Articles | Volume 20, issue 11
https://doi.org/10.5194/acp-20-6455-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-6455-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Jun 2020
Research article |
| 04 Jun 2020
| 04 Jun 2020
Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ
Department of Atmospheric and Oceanic Sciences, University of
California – Los Angeles, Los Angeles, CA, USA
Institute of the Environment and Sustainability, University of
California – Los Angeles, Los Angeles, CA, USA
Department of Geography, Hong Kong Baptist University, Hong Kong SAR,
China
Zifeng Lu
Energy Systems Division, Argonne National Laboratory, Lemont, IL
60439, USA
Daniel L. Goldberg
Energy Systems Division, Argonne National Laboratory, Lemont, IL
60439, USA
David G. Streets
Energy Systems Division, Argonne National Laboratory, Lemont, IL
60439, USA
Jung-Hun Woo
Department of Technology Fusion Engineering, Konkuk University, Seoul,
South Korea
Andreas Beyersdorf
Department of Chemistry & Biochemistry, California State University
San Bernardino, San Bernardino, CA, USA
Chelsea A. Corr
USDA UV-B Monitoring and Research Program, Natural Resource Ecology
Laboratory, Colorado State University, Fort Collins, CO, USA
Kenneth L. Thornhill
NASA Langley Research Center, Hampton, VA, USA
Science Systems and Applications Inc., Hampton, VA USA
Bruce Anderson
NASA Langley Research Center, Hampton, VA, USA
Johnathan W. Hair
NASA Langley Research Center, Hampton, VA, USA
Amin R. Nehrir
NASA Langley Research Center, Hampton, VA, USA
Glenn S. Diskin
NASA Langley Research Center, Hampton, VA, USA
Jose L. Jimenez
Department of Chemistry, and Cooperative Institute for Research in
Environmental Sciences, University of Colorado, Boulder, CO, USA
Benjamin A. Nault
Department of Chemistry, and Cooperative Institute for Research in
Environmental Sciences, University of Colorado, Boulder, CO, USA
Pedro Campuzano-Jost
Department of Chemistry, and Cooperative Institute for Research in
Environmental Sciences, University of Colorado, Boulder, CO, USA
Jack Dibb
Institute for the Study of Earth, Oceans, and Space, University of
New Hampshire, Durham, NH, USA
Eric Heim
Institute for the Study of Earth, Oceans, and Space, University of
New Hampshire, Durham, NH, USA
Kara D. Lamb
Chemical Sciences Laboratory, Earth System Research Laboratories, Boulder, CO, USA
Joshua P. Schwarz
Chemical Sciences Laboratory, Earth System Research Laboratories, Boulder, CO, USA
Anne E. Perring
Department of Chemistry, Colgate University, Hamilton, NY, USA
Jhoon Kim
Department of Atmospheric Sciences, Yonsei University, Seoul, 03722,
Korea
Myungje Choi
Department of Atmospheric Sciences, Yonsei University, Seoul, 03722,
Korea
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Brent Holben
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Gabriele Pfister
Atmospheric Chemistry Observations and Modeling Lab, National Center
for Atmospheric Research, Boulder, CO, USA
Alma Hodzic
Atmospheric Chemistry Observations and Modeling Lab, National Center
for Atmospheric Research, Boulder, CO, USA
Gregory R. Carmichael
Center for Global & Regional Environmental Research, University of
Iowa, Iowa City, Iowa, USA
Louisa Emmons
Atmospheric Chemistry Observations and Modeling Lab, National Center
for Atmospheric Research, Boulder, CO, USA
James H. Crawford
NASA Langley Research Center, Hampton, VA, USA
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Cited
25 citations as recorded by crossref.
