ORCID Profile
0000-0003-3567-9634
Current Organisation
North South University
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Publisher: Elsevier BV
Date: 06-2019
Publisher: Copernicus GmbH
Date: 29-04-2019
Publisher: Copernicus GmbH
Date: 29-04-2016
Abstract: Abstract. This study investigates the fine particulate matter (PM2.5) variability in the Klang Valley urban-industrial environment. In total, 94 daily PM2.5 s les were collected during a 1-year c aign from August 2011 to July 2012. This is the first paper on PM2.5 mass, chemical composition and sources in the tropical environment of Southeast Asia, covering all four seasons (distinguished by the wind flow patterns) including haze events. The s les were analysed for various inorganic components and black carbon (BC). The chemical compositions were statistically analysed and the temporal aerosol pattern (seasonal) was characterised using descriptive analysis, correlation matrices, enrichment factor (EF), stoichiometric analysis and chemical mass closure (CMC). For source apportionment purposes, a combination of positive matrix factorisation (PMF) and multi-linear regression (MLR) was employed. Further, meteorological–gaseous parameters were incorporated into each analysis for improved assessment. In addition, secondary data of total suspended particulate (TSP) and coarse particulate matter (PM10) s led at the same location and time with this study (collected by Malaysian Meteorological Department) were used for PM ratio assessment. The results showed that PM2.5 mass averaged at 28 ± 18 µg m−3, 2.8-fold higher than the World Health Organisation (WHO) annual guideline. On a daily basis, the PM2.5 mass ranged between 6 and 118 µg m−3 with the daily WHO guideline exceeded 43 % of the time. The north-east (NE) monsoon was the only season with less than 50 % s le exceedance of the daily WHO guideline. On an annual scale, PM2.5 mass correlated positively with temperature (T) and wind speed (WS) but negatively with relative humidity (RH). With the exception of NOx, the gases analysed (CO, NO2, NO and SO2) were found to significantly influence the PM2.5 mass. Seasonal variability unexpectedly showed that rainfall, WS and wind direction (WD) did not significantly correlate with PM2.5 mass. Further analysis on the PM2.5 ∕ PM10, PM2.5 ∕ TSP and PM10 ∕ TSP ratios reveal that meteorological parameters only greatly influenced the coarse particles (particles with an aerodynamic diameter of greater than 2.5 µm) and less so the fine particles at the site. Chemical composition showed that both primary and secondary pollutants of PM2.5 are equally important, albeit with seasonal variability. The CMC components identified were in the decreasing order of (mass contribution) BC secondary inorganic aerosols (SIA) dust trace elements sea salt K+. The EF analysis distinguished two groups of trace elements: those with anthropogenic sources (Pb, Se, Zn, Cd, As, Bi, Ba, Cu, Rb, V and Ni) and those with a crustal source (Sr, Mn, Co and Li). The five identified factors resulting from PMF 5.0 were (1) combustion of engine oil, (2) mineral dust, (3) mixed SIA and biomass burning, (4) mixed traffic and industrial and (5) sea salt. Each of these sources had an annual mean contribution of 17, 14, 42, 10 and 17 % respectively. The dominance of each identified source largely varied with changing season and a few factors were in agreement with the CMC, EF and stoichiometric analysis, accordingly. In relation to meteorological–gaseous parameters, PM2.5 sources were influenced by different parameters during different seasons. In addition, two air pollution episodes (HAZE) revealed the influence of local and/or regional sources. Overall, our study clearly suggests that the chemical constituents and sources of PM2.5 were greatly influenced and characterised by meteorological and gaseous parameters which vary greatly with season.
