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Quantifying Nonlinear Multiregional Contributions to Ozone and Fine Particles Using an Updated Response Surface Modeling Technique

机译:使用更新的响应面建模技术量化对臭氧和细颗粒的非线性多区域贡献

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摘要

Tropospheric ozone (O_3) and fine particles (PM_(2.5)) come from both local and regional emissions sources. Due to the nonlinearity in the response of O_3 and PM_(2.5) to their precursors, contributions from multiregional sources are challenging to quantify. Here we developed an updated extended response surface modeling technique (ERSMv2.0) to address this challenge. Multiregional contributions were estimated as the sum of three components: (1) the impacts of local chemistry on the formation of the pollutant associated with the change in its precursor levels at the receptor region; (2) regional transport of the pollutant from the source region to the receptor region; and (3) interregional effects among multiple regions, representing the impacts on the contribution from one source region by other source regions. Three components were quantified individually in the case study of Beijing-Tianjin-Hebei using the ERSMv2.0 model. For PM_(2.5) in most cases, the contribution from local chemistry (i.e., component 1) is greater than the contribution from regional transport (i.e., component 2). However, regional transport is more important for O_3. For both O_3 and PM_(2.5), the contribution from regional sources increases during high-pollution episodes, suggesting the importance of joint controls on regional sources for reducing the heavy air pollution.
机译:对流层臭氧(O_3)和细颗粒物(PM_(2.5))来自本地和区域排放源。由于O_3和PM_(2.5)对它们的前体的响应具有非线性,因此多区域来源的贡献难以量化。在这里,我们开发了更新的扩展响应表面建模技术(ERSMv2.0)来解决这一挑战。多区域贡献估计为三个部分的总和:(1)局部化学对污染物形成的影响,该污染物与其在受体区域前体水平的变化有关; (2)污染物从源区到受体区的区域性运输; (3)多个区域之间的区域间影响,表示对一个源区域的贡献对其他源区域的影响。在北京-天津-河北的案例研究中,使用ERSMv2.0模型分别量化了三个组成部分。在大多数情况下,对于PM_(2.5),局部化学作用(即组分1)的贡献大于区域运输的贡献(即组分2)。但是,区域运输对O_3更为重要。对于O_3和PM_(2.5)而言,在高污染事件期间来自区域源的贡献增加,这表明对区域源进行联合控制对于减少重度空气污染的重要性。

著录项

  • 来源
    《Environmental Science & Technology》 |2017年第20期|11788-11798|共11页
  • 作者单位

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China;

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China;

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China,Joint Institute for Regional Earth System Science and Engineering, Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, United States;

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China;

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China;

    U.S. Environmental Protection Agency, Research Triangle Park, NC, United States;

    College of Environmental Science and Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou, China;

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China;

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China,Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, Mainz, Germany;

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China;

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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  • 正文语种 eng
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