Articles | Volume 21, issue 23
https://doi.org/10.5194/acp-21-17727-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-21-17727-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model
Zhonghua Zheng
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Matthew West
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Po-Lun Ma
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
Xiaohong Liu
Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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Cited
13 citations as recorded by crossref.
- The impacts of aerosol mixing state on heterogeneous N 2 O 5 hydrolysis Y. Liu et al. 10.1080/02786826.2024.2443587
- Integrating Simulations and Observations: A Foundation Model for Estimating the Aerosol Mixing State Index F. Jiang et al. 10.1021/acsestair.4c00329
- How does tropospheric VOC chemistry affect climate? An investigation of preindustrial control simulations using the Community Earth System Model version 2 N. Stanton & N. Tandon 10.5194/acp-23-9191-2023
- Enhanced Aging of Black Carbon under Recent Clean Air Actions and Future Carbon Neutrality Scenario in China W. Shen et al. 10.1021/acs.est.4c02030
- Global organic and inorganic aerosol hygroscopicity and its effect on radiative forcing M. Pöhlker et al. 10.1038/s41467-023-41695-8
- Evaluating BC Aging Processes in the Community Atmosphere Model Version 6 (CAM6) W. Shen et al. 10.1029/2022JD037427
- Morphology and Fractal Dimension of Size‐Resolved Soot Particles Emitted From Combustion Sources Y. Pang et al. 10.1029/2022JD037711
- Quantifying evolution of soot mixing state from transboundary transport of biomass burning emissions X. Chen et al. 10.1016/j.isci.2023.108125
- Measurements of the Optical Scattering Properties of Single Suspended Particles and Implications for Atmospheric Studies: A Review W. Yao et al. 10.1007/s40726-024-00323-9
- Quantifying particle-to-particle heterogeneity in aerosol hygroscopicity L. Yuan & C. Zhao 10.5194/acp-23-3195-2023
- Explicit stochastic advection algorithms for the regional-scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0) J. Curtis et al. 10.5194/gmd-17-8399-2024
- Enhancing Fine Aerosol Simulations in the Remote Atmosphere with Machine Learning M. Lu & C. Gao 10.3390/atmos15111356
- A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0) L. Li et al. 10.5194/gmd-16-4017-2023
13 citations as recorded by crossref.
- The impacts of aerosol mixing state on heterogeneous N 2 O 5 hydrolysis Y. Liu et al. 10.1080/02786826.2024.2443587
- Integrating Simulations and Observations: A Foundation Model for Estimating the Aerosol Mixing State Index F. Jiang et al. 10.1021/acsestair.4c00329
- How does tropospheric VOC chemistry affect climate? An investigation of preindustrial control simulations using the Community Earth System Model version 2 N. Stanton & N. Tandon 10.5194/acp-23-9191-2023
- Enhanced Aging of Black Carbon under Recent Clean Air Actions and Future Carbon Neutrality Scenario in China W. Shen et al. 10.1021/acs.est.4c02030
- Global organic and inorganic aerosol hygroscopicity and its effect on radiative forcing M. Pöhlker et al. 10.1038/s41467-023-41695-8
- Evaluating BC Aging Processes in the Community Atmosphere Model Version 6 (CAM6) W. Shen et al. 10.1029/2022JD037427
- Morphology and Fractal Dimension of Size‐Resolved Soot Particles Emitted From Combustion Sources Y. Pang et al. 10.1029/2022JD037711
- Quantifying evolution of soot mixing state from transboundary transport of biomass burning emissions X. Chen et al. 10.1016/j.isci.2023.108125
- Measurements of the Optical Scattering Properties of Single Suspended Particles and Implications for Atmospheric Studies: A Review W. Yao et al. 10.1007/s40726-024-00323-9
- Quantifying particle-to-particle heterogeneity in aerosol hygroscopicity L. Yuan & C. Zhao 10.5194/acp-23-3195-2023
- Explicit stochastic advection algorithms for the regional-scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0) J. Curtis et al. 10.5194/gmd-17-8399-2024
- Enhancing Fine Aerosol Simulations in the Remote Atmosphere with Machine Learning M. Lu & C. Gao 10.3390/atmos15111356
- A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0) L. Li et al. 10.5194/gmd-16-4017-2023
Latest update: 08 May 2025
Short summary
Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. We present a framework for evaluating the error in aerosol mixing state induced by aerosol representation assumptions, which is one of the important contributors to structural uncertainty in aerosol models. Our study provides insights into potential improvements to model process representation for aerosols.
Aerosol mixing state is an important emergent property that affects aerosol radiative forcing...
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