• 교육녹색환경연구
• /
• 제6권2호
• /
• pp.66-90
• /
• 2007

The purpose of this study is to measure and analyze primary causes of indoor air pollution, including carbon dioxide, minute dust, and total volatile organic compounds, for each room before the beginning of a class through the time of discharge after the end of the class in general classrooms, computer rooms, and science rooms of three newly-established schools that opened in 2006, examine properties of indoor air environment in each room by educational activities at school, and determine effective management schemes; the results of this study can be summarized as follows: 1) As for implications for each item found in the mean for each place, since minute dust (PM10) was more likely to occur in time slots full of students' activities, such as a traveling class and a recess, than in the middle of a class and could be expected fully, it is necessary to make a scheme for cleaning in order to reduce minute dust within a room, for example, by usually using a vacuum cleaner indoors. 2) While carbon dioxide was expected to vary with the differences in the amount of breath between higher-graders and lower-graders in a general classroom but showed insignificant difference by grades, showing differences in pollution by four times at a maximum according to the opening of a window as expected, it is necessary to implement artificial or natural ventilation and take a positive measure, for example, by presenting a concrete ventilation scheme, in order to improve indoor air pollution at a room practice. 3) Total volatile organic compounds were found to exceed the standard by more than twice in general classrooms, science rooms, and computer rooms of the schools because of building materials, furnitures including desks and chairs, panels and boards for environment beautification, and items which could be detected even from students' clothes; while a field directly-reading tool was used, obtaining high reliability for the results, it is necessary to apply an analytical method based on process test separately for actual correct measurement if a significantly great amount of total volatile organic compounds appear as compared with other schools due to measuring expenses and consecutive measurements. 4) Since formaldehyde (HCHO) was generally found to exceed the standard in general classrooms, science rooms, and computer rooms, it is necessary to establish and operate a ventilator during a class in a computer room which requires airtightness and a science room in which an organic compound should be used for a class.

• Asian Journal of Atmospheric Environment
• /
• 제4권2호
• /
• pp.106-114
• /
• 2010

By the application of novel double detector system of micro-PIXE that can detect light elements (Z<14), we made an attempt to provide a thorough discussion on the aging processes of Asian dust (hereafter called "AD") particle by reaction with sea-slat. The elemental spectra and maps obtained from the microbeam radiation of micro-PIXE to individual AD particles were useful for fractionating AD particles into both internally and externally mixed particles. A spatial distribution of elements in a minute domain of single particle obtained by scanning the microbeam irradiation enabled us not only to estimate the chemical mixing state of individual AD particles but also to presume their aging processes in both ambient air and cloud. By calculating the normalized micro-PIXE net count of elements, it was possible to classify individual AD particles into three distinct groups (i.e., (1) Aging type 1: AD particle coated by the gaseous Cl evaporated by the reaction between artificial acids and sea salt; (2) Aging type 2: AD particle mixed with sea salt but no additional reaction with artificial acids; and (3) Non-aged type) A relatively high transformation rate (63.3-75.9%) was shown in large particles (greater than $5.1\;{\mu}m$ in diameter).

• 대한화학회지
• /
• 제6권2호
• /
• pp.155-157
• /
• 1962

A tiny dust found at the balcony of the Institute indicated about 8,0000 counts per minute by T.G.C.-2 Geiger-Muller tube (1.8mg/$cm^2$ window-thickness) at the distance of 2cm from the window. The main fission fragments, as identified by the present analysis, are 12.5day Ba-140 and 33.1 day Ce-141. The gamma energies were determined using $2"{\times}2"$ NaI(Tl) scintillation detector connected to RCL-256 channel pulse heigt analyzer. The beta energies were evaluated by Feather plot.

• 한국건설관리학회논문집
• /
• 제9권5호
• /
• pp.176-185
• /
• 2008

도심이 과밀화됨에 따라 재건축 및 재개발의 활성화, 대규모 택지개발에 의한 신도시 개발, 사회기반시설 확충 등으로 건설폐기물이 급증하고 있다. 이와 더불어 도심지내 공사장 등에 의한 소음, 진동 및 분진 발생원이 지속적으로 증가하고 다양화됨에 따라 이와 관련된 환경 분쟁 및 민원이 급증하고 있는 추세이다. 이에 따라 정부는 생활주변의 정온한 환경을 조성하기 위하여 가까운 미래에 각종관련기준을 상향 적용할 계획이며, 결과적으로 건설공사관련 환경 분쟁 및 민원의 발생이 더욱 증가할 것으로 예상된다. 따라서 본 연구에서는 현장파쇄시설을 운영하고 있는 현장에서의 소음, 진동, 분진 발생량을 측정하고 분석하여, 현장파쇄시설에서 발생되는 환경민원발생 예방측면에서 대책을 마련하여 건설폐기물의 현장재활용 활성화를 위한 기초 자료를 제시하고자 한다.

