ESTIMATING PM2.5 IN XI’AN , CHINA USING AEROSOL OPTICAL DEPTH OF NPP VIIRS DATA AND METEOROLOGICAL MEASUREMENTS
- College of Geological Engineering and Surveying, Chang’an University, 710054 Xi’an, China
Keywords: Aerosol optical depth, PM2.5, VIIRS, Remote sensing inversion, Nonlinear model
Abstract. In recent years, the air pollution is becoming more and more serious, which not only causes the decrease of the visibility, but also affects the human health. As the most important pollutant particulate matter, remote sensing satellite measurements have been widely used to estimate PM2.5 concentration on the ground. Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the instruments which is taken in the National Polar-orbiting Partnership (NPP) satellite. In this study, VIIRS was used to retrieve aerosol optical depth (AOD) with the way of dark pixels, and several other major meteorological variables (wind speed, relative humidity, NO2 concentration, ground surface relative humidity and planetary boundary layer height) were combined with AOD to construct a nonlinear multiple regression mode for establishing the relationship between AOD and PM2.5 concentration. The North Basin of Shaanxi province of China, which includes Xi’an, is located in the north of Qinling Mountains, south of the Loess Plateau, and in the central of Weihe basin, with special structure and other adverse weather conditions (static wind, less rain) to cause the frequent haze weather in Xi'an. Xi’an city was selected as the area of the experiment due to its particularity. This research obtained the AOD results from August 1, 2013 to October 30, 2013. The inversion results were compared with ground-based PM2.5 concentration date from air quality monitoring station of Xi’an. The result showed that there is a significant correlation between the two, and the correlation coefficient is 0.783. The inversion result verified that the model of VIIRS data agreed well AOD, which could be used to estimate the surface PM2.5 concentration and monitor the regional air quality.