Mi-Kyoung Hwang

Identification and Interpretation of Representative Ozone Distributions in Association with the Sea Breeze from Different Synoptic Winds over the Coastal Urban Area in Korea

Abstract To aid the studies of long-term impact assessment of cumulative ozone (O3) exposures, the representative 8-hr O3 pollution patterns have been identified over the Greater Seoul Area (GSA) in Korea. Principal component analysis and two-stage clustering techniques were used to identify the representative O3 patterns, and numerical and observational analyses were also used to interpret the identified horizontal distribution patterns. The results yielded three major O3 distribution patterns, and each of the three patterns was found to have strong correlations with local and synoptic meteorological conditions over the GSA. For example, pattern 1, accounting for 46% of O3 concentration distributions, mostly occurred under relatively weak westerly synoptic winds. The predominant features of this pattern were infrequent high O3 levels but a distinct gradient of O3 concentration from the western coastal area to the eastern inland area that was mainly induced by the local sea breeze. Pattern 2, accounting for 31% of O3 concentration distributions, was found with higher O3 levels in the western coastal area but lower in the eastern inland area. This is due to the modified sea breeze under the relatively stronger easterly opposing synoptic wind, affecting the high O3 occurrence in the western coastal area only. However, pattern 3, accounting for 21% of O3 concentration distributions, showed significantly higher O3 concentrations over the whole GSA mainly due to the retarded and slow-moving sea-breeze front under the weak opposing synoptic flow. Modeling study also indicated that local and synoptic meteorological processes play a major role in determining the high O3 concentration distribution patterns over the GSA.

High-resolution Simulation of Meteorological Fields over the Coastal Area with Urban Buildings

A meso-urban meteorological model (Urbanized MM5; uMM5) with urban canopy parameterization (UCP) was applied to the high-resolution simulation of meteorological fields in a complex coastal urban area and the assessment of urban impacts. Multi-scale simulations with the uMM5 in the innermost domain (1-km resolution) covering the Busan metropolitan region were performed during a typical sea breeze episode (4~8 August 2006) with detailed fine-resolution inputs (urban morphology, land-use/land-cover sub-grid distribution, and high-quality digital elevation model data sets). An additional simulation using the standard MM5 was also conducted to identify the effects of urban surface properties under urban meteorological conditions. Results showed that the uMM5 reproduced well the urban thermal and dynamic environment and captured well the observed feature of sea breeze. When comparison with simulations of the standard MM5, it was found that the uMM5 better reproduced urban impacts on temperature (especially at nighttime) and urban wind flows: roughness-induced deceleration and UHI (Urban Heat Island)-induced convergence.

Intercomparison of Wind and Air Temperature Fields of Meteorological Model for Forecasting Air Quality in Seoul Metropolitan Area

The MM5, RAMS and WRF, meteorological models have provided the dynamical parameters as inputs to air quality model. A major content of this study is that significant characteristics of three models for high-ozone occurrence analyze for surface wind and air temperature fields and compare with observation data in Seoul metropolitan area. An analysis of air temperature field revealed that location of core in high temperature of MM5 and WRF differed from that of RAMS. MM5 and WRF indicated high temperature in Seoul but RAMS represented it on the outskirts of Seoul. MM5 and WRF were underestimated maximum temperature during daytime but RAMS simulated similar value with observation data. Surface wind field with three models, it was shown many differences at horizontal distribution of wind direction. RAMS indicated weak wind speed in land and strong sea breeze at coastal areas than MM5 and WRF. However wind speed simulated by three model were overestimated during both daytime and nighttime.

Modeling of the Air Pollutant Recirculation using the MM5-CAMx on Ozone Episode in Greater Seoul Area during June, 2004

Recent evidence has demonstrated that the pollutant recirculation can play an important role in leading to high ozone concentrations. In this study, the MM5-CAMx air quality modeling system was applied to simulate the pollutant recirculation and identify the transport of pollution during the high event (the maximum of 195 ppb) observed in the Greater Seoul Area (GSA) on June in 2004. The results showed a weak northeasterly synoptic wind during the night and early morning moved the air parcels containing the locally emitted urban pollution to the coast, which contributed to enhance formation in the southwest part of the GSA. As the sea breeze developed and started to penetrate inland in the late afternoon, the rapid build-up of concentration was found in the southwest coastal area due to the recirculation of the polluted air loaded with high level . The simulated backward trajectories and observations at coastal sites confirmed the recirculation of pollutant with the late sea breeze is the dominant factor affecting the occurrence of high concentrations in the southwestern GSA.

