摘要
本研究结合地面观测资料,ERA5再分析数据和PCT客观分型法,分析了2014~2019年四川盆地区域性O_(3)污染特征以及天气形势与O_(3)污染的关系.结果表明,2014~2019年四川盆地O_(3)区域污染发生频数呈单峰型分布,于2016年达到峰值,且发生区域主要集中在成都平原城市群.在6种典型天气类型中,类型1、2、6为污染型,其海平面气压呈西高东低,四川盆地受低压系统控制.类型3、4为清洁型,其中类型3呈北高南低,且在四川盆地东部存在1个低值中心;类型4呈东高西低,在青藏高原区域有一些小范围的高压中心.在污染型天气形势下,四川盆地的气象条件为温度高、云量低、地面接收到的紫外辐射强、相对湿度低,加速了O_(3)的生成,再叠加类型1的静风条件不利于污染物扩散;类型2、6盛行的东南气流对O_(3)及其前体物的输送,造成污染型天气类型发生区域性O_(3)污染比例明显高于其他几种类型.此外,基于环流分型的预测结果表明环流形势对四川盆地各城市群区域O_(3)污染影响可以达到其年变化的2倍以上,对整个四川盆地O_(3)浓度变化的贡献率为34.8%~66.3%.
The features of regional O_(3)pollution and its relationship between synoptic patterns in Sichuan Basin during 2014~2019 were quantitatively analyzed based on the ambient measurements,ERA5 reanalysis data as well as the PCT objective classification method.The frequency of regional O_(3)pollution in the Sichuan Basin during 2014~2019 showed a unimodal distribution with the highest frequency in 2016.The Chengdu Plain was the most polluted region with elevated O_(3)levels in the Sichuan Basin.Among the six classified synoptic patterns,Type1,2,6 were classified as polluted synoptic patterns which exhibited a western-eastern pressure gradient.Meanwhile,the Sichuan Basin was controlled by a low-pressure system in these synoptic patterns.In contrast,Type3 and Type4 were identified as clean synoptic patterns.The sea level pressure in Type3 was high over the northern SCB and low over the southern SCB,with a low-pressure center located at the eastern Sichuan Basin.Unlike Type3,the sea level pressure in Type4 was higher in the east and lower in the west,with some small-scale high-pressure centers distributed in the Tibetan Plateau.The high temperature,low cloud coverage,strong solar radiation,and low relative humidity in Sichuan Basin under the polluted synoptic types were beneficial to the O_(3)formation.The stagnant conditions in Type1 and the strong regional transport of O_(3)and its precursors by the prevailing southeast wind fields in Type 2 and 6 were primary processes that leading to the frequent regional O_(3)episodes occurred in polluted synoptic types.In addition,the prediction method based on synoptic pattern classification showed that the contribution of synoptic patterns on the inter-annual variability of O_(3)concentration in the Sichuan Basin ranged from 34.8%to 66.3%,with the contribution can even reached more than twice its annual variation of specific city cluster within SCB.
作者
杨显玉
吕雅琼
王禹润
乔玉红
张公亮
王式功
张小玲
刘志红
刘奕麟
朱新胜
YANG Xian-yu;LU Ya-qiong;WANG Yu-run;QIAO Yu-hong;ZHANG Gong-liang;WANG Shi-gong;ZHANG Xiao-ling;LIU Zhi-hong;LIU Yi-lin;ZHU Xin-sheng(Plateau Atmosphere and Environment Key Laboratory of Sichuan Province,School of Atmospheric Sciences,Chengdu University of Information Technology,Chengdu 610225,China;Institute of Mountain Hazards and Environment,Chinese Academy of Sciences,Chengdu 610041,China;Sichuan Academy of Environmental Sciences,Chengdu 610000,China;Chinese Academy of Meteorological Sciences,Beijing 100081,China;Nanjing Institute of Environmental Sciences,Ministry of Environmental Protection,Nanjing 210042,China)
出处
《中国环境科学》
EI
CAS
CSCD
北大核心
2021年第6期2526-2539,共14页
China Environmental Science
基金
国家自然科学基金资助项目(91744209,91644226)
四川省科技计划项目(2018SZDZX0023)
成都市科技局项目(2018-ZM01-00037-SN)
成都信息工程大学创新创业训练计划(201910621132)。
关键词
臭氧污染
天气形势
四川盆地
PCT客观分型法
ozone pollution
synoptic pattern
Sichuan Basin
PCT objective classification method