• Proceedings of the Korean Environmental Sciences Society Conference
• /
• 2006.11a
• /
• pp.122-123
• /
• 2006

본 연구에서는 2001년부터 2005년까지의 최근 5년간의 대구시 보건환경연구원의 대기질 자동측정망 자료와 대구기상대의 기상자료를 이용하여 통계적 방법을 이용하여 대구시 주거지역의 오존농도를 평가하였다. 분석기간은 2001년부터 2005년까지 고농도 오존일이 가장 많이 발생한 5, 6월을 대상으로 하여, 오존농도와 대기오염물질 및 기상요소와의 상관관계분석과 교차상관관계 분석을 실시하였다. 대구지역의 오존농도는 측정지점별로 약간의 차이는 있지만, 기온 및 일사량이 증가하는 하절기에 증가하고, 동절기에 감소하는 전형적인 패턴을 보여주었다. 분석기간 중 오존최고농도는 상관관계분석 결과 고농도 오존에 영향을 주는 인자로 대기오염물질로는 $NO_2$, NO 그리고 기상요소로는 온도, 상대습도, 일사량으로 나타났다. 교차상관관계분석 결과 NO2, NO, 온도와 상대습도는 0시간 차이에서 가장 높은 상관계수를 나타내었으며, 일사량의 경우 오존농도가 최고치를 나타낼 때보다 -2시간 차이에서 가장 높은 상관계수를 나타내었다.

• Spatial Information Research
• /
• v.6 no.1
• /
• pp.65-76
• /
• 1998

Air contaminant density must be inferred exactly to manage air pollution. Each land use of air pollution source is duplicated in the existing air contaminant distribution because the resolution of the land use map is low. The purpose of this study is to understand how the land use map is used to determine effectively in the distribution calculation of the emission volume and the inference of air contaminant density, as it is made in a high resolution. The major findings are as follows : In this study, as to making a high resolution($28.5m{\times}28.5m$) map of land use with GIS, each air pollution source is not duplicated spatially and land use can be reflected effectively. In Seoul, each air contaminant density was inferred (using a TCM-2 model) with the existing distribution map of emission volume, whose resolution is $1km{\times}1km$, and the new distribution map of emission volume, whose resolution is $28.5km{\times}28.5km$. According to the result, the inference value of the new distribution map was more similar to the actual value of an automatic survey network.

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

• Spatial Information Research
• /
• v.20 no.2
• /
• pp.25-34
• /
• 2012

Air quality in Daegu area is lower compared to many other cities, since Daegu is a basin surrounded by mountains. Accordingly, the present study investigated the location of carbon monoxide(CO) monitoring stations for systematic CO pollution management on the basis of the CO emission distribution in Daegu area. In order to achieve this purpose, the location of CO monitoring stations, which can be used for the establishment of CO management, were assessed. Emission map in Daegu area was prepared using numerical map and Clean Air Policy Support System(CAPSS) data supplied by the M inistry of Environment. Average emissions were estimated by dividing emission sources into four subgroups(roadway, apartment, industry, and municipal incineration facility) according to legal division. The CO emission intensities were subdivided into 10, which a high number represents a high emission intensity, and the current monitoring stations were evaluated for the determination of their steps in CO emission intensities. As a result, additional installation of monitoring stations were suggested for the high CO emission areas rather than the low CO emission areas. A systematic CO management strategy would be established by the supplying various principle CO data when the CO monitoring stations are additionally installed at Kukwudong and other six sites on the basis of analyses of data obtained from 1999 to 2007.

• Journal of Environmental Science International
• /
• v.20 no.1
• /
• pp.81-91
• /
• 2011

Air quality monitoring networks are very important facilities to manage urban air pollution control and to set up an environmental policy. Since air quality monitoring network of Daegu was allocated from 1980s to mid-90s, there is need to reevaluate it and relocated its site. This study was evaluated the position of Daegu air quality monitoring station by unit environmental sensitivity index, grid emission rate, CAI (Comprehensive Air-quality Index) point. The investigation domain covered an area of 16 $\times$ 24 km centered at the metropolitan area of Daegu with grid spacing of 2 km. The location of alternative air quality monitoring networks was selected through optimization and quintiles analysis of total score. The result showed that all things considered, new air quality monitoring network need to install grid numbers 10, 28, 36, 37, 46. We also recommand three scenarios of alternative air quality monitoring network when considering unit environmental sensitivity index, emission rate and CAI point.

• Journal of the Korean earth science society
• /
• v.24 no.3
• /
• pp.190-204
• /
• 2003

The PM (particulate matter) concentration data sets exceeding the Daily Air Quality Guidance Levels (i.e., established by the Korean Ministry of Environment) were selected from 31 air qality monitoring stations in Seoul from 1990 to 2000. (For reference, the 24hr environmental standard values of PM$_{10}$ and TSP are 150 and 300${\mu}$g/m$^{3}$, respectively.) When the data sets were compared between land use types, both PM fractions were exceeded most frequently in residential areas. However, the highest TSP concentration was measured at industrial areas (351.0${\pm}$35.9${\mu}$g m$^{3}$), while the highest PM$_{10}$ concentration was measured in residential areas (182.9${\pm}$42.4${\mu}$g m$^{3}$). When the temporal distribution patterns of the exceedance data sets were compared to those measured routinely (without any discrimination based on exceedance criteria), large differences were present. It was demonstrated that the occurrences of exceedance data sets increased rather significantly in recent years.

