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Evaluation and potential improvements of WRF/CMAQ in simulating multi-levels air pollution in megacity Shanghai, China

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Abstract

The accuracy of atmospheric numerical model is important for the prediction of urban air pollution. This study investigated and quantified the uncertainties of meteorological and air quality model during multi-levels air pollution periods. We simulated the air quality of megacity Shanghai, China with WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) at both non-pollution and heavy-pollution episodes in 2012. The weather prediction model failed to reproduce the surface temperature and wind speed in condition of high aerosol loading. The accuracy of the air quality model showed a clear dropping tendency from good air quality conditions to heavily polluted episodes. The absolute model bias increased significantly from light air pollution to heavy air pollution for SO2 (from 2 to 14%) and for PM10 (from 1 to 33%) in both urban and suburban sites, for CO in urban sites (from 8 to 48%) and for NO2 in suburban sites (from 1 to 58%). A test of applying the Urban Canopy Model scheme to the WRF model showed fairly good improvement on predicting the meteorology field, but less significant effect on the air pollutants (6% for SO2 and 19% for NO2 decease in model bias found only in urban sites). This study gave clear evidence to the sensitivities of the model performance on the air pollution levels. It is suggested to consider this impact as a source for model bias in the model assessment and make improvement in the model development in the future.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (21677038), the Science & Technology Commission of Shanghai Municipality (No. 14ZR1402800, 15DZ1205404), the National Key Technology R&D Program of Ministry of Science and Technology of China (2014BAC16B01).

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Authors and Affiliations

  1. Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, People’s Republic of China

    Jiani Tan, Yan Zhang, Weichun Ma, Qi Yu, Bin Zhou, Jianmin Chen & Limin Chen

  2. Shanghai Environmental Monitoring Center, Shanghai, 200030, People’s Republic of China

    Qian Wang & Qingyan Fu

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  1. Jiani Tan
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  2. Yan Zhang
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  3. Weichun Ma
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  4. Qi Yu
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  5. Qian Wang
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  6. Qingyan Fu
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  7. Bin Zhou
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  8. Jianmin Chen
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  9. Limin Chen
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Correspondence to Yan Zhang.

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Tan, J., Zhang, Y., Ma, W. et al. Evaluation and potential improvements of WRF/CMAQ in simulating multi-levels air pollution in megacity Shanghai, China. Stoch Environ Res Risk Assess 31, 2513–2526 (2017). https://doi.org/10.1007/s00477-016-1342-3

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