• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.48-59
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• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.

• Environmental Engineering Research
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• v.14 no.1
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• pp.53-60
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• 2009

The main objective was to develop and assess a dynamic fate and transport model for lead in air, soil, sediment, water and vegetation. Daejeon was chosen as the study area for its relatively high contamination and emission levels. The model was assessed by comparing model predictions with measured concentrations in multi-media and atmospheric deposition flux. Given a lead concentration in air, the model could predict the concentrations in water and soil within a factor of five. Sensitivity analysis indicated that effective compartment volumes, rain intensity, scavenging ratio, run off, and foliar uptake were critical to accurate model prediction. Important implications include that restriction of air emission may be necessary in the future to protect the soil quality objective as the contamination level in soil is predicted to steadily increase at the present emission level and that direct discharge of lead into the water body was insignificant as compared to atmospheric deposition fluxes. The results strongly indicated that atmospheric emission governs the quality of the whole environment. Use of the model developed in this study would provide quantitative and integrated understanding of the cross-media characteristics and assessment of the relationships of the contamination levels among the multi-media environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4B
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• pp.337-346
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• 2010

Climate change has a huge impact on various parts of the world. This study quantified and analyzed the effects on hydrological behavior caused by climate, vegetation canopy and land use change of Soyanggang dam watershed (2,694.4 $km^2$) using the semi-distributed model SWAT (Soil Water Assessment Tool). For the 1997-2006 daily dam inflow data, the model was calibrated with the Nash-Sutcliffe model efficiencies between the range of 0.45 and 0.91. For the future climate change projection, three GCMs of MIROC3.2hires, ECHAM5-OM, and HadCM3 were used. The A2, A1B and B1 emission scenarios of IPCC (Intergovernmental Panel on Climate Change) were adopted. The data was corrected for each bias and downscaled by Change Factor (CF) method using 30 years (1977-2006, baseline period) weather data and 20C3M (20th Century Climate Coupled Model). Three periods of data; 2010-2039 (2020s), 2040-2069 (2050s), 2070-2099 (2080s) were prepared for future evaluation. The future annual temperature and precipitation were predicted to change from +2.0 to $+6.3^{\circ}C$ and from -20.4 to 32.3% respectively. Seasonal temperature change increased in all scenarios except for winter period of HadCM3. The precipitation of winter and spring increased while it decreased for summer and fall for all GCMs. Future land use and vegetation canopy condition were predicted by CA-Markov technique and MODIS LAI versus temperature regression respectively. The future hydrological evaluation showed that the annual evapotranspiration increases up to 30.1%, and the groundwater recharge and soil moisture decreases up to 55.4% and 32.4% respectively compared to 2000 condition. Dam inflow was predicted to change from -38.6 to 29.5%. For all scenarios, the fall dam inflow, soil moisture and groundwater recharge were predicted to decrease. The seasonal vapotranspiration was predicted to increase up to 64.2% for all seasons except for HadCM3 winter.

• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.33-50
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• 2009

The impact on hydrologic components considering future potential climate, land use change and vegetation cover information was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated (1999 - 2000) and validated (2001 - 2002) for the upstream watershed ($260.4\;km^2$) of Gyeongancheon water level gauging station with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.77 to 0.60 and 0.79 to 0.60, respectively. Two GCMs (MIROC3.2hires, ECHAM5-OM) future weather data of high (A2), middle (A1B) and low (B1) emission scenarios of the IPCC (Intergovernmental Panel on Climate Change) were adopted and the data was corrected by 20C3M (20th Century Climate Coupled Model) and downscaled by Change Factor (CF) method using 30 years (1977 - 2006, baseline period) weather data. Three periods data of 2010 - 2039 (2020s), 2040 - 2069 (2050s), 2070 - 2099 (2080s) were prepared. To reduce the uncertainty of land surface conditions, future land use and vegetation canopy prediction were tried by CA-Markov technique and NOAA NDVI-Temperature relationship respectively. MIROC3.2 hires and ECHAM5-OM showed increase tendency in annual streamflow up to 21.4 % for 2080 A1B and 8.9 % for 2050 A1B scenario respectively. The portion of future predicted ET about precipitation increased up to 3 % in MIROC3.2 hires and 16 % in ECHAM5-OM respectively. The future soil moisture content slightly increased compared to 2002 soil moisture.

• Journal of Environmental Science International
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• v.22 no.6
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• pp.745-759
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• 2013

The characteristics of meteorological conditions and air pollution were investigated in a valley city (Yangsan) on bad visibility days (from 05:00 to 09:00 LST) of the cold half year (November 2008 to April 2009). This analysis was performed using the hourly observed data of meteorological variables (temperature, wind speed and direction, relative humidity, and 2 m and 10 m temperature) and air pollutants ($NO_2$, $SO_2$, $PM_{10}$, and $O_3$). In addition, visibility data based on visual measurements and a visibility meter were used. The bad visibility days were classified into four types: fog, mist, haze, and the mixture (mist+haze). The results showed that the bad visibility days of the four types in the valley city were observed to be more frequently (about 50% of the total study period (99 days except for missing data)) than (27%) those near coastal metropolitan city (Busan). The misty days (39%) in the valley city were the most dominant followed by the hazy (37%), mixture (14%), and foggy days (10%). The visibility degradation on the misty days in Yangsan was closely related to the combined effect of high-level relative humidity due to the accumulation of water vapor from various sources (e.g. river, stream, and vegetation) and strong inversion due to the development of surface radiative cooling within the valley. On the hazy days, the visibility was mainly reduced by the increase in air pollutant (except for $O_3$) concentrations from the dense emission sources under local conditions of weaker winds from the day before and stronger inversion than the misty days. The concentrations of $NO_2$, $PM_{10}$, and $SO_2$ (up to +36 ppb, $+25{\mu}g/m^3$, and +7 ppb) on the hazy days were a factor of 1.4-2.3 higher than those (+25 ppb, $+14{\mu}g/m^3$, and +3 ppb) on the misty days.