• Journal of Environmental Impact Assessment
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• v.5 no.1
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• pp.79-85
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• 1996

Simultaneous monitoring in many locations is necessary to evaluate the air quality and analyze future trend of a city, For this purpose, it is essential to install air pollution monitoring network. The first automatic air pollution monitoring network was introduced Seoul in 1973. As of 1995, 20 monitoring stations are now in operation. Concerning the management of the air pollution monitoring network, there was some argument among the relavant scholars, non-governmental organization(NGO) and the government organization. So far, there was no extensive evaluation and analysis about the network. The purpose of this study was to evaluate the representativeness of air quality monitoring network through actual measurement of the concentration of the air pollutant. The concentration of NOx was extensively measured widely in Seoul area three times using the TEA simple measuring technique. Even the judgement level for the area representativeness was lowered to 80%, Ssangmun-dong monitoring station tend to overestimate the pollutant concentration of the covered area. While, Sinlimdong monitoring station tend to underestimate the pollutant concentration of the covered area.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.439-441
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• 2007

The seoul metropolitan subway has installed 8 lines and about 500 stations to transport 5 million passengers everyday. The underground air pollution level in the subway stations is very severe status, which is very harmful to the commutators and its personals. Although subway roles as such a massive and huge transportation system, the subway doesn't adapt yet any real-time air monitoring system. They have only some hand-held type detector equipments for monitoring air pollution. Therefore subway passengers are exposed to the harmful air pollution environment. The most harmful environmental parameters among the air pollution are known as the dust and sound noise dB level in the subway station. Because the dust is consisted of very small particles, we can't see them easily in dark condition on the platform, but it is very harmful. The monitoring system for air pollution is developed using embedded system attached with 6 different environmental sensors. This system monitors air pollution of dust sound noise, gas, temperature, humidity, inflammable gas, toxic gas in the subway ?station. The sensor unit of the ARM-CPU board and sensor transmits real time environmental data to the main server using Zigbee wireless communication module and TCP/IP network. The main control server receives and displays the real-time environmental data, and it send alarms to the personals when high level value.

• Journal of Environmental Science International
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• v.15 no.8
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• pp.737-744
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• 2006

Present study was designed to characterize the concentrations of major roadside air pollutants in Daegu and to compare with those of Seoul and Busan. Evaluated were the exceedance frequence of mean concentrations of target compounds(CO, NO$_2$, O$_3$, PM$_{10}$, SO$_2$) and the relationship for time variation. Two air pollution monitoring stations(one roadside station and one residential station) in Daegu were selected for this study. In addition, one roadside monitoring station from each of Seoul and Busan was chosen for the comparison of Daegu monitoring stations. The data analyzed in the current study were collected from 1998 to 2000 by Daegu Regional Environmental Management Office. The roadside concentrations of NO2 and PM to and the exceedance frequency of ambient air standard levels in Daegu were higher than those of Seoul and Busan. Except 03, the roadside concentrations of all target compounds showed following three distinguished patterns; first, possibly due to increased traffic density, the concentrations increased from 0500 to 0900(LST), second, the concentrations decreased from 0900 to 1700(LST) possibly due to the increased wind velocity and decreased traffic density, and finally, increased traffic density, the concentrations increased again from 1700 to 2100(LST). An implication was that major air pollution sources shifted from residential area to road-area during rush hours.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.5
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• pp.583-591
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• 2004

In this study, methodologies for the rational organization of air pollution monitoring network were examined by understanding the characteristics of temporal and spatial distribution of secondary air pollution, whose significance would increase hereafter. The data on $O_3$ and $NO_2$ concentrations during high ozone period in 1998~1999 recorded at the nine air pollution monitoring station in Busan were analysed using principal component analysis (PCA) and cumulative semivariogram. It was found that the ozone concentration was deeply associated with the daily emission characteristics or the $O_3$ precusors, and nitrogen dioxide concentration largely depends on the emission strength of regional sources. According to the spatial distribution analysis of ozone and nitrogen dioxide in Busan using cumulative semivariograms, the number of monitoring stations for the secondary air pollution can be reduced in east-west direction, but reinforced in north-south direction to explain the spacial variability. More scientific and rational relocation of air pollution monitoring network in Busan would be needed to investigate pollution status accurately and to plan and implement the pollution reduction policies effectively.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2005.11a
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• pp.308-309
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• 2005

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.4
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• pp.405-420
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• 2006