- Optical Properties of Boundary Layer Aerosols From High Spectral Resolution Lidar Measurements in a Polluted Urban Environment (Seoul, Korea) S. Park et al. https://doi.org/10.1029/2023JD038523
- A Lagrangian view on severe haze in Beijing: local and long-range sources of trace gases and primary and secondary aerosols B. Foreback et al. https://doi.org/10.1016/j.atmosenv.2025.121602
- Evaluation of accuracy on bottom-up NH3 emissions and sensitivity of PM2.5 to emission control in South Korea K. Han et al. https://doi.org/10.1016/j.atmosenv.2025.121434
- Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire X. Ye et al. https://doi.org/10.5194/acp-21-14427-2021
- Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the southeastern Atlantic S. Doherty et al. https://doi.org/10.5194/acp-22-1-2022
- NUMAC: Description of the Nested Unified Model With Aerosols and Chemistry, and Evaluation With KORUS‐AQ Data H. Gordon et al. https://doi.org/10.1029/2022MS003457
- Airborne observations during KORUS-AQ show that aerosol optical depths are more spatially self-consistent than aerosol intensive properties S. LeBlanc et al. https://doi.org/10.5194/acp-22-11275-2022
- A new parameterization of uptake coefficient of SO2 and its impact on sulfate concentration K. Kim et al. https://doi.org/10.1016/j.atmosenv.2025.121503
- Ozone, nitrogen dioxide, and PM2.5 estimation from observation-model machine learning fusion over S. Korea: Influence of observation density, chemical transport model resolution, and geostationary remotely sensed AOD B. Tang et al. https://doi.org/10.1016/j.atmosenv.2024.120603
- NOx emissions constraints from GEMS NO2 retrievals: inversion methodology and air quality model evaluation in Bangkok using ASIA-AQ multi-platform observations J. Christopoulos et al. https://doi.org/10.5194/acp-26-8021-2026
- Implementation of aerosol data assimilation in WRFDA (v4.0.3) for WRF-Chem (v3.9.1) using the RACM/MADE-VBS scheme S. Ha https://doi.org/10.5194/gmd-15-1769-2022
- A Deep Learning Approach to Increase the Value of Satellite Data for PM2.5 Monitoring in China B. Li et al. https://doi.org/10.3390/rs15153724
- Multi-model intercomparisons of air quality simulations for the KORUS-AQ campaign R. Park et al. https://doi.org/10.1525/elementa.2021.00139
- Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 2. Bias Correction With Satellite Data for Rural Areas H. Zhang et al. https://doi.org/10.1029/2021JD035563
- Sensitivity of aerosol optical properties to the aerosol size distribution over central Europe and the Mediterranean Basin using the WRF-Chem v.3.9.1.1 coupled model L. Palacios-Peña et al. https://doi.org/10.5194/gmd-13-5897-2020
- Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter D. Zhang et al. https://doi.org/10.1021/acsestair.4c00084
- Understanding the Evolution of Smoke Mass Extinction Efficiency Using Field Campaign Measurements P. Saide et al. https://doi.org/10.1029/2022GL099175
- WRF-Chem quantification of transport events and emissions sensitivity in Korea during KORUS-AQ B. Tang et al. https://doi.org/10.1525/elementa.2022.00096
- Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns C. Howes et al. https://doi.org/10.5194/acp-23-13911-2023
- Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM2.5): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations S. Zhai et al. https://doi.org/10.5194/acp-21-16775-2021
- Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns H. Lim et al. https://doi.org/10.5194/amt-14-4575-2021
- Aerosol characterization in a Central-West site of Brazil: influence of farming activities and toxicity Y. Parra et al. https://doi.org/10.1007/s11869-023-01467-1
- Assessment of NO2 observations during DISCOVER-AQ and KORUS-AQ field campaigns S. Choi et al. https://doi.org/10.5194/amt-13-2523-2020
- Improving the sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosols of the Weather Research and Forecasting-Chemistry (WRF-Chem) model with the revised Gridpoint Statistical Interpolation system and multi-wavelength aerosol optical measurements: the dust aerosol observation campaign at Kashi, near the Taklimakan Desert, northwestern China W. Chang et al. https://doi.org/10.5194/acp-21-4403-2021
- Role of Upwind Precipitation in Transboundary Pollution and Secondary Aerosol Formation: A Case Study during the KORUS-AQ Field Campaign Y. Ryu et al. https://doi.org/10.1175/JAMC-D-21-0162.1
25 citations as recorded by crossref.
