• Journal of Preventive Medicine and Public Health
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• v.36 no.1
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• pp.47-53
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• 2003

Objectives : I used a case-crossover design to investigate the association between air pollution, and hospital admissions for asthmatic children under the age of 15 years in Seoul, Korea Methods : I estimated the changes in the levels of hospitalization risk from theinterquartile (IQR) increase in each pollutant concentrations, using conditional logistic regression analyses, with controls for weather information. Results : Using bidirectional control sampling, the results from a conditional logistic regression model, with controls for weather conditions, showed the estimated relative risk of hospitalization for asthma among children to be 1.04 (95% confidence interval (CI), 1.01-1.08) for particulate matter with an aerodynamic diameter less than or equal to 10m (IQR=40.4ug/m3); 1.05 (95% CI, 1.00- 1.09) for nitrogen dioxide (IQR=14.6ppb): 1.02 (95% CI,0.97-1.06) for sulfur dioxide (IQR=4.4ppb): 1.03 (95% CI, 0.99-1.08) for ozone (IQR=21.7ppb): and 1.03 (95% CI, 0.99-1.08) for carbon monoxide f10R=1.0ppm). Conclusions : This empirical analysis indicates the bidirectional control sampling methods, by design, would successfully control the confounding factors due to the long-term time trends of air pollution. These findings also support the hypothesis that air pollution at levels below the current ambient air quality standards of Korea is harmful to sensitive subjects, such as asthmatic children.

• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.6 s.113
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• pp.90-97
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• 2006

The effects of a green buffer zone to protect a residential area from air pollution from industrial facilities and traffic was examined by analyzing the case of a green buffer zone in the Shiwha industrial complex. The green buffer zone is 175 m wide. The intent was to assess the dispersion patterns of atmospheric air pollutants and the reduction in concentration around the green buffer zone. To measure atmospheric sulfur dioxide$(SO_2)$ and nitrogen dioxide$(NO_2)$ concentration, badge-type passive samplers were used and set up at 76 locations in order to measure the concentration of air pollutants with respect to the spatial dispersion. The weighted mean values of $SO_2\;and\;NO_2$ concentration were $3\~57 ppb\;and\;18\~62 ppb$ and the differences among the green buffer zone, the industrial area and the residential areas were $0.7\~1.1 ppb$. Mean values of atmospheric concentrations of $NO_2$ were similar in industrial and, residential areas and the green buffer zone. Results of the study show that the effect of the green buffer zone on reducing the dispersion of air pollutants was very low. This study also recommends that micro-climate, i.e., wind direction should be considered as a factor for planning and design of green buffer zones.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.604-612
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• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1153-1164
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• 2008

The ozone data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model have been considered for analyzing the ozone data at the northern part of the Gyeonggi-Do, Uijeongbu monitoring site in Korea. The result showed that both overall and monthly ARE models are suited for describing the ozone concentration. In the ARE model, seven meteorological variables and four pollution variables are used as the as the explanatory variables for the ozone data set. The seven meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, dew point temperature, steam pressure, and amount of cloud. The four air pollution explanatory variables are Sulfur dioxide(SO2), Nitrogen dioxide(NO2), Cobalt(CO), and Promethium 10(PM10). Also, the high level ozone data (over 80ppb) have been analyzed four ARE models, General ARE, HL ARE, PM10 add ARE, Temperature add ARE model. The result shows that the General ARE, HL ARE, and PM10 add ARE models are suited for describing the high level of ozone data.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1117-1124
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• 2010

The PM10 (Promethium 10) data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model has been considered for analyzing the monthly PM10 data at the southern part of the Gyeonggi-Do, Suwon monitoring site in Korea. In the ARE model, six meteorological variables and four pollution variables are used as the explanatory variables for the PM10 data set. The six meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, radiation, and amount of cloud. The four air pollution explanatory variables are sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), carbon monoxide (CO), and ozone ($O_3$). The result showed that the monthly ARE models explained about 13-49% for describing the PM10 concentration.

• Journal of Environmental Science International
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• v.14 no.6
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• pp.555-563
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• 2005

This study presents the characteristics of nocturnal inversion layer and their effect on the concentration variations of surface air pollutants using tethersonde and automatic weather station (AWS, 2 layer tower) system in Ulsan during 2003, The method for the distinction of inversion intensity was decided based on the sum of nocturnal temperature gradient. As the results, there was a close correlation (correlation coefficient of 0,76) between the maximum inversion height obtained from tethersonde and the sum of nocturnal temperature gradient. The air pollutant concentration was also directly proportional to the inversion intensity. When the inversion intensity was strong in the nighttime, ozone $(O_3)$ concentration was lower, while nitrogen dioxide $(NO_2)$ concentration was higher. The carbon monoxide (CO) concentration was gradually higher according to the nocturnal inversion intensity, whereas sulfur dioxide $(SO_2)$ concentration was relatively constant. In addition, we found that there was no correlation between the inversion intensity and TSP concentration.

