• Journal of Environmental Science International
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• v.26 no.8
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• pp.927-938
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• 2017

This study was conducted to determine correlations and similarity between the ozone and $PM_{10}$ data of 19 air quality monitoring stations in Busan from 2013 to 2016, using correlation and cluster analyses. Ozone concentrations ranged from $0.0278{\pm}0.0148ppm$ at Gwangbok to $0.0378{\pm}0.017ppm$ at Taejongdae and were high in suburban areas, such as Yongsuri and Gijang, as well as in coastal areas, such as Jaw, Gwangan, Taejongdae and Noksan. $PM_{10}$ concentrations ranged from $37.2{\pm}25.0ug/m^3$ at Gijang to $58.3{\pm}32.2ug/m^3$ at and Jangrim. $PM_{10}$ concentrations were high in the west, exceeding the annual ambient air quality standard of $50ug/m^3$. Positive correlations were observed for ozone at most stations, ranging from 0.61 between Taejongdae and Sujeong to 0.92 between Bugok and Myeongjang. The correlation coefficients of $PM_{10}$ between stations ranged from 0.62 between Jangrim and Jaw to 0.9 between Gwangbok and Sujeong. Yeonsan, Daeyeon, and Myeongjang were highly correlated with other stations, so they needed to be reviewed for redundancy. Ozone monitoring stations were initially divided into two sections, north-western areas and suburban-coastal areas. The suburban-coastal areas were subsequently divided into three sections. $PM_{10}$ monitoring stations were initially divided into western and remaining areas, and then the remaining areas were subsequently divided into three sections.

• 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.

• Environmental Engineering Research
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• v.20 no.3
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• pp.260-267
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• 2015

The $PM_{10}$, $SO_2$ and $NO_2$ mass concentrations were obtained over five years from monitoring stations across Nanchong, a southwest city in China. Changes in urban air quality over time, as well as the factors influencing that change, were evaluated based on air pollutant concentrations, the Air Pollution Index (API), and the Comprehensive Pollution Index (P). The results showed that the total annual mean $PM_{10}$, $SO_2$ and $NO_2$ concentrations over the five years studied were $61.1{\pm}1.1$, $45.0{\pm}3.9$ and $34.9{\pm}4.9{\mu}g{\cdot}m^{-3}$, respectively. The annual mean concentrations displayed a generally decreasing trend; lower than the annual mean second-level air quality limit. Meanwhile, the annual mean API values were in a small range of 52-53, the air quality levels were grade II, and P values were 1.06-1.21 less than the slight level ($P{\leq}1.31$). Total monthly mean $PM_{10}$, $SO_2$, $NO_2$ concentrations, and API and P values were consistently higher in winter and spring than during autumn and summer. The results of a correlation analysis showed that temperature and pressure were the major meteorological factors influencing pollution levels. Pollution sources included industrial coal and straw burning, automobiles exhaust and road dust, fireworks, and dust storms.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.4
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• pp.439-446
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• 2013

In this research, the present standard analytical methods for the monitoring of air pollution levels established by the Korean Ministry of Environment (KMOE) were examined in reference to the recent outputs of several research projects conducted for their amendments. The evaluation of the two criterion methods between the main (the present guideline) and reference methods (the proposed alternate guideline) was made in terms of authenticity and reliability of the quality assurance (QA) and of compatibility of methods. The results of this comparative evaluation are presented for the analysis of both ambient air and source samples. Based on this analysis, we propose a new direction for the future amendment.

• Journal of Environmental Impact Assessment
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• v.7 no.2
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• pp.83-88
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• 1998

Filter badge type sampler has not been widely used to evaluate air quality over large cities in Korea while it can be successfully used for multi-point sampling and analysis. We evaluated the passive sampler as a new tool to monitor air quality over large cities. We latticed Metropolitan Seoul into $2{\times}2Km$ to give 136 points. $NO_2$ concentrations were measured at all the points in the Spring and Summer of 1997. According to the passive sampler data, natural green zones generally recorded lower $NO_2$ concentrations than major streets and traffic congestion areas. Passive samplers with abundant 136 points gave more detailed picture of $NO_2$ distribution while auto-monitoring network did not clearly provide the characteristics of local land use. Also, passive samplers gave 15% higher values than auto-monitoring network. The correlation between the two values appears very high judging from the regression slope of 0.92 and correlation coefficient of 0.91. This study clearly demonstrates the effectiveness of the passive sampler as a tool to monitor air quality over large cities.

