Abstract
Aerosol optical depth (AOD) derived from satellite remote sensing is widely used to estimate surface PM2.5 (dry mass concentration of particles with an in situ aerodynamic diameter smaller than 2.5 µm) concentrations. In this research, a two-stage spatio-temporal statistical model for estimating daily surface PM2.5 concentrations in the Guanzhong Basin of China is proposed, using 6 km × 6 km AOD data available from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument as the main variable and meteorological factors, land-cover, and population data as auxiliary variables. The model is validated using a cross-validation method. The linear mixed effects (LME) model used in the first stage could be improved by using a geographically weighted regression (GWR) model or the generalized additive model (GAM) in the second stage, and the predictive capability of the GWR model is better than that of GAM. The two-stage spatio-temporal statistical model of LME and GWR successfully captures the temporal and spatial variations. The coefficient of determination (R2), the bias and the root-mean-squared prediction errors (RMSEs) of the model fitting to the two-stage spatio-temporal models of LME and GWR were 0.802, −0.378 µg/m3, and 12.746 µg/m3, respectively, and the model cross-validation results were 0.703, 1.451 µg/m3, and 15.731 µg/m3, respectively. The model prediction maps show that the topography has a strong influence on the spatial distribution of the PM2.5 concentrations in the Guanzhong Basin, and PM2.5 concentrations vary with the seasons. This method can provide reliable PM2.5 predictions to reduce the bias of exposure assessment in air pollution and health research.
Highlights
Ambient air pollution is associated with human health and, considered as a public health concern worldwide [1,2]
The global Visible Infrared Imaging Radiometer Suite (VIIRS)-retrieved Aerosol optical depth (AOD) was validated with ground-based reference AOD data from the Aerosol Robotic Network (AERONET) [63]; over China, the VIIRS AOD with different quality flags was validated using AERONET data [17]
Sky Radiometer Observation Network (SONET) AOD collocated with the VIIRS overpass time was averaged over one hour (i.e., ±30 min from the VIIRS overpass time) and compared with the VIIRS AOD
Summary
Ambient air pollution is associated with human health and, considered as a public health concern worldwide [1,2]. PM2.5 (the integrated mass concentration of fine particulate matter with aerodynamic diameter less than or equal to 2.5 μm) is used as a measure of the health-related aerosol mass concentration. High concentrations of PM2.5 occur in regions across the world [3] with strong contributions from anthropogenic emissions, biomass burning aerosols, and desert dust, augmented by meteorological conditions conducive for the formation of haze (e.g., References [4,5]). Where anthropogenic emissions occur in certain regions with much industrial activity, traffic, urbanization, etc., and little emission control, such as some developed countries and developing countries like India and China, biomass burning activities such as forest fires and agricultural burning are seasonal and may contribute strongly to the local and reginal air pollution (e.g., Reference [6]). Dust pollution is a serious environmental issue, e.g., in the Atlantic [9], Carpathian Basin (central Europe) [10], Fuerteventura (Canary Islands) [11], Delhi, India [12], and southeast China [13]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
