• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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• pp.415-426
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• 1997

Some arguments have been about over the representativeness of government-run air quality monitoring stations among scholars and non-governmental organizations (NGOs). However, it is not a simple problem to move monitoring stations because of continuity of data and high cost. So it is necessary to complement the monitoring data if it do not represent the ambient air quality properly. The purpose of this study was to evaluate the representativeness of some monitoring stations using passive $NO_2$ samplers and to find a complementary method from linear regression. Two stations were chosen for the evaluation: Shinlim Station was one of the most controversial stations in Seoul and Banpo Station had the best reputation. Air qualities were surveyed at seven points around each monitoring station with consideration of land use and distance. The ratios of the average $NO_2$ levels of the areas to these at the monitoring stations were 1.59 for Shinlim Station and 1.03 for Banpo Station. The differences between the average $NO_2$ levels and those at the monitoring stations were 10.75 ppb for Shilim Station and 0.34 ppb for Banpo Station. The correlation coefficients between the two levels were 0.7668 for Shinlim and 0.7662 for Banpo. The average coefficients of determination $(R^2)$ were 0.61 for Shinlim and 0.61 for Banpo. The Shinlim Station could not represent the air quality of Shinlim-Dong good because it is located in a green area at an outskirt of Shinlim-Dong. But the Banpo Station located in a central residential area of Banpo-Dong showed a fair representativeness. However, air quality turned out to be different with land use such as residential area, green area or road: the air quality data from a monitoring station located at a certain land use should not be interpreted as representing the air quality at any sites around the station. Equations to predict the average $NO_2$ levels of each area from the data from the monitoring stations were presented based on linear regression.

• 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.

• Journal of Environmental Impact Assessment
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• v.20 no.1
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• pp.49-59
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• 2011

The results of comparing $PM_{10}$ concentration between 'Namsan' and 'Yongsan-gu' air quality monitoring stations show similar values with averaged concentration in the whole Seoul. The correlation factors in both sites were 0.865, 0.828 in 2005, 2006, respectively. For 'Bukhansan' and 'Gangbuk-gu' air quality monitoring stations, different from the results mentioned above, they showed clear differences as altitude changes. PM10 concentration in 'Bukhansan' monitoring stations was 10 ${\mu}g/m^3$ lower than 'Gangbuk-gu' monitoring station which is located near the ground. Also, averaged PM10 concentration in 'Bukhansan' and 'Gangbuk-gu' monitoring stations was lower than that in the whole Seoul. When comparing $NO_2$ concentration between 'Namsan' and 'Yongsan-gu' monitoring stations, $NO_2$ concentration in 'Namsan' monitoring station was lower than 'Yongsan-gu' monitoring station. For $NO_2$ concentration in 'Bukhansan', 'Gangbuk-gu' and 'the whole Seoul', there were the same pattern in 'Gangbuk-gu' and the 'the whole Seoul' and low values in 'Bukhansan' monitoring station. The correlation factors of $NO_2$ concentration in 'Bukhansan' and 'Gangbukgu' was 0.525, 0.549 in 2005, 2006, respectively, which stands for low correlationship.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.5
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• pp.526-538
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• 2007

Since air quality monitoring data sets are important base for developing of air quality management strategies including policy making and policy performance assessment, the environmental protection authorities need to organize and operate monitoring network properly. Air quality monitoring network of Busan, consisting of 18 stations, was allocated under unscientific and irrational principles. Thus the current state of air quality monitoring networks was reassessed the effect and appropriateness of monitoring objectives such as population protection and sources surveillance. In the process of the reassessment, a GIS-based decision support system was constructed and used to simulate air quality over complex terrain and to conduct optimization analysis for air quality monitoring network with multi-objective. The maximization of protection capability for population appears to be the most effective and principal objective among various objectives. The relocation of current monitoring stations through optimization analysis of multi-objective appears to be better than the network building for maximization of population protection capability. The decision support system developed in this study on the basis of GIS-based database appear to be useful for the environmental protection authorities to plan and manage air quality monitoring network over complex terrain.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1931-1938
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• 2012

