| 2013年12月上海市重度污染期间细颗粒物化学特征与输送轨迹影响 |
| 摘要点击 3000 全文点击 1427 投稿时间：2015-10-20 修订日期：2015-12-03 |
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| 中文关键词 灰霾 颗粒物 化学组成 气团轨迹 聚类分析 上海 |
| 英文关键词 haze particles chemical composition air trajectories cluster analysis Shanghai |
| 作者 | 单位 | E-mail | | 周敏 | 上海市环境科学研究院, 上海 200233
国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233 | zhoum@saes.sh.cn | | 乔利平 | 上海市环境科学研究院, 上海 200233
国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233 | | | 朱书慧 | 上海市环境科学研究院, 上海 200233
国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233 | | | 李莉 | 上海市环境科学研究院, 上海 200233
国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233 | lili@saes.sh.cn | | 楼晟荣 | 上海市环境科学研究院, 上海 200233
国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233 | | | 王红丽 | 上海市环境科学研究院, 上海 200233
国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233 | | | 陶士康 | 上海市环境科学研究院, 上海 200233
国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233 | | | 黄成 | 上海市环境科学研究院, 上海 200233
国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233 | | | 陈长虹 | 上海市环境科学研究院, 上海 200233
国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233 | |
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| 中文摘要 |
| 2013年12月我国中东部地区发生多场大范围高强度的颗粒物污染. 期间,本研究采用在线连续观测手段测量了上海市城区大气中气态污染物、颗粒物的质量浓度、细颗粒物的化学组分等,获得了浮尘污染、灰霾污染、雾霾污染、长距离传输的过境污染过程中颗粒物的污染特征变化. 观测结果显示,雾霾污染最为严重,PM10和PM2.5日均最大浓度分别达到536 μg ·m-3和411 μg ·m-3,PM2.5/PM10高达76.7%,高湿度加强了大气颗粒物中NO3-、SO42-、NH4+等二次组分的生成. 浮尘污染中PM2.5的Ca2+浓度在所有污染过程中最高,且PM2.5中一次组分比重明显上升. 长距离传输的过境污染中PM2.5的SO42-浓度最高,且增长速度很快. 同时本研究还采用Hysplit反向轨迹结合聚类分析方法,得到了不同污染过程中到达上海的主要气团轨迹,并结合上海城区在线观测的PM2.5及其化学组分浓度数据,探讨了不同气团下PM2.5组分特征差异和不同污染过程的大致来源. 结果表明,观测期间上海的气团轨迹可以聚类为六类. 其中,移动速度快的cluster6出现时,上海市不易出现颗粒物污染; 始于蒙古的cluster2和cluster3导致上海出现沙尘污染,该气团下PM2.5/PM10的比例都较低,且PM2.5中Ca2+浓度较高. 移动缓慢的cluster5和cluster4有利于污染物的二次生成,静稳天气同时加剧了污染物的累积,加上他们经海上夹带水汽传输至上海,这些不利条件是导致上海出现严重污染的关键因素. |
| 英文摘要 |
| Intensive haze shrouded central and eastern parts of China in Dec. 2013. In this study, the mass concentrations of gaseous and particulate pollutants, and also the chemical compositions of fine particulate matters were obtained based on in-situ measurement in Shanghai urban area. The characteristics of PM2.5 were investigated during different pollution episodes, including dust, haze, fog-haze and long-rang transport episodes. The results showed that pollution was most serious during the fog-haze episode, during which the maximum daily mass concentrations of PM10 and PM2.5 reached 536 μg ·m-3 and 411 μg ·m-3, respectively. During the fog-haze episode, the ratio of PM2.5 to PM10 was over 76.7%, suggesting that high humidity enhanced the secondary formation of NO3-, SO42- and NH4+ in PM2.5. Highest concentration of Ca2+ in PM2.5 occurred during the dust episode and the proportion of primary components in PM2.5 increased obviously. Highest concentration of SO42- was observed in PM2.5 during the long-rang transport episode, with a fast growth rate. Meanwhile, the trajectories reaching Shanghai urban area and cluster analysis during different pollution episodes were simulated by HYSPLIT model. Combined with observation data of PM2.5 in Shanghai urban area, chemical characteristics of PM2.5 in different clusters and potential source apportionment of various pollution episodes were also studied in this study. The result revealed that the air trajectories could be grouped into six clusters based on their spatial similarities. Among these clusters, cluster6 which moved fast was associated with clean air. Cluster2 and cluster3 originating from Mongolia region had strong correlations to dust pollution, along with low PM2.5/PM10 ratio and high concentration of Ca2+ in PM2.5. Compared with other clusters, cluster5 and cluster4 with slow moving speed were more favorable for reactions between particulate species and formation of secondary pollutants during transport. Additionally, the stagnant weather condition under these two clusters with high water vapor when passing over the East China Sea further led to the aggravation of atmospheric pollution in Shanghai. |
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