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李漫, 高贵生, 贺晓东, 刘琳娥, 李志静, 宋冀凤, 奉姝, 李鹏飞. 本溪市大气主要污染物与气象因素相关性[J]. 中国公共卫生, 2018, 34(1): 130-133. DOI: 10.11847/zgggws1116231
引用本文: 李漫, 高贵生, 贺晓东, 刘琳娥, 李志静, 宋冀凤, 奉姝, 李鹏飞. 本溪市大气主要污染物与气象因素相关性[J]. 中国公共卫生, 2018, 34(1): 130-133. DOI: 10.11847/zgggws1116231
Man LI, Gui-sheng GAO, Xiao-dong HE, . Correlation between main atmospheric pollutants and meteorological factors in Benxi city[J]. Chinese Journal of Public Health, 2018, 34(1): 130-133. DOI: 10.11847/zgggws1116231
Citation: Man LI, Gui-sheng GAO, Xiao-dong HE, . Correlation between main atmospheric pollutants and meteorological factors in Benxi city[J]. Chinese Journal of Public Health, 2018, 34(1): 130-133. DOI: 10.11847/zgggws1116231

本溪市大气主要污染物与气象因素相关性

Correlation between main atmospheric pollutants and meteorological factors in Benxi city

  • 摘要:
      目的  分析本溪市2014 — 2015年大气主要污染物与气象因素的相关性,为大气污染防治提供依据。
      方法  本溪市环境监测站共设立6个大气监测点(溪湖、彩屯、东明、大峪、新立屯和威宁)进行常年大气污染物监测工作。选取 2014 — 2015年大气二氧化硫(SO2)、二氧化氮(NO2)、可吸入颗粒物(PM10)和细颗粒物(PM2.5)日均浓度与气象监测资料进行相关性分析和多元逐步回归分析,找出气象因素与大气污染物浓度的关系及气象因素对大气污染物浓度的影响规律。
      结果  SO2日均浓度与气温和相对湿度呈负相关(r = – 0.793、– 0.288,P均< 0.01);PM10与气温、风速、湿相对度均呈负相关(r = – 0.338、– 0.176、– 0.138,P均< 0.01);NO2与温度和风速呈负相关(r = – 0.507、– 0.313,P均 < 0.01);PM2.5与温度和风速呈负相关(r = – 0.379、– 0.264,P均< 0.01)。
      结论  气象因素与大气污染物浓度密切相关,气象因素对大气污染物浓度的影响有一定规律性,可通过回归方程进行模拟预测。

     

    Abstract:
      Objective  To investigate the correlation between major air pollutants and meteorological factors in Benxi city in 2014 – 2015, and to provide evidences for prevention and control of air pollution.
      Methods  We collected data on daily concentration of the sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter less than 10 μm in aerodynamic diameter (PM10), and particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) at 6 monitoring sites (Xihu, Caitun, Dongming, Dayu, Xinlitun, and Weining) during the period from 2014 through 2015. We also extracted meteorological monitoring data of the same period from Benxi Municipal Meteorological Bureau. Correlation analysis and stepwise regression analysis were used to assess the influences of meteorological factors on concentrations of air pollutants.
      Results  The daily SO2 concentration was negatively correlated to atmospheric temperature and relative humidity (rtem = – 0.793, rRH = – 0.288; both P < 0.01); the concentration of PM10 was negatively associated with atmospheric temperature, humidity, and wind speed (rtem = – 0.338, rwin = – 0.176, rRH = – 0.138; P < 0.01 for all); the concentration of NO2 and PM2.5 were negatively correlated with atmospheric temperature and wind speed (r NO2-tem = – 0.507, r NO2-win = – 0.313; r PM2.5-tem = – 0.379, r PM2.5-win = – 0.264; P < 0.01 for all).
      Conclusion  Meteorological factors are closely related to concentrations of atmospheric pollutants in a manner which could be simulated with regression analysis in Benxi city of Liaoning province.

     

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