| 上海典型持续性PM2.5重度污染的数值模拟 |
| 摘要点击 2983 全文点击 1285 投稿时间：2015-07-08 修订日期：2015-10-08 |
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| 中文关键词 PM2.5 污染特征 WRF-Chem 上海 输送通量 |
| 英文关键词 PM2.5 pollution characteristics WRF-Chem Shanghai transportation flux |
| 作者 | 单位 | E-mail | | 常炉予 | 上海市气象局, 上海 200030
长三角环境气象预报预警中心, 上海 200135 | changluyu1989@126.com | | 许建明 | 上海市气象局, 上海 200030
长三角环境气象预报预警中心, 上海 200135 | metxujm@163.com | | 周广强 | 上海市气象局, 上海 200030
长三角环境气象预报预警中心, 上海 200135 | | | 吴剑斌 | 上海市气象局, 上海 200030
长三角环境气象预报预警中心, 上海 200135 | | | 谢英 | 上海市气象局, 上海 200030
长三角环境气象预报预警中心, 上海 200135 | | | 余钟奇 | 上海市气象局, 上海 200030
长三角环境气象预报预警中心, 上海 200135 | | | 杨辰 | 上海市气象灾害防御工程技术中心, 上海 200030 | |
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| 中文摘要 |
| 本研究针对2013年1月23~24日的上海PM2.5持续重污染过程,采用WRF-Chem大气化学模式以及PM2.5质量浓度、能见度、气象要素等地面实测资料相结合的方式,揭示了造成上海冬季PM2.5持续性重污染的一类"天气学必要成因",即一次弱冷空气活动过程导致了两种不利污染天气条件——"弱气压场(静稳形势)"和"弱冷空气扩散(输送形势)",两者先后影响上海造成PM2.5浓度持续上升. 主要过程如下:首先弱冷空气影响之前,上海处在不利的局地气象扩散条件下,受弱气压场控制10 h后本地PM2.5质量浓度达到重度污染水平,之后夜间稳定边界层(地面静风和低层逆温)使得PM2.5重度污染维持了7 h,期间PM2.5平均质量浓度为172.4 μg ·m-3. 后期弱冷空气影响上海,虽然改善了局地扩散条件但是同时产生了明显的周边污染物输送,使得本地PM2.5质量浓度升高并达到峰值(280 μg ·m-3),继续加重污染水平,期间PM2.5平均质量浓度为213.6 μg ·m-3. WRF-Chem模拟结果进一步表明,整个污染过程周边区域输送对上海PM2.5平均贡献率为23%,其中两个阶段周边区域输送的平均贡献率分别为17.2%和32.2%,可见在不同的污染天气条件下周边污染源的贡献存在显著差异,因此可以根据对污染天气类型的预判制定应急减排方案. |
| 英文摘要 |
| To analyze the characteristics and formation mechanism of a heavy air pollution episode in Shanghai City from January 23th to January 24th, 2013, the observed data of PM2.5 concentration and ground meteorological data and the WRF-Chem model were collected. The analysis revealed that the synoptic necessary mechanism of the heavy air pollution episode could be characterized by the following patterns: Accompanied with weak cold front activities, the city experienced weak winds (i.e. stable atmosphere) at first and then northerly winds (i.e. pollutant transport process), causing the continuous increase and maintaining of pollutant concentration. The detailed results are shown as follows: Firstly, the stable atmosphere circulation pattern which lasted for 10 hours was not good for air pollution dispersion, as a result, local PM2.5 concentrations continued to increase and reached severe pollution level and the high concentrations maintained for 7 hours caused by the stable boundary layer (e.g. static surface winds and low level temperature inversion) during nighttime, and the average PM2.5 concentrations during the stable weather process was 172.4 μg ·m-3. Secondly, the dispersion condition was slightly improved later on with the arrival of a weak cold front, the upstream pollution transportation occurred at the same time, leading to further increase of PM2.5 concentration (up to 280 μg ·m-3), and the average PM2.5 concentration during the upstream transportation process was 213.6 μg ·m-3. Numerical simulation with the WRF-Chem model showed that, average contribution of upstream transportation to local PM2.5 concentrations during the episode was 23%. Among them, the contribution during the stable weather and upstream transportation stage was 17.2% and 32.2%. Our results suggested that there were significant differences in the contribution of upstream transportation to the local PM2.5 concentration of Shanghai due to variation of weather conditions. Therefore, the government can design effective emission control strategy in advance taking pollution weather forecasting into account. |
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