化学特征。该模型的重要功能得到了增强,包括美国国家大气研究中心(NCAR)对流层紫外线和可见光(TUV)辐射模型模拟的光解速率,以及从大气中输入的挥发性有机化合物(VOC)浓度的每小时变化。现场采样。通常,组合模型可以较好地表示该区域的O_3高水平。该模型在2010年秋季成功捕获了为期多天的O_3事件。对样本的VOC数据通过正矩阵分解(PMF)进行了源分配,以确定该地区的主要源。基于PMF源分配的结果,使用开发的光化学模型进行了敏感性分析,并用于估计在不同源去除方案下O_3的减少。结果表明,车辆排放是导致O_3形成的主要VOC来源。这项研究证明了一种结合现场测量和建模方法的潜在有效的二级污染物控制方法。

著录项

  • 来源
    《Atmospheric environment》 |2013年第12期|166-176|共11页
  • 作者单位

    Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong,School of Chemistry and Biochemistry, University of Western Australia, Perth, Australia;

    School of Chemistry and Biochemistry, University of Western Australia, Perth, Australia;

    Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong;

    Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong;

    International Institute for Earth System Science, Nanjing University, Nanjing, China;

    Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China;

    Department of Atmospheric Sciences, Nanjing University, Nanjing, China;

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

    Photochemical model; Master Chemical Mechanism (MCM); Volatile Organic Compounds (VOC); Photochemical Ozone Creation Potential; (POCP); Positive Matrix Factorization (PMF);

    机译:光化学模型主化学机制(MCM);挥发性有机化合物(VOC);光化学臭氧产生潜能;(POCP);正矩阵分解(PMF);

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