Now showing 1 - 2 of 2
  • Publication
    Characteristics of PM10 Level during haze events in Malaysia based on quantile regression method
    (MDPI, 2023)
    Siti Nadhirah Redzuan
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    ;
    Nur Alis Addiena A. Rahim
    ;
    Izzati Amani Mohd Jafri
    ;
    Syaza Ezzati Baidrulhisham
    ;
    Ahmad Zia Ul-Saufie
    ;
    Andrei Victor Sandu
    ;
    Petrica Vizureanu
    ;
    Mohd Remy Rozainy Mohd Arif Zainol
    ;
    György Deák
    Malaysia has been facing transboundary haze events repeatedly, in which the air contains extremely high particulate matter, particularly PM10, which affects human health and the environment. Therefore, it is crucial to understand the characteristics of PM10 concentration and develop a reliable PM10 forecasting model for early information and warning alerts to the responsible parties in order for them to mitigate and plan precautionary measures during such events. This study aims to analyze PM10 variation and investigate the performance of quantile regression in predicting the next-day, the next two days, and the next three days of PM10 levels during a high particulate event. Hourly secondary data of trace gases and the weather parameters at Pasir Gudang, Melaka, and Petaling Jaya during historical haze events in 1997, 2005, 2013, and 2015. The Pearson correlation was calculated to find the correlation between PM10 level and other parameters. Moderate correlated parameters (r > 0.3) with PM10 concentration were used to develop a Pearson–QR model with percentiles of 0.25, 0.50, and 0.75 and were compared using quantile regression (QR) and multiple linear regression (MLR). Several performance indicators, namely mean absolute error (MAE), root mean squared error (RMSE), coefficient of determination (R2), and index of agreement (IA), were calculated to evaluate and compare the performances of the predictive model. The highest daily average of PM10 concentration was monitored in Melaka within the range of 69.7 and 83.3 µg/m3. CO and temperature were the most significant parameters associated with PM10 level during haze conditions. Quantile regression at p = 0.75 shows high efficiency in predicting PM10 level during haze events, especially for the short-term prediction in Melaka and Petaling Jaya, with an R2 value of >0.85. Thus, the QR model has high potential to be developed as an effective method for forecasting air pollutant levels, especially during unusual atmospheric conditions when the overall mean of the air pollutant level is not suitable for use as a model.
      1  9
  • Publication
    Variability of PM10 level with gaseous pollutants and meteorological parameters during episodic haze event in Malaysia: domestic or solely transboundary factor?
    (Elsevier, 2023)
    Nur Alis Addiena A Rahim
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    ;
    Izzati Amani Mohd Jafri
    ;
    Ahmad Zia Ul-Saufie
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    ;
    Ain Nihla Kamarudzaman
    ;
    ;
    Mohd Remy Rozainy Mohd Arif Zainol
    ;
    Sandu Andrei Victor
    ;
    Gyorgy Deak
    Haze has become a seasonal phenomenon affecting Southeast Asia, including Malaysia, and has occurred almost every year within the last few decades. Air pollutants, specifically particulate matter, have drawn a lot of attention due to their adverse impact on human health. In this study, the spatial and temporal variability of the PM10 concentration at Kelang, Melaka, Pasir Gudang, and Petaling Jaya during historic haze events were analysed. An hourly dataset consisting of PM10, gaseous pollutants and weather parameters were obtained from Department of Environment Malaysia. The mean PM10 concentrations exceeded the stipulated Recommended Malaysia Ambient Air Quality Guideline for the yearly average of 150 μg/m3 except for Pasir Gudang in 1997 and 2005, and Petaling Jaya in 2013. The PM10 concentrations exhibit greater variability in the southwest monsoon and inter-monsoon periods at the studied year. The air masses are found to be originating from the region of Sumatra during the haze episodes. Strong to moderate correlation of PM10 concentrations was found between CO during the years that recorded episodic haze, meanwhile, the relationship of PM10 level with SO2 was found to be significant in 2013 with significant negatively correlated relative humidity. Weak correlation of PM10-NOx was measured in all study areas probably due to less contribution of domestic anthropogenic sources towards haze events in Malaysia.
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