Publisher: American Geophysical Union (AGU)
Date: 23-12-2016
DOI: 10.1002/2016JD025894
Publisher: Copernicus GmbH
Date: 19-01-2016
Abstract: Abstract. The health implications of PM2.5 in the tropical region of Southeast Asia (SEA) are significant as PM2.5 can pose serious health concerns. PM2.5 concentration and sources here are strongly influenced by changes in the monsoon regime from the south-west quadrant to the north-east quadrant in the region. In this work, PM2.5 s les were collected at a semi-urban area using a high-volume air s ler at different seasons on 24 h basis. Analysis of trace elements and water-soluble ions was performed using inductively coupled plasma mass spectroscopy (ICP-MS) and ion chromatography (IC), respectively. Apportionment analysis of PM2.5 was carried out using the United States Environmental Protection Agency (US EPA) positive matrix factorization (PMF) 5.0 and a mass closure model. We quantitatively characterized the health risks posed to human populations through the inhalation of selected heavy metals in PM2.5. 48 % of the s les collected exceeded the World Health Organization (WHO) 24 h PM2.5 guideline but only 19 % of the s les exceeded 24 h US EPA National Ambient Air Quality Standard (NAAQS). The PM2.5 concentration was slightly higher during the north-east monsoon compared to south-west monsoon. The main trace metals identified were As, Pb, Cd, Ni, Mn, V, and Cr while the main ions were SO42−, NO3−, NH4+, and Na. The mass closure model identified four major sources of PM2.5 that account for 55 % of total mass balance. The four sources are mineral matter (MIN) (35 %), secondary inorganic aerosol (SIA) (11 %), sea salt (SS) (7 %), and trace elements (TE) (2 %). PMF 5.0 elucidated five potential sources: motor vehicle emissions coupled with biomass burning (31 %) were the most dominant, followed by marine/sulfate aerosol (20 %), coal burning (19 %), nitrate aerosol (17 %), and mineral/road dust (13 %). The hazard quotient (HQ) for four selected metals (Pb, As, Cd, and Ni) in PM2.5 mass was highest in PM2.5 mass from the coal burning source and least in PM2.5 mass originating from the mineral/road dust source. The main carcinogenic heavy metal of concern to health at the current location was As the other heavy metals (Ni, Pb, and Cd) did not pose a significant cancer risk in PM2.5 mass concentration. Overall, the associated lifetime cancer risk posed by the exposure of hazardous metals in PM2.5 is 3–4 per 1 000 000 people at this location.
Publisher: Elsevier BV
Date: 09-2015
Publisher: Elsevier BV
Date: 02-2020
Publisher: MDPI AG
Date: 18-08-2023
DOI: 10.3390/SU151612532
Abstract: Polycyclic aromatic hydrocarbons (PAHs) are persistent organic pollutants (POPs) found in the environment, posing significant health concerns for the population. This research aimed to assess the PAH levels in road dust near bus stops, identify their sources, and evaluate potential health risks. The analysis involved the use of a gas chromatography–flame ionization detector (GC-FID) to measure PAHs and absolute principal component score-multiple linear regression (APCS-MLR) for source apportionment of PAHs. The results indicated that the measured PAHs concentrations in road dust ranged from 137.8 to 5813 ng g−1, with Indeno[1,2,3-c,d]pyrene having the highest PAHs concentrations. The study identified three main sources of PAHs such as oil spills, fuel combustion, and coal burning, determined through APCS-MLR modeling. Further analysis revealed that the aggregate incremental lifetime cancer risk (ILCR) for children and adults were 2.16 × 10−6 and 2.08 × 10−6, respectively. Additionally, the hazard index (HI) for children exceeded that of adults, suggesting greater vulnerability to the potential health effects of PAH exposure. The findings indicate that long-term exposure to PAHs may negatively impact lung function and increase the risk of cancer and skin diseases. As a result, it is crucial for the local government to implement effective measures aimed at improving fuel quality and promoting green public transportation within the city. These initiatives may help mitigate PAH emissions and safeguard public health.
Publisher: Springer Science and Business Media LLC
Date: 03-09-2016
Publisher: Copernicus GmbH
Date: 03-09-2019
DOI: 10.5194/ACP-19-11105-2019
Abstract: Abstract. Indonesia contains large areas of peatland that have been drained and cleared of natural vegetation, making them susceptible to burning. Peat fires emit considerable amounts of carbon dioxide, particulate matter (PM) and other trace gases, contributing to climate change and causing regional air pollution. However, emissions from peat fires are uncertain, due to uncertainties in emission factors and fuel consumption. We used the Weather Research and Forecasting model with chemistry and measurements of PM concentrations to constrain PM emissions from Indonesian fires during 2015, one of the largest fire seasons in recent decades. We estimate primary PM2.5 (particles with diameters less than 2.5 µm) emissions from fires across Sumatra and Borneo during September–October 2015 were 7.33 Tg, a factor 3.5 greater than those in the Fire Inventory from NCAR (FINNv1.5), which does not include peat burning. We estimate similar dry fuel consumption and CO2 emissions to those in the Global Fire Emissions Database (GFED4s, including small fires) but PM2.5 emissions that are a factor of 1.8 greater, due to updated PM2.5 emission factors for Indonesian peat. Fires were responsible for an additional 3.12 Tg of secondary organic aerosol formation. Through comparing simulated and measured PM concentrations, our work provides independent support of these updated emission factors. We estimate peat burning contributed 71 % of total primary PM2.5 emissions from fires in Indonesia during September–October 2015. We show that using satellite-retrieved soil moisture to modify the assumed depth of peat burn improves the simulation of PM, increasing the correlation between simulated and observed PM from 0.48 to 0.56. Overall, our work suggests that peat fires in Indonesia produce substantially greater PM emissions than estimated in current emission inventories, with implications for the predicted air quality impacts of peat burning.
