Aerosol optical depth (AOD) derived from satellite remote sensing is widely used to estimate surface PM_2.5 (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 PM_2.5 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 PM_2.5 concentrations in the Guanzhong Basin, and PM_2.5 concentrations vary with the seasons. This method can provide reliable PM_2.5 predictions to reduce the bias of exposure assessment in air pollution and health research.

To investigate aerosol radiative effects, the Sun–Sky Radiometer Observation Network (SONET) has performed long-term observations of columnar atmospheric aerosol properties at 20 distributed stations around China. The aerosol direct radiative forcing (RF) and efficiency (RFE, the rate at which the atmosphere is forced per unit of aerosol optical depth) were estimated using radiative transfer model simulations based on the ground-based observations dating back to 2009. Results of multi-year monthly average RF illustrated that: the dust-dominant aerosol population at arid and semi-arid sites exerted moderate cooling effects (−8.0~−31.2 W/m²) at the top and bottom of atmosphere (TOA and BOA); RF at continental background site was very weak (−0.8~−2.9 W/m²); fine-mode dominant aerosols at urban and suburban sites exerted moderate cooling effects (−9.3~−24.1 W/m²) at TOA but more significant cooling effects (−19.4~−50.6 W/m²) at BOA; RF at coastal sites was comparable with values of urban sites (−5.5~−19.5 W/m² at TOA, and −15.6~−44.6 W/m² at BOA), owing to combined influences by marine and urban–industrial aerosols. Differences between RFE at TOA and BOA indicated that coarse-mode dominant aerosols at arid, semi-arid, and continental background sites were less efficient to warm the atmosphere; but fine-mode dominant aerosols at urban, suburban, and coastal sites were shown to be more efficient to heat the atmosphere.

A thorough understanding of aerosol optical properties and their spatio-temporal variability are required to accurately evaluate aerosol effects in the climate system. In this study, a multi-year study of aerosol optical and microphysical properties was firstly performed in Xi’an based on three years of sun photometer remote sensing measurements from 2012 to 2015. The multi-year average of aerosol optical depth (AOD) at 440 nm was about 0.88 ± 0.24 (mean ± SD), while the averaged Ångström Exponent (AE) between 440 and 870 nm was 1.02 ± 0.15. The mean value of single scattering albedo (SSA) was around 0.89 ± 0.03. Aerosol optical depth and AE showed different seasonal variation patterns. Aerosol optical depth was slightly higher in winter (0.99 ± 0.36) than in other seasons (~0.85 ± 0.20), while AE showed its minimum in spring (0.85 ± 0.05) due to the impact of dust episodes. The seasonal variations of volume particle size distribution, spectral refractive index, SSA, and asymmetry factor were also analyzed to characterize aerosols over this region. Based on the aerosol products derived from sun photometer measurements, the classification of aerosol types was also conducted using two different methods in this region. Results show that the dominant aerosol types are absorbers in all seasons, especially in winter, demonstrating the strong absorptivity of aerosols in Xi’an.