Articles | Volume 23, issue 13
https://doi.org/10.5194/acp-23-7823-2023
© Author(s) 2023. 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-23-7823-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Multi-model ensemble projection of the global dust cycle by the end of 21st century using the Coupled Model Intercomparison Project version 6 data
Yuan Zhao
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, China
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, China
Yang Cao
Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Jun Zhu
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, China
Chenguang Tian
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, China
Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Yuwen Chen
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, China
Yihan Hu
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, China
Weijie Fu
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, China
Xu Zhao
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, China
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Cited
8 citations as recorded by crossref.
- Unusually low dust activity in North Africa in June 2023: Causes, impacts and future projections D. Francis et al. 10.1016/j.atmosres.2024.107594
- Historical footprints and future projections of global dust burden from bias-corrected CMIP6 models J. Liu et al. 10.1038/s41612-023-00550-9
- The key role of atmospheric absorption in the Asian summer monsoon response to dust emissions in CMIP6 models A. Zhao et al. 10.5194/acp-24-13385-2024
- Anthropogenic sulfate-climate interactions suppress dust activity over East Asia X. Xie et al. 10.1038/s43247-025-02147-x
- Projection of Long‐Term Climate Change in China Under COVID‐19 Recovery Emission Scenarios C. Tian et al. 10.1029/2023JD039197
- Status and Perspectives of the Validation and Evaluation of Wind-Blown Dust Models Using Three-Dimensional Air Quality Models H. Lee & S. Park 10.5572/KOSAE.2025.41.2.199
- Particle-bound mercury in Saharan dust-loaded particulate matter in Cabo Verde E. Souza et al. 10.1016/j.jhazmat.2024.137053
- Future Projections of Dust Storm Dynamics and Sources in the Middle East: Insights from CMIP6 Models A. Saadat Abadi et al. 10.1016/j.apr.2025.102775
8 citations as recorded by crossref.
- Unusually low dust activity in North Africa in June 2023: Causes, impacts and future projections D. Francis et al. 10.1016/j.atmosres.2024.107594
- Historical footprints and future projections of global dust burden from bias-corrected CMIP6 models J. Liu et al. 10.1038/s41612-023-00550-9
- The key role of atmospheric absorption in the Asian summer monsoon response to dust emissions in CMIP6 models A. Zhao et al. 10.5194/acp-24-13385-2024
- Anthropogenic sulfate-climate interactions suppress dust activity over East Asia X. Xie et al. 10.1038/s43247-025-02147-x
- Projection of Long‐Term Climate Change in China Under COVID‐19 Recovery Emission Scenarios C. Tian et al. 10.1029/2023JD039197
- Status and Perspectives of the Validation and Evaluation of Wind-Blown Dust Models Using Three-Dimensional Air Quality Models H. Lee & S. Park 10.5572/KOSAE.2025.41.2.199
- Particle-bound mercury in Saharan dust-loaded particulate matter in Cabo Verde E. Souza et al. 10.1016/j.jhazmat.2024.137053
- Future Projections of Dust Storm Dynamics and Sources in the Middle East: Insights from CMIP6 Models A. Saadat Abadi et al. 10.1016/j.apr.2025.102775
Latest update: 24 Oct 2025
Short summary
We project the future changes of dust emissions and loading using an ensemble of model outputs from the Coupled Model Intercomparison Project version 6 under four scenarios. We find increased dust emissions and loading in North Africa, due to increased drought and strengthened surface wind, and decreased dust loading over Asia, following enhanced precipitation. Such a spatial pattern remains similar, though the regional intensity varies among different scenarios.
We project the future changes of dust emissions and loading using an ensemble of model outputs...
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