Quantifying the Fractal Dimension and Morphology of Individual Atmospheric Soot Aggregates
Yuner Pang, Yuanyuan Wang, Zhicheng Wang, Yinxiao Zhang, Lei Liu, Shaofei Kong, Fengshan Liu, Zongbo Shi, Weijun Li
Abstract
Abstract The complex morphology of soot aggregates is a major source of uncertainty in evaluating their warming effects in the atmosphere. Fractal dimension (D f ) is a key parameter in quantifying the morphology of soot particles. Previous studies are mostly based on manual identification of soot monomers in electron microscopic images and are hard to provide comparable results in determination of D f . Here we develop a novel image recognition technique to automatically determine the D f of individual soot aggregates from electron microscopy images. The novel method has been shown to be able to trace the small change of the soot D f from an urban tunnel (1.61 ± 0.19) to its exit (1.70 ± 0.15). By applying this new method, we show a substantial difference in average D f of soot particles emitted from vehicles (1.66 ± 0.17) than from biomass burning (1.75 ± 0.18) and coal burning (1.76 ± 0.18). Average D f of soot from an urban atmosphere (1.77 ± 0.18) is close to that from biomass and coal combustion but much lower than that from a rural atmosphere (1.85 ± 0.13). In summary, the new technique provides an automatic, accurate and reliable quantification of soot morphology D f , enabling an improved understanding of soot aging processes and a more accurate modeling of soot impact on their climate.