This study was conducted to understand the change of spatial environmental factors including populations, air pollution source and land-use in Busan, during the period of 1995 and 2004. Firstly, the grids (5 km $\times$ 5 km) were divided using the TM coordinates of Busan and the statistical data of populations and land-use were marked on each grid during studying period. Secondly, the SO$_2$, NO$_2$ and O$_3$ concentrations of areas where air quality monitoring station was not established were estimated on the basis of these air pollutants measured at close air quality monitoring station by kriging method. In order to understand spatial change of air pollution and to investigate duplication and reduction of existing stations, semivariogram, correlation and cluster analysis were carried out. This study showed that the population increased in 2004 only on 8 grids compared to in 1995. The spatial change of SO$_2$, NO$_2$ and O$_3$ was investigated by semivariogram in Busan area. As the results of semivariogram, the spatial change of 502 become smaller and simpler, while that of NO2,03 become larger and more complex in 2004 than in 1995, According to the result of correlation and cluster analysis, the reduction of measurement item or the relocation of air quality monitoring station can be needed in the high dense grid area.

• Journal of Environmental Science International
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• v.25 no.5
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• pp.673-681
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• 2016

The adequacy of urban air quality monitoring networks in the largest metropolitan city, Seoul was evaluated using multivariate analysis for $SO_2$, $NO_2$, CO, PM10, and $O_3$. Through cluster analysis for 5 air pollutants concentrations, existing monitoring stations are seen to be clustered mostly by geographical locations of the eight zones in Seoul. And the stations included in the same cluster are redundantly monitoring air pollutants exhibiting similar atmospheric behavior, thus it can be seen that they are being operated inefficiently. Because monitoring stations groups representing redudancy were different depending on measurement items and several pollutants are being measured at the same time in each air monitoring station, it is seemed to be not easy to integrate or transmigrate stations. But it may be proposed as follows : the redundant stations can be integrated or transmigrated based on ozone of which measures are increasing in recent years and alternatively the remaining pollutants other than the pollutant exhibiting similar atmospheric behavior with nearby station's can be measured. So it is considered to be able to operate air quality monitoring networks effectively and economically in order to improve air quality.

• Particle and aerosol research
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• v.10 no.2
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• pp.61-75
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• 2014

Five on-road measurements were made using a mobile laboratory (ML) to characterize spatial and temporal air pollutant distributions over roads around a day-care center in urban area on 30 August 2013. Fixed monitoring was also done near the day-care center using the ML during the periods between on-road measurements. On-road air pollution monitoring route was classified into seven sections and three zones to identify severe polluted roads among many roads having different traffic volumes and directions. Typical pollutants emitted from vehicles such as $NO_x$, black carbon, particle-bound polycyclic aromatic hydrocarbons, and submicron particles including nanoparticles were monitored using real-time instruments. Peak concentration episodes were frequently observed during the on-road measurements and most peaks were simultaneously monitored at four pollutants. Colored on-road air pollution map for each pollutant provides an insight on spatial air pollution distribution, showing heavily polluted roads and sections. Average on-road $NO_x$ concentration of each run was similar to that monitored at the nearest roadside air monitoring station.

• Journal of Environmental Science International
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• v.13 no.1
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• pp.27-36
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• 2004

Present study analyzed the temporal and spatial characteristics of PM10 pollution in Metropolitan Daegu area based on air pollution monitoring station data and measurements of PM10 concentrations in background area in order to provide essential data for efficient PM10 pollution management. The significant variation of spatial and temporal PM10 concentrations in Daegu area was observed during the study years. The highest maximum PM10 concentration(332 $\mu\textrm{g}$/㎥), average concentration(88 $\mu\textrm{g}$/㎥) and frequency exceeding PM10 daily standard(150 $\mu\textrm{g}$/㎥) were all observed in Namsandong located near a major roadway. The hourly and weekly variations of PM10 concentrations had different pattern for the measurement sites. The monthly and seasonal concentrations exhibited a notable characteristic： the maximum concentration was obtained in spring season, most likely due to Yellow sand effects. Furthermore, this temporal variation of PM10 pollution varied with study site. Meanwhile, the PM10 values measured at the monitoring site, Manchondong, were comparable with those of a control site. The average PM10 concentration ranged from 23 $\mu\textrm{g}$/㎥ to 115 $\mu\textrm{g}$/㎥ with a mean value of 53 $\mu\textrm{g}$/㎥ in the former site and from 22 $\mu\textrm{g}$/㎥ to 91 $\mu\textrm{g}$/㎥ with a mean value of 45 $\mu\textrm{g}$/㎥ in the latter site.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2010.04a
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• pp.287-288
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• 2010