Spatial Distribution of Air Pollution in the Ulsan Metropolitan Region

The spatial air pollution distribution of the Ulsan metropolitan region (UMR) was analyzed using monitoring data and high-resolution numerical simulations. A three-year (2011~2014) analysis for the average concentrations from the 13 air quality monitoring sites in the UMR showed that SO2 and PM10 levels in industrial regions were much higher than those in other regions, whereas spatial differences of NO2 and CO concentrations were not significant. In particular, elevated O3 concentrations were clearly found at urban sites near petrochemical complex area. Results from high-resolution simulations by CMAQ model performed for four months of 2012 showed large spatial variations in grid-average pollutant concentrations between industrial areas and other areas in the UMR, which displayed significant changes with wind pattern by season. It was noted that the increases of SO2 and PM10 levels were limited in costal industrial areas or over the area nearby the sea in all seasons. Modeled O3 concentrations were quite low in industrial areas and main urban roads with large NOx emissions. However, the model presented that all pollutant concentrations were significantly increased in the urban residential areas near the industrial complexes in summer season with increase of southerly wind.

Modeling the Impacts of Increased Urbanization on Local Meteorology in the Greater Seoul Area

The impact of urbanization on local meteorology (e.g., surface temperature, PBL height, wind speed, etc.) in the Greater Seoul Area (GSA) was quantitatively evaluated based on a numerical modeling approach during a 1-month period of 2001 (9 Sep. through 8 Oct. 2001). The analysis was carried out by two sets of simulation scenarios: (1) with the global land use and topographic data from the U.S. Geological Survey (USGS) in 1990s (i.e., LU-USGS case) and (2) with the land use data from the Environmental Geographic Information System (EGIS) along with the 3 sec elevation data from the Shuttle Radar Topography Mission (SRTM) in 2000s (i.e., LU-EGIS case). The extension of urban areas in the GSA (especially, the southern parts of Seoul) accounted for 1.8% in the LU-USGS case and 6.2% in the LU-EGIS case. For the simulations, the surface temperature and PBL height due to urbanization in the LU-EGIS case was higher (the differences of up to and 36 m, respectively) than those in the LU-USGS case, whereas the wind speed (up to 0.3 ) in the former was lower than that in the latter at 1500 LST. The increase in surface temperature due to urbanization in the GSA (especially, the southern parts of Seoul) was led to the strong convergence of air masses, causing the early sea breeze and its rapid propagation to inland locations. In addition, the vertical mixing motion in the extended urban areas for the LU-EGIS case was predicted to be stronger than that for the LU-USGS case and vice versa for the original urban areas.

Ozone Exposure Assessment by Population Characteristics: A Case Study for High Ozone Days in Busan

【Objectives: Photochemical ozone pollution is associated with increased mortality risk. This study aims to assess the population exposure to ozone according to population characteristics for high ozone days in the Busan metropolitan region (BMR). Methods: The ozone exposure assessment in this study was performed using the WRF-CMAQ simulated ozone concentrations and the population data in the BMR. The settled and daytime population and their activity were considered to conduct the static and dynamic ozone exposure assessment. Results: Applying a static exposure assessment, in case that high ozone occurred throughout Busan area, the highest exposure levels were evaluated in urban neighborhoods. In case of ozone pollution in outer Busan, because sensitive groups have been relatively higher exposure, this case was also evaluated as part of that should not be overlooked. The dynamic exposure was higher than static exposure because the number of population exposed to ozone of high concentration is increased. This approach is important in a regard consider that daytime population distribution when high ozone occur. Conclusion: This study shows the different population exposure according to various ozone distributions for each episode day. Considering demographic characteristic such as population density and activity should be important to understanding the population exposure assessment when ozone pollution occurs.】

