• Journal of Korean Society for Atmospheric Environment
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• v.24 no.4
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• pp.423-438
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• 2008

BEIS2 (Biogenic Emissions Inventory System version 2) and BEIS3.12 (BEIS version 3.12) were used to estimate hourly biogenic emissions over South Korea using a set of vegetation and meteorological data simulated with the MM5 (Mesoscale Model version 5). Two biogenic emission models utilized different emission factors and showed different responses to solar radiations, resulting in about $10{\sim}20%$ difference in the nationwide isoprene emission estimates. Among the 11-vegetation classes, it was found that mixed forest and deciduous forest are the most important vegetation classes producing isoprene emissions over South Korea comprising ${\sim}90%$ of the total. The simulated isoprene concentrations over Seoul metropolitan area show that diurnal and daily variations match relatively well with the PAMS (Photochemical Air Monitoring Station) measurements during the period of June 3${\sim}$June 10, 2004. Compared to BEIS2, BEIS3.12 yielded ${\sim}35%$ higher isoprene concentrations during daytime and presented better matches to the high peaks observed over the Seoul area. This study showed that the importance of vegetation data and emission factors to estimate biogenic emissions. Thus, it is expected to improve domestic vegetation categories and emission factors in order to better represent biogenic emissions over South Korea.

• Asian Journal of Atmospheric Environment
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• v.9 no.4
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• pp.259-271
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• 2015

This study conducted analyses on biogenic volatile organic compounds (BVOC) emission sources contributing to urban ozone ($O_3$) concentration in Osaka Prefecture, Japan in summer 2010 by using the Weather Research and Forecasting model (WRF) version 3.5.1 and the Community Multiscale Air Quality model (CMAQ) version 5.0.1. This prefecture is characterized by highly urbanized area with small forest area. The contributions of source regions surrounding Osaka were estimated by comparing the baseline case and zero-out cases for BVOC emissions from each source region. The zero-out emission runs showed that the BVOC emissions substantially contributed to urban $O_3$ concentration in Osaka (10.3 ppb: 15.9% of mean daily maximum 1-h $O_3$ concentration) with day-by-day variations of contributing source regions, which were qualitatively explained by backward trajectory analyses. Although $O_3$ concentrations were especially high on 23 July and 2 August 2010, the contribution of BVOC on 23 July (35.4 ppb: 25.6% of daily maximum $O_3$) was much larger than that on 2 August (20.9 ppb: 14.2% of daily maximum $O_3$). To investigate this difference, additional zero-out cases for anthropogenic VOC (AVOC) emissions from Osaka and for VOC emissions on the target days were performed. On 23 July, the urban $O_3$ concentration in Osaka was dominantly increased by the transport from the northwestern region outside Osaka with large contribution of $O_3$ that was produced through BVOC reactions by the day before and was retained over the nocturnal boundary layer. On 2 August, the concentration was dominantly increased by the local photochemical production inside Osaka under weak wind condition with the particularly large contribution of AVOC emitted from Osaka on the day.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.1
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• pp.1-17
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• 2001

The high-ozone episode in the Greater Seoul Area for the period of July 27 to August 1 1997 was modeled by the CIT(California Institute of Technology) three-dimensional photochemical model. Emission data were prepared by scaling the NIER(1994) data through and optimization method using VOC measurements in August 1997 and EKMA(Empirical Kinetic Modeling Approach). Two sets of meteorological data were prepared by the diagnostic routine. a part of the CIT model : one only utilized observations from the surface weather stations and the other also utilized observations from the automatic weather stations that were more densely distributed than those from the surface weather stations. The results showed that utilizing observations from the automatic weather stations could represent fine variations in the sind field such as those caused by topography. A better wind field gave better peak ozones and a more reasonable spatial distribution of ozone concentrations. Nevertheless, there were still many differences between predictions and observations particularly for primary pollutant such as NOx and CO. This was probably due to the inaccuracy of emission data that could not resolve both temporal and spatial variations.

