• 한국환경과학회지
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• 제12권10호
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• pp.1033-1041
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• 2003

Hourly data of PM10 concentration collected from nine automatic air quality monitoring stations in Busan from 1999 to 2002 were analyzed to evaluate the spatio-temporal variation and meteorological characteristics of PM10 episodes in Busan metropolitan area. Mean concentrations ranged from 47$\mu\textrm{g}$/㎥ to 77$\mu\textrm{g}$/㎥. For most stations, mean seasonal hourly concentrations are lowest in summer and highest in spring. PM10 episode above daily mean standard(150$\mu\textrm{g}$/㎥) exhibited a maximum frequency at Gamjeondong and a minimum at Dongsamdong, and a maximum in March and a minimum in July and August. The diurnal variation of PM10 episode days is strongly influenced by traffic loads and meteorological conditions.

• Asian Pacific Journal of Cancer Prevention
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• 제14권3호
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• pp.1879-1887
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• 2013

To investigate the level of genotoxicity over Bangkok atmosphere, $PM_{10}$ samples were collected at the Klongchan Housing Authority (KHA), Nonsree High School (NHS), Watsing High School (WHS), Electricity Generating Authority of Thailand (EGAT), Chokchai 4 Police Station (CPS), Dindaeng Housing Authority (DHA) and Badindecha High School (BHS). For all monitoring stations, each sample covered a period of 24 hours taken at a normal weekday every month from January-December 2006 forming a database of 84 individual air samples (i.e. $12{\times}7=84$). Atmospheric concentrations of low molecular weight PAHs (i.e. phenanthrene, anthracene, pyrene and fluoranthene) were measured in $PM_{10}$ at seven observatory sites operated by the pollution control department of Thailand (PCD). The mutagenicity of extracts of the samples was compared in Salmonella according to standard Ames test method. The dependence of the effects on sampling time and on sampling location was investigated with the aid of a calculation of mutagenic index (MI). This MI was used to estimate the increase in mutagenicity above background levels (i.e. negative control) at the seven monitoring sites in urban area of Bangkok due to anthropogenic emissions within that area. Applications of the AMES method showed that the average MI of $PM_{10}$ collected at all sampling sites were $1.37{\pm}0.10$ (TA98; +S9), $1.24{\pm}0.08$ (TA98; -S9), $1.45{\pm}0.10$ (TA100; +S9) and $1.30{\pm}0.09$ (TA100; -S9) with relatively less variations. Analytical results reconfirm that the particulate PAH concentrations measured at PCD air quality monitoring stations are moderately low in comparison with previous results observed in other countries. In addition, the concept of incremental lifetime particulate matter exposure (ILPE) was employed to investigate the potential risks of exposure to particulate PAHs in Bangkok atmosphere.

• 한국대기환경학회지
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• 제26권3호
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• pp.276-285
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• 2010

Recently the Korean government has tried to cut down the $PM_{10}$ concentration by the Special Law for Air Quality Improvement. But the concentrations of $PM_{10}$ have exceeded the air quality standard at most monitoring stations. Primary $PM_{10}$ emitted from various sources and emission data have large uncertainty. The biomass burning is one of the major sources of $PM_{10}$ emission. The biomass burning is composed of wood stove usage, meat cooking and agricultural combustion etc.. Activity data and emission factors for the biomass burning are limited, and it is hard to calculate the air pollution emissions from these sources. In this study, we tried to estimate the air pollution emission from residential wood stove usage. The number of total wood stoves is estimated by the survey of wood stove manufacturer. And air pollution emission factors for the wood stove are investigated using the flue gas measurement by U.S. EPA particulate test method (Method 5G). As the results, the $PM_{10}$ and CO emission factors of wood stove are estimated as 7.7 g/kg-wood and 78.8 g/kg-wood respectively. The annual $PM_{10}$ and CO emissions from wood stove are calculated as 1,200~3,600 ton/year and 12,600~36,400 ton/year in Korea. It is confirmed that wood stove is the one of major sources of biomass burning, and the survey for activity data and the measurement for emission factors are needed for reducing the uncertainty of these emission data.

• 한국환경보건학회지
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• 제45권6호
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• pp.577-582
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• 2019

Objectives: The purpose of this survey was to assess the concentrations of heavy metals in the atmosphere of Pocheon City by measuring heavy metals in the industrial complex area and at the city air measuring station, and also to assess the degree of impact that the industrial area has on urban air quality. Methods: Sampling was carried out between February 2018 and November 2018 at two sites in the industrial complex and in the city air monitoring stations. Results: At the industrial complex in Pocheon City, air pollutant emitting businesses were emitting concentrations of fine dust (PM₁₀) between 45 and 60 ㎍/㎥ higher than in the city air. The daily maximum concentrations of lead (Pb), manganese (Mn), and cadmium (Cd) in the industrial complex are below the WHO recommendation standard (annual average), and the impact on the urban atmosphere is judged to be insignificant. Three to five percent of fine dust (PM₁₀) consists of metallic materials, and as the fine dust increased, metals were detected proportionally. Although cadmium (Cd) and beryllium (Be) were not detected in the city air in Pocheon and chromium (Cr), copper (Cu), and arsenic (As) were found to be 50 percent or less, it is deemed that copper (Cu) was detected at unusually high levels due to unknown air pollutants, which requires regular heavy metal measurement and cause verification. Conclusions: An analysis of the heavy metals in the industrial zone and the urban atmosphere in Pocheon City in this study showed that the linear relationship of heavy metals in the industrial zone, or the direct impact relationship, on the heavy metals in the urban atmosphere could not be estimated. The sampling device for equivalent assessment of particulate matter installed at air pollution monitoring stations is highly likely to be used for analysis of fine dust and heavy metals.

