• Journal of the Korean Society of Tobacco Science
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• v.14 no.1
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• pp.48-56
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• 1992

This studies were carried out to investigate the effects of leaf loading quantity and circulating air volume during bulk curing on the variation of physical and chemical characteristics in flue-cured tobacco. The results are as follows : 1. The content of sugar in cured leaves was decreased with more circulating air volume and leaf loading quantity at bulk curing. 2. Total nitrogen and protein nitrogen were decreased with less circulating air volume and more leaf loading quantity, while amino nitrogen was increased. 3. The contents of linolenic acid and linoleic acid were increased with more leaf loading quantity and oxalic acid and citric acid had a tendency of being increased in case of high circulating air volume. 4. In general, major aromatic compounds were increased through flue-curing. Relatively high content of solanone in case of lower air volume and less leaf loading were observed, while megastig matrienone was increased when leaf loading was small. 5. The more circulation air volume with leaf loading quantity caused lowering equilibrium moisture content and higher shatter index, which resulted in poor quality of cured leaves based on quality index, nitrogen number, taste index phillips index, and sugar-nicotine ratio.

• Korean Journal of Geomatics
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• v.2 no.2
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• pp.145-151
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• 2002

GIS technique is applied to the analysis of ambient air quality information. For this study, the TMS-monitored air quality information was imported with the geographical information of the TMS stations in Capital Area. It is found that currently available GIS technique has a great extend of potential for air quality management. From the analysis of air quality information, the GIS application demonstrates the poor air quality in the central Capital Area and the it is improved as it travels down to the suburb area. The ambient air quality is also proven to be highly influenced by the ozone concentration in a mid-summer day.

• Advances in environmental research
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• v.1 no.4
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• pp.277-288
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• 2012

This study investigated exposure to air pollutants in rooms in low-income houses at Shomolu (R1), Mafoluku (R2) and Mushin (R3) in Lagos state. The concentrations of most measured exceeded limits of Illinois Department of Public Health (IDPH) for indoor air quality. Air quality index (AQI) in rooms studied was unhealthy for sensitive people in terms of CO, unhealthy in terms of $SO_2$ and very unhealthy in terms of $NO_2$ while moderate air quality was obtained in terms of $PM_{10}$ in most rooms. High concentrations of carbontetrachloride, formaldehyde and xylene measured could have been responsible for some of the health complaints of the occupants. Factor analysis shows that cooking with kerosene, use of gasoline generator and insecticide were the major contributors to indoor air pollution in these rooms. Therefore, there is need to urgently tackle poverty as all affected by these pollutants were poor who live in substandard houses without kitchens.

• Journal of Korean Society for Quality Management
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• v.48 no.2
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• pp.329-344
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• 2020

Purpose: The purpose of this study is to measure the Airline Educational Service Quality and to find ways to improve the priority factors that need improvement. Methods: The 267 collected data from the survey of K-airline calculate the Potential Customer Service Improvement Index based on the Kano Model, Timko Customer Satisfaction Index and conduct Focus Group Interview. Results: The satisfaction of Airline Educational Service Quality can be improved if instructor operations are intensively managed considering field experience and contents that can be applied in the field. Conclusion: This study would provide useful information about Airline Educational Service Quality and can be applied to map out strategies to improve the satisfaction of the Airline Educational Service.

• Journal of Environmental Impact Assessment
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• v.30 no.6
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• pp.380-392
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• 2021

An indoor air quality index for school classrooms based on the Hazard Quotient (HQ) was developed in this study. The current index (IAQI-S) covered PM₁₀, PM_2.5, and CO₂, and breakpoints of IAQI-S were calculated using each HQ value. IAQI-S was applied to the real-time data obtained from 123 classrooms of 46 schools during November 2017 to December 2020. As a result of the comprehensive assessment, 93.1% of PM₁₀ and 94% of PM_2.5 belonged to 'good' and 'moderate', respectively. The IAQI-S based on an 8-hour predicted moving average was compared with Comprehensive Air-quality Index (CAI) and with the IAQI of a foreign reference. The IAQI-S includes CO₂ and consists of more stringent levels comparing to outdoor index (CAI).

• Advances in environmental research
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• v.4 no.2
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• pp.83-104
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• 2015

Air Quality Index (AQI) is a pointer to broadcast short term air quality. This paper presents one day ahead AQI forecasting on seasonal basis for three major cities in Maharashtra State, India by using Artificial Neural Networks (ANN) and Genetic Programming (GP). The meteorological observations & previous AQI from 2005-2008 are used to predict next day's AQI. It was observed that GP captures the phenomenon better than ANN and could also follow the peak values better than ANN. The overall performance of GP seems better as compared to ANN. Stochastic nature of the input parameters and the possibility of auto-correlation might have introduced time lag and subsequent errors in predictions. Spectral Analysis (SA) was used for characterization of the error introduced. Correlational dependency (serial dependency) was calculated for all 24 models prepared on seasonal basis. Particular lags (k) in all the models were removed by differencing the series, that is converting each i'th element of the series into its difference from the (i-k)"th element. New time series is generated for all seasonal models in synchronization with the original time line & evaluated using ANN and GP. The statistical analysis and comparison of GP and ANN models has been done. We have proposed a promising approach of use of GP coupled with SA for real time prediction of seasonal multicity AQI.