• 환경위생공학
• /
• 제24권4호
• /
• pp.1-26
• /
• 2009

We conclude the following with air pollution data measured from city measurement net administered and managed in Gwangju for the last 7 years from January in 2001 to December in 2007. In addition, some major statistics governed by Gwangju city and data administered by Gwangju as national official statistics obtained by estimating the amount of national air pollutant emission from National Institute of Environmental Research were used. The results are as follows ; 1. The distribution by main managements of air emission factory is the following ; Gwangju City Hall(67.8%) > Gwangsan District Office(13.6%) > Buk District Office(9.8%) > Seo District Office(5.5%) > Nam District Office(3.0%) > Dong District Office(0.3%) and the distribution by districts of air emission factory ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%). That by types(Year 2004~2007 average) is also following ; Type 5(45.2%) > Type 4(40.7%) > Type 3(8.6%) > Type 2(3.2%) > Type 1(2.2%) and the most of them are small size of factory, Type 4 and 5. 2. The distribution by districts of the number of car registrations is the following ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%) and the distribution by use of car fuel in 2001 ; Gasoline(56.3%) > Diesel(30.3%) > LPG(13.4%) > etc.(0.2%). In 2007, there was no ranking change ; Gasoline(47.8%) > Diesel(35.6%) > LPG(16.2%) >etc.(0.4%). The number of gasoline cars increased slightly, but that of diesel and LPG cars increased remarkably. 3. The distribution by items of the amount of air pollutant emission in Gwangju is the following; CO(36.7%) > NOx(32.7%) > VOC(26.7%) > SOx(2.3%) > PM-10(1.5%). The amount of CO and NOx, which are generally generated from cars, is very large percentage among them. 4. The distribution by mean of air pollutant emission(SOx, NOx, CO, VOC, PM-10) of each county for 5 years(2001~2005) is the following ; Buk District(31.0%) > Gwangsan District(28.2%) > Seo District(20.4%) > Nam District(12.5%) > Dong District(7.9%). The amount of air pollutant emission in Buk District, which has the most population, car registrations, and air pollutant emission businesses, was the highest. On the other hand, that of air pollutant emission in Dong District, which has the least population, car registrations, and air pollutant emission businesses, was the least. 5. The average rates of SOx for 5 years(2001~2005) in Gwangju is the following ; Non industrial combustion(59.5%) > Combustion in manufacturing industry(20.4%) > Road transportation(11.4%) > Non-road transportation(3.8%) > Waste disposal(3.7%) > Production process(1.1%). And the distribution of average amount of SOx emission of each county is shown as Gwangsan District(33.3%) > Buk District(28.0%) > Seo District(19.3%) > Nam District(10.2%) > Dong District(9.1%). 6. The distribution of the amount of NOx emission in Gwangju is shown as Road transportation(59.1%) > Non-road transportation(18.9%) > Non industrial combustion(13.3%) > Combustion in manufacturing industry(6.9%) > Waste disposal(1.6%) > Production process(0.1%). And the distribution of the amount of NOx emission from each county is the following ; Buk District(30.7%) > Gwangsan District(28.8%) > Seo District(20.5%) > Nam District(12.2%) > Dong District(7.8%). 