Articles | Volume 21, issue 6
https://doi.org/10.5194/acp-21-4319-2021
© Author(s) 2021. 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-21-4319-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Mar 2021
Research article |
| 22 Mar 2021
| 22 Mar 2021
A revised mineral dust emission scheme in GEOS-Chem: improvements in dust simulations over China
Rong Tian
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD)/Key Laboratory for
Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing
University of Information Science & Technology, Nanjing 210044, China
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD)/Key Laboratory for
Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing
University of Information Science & Technology, Nanjing 210044, China
Jianqi Zhao
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD)/Key Laboratory for
Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing
University of Information Science & Technology, Nanjing 210044, China
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Cited
16 citations as recorded by crossref.
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- Investigation of the influence of mineral dust on airborne particulate matter during the COVID-19 epidemic in spring 2020 over China L. Liang et al. 10.1016/j.apr.2022.101424
- Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions M. Qiu et al. 10.5194/acp-22-10551-2022
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- Using machine learning to quantify drivers of aerosol pollution trend in China from 2015 to 2022 Y. Ji et al. 10.1016/j.apgeochem.2023.105614
- Spatiotemporal trends and impact factors of PM<sub>2.5</sub> and O<sub>3</sub> pollution in major cities in China during 2015–2020 Y. Zhang et al. 10.1360/TB-2021-0767
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16 citations as recorded by crossref.
- An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation Y. Wang et al. 10.5194/gmd-17-7995-2024
- Quantifying the contributions of natural and anthropogenic dust sources in Shanxi Province, northern China C. Xu et al. 10.1016/j.chemosphere.2023.140280
- Impact of Molecular Chlorine Production from Aerosol Iron Photochemistry on Atmospheric Oxidative Capacity in North China Q. Chen et al. 10.1021/acs.est.4c02534
- Exploring aerosol–cloud interactions in liquid-phase clouds over eastern China and its adjacent ocean using the WRF-Chem–SBM model J. Zhao et al. 10.5194/acp-24-9101-2024
- A Computational Perspective on the Chemical Reaction of HFO-1234zc with the OH Radical in the Gas Phase and in the Presence of Mineral Dust G. Manonmani et al. 10.1021/acs.jpca.2c03229
- Simulation of a Severe Sand and Dust Storm Event in March 2021 in Northern China: Dust Emission Schemes Comparison and the Role of Gusty Wind J. Wang et al. 10.3390/atmos13010108
- Planetary Helicopter Brownout Simulation of Ingenuity Using a Eulerian Dust Transport Model D. Caprace et al. 10.2514/1.J065017
- Freeze-thaw process boosts penguin-derived NH3 emissions and enhances climate-relevant particles formation in Antarctica R. Tian et al. 10.1038/s41612-024-00873-1
- Exploring dust heterogeneous chemistry over China: Insights from field observation and GEOS-Chem simulation R. Tian et al. 10.1016/j.scitotenv.2021.149307
- Investigation of the influence of mineral dust on airborne particulate matter during the COVID-19 epidemic in spring 2020 over China L. Liang et al. 10.1016/j.apr.2022.101424
- Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions M. Qiu et al. 10.5194/acp-22-10551-2022
- Spatiotemporal variation in soil degradation and economic damage caused by wind erosion in Northwest China H. Zhao et al. 10.1016/j.jenvman.2022.115121
- Emission, transport, deposition, chemical and radiative impacts of mineral dust during severe dust storm periods in March 2021 over East Asia L. Liang et al. 10.1016/j.scitotenv.2022.158459
- Using machine learning to quantify drivers of aerosol pollution trend in China from 2015 to 2022 Y. Ji et al. 10.1016/j.apgeochem.2023.105614
- Spatiotemporal trends and impact factors of PM<sub>2.5</sub> and O<sub>3</sub> pollution in major cities in China during 2015–2020 Y. Zhang et al. 10.1360/TB-2021-0767
- Improving annual fine mineral dust representation from the surface to the column in GEOS-Chem 14.4.1 D. Zhang et al. 10.5194/gmd-18-6767-2025
Latest update: 23 Oct 2025
Short summary
We improve the treatment of the dust emission process in GEOS-Chem by considering the effect of geographical variation of aerodynamic roughness length, smooth roughness length and soil texture, as well as the Owen effect and a more physically based formulation of sandblasting efficiency, which improve estimated threshold friction velocity and dust concentrations over China. Our study highlights the importance of incorporation of realistic land-surface properties into the dust emission scheme.
We improve the treatment of the dust emission process in GEOS-Chem by considering the effect of...
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