Estimating Ground-Level PM_2.5 Using Fine-Resolution Satellite Data in the Megacity of Beijing, China

10.4209/aaqr.2015.01.0009

Rong Li；Jianhua Gong；Liangfu Chen；Zifeng Wang

Particulate matter ； Satellite remote sensing ； Statistical models ； Air quality

Aerosol and Air Quality Research

15卷4期（2015 / 08 / 01）

1347 - 1356

英文

Estimating ground-level PM_2.5 in urban areas from satellite-retrieved AOD data is limited because of the coarse resolution of the data. The spatial resolution of recent MODIS Collection 6 aerosol data has increased from 10km to 3km. Taking advantage of this new AOD dataset, we used a mixed effects model to calibrate the day-to-day relationship between satellite AOD and ground-level PM_2.5 concentrations. Regional daily PM_2.5 concentrations were estimated by the AOD from March 1, 2013, to February 28, 2014, in the megacity of Beijing. Compared with the simple linear regression model, the accuracy of the PM_2.5 prediction improved significantly, with an R2 of 0.796 and a root mean squared error of 16.04μg/m^3. The results showed high PM_2.5 concentrations in the intra-urban region of Beijing because of local emissions. The PM_2.5 concentrations were relatively low in the northern rural area but high in the southern rural area, which was close to the industrial sector in Hebei Province. We found that the 3km AOD produces detailed spatial variability in the Beijing area but introduces somewhat large biases due to missing AOD pixels.