• Journal of Korean Society for Atmospheric Environment
• /
• v.13 no.6
• /
• pp.415-426
• /
• 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 the Korean earth science society
• /
• v.40 no.6
• /
• pp.549-560
• /
• 2019

The effects of the coal-fired power plant emissions, as the biggest point source of air pollutants, on spatiotemporal surface air pollution over the remote area are investigated in this study, based on a set of date selection and statistical technique to consider meteorological and geographical effects in the emission-concentration (source-receptor) relationship. We here proposed the sophisticated technique of data processing to separate and quantify the effects. The data technique comprises a set of data selection and statistical analysis procedure that include data selection criteria depending on meteorological conditions and statistical methods such as Kolmogorov-Zurbenko filter (K-Z filter) and empirical orthogonal function (EOF) analysis. The data selection procedure is important for filtering measurement data to consider the meteorological and geographical effects on the emission-concentration relationship. Together with meteorological data from the new high resolution ECMWF reanalysis 5 (ERA5) and the Korea Meteorological Administration automated surface observing system, air pollutant emission data from the telemonitoring system (TMS) of Dangjin and Taean power plants as well as spatio-temporal air pollutant concentrations from the air quality monitoring system are used for 4 years period of 2014-2017. Since all the data used in this study have the temporal resolution of 1 hour, the first EOF mode of spatio-temporal changes in air pollutant concentrations over the Seoul metropolitan area (SMA) due to power plant emission have been analyzed to explain over 97% of total variability under favorable meteorological conditions. It is concluded that SO₂, NO₂, and PM₁₀ concentrations over the SMA would be decreased by 0.468, 1.050 ppb, and 2.045 ㎍ m^-3 respectively if SO₂, NO₂, and TSP emissions from Dangjin power plant were reduced by 10%. In the same way, the 10% emission reduction in Taean power plant emissions would cause SO₂, NO₂, and PM₁₀ decreased by 0.284, 0.842 ppb, and 1.230 ㎍ m^-3 over the SMA respectively. Emissions from Dangjin power plant affect air pollution over the SMA in higher amount, but with lower R value, than those of Taean under the same meteorological condition.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.6 no.1
• /
• pp.38-48
• /
• 2004

Tropospheric ozone data in Korea for 1998-2002 were analyzed to assess the impact on vegetation. SUM06(sum of hourly concentrations at or above 0.06 ppm) and AOT40(accumulated exposure over a threshold of 40 ppb), widely used as ozone indices in the U.S. and Europe, were calculated based on hourly ozone concentration in 612 areas during 1998-2002 in Korea. SUM06 of the highest 30 areas were 5-12 ppm/hr which were almost the same levels of the U.S. average, and a crop loss of 5% would be expected. Ozone pollution in Seoul during 1998-2002 had decreased compared to that for 1990-97 except in the Northern area; however, ozone pollution in Kyunggi during 1998-2002 had been increased twice compare to the previous 5 years. Korea was divided into four regions: Seoul Metropolitan area, Jungbu, Honam, and Youngnam. Ozone pollution in the Seoul Metropolitan area was much higher during 1998-2000 than the other areas, but ozone pollution during 2001-2002 was almost the same in all four regions. Chunnam-Kwangyang na Kyungbuk-Gumi, famous industrial complexes in southern Korea, were significant ozone pollution areas. However, other industrial complexes, such as Incheon, Ulsan, and Kyunggi-Sihwa, were not polluted compared to their neighbors. Comparing all ozone indices, SUM06(yr), SUM06(3mon), AOT40(yr), AOT40(3mon), number of hours exceeding 100 ppb, 95 percentile, 99 percentile, and maximum concentration, it was determined reasonable to use SUM06(3mon), AOT40(3mon) and number of hours exceeding 100 ppb for evaluation of the chronic impact of ozone on vegetation.

• Journal of the Korean earth science society
• /
• v.23 no.8
• /
• pp.683-696
• /
• 2002

In this work. we investigated the ozone data sets that exceeded ambient air quality standards from 31 air quality monitoring stations dispersed across the Seoul metropolitan city during the period covering 1990 and 2000. To specifically describe spatial dependency of high level O$_3$ occurrence, we grouped our data into four different geographical ozone exceedance is much longer in SW than the other three sectors. When we compared the exceedance data in terms of occurrence frequency, the month of maximum frequency differed slightly among different sectors. Examination of long-term exceedance trend indicated that its frequency increased continuously from all sectors over the past years, although slightly opposite patterns existed in their absolute values. Most importantly, its peak occurrence frequency seemed to center in very recent years such as 1998 (NE sector) and 2000 (ail pattern sectors except NE). Consequently, we were able to describe the existence of certain patterns of ozone exceedance data sets in terms of both temporal and spatial scales.