A simple model based on the statistics of individual atoms [Europhys. Lett. 94 40002 （2011）] or molecules [Chin. Phys. Lett. 29 080504 （2012）] was used to predict chemical reaction rates without empirical paramete...A simple model based on the statistics of individual atoms [Europhys. Lett. 94 40002 （2011）] or molecules [Chin. Phys. Lett. 29 080504 （2012）] was used to predict chemical reaction rates without empirical parameters, and its physical basis was further investigated both theoretically and via MD simulations. The model was successfully applied to some reactions of extensive experimental data, showing that the model is significantly better than the conventional transition state theory. It is worth noting that the prediction of the model on ab initio level is much easier than the transition state theory or unimolecular RRKM theory.展开更多
Sulphate(SO_(4)^(2-))is a main component of PM_(2.5)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 ...Sulphate(SO_(4)^(2-))is a main component of PM_(2.5)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 Weather Research Forecast-Chemistry(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(Data Assistance Research Testbed)system,the near-ground concentrations of SO_(4)^(2-),SO_(2),NO_(2),O_(3)and particulate matter are assimilated to adjust the six parameters.After adjusting the parameters,the new scheme can effectively solve the underestimation of SO_(4)^(2-)and overestimation of SO_(2).The simulation of SO_(4)^(2-)improved as the mean bias changed from-13.1μg m^(-3)to 3.5μg m^(-3)while SO_(2)improved from 17.0μg m^(-3)to 6.3μg m^(-3).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.Furthermore,the reaction rates of the SO_(4)^(2-)parameterisation scheme of the WRF-Chem model are improved in this study,and a new method for improving the accuracy of the air quality model is provided.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.11274073)the Leading Academic Discipline Project of Shanghai,China(Grant No.B107)
文摘A simple model based on the statistics of individual atoms [Europhys. Lett. 94 40002 （2011）] or molecules [Chin. Phys. Lett. 29 080504 （2012）] was used to predict chemical reaction rates without empirical parameters, and its physical basis was further investigated both theoretically and via MD simulations. The model was successfully applied to some reactions of extensive experimental data, showing that the model is significantly better than the conventional transition state theory. It is worth noting that the prediction of the model on ab initio level is much easier than the transition state theory or unimolecular RRKM theory.
基金supported by the National Key Research and Development Program of China(Grant Nos.2020YFA0607802&2019YFC0214603)。
文摘Sulphate(SO_(4)^(2-))is a main component of PM_(2.5)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 Weather Research Forecast-Chemistry(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(Data Assistance Research Testbed)system,the near-ground concentrations of SO_(4)^(2-),SO_(2),NO_(2),O_(3)and particulate matter are assimilated to adjust the six parameters.After adjusting the parameters,the new scheme can effectively solve the underestimation of SO_(4)^(2-)and overestimation of SO_(2).The simulation of SO_(4)^(2-)improved as the mean bias changed from-13.1μg m^(-3)to 3.5μg m^(-3)while SO_(2)improved from 17.0μg m^(-3)to 6.3μg m^(-3).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.Furthermore,the reaction rates of the SO_(4)^(2-)parameterisation scheme of the WRF-Chem model are improved in this study,and a new method for improving the accuracy of the air quality model is provided.
