• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.551-561
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• 2023

In this study, we investigated the effects of the spectral fitting window and absorption cross-section on the retrieval of the formaldehyde (HCHO) slant column density (SCD) from the direct-sun measurement of pandora spectrometer system using differential optical absorption spectroscopy (DOAS). Pandora Level 1 data observed at Yonsei University in Seoul from October 12 to 31, 2022 were used. The HCHO column density was retrieved under eight ranges including the spectral fitting window used in the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) and seven types of absorption cross-section composition. The spectral fitting window was selected from 336.5 to 359.0 nm with minimum residual and HCHO SCD error. When the nitrogen dioxide (NO2) absorption cross-section at 220 K was added to the cross-section composition used in the CINDI-2 campaign among seven types, the residual and HCHO SCD error were the smallest and the HCHO column density wasstably retrieved. The average HCHO SCD with the highest retrieval accuracy and the values retrieved under other conditions differed from a minimum of 4% to a maximum of 40%.

• Journal of Preventive Medicine and Public Health
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• v.51 no.5
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• pp.263-264
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• 2018

Based on epidemiological and genomic characteristics, lung cancer in never smokers (LCNS) is a different disease from lung cancer in smokers. Based on current research, the main risk factor for LCNS may be air pollution. A recent case-control study in Koreans reported that nitrogen dioxide ($NO_2$) may be a risk factor for LCNS. Additionally, a cohort study showed that exposure to $NO_2$ was associated with significant hypomethylation. Thus, epigenetic epidemiology studies are needed in the near future to evaluate the carcinogenesis of LCNS according to chronic exposure to air pollution and/or viral infections.

• Journal of Korean Society for Atmospheric Environment
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• v.12 no.4
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• pp.429-439
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• 1996

A comprehensive air quality monitoring was carried out in this study to investigate the concentrations of criteria air pollutants in indoor and outdoor air of public facilities in Taegu area. Four different kinds of public facilities were seleced as sampling sites, which are underground stores, stations & terminals, general hospitals, and department stores. Each group of the public facilities was consisted of three different sampling sites. As a consequence, a total of 12 different sampling sites were surveyed throughout this study. Sampling was conducted simultaneously indoors, three times per day (in the morning, afternoon, and evening) and four times per year (spring, summer, fall, and winter) at each sampling site during the period of October 1994 to July 1995. A range of criteria pollutants were measured in order to obtain a broad profile of indoor and ambient air quality, including total suspended particles (TSP), carbon monoxide (CO), carbon dioxide ($CO_2$), formaldehyde (HCHO), sulfur dioxide ($SO_2$), and nitrogen dioxide ($NO_2$). In addition, temperature, relative humidity, and air current were measured on site together with those air pollutants. Results of this study indicated that the indoor levels of TSP, CO, $SO_2, and NO_2$ appeared to be generally higher in stations/terminals and underground stores than those in department stores and hospitals. However, HCHO and $CO_2$ were found to have higher levels in the department stores and hospitals than other places, indicating that the effects of indoor sources for these pollutants are significantly different from other combustion related pollutants such as TSP, CO, and $SO_2$. It was also found that there are marked seasonal and daily variations both in indoor and outdoor air quality. In general, combustion related pollutants such as CO, $SO_2$ and $NO_2$ showed a typical pattern of higher levels in winter than insummer, and also higher in the morning and/or in the evening than in the afternoon. However, the seasonal and daily patterns of HCHO appeared to be opposite to the combustion related pollutants, i.e., higher both in summer and in the afternoon, implying the effect of temperature on the volatilization from indoor sources of HCHO. Results of correlation analyses between indoor and outdoor air quality also indicated that the effects of outdoor sources on the indoor levels of TSP, $SO_2$, CO, and $NO_2$ and much significant, whilst no significant correlations between indoor and outdoor levels were found for HCHO and $CO_2$.

• Proceedings of the Korean Environmental Health Society Conference
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• 2004.12a
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• pp.45-50
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• 2004

Indoor air quality can be affected by indoor sources, ventilation, decay and outdoor levels. Alt hough technologies exist to measure these factors, direct measurements are often difficult. The purpose of this study was to develop an alternative method to characterize indoor environmental factors by multiple indoor and outdoor measurements. Daily indoor and outdoor NO2 concentrations were measured for 30 consecutive days in 28 houses in Brisbane, Australia, and for 21 consecutive days in 37 houses in Seoul, Korea. Using a mass balance model and regression analysis, penetration factor (ventilation rate divided by the sum of ventilation rate and deposition constant) and source strength factor (source strength divided by the sum of ventilation rate and deposition constant) were calculated using multiple indoor and outdoor measurements. Subsequently, the ventilation rate and NO2 source strength were estimated. Geometric means of ventilation rate were 1.44 ACH in Brisbane, assuming a residential NO2 deposition constant of 1.05 hr-1, and 1.36 ACH in Seoul, with the measured residential NO2 deposition constant of 0.94 hr-1. Source strengths of N02 were 15.8 ${\pm}$ 18.2 ${\mu}$g/m3${\cdot}$hr and 44.7 ${\pm}$ 38.1 ${\mu}$g/m3${\cdot}$hr in Brisbane and Seoul, respectively. In conclusion, indoor environmental factors were effectively characterized by this method using multiple indoor and outdoor measurements.

