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Norazian Mohamed Noor
Preferred name
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
Main Affiliation
Scopus Author ID
25221616600
Researcher ID
M-6956-2019
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1 - 3 of 3
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PublicationSpatio-temporal variation of Particulate Matter (PM10) during High Particulate Event (HPE) in Malaysia(Springer Science and Business Media Deutschland GmbH, 2022-01-01)
;Ridzuan N.A.M. ; ;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 µg/m3 and 66.22 µg/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.2 2 -
PublicationCharacteristics of PM10 Level during haze events in Malaysia based on quantile regression method(MDPI, 2023)
;Siti Nadhirah Redzuan ; ;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 ZainolGyörgy DeákMalaysia 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 -
PublicationVariability 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 ; ;Izzati Amani Mohd Jafri ;Ahmad Zia Ul-Saufie ; ;Ain Nihla Kamarudzaman ; ;Mohd Remy Rozainy Mohd Arif Zainol ;Sandu Andrei VictorGyorgy DeakHaze 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.24 2