• Journal of Environmental Science International
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• v.25 no.1
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• pp.85-97
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• 2016

A comparison of ozone simulations in the seoul metropolitan region (SMR) using the community multiscale air quality (CMAQ) model with SAPRC99 and CB05 chemical mechanisms (i.e. EXP-SP99 and EXP-CB05) has been conducted during four seasons of 2012. The model results showed that the differences in average ozone concentrations between the EXP-SP99 and EXP-CB05 were found to be large in summer, but very small in the other seasons. This can be attributed that the SAPRC99 tends to produce more ozone than the CB05 in urban area like the SMR with low VOC/NOx ratio under high ozone conditions. Through quantitative comparison between two mechanisms for the summer, it was found that the average ozone concentrations from the EXP-SP99 were about 3 ppb higher than those from the EXP-CB05 and agreed well with the observations. Horizontal differences in ozone concentrations between SAPRC99 and CB05 showed that significant differences were found in southern part of the SMR and over the sea near the coast in summer.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.5
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• pp.580-602
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• 2011

Volatile organic compound (VOC) emissions in the 2007 CAPSS (Clean Air Protection Supporting System) emissions inventory are chemically speciated for the SAPRC99 (Statewide Air Pollution Research Center 99) mechanism, following the Source Classification Code (SCC) matching method to borrow the U.S.EPA's chemical speciation profiles. CMAQ simulations with High-order Direct Decoupled Method (HDDM) are in turn applied to evaluate uncertainty in the method by comparing the simulated model VOC species to the observations in the Seoul Metropolitan Area (SMA) for a 2007 June episode. Simulations under-predicted ALK1 to ALK4 in SAPRC99 by a factor of 2 to 5 and over-predicted ALK5 by a factor of 7.5 while ARO1, ARO2, OLE1, and ethylene (ETH) are comparable to the observations, showing relative difference by 10 to 30%. OLE2 emissions are roughly 4 times overestimated. Emission rates for individual VOC model species are revised referring to the ratio of simulated to observed concentrations. Impact of the VOC emission changes on the overall ozone prediction was insignificant for the days of which 1-hr maximum ozone are lower than 100 ppb. However, simulations showed ozone difference by 5 to 10 ppb when high ozone above 120 ppb was observed in the vicinity of Seoul. This result suggests that evaluations on individual model VOC emissions be necessary to lead ozone control plans to the right direction. Moreover, the simulated ratios of ARO1 and ARO2 to $NO_x$ are roughly 50% lower than the observed ones, which imply that adjustment in $NO_x$ and VOC emission rates may be required to mimic the real VOC/$NO_x$ condition over the area.

• Journal of the Korean earth science society
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• v.36 no.1
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• pp.36-50
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• 2015

The purpose of this study is to assign emission source profiles of volatile organic compounds (VOCs) and particulate matters (PMs) for chemical speciation, and to correct the temporal allocation factor and the chemical speciation of source profiles according to the source classification code within the sparse matrix operator kernel emission system (SMOKE) in the Seoul metropolitan area. The chemical speciation from the source profiles of VOCs such as gasoline, diesel vapor, coating, dry cleaning and LPG include 12 and 34 species for the carbon bond IV (CBIV) chemical mechanism and the statewide air pollution research center 99 (SAPRC99) chemical mechanism, respectively. Also, the chemical speciation of PM2.5 such as soil, road dust, gasoline and diesel vehicles, industrial source, municipal incinerator, coal fired, power plant, biomass burning and marine was allocated to 5 species of fine PM, organic carbon, elementary carbon, $NO_3{^-}$, and $SO_4{^2-}$. In addition, temporal profiles for point and line sources were obtained by using the stack telemetry system (TMS) and hourly traffic flows in the Seoul metropolitan area for 2007. In particular, the temporal allocation factor for the ozone modeling at point sources was estimated based on $NO_X$ emission inventories of the stack TMS data.