The complex morphology of soot aggregates is a major source of uncertainty in evaluating their warming effects in the atmosphere. Fractal dimension (Df) 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 Df. Here we develop a novel image recognition technique to automatically determine the Df 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 Df 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 Df 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 Df 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 Df, enabling an improved understanding of soot aging processes and a more accurate modeling of soot impact on their climate.
Bibliographical noteFunding Information:
This work was funded by the National Natural Science Foundation of China (42,075,096; 91,844,301) and Zhejiang Provincial Natural Science Foundation of China (LZ19D050001).
© 2022. American Geophysical Union. All Rights Reserved.
- aging process
- emission source
- fractal dimension
- image recognition
- soot particle
ASJC Scopus subject areas
- Atmospheric Science
- Earth and Planetary Sciences (miscellaneous)
- Space and Planetary Science