Health Vulnerability Assessment for PM 10 in Busan

Objectives: This study seeks to evaluate the vulnerability assessment of the human health sector for PM 10 , which is reflected in the regional characteristics and related disease mortality rates for PM 10 in Busan over the period of 2006-2010. Methods: According to the vulnerability concept suggested by the Intergovernmental Panel on Climate Change (IPCC), vulnerability to PM 10 is comprised of the categories of exposure, sensitivity, and adaptive capacity. The indexes of the exposure and sensitivity categories indicate positive effects, while the adaptive capacity index indicates a negative effect on vulnerability to PM 10 . Variables of each category were standardized by the rescaling method, and each regional relative vulnerability was computed through the vulnerability index calculation formula. Results: The regions with a high exposure index are Jung-Gu (transportation region) and Saha-Gu (industrial region). Major factors determining the exposure index are the PM 10 concentration, days of PM 10 ≥ 50 ,μg/m³, and PM 10 emissions. The regions that show a high sensitivity index are urban and rural regions; these commonly have a high mortality rate for related disease and vulnerable populations. The regions that have a high adaptive capacity index are Jung-Gu, Gangseo-Gu, and Busanjin-Gu, all of which have a high level of economic/welfare/health care factors. The high-vulnerability synthesis of the exposure, sensitivity, and adaptive capacity indexes show that Dong-Gu and Seo-Gu have a risk for PM 10 potential effects and a low adaptive capacity. Conclusions: This study presents the vulnerability index to PM 10 through a relative comparison using quantitative evaluation to draw regional priorities. Therefore, it provides basic data to reflect environmental health influences in favor of an adaptive policy limiting damage to human health caused by vulnerability to PM 10 .Objectives: This study seeks to evaluate the vulnerability assessment of the human health sector for PM10, which is reflected in the regional characteristics and related disease mortality rates for PM10 in Busan over the period of 2006-2010. Methods: According to the vulnerability concept suggested by the Intergovernmental Panel on Climate Change (IPCC), vulnerability to PM10 is comprised of the categories of exposure, sensitivity, and adaptive capacity. The indexes of the exposure and sensitivity categories indicate positive effects, while the adaptive capacity index indicates a negative effect on vulnerability to PM10. Variables of each category were standardized by the rescaling method, and each regional relative vulnerability was computed through the vulnerability index calculation formula. Results: The regions with a high exposure index are Jung-Gu (transportation region) and Saha-Gu (industrial region). Major factors determining the exposure index are the PM10 concentration, days of PM10 ≥ 50 ,μg/m , and PM10 emissions. The regions that show a high sensitivity index are urban and rural regions; these commonly have a high mortality rate for related disease and vulnerable populations. The regions that have a high adaptive capacity index are Jung-Gu, Gangseo-Gu, and Busanjin-Gu, all of which have a high level of economic/welfare/ health care factors. The high-vulnerability synthesis of the exposure, sensitivity, and adaptive capacity indexes show that Dong-Gu and Seo-Gu have a risk for PM10 potential effects and a low adaptive capacity. Conclusions: This study presents the vulnerability index to PM10 through a relative comparison using quantitative evaluation to draw regional priorities. Therefore, it provides basic data to reflect environmental health influences in favor of an adaptive policy limiting damage to human health caused by vulnerability to PM10.

Numerical Modeling for the Effect of High-rise Buildings on Meteorological Fields over the Coastal Area Using Urbanized MM5

Modeling the effects of high-rise buildings on thermo-dynamic conditions and meteorological fields over a coastal urban area was conducted using the modified meso-urban meteorological model (Urbanized MM5; uMM5) with the urban canopy parameterization (UCP) and the high-resolution inputs (urban morphology, land-use/land-cover sub-grid distribution, and high-quality digital elevation model data sets). Sensitivity simulations was performed during a typical sea-breeze episode (4~8 August 2006). Comparison between simulations with real urban morphology and changed urban morphology (i.e. high-rise buildings to low residential houses) showed that high-rise buildings could play an important role in urban heat island and land-sea breeze circulation. The major changes in urban meteorologic conditions are followings: significant increase in daytime temperature nearly by due to sensible heat flux emitted from high density residential houses, decrease in nighttime temperature nearly by because of the reduction in the storage heat flux emitted from high-rise buildings, and large increase in wind speed (maximum 2 m ) during the daytime due to lessen drag-force or increased gradient temperature over coastal area.

Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010

Oak pollen concentrations over the Houston-Galveston-Brazoria (HGB) area in southeastern Texas were modeled and evaluated against in-situ data. We modified the Community Multi-scale Air Quality (CMAQ) model to include oak pollen emission, dispersion, and deposition. The Oak Pollen Emission Model (OPEM) calculated gridded oak pollen emissions, which are based on a parameterized equation considering a plant-specific factor (Ce), surface characteristics, and meteorology. The simulation period was chosen to be February 21 to April 30 in the spring of 2010, when the observed monthly mean oak pollen concentrations were the highest in six years (2009-2014). The results indicated Ce and meteorology played an important role in the calculation of oak pollen emissions. While Ce was critical in determining the magnitude of oak pollen emissions, meteorology determined their variability. In particular, the contribution of the meteorology to the variation in oak pollen emissions increased with the oak pollen emission rate. The evaluation results using in-situ surface data revealed that the model underestimated pollen concentrations and was unable to accurately reproduce the peak pollen episodes. The model error was likely due to uncertainty in climatology-based Ce used for the estimation of oak pollen emissions and inaccuracy in the wind fields from the Weather Research and Forecast (WRF) model.