Volume 8 Issue 5
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Article Navigation >  Journal of Environmental Engineering Technology  > 2018  >  8(5): 533-538
XIONG Junli, LI Caiyan. Study on variation characteristics and estimation model of PM2.5 concentration in Beijing in winter[J]. Journal of Environmental Engineering Technology, 2018, 8(5): 533-538. doi: 10.3969/j.issn.1674-991X.2018.05.070
Citation: XIONG Junli, LI Caiyan. Study on variation characteristics and estimation model of PM2.5 concentration in Beijing in winter[J]. Journal of Environmental Engineering Technology, 2018, 8(5): 533-538. doi: 10.3969/j.issn.1674-991X.2018.05.070
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Study on variation characteristics and estimation model of PM2.5 concentration in Beijing in winter

doi: 10.3969/j.issn.1674-991X.2018.05.070

  • Hunan Baohua Environmental Protection Co., Ltd., Changsha 410004, China

  • Received Date: 2018-03-22
  • Publish Date: 2018-09-20
    Abstract
  • Based on the hourly air quality monitoring data in Beijing in January 2017, the hourly and regional changes of the concentration of PM2.5 in Beijing were discussed, and the estimation models of PM2.5, PM10 and major gaseous pollutants of 12 sites were constructed by multiple stepwise regression. The results showed that the hourly concentration change trend of PM2.5 concentration in Beijing was high at night (18:00-07:00) and low in the daytime (08:00-17:00), the monthly averaged PM2.5 concentrations of 3 sites in Huairou Town, Changping Town and Dingling were relatively low (78-94 μg∕m 3), while that of other sites were between 106-128 μg∕m 3. The correlation between PM10, 4 kinds of gaseous pollutants and PM2.5 was in the order of PM10>CO>NO2>O3>SO2. The adjustment coefficient R adj 2 of the PM2.5 concentration estimation model of the 12 sites was all more than 0.96, and the standard error SE was between 13.6-24.5. It is more effective to estimate the PM2.5 concentration of the site by using the estimation model of the site itself, and the effect of estimating the PM2.5 concentration was poorer by using the data of other sites.

     

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