This study evaluated whether the installed location of air quality monitoring stations is at an optimal level in an effort to improve the health and environmental quality of the surrounding areas of the Pohang Steel Complex. As a result of analyzing the atmospheric flow field, it was found that the location of air quality monitoring stations was acceptable in case of Daesong-myeon(The 1st Division of Local Wind Sector) and Jukdo-dong(The 3rd Division of Local Wind Sector). However, the air quality monitoring stations installed at Daedo-dong and Jukdo-dong is judged to have made an overlapped measurement because the stations existed at the Division of the same Wind Sector. Accordingly, this study suggests that the further air quality monitoring stations should be additionally installed at Buk-gu areas of Pohang where more than 50% of the population of Pohang is living presently. As a result of the analysis of air contaminant concentration distribution, the Jangheung-dong area showed higher concentration distribution than other areas in case of $PM_{10}$ while the Daesong-myeon area showed a comparatively higher concentration distribution in case of $O_3$. Conclusively, this study indicates that it is high time to prepare an aggressive management of $PM_{10}$ and $O_3$ which causes a harmful impact on the life and health of the residents of the target areas.

• 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 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.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.205-208
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• 2008

This article presents a methodology for the monitoring of air pollution. All over the world, the interest in the environment has been continuously increasing. Unfortunately, much of this interest is due to emerging problems, such as the greenhouse effect and climate change. For this reason, research into carbon dioxide, which causes the greenhouse effect, is progressing rapidly. This article presents a method of measuring the level of carbon dioxide and other substances in the air through the utilization of mobile-networking base stations and measured data. First of all, sensors are attached at the appropriate position of the mobile-networking base stations. These sensors will measure the air quality in their respective positions, and send sensor data to an urban management center via network gateways and data-collecting systems. The measured data can be used for various purposes. In general, it can be used to measure the air quality, which can then be used as a basis for urban planning. The method described herein utilizes airpollution sensors that are attached to the base stations in different locations and at varying heights. The data obtained hereby will be applicable in many fields. At this time this is simply a methodology, however we hope that it will lead to a practical application.

• Asian Journal of Atmospheric Environment
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• v.7 no.4
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• pp.177-190
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• 2013

Air pollution trends in Japan between 1970 and 2012 were analyzed, and the impact of air pollution countermeasures was evaluated. Concentrations of CO decreased from 1970 to 2012, and in 2012, the Japanese environmental quality standard (EQS) for CO was satisfied. Concentrations of $SO_2$ dropped markedly in the 1970s, owing to use of desulfurization technologies and low-sulfur heavy oil. Major reductions in the sulfur content of diesel fuel in the 1990s resulted in further decreases of $SO_2$ levels. In 2012, the EQS for $SO_2$ was satisfied at most air quality monitoring stations. Concentrations of $NO_2$ decreased from 1970 to 1985, but increased from 1985 to 1995. After 1995, $NO_2$ concentrations decreased, especially after 2006. In 2012, the EQS for $NO_2$ was satisfied at most air quality monitoring stations, except those alongside roads. The annual mean for the daily maximum concentrations of photochemical oxidants (OX) increased from 1980 to 2010, but after 2006, the $98^{th}$ percentile values of the OX concentrations decreased. In 2012, the EQS for OX was not satisfied at most air quality monitoring stations. Non-methane hydrocarbon (NMHC) concentrations generally decreased from 1976 to 2012. In 2011, NMHC concentrations near roads and in the general environment were nearly the same. The concentration of suspended particulate matter (SPM) generally decreased. In 2011, the EQS for SPM was satisfied at 69.2% of ambient air monitoring stations, and 72.9% of roadside air-monitoring stations. Impacts from mineral dust from continental Asia were especially pronounced in the western part of Japan in spring, and year-round variation was large. The concentration of $PM_{2.5}$ generally decreased, but the EQS for $PM_{2.5}$ is still not satisfied. The air pollution trends were closely synchronized with promulgation of regulations designed to limit pollutant emissions. Trans-boundary OX and $PM_{2.5}$ has become a big issue which contains global warming chemical species such as ozone and black carbon (so called SLCP: Short Lived Climate Pollutants). Cobeneficial reduction approach for these pollutants will be important to improve both in regional and global atmospheric environmental conditions.