Sains Malaysiana 47(3)(2018): 471–479

http://dx.doi.org/10.17576/jsm-2018-4703-06

Applied Chemometric Approach in Identification Sources of Air Quality Pattern in Selangor, Malaysia

(Aplikasi Pendekatan Kimometriks dalam Mengenal Pasti Corak Sumber Kualiti Udara di Selangor, Malaysia)

ANG KEAN HUA*

Department of Environmental Sciences, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia

Received: 3 July 2017/Accepted: 17 October 2017

ABSTRACT

In recent years, Malaysia has experienced quite a few number of chronic air pollution problems and it has become a major contributor to the deterioration of human health and ecosystems. This study aimed to assess the air quality data and identify the pattern of air pollution sources using chemometric analysis through hierarchical cluster analysis (HCA), discriminant analysis (DA), principal component analysis (PCA) and multiple linear regression analysis (MLR). The air quality data from January 2016 until December 2016 was obtained from the Department of Environment Malaysia. Air quality data from eight sampling stations in Selangor include the selected variables of nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂), carbon monoxide (CO) and particulate matter (PM10). The HCA resulted in three clusters, namely low pollution source (LPS), moderate pollution source (MPS) and slightly high pollution source (SHPS). Meanwhile, DA resulted in two and four variables for the forward stepwise mode and the backward stepwise mode, respectively. Through PCA, it was identified that the main pollutants of LPS, MPS and SHPS came from industrial and vehicle emissions, agricultural systems, residential factors and natural emission sources. Among the three models yielded from the MLR analysis, it was found that SHPS is the most suitable model to be used for the prediction of Air Pollution Index. This study concluded that a clearer review and practical design of air quality monitoring network would be beneficial for better management of air pollution. The study also suggested that chemometric techniques have the ability to show significant information on spatial variability for large and complex air quality data.

Keywords: Discriminant analysis; hierarchical cluster analysis; multiple linear regression analysis; principal component analysis

ABSTRAK

Sejak beberapa tahun kebelakangan ini, Malaysia telah mengalami beberapa masalah pencemaran udara yang kronik dan ia telah menjadi salah satu penyebab utama dalam kemerosotan kesihatan manusia dan ekosistem. Matlamat kajian ini adalah untuk menilai data kualiti udara dan mengenal pasti corak sumber pencemaran udara menggunakan teknik kimometriks melalui analisis pengkelasan hierarki (HCA), analisis diskriminan (DA), analisis komponen berprinsip (PCA) dan analisis regrasi linear pelbagai (MLR). Data kualiti udara bermula dari Januari hingga Disember 2016 telah diperoleh daripada Jabatan Alam Sekitar Malaysia. Data kualiti udara dari lapan stesen persampelan di Negeri Selangor melibatkan pemboleh ubah terpilih nitrogen dioksida (NO₂), ozon (O₃), sulfur dioksida (SO₂), karbon monoksida (CO) dan zarahan terampai (PM10). Proses HCA telah menghasilkan tiga kluster iaitu sumber pencemar rendah (LPS), sumber pencemar sederhana (MPS) dan sumber pencemar sedikit tinggi (SHPS). Sementara itu, proses DA telah menghasilkan dua pemboleh ubah bagi mod ke hadapan berperingkat dan empat pemboleh ubah bagi mod ikut langkah kebelakang. Melalui proses PCA, ia telah dikenal pasti bahawa bahan pencemar utama bagi LPS, MPS dan SHPS berasal daripada hasil pelepasan industri dan pengangkutan, sistem pertanian, faktor kediaman dan sumber pelepasan semula jadi. Antara ketiga-tiga model yang dihasilkan melalui analisis MLR, ia didapati bahawa SHPS adalah model yang paling sesuai untuk digunakan bagi kerja-kerja ramalan Indeks Pencemaran Udara. Kajian ini menyimpulkan bahawa ulasan serta reka bentuk praktikal ke atas rangkaian pengawasan kualiti udara akan memberi manfaat dalam usaha mengurus pencemaran udara dengan lebih baik. Kajian ini juga mencadangkan bahawa teknik kimometriks mempunyai keupayaan untuk mendedahkan maklumat yang penting tentang pemboleh ubah reruang bagi data kualiti udara yang besar dan rumit.

Kata kunci: Analisis diskriminan; analisis komponen berprinsip; analisis pengkelasan hierarki; analisis regrasi linear pelbagai

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*Corresponding author; email: angkeanhua@yahoo.com