| 臭氧污染动态源贡献分析方法及应用初探 |
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| 引用本文： | 李敏辉,朱云,Carey Jang,吴志伟,王书肖,谢阳红,梁俊明,朱振华,叶代启,余斌.臭氧污染动态源贡献分析方法及应用初探[J].环境科学学报,2016,36(7):2297-2304. |
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| 作者姓名： | 李敏辉 朱云 Carey Jang 吴志伟 王书肖 谢阳红 梁俊明 朱振华 叶代启 余斌 |
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| 作者单位： | 华南理工大学环境与能源学院, 广东省大气环境与污染控制重点实验室, 广州 510006,华南理工大学环境与能源学院, 广东省大气环境与污染控制重点实验室, 广州 510006,USEPA/Office of Air Quality Planning & Standards, RTP, NC27711, USA,顺德区环境运输和城市管理局, 佛山 528300,清华大学环境学院, 北京 100084,顺德区环境运输和城市管理局, 佛山 528300,顺德区环境运输和城市管理局, 佛山 528300,华南理工大学环境与能源学院, 广东省大气环境与污染控制重点实验室, 广州 510006,华南理工大学环境与能源学院, 广东省大气环境与污染控制重点实验室, 广州 510006,广州市环境监测中心站, 广州 510030 |
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| 基金项目： | 空气质量管理费效及达标规划评估技术及示范研究（No.2014A050503019）；顺德区大气复合污染机理研究及质量达标规划编制项目（No.x2hjD8143160）；工业点源排放大气汞沉降外场观测及分布特征研究（No.2014J4100089）；珠三角典型工业点源汞排放沉降数值模拟及观测（No.x2hjB2150020）；广东省环境风险防控与应急处置工程技术研究中心（No.b2152120） |
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| 摘 要： | 论文创新提出了基于RSM/CMAQ臭氧污染动态源贡献分析方法,并以佛山市顺德区2014年10月为例,分析了不同区域的人为可控源NO_x和VOCs减排情景下(10%、70%和100%)对本地O_3浓度变化的量化贡献.研究结果表明顺德区O_3的人为可控比例约43%,且受区域排放影响非常明显,主导上风向广州排放源总贡献(14%)超过顺德本地贡献(7%).VOCs的减排可有效削减顺德区O_3浓度,当减排力度较小时(12%),若仅控制区域NO_x排放将导致顺德区O_3浓度上升,随着减排力度的加大,区域NO_x的削减贡献会反超VOCs.RSM/CMAQ动态源贡献分析方法可为空气质量管理提供科学决策依据.
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| 关 键 词： | 臭氧 曲面响应模型 空气质量模型 动态源贡献分析 空气质量管理 |
| 收稿时间： | 2015/9/17 0:00:00 |
| 修稿时间： | 2015/11/23 0:00:00 |
Dynamic source contribution analysis of ozone and its preliminary application |
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| LI Minhui,ZHU Yun,Carey Jang,WU Zhiwei,WANG Shuxiao,XIE Yanghong,LIANG Junming,ZHU Zhenhu,YE Daiqi and YU bin.Dynamic source contribution analysis of ozone and its preliminary application[J].Acta Scientiae Circumstantiae,2016,36(7):2297-2304. |
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| Authors: | LI Minhui ZHU Yun Carey Jang WU Zhiwei WANG Shuxiao XIE Yanghong LIANG Junming ZHU Zhenhu YE Daiqi and YU bin |
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| Institution: | Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou 510006,Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou 510006,USEPA/Office of Air Quality Planning & Standards, RTP, NC27711, USA,Environment & Transportation and City Authority of Shunde District, Foshan 528300,School of Environment, Tsinghua University, Beijing 100084,Environment & Transportation and City Authority of Shunde District, Foshan 528300,Environment & Transportation and City Authority of Shunde District, Foshan 528300,Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou 510006,Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou 510006 and Guangzhou Environmental Monitoring Center, Guangzhou 510030 |
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| Abstract: | This paper describes a dynamic source contribution analysis method of ozone based on Response Surface Model (RSM). The case of Shunde District of Foshan City in Guangdong, China in October 2014 was used to analyze the contributions of pollutant emissions to ambient O3 concentrations at different NOx and VOCs emission control scenarios of 10%, 70% and 100% reductions in multiple regions. The results showed that the controllable proportion of anthropogenic O3 in Shunde was about 43%, and it was dominated by regional transported pollutants. Guangzhou, as the main upwind city in October 2014, contributed 14% by regional transport and was larger than the local contribution of Shunde (7%). The emission control of VOCs could reduce O3 concentration of Shunde effectively. O3 concentration could increase when the NOx emission control was less than 12% without VOCs emission control. However, O3 concentration would decrease with co-control on NOx and VOCs emissions. The contribution of NOx control could be even larger than that of VOCs control under the higher emissions control strength. The dynamic source contribution analysis based on RSM can provide an effective and scientific support for air quality management of O3. |
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| Keywords: | ozone response surface model air quality model dynamic source contribution analysis air quality management |
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