• Journal of Animal Science and Technology
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• v.61 no.3
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• pp.122-137
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• 2019

Methane, one of the important greenhouse gas, has a higher global warming potential than that of carbon dioxide. Agriculture, especially livestock, is considered as the biggest sector in producing anthropogenic methane. Among livestock, ruminants are the highest emitters of enteric methane. Methanogenesis, a continuous process in the rumen, carried out by archaea either with a hydrogenotrophic pathway that converts hydrogen and carbon dioxide to methane or with methylotrophic pathway, which the substrate for methanogenesis is methyl groups. For accurate estimation of methane from ruminants, three methods have been successfully used in various experiments under different environmental conditions such as respiration chamber, sulfur hexafluoride tracer technique, and the automated head-chamber or GreenFeed system. Methane production and emission from ruminants are increasing day by day with an increase of ruminants which help to meet up the nutrient demands of the increasing human population throughout the world. Several mitigation strategies have been taken separately for methane abatement from ruminant productions such as animal intervention, diet selection, dietary feed additives, probiotics, defaunation, supplementation of fats, oils, organic acids, plant secondary metabolites, etc. However, sustainable mitigation strategies are not established yet. A cumulative approach of accurate enteric methane measurement and existing mitigation strategies with more focusing on the biological reduction of methane emission by direct-fed microbials could be the sustainable methane mitigation approaches.

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.237-250
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• 2024

The emission of noxious gases is a significant problem in pig production, as it can lead to poor production, welfare concerns, and environmental pollution. The noxious gases are the gasses emitted from the pig manure that contribute to air pollution. The increased concentration of various harmful gasses can pose health risks to both animals and humans. The major gases produced in the pig farm include methane, hydrogen sulfide, carbon dioxide, ammonia, sulfur dioxide and volatile fatty acids, which are mainly derived from the fermentation of undigested or poorly digested nutrients. Nowadays research has focused on more holistic approaches to obtain a healthy farm environment that helps animal production. The use of probiotics, prebiotics, dietary enzymes, and medicinal plants in animal diets has been explored as a means of reducing harmful gas emissions. This review paper focuses on the harmful gas emissions from pig farm, the mechanisms of gas production, and strategies for reducing these emissions. Additionally, various methods for reducing gas in pigs, including probiotic interventions; prebiotic interventions, dietary enzymes supplementation, and use of medicinal plants and organic acids are discussed. Overall, this paper provides a comprehensive review of the current state of knowledge on reducing noxious gas in pigs and offers valuable insights for pig producers, nutritionists, and researchers working in this area.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.187-197
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• 2010

Carbon dioxide Capture and Storage(CCS) is regarded as one of the most promising options to response climate change. CCS is a three-stage process consisting of the capture of carbon dioxide($CO_2$), the transport of $CO_2$ to a storage location, and the long term isolation of $CO_2$ from the atmosphere for the purpose of carbon emission mitigation. Up to now, process design for this $CO_2$ marine geological storage has been carried out mainly on pure $CO_2$. Unfortunately the $CO_2$ mixture captured from the power plants and steel making plants contains many impurities such as $N_2$, $O_2$, Ar, $H_2O$, $SO_2$, $H_2S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification, transport and injection processes. In order to design a reliable $CO_2$ marine geological storage system, it is necessary to analyze the impact of these impurities on the whole CCS process at initial design stage. The purpose of the present paper is to compare and analyse the relevant physical property models including BWRS, PR, PRBM, RKS and SRK equations of state, and NRTL-RK model which are crucial numerical process simulation tools. To evaluate the predictive accuracy of the equation of the state for $CO_2-SO_2$ mixture, we compared numerical calculation results with reference experimental data. In addition, optimum binary parameter to consider the interaction of $CO_2$ and $SO_2$ molecules was suggested based on the mean absolute percent error. In conclusion, we suggest the most reliable physical property model with optimized binary parameter in designing the $CO_2-SO_2$ mixture marine geological storage process.

• Korean journal of applied entomology
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• v.20 no.4 s.49
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• pp.229-233
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• 1981

This study was to investigate ornamental trees injuries at the Tobong ornamental tree farm, which is located in Uichongpu City, Kyonggido. The injury was caused by $SO_2$ gas from the smoke of the vicinal factories. The results obtained are as follows: 1 The total concentration of sulfur in leaves was increased with incerased degree of injury The most severe injuries were found at the distance between 70-120m from the western boundary of the Tobong ornamental 4ree farm with a highest concentration of total sulfur at $0.5-0.6\%$. This means the injuries caused by the acute injury and the temperature changes. 2. Significant differences were found between normal and injured portion of the same trees in Juniperus chinensis. 3. Anatomical study of the leaf tissues, showed the plasmolysis occured both in spongy and epidermal cells, leading to shrinkage and destruction. An intercellular space and stomatal periphery became wider.