• Communications for Statistical Applications and Methods
• /
• 제25권2호
• /
• pp.199-215
• /
• 2018

Interest in $PM_{10}$ concentrations have increased greatly in Korea due to recent increases in air pollution levels. Therefore, we consider a forecasting model for next day $PM_{10}$ concentration based on the principal elements of air pollution, weather information and Beijing $PM_{2.5}$. If we can forecast the next day $PM_{10}$ concentration level accurately, we believe that this forecasting can be useful for policy makers and public. This paper is intended to help forecast a daily mean $PM_{10}$, a daily max $PM_{10}$ and four stages of $PM_{10}$ provided by the Ministry of Environment using various data mining techniques. We use seven models to forecast the daily $PM_{10}$, which include five regression models (linear regression, Randomforest, gradient boosting, support vector machine, neural network), and two time series models (ARIMA, ARFIMA). As a result, the linear regression model performs the best in the $PM_{10}$ concentration forecast and the linear regression and Randomforest model performs the best in the $PM_{10}$ class forecast. The results also indicate that the $PM_{10}$ in Seoul is influenced by Beijing $PM_{2.5}$ and air pollution from power stations in the west coast.

• 한국환경과학회지
• /
• 제26권2호
• /
• pp.159-172
• /
• 2017

Asthma deaths in Seoul peaked on the third, fifth, and second days after the PM concentration exceeded the daily average concentration standard. We classified the synoptic meteorological conditions, based on the days involving such cases, into three categories. Type 1 included the meteorological condition likely to cause high air pollution concentrations in the leeward region, the dominant wind direction of which is the northwest. Type 2 included the meteorological condition likely to cause high air pollution concentrations due to the weak wind velocity under stable atmospheric conditions. Type 3 was when the passage low atmospheric pressure and the expansion of high atmospheric pressure occurred at the rear, indicating a meteorological condition likely to cause high air pollution, in certain regions. Type 1 occurred 11 times, with high concentrations of over $100{\mu}g/m^3$ being observed in the southeastern part of Seoul. Type 2 occurred 24 times, often accompanied by a PM concentration of $100{\sim}400{\mu}g/m^3$. Type 3 occurred 11 times, and was accompanied by several days of yellow dust that accounted for the highest concentrations.

• 환경위생공학
• /
• 제9권1호
• /
• pp.38-52
• /
• 1994

This study examines three different relation effects of air pollution on health in Seoul city during 1988-90 : an effect on respiratory disease mortality, the frequency of hospital in- patients for asthma, and jogging in the morning. The results seemed likely to show positive association between respiratory mortality and asthma in- patients and ozone concentration. It also suggested that jogging as morning exercise was not recommended in the morning because of the highest concentration of major pollutants in the morning 7 : 00-8'00 a.m ). The epidemiological and statistical investigation of air pollution on health effects to be studied in further detail since these findings have provided some limited conclusions.

• 한국대기환경학회:학술대회논문집
• /
• 한국대기환경학회 2005년도 추계학술대회 논문집
• /
• pp.443-445
• /
• 2005

• The Korean Journal of Ecology
• /
• 제26권2호
• /
• pp.87-89
• /
• 2003

Although a forest damage of large area due to air pollution has not yet been found in Korea, declines of Korean red pine (Pinus densiflora Sieb. et Zucc.), the most common coniferous species, have been locally reported. To evaluate the effect of air pollution and acid deposition on the forests, SO$_2$ concentration, acid load, soil pH and tree decline were monitored for 13 years from 1988 to 2001 in Namsan, Doowang and Gyebangsan with the gradient of air pollution. During the study period, annual mean SO$_2$ concentration in Namsan, Doowang and Gyebangsan were 14 ppb, 13 ppb and 6 ppb, respectively. Annual mean acid loads in Namsan and Doowang were three to four times more than that in Gyebangsan. As respected, forest surface soils in Namsan and Doowang were acidified to pH 4.1 and 4.3, whereas that in Gyebangsan showed normal value as pH 5.4. On the other hand, decline degrees of Korean red pines in Namsan and Doowang in both 1996 and 2001 were higher than those in Gyebangsan. It is reasonable that the severer tree declines in Namsan and Doowang could be closely related with the higher air pollution, acid load, and the effects (possibly Ca deficit and Al toxicity) of soil acidification.

• 한국주거학회논문집
• /
• 제26권4호
• /
• pp.55-62
• /
• 2015

The international concern on the inhalable fine dust is continuing to increase. In addition to the toxic properties of the fine dust itself, it can be more dangerous than other environmental factors since the dust pollution is hard to be detected by human sense. Although the information on outdoor air condition can be acquired easily, the indoor dust concentration is another problem because the indoor air condition is influenced by the architectural environment and human activity. It means occupants may be exposed to indoor dust pollution over a long period without being aware. Therefore the indoor dust concentration should be measured separately and visualized as an intuitive information. By visualizing, the indoor dust concentration in each space can be recognized practically in compare with the degree of pollution in adjacent spaces. Besides the visualization outcome can be used as base data for related research such as an analysis of the relation between indoor dust concentration and architectural environment. Meanwhile, with the development of network and micro sensing devices, it became possible to collect wide range of indoor environment data. In this regards, this paper suggests a system for visualization of indoor dust concentration and demonstrates it on an actual space.