• 한국대기환경학회지
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• 제12권4호
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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 $CO_2$.

• 대기
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• 제34권3호
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• pp.283-304
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• 2024

This study analyzed the variability and correlation between ground-level air pollutant concentrations and the atmospheric mixing layer height using data from four types of air pollutants (PM_2.5, PM₁₀, NO₂, and O₃) collected at AirKorea monitoring stations nationwide over a five-year period (2018~2022), and aerosol backscatter data observed by the Vaisala CL31 to derive atmospheric mixing layer heights. The five-year trends and variability of ground-level air pollutant concentrations under seasonal and hourly conditions were examined, as well as the seasonal distribution and diurnal variation of the atmospheric mixing layer height. Five correlation coefficient methodologies were applied to analyze the correlations between ground-level air pollutants and atmospheric mixing layer height under various seasonal and hourly conditions, confirming the dilution effect of the atmospheric mixing layer height. The results showed that PM_2.5, PM₁₀, and NO₂ generally had negative correlations with the atmospheric mixing layer height, while O₃ showed a strong positive correlation up to an altitude of 1,200~1,500 meters, and a negative correlation beyond that altitude. It was also shown that a single high concentration event (e.g., PM₁₀) can alter the overall correlation. The correlation can also vary depending on the characteristics of the correlation coefficient methodology, highlighting the importance of applying the appropriate methodology for each case during the analysis process.

• 한국환경과학회지
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• 제24권8호
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• pp.993-1001
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• 2015

Comparing to the other air pollutants like $SO_2$, CO, the number of exceedance of the ozone national ambient air quality standard(NAAQS) and the ozone warning increased recently in Busan. The purpose of this study is to find out the preliminary symptoms for high ozone days in Busan area. In order to find out the preliminary symptoms, the hourly ozone data at air quality monitoring stations and the hourly meterological parameters at Busan regional meteorological 2007 to 2013 were used for the analysis. Averaged daily max ozone concentration was the highest(0.055 ppm) at Noksan and Youngsuri in the ozone season from 2007 to 2013. The horizontal distributions of daily max. ozone including all stations in Busan at high ozone days(the day exceeding 0.1 ppm of ozone concentration at least one station) were classified from two to five clusters by hierarchial cluster analysis. The meteorological variables showing strong correlation with daily max. ozone were the daily mean dew point temperature, averaged total insolation, the daily mean relative humidity and the daily mean cloud amount. And the most frequent levels were $19-23^{\circ}C$ in dew point temperature, $21-24 MJ/m^2$ in total insolation on the day before, $2.6-3.0 MJ/m^2$ on the very day, 67-80% in relative humidity and 0-3 in cloud amount.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2003년도 추계학술대회 논문집
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• pp.121-122
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• 2003

현재, 대기 환경 자료의 정확한 분석을 위하여 정부와 지자체는 여러 종류의 대기 오염 측정망을 설치하여 운영하고 있다. 측정망으로부터 산출된 이러한 자료들의 품질은 대기 환경 학자 및 전문가들은 물론이고 일반 국민들의 일상적인 활동에도 중요한 영향을 미치고 있기 때문에, 측정 결과의 정화한 이해와 사용을 위한 품질 보증이 매우 중요한 실정에 있다. 그러나, 국제적인 수준의 품질 보증이 이루어지기 위해서는 측정 실험실의 인증 요건(ISO 17025) 및 측정 불확도 표기(ISO Guide) 등에 관한 국제적인 규격들의 적용이 매우 엄격하게 요구되고 있는 실정이다. (중략)

• 대한원격탐사학회지
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• 제36권4호
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• pp.637-643
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• 2020

In this study, the information from environmental impact statements was converted into spatial data because environmental data from development sites are collected during the environmental impact assessment (EIA) process. Spatiotemporal big data were built from environmental spatial data for each environmental medium for 2,235 development sites during 2007-2018, available from public data portals. Comparing air-quality monitoring stations, 33,863 measurement points were constructed, which is approximately 75 times more measurement points than that 452 in Air Korea's real-time measurement network. Here, spatiotemporal big data from 2,677,260 EIAs were constructed. In the future, such data might be used not only for EIAs but also for various spatial plans.

• 대한원격탐사학회지
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• 제38권1호
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.