Volume 11 Issue 2
Mar.  2021
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LI Na, ZHOU Tao, LIU Xiaoxue, XU Min, LI Hongxing. Characteristics of ozone pollution and its relationship with meteorological factors in Langfang City[J]. Journal of Environmental Engineering Technology, 2021, 11(2): 217-225. doi: 10.12153/j.issn.1674-991X.20200147
Citation: LI Na, ZHOU Tao, LIU Xiaoxue, XU Min, LI Hongxing. Characteristics of ozone pollution and its relationship with meteorological factors in Langfang City[J]. Journal of Environmental Engineering Technology, 2021, 11(2): 217-225. doi: 10.12153/j.issn.1674-991X.20200147

Characteristics of ozone pollution and its relationship with meteorological factors in Langfang City

doi: 10.12153/j.issn.1674-991X.20200147
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  • Corresponding author: XU Min E-mail: hblfxm@163.com
  • Received Date: 2020-06-09
  • Publish Date: 2021-03-20
  • The over-standard characteristics of the surface O3 in Langfang City and its relationship with meteorological factors were discussed by using the hourly data of 4 environmental monitoring stations and the continuous observation data of the national meteorological station in Langfang City from 2014 to 2019 with statistical methods. The results showed that the phenomenon of O3 exceeding the standard mainly appeared from May to September and had obvious seasonal characteristics. The diurnal distribution of the over-standard rate of O3 presented a clear unimodal pattern with its peak appearing around 16:00 for O3 1 h concentration and 19:00 for O3 8 h concentration. The O3 8 h concentration was positively correlated with daily average temperature, and was negative correlated with daily mean sea level pressure, and was nonlinear correlated with daily average relative humidity and wind speed. The concentration of ozone was easy to exceed the standard in Langfang City with the daily mean temperature higher than 25 ℃, daily mean relative humidity was 40%-80%, wind direction were south and east, daily mean wind speed was 0.5-2.5 m/s and daily mean sea level pressure less than 1 010 hPa. The prediction equation of O3 8 h concentration from May to September was established by multiple linear regression method, and the results showed that the prediction model had good fitting degree and accurate predictability.

     

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