PM2.5 over North China based on MODIS AOD and effect of meteorological elements during 2003‒2015
Youfang Chen, Yimin Zhou, Xinyi Zhao
PM2.5 over North China based on MODIS AOD and effect of meteorological elements during 2003‒2015
• The Taihang Mountains was the boundary between high and low pollution areas.
• There were one high value center for PM2.5 pollution and two low value centers.
• In 2004, 2009 and after 2013, PM2.5 concentration was relatively low.
Over the past 40 years, PM2.5 pollution in North China has become increasingly serious and progressively exposes the densely populated areas to pollutants. However, due to limited ground data, it is challenging to estimate accurate PM2.5 exposure levels, further making it unfavorable for the prediction and prevention of PM2.5 pollutions. This paper therefore uses the mixed effect model to estimate daily PM2.5 concentrations of North China between 2003 and 2015 with ground observation data and MODIS AOD satellite data. The tempo-spatial characteristics of PM2.5 and the influence of meteorological elements on PM2.5 is discussed with EOF and canonical correlation analysis respectively. Results show that overall R2 is 0.36 and the root mean squared predicted error was 30.1 μg/m3 for the model prediction. Our time series analysis showed that, the Taihang Mountains acted as a boundary between the high and low pollution areas in North China; while the northern part of Henan Province, the southern part of Hebei Province and the western part of Shandong Province were the most polluted areas. Although, in 2004, 2009 and dates after 2013, PM2.5 concentrations were relatively low. Meteorological/topography conditions, that include high surface humidity of area in the range of 34°‒40°N and 119°‒124°E, relatively low boundary layer heights, and southerly and easterly winds from the east and north area were common factors attributed to haze in the most polluted area. Overall, the spatial distribution of increasingly concentrated PM2.5 pollution in North China are consistent with the local emission level, unfavorable meteorological conditions and topographic changes.
Aerosol optical depth / PM2.5 / MODIS / Mixed effect model / Canonical correlation analysis
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