Publisher: Copernicus GmbH
Date: 29-04-2019
DOI: 10.5194/ACP-2019-323
Abstract: Abstract. Indonesia contains large areas of peatland which are being drained and cleared of natural vegetation, making them susceptible to burning. Peat fires emit considerable amounts of carbon dioxide, particulate matter (PM) and other trace gases, contributing to climate change and causing regional air pollution. However emissions from peat fires are uncertain due to uncertainties in emission factors and burn depth of peat. We used the Weather Research and Forecasting model with chemistry, and measurements of PM concentrations to constrain PM emissions from Indonesian fires during 2015, one of the largest fire seasons in recent decades. We estimate PM2.5 (particles with diameters less than 2.5 μm) emissions from fires across Sumatra and Borneo during September to October 2015 were 7.33 Tg, a factor 3.5 greater than those in Fire Inventory from NCAR (FINNv1.5), which does not include peat burning. We estimate similar dry fuel consumption and CO2 emissions to those in the Global Fire Emissions Database (GFED4s), but a factor 1.8 greater PM2.5 emissions, due to updated PM2.5 emission factors for Indonesian peat. Through comparing simulated and measured PM concentrations, our work provides an independent confirmation of these updated emission factors. We estimate peat burning contributes 71 % of total PM2.5 emissions from fire in Indonesia during September–October 2015. We show that using satellite-retrieved soil moisture to modify the assumed depth of peat burn improves the simulation of PM, increasing the correlation between simulated and observed PM from 0.48 to 0.56. Overall, our work suggests that peat fires in Indonesia produce substantially greater PM emissions than estimated in current emission datasets, with implications for the predicted air quality impacts of peat burning.
Publisher: Informa UK Limited
Date: 06-2015
DOI: 10.1080/10962247.2015.1042094
Abstract: 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 [NO(x)], 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 wind-blown particles (1%). However, the apportionment procedure left 28.0 μg m⁻³, that is, 51% of PM10 undetermined.
Publisher: Elsevier BV
Date: 04-2015
Publisher: Springer Science and Business Media LLC
Date: 05-2015
DOI: 10.1007/S11356-015-4541-4
Abstract: Principal component analysis (PCA) and correlation have been used to study the variability of particle mass and particle number concentrations (PNC) in a tropical semi-urban environment. PNC and mass concentration (diameter in the range of 0.25->32.0 μm) have been measured from 1 February to 26 February 2013 using an in situ Grimm aerosol s ler. We found that the 24-h average total suspended particulates (TSP), particulate matter ≤10 μm (PM10), particulate matter ≤2.5 μm (PM2.5) and particulate matter ≤1 μm (PM1) were 14.37 ± 4.43, 14.11 ± 4.39, 12.53 ± 4.13 and 10.53 ± 3.98 μg m(-3), respectively. PNC in the accumulation mode (<500 nm) was the most abundant (at about 99 %). Five principal components (PCs) resulted from the PCA analysis where PC1 (43.8 % variance) predominates with PNC in the fine and sub-microme tre range. PC2, PC3, PC4 and PC5 explain 16.5, 12.4, 6.0 and 5.6 % of the variance to address the coarse, coarser, accumulation and giant fraction of PNC, respectively. Our particle distribution results show good agreement with the moderate resolution imaging spectroradiometer (MODIS) distribution.
Publisher: Elsevier BV
Date: 02-2018
DOI: 10.1016/J.SCITOTENV.2017.08.025
Abstract: 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 s les 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, SO
Publisher: Elsevier BV
Date: 12-2017
DOI: 10.1016/J.SCITOTENV.2017.05.153
Abstract: This study aims to determine PM
Publisher: Springer Science and Business Media LLC
Date: 13-07-2017
Publisher: Springer Science and Business Media LLC
Date: 05-02-2015
DOI: 10.1007/S00128-015-1477-9
Abstract: This study determined the source contribution of PM2.5 (particulate matter <2.5 μm) in air at three locations on the Malaysian Peninsula. PM2.5 s les were collected using a high volume s ler equipped with quartz filters. Ion chromatography was used to determine the ionic composition of the s les and inductively coupled plasma mass spectrometry was used to determine the concentrations of heavy metals. Principal component analysis with multilinear regressions were used to identify the possible sources of PM2.5. The range of PM2.5 was between 10 ± 3 and 30 ± 7 µg m(-3). Sulfate (SO4 (2-)) was the major ionic compound detected and zinc was found to dominate the heavy metals. Source apportionment analysis revealed that motor vehicle and soil dust dominated the composition of PM2.5 in the urban area. Domestic waste combustion dominated in the suburban area, while biomass burning dominated in the rural area.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Md Firoz Khan.