Quantifying cloud chemical processes and aerosol optical properties using a particle–resolved aerosol model

Yao, Yu

Permalink

https://hdl.handle.net/2142/113992 Copy

Description

Title

Quantifying cloud chemical processes and aerosol optical properties using a particle–resolved aerosol model

Author(s)

Yao, Yu

Issue Date

2021-12-03

Director of Research (if dissertation) or Advisor (if thesis)

Riemer, Nicole

Doctoral Committee Chair(s)

Riemer, Nicole

Committee Member(s)

• Lasher-Trapp, Sonia
• West, Matthew
• Dawson, Matt

Department of Study

Atmospheric Sciences

Discipline

Atmospheric Sciences

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• cloud process
• aerosol mixing state
• CCN
• particle-resolved
• aqueous chemistry
• aerosol radiative effects

Abstract

Aerosol particles exert substantial radiative effects on the Earth's climate directly by scattering and absorbing incoming solar radiation, and indirectly by interacting with clouds. These climate effects depend on particle size distributions and chemical composition, and these properties evolve as particles are transported in the atmosphere. As an important aging process, cloud processing changes particle size and composition through cloud chemistry and in-cloud coagulation. These processes are highly affected by per-particle properties, by determining which particles can be activated and which reactions occur within each droplet. It is challenging for global or regional models with simplified aerosol representations to accurately capture these processes. The aim of the first part of this thesis was to (1) quantify the changes of aerosol mixing state and microphysical properties after cloud processing (2) quantify the role of coagulation between the interstitial particles and cloud droplets for mixing state of the aerosol. By coupling an aqueous chemistry mechanism to the particle-resolved model PartMC-MOSAIC, the new model was able to track the evolution of compositions and sizes of individual aerosol particles in the cloud without averaging their composition within size bins or modes. Aqueous-phase chemistry processes caused aerosol populations to be more internally mixed, and cloud condensation nuclei concentrations increased substantially after cloud processing for supersaturation levels lower than the maximum cloud supersaturation. Coagulation within clouds had a negligible impact on aerosol mixing state. The aim of the second part of the thesis was to systematically quantify the impact of aerosol mixing state on aerosol optical properties. To this end, I created a reference scenario library with aerosol populations of a wide range of mixing states using the particle-resolved model PartMC-MOSAIC. The impact of aerosol mixing state on optical properties was quantified by comparing the reference populations to populations with the same number and mass size distributions but with averaged aerosol composition in prescribed size bins. Particle absorption coefficients were universally overestimated after using internal mixture assumptions, with the overestimation reaching up to 70% for externally-mixed populations. In contrast, scattering coefficients were underestimated, with a maximum error of -32%. Overall, this led to an underestimation in single scattering albedo of up to -22%. The environmental relative humidity and associated aerosol water uptake only had a small impact on the magnitude of these errors.

Graduation Semester

2021-12

Type of Resource

Thesis

Permalink

http://hdl.handle.net/2142/113992

Copyright and License Information

Copyright 2021 Yu Yao

Owning Collections