• Particle and aerosol research
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• v.17 no.1
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• pp.9-20
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• 2021

As a large city advanced, the urban environment is becoming an issue. The contribution of vehicle emissions in air pollutants was very high according to the clean air policy support system (CAPSS). In order to improve the air quality in large cities, it is necessary to establish improvement measures by sources, analyzing the air quality of roadside. We divided Bucheon city into 4 regions to investigate the roadside pollutants of each district using the mobile laboratory (ML) and air quality monitoring station (AQMS). ML was used to measure pollutants emitted from vehicles and AQMS data was used as a comparison group of ML data. As a measurement result of pollutants in the roadside, the concentration of air pollutants in industrial & engineering complex area was the highest and concentration of air pollutants in residential & forest complex area was lower. By street, Bucheon-ro, Sinheung-ro, Sosa-ro, and Gyeongin-ro were identified as high concentrations. Therefore, further researches on preparing management measures for roads in the hot-spot area are needed.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.5
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• pp.536-546
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• 2016

The diurnal variations of $O_3$ and $NO_2$ in an urban park and the effects of air temperature and wind speed on the diurnal variations are investigated. $O_3$ and $NO_2$ concentrations were observed at a site in an urban park of Seoul from 27 July 2015 to 9 August 2015. The $O_3$ and $NO_2$ concentrations observed in the urban park are compared to those observed at the Gangnam air quality monitoring station (AQMS). The $O_3$ concentration is higher in the urban park than at the Gangnam AQMS in the daytime because the amount of $O_3$ dissociated by NO is smaller as well as partly because the amount of $O_3$ produced in the oxidation process of biogenic volatile organic compounds (VOCs) is larger in the urban park than at the Gangnam AQMS. The $NO_2$ concentration is lower in the urban park than at the Gangnam AQMS during day and night because the observation site in the urban park is relatively far from roads where $NO_x$ is freshly emitted from vehicles. The difference in $NO_2$ concentration is larger in the daytime than in the nighttime. To examine the effects of air temperature and wind speed on the diurnal variations of $O_3$ and $NO_2$, the observed $O_3$ and $NO_2$ concentrations are classified into high or low air temperature and high or low wind speed days. The high $O_3$ and $NO_2$ concentrations in the daytime appear for the high air temperature and low wind speed days. This is because the daytime photochemical processes are favorable when the air temperature is high and the wind speed is low. The scatter plots of the daytime maximum $O_3$ and minimum $NO_2$ concentrations versus the daytime averages of air temperature and wind speed show that the daytime maximum $O_3$ and minimum $NO_2$ concentrations tend to increase as the air temperature increases or the wind speed decreases. The daytime maximum $O_3$ concentration is more sensitive to the changes in air temperature and wind speed in the urban park than at the Gangnam AQMS.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.679-692
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• 2020

We coupled a CFD model to the WRF-Chem model (WRF-CFD model) and investigated the characteristics of flows and carbon monoxide (CO) distributions in a building-congested district. We validated the simulated results against the measured wind speeds, wind directions, and CO concentrations. The WRF-Chem model simulated the winds from southwesterly to southeasterly, overestimating the measured wind speeds. The statistical validation showed that the WRF-CFD model simulated the measured wind speeds more realistically than the WRF-Chem model. The WRF-Chem model significantly underestimated the measured CO concentrations, and the WRF-CFD model improved the CO concentration prediction. Based on the statistical validation results, the WRF-CFD model improved the performance in predicting the CO concentrations by taking complicatedly distributed buildings and mobiles sources of CO into account. At 04 KST on May 22, there was a downdraft around the AQMS, and airflow with a relatively low CO concentration was advected from the upper layer. Resultantly, the CO concentration was lower at the AQMS than the surrounding area. At 15 KST on May 22, there was an updraft around the AQMS. This resulted in a slightly higher CO concentration than the surroundings. The WRF-CFD model transported CO emitted from the mobile sources to the AQMS measurement altitude, well reproducing the measured CO concentration. At 18 KST on May 22, the WRF-CFD model simulated high CO concentrations because of high CO emission, broad updraft area, and an increase in turbulent diffusion cause by wind-shear increase near the ground.

• Journal of Environmental Health Sciences
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• v.48 no.6
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• pp.298-305
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• 2022

Background: The concentration of air pollutants as measured by the Air Quality Monitoring System (AQMS) is not an accurate population exposure level since actual human activities and temporal and spatial variability need to be considered. Therefore, to increase the accuracy of exposure assessment, the population should be considered. However, it is difficult to obtain population data due to limitations such as personal information. Objectives: The existing population defined in this study is the number of people in each region's grid. The purpose is to provide a methodology for evaluating exposure to PM_2.5 through existing population data provided by the National Geographic Information Institute. Methods: The selected study period was from October 26 to October 28, 2021. Using PM_2.5 concentration data measured at the Sensor-based Air Monitoring Station (SAMS) installed in Guro-gu and Wonju-si, the concentration for each grid was estimated by applying inverse distance weights through QGIS version 3.22. Considering the existing population, population-weighted average concentration (PWAC) was calculated and the exposure level of the population was compared by region. Results: The outdoor PM_2.5 concentration as measured through the SAMS was high in Wonju-si on all three days. Wonju-si showed an average 22% higher PWAC than Guro-gu. As a result of comparing the PWAC and outdoor PM_2.5 concentration by region, the PWAC in Guro-gu was 1~2% higher than the observed value, but it was almost the same. Conversely, observations of Wonju-si were 10.1%, 11.3%, and 8.2% higher than PWAC. Conclusions: It is expected that the Geographic Information System (GIS) method and the existing population will be used to evaluate the exposure level of a population with a narrow activity radius in further research. In addition, based on this study, it is judged that research on exposure to environmental pollutants and risk assessment methods should be expanded.