大气与环境光学学报 ›› 2016, Vol. 11 ›› Issue (2): 111-117.

• 环境光学监测技术 • 上一篇    下一篇

基于AQI数据的大连夏季空气质量分析

刘淼, 顾吉林, 刘丽娟, 王震, 黄善鹏, 刘颖波, 段婉玲, 冯秋实   

  1. (辽宁师范大学物理与电子技术学院, 辽宁 大连 116021)
  • 收稿日期:2015-10-30 修回日期:2015-11-10 出版日期:2016-03-28 发布日期:2016-03-18
  • 通讯作者: 顾吉林(1981-),辽宁省大连市人,博士,研究生导师,研究方向为大气辐射传输。 E-mail:gujilin@lnnu.edu.cn
  • 作者简介:刘淼(1995-),辽宁省铁岭市人,研究方向为大气光学。
  • 基金资助:

    辽宁省教育厅科学研究一般项目(L2015286),辽宁师范大学青年科研项目(LS2014L004),国家级大学生创新创业训练项目(201510165005)资助

Air Quality Analysis of Dalian in the Summer Based on the Data of AQI

LIU Miao, GU Jilin, LIU Lijuan, WANG Zhen, HUANG Shanpeng, LIU Yingbo, DUAN Wanling, FENG Qiushi   

  1. (School of Physics and Electronic Technology, Liaoning Normal University, Dalian 116029,China)
  • Received:2015-10-30 Revised:2015-11-10 Published:2016-03-28 Online:2016-03-18

摘要:

针对大连市2015年6月至8月10个国控自动空气质量监测站的AQI、PM2.5、PM10、SO2、NO2、CO、O3七个参数进行分析,探讨空气质量指数的日均值变化规律、小时变化规律、特殊污染日的分析及AQI与其他参量的相关性分析。结果表明,2015年大连市夏季空气质量优占44.6%,达标率为97.9%。AQI日均值变化幅度较大,呈波浪型变化趋势,6月至8月AQI变化规律大致相同,8月由于特殊气候影响,AQI数值最大为130.4,而后由于降雨,AQI显著减小。AQI小时变化规律00:00~07:00数据变化缓慢,上班高峰以及下班高峰数据会开始上升,AQI呈波峰、波谷变化。通过相关性计算,AQI与PM2.5、PM10呈显著相关,与CO、NO2、O3呈较好的相关性,而与SO2相关性不明显,为大连市大气污染治理提供依据。

关键词: AQI, 日均值, PM2.5, 空气质量分析, 相关性

Abstract:

The data of seven parameters AQI, PM2.5, PM10, SO2, NO2, CO and O3 from 10 national-controlled automatic air quality monitoring station of Dalian from June to August in 2015 were analyzed to investigate the daily mean change of air quality index, the change of the hour, the special pollution date analysis and the correlation analysis between AQI and other parameters. The results showed that the excellent air quality in Dalian was 44.6%, the standard rate was 97.9% in the summer. The mean change of AQI days was large, and the change trend of AQI wave form was the same from June to August. For the special climate, AQI value maximum was 130.4 in August, and the AQI was significantly decreased due to the rainfall. The regularity of AQI hours 00:00~07:00 when the data changed slowly, the data began to rise in rush hour, and AQI changed between peak and valley. Through correlation calculation, AQI, PM2.5, PM10 were significantly correlated, and CO, NO2, O3 showed a good correlation with AQI. But the correlation between SO2 and AQI was not obvious, which is the basis for the treatment of air pollution in Dalian.

Key words: air quality index, day average, PM2.5, air quality analysis, correlation