| 上海秋冬季PM2.5污染天气形势的客观分型研究 |
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| 引用本文： | 许建明,常炉予,马井会,毛卓成,陈镭,曹钰.上海秋冬季PM2.5污染天气形势的客观分型研究[J].环境科学学报,2016,36(12):4303-4314. |
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| 作者姓名： | 许建明 常炉予 马井会 毛卓成 陈镭 曹钰 |
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| 作者单位： | 1 上海市气象局, 上海 200030;长三角环境气象预报预警中心, 上海 200030;2 上海市气象与健康重点实验室, 上海 200030,1 上海市气象局, 上海 200030;长三角环境气象预报预警中心, 上海 200030;2 上海市气象与健康重点实验室, 上海 200030,1 上海市气象局, 上海 200030;长三角环境气象预报预警中心, 上海 200030;2 上海市气象与健康重点实验室, 上海 200030,1 上海市气象局, 上海 200030;长三角环境气象预报预警中心, 上海 200030;2 上海市气象与健康重点实验室, 上海 200030,1 上海市气象局, 上海 200030;长三角环境气象预报预警中心, 上海 200030;2 上海市气象与健康重点实验室, 上海 200030,1 上海市气象局, 上海 200030;长三角环境气象预报预警中心, 上海 200030;2 上海市气象与健康重点实验室, 上海 200030 |
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| 基金项目： | 国家重点研发计划（No.SQ2016ZY01003765）；上海市气象局科学技术研究项目（No.QM201517） |
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| 摘 要： | 通过分析2013—2015年上海地面PM_(2.5)质量浓度观测资料,发现11、12、1月3个月对PM_(2.5)年总浓度的贡献达到36.4%,对总污染日数的贡献达到50.4%,对PM_(2.5)环境质量的影响最显著.采用T-mode斜交旋转分解方法(PCT),对2012—2015每年11月、12月和次年1月的海平面气压场和10 m风场进行大样本客观分型研究,揭示了4种秋冬季上海PM_(2.5)易污染的天气环流类型,分别为冷锋(Cw)、高压后部弱气压场(WGh)、高压前部弱气压场(WGl和WGf).对上海而言,冷锋、高后弱气压、高前弱气压分别表现为有利于上游污染输送、本地静稳累积、以及本地积累和上游输送相叠加的天气学特征.对比2个典型污染月(2013年1月和12月)和清洁月(2014年11月和2015年11月)的逐日分型结果发现,Cw环流控制下污染输送对秋冬季上海PM_(2.5)环境质量影响显著,高前弱气压的维持是导致上海3次连续重度污染的重要原因.
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| 关 键 词： | 客观分型 PM2.5重污染 PCT |
| 收稿时间： | 2016/3/21 0:00:00 |
| 修稿时间： | 2016/5/18 0:00:00 |
Objective synoptic weather classification on PM2.5 pollution during autumn and winter seasons in Shanghai |
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| XU Jianming,CHANG Luyu,MA Jinghui,MAO Zhuocheng,CHEN Lei and CAO Yu.Objective synoptic weather classification on PM2.5 pollution during autumn and winter seasons in Shanghai[J].Acta Scientiae Circumstantiae,2016,36(12):4303-4314. |
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| Authors: | XU Jianming CHANG Luyu MA Jinghui MAO Zhuocheng CHEN Lei and CAO Yu |
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| Institution: | Shanghai Meteorological Service, Shanghai 200030;Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai 200030;Shanghai key laboratory of meteorology and health, Shanghai 200030,Shanghai Meteorological Service, Shanghai 200030;Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai 200030;Shanghai key laboratory of meteorology and health, Shanghai 200030,Shanghai Meteorological Service, Shanghai 200030;Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai 200030;Shanghai key laboratory of meteorology and health, Shanghai 200030,Shanghai Meteorological Service, Shanghai 200030;Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai 200030;Shanghai key laboratory of meteorology and health, Shanghai 200030,Shanghai Meteorological Service, Shanghai 200030;Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai 200030;Shanghai key laboratory of meteorology and health, Shanghai 200030 and Shanghai Meteorological Service, Shanghai 200030;Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai 200030;Shanghai key laboratory of meteorology and health, Shanghai 200030 |
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| Abstract: | Based on surface measurements from 2013 to 2015, we found PM2.5 concentrations in November, December, and January were significantly higher than other months in Shanghai. These three months had significant contributions to the total PM2.5 mass concentration (36.4%) and number of pollution days (50.4%). In order to investigate the synoptic conditions favorable for the occurrence and aggravation of PM2.5 pollution in the area, obliquely rotated T-mode principal component analysis (PCT) method was applied for synoptic weather classification using NCEP reanalysis data (i.e. sea level pressure and 10 m winds) for November, December and January of year 2012 to 2015. Four synoptic weather types, including cold font (Cw), weak pressure behind high (WGh) and weak pressure before high (WGl & WGf) were identified to be favorable for inducing PM2.5 pollution. Under the control of Cw and WGh, surface meteorological conditions in Shanghai were conductive for upstream transport and local accumulation respectively. On the other hand, weak local dispersion and significant upstream transport occurred simultaneouslyunder WGl and WGf. By comparing daily synoptic weather types between typical polluted and clean months, we found that transport resulted from Cw had significant impact on autumn and winter PM2.5 levels in Shanghai, whereas persistent severe pollution events were more closely related to WGl & WGf. |
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| Keywords: | synoptic weather classification severe PM2 5 pollution PCT |
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