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运用更新的响应面建模技术量化臭氧和细颗粒物的非线性多区域贡献。

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

机构信息

State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University , Beijing 100084, China.

Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California , Los Angeles, California 90095, United States.

出版信息

Environ Sci Technol. 2017 Oct 17;51(20):11788-11798. doi: 10.1021/acs.est.7b01975. Epub 2017 Sep 26.

Abstract

Tropospheric ozone (O) and fine particles (PM) come from both local and regional emissions sources. Due to the nonlinearity in the response of O and PM 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 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. For both O and PM, 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.

摘要

对流层臭氧 (O) 和细颗粒物 (PM) 既来自本地排放源,也来自区域排放源。由于 O 和 PM 对其前体的响应是非线性的,因此多区域源的贡献难以量化。在这里,我们开发了一种经过更新的扩展响应面建模技术 (ERSMv2.0) 来应对这一挑战。多区域贡献被估计为三个分量的总和:(1) 受体区域中污染物与其前体水平变化相关的形成过程中本地化学的影响;(2) 污染物从源区域到受体区域的区域传输;以及 (3) 多个区域之间的区域间效应,代表一个源区域对其他源区域贡献的影响。使用 ERSMv2.0 模型,在北京-天津-河北的案例研究中单独量化了这三个分量。在大多数情况下,对于 PM,本地化学的贡献(即分量 1)大于区域传输的贡献(即分量 2)。然而,对于 O 来说,区域传输更为重要。对于 O 和 PM,在污染严重的时期,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严重的空气污染非常重要。

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