Sains Malaysiana 52(12)(2023): 3893-3906

http://doi.org/10.17576/jsm-2023-5212-20

Quantifying Haze Effect using Air Pollution Index Data

(Pengukuran Kesan Jerebu menggunakan Data Indeks Pencemaran Udara)

RAZIK RIDZUAN MOHD TAJUDDIN* & NURULKAMAL MASSERAN

Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia

Received: 13 July 2023/Accepted: 7 December 2023

Abstract

Malaysia has been misfortunate with intermittent haze episodes since 1997 which affect the air quality tremendously. In Malaysia, an instrument named air pollution index (API) is utilized in determining the quality of air, which is influenced by the presence of haze. API values are calculated by considering the concentration of harmful particles in haze. Therefore, any haze episode heavily affects the API values and can be considered as a determining factor. Since Malaysia is prone to haze, it is crucial to identify and quantify the haze effect on the API values. Therefore, a regression model with autoregressive integrated moving average errors (ARIMAX) is employed. It is found that ARIMAX (4,0,1) with non-zero mean is the best model in describing the API data with presence of haze as external regressor based on the smallest adequacy and error measures for training and test datasets. In conclusion, the effect of haze is significant in describing the API values and thus, proper health managements is required during haze episodes.

Keywords: ARIMAX; haze effect; regression with ARIMA errors

Abstrak

Malaysia mengalami nasib malang dengan episod jerebu yang berterusan sejak tahun 1997 yang memberi kesan yang besar terhadap kualiti udara. Di Malaysia, terdapat satu pengukur yang dikenali sebagai indeks pencemaran udara (IPU) yang digunakan untuk menentukan kualiti udara yang dipengaruhi oleh kehadiran jerebu. Nilai IPU dihitung berdasarkan kepekatan zarah berbahaya dalam jerebu. Oleh itu, apa-apa episod jerebu akan memberi kesan yang besar kepada nilai IPU dan boleh dianggap sebagai suatu faktor penentu. Memandangkan Malaysia cenderung untuk mengalami jerebu, adalah penting untuk mengenal pasti dan mengukur kesan jerebu terhadap nilai IPU. Oleh itu, satu model regresi dengan ralat purata bergerak terintegrasi auto regresif (ARIMAX) digunakan. Didapati bahawa ARIMAX (4,0,1) dengan min bukan sifar merupakan model terbaik dalam menerangkan data IPU dengan kehadiran jerebu sebagai regresor luaran berdasarkan ukuran kecukupan serta ralat terkecil untuk set data latihan dan set data ujian. Kesimpulannya, kesan jerebu adalah signifikan dalam menerangkan nilai IPU dan oleh yang demikian, pengurusan kesihatan yang betul diperlukan sepanjang jerebu berlaku.

Kata kunci: ARIMAX; kesan jerebu; regresi dengan ralat ARIMA

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*Corresponding author; email: rrmt@ukm.edu.my