Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport Events
Abstract Long-range pollution transport (LRT) events have a wide impact across East Asia, but are often difficult to track due to imprecise emission inventories and changing domain scales as the plume moves from source to receptor locations. This study adjusts a bottom-up emission inventory based on...
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| Format: | Article |
| Language: | English |
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Springer
2021-09-01
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| Series: | Aerosol and Air Quality Research |
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| Online Access: | https://doi.org/10.4209/aaqr.210121 |
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| author | Wei-Syun Huang Stephen M. Griffith Yi-Chun Lin Ying-Chieh Chen Chung-Te Lee Charles C.-K. Chou Ming-Tung Chuang Sheng-Hsiang Wang Neng-Huei Lin |
| author_facet | Wei-Syun Huang Stephen M. Griffith Yi-Chun Lin Ying-Chieh Chen Chung-Te Lee Charles C.-K. Chou Ming-Tung Chuang Sheng-Hsiang Wang Neng-Huei Lin |
| author_sort | Wei-Syun Huang |
| collection | DOAJ |
| description | Abstract Long-range pollution transport (LRT) events have a wide impact across East Asia, but are often difficult to track due to imprecise emission inventories and changing domain scales as the plume moves from source to receptor locations. This study adjusts a bottom-up emission inventory based on changes in remotely sensed NO2 column densities for a source region of East Asia, then with CMAQv5.2.1 simulates transport of LRT plumes to Taiwan. Adjustment of an emissions inventory based on satellite measurements during the COVID-19 lockdown in China led to a ~59% reduction in emissions over the relevant source area in China compared to base emissions. As a result, PM2.5 mass concentrations were reproduced to match observations (mean fractional bias, MFB of –13.9% and 18.5% at a remote and urban station) as the plume passed through northern Taiwan. Furthermore, the OMI-adjusted emissions simulation brought all of the major PM2.5 components to within ~50% of the measured values. Another LRT event from 2018 with more subtle OMI-adjustments to the emissions was also simulated and with improved overall PM2.5 mass concentration at the northern tip of Taiwan (MFB: –91.5%) compared to the base model (MFB: –102.1%), and an acceptable index of agreement (0.78). For the 2018 event, non sea-salt sulfate concentrations were consistently underpredicted (0.2–0.4), while nitrate concentrations were overpredicted by up to factor of 11. Copernicus Atmosphere Monitoring Service (CAMS) reanalysis of the PM2.5 concentrations shows high sulfate concentrations in eastern China in the areas associated with 72-h back-trajectories from northern Taiwan during both events, lending support for future model investigations of sulfate source area production and transport to Taiwan. In order to better track these LRT events out of East Asia and optimize OMI-adjustment methodology, it is recommended to explore other satellite-based products to map unaccounted for SO2 sources upstream of Taiwan. |
| format | Article |
| id | doaj-art-806bafd3cc4b4531a5a9454b437f1795 |
| institution | Kabale University |
| issn | 1680-8584 2071-1409 |
| language | English |
| publishDate | 2021-09-01 |
| publisher | Springer |
| record_format | Article |
| series | Aerosol and Air Quality Research |
| spelling | doaj-art-806bafd3cc4b4531a5a9454b437f17952025-02-09T12:21:09ZengSpringerAerosol and Air Quality Research1680-85842071-14092021-09-01211011610.4209/aaqr.210121Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport EventsWei-Syun Huang0Stephen M. Griffith1Yi-Chun Lin2Ying-Chieh Chen3Chung-Te Lee4Charles C.-K. Chou5Ming-Tung Chuang6Sheng-Hsiang Wang7Neng-Huei Lin8Department of Atmospheric Sciences, National Central UniversityDepartment of Atmospheric Sciences, National Central UniversityDepartment of Atmospheric Sciences, National Central UniversityCenter for Environmental Monitoring and Technology, National Central UniversityGraduate Institute of Environmental Engineering, National Central UniversityResearch Center for Environmental Changes, Academia SinicaResearch Center for Environmental Changes, Academia SinicaDepartment of Atmospheric Sciences, National Central UniversityDepartment of Atmospheric Sciences, National Central UniversityAbstract Long-range pollution transport (LRT) events have a wide impact across East Asia, but are often difficult to track due to imprecise emission inventories and changing domain scales as the plume moves from source to receptor locations. This study adjusts a bottom-up emission inventory based on changes in remotely sensed NO2 column densities for a source region of East Asia, then with CMAQv5.2.1 simulates transport of LRT plumes to Taiwan. Adjustment of an emissions inventory based on satellite measurements during the COVID-19 lockdown in China led to a ~59% reduction in emissions over the relevant source area in China compared to base emissions. As a result, PM2.5 mass concentrations were reproduced to match observations (mean fractional bias, MFB of –13.9% and 18.5% at a remote and urban station) as the plume passed through northern Taiwan. Furthermore, the OMI-adjusted emissions simulation brought all of the major PM2.5 components to within ~50% of the measured values. Another LRT event from 2018 with more subtle OMI-adjustments to the emissions was also simulated and with improved overall PM2.5 mass concentration at the northern tip of Taiwan (MFB: –91.5%) compared to the base model (MFB: –102.1%), and an acceptable index of agreement (0.78). For the 2018 event, non sea-salt sulfate concentrations were consistently underpredicted (0.2–0.4), while nitrate concentrations were overpredicted by up to factor of 11. Copernicus Atmosphere Monitoring Service (CAMS) reanalysis of the PM2.5 concentrations shows high sulfate concentrations in eastern China in the areas associated with 72-h back-trajectories from northern Taiwan during both events, lending support for future model investigations of sulfate source area production and transport to Taiwan. In order to better track these LRT events out of East Asia and optimize OMI-adjustment methodology, it is recommended to explore other satellite-based products to map unaccounted for SO2 sources upstream of Taiwan.https://doi.org/10.4209/aaqr.210121PM2.5East AsiaNOx emissionsCMAQ |
| spellingShingle | Wei-Syun Huang Stephen M. Griffith Yi-Chun Lin Ying-Chieh Chen Chung-Te Lee Charles C.-K. Chou Ming-Tung Chuang Sheng-Hsiang Wang Neng-Huei Lin Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport Events Aerosol and Air Quality Research PM2.5 East Asia NOx emissions CMAQ |
| title | Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport Events |
| title_full | Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport Events |
| title_fullStr | Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport Events |
| title_full_unstemmed | Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport Events |
| title_short | Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport Events |
| title_sort | satellite based emission inventory adjustments improve simulations of long range transport events |
| topic | PM2.5 East Asia NOx emissions CMAQ |
| url | https://doi.org/10.4209/aaqr.210121 |
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