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http://dx.doi.org/10.5572/KOSAE.2018.34.2.306

Evaluation of the Simulated PM2.5 Concentrations using Air Quality Forecasting System according to Emission Inventories - Focused on China and South Korea  

Choi, Ki-Chul (Air Quality Forecasting Center, National Institute of Environmental Research)
Lim, Yongjae (Air Quality Forecasting Center, National Institute of Environmental Research)
Lee, Jae-Bum (Air Quality Forecasting Center, National Institute of Environmental Research)
Nam, Kipyo (Air Quality Forecasting Center, National Institute of Environmental Research)
Lee, Hansol (Air Quality Forecasting Center, National Institute of Environmental Research)
Lee, Yonghee (Air Quality Forecasting Center, National Institute of Environmental Research)
Myoung, Jisu (Air Quality Forecasting Center, National Institute of Environmental Research)
Kim, Taehee (Air Quality Forecasting Center, National Institute of Environmental Research)
Jang, Limseok (Air Quality Forecasting Center, National Institute of Environmental Research)
Kim, Jeong Soo (Air Quality Forecasting Center, National Institute of Environmental Research)
Woo, Jung-Hun (College of Global Integrated Studies, Konkuk University)
Kim, Soontae (Department of Environmental & Safety Engineering, Ajou University)
Choi, Kwang-Ho (Department of General Education, Namseoul University)
Publication Information
Journal of Korean Society for Atmospheric Environment / v.34, no.2, 2018 , pp. 306-320 More about this Journal
Abstract
Emission inventory is the essential component for improving the performance of air quality forecasting system. This study evaluated the simulated daily mean $PM_{2.5}$ concentrations in South Korea and China for 1-year period (Sept. 2016~Aug. 2017) using air quality forecasting system which was applied by the emission inventory of E2015 (predicted CAPSS 2015 for South Korea and KORUS 2015 v1 for the other regions). To identify the impacts of emissions on the simulated $PM_{2.5}$, the emission inventory replaced by E2010 (CAPSS 2010 and MIX 2010) were also applied under the same forecasting conditions. These results showed that simulated daily mean $PM_{2.5}$ concentrations had generally suitable performance with both emission data-sets for China (IOA>0.87, R>0.87) and South Korea (IOA>0.84, R>0.76). The impacts of the changes in emission inventories on simulated daily mean $PM_{2.5}$ concentrations were quantitatively estimated. In China, normalized mean bias (NMB) showed 5.5% and 26.8% under E2010 and E2015, respectively. The tendency of overestimated concentrations was larger in North Central and Southeast China than other regions under both E2010 and E2015. Seasonal differences of NMB were higher in non-winter season (28.3% (E2010)~39.3% (E2015)) than winter season (-0.5% (E2010)~8.0% (E2015)). In South Korea, NMB showed -5.4% and 2.8% for all days, but -15.2% and -11.2% for days below $40{\mu}g/m^3$ to minimize the impacts of long-range transport under E2010 and E2015, respectively. For all days, simulated $PM_{2.5}$ concentrations were overestimated in Seoul, Incheon, Southern part of Gyeonggi and Daejeon, and underestimated in other regions such as Jeonbuk, Ulsan, Busan and Gyeongnam, regardless of what emission inventories were applied. Our results suggest that the updated emission inventory, which reflects current status of emission amounts and spatio-temporal allocations, is needed for improving the performance of air quality forecasting.
Keywords
$PM_{2.5}$; Emission inventory; Air quality forecasting; CMAQ;
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Times Cited By KSCI : 3  (Citation Analysis)
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