| dc.description.abstract | The lockdown of cities in China caused by the outbreak of the COVID-19 pandemic has led to unprecedented nationwide large-scale and long-term reduction in atmospheric pollution emissions that has not ever occurred. It resulted in the improvement of the country’s air quality, and even the air quality over the downwind Taiwan. Hence, this study aims to apply the WRF/CMAQ model simulation to investigate the aforementioned abrupt reduction of emissions due to the outbreak of COVID-19, and to evaluate its impact on downwind Taiwan. The OMI-NO2 satellite data is used to adjust the existing emission data to make it closer to the actual situation. Simulation and discussion are conducted for 2 cases to explore the possibility to adjust the emission through satellite data when Taiwan is under the influence of long-range transport of foreign pollution. They are (i) case 1 (2020/1/28-2/1) during northeast monsoon with influence from the COVID-19 pandemic lockdown, (ii) case 2 (2018/1/30-2/2) with similar weather conditions during the similar season but in 2018 without the influence of COVID-19.
In case 1, satellite data was used to adjust the original emission data to the abnormal emission variation caused by the pandemic. Affected by the large-scale closure of cities in China and the suspension of work, the pollution emissions in the East Asia region fluctuated greatly, and the overall decrease was significant. The simulation results using the OMI-NO2-adjusted emission for all species show that the near-surface PM2.5 concentrations at Cape Fuguei and Banqiao are significantly reduced, and are closer to the observed values. The correlation of IOA (Index Of Agreement, often used to compare the consistency of two datasets, is considered highly correlated when greater than 0.6) has significantly increased for Cape Fuguei from the original 0.72 to 0.89, and the Banqiao station also increased from 0.51 to 0.82.
Compared with case 1, case 2 was not affected by COVID-19 and the resulting closure of the city, so the adjustment of pollution emissions through OMI-NO2 is much smaller. The overall accuracy of the model performance for case 2 is poor. Nevertheless, the model with OMI-NO2-adjusted emission for all species performed much better compared to the OMI-NO2-adjusted emission that only adjusted for NOx in East Asia.
In addition, the modelled PM2.5 chemical composition of Cape Fuguei and Banqiao Stations was compared to the observation data to further evaluate the model performance of using the original and OMI-NO2-adjusted emissions, respectively. The results show that using the OMI-NO2-adjusted emissions reduces the deviation from the observed values compared to the original emissions simulation results for PM2.5.
Based on the above simulation results, the study shows that the use of OMI-NO2 data to adjust the bottom-up emission can better represent the changes in pollutant emissions during major changes in pollution emissions, thereby improving the simulation accuracy of PM2.5 concentration and composition. Nevertheless, there is still room for improvement in scenarios where pollution emissions are only slightly changed.
Finally, in order to better understand the impact of pollution transport from East Asia to northern Taiwan, this study further used the OMI-NO2-adjusted emissions to simulate and explore acid deposition (NO3- and SO42-). A simulation study was conducted on the rainfall events in northern Taiwan during the above two cases. It can be found that NO3- whether it is dry or wet deposition, has a more significant proportional change with different emission scenarios (different East Asian emission reductions), while the variation of SO42- deposition is less significant. Based on the above discussion, the adjustment of the emission database with near real-time satellite data may improve the simulation of acid deposition and short-term air quality forecast. | en_US |