Application of Gaussian Mixture Models for aerosol type analysis in China

Abstract

The relative contributions of different aerosol types to the total aerosol content were determined using sun photometer derived inversion data from four Aerosol Robotic Network (AERONET) stations in China, i.e. Beijing, NUIST, Hong Kong PolyU and SACOL. Five main aerosol types were considered: dust (DU), mixed (MI), urban industry (UI), biomass burning (BB) and maritime (MA). The identification of these aerosol types is based on cluster analysis using Gaussian mixture models (GMMs), together with the Mahalanobis distance (MD) to each reference centroid. The results show that the aerosol types are distinctly different between the different sites as regards fine and coarse particles. MI is the dominant aerosol type at four locations, with the largest contribution at NUIST (73.4%). The largest contribution of DU (18.8%) is observed at SACOL and at Beijing the contribution of UI is largest (33.7%). BB contributions are relatively small, with the largest at NUIST (2.7%). For the analysis, two periods are considered, i.e. before and after the implementation of the national ambient air quality standard (GB3095–2012) in 2012. The clustering results revealed a changing trend in the proportion of UI and MI aerosols in Chinese cities. Although the proportion of UI aerosols has increased, MI aerosols still remain dominant. The proportion of DU in SACOL station also increased. The seasonal analysis shows that DU dominates in spring at the SACOL station (55.3%), which is near the dust source area. Among the other stations, the contribution of DU due to long-range transport from the source regions, is largest (10.6%) in Beijing, with a small contribution at NUIST. The aerosol volume size distributions in different regions exhibit substantial differences due to variations in aerosol types: Beijing and SACOL are dominated by coarse mode particles, while NUIST and Hong Kong PolyU are dominated by fine mode particles.