Application of APCA-MLR receptor model for source apportionment of char and soot in sediments

Abstract

Black carbon (char and soot) has attracted increasing attention due to its important role in the global carbon cycle, adsorption of pollutants (polycyclic aromatic hydrocarbons (PAHs) and heavy metals), climate effects and threats to human health. However, few studies have included source analysis of black carbon (char and soot). In this study, the levels of char, soot and PAHs in sediments of West Taihu Lake were assessed, and an absolute principal component analysis followed by multiple linear regression (APCA-MLR) receptor model was used to successfully analyze the material sources of char and soot, providing a new perspective and method for exploring the sources of char and soot. The contributions of coal combustion sources to char and soot are 62.0% and 43.2%, respectively, which are significantly higher than those of biomass combustion sources (13.7% and 19.8%). The contributions of oil combustion sources to char and soot are 24.3% and 37.0%, respectively. The contributions of coal, oil and biomass combustion to char and soot have similar spatial distributions: the coal combustion sources and biomass combustion sources are mainly affected by urban development, which is largely distributed in the northwest of the study area, whereas the oil combustion sources are mainly affected by automobile traffic and lake ports, which are mainly distributed in the west of the study area, and these effects decrease with an increase in offshore distance.