image: The time series of SO42− and SO2 concentrations and the corresponding observations for stations under each simulation scheme are shown. PE_OW used the priori emission and the original unmodified WRF-Chem. DE_OW was performed using the assimilated emissions and the original WRF-Chem. DE_PW used the assimilated emissions inventory and the addition reaction rate parameters from the initial ensemble expectations (prior parameters). DE_4W and DE_1W used assimilated emissions and new reactions added, using reaction rate parameters averaged from the last four posterior averages and from the last posterior average.
Credit: ©Science China Press
This study is led by Pro. Tijian Wang from Nanjing University, Dr. Congwu Huang and Dr. Chaoqun Ma studied the sulphate reaction rates assimilation method based on WRF-Chem/DART (Weather Research Forecast-Chemistry/Data Assimilation Research Testbed). The reaction rates of the SO42− parameterisation scheme of the WRF-Chem model are improved, and a new method for improving the accuracy of the air quality model is provided.
Sulphate (SO42−) is a main component of PM2.5 in China. The chemical formation mechanisms of sulphate are complex, and many air quality models have been used to analyse these mechanisms. To improve the accuracy of WRF-Chem on sulphate, an alternative method is proposed in this paper. Moreover, data assimilation is performed to adjust the chemical reaction rates of sulphate. Based on the original reactions, a new sulphate parameterisation scheme, which includes two hypothetical reactions and six undetermined parameters, was added. Based on the WRF-Chem/DART system, the near-ground concentrations of SO42−, SO2, NO2, O3 and particulate matter are assimilated to adjust the six parameters. After adjusting the parameters, the new scheme can effectively solve the underestimation of SO42− and overestimation of SO2. The simulation of SO42− improved as the mean bias changed from -13.1 μg/m3 to 3.5 μg/m3 while SO2 improved from 17.0 μg/m3 to 6.3 μg/m3. The temporal and spatial variation characteristics predicted by the new scheme are consistent with the theoretical research results, indicating that the complex mechanism of sulphate formation could be replaced by the temporal and spatial variation characteristics predicted by the new scheme and that the parameters can be adjusted by data assimilation.
Hang C, Ma C, Wang T, Qu Y, Li M, Li S, Zhuang B, Xie Y. 2023. Study on the assimilation of the sulphate reaction rates based on WRF-Chem/DART. Science China Earth Sciences, 66(10): 2239‒2253, https://doi.org/10.1007/s11430-023-1153-9
Journal
Science China Earth Sciences