• Journal of Environmental Health Sciences
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• v.44 no.6
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• pp.539-547
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• 2018

Objectives: Ozone ($O_3$) advisories are issued by provincial/prefectural and city governments in Korea and Japan when oxidant concentrations exceed the criteria of the related country. Advisories issued only after exposure to high $O_3$ concentrations cannot be considered ideal measures. Forecasts of $O_3$ would be more beneficial to citizens' health and daily life than real-time advisories. The present study was undertaken to present a simplified forecasting model that can predict surface $O_3$ concentrations for the afternoon of the day of the forecast. Methods: For the construction of a simple and practical model, a multivariate regression model was applied. The monitored data on gases and climate variables from Japan's air quality networks that were recorded over nearly one year starting from April 2016 were applied as the subject for our model. Results: A well-known inverse correlation between $NO_2$ and $O_3$ was confirmed by the monitored data for Iksan, Korea and Fukuoka, Japan. Typical time fluctuations for $O_3$ and $NO_x$ were also found. Our model suggests that insolation is the most influential factor in determining the concentration of $O_3$. $CH_4$ also plays a major role in our model. It was possible to visually check for the fit of a theoretical distribution to the observed data by examining the probability-probability (P-P) scatter plot. The goodness of fit of the model in this study was also successfully validated through a comparison (r=0.8, p<0.05) of the measured and predicted $O_3$ concentrations. Conclusions: The advantage of our model is that it is capable of immediate forecasting of surface $O_3$ for the afternoon of the day from the routinely measured values of the precursor and meteorological parameters. Although a comparison to other approaches for $O_3$ forecasting was not carried out, the model suggested in this study would be very helpful for the citizens of Korea and Japan, especially during the $O_3$ season from May to June.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.1
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• pp.64-74
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• 2017

In this study, we have analyzed relationship between the measured Water Soluble Organic Carbon (WSOC) concentrations and the estimated aerosol water content of $PM_{10}$ (particulate matter with an aerodynamic diameter of less than or equal to $10{\mu}m$) for the period between September 2006 and August 2007 at Seoul, Korea. Water content of $PM_{10}$ was estimated by using a gas/particle equilibrium model, Simulating composition of Atmospheric Particles at Equilibrium 2 (SCAPE2). The WSOC concentrations showed low correlation with Elemental Carbon (EC), but Water Insoluble Organic Carbon (WISOC) were highly correlated with EC. It seemed that hydrophilic groups were produced by secondary formation rather than primary formation. As with the previous studies, WSOC showed good correlation with secondary ions ($NO_3{^-}$, $SO_4{^{2-}}$, $NH_4{^+}$), especially WSOC was highly correlated with $NO_3{^-}$ that is a secondary ion formed by photochemical oxidation from more local sources than $SO_4{^{2-}}$. No apparent correlation between the measured WSOC and estimated water content was observed. However, WSOC showed good correlation with estimated water content when it was assumed that relative humidity was higher than the deliquescence relative humidity of the system. In conclusion, WSOC is correlated with water content by hygroscopic ions and it is expected that nitrate play an important role among the water content and WSOC.

• Atmosphere
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• v.27 no.1
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• pp.41-54
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• 2017

Organic carbon (OC) and elemental carbon (EC) in $PM_{2.5}$ were measured using Sunset OC/EC Field Analyzer at Seoul Hwangsa Monitoring Center from March to April, 2016. The mean concentrations of OC and EC during the entire period were $4.4{\pm}2.0{\mu}gC\;m^{-3}$ and $1.4{\pm}0.6{\mu}gC\;m^{-3}$, respectively. OC/EC ratio was $3.4{\pm}1.0$. The average concentrations of $PM_{10}$ and $PM_{2.5}$ were $57.4{\pm}25.9$ and $39.7{\pm}19.8{\mu}g\;m^{-3}$, respectively, which were detected by an optical particle counter. The OC and EC peaks were observed in the morning, which were impacted by vehicle emission, however, their diurnal variations were not noticeable. This is determined to be contributed by the long-range transported OC or secondary formation via photochemical reaction by volatile organic compounds at afternoon. A conditional probability function (CPF) model was used to identify the local source of pollution. High concentrations of $PM_{10}$ and $PM_{2.5}$ were observed from the westerly wind, regardless of wind speed. When wind velocity was high, a mixing plume of dust and pollution during long-range transport from China in spring was observed. In contrast, pollution in low wind velocity was from local source, regardless of direction. To know the effect of long-range transport on pollution, a concentration weighted trajectory (CWT) model was analyzed based on a potential source contribution function (PSCF) model in which 75 percentiles high concentration was picked out for CWT analysis. $PM_{10}$, $PM_{2.5}$, OC, and EC were dominantly contributed from China in spring, and EC results were similar in both PSCF and CWT. In conclusion, Seoul air quality in spring was mainly affected by a mixture of local pollution and anthropogenic pollutants originated in China than the Asian dust.