7. The distribution of the amount of carbon monoxide emission in Gwangju is shown as Road transportation(82.0%) > Non industrial combustion(10.6%) > Non-road transportation(5.4%) > Combustion in manufacturing industry(1.7%) > Waste disposal(0.3%). And the distribution of the amount of carbon monoxide emission from each county is the following ; Buk District(33.0%) > Seo District(22.3%) > Gwangsan District(21.3%) > Nam District(14.3%) > Dong District(9.1%). 8. The distribution of the amount of Volatile Organic Compound emission in Gwangju is shown as Solvent utilization(69.5%) > Road transportation(19.8%) > Energy storage & transport(4.4%) > Non-road transportation(2.8%) > Waste disposal(2.4%) > Non industrial combustion(0.5%) > Production process(0.4%) > Combustion in manufacturing industry(0.3%). And the distribution of the amount of Volatile Organic Compound emission from each county is the following ; Gwangsan District(36.8%) > Buk District(28.7%) > Seo District(17.8%) > Nam District(10.4%) > Dong District(6.3%). 9. The distribution of the amount of minute dust emission in Gwangju is shown as Road transportation(76.7%) > Non-road transportation(16.3%) > Non industrial combustion(6.1%) > Combustion in manufacturing industry(0.7%) > Waste disposal(0.2%) > Production process(0.1%). And the distribution of the amount of minute dust emission from each county is the following ; Buk District(32.8%) > Gwangsan District(26.0%) > Seo District(19.5%) > Nam District(13.2%) > Dong District(8.5%). 10. According to the major source of emission of each items, that of oxides of sulfur is Non industrial combustion, heating of residence, business and agriculture and stockbreeding. And that of NOx, carbon monoxide, minute dust is Road transportation, emission of cars and two-wheeled vehicles. Also, that of VOC is Solvent utilization emission facilities due to Solvent utilization. 11. The concentration of sulfurous acid gas has been 0.004ppm since 2001 and there has not been no concentration change year by year. It is considered that the use of sulfurous acid gas is now reaching to the stabilization stage. This is found by the facts that the use of fuel is steadily changing from solid or liquid fuel to low sulfur liquid fuel containing very little amount of sulfur element or gas, so that nearly no change in concentration has been shown regularly. 12. Concerning changes of the concentration of throughout time, the concentration of NO has been shown relatively higher than that of $NO_2$ between 6AM~1PM and the concentration of $NO_2$ higher during the other time. The concentration of NOx(NO, $NO_2$) has been relatively high during weekday evenings. This result shows that there is correlation between the concentration of NOx and car traffics as we can see the Road transportation which accounts for 59.1% among the amount of NOx emission. 13. 49.1~61.2% of PM-10 shows PM-2.5 concerning the relationship between PM-10 and PM-2.5 and PM-2.5 among dust accounts for 45.4%~44.5% of PM-10 during March and April which is the lowest rates. This proves that particles of yellow sand that are bigger than the size $2.5\;{\mu}m$ are sent more than those that are smaller from China. This result shows that particles smaller than $2.5\;{\mu}m$ among dust exist much during July~August and December~January and 76.7% of minute dust is proved to be road transportation in Gwangju.

