COVID-19疫情爆發所導致的中國封城停工事件，是未曾發生大範圍且長時間之實際污染排放大幅減量情況，導致空氣品質改善，甚至下風處臺灣亦受影響。藉此，本研究旨在應用WRF/CMAQ模式模擬探討因COVID-19疫情爆發導致前述實際排放驟然減量的情況下，評估其對下風處臺灣所造成的影響。並利用OMI-NO2衛星調整現有之排放資料，使其更為接近實際情況。模擬受到COVID-19疫情影響之東北季風個案一 (2020/1/28-2/1) ，以及於2018年相近季節時期且相似氣象條件之個案二 (2018/1/30-2/2)，以期探討在相同的方法與設定下，是否同樣能夠改善境外污染對臺灣之影響的模擬結果。
個案一利用衛星資料把原始排放資料調整成因疫情事件引發異常排放情況，以及受到中國大範圍封城停工影響，東亞區域的污染排放亦變動，整體為大幅降低。模擬結果分析顯示若使用OMI-NO2衛星資料調整全部排放物種之後，富貴角站及板橋站近地面PM2.5濃度顯著的降低，且更為接近實際的觀測值。IOA (Index Of Agreement，常用於比對兩數串之一致性，一般而言大於0.6即視為高相關性) 於富貴角站從原先的0.72提升至0.89，而板橋站也從0.51提升至0.82，相當顯著。
相較於個案一，個案二期間並未受到COVID-19及其導致之封城停工影響，污染排放因此受衛星資料所調整的幅度較小。根據模擬跟觀測比對結果顯示整體準確度較差，但在利用衛星資料調整全部排放的模擬結果比原始排放與僅調整東亞NOx排放更為接近實際觀測值。
此外，比較富貴角及板橋站之模擬結果與PM2.5成分觀測數據，進一步評估模式使用原始排放量與利用OMI-NO2調整污染排放量的模擬表現，結果顯示使用調整過後的排放量比原始排放模擬結果降低與觀測值的偏差。
綜合模擬分析結果顯示利用OMI-NO2衛星資料調整bottom-up的排放資料庫，能夠掌握污染排放出現重大變化期間污染物排放之變化，進而提升對PM2.5濃度和成分之模擬準確度，但對於污染排放僅有些微改變的情境則仍有改善的空間。
最後為更瞭解東亞境外污染移入對北臺灣的影響，本研究進一步利用調整後之排放量對酸沉降 (NO3-及SO42-) 進行模擬探討，並針對上述兩個個案期間北臺灣之降雨事件進行分析。雖然模擬結果不盡理想，但發現NO3-不論是乾或溼沉降量，在隨著排放情境 (不同的東亞減排情況) 的不同而有較為顯著之比例改變，而SO42-沉降量變化較不明顯。綜合上述探討，藉由近即時衛星資料調整排放資料庫，或可精進提升酸沉降及短期空品預報之模擬。

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.

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