Articles | Volume 17, issue 21
https://doi.org/10.5194/acp-17-13103-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-17-13103-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
07 Nov 2017
Research article |
| 07 Nov 2017
Ensemble prediction of air quality using the WRF/CMAQ model system for health effect studies in China
Jianlin Hu
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Engineering Technology Research Center of
Environmental Cleaning Materials, Jiangsu Collaborative Innovation Center of
Atmospheric Environment and Equipment Technology, School of Environmental
Science and Engineering, Nanjing University of Information Science &
Technology, 219 Ningliu Road, Nanjing 210044, China
Xun Li
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Engineering Technology Research Center of
Environmental Cleaning Materials, Jiangsu Collaborative Innovation Center of
Atmospheric Environment and Equipment Technology, School of Environmental
Science and Engineering, Nanjing University of Information Science &
Technology, 219 Ningliu Road, Nanjing 210044, China
Lin Huang
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Engineering Technology Research Center of
Environmental Cleaning Materials, Jiangsu Collaborative Innovation Center of
Atmospheric Environment and Equipment Technology, School of Environmental
Science and Engineering, Nanjing University of Information Science &
Technology, 219 Ningliu Road, Nanjing 210044, China
Qi Ying
Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843-3136, USA
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Engineering Technology Research Center of
Environmental Cleaning Materials, Jiangsu Collaborative Innovation Center of
Atmospheric Environment and Equipment Technology, School of Environmental
Science and Engineering, Nanjing University of Information Science &
Technology, 219 Ningliu Road, Nanjing 210044, China
Qiang Zhang
Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
Shuxiao Wang
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 77803, USA
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Engineering Technology Research Center of
Environmental Cleaning Materials, Jiangsu Collaborative Innovation Center of
Atmospheric Environment and Equipment Technology, School of Environmental
Science and Engineering, Nanjing University of Information Science &
Technology, 219 Ningliu Road, Nanjing 210044, China
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- Rapid reduction of air pollution and short-term exposure risks in China H. Fan et al. 10.1016/j.jes.2023.11.002
- Characterization and source apportionment of marine aerosols over the East China Sea M. Kang et al. 10.1016/j.scitotenv.2018.10.174
- Application of machine learning algorithms to improve numerical simulation prediction of PM2.5 and chemical components L. Lv et al. 10.1016/j.apr.2021.101211
- The associations of prenatal exposure to PM2.5 and its constituents with fetal growth: A prospective birth cohort in Beijing, China S. Zhou et al. 10.1016/j.envres.2022.114196
- Influence of meteorological reanalysis field on air quality modeling in the Yangtze River Delta, China X. Wang et al. 10.1016/j.atmosenv.2023.120231
- Improving the accuracy of O3 prediction from a chemical transport model with a random forest model in the Yangtze River Delta region, China K. Xiong et al. 10.1016/j.envpol.2022.120926
Latest update: 20 Nov 2024
Short summary
The model performance of CMAQ with WRF using four different emission inventories in China was validated and compared to obtain the best air pollutants prediction for health effect studies of severe air pollution. The differences in performance of chemical transport model were analyzed for different months and regions in the vast part of China and ensemble predictions were firstly obtained from different inventories for health analysis with minimized errors for pollutants including PM2.5 and O3.
The model performance of CMAQ with WRF using four different emission inventories in China was...
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