Norhaniza Amil

Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur

Long-term measurements (2004–2011) of PM10 (particulate matter with an aerodynamic diameter <10 μm) and trace gases (carbon monoxide [CO], ozone [O3], nitrogen oxide [NO], oxides of nitrogen [NOx], nitrogen dioxide [NO2], sulfur dioxide [SO2], methane [CH4], nonmethane hydrocarbon [NMHC]) have been conducted to study the effect of physicochemical factors on the PM10 concentration. In addition, this study includes source apportionment of PM10 in Kuala Lumpur urban environment. An advanced principal component analysis (PCA) technique coupled with absolute principal component scores (APCS) and multiple linear regression (MLR) has been applied. The average annual concentration of PM10 for 8 yr is 51.3 ± 25.8 μg m−3, which exceeds the Recommended Malaysian Air Quality Guideline (RMAQG) and international guideline values. Detail analysis shows the dependency of PM10 on the linear changes of the motor vehicles in use and the amount of biomass burning, particularly from Sumatra, Indonesia, during southwesterly monsoon. The main sources of PM10 identified by PCA-APCS-MLR are traffic combustion (28%), ozone coupled with meteorological factors (20%), and windblown particles (1%). However, the apportionment procedure left 28.0 μg m−3, that is, 51% of PM10 undetermined. Implications: Air quality is always a top concern around the globe. Especially in the South Asian regions, measures are not yet sufficient; as revealed in our studies, the concentrations of particulate matters exceed the tolerable limits. Long-term data analysis and characterization of particular matters and their sources will aid the policy makers and the concerned authority to adapt measures and policies according to the circumstances. Additionally, similar intensive studies will give insight about future implications of air quality management.

Comprehensive assessment of PM2.5 physicochemical properties during the Southeast Asia dry season (southwest monsoon)

A comprehensive assessment of fine particulate matter (PM2.5) compositions during the Southeast Asia dry season is presented. Samples of PM2.5 were collected between 24 June and 14 September 2014 using a high-volume sampler. Water-soluble ions, trace species, rare earth elements, and a range of elemental carbon (EC) and organic carbon were analyzed. The characterization and source apportionment of PM2.5 were investigated. The results showed that the 24 h PM2.5 concentration ranged from 6.64 to 68.2 µg m−3. Meteorological driving factors strongly governed the diurnal concentration of aerosol, while the traffic in the morning and evening rush hours coincided with higher levels of CO and NO2. The correlation analysis for non sea-salt K+-EC showed that EC is potentially associated with biomass burning events, while the formation of secondary organic carbon had a moderate association with motor vehicle emissions. Positive matrix factorization (PMF) version 5.0 identified the sources of PM2.5: (i) biomass burning coupled with sea salt [I] (7%), (ii) aged sea salt and mixed industrial emissions (5%), (iii) road dust and fuel oil combustion (7%), (iv) coal-fired combustion (25%), (v) mineral dust (8%), (vi) secondary inorganic aerosol (SIA) coupled with F− (15%), and (vii) motor vehicle emissions coupled with sea salt [II] (24%). Motor vehicle emissions, SIA, and coal-fired power plant are the predominant sources contributing to PM2.5. The response of the potential source contribution function and Hybrid Single-Particle Lagrangian Integrated Trajectory backward trajectory model suggest that the outline of source regions were consistent to the sources by PMF 5.0.

Physicochemical factors and their potential sources inferred from long-term rainfall measurements at an urban and a remote rural site in tropical areas

Air pollution can be detected through rainwater composition. In this study, long-term measurements (2000-2014) of wet deposition were made to evaluate the physicochemical interaction and the potential sources of pollution due to changes of land use. The rainwater samples were obtained from an urban site in Kuala Lumpur and a highland-rural site in the middle of Peninsular Malaysia. The compositions of rainwater were obtained from the Malaysian Meteorological Department. The results showed that the urban site experienced more acidity in rainwater (avg=277mm, range of 13.8 to 841mm; pH=4.37) than the rural background site (avg=245mm, range of 2.90 to 598mm; pH=4.97) due to higher anthropogenic input of acid precursors. The enrichment factor (EF) analysis showed that at both sites, SO42-, Ca2+ and K+ were less sensitive to seawater but were greatly influenced by soil dust. NH4+ and Ca2+ can neutralise a larger fraction of the available acid ions in the rainwater at the urban and rural background sites. However, acidifying potential was dominant at urban site compared to rural site. Source-receptor relationship via positive matrix factorisation (PMF 5.0) revealed four similar major sources at both sites with a large variation of the contribution proportions. For urban, the major sources influence on the rainwater chemistry were in the order of secondary nitrates and sulfates>ammonium-rich/agricultural farming>soil components>marine sea salt and biomass burning, while at the background site the order was secondary nitrates and sulfates>marine sea salt and biomass burning=soil components>ammonia-rich/agricultural farming. The long-term trend showed that anthropogenic activities and land use changes have greatly altered the rainwater compositions in the urban environment while the seasonality strongly affected the contribution of sources in the background environment.

Characterization and Source Apportionment of Fine Particulate Matter during 2011 Haze Episode in UKM Bangi, Malaysia

This study aims to improve understanding of the haze episode particularly on PM2.5 by investigating the mass concentrations and its relation to chemical compositions and related gaseous-meteorological parameters during 2011 haze episode at UKM Bangi. Overall, PM2.5 mass concentrations for the haze episode averaged at 48.32 ± 10.07 μg/m3 with 30.24 % portioned by 29 elements studied. The examinations of the relationships between PM2.5 mass and gaseous-meteorological parameters shows that PM2.5 mass within the study area is predominantly correlated with O3, NO2, NOx and wind speed. The application of a receptor mode (PCA-MLR) to a database made up of chemical composition of PM2.5 resulted with five factors identified as: (1) motor vehicle emission; (2) soil dust; (3) industrial; (4) sea-salt; and (5) undefined source. A synoptic wind stream for south-west period together with results of HYSPLIT backward trajectories for the sampling site-period traced to three locations at Sumatra. The results attained in this study highlights to us that whilst the trans-boundary smoke is the major contributor to the poor air quality of Bangi, local conditions, in particular traffic, may contribute a significant portion towards the haze event.

Receptor Modeling Prediction for Potential Sources of PM10 at an Urban Location in Klang Valley, Malaysia

This study aims to investigate the characterization and source apportionment of PM10 at an urban site in Peninsular Malaysia. Principle component analysis (PCA) coupled with absolute principle component score (APCS) and multiple linear regression analysis (MLRA) were employed as a hybrid receptor model to perform the apportionment of PM10 sources. An hourly real time in situ data set of gases (e.g. CO, O3, SO2, NOx, NO, and NO2) and meteorological variables (e.g., ambient temperature, relative humidity and wind speed) measured at Petaling Jaya site of Selangor for a span of one year from January till December 2009 were used. The most sporadic variability of concentration of PM10 was noticed during south westerly and north easterly monsoon. PCA-APCS-MLRA predicted two predominant factors: (a) traffic emission and (b) meteorological factors-O3 source by which contributed 25 and 8 %, respectively, to PM10 concentration.