• Journal of Environmental Health Sciences
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• v.39 no.1
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• pp.99-103
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• 2013

Objectives: This paper was prepared in memory of Jerry Sherwood, who provided a significant contribution to the Korean environmental and occupational health fields. Methods: Rare air quality data in Seoul were gathered by Jerry Sherwood when he visited Korea in the early 1980s. $SO_2$ and TPM concentrations were measured. These air quality measurements were based on ambient stationary monitoring and indoor air quality monitoring in various locations. Measurement during transportation was also applied. Results: Ambient $SO_2$ and TPM concentrations in Seoul were very high in the early 1980s. Ambient $SO_2$ concentrations were higher at nighttime. While ambient $SO_2$ concentrations varied by location, the Guro industrial area showed high levels. When indoor sources were presented, indoor $SO_2$ concentration was higher than outdoor level. Coal briquettes were closely associated with high indoor $SO_2$ concentration. Conclusion: This paper provided valuable historical information of air quality in Seoul.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.449-452
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• 2005

For home networking system with a function of air quality monitoring, a wireless sensor module with several air quality monitoring sensors was developed for indoor environment monitoring system in home networking. The module has various enlargements for various kinds of sensors such as humidity sensor, temperature sensor, CO2 sensor, flying dust sensor, and etc. The developed wireless module is very convenient to be installed on the wall of a room or office, and the sensors in the module can be easily replaced due to well designed module structure and RF connection method. To reduce the system cost, only one RF transmission block was used for sensors' signal transmission to 8051 microcontroller board in time sharing method. In this home networking system, various indoor environmental parameters could be monitored in real time from RF wireless sensor module. Indoor vision was transferred to client PC or PDA from surveillance camera installed indoor or desired site. Web server using Oracle DB was used for saving the visions by web-camera and various data from wireless sensor module.

• Advances in environmental research
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• v.6 no.2
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• pp.83-94
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• 2017

Air quality planning and management requires accurate and consistent records of the air quality parameters. Limited number of monitoring stations and inconsistent measurements of the air quality parameters is a very serious problem in many parts of India. It becomes difficult for the authorities to plan proactive measures with such a limited data. Estimation models can be developed using soft computing techniques considering the physics behind pollution dispersion as they can work very well with limited data. They are more realistic and can present the complete picture about the air quality. In the present case study spatio-temporal models using Linear Genetic Programming (LGP) have been developed for estimation of air quality parameters. The air quality data from four monitoring stations of an Indian city has been used and LGP models have been developed to estimate pollutant concentration of the fifth station. Three types of models are developed. In the first type, models are developed considering only the pollutant concentrations at the neighboring stations without considering the effect of distance between the stations as well the significance of the prevailing wind direction. Second type of models are distance based models based on the hypothesis that there will be atmospheric interactions between the two stations under consideration and the effect increases with decrease in the distance between the two. In third type the effect of the prevailing wind direction is also considered in choosing the input stations in wind and distance based models. Models are evaluated using Band Error and it was observed that majority of the errors are in +/-1 band.

• Journal of Environmental Health Sciences
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• v.43 no.4
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• pp.267-272
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• 2017

Objectives: The purposes of the study were to analyze the temporal variation of carbon dioxide ($CO_2$) and particulate matter (PM) in daycare centers and evaluate the appropriateness of the official test method of one-time measurement. Methods: Indoor air quality in 46 daycare centers in the Seoul Metropolitan Area was measured as specified in the official test method of Indoor Air Quality Management law. In addition, indoor air quality in the 46 daycare centers was measured over 37 days using a real-time monitor (AirGuard K). Results: The daily means of $CO_2$ and PM in the 46 daycare centers were $1042.74{\pm}134.45ppm$ and $67.60{\pm}18.25{\mu}g/m^3$, respectively. Indoor air quality in the daycare centers showed significant temporal fluctuation. Measurements for single days were significantly different from the 37-day average exposure. Relative error of short term exposure decreased with an increase in the number of sampling days. The noncompliance rate for $CO_2$ using the official testing method was 2.17%, and none exceeded the $PM_{10}$ standard of $100{\mu}g/m^3$. With monitoring over 37 days, the daily noncompliance rate for $CO_2$ was 50.4% and the daily noncompliance rate for PM was 13.8%. Conclusions: When the official test method evaluates the indoor air at daycare centers one day per year, the results may not represent actual indoor air quality over a longer period of time. Real-time monitoring devices could be an alternative for managing indoor air quality.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.556-559
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• 2007

The Urban Environmental Quality (UEQ) indicates a complex and various parameters resulting from both human and natural factors in an urban area. Vegetation, climate, air quality, and the urban infrastructure may interact to produce effects in an urban area. There are relationships among air pollution, vegetation, and degrading environmental the urban heat island (UHI) effect. This study investigates the application of multi-spectral remote sensing data from the Landsat ETM and TM sensors for the mapping of air quality and UHI intensity in Seoul from 2000 to 2006 in fine resolution (30m) using the emissivity-fusion method. The Haze Optimized Transform (HOT) correction approach has been adopted for atmospheric correction on all bands except thermal band. The general UHI values (${\Delta}(T_{urban}-T_{rural})$) are 8.45 (2000), 9.14 (2001), 8.61 (2002), and $8.41^{\circ}C$ (2006), respectively. Although the UHI values are similar during these years, the spatial coverage of "hot" surface temperature (>$24^{\circ}C$) significantly increased from 2000 to 2006 due to the rapid urban development. Furthermore, high correlations between vegetation index and land surface temperature were achieved with a correlation coefficients of 0.85 (2000), 0.81 (2001), 0.84(2002), and 0.89 (2006), respectively. Air quality is shown to be an important factor in the spatial variation of UEQ. Based on the quantifiable fine resolution satellite image parameters, UEQ can promote the understanding of the complex and dynamic factors controlling urban environment.