- Optical Properties of Boundary Layer Aerosols From High Spectral Resolution Lidar Measurements in a Polluted Urban Environment (Seoul, Korea) S. Park et al. https://doi.org/10.1029/2023JD038523
- A Lagrangian view on severe haze in Beijing: local and long-range sources of trace gases and primary and secondary aerosols B. Foreback et al. https://doi.org/10.1016/j.atmosenv.2025.121602
- Evaluation of accuracy on bottom-up NH3 emissions and sensitivity of PM2.5 to emission control in South Korea K. Han et al. https://doi.org/10.1016/j.atmosenv.2025.121434
- Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire X. Ye et al. https://doi.org/10.5194/acp-21-14427-2021
- Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the southeastern Atlantic S. Doherty et al. https://doi.org/10.5194/acp-22-1-2022
- NUMAC: Description of the Nested Unified Model With Aerosols and Chemistry, and Evaluation With KORUS‐AQ Data H. Gordon et al. https://doi.org/10.1029/2022MS003457
- Airborne observations during KORUS-AQ show that aerosol optical depths are more spatially self-consistent than aerosol intensive properties S. LeBlanc et al. https://doi.org/10.5194/acp-22-11275-2022
- A new parameterization of uptake coefficient of SO2 and its impact on sulfate concentration K. Kim et al. https://doi.org/10.1016/j.atmosenv.2025.121503
- Ozone, nitrogen dioxide, and PM2.5 estimation from observation-model machine learning fusion over S. Korea: Influence of observation density, chemical transport model resolution, and geostationary remotely sensed AOD B. Tang et al. https://doi.org/10.1016/j.atmosenv.2024.120603
- NOx emissions constraints from GEMS NO2 retrievals: inversion methodology and air quality model evaluation in Bangkok using ASIA-AQ multi-platform observations J. Christopoulos et al. https://doi.org/10.5194/acp-26-8021-2026
- Implementation of aerosol data assimilation in WRFDA (v4.0.3) for WRF-Chem (v3.9.1) using the RACM/MADE-VBS scheme S. Ha https://doi.org/10.5194/gmd-15-1769-2022
- A Deep Learning Approach to Increase the Value of Satellite Data for PM2.5 Monitoring in China B. Li et al. https://doi.org/10.3390/rs15153724
- Multi-model intercomparisons of air quality simulations for the KORUS-AQ campaign R. Park et al. https://doi.org/10.1525/elementa.2021.00139
- Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 2. Bias Correction With Satellite Data for Rural Areas H. Zhang et al. https://doi.org/10.1029/2021JD035563
- Sensitivity of aerosol optical properties to the aerosol size distribution over central Europe and the Mediterranean Basin using the WRF-Chem v.3.9.1.1 coupled model L. Palacios-Peña et al. https://doi.org/10.5194/gmd-13-5897-2020
- Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter D. Zhang et al. https://doi.org/10.1021/acsestair.4c00084
- Understanding the Evolution of Smoke Mass Extinction Efficiency Using Field Campaign Measurements P. Saide et al. https://doi.org/10.1029/2022GL099175
- WRF-Chem quantification of transport events and emissions sensitivity in Korea during KORUS-AQ B. Tang et al. https://doi.org/10.1525/elementa.2022.00096
- Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns C. Howes et al. https://doi.org/10.5194/acp-23-13911-2023
- Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM2.5): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations S. Zhai et al. https://doi.org/10.5194/acp-21-16775-2021
- Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns H. Lim et al. https://doi.org/10.5194/amt-14-4575-2021
- Aerosol characterization in a Central-West site of Brazil: influence of farming activities and toxicity Y. Parra et al. https://doi.org/10.1007/s11869-023-01467-1
- Assessment of NO2 observations during DISCOVER-AQ and KORUS-AQ field campaigns S. Choi et al. https://doi.org/10.5194/amt-13-2523-2020
- Improving the sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosols of the Weather Research and Forecasting-Chemistry (WRF-Chem) model with the revised Gridpoint Statistical Interpolation system and multi-wavelength aerosol optical measurements: the dust aerosol observation campaign at Kashi, near the Taklimakan Desert, northwestern China W. Chang et al. https://doi.org/10.5194/acp-21-4403-2021
- Role of Upwind Precipitation in Transboundary Pollution and Secondary Aerosol Formation: A Case Study during the KORUS-AQ Field Campaign Y. Ryu et al. https://doi.org/10.1175/JAMC-D-21-0162.1
Saved (final revised paper)
Latest update: 17 Jul 2026
Short summary
Air quality forecasts over the Korean Peninsula captured aerosol optical depth but largely overpredicted surface PM during a Chinese haze transport event. Model deficiency was related to the calculation of optical properties. In order to improve it, aerosol size representation needs to be refined in the calculations, and the representation of aerosol properties, such as size distribution, chemical composition, refractive index, hygroscopicity parameter, and density, needs to be improved.
Air quality forecasts over the Korean Peninsula captured aerosol optical depth but largely...
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