• Journal of Environmental Health Sciences
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• v.26 no.4
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• pp.134-140
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• 2000

The increase in traffic is a worldwide phenomenon. In Korea, it has been increased by 20% per annual in recent 1990’s and approximately 10 millions cars had been registered until 1997. This traffic could easily affect and contribute the local outdoor air quality(QAQ) concerned. The QAQ in highway in one of the examples and the subject in this study. The seoul tollgate located at the north-end of Keypngbu Highway was selected for the study. In case of highway tollgate, the local air pollution could be directly affected by the traffic to approach, wait and start the tollgate. Nitrogen dioxide (NO$_2$) concentration exceeded the EAQS(Environmental Air Quality Standards), but overall indoor air quality was a little better than the outdoor air quality. The measured TSP concentration was much higher than that of the EAQS. To apply a management to a air quality problem of Seoul tollgate, it was predicted air quality with traffic volume and weather condition. It was calculated NO$_2$ emission with traffic volume and predicted in and out of booth by CALINE3 at the Seoul tollgate. To make a comparison between measured and predicted concentration, the prediction was good. It was shown that NO$_2$ concentration was high in the morning at the from Seoul direction and in the evening at the to Seoul direction. it was thought that NO$_2$ concentration variation was reflected according to the traffic volume.

• Journal of the Optical Society of Korea
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• v.15 no.1
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• pp.96-102
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• 2011

Simultaneous measurements using a scanning spectrograph system and transmissometer were performed for the first time over an urban site in Gwangju, Korea, to derive the ambient $NO_2$ volume mixing ratio. The differential slant column densities retrieved from the scanning spectrograph system were converted to volume mixing ratios using the light traveling distance along the scanning line of sight derived from the transmissometer light extinction coefficients. To assess the performance of this system, we compared the derived $NO_2$ volume mixing ratios with those measured by an in situ chemiluminescence monitor under various atmospheric conditions. For a cloudless atmosphere, the linear correlation coefficient (R) between the two data sets (i.e., data derived from the scanning spectrograph and from the in situ monitor) was 0.81; the value for a cloudy atmosphere was 0.69. The two sets of $NO_2$ volume mixing ratios were also compared for various wind speeds. We also consider the measurement errors, as estimated from an error propagation analysis.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.604-612
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• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1153-1164
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• 2008

The ozone data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model have been considered for analyzing the ozone data at the northern part of the Gyeonggi-Do, Uijeongbu monitoring site in Korea. The result showed that both overall and monthly ARE models are suited for describing the ozone concentration. In the ARE model, seven meteorological variables and four pollution variables are used as the as the explanatory variables for the ozone data set. The seven meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, dew point temperature, steam pressure, and amount of cloud. The four air pollution explanatory variables are Sulfur dioxide(SO2), Nitrogen dioxide(NO2), Cobalt(CO), and Promethium 10(PM10). Also, the high level ozone data (over 80ppb) have been analyzed four ARE models, General ARE, HL ARE, PM10 add ARE, Temperature add ARE model. The result shows that the General ARE, HL ARE, and PM10 add ARE models are suited for describing the high level of ozone data.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1117-1124
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• 2010

The PM10 (Promethium 10) data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model has been considered for analyzing the monthly PM10 data at the southern part of the Gyeonggi-Do, Suwon monitoring site in Korea. In the ARE model, six meteorological variables and four pollution variables are used as the explanatory variables for the PM10 data set. The six meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, radiation, and amount of cloud. The four air pollution explanatory variables are sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), carbon monoxide (CO), and ozone ($O_3$). The result showed that the monthly ARE models explained about 13-49% for describing the PM10 concentration.

• Journal of Platform Technology
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• v.9 no.4
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• pp.79-89
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• 2021

In this paper, the fine dust (PM10) and ultrafine dust (PM2.5) measurement platforms are designed to be mobile and fixed using oneM2M, the international standard for IoT. The fine dust measurement platform is composed and designed with a fine dust measurement device, agent, oneM2M platform, oneM2M IPE, and monitoring system. The main difference between mobile and fixed is that the mobile uses the MQTT protocol for interconnection between devices and services without blind spots based on LTE connection, and the fixed uses the LoRaWAN protocol with low power and wide communication range. Not only fine dust, but also temperature, humidity, atmospheric pressure, volatile organic compounds (VOC), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and noise data related to daily life were collected. The collected sensor values were managed using the common API provided by oneM2M through the agent and oneM2M IPE, and it was designed into four resource types: AE and container. Six functions of operability, flexibility, convenience, safety, reusability, and scalability were analyzed through the fine dust measurement platform design.