• 천문학회보
• /
• 제35권1호
• /
• pp.92-92
• /
• 2010

A short-period comet, 17P/Holmes, is one of the most outstanding comets because of the outburs in 2007. It orbits the sun at the distance between 2.1AU and 5.2 AU with the orbital period of 6.9 year. On 2007 October 23, its brightness was suddenly increased by about a million times from 17 mag to 2.5 mag. We made observations of 17P/Holmes soon after the outburst on October 25, 27 and 28, using a 105cm telescope at the Ishigakijima Astronomical observatory, Japan. We took the images with V, R and I-band filters simultaneously. Total exposure times are 15 (October 25), 69 (October 27), and 37 (October 28) minute in each filter. The composite images provide good signal to noise ratio and help us to recognize faint structures embedded in the dust cloud. We examined a sequence of images using a digital filter that enhances the small-scale structures. As the result of the data analysis, we confirm (1) the radial expanded structure coming out from the nucleus of comet, and (2) dozens of blobs that moved radially away from the nucleus. In this presentation, we introduce the observations and the data reductions, and consider the origins of these fine structure.

• 한국축산시설환경학회지
• /
• 제11권3로
• /
• pp.197-206
• /
• 2005

본 연구는 무창육계사의 계절별 먼지 농도와 계사 먼지의 특성을 알아보고자 경기 화성 소재 육계농장의 무창계사에서 시험을 수행하였으며 결과는 다음과 같다. 1 여름철 무창육계사의 주령별 먼지농도는 TSP의 경우 1주령 1,229, 2주령 904.5, 3주령 558.8 그리고 4주령시 $1,053{\mu}g/m^3$이었다. 2. 겨울철에는 주령이 경과함에 따라 급격히 증가하는 경향이었으며, TSP의 경우 1주령시 465.4, 2주령시 1,401, 3주령시 4,497, 4주령시 5,097 그리고 5주령시 $6,873{\mu}g/m^3$이었다. 3. 겨울철 5주령시 최대 TSP량은 $11,132{\mu}g/m^3$을 보여 노출기준에 비하여 매우 높게 검출되었다. 4. 하루중의 먼지 분포는 여름철의 경우 이른 아침에 높게 나타났으며 환기량이 많은 오후에 최소량이 검출되었다 그러나 겨울철에는 이른 아침에 낮은 량이 검출되고 닭의 활동이 많은 오후에 먼지농도가 높게 검출되었다. 5. 먼지 입자 크기 분포에 있어서 숫자 기준으로 하였을 경우에는 $0.05\~0.35{\mu}m$ 크기의 먼지 분포가 높게 나타났으나 용적을 기준으로 하였을 경우에는 $16\~99{\mu}m$의 큰 먼지가 높은 분포를 보였다. 6. 먼지의 조단백질 함량은 DM기준으로 $42.8\~65.2\%$를 보여 급여사료의 조단백질 함량 $20.5\~24.5\%$에 비하여 높았으며 중금속의 경우에도 급여사료에 비하여 높은 농도를 보였다

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2009년도 춘계학술대회 논문집
• /
• pp.919-929
• /
• 2009

2008, Seoulmetro transports an average of 3,952,000 passengers every day with a 0.8% increase of the daily ridership compared to last year.(Korean Economics '09.01.21) Seoul subway systems ridden by a considerable number of Seoul citizens place their top priority on swiftness, safety and clean underground air quality so as to meet the customer satisfaction. One of the most important problems is to eliminate minute dust(PM10) among the pollutants such as the gas attributable to air pollution and floating particulate matter defined by the ordinance of the Ministry of Environment. Seoulmetro install and operate many kinds of air filtration facilities, however we've launched a research on "Standardization Plan on Underground Air Filtration Facility" for the installation and improvement of optimum standardized air filtration system. As a preliminary study, we're going to consider ventilation system and air filter to supply filtered metropolitan outdoor air aimed at ensuring clean underground environment.

• 플랜트 저널
• /
• 제16권1호
• /
• pp.34-37
• /
• 2020

최근 한국의 미세 먼지 오염도가 급격히 증가함에 따라 배가스 내 미세먼지를 더욱 효과적으로 집진할 수 있는 기술에 대한 관심 또한 증가하였다. 본 연구에서는 습식 전기집진기와 사이클론 집진기에 정전분무 기술을 결합하여 집진 성능의 증대를 목표로 한다. 정전분무는 일반적으로 질량분석, 혹은 반도체 코팅에 이용되므로 그 유량이 매우 적다. 분무 액적과 미세먼지의 이온결합을 통하여 집진을 해야하는 본 연구의 특성상 기존 정전분무의 유량에 대비하여 매우 큰 유량을 사용하게 된다. 따라서 기존의 정전분무 시작 전압, 혹은 분무 형상과는 다른 형상을 보일 수 있다. 본 연구에서는 기존 정전분무와는 다른 유량 및 전압 범위를 사용함으로써 예상되는 다양한 형상 특성을 살펴보고자 한다.

• 대기
• /
• 제26권4호
• /
• pp.541-551
• /
• 2016

A real-time quality control algorithm for $PM_{10}$ concentration measured by Continuous Ambient Particulate Monitor (FH62C14, Thermo Fisher Scientific Inc.) has been developed. The quality control algorithm for $PM_{10}$ data consists of five main procedures. The first step is valid value check. The values should be within the acceptable range limit. Upper ($5,000{\mu}g\;m^{-3}$) and lower ($0{\mu}g\;m^{-3}$) values of instrument detectable limit have to be eliminated as being unrealistic. The second step is valid error check. Whenever unusual condition occurs, the instrument will save error code. Value having an error code is eliminated. The third step is persistence check. This step checks on a minimum required variability of data during a certain period. If the $PM_{10}$ data do not vary over the past 60 minutes by more than the specific limit ($0{\mu}g\;m^{-3}$) then the current 5-minute value fails the check. The fourth step is time continuity check, which is checked to eliminate gross outlier. The last step is spike check. The spikes in the time series are checked. The outlier detection is based on the double-difference time series, using the median. Flags indicating normal and abnormal are added to the raw data after quality control procedure. The quality control algorithm is applied to $PM_{10}$ data for Asian dust and non-Asian dust case at Seoul site and dataset for the period 2013~2014 at 26 sites in Korea.