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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/gmd-2020-42
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-42
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model experiment description paper 05 Jun 2020

Submitted as: model experiment description paper | 05 Jun 2020

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This preprint is currently under review for the journal GMD.

Numerical study of the initial condition and emission on simulating PM2.5 concentrations in Comprehensive Air Quality Model with extensions version 6.1 (CAMx v6.1): Taking Xi'an as example

Han Xiao1, Qizhong Wu1, Xiaochun Yang1,2, Lanning Wang1, and Huaqiong Cheng1 Han Xiao et al.
  • 1College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
  • 2Xi’an Meteorological Bureau, Xi’an, Shaanxi Province 710016, China

Abstract. A series of model sensitivity experiments is designed to explore the effects of different initial conditions and emissions in Xi'an in December 2016, which is a major city in the key area "Fen-Wei Plains" for air pollution control in China. Three methods were applied for the initial condition tests: clean initial mechanism, restart mechanism and continuous simulation. In clean initial mechanism test, the sensitivity experiments C00, C06, C12, C18, and C24 were conducted according to the intercepted time periods, and the results showed that the model performance of PM2.5 was better with the delay of the start time of the intercepted time periods. From experiments C00 to C24, the absolute mean bias (MB) decreased from 51.07 µg/m3 to 3.72 µg/m3 and the index of agreement (IOA) increased from 0.49 to 0.86, which illustrates that the model performance of C24 is much better than C00. In order to explore the restart mechanism, sensitivity experiments R1120 and R1124 were set according to the time of the first day for the model simulation. Although the start times of simulations were different, after a period of spin-up time, the simulation results with different start time were nearly consistent, the results showed that the spin-up time is about 27 hours. As for the continuous simulation test, CT12 and CT24 were conducted. The start time of the intercepted time periods for CT12 and R1120 were the same, and the simulation results were nearly identical. The simulation results of CT24 performed best in all the sensitivity experiments, with the correlation coefficient (R), MB, and IOA reaching 0.81, 6.29 µg/m3, and 0.90, respectively. For the emission tests, the updated local emission inventory with construction fugitive dust emissions have been added and compared to the simulation results of the original emission inventory. The simulation with the updated local emissions showed a much better performance on PM2.5 modelling. Therefore, combining the method of CT24 with the updated local emission inventory can nicely improve the model performance of PM2.5 in Xi'an, the absolute MB decreased from 35.16 µg/m3 to 6.29 µg/m3 and the IOA reached 0.90.

Han Xiao et al.

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The dataset of the manuscript "Numerical study of the initial condition and emission on simulating PM2.5 concentrations in Comprehensive Air Quality Model with extensions version 6.1 (CAMx v6.1): Taking Xi'an as example H. Xiao, Q. Wu, Y. Yang, L. Wang, and H. Cheng https://doi.org/10.5281/zenodo.3824676

Han Xiao et al.

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Short summary
Few studies have investigated the effects of initial condition on the simulation or prediction of PM2.5 concentrations. The sensitivity experiments are designed to explore the effects of three initial mechanism (clean, restart and continuous) and emissions in Xi’an in December 2016. According to this work, if the restart mechanism cannot be used due to the limitation of computing resources and storage space when forecasting PM2.5 concentrations, it takes at least 27 hours as the spin-up time.
Few studies have investigated the effects of initial condition on the simulation or prediction...
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