Environmetric Study on Air Quality Pattern for Assessment in Klang Valley, Malaysia
Syazwani Sahrir1, Ahmad Makmom Abdullah2, Zakiah Ponrahono3, Amir Hamzah Sharaai4
1Syazwani Sahrir, Department of Environmental Management, Faculty of Environmental Studies, Universiti Putra, Serdang, Malaysia.
2Ahmad Makmom Abdullah, Department of Environmental Sciences, Faculty of Environmental Studies, Universiti Putra, Serdang, Malaysia.
3Zakiah Ponrahono, Department of Environmental Management, Faculty of Environmental Studies, Universiti Putra, Serdang, Malaysia.
4Amir Hamzah Sharaai, Department of Environmental Management, Faculty of Environmental Studies, Universiti Putra, Serdang, Malaysia.
Manuscript received on 22 April 2019 | Revised Manuscript received on 05 May 2019 | Manuscript Published on 17 May 2019 | PP: 17-24 | Volume-8 Issue-1S May 2019 | Retrieval Number: A10030581S19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Air pollution had turned into one of the major environmental issues in Malaysia due to the heavy transportation activities in logistics and automobile dependencies, industrial activities and transboundary pollution from the neighbouring countries. The emission from such events such as infrastructure works, traffic (road, sea, air) and industry are directly responsible for air pollution. The objective of this study was to determine the significant pollutant parameters contributing to air quality issues and to identify air quality pattern at five air monitoring stations in Klang Valley, Malaysia for the years of 2010 until 2014 (five years). This dataset was derived from the Department of Environment, Malaysia (DOE). Air pollution index (API) such as SO2, CO2, NO2, O3, and PM10 were examined in this study. Environmental metric techniques used was cluster analysis (CA) to determine the air quality pattern based on yearly and specific monthly basis. Discriminant analysis (DA) was applied to a distinctive different class. The study identifies that there were different variables or predictors between each class. Principal component analysis (PCA) was used to identify the significant pollutant parameters based on five pollutants in air pollution index (API) which cause by many activities either internal or external factors. This study identified that SO2, CO2, NO2, and PM10 are the primary pollutants contributing to the deteriorating of air pollution in Klang Valley. By using the environmetric technique for analysing the data, it contributes to a better understanding of air quality pattern and clearly identified the vital of atmospheric pollutant parameters.
Keywords: Air Pollution, API Index, Environmentric Techniques, Pollution Parameters, Principle Component Analysis.
Scope of the Article: Environmental Engineering