Black Carbon Aerosols Alter Cloud Microphysical Properties

Riemer, N., University of Illinois, Urbana

Aerosol Processes

Aerosol Processes

Ching J, N Riemer, and M West. 2016. "Black carbon mixing state impacts on cloud microphysical properties: Effects of aerosol plume and environmental conditions." Journal of Geophysical Research: Atmospheres, 121(10), 10.1002/2016jd024851.


Black carbon is usually mixed with other aerosol species within individual aerosol particles. To accurately simulate the impact of black-carbon-containing aerosol particles on clouds, it is important to represent particle composition. Neglecting this information causes errors in the prediction of cloud droplet number concentration and droplet sizes, and of the amount of black carbon that is incorporated by clouds.


Black carbon aerosol is known as an important short-lived climate forcer. It impacts climate by a variety of sometimes counteracting pathways, which makes it difficult to estimate the overall impact of black carbon mitigation strategies. This work provides a framework to quantify the impact of black carbon on clouds, and to estimate the errors that are associated with simplified aerosol representations commonly used in global models.


Our goal was to quantify the impact of black-carbon-containing particles on cloud properties. To this end, the particle-resolved aerosol model PartMC-MOSAIC (Particle Monte Carlo-Model for Simulating Aerosol Interactions and Chemistry) was used to perform a suite of 100 cloud parcel simulations. A wide range of environmental conditions were explored by varying black carbon emission rates, aerosol background concentrations, trace gas concentrations, and ambient updraft speeds during cloud formation. Increases in black carbon concentrations could lead to either increases or decreases in cloud droplet number concentration, with the response depending on the mixing state of the particle population. Moreover, neglecting detailed aerosol composition information led to -12% to +45% error in the fraction of particles that can act as cloud condensation nuclei. Errors in effective radius and spectral dispersion of the cloud droplet distribution ranged from -12% to +4% and -30% to +60%, respectively, and the BC mass fraction removed by nucleation scavenging could potentially be overestimated by a factor of 10. These findings illustrate the need to resolve aerosol mixing state for accurate prediction of cloud droplet number concentration and hence aerosol indirect forcing to reduce uncertainties in climate projection.