| 结合外场观测分析珠三角二次有机气溶胶的数值模拟 |
| 摘要点击 4730 全文点击 2346 投稿时间：2013-09-18 修订日期：2013-12-09 |
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| 中文关键词 二次有机气溶胶 数值模拟 地面观测 VBS SORGAM 珠江三角洲 |
| 英文关键词 secondary organic aerosol(SOA) numerical modeling ground-based measurements volatile basis set(VBS) secondary organic aerosol model(SORGAM) Pearl River Delta(PRD) |
| 作者 | 单位 | E-mail | | 郭晓霜 | 中山大学环境科学与工程学院,广州 510275 | gxs09358090@163.com | | 司徒淑娉 | 中山大学环境科学与工程学院,广州 510275 | | | 王雪梅 | 中山大学环境科学与工程学院,广州 510275 | eeswxm@mail.sysu.edu.cn | | 丁翔 | 中国科学院广州地球化学研究所,有机地球化学国家重点实验室,广州 510640 | | | 王新明 | 中国科学院广州地球化学研究所,有机地球化学国家重点实验室,广州 510640 | | | 闫才青 | 北京大学环境科学与工程学院,环境模拟与污染控制国家重点联合实验室,北京 100871 | | | 李小滢 | 北京大学环境科学与工程学院,环境模拟与污染控制国家重点联合实验室,北京 100871 | | | 郑玫 | 北京大学环境科学与工程学院,环境模拟与污染控制国家重点联合实验室,北京 100871 | |
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| 中文摘要 |
| 结合2008年11月18~25日期间珠三角地区的二次有机气溶胶（SOA）外场观测数据，验证区域空气质量模式WRF/Chem（weather research and forecasting model with chemistry）中两种SOA化学机制——VBS（volatile basis set）和SORGAM（secondary organic aerosol model）对珠三角SOA的模拟效果. VBS机制考虑了更为广泛的SOA前体物和化学老化过程，SOA模拟值更接近观测值，能合理反映SOA观测值的逐天变化趋势，与观测值的平均绝对偏差和相关性分别是-4.88 μg·m-3和0.91，而SORGAM机制的分别为-5.32 μg·m-3和0.18. 利用VBS机制模拟区域内SOA的时空分布，结果显示SOA浓度具有显著的昼夜变化特征，浓度峰值出现在中午时段. 受到输送和臭氧区域分布的影响，各城市SOA浓度差异显著，下风向的城市（如中山、珠海、江门）SOA浓度较高. |
| 英文摘要 |
| Two simulations were conducted with different secondary organic aerosol (SOA) methods—VBS (volatile basis set) approach and SORGAM (secondary organic aerosol model), which have been coupled in the WRF/Chem (weather research and forecasting model with chemistry) model. Ground-based observation data from 18th to 25th November 2008 were used to examine the model performance of SOA in the Pearl River Delta(PRD)region. The results showed that VBS approach could better reproduce the temporal variation and magnitude of SOA compared with SORGAM, and the mean absolute deviation and correlation coefficient between the observed and the simulated data using VBS approach were -4.88μg·m-3 and 0.91, respectively, while they were -5.32μg·m-3 and 0.18 with SORGAM. This is mainly because the VBS approach considers SOA precursors with a wider volatility range and the process of chemical aging in SOA formation. Spatiotemporal distribution of SOA in the PRD from the VBS simulation was also analyzed. The results indicated that the SOA has a significant diurnal variation, and the maximal SOA concentration occurred at noon and in the early afternoon. Because of the transport and the considerable spatial distribution of O3, the SOA concentrations were different in different PRD cities, and the highest concentration of SOA was observed in the downwind area, including Zhongshan, Zhuhai and Jiangmen. |
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