• Journal of Preventive Medicine and Public Health
• /
• 제27권3호
• /
• pp.505-516
• /
• 1994

For the purpose of preparing the fundamental data on air pollution in underground shopping center and also contributing to the health improvement of residents, the authors measured the level of $SO_2,\;NO_2,\;TSP,\;CO,\;CO_2$ and also some related factors as air temperature, air movement, relative humidity and mean radiation temperature at inside and outside of underground shopping center in Pusan from January to February and from July to August 1994. The results were as follows : 1. The mean concentration of CO within the underground shopping center was $3.1{\pm}1.3ppm$ in winter and $2.1{\pm}0.9ppm$ in summer. There was a negative correlation (p<0.01) between inner CO concentration and temperature in summer and no correlation between inner CO concentration and outer CO concentration in underground shopping center 2. The mean concentration of COE within the underground shopping center was $876{\pm}353ppm$ in winter and $757{\pm}125ppm$ in summer. There was a negative correlation (p<0.01) between inner $CO_2$ concentration and air movement in summer and positive correlation (p<0.05) between inner $CO_2$ concentration and outer $CO_2$ concentration in underground shopping center. 3. The mean concentration of $SO_2$ within a underground shopping center was $0.036{\pm}0.019ppm$ in winter and $0.040{\pm}0.013ppm$ in summer. There was a positive correlation(p<0.01) between inner $SO_2$ concentration and temperature in summer and positive correlation between inner $SO_2$ concentration and outer $SO_2$ concentration in summer and winter in underground shopping center. 4. The mean concentration of $NO_2$ within a underground shopping center was $0.052{\pm}0.038ppm$ in winter and $0.042{\pm}0.016ppm$ in summer. There was a no correlation between inner $SO_2$ concentration and thermal factors in summer and winter and low correlation between inner $SO_2$ concentration and outer $SO_2$ concentration in underground shopping center 5. The mean concentration of TSP within a underground shopping center was $430{\pm}214{\mu}g/m^3$ in winter, $366{\pm}73{\mu}g/m^3$ in summer, and very in excess of the atmospheric environmental quality standards of Korea ($150{\mu}g/m3{\downarrow}$). There was low correlation between inner TSP concentration and temperature in summer and high correlation between inner TSP concentration and outer TSP concentration in underground shopping center.

• 한국대기환경학회지
• /
• 제2권2호
• /
• pp.19-30
• /
• 1986

This study was performed to develop a long-term air pollution dispersion model based on CDM program for use in the personal computer. The model CDM.PC, developmented for use of this study, simplified the plum equation of point pollution source in a windy state and sindless state. We used the classified 8 class stability, 16 wind direction and 4 class wind speed for the computer input climatological data. The plum rise equation is applied for CONCAWE's equation above 2,000 Kcal/sec of the exhaust calorie and Moses-Carson's equation below 2,000Kcal/sec at windy state, and Brigg's equation at calm. The time required is 200 minutes for drawing the air pollution contour for treating ten stacks under the above-stated conditions. It is the weakness of using personal computer that the operation time is longer than a large-size computer. But it strength is that the personal computer is used widely. To compare the treatment results of CDM.PC with TCM, we comfirmed that the shape of $SO_2$ pollution contour is similar but the concentration distribution is quite different because of characteristics of each models. Estimated and measured $SO_2$ concentration were similar, namely, Cest/Cob ratio of CDM.PC and TCM were respectively $0.96 \pm 0.25 (mean\pmS.D)$ and $1.08\pm0.26$.

• Journal of Korea Trade
• /
• 제26권3호
• /
• pp.117-136
• /
• 2022

Purpose - Port is vital for international trade accounting for approximately 80% of world cargo transportation in the global trade sector. Air pollutants emitted owing to the related industry interfaces developed around the port spread throughout the dense population region can have harmful effects on the nearby residents. This study aims to analyze high-concentration diffusion pattern by air pollutants, considering the main management periods by air pollutants. Design/methodology - Employing the concentration criteria per main air pollutant, the analyses of concentration change patterns per air pollutant, wind characteristics that directly affected the air pollutant diffusion, distribution types per air pollutant, and high-concentration diffusion patterns by season according to time changes were conducted. Findings - The substances that caused harmful levels of air pollution in the hinterland living zone of the Busan New Port were PM_10, PM_2.5, and NO_2. Furthermore, the intensive management periods were as follows: For PM_10, 24-h (spring), 12:00-16:00 (summer), 12:00-16:00 (summer), 20:00-12:00 (fall), and 24:00-20:00 (winter), and for PM_2.5, 24-h (all four seasons), and for NO_2, 23:00-04:00 (spring), 23:00-08:00 (summer), and 20:00-08:00 (fall), and 23:00-04:00 (winter). Originality/value - Research finding indicates that regular monitoring and countermeasures to reduce air pollution for each air pollutant makes it possible to achieve effective air quality control in the port and hinterland living zones.

• Asian Journal of Atmospheric Environment
• /
• 제8권1호
• /
• pp.25-34
• /
• 2014

In winter 2013, extreme air pollution by fine particulate matter ($PM_{2.5}$) in China attracted much public attention. In order to simulate the $PM_{2.5}$ pollution, the Community Multiscale Air Quality model driven by the Weather Research and Forecasting model was applied to East Asia in a period from 1 January 2013 to 5 February 2013. The model generally reproduced $PM_{2.5}$ concentration in China with emission data in the year 2006. Therefore, the extreme $PM_{2.5}$ pollution seems to be mainly attributed to meteorological (weak wind and stable) conditions rather than emission increases in the past several years. The model well simulated temporal and spatial variations in $PM_{2.5}$ concentrations in Japan as well as China, indicating that the model well captured characteristics of the $PM_{2.5}$ pollutions in both areas on the windward and leeward sides in East Asia in the study period. In addition, contribution rates of four anthropogenic emission sectors (power generation, industrial, residential and transportation) in China to $PM_{2.5}$ concentration were estimated by conducting zero-out emission sensitivity runs. Among the four sectors, the residential sector had the highest contribution to $PM_{2.5}$ concentration. Therefore, the extreme $PM_{2.5}$ pollution may be also attributed to large emissions from combustion for heating in cold regions in China.