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Relationship between Coating-Induced Soot Aggregate Restructuring and Primary Particle Number
Kaiser K Leung1, Elijah G Schnitzler2, Ramin Dastanpour3
1Department of Mechanical Engineering, University of Alberta , Edmonton, Alberta, Canada T6G 2G8.
Environmental Science & Technology
|June 30, 2017
Summary
Secondary organic aerosol (SOA) coatings cause soot aggregates to restructure. The degree of restructuring depends linearly on the number of primary particles, enabling morphology prediction for atmospheric models.
Area of Science:
- Atmospheric Chemistry
- Aerosol Science
- Environmental Engineering
Background:
- Soot aggregates are significant atmospheric components.
- Secondary organic aerosols (SOA) influence aggregate properties.
- Understanding soot restructuring is crucial for climate and air quality models.
Purpose of the Study:
- To investigate soot aggregate restructuring caused by secondary organic aerosol (SOA) coatings.
- To determine the factors influencing the morphological evolution of soot aggregates.
- To establish a predictive relationship for soot aggregate restructuring.
Main Methods:
- Generated soot aggregates from three distinct sources (ethylene burner, methane burner, diesel generator).
- Coated soot aggregates with secondary organic aerosols (SOA) from p-xylene photo-oxidation.
- Analyzed aggregate morphology and restructuring using in situ mobility/mass measurements and ex situ transmission electron microscopy.
Main Results:
- Diesel soot aggregates were less dense and restructured to smaller sizes compared to burner-generated aggregates.
- A universal linear relationship was found between the degree of soot aggregate restructuring and the number of primary particles per aggregate.
- This relationship held true for atmospherically relevant SOA coatings.
Conclusions:
- The restructuring of soot aggregates by SOA coatings follows a predictable pattern.
- The number of primary particles is a key factor governing soot aggregate morphology evolution.
- This finding can improve atmospheric models' ability to predict aerosol behavior and climate impact.
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