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RISS 인기검색어
- 검색키워드
- 저자 : Jackson Hian Wui Chang (검색결과 2 건)
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Jackson CHANG Hian Wui,CHEE Fuei Pien,Steven KONG Soon Kai,Justin SENTIAN 한국대기환경학회 2018 Asian Journal of Atmospheric Environment (AJAE) Vol.12 No.2
This paper presents seasonal variation of PM10 over five urban sites in Sabah, Malaysia for the period of January through December 2012. The variability of PM10 along with the diurnal and weekly cycles of CO, NO2, SO2, and O3 at Kota Kinabalu site were also discussed to investigate the possible sources for increased PM10 concentration at the site. This work is crucial to understand the behaviour and possible sources of PM10 in the urban atmosphere of Sabah region. In Malaysia, many air pollution studies in the past focused in west Peninsular, but very few local studies were dedicated for Sabah region. This work aims to fill the gap by presenting the descriptive statistics on the variability of PM10 concentration in the urban atmosphere of Sabah. To further examine its diurnal and weekly cycle pattern, its responses towards the variations of CO, NO2, SO2, and ozone were also investigated. The highest mean value of PM10 for the whole study period is seen from Tawau (35.7±17.8 μg m-3), while the lowest is from Keningau (31.9± 18.6 μg m-3). The concentrations of PM10 in all cities exhibited seasonal variations with the peak values occurred during the south-west monsoons. The PM10 data consistently exhibited strong correlations with traffic related gaseous pollutants (NO2, and CO), except for SO2 and O3. The analysis of diurnal cycles of PM10 levels indicated that two peaks were associated during the morning and evening rush hours. The bimodal distribution of PM10, CO, and NO2 in the front and at the back of ozone peak is a representation of urban air pollution pattern. In the weekly cycle, higher PM10, CO, and NO2 concentrations were observed during the weekday when compared to weekend. The characteristics of NO2 concentration rationed to CO and SO2 suggests that mobile sources is the dominant factor for the air pollution in Kota Kinabalu, particularly during weekdays. This paper presents seasonal variation of PM10 over five urban sites in Sabah, Malaysia for the period of January through December 2012. The variability of PM10 along with the diurnal and weekly cycles of CO, NO2, SO2, and O3 at Kota Kinabalu site were also discussed to investigate the possible sources for increased PM10 concentration at the site. This work is crucial to understand the behaviour and possible sources of PM10 in the urban atmosphere of Sabah region. In Malaysia, many air pollution studies in the past focused in west Peninsular, but very few local studies were dedicated for Sabah region. This work aims to fill the gap by presenting the descriptive statistics on the variability of PM10 concentration in the urban atmosphere of Sabah. To further examine its diurnal and weekly cycle pattern, its responses towards the variations of CO, NO2, SO2, and ozone were also investigated. The highest mean value of PM10 for the whole study period is seen from Tawau (35.7±17.8 μg m-3), while the lowest is from Keningau (31.9± 18.6 μg m-3). The concentrations of PM10 in all cities exhibited seasonal variations with the peak values occurred during the south-west monsoons. The PM10 data consistently exhibited strong correlations with traffic related gaseous pollutants (NO2, and CO), except for SO2 and O3. The analysis of diurnal cycles of PM10 levels indicated that two peaks were associated during the morning and evening rush hours. The bimodal distribution of PM10, CO, and NO2 in the front and at the back of ozone peak is a representation of urban air pollution pattern. In the weekly cycle, higher PM10, CO, and NO2 concentrations were observed during the weekday when compared to weekend. The characteristics of NO2 concentration rationed to CO and SO2 suggests that mobile sources is the dominant factor for the air pollution in Kota Kinabalu; particularly during weekdays.
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Muhammad Izzuddin Rumaling,Fuei Pien Chee,Jedol Dayou,Jackson Hian Wui Chang,Steven Soon Kai Kong,Justin SENTIAN 한국대기환경학회 2020 Asian Journal of Atmospheric Environment (AJAE) Vol.14 No.1
Missing data in large data analysis has affected further analysis conducted on dataset. To fill in missing data, Nearest Neighbour Method (NNM) and Expectation Maximization (EM) algorithm are the two most widely used methods. Thus, this research aims to compare both methods by imputing missing data of air quality in five monitoring stations (CA0030, CA0039, CA0042, CA0049, CA0050) in Sabah, Malaysia. PM10 (particulate matter with aerodynamic size below 10 microns) dataset in the range from 2003-2007 (Part A) and 2008-2012 (Part B) are used in this research. To make performance evaluation possible, missing data is introduced in the datasets at 5 different levels (5%, 10%, 15%, 25% and 40%). The missing data is imputed by using both NNM and EM algorithm. The performance of both data imputation methods is evaluated using performance indicators (RMSE, MAE, IOA, COD) and regression analysis. Based on performance indicators and regression analysis, NNM performs better compared to EM in imputing data for stations CA0039, CA0042 and CA0049. This may be due to air quality data missing at random (MAR). However, this is not the case for CA0050 and part B of CA0030. This may be due to fluctuation that could not be detected by NNM. Accuracy evaluation using Mean Absolute Percentage Error (MAPE) shows that NNM is more accurate imputation method for most of the cases.
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