Articles | Volume 12, issue 11
https://doi.org/10.5194/gmd-12-4603-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-4603-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Multimodel simulations of a springtime dust storm over northeastern China: implications of an evaluation of four commonly used air quality models (CMAQ v5.2.1, CAMx v6.50, CHIMERE v2017r4, and WRF-Chem v3.9.1)
Siqi Ma
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
University of Chinese Academy of Sciences, Beijing 100049, China
Air Resources Laboratory, National Oceanic & Atmospheric Administration, College Park, MD 20740, USA
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Center for Spatial Information Science and Systems, George Mason
University, Fairfax, VA 22030, USA
Chao Gao
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
University of Chinese Academy of Sciences, Beijing 100049, China
Center for Spatial Information Science and Systems, George Mason
University, Fairfax, VA 22030, USA
Aijun Xiu
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Guangjian Wu
Key Laboratory of Tibetan Environment Changes and Land Surface
Processes, Institute of Tibetan Plateau Research, Chinese Academy of
Sciences, Beijing 100101, China
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing
100101, China
Xinyuan Cao
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
University of Chinese Academy of Sciences, Beijing 100049, China
Ling Huang
School of Environmental and Chemical Engineering, Shanghai
University, Shanghai 200444, China
Hongmei Zhao
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Shichun Zhang
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Department of Marine, Earth, and Atmospheric Sciences, North Carolina
State University, Raleigh, NC 27695, USA
Sergio Ibarra-Espinosa
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Department of Atmospheric Sciences, Universidade de São Paulo,
São Paulo, SP, Brazil
Key Laboratory for Semi-Arid Climate Change of the Ministry of
Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou
730000, China
Xiaolan Li
Institute of Atmospheric Environment, China Meteorological
Administration, Shenyang 110166, China
School of Meteorology, University of Oklahoma, Norman, OK 73072, USA
Mo Dan
Beijing Municipal Institute of Labor Protection, Beijing 100054,
China
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- A revised mineral dust emission scheme in GEOS-Chem: improvements in dust simulations over China R. Tian et al. 10.5194/acp-21-4319-2021
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- Dust emission, transport, and deposition in central Iran and their radiative forcing effects: A numerical simulation S. Hosseini Dehshiri & B. Firoozabadi 10.1016/j.apr.2024.102267
- Investigating uncertainties in air quality models used in GMAP/SIJAQ 2021 field campaign: General performance of different models and ensemble results Y. Cha et al. 10.1016/j.atmosenv.2024.120896
- Spatial and Temporal Variations in Spring Dust Concentrations from 2000 to 2020 in China: Simulations with WRF-Chem F. Wang et al. 10.3390/rs14236090
- Regional source contributions to fine particulate matter of less studied cities in Beijing-Tianjin-Hebei region in 2017 Q. Liu et al. 10.1016/j.partic.2023.01.011
- Quantifying the impact of cropland wind erosion on air quality: A high-resolution modeling case study of an Arizona dust storm J. Joshi 10.1016/j.atmosenv.2021.118658
- Improving dust simulations in WRF-Chem v4.1.3 coupled with the GOCART aerosol module A. Ukhov et al. 10.5194/gmd-14-473-2021
- Quantifying the contributions of natural and anthropogenic dust sources in Shanxi Province, northern China C. Xu et al. 10.1016/j.chemosphere.2023.140280
- Winter vacation, indoor air pollution and respiratory health among rural college students: A case study in Gansu Province, China X. He et al. 10.1016/j.buildenv.2020.107481
- Identifying a suitable model for predicting hourly pollutant concentrations by using low-cost microstation data and machine learning R. Yang et al. 10.1038/s41598-022-24470-5
- Impact of atmospheric circulation patterns on properties and regional transport pathways of aerosols over Central-West Asia: Emphasizing the Tibetan Plateau Y. Hu et al. 10.1016/j.atmosres.2021.105975
- Multisensor and Multimodel Monitoring and Investigation of a Wintertime Air Pollution Event Ahead of a Cold Front Over Eastern China X. Hu et al. 10.1029/2020JD033538
- Air quality historical correlation model based on time series Y. Liu et al. 10.1038/s41598-024-74246-2
- Sand and dust storm trajectories from Iraq Mesopotamian flood plain to Kuwait A. Al-Hemoud et al. 10.1016/j.scitotenv.2019.136291
Latest update: 19 Nov 2024
Short summary
Dust storms are thought to be a worldwide societal issue, and numerical modeling is an effective way to help us to predict dust events. Here we present the first comprehensive evaluation of dust emission modules in four commonly used air quality models for northeastern China. The results showed that most of these models were able to capture this dust event and indicated the dust source maps should be carefully selected or replaced with a new one that is constructed with local data.
Dust storms are thought to be a worldwide societal issue, and numerical modeling is an effective...