The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLII-4
19 Sep 2018
 | 19 Sep 2018


J. Chen and X. Huang

Keywords: Himawari-8, Hourly AOD, Hourly PM2.5, Wind, Hubei Province, Observation Frequency

Abstract. Satellite remote sensing can effectively estimate the particulate matter on a large scale. Polar-orbiting satellites have limited frequency of observations, which cannot help us understand PM2.5 evolution. The observation frequency of Himawari-8, a geostationary meteorological satellite, increases to at least once every 10 min. Besides, this satellite can provide the hourly aerosol optical depth (AOD). PM2.5 concentration is closely associated with changes in wind speed. The air quality changes with the variations of wind direction and speed. In Hubei Province, the daily average wind speed varies greatly, while the wind significantly impacts the PM2.5 diffusion. In the present study, a mixed effect regression model is developed which predicts ground-level hourly PM2.5 concentrations in Hubei province and analyzes the hourly time variation trend and spatial distribution characteristics of the near ground PM2.5 concentrations using the annual Himawar-8 Level 2 aerosol product in 2016. The estimated hourly PM2.5 concentrations are consistent well with the surface PM2.5 measurements with high R2 (0.74) and low RMSE (20.5 μg∙m−3). The average estimated PM2.5 in Hubei province during the study is about 46.1 μg∙m−3. A clear regional distribution is shown in the spatial distribution of PM2.5 concentrations, and the PM2.5 concentrations in the central and eastern regions of Hubei Province is significant higher than that of the western region; from the perspective of time change, the pollution peak appears at 15 o'clock in the local time, the average concentration of PM2.5 reaches 50.1 ± 21.8 μg∙m−3; the pollution reaches the lightest at 9 o'clock a.m., and the average PM2.5 concentrations is 41.7 ± 17.5 μg∙m−3. These results are conducive to assessing surface PM2.5 concentrations and monitoring regional air quality.