Peer-Reviewed Journal Details
Mandatory Fields
Willis, MD;Healy, RM;Riemer, N;West, M;Wang, JM;Jeong, CH;Wenger, JC;Evans, GJ;Abbatt, JPD;Lee, AKY
2016
January
Atmospheric Chemistry and Physics
Quantification of black carbon mixing state from traffic: implications for aerosol optical properties
Validated
Optional Fields
SINGLE-PARTICLE CHARACTERIZATION POSITIVE MATRIX FACTORIZATION MASS-SPECTROMETER DEVELOPMENT LIGHT-SCATTERING MODULE EUROPEAN MEGACITY PARIS ORGANIC AEROSOL SOOT PARTICLES BROWN CARBON PHOTOACOUSTIC SPECTROMETER HYGROSCOPIC PROPERTIES
16
4693
4706
The climatic impacts of black carbon (BC) aerosol, an important absorber of solar radiation in the atmosphere, remain poorly constrained and are intimately related to its particle-scale physical and chemical properties. Using particle-resolved modelling informed by quantitative measurements from a soot-particle aerosol mass spectrometer, we confirm that the mixing state (the distribution of co-emitted aerosol amongst fresh BC-containing particles) at the time of emission significantly affects BC-aerosol optical properties even after a day of atmospheric processing. Both single particle and ensemble aerosol mass spectrometry observations indicate that BC near the point of emission co-exists with hydrocarbon-like organic aerosol (HOA) in two distinct particle types: HOA-rich and BC-rich particles. The average mass fraction of black carbon in HOA-rich and BC-rich particle classes was < 0.1 and 0.8, respectively. Notably, approximately 90aEuro-% of BC mass resides in BC-rich particles. This new measurement capability provides quantitative insight into the physical and chemical nature of BC-containing particles and is used to drive a particle-resolved aerosol box model. Significant differences in calculated single scattering albedo (an increase of 0.1) arise from accurate treatment of initial particle mixing state as compared to the assumption of uniform aerosol composition at the point of BC injection into the atmosphere.
GOTTINGEN
1680-7316
10.5194/acp-16-4693-2016
Grant Details