• Asian Journal of Business Environment
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• v.10 no.4
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• pp.15-19
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• 2020

Purpose: This research aims to explore the level of air pollution in Jakarta, the epicenter of COVID-19 Pandemic in Indonesia and its surrounding provinces during the first month of the Pandemic. Research design, data and methodology: This study uses data, which have been obtained real time from API (Application Programming Interfaces) of air quality website. The measurements of Air Quality Index (AQI), temperature, humidity, and other factors from several cities and regencies in Indonesia were obtained eight times a day. The data collected have been analyzed using descriptive statistics and mapped using QGIS. Results: The finding of this study indicates that The Greater Jakarta Area experienced a decrease in pollutant levels, especially in the Bogor area. Nevertheless, some areas, such as the north Jakarta, have exhibited slow reduction. Furthermore, the regions with high COVID-19 confirmed cases have experienced a decline in AQI. Conclusions: The study concludes that the air quality of three provinces, Jakarta, Banten, and West Java, especially in cities located in the Jakarta Metropolitan Area during COVID-19 pandemic and large-scale social restrictions, is getting better. However, in some regions, the reduction of pollutant concentrations requires a longer time, as it was very high before the pandemic.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2010.04a
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• pp.329-330
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• 2010

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.2
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• pp.243-257
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• 2005

The effects of Traffic Control Program (TCP) on the ambient urban air quality of SO$_{2}$, NO$_{2}$, O$_{3}$, and PM$_{10}$ were evaluated in Seoul metropolitan area by using the lower atmospheric vertical stability index and daily mean wind speeds. The vertical stability index; temperature lapse rate between 1000 hPa and 850 hPa geopotential height fields, were used to identify daily vertical stability index during the 2002 World Cup period where traffic amount was reportedly reduced to half the number of vehicles. The indicated air quality levels of TCP days were then compared with those of the cases observed with analogous vertical stability during the recent 3 years from 2000 to 2002. The result indicates that the effect of TCP on the primary air pollutants are found to be approximately 39$\%$, 23$\%$ and 20$\%$ lower for SO$_{2}$, NO$_{2}$ and PM$_{10}$, respectively. The secondary air pollutant; ozone, showed relatively smaller decreasing rate (13$\%$) of daily mean concentrations (even increased during the night time). The comparison of daily maximum or peak concentrations reveals that the pronounced decreasing effects of TCP on the ambient air quality for both primary and secondary air pollutants, suggesting that TCP is one of the effective strategies to control peak or higher concentrations for most urban scale air pollutants in and around the Seoul metropolitan area.

• Journal of Environmental Health Sciences
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• v.46 no.4
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• pp.444-456
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• 2020

Objectives: This study developed an index for the indoor air quality management of city buses to allow the provision of indoor air quality information to city bus users. Methods: Nine city buses in Seoul were measured for PM₁₀, PM_2.5, CO₂, temperature, and relative humidity through IoT sensors. Big data collected through the sensors was analyzed to identify indoor air quality on city buses and graded through the index. Results: As a result of dividing the measured city bus data into five grades through the IAQ index, PM₁₀ was rated "good" for 30.4% of the total measured values, and 9.2% were rated "risky". For PM_2.5, 67.7 percent were rated "good" and 0.4 percent were rated "risky". For CO₂, 0.9% were 'good' and 1.1% were 'risky'. The results of the classification through the IAQ index for city buses showed that the impact of good, normal, sensitive, bad, and dangerous were 2.7, 38.8, 46.0, 12.4, and 0.1%, respectively. According to the analysis by measurement area, Seocho-gu, Gangnam-gu, Seongdong-gu, Gwangjin-gu, and Dobong-gu are "normal" and other areas (Seodaemoon-gu, Jongno-gu, Yongsan-gu, Jung-gu, Seongbuk-gu, Dongdaemun-gu, Junggye-gu, Gangbuk-gu, and Nowon-gu) are all rated "sensitive". Conclusions: When analyzing cases where PM₁₀ and CO₂ indices are in the "bad" zone, the concentration is generally found to increase during rush hour, during which there are a large number of passengers. It is expected that indoor air quality management in vehicles will be necessary during rush hour.