Study on the assimilation of the sulphate reaction rates based on WRF-Chem/DART
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...
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Veröffentlicht in: | Science China. Earth sciences 2023-10, Vol.66 (10), p.2239-2253 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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 −13.1 µg m
−3
to 3.5 µg m
−3
while SO
2
improved from 17.0 µg m
−3
to 6.3 µg 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. |
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ISSN: | 1674-7313 1869-1897 |
DOI: | 10.1007/s11430-023-1153-9 |