Norazian Mohamed Noor
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Norazian Mohamed Noor
Official Name
Norazian, Mohamed Noor
Alternative Name
Noor, Norazian Mohamed
Norazian, M. N.
Noor, Norazian Mohamad
Noor, N. M.
Mohamed, Norazian N.
Mohamed, N. N.
Zizi, Na Mohd
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Scopus Author ID
25221616600
Researcher ID
M-6956-2019

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Publication

Performance of Bayesian Model Averaging (BMA) for short-term prediction of PM10 concentration in the Peninsular Malaysia

2023 , Norazrin Ramli , Hazrul Abdul Hamid , Ahmad Shukri Yahaya , Ahmad Zia Ul-Saufie , Norazian Mohamed Noor , Ain Nihla Kamarudzaman , György Deák , Nor Amirah Abu Seman @ Haji Ahmad

In preparation for the Fourth Industrial Revolution (IR 4.0) in Malaysia, the government envisions a path to environmental sustainability and an improvement in air quality. Air quality measurements were initiated in different backgrounds including urban, suburban, industrial and rural to detect any significant changes in air quality parameters. Due to the dynamic nature of the weather, geographical location and anthropogenic sources, many uncertainties must be considered when dealing with air pollution data. In recent years, the Bayesian approach to fitting statistical models has gained more popularity due to its alternative modelling strategy that accounted for uncertainties for all air quality parameters. Therefore, this study aims to evaluate the performance of Bayesian Model Averaging (BMA) in predicting the next-day PM10 concentration in Peninsular Malaysia. A case study utilized seventeen years’ worth of air quality monitoring data from nine (9) monitoring stations located in Peninsular Malaysia, using eight air quality parameters, i.e., PM10, NO2, SO2, CO, O3, temperature, relative humidity and wind speed. The performances of the next-day PM10 prediction were calculated using five models’ performance evaluators, namely Coefficient of Determination (R2), Index of Agreement (IA), Kling-Gupta efficiency (KGE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The BMA models indicate that relative humidity, wind speed and PM10 contributed the most to the prediction model for the majority of stations with (R2 = 0.752 at Pasir Gudang monitoring station), (R2 = 0.749 at Larkin monitoring station), (R2 = 0.703 at Kota Bharu monitoring station), (R2 = 0.696 at Kangar monitoring station) and (R2 = 0.692 at Jerantut monitoring station), respectively. Furthermore, the BMA models demonstrated a good prediction model performance, with IA ranging from 0.84 to 0.91, R2 ranging from 0.64 to 0.75 and KGE ranging from 0.61 to 0.74 for all monitoring stations. According to the results of the investigation, BMA should be utilised in research and forecasting operations pertaining to environmental issues such as air pollution. From this study, BMA is recommended as one of the prediction tools for forecasting air pollution concentration, especially particulate matter level.

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Spatio-temporal variation of Particulate Matter (PM10) during High Particulate Event (HPE) in Malaysia

2022-01-01 , Ridzuan N.A.M. , Norazian Mohamed Noor , Rahim N.A.A.A. , Jafri I.A.M. , Gyeorgy D.

Particulate matter (PM10) is the key indicator of air quality index in Malaysia and Southeast Asia's main haze-related pollutant. PM10 emanation is believed to cause the strongest harm to public health and the environment. Therefore, it is very important to study the temporal and spatial characteristics of PM10 and the weather parameters, hence the relationship between them can be identified. A database with hourly PM10 concentration and weather parameters were obtained from Department of Environment (DOE) Malaysia from the period of 2012–2016 at two study areas that are located in Klang Valley, namely, Petaling Jaya and Shah Alam. The temporal analysis for PM10 concentration was observed by using descriptive statistics, boxplot and time series plot whereas the spatial analysis was conducted using windrose diagram. The finding shows that the highest average concentration of PM10 at Petaling Jaya and Shah Alam in 2015 exceeded the Malaysia Ambient Air Quality Standard, which were 60.13 Âµg/m3 and 66.22 Âµg/m3 respectively. It was due to high particulate event (HPE) that had affected Malaysia during the period of Southwest Monsoon, where the massive land and forest fires came from Sumatra and Kalimantan, Indonesia. According to the wind rose rose diagram, the wind mostly blew from northeast in January until February as Malaysia experienced northeast monsoon where rainfall happened. Shah Alam received stronger wind compared to the Petaling Jaya because the topography of city.

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Variability of PM10 level with gaseous pollutants and meteorological parameters during episodic haze event in Malaysia: domestic or solely transboundary factor?

2023 , Nur Alis Addiena A Rahim , Norazian Mohamed Noor , Izzati Amani Mohd Jafri , Ahmad Zia Ul-Saufie , Norazrin Ramli , Ain Nihla Kamarudzaman , Nor Amirah Abu Seman @ Haji Ahmad , 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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