Dhaka and its neighboring areas suffer from severe air pollution, especially during dry season (November-April). We investigated temporal and directional variations in particulate matter (PM) concentrations in Dhaka, Gazipur, and Narayanganj from October 2012 to March 2015 to understand different aspects of PM concentrations and possible sources of high pollution in this region. Ninety-six-hour backward trajectories for the whole dry season were also computed to investigate incursion of long-range pollution into this area. We found yearly PM10 concentrations in this area about three times and yearly PM2.5 concentrations about six times greater than the national standards of Bangladesh. Dhaka and its vicinity experienced several air pollution episodes in dry season when PM2.5 concentrations were 8-13 times greater than the World Health Organization (WHO) guideline value. Higher pollution and great contribution of PM2.5 most of the time were associated with the north-westerly wind. Winter (November to January) was found as the most polluted season in this area, when average PM10 concentrations in Dhaka, Gazipur, and Narayanganj were 257.1, 240.3, and 327.4 μg m(-3), respectively. Pollution levels during wet season (May-October) were, although found legitimate as per the national standards of Bangladesh, exceeded WHO guideline value in 50 % of the days of that season. Trans-boundary source identifications using concentration-weighted trajectory method revealed that the sources in the eastern Indian region bordering Bangladesh, in the north-eastern Indian region bordering Nepal and in Nepal and its neighboring areas had high probability of contributing to the PM pollutions at Gazipur station.
This study determined the effect of monsoonal changes on the composition of atmospheric surfactants in coastal areas. The composition of anions (SO4(2-), NO3(-), Cl(-), F(-)) and the major elements (Ca, K, Mg, Na) in aerosols were used to determine the possible sources of surfactants. Surfactant compositions were determined using a colorimetric method as methylene blue active substances (MBAS) and disulphine blue active substances (DBAS). The anion and major element compositions of the aerosol samples were determined by ion chromatography (IC) and inductively coupled plasma mass spectrometry (ICP-MS), respectively. The results indicated that the concentrations of surfactant in aerosols were dominated by MBAS (34-326pmolm(-3)). Monsoonal changes were found to significantly affect the concentration of surfactants. Using principal component analysis-multiple linear regressions (PCA-MLR), major possible sources for surfactants in the aerosols were motor vehicle emissions, secondary aerosol and the combustion of biomass along with marine aerosol.
This study aimed to investigate the chemical composition and potential sources of PM10 as well as assess the potential health hazards it posed to school children. PM10 samples were taken from classrooms at a school in Kuala Lumpur's city centre (S1) and one in the suburban city of Putrajaya (S2) over a period of eight hours using a low volume sampler (LVS). The composition of the major ions and trace metals in PM10 were then analysed using ion chromatography (IC) and inductively coupled plasma-mass spectrometry (ICP-MS), respectively. The results showed that the average PM10 concentration inside the classroom at the city centre school (82µg/m(3)) was higher than that from the suburban school (77µg/m(3)). Principal component analysis-absolute principal component scores (PCA-APCS) revealed that road dust was the major source of indoor PM10 at both school in the city centre (36%) and the suburban location (55%). The total hazard quotient (HQ) calculated, based on the formula suggested by the United States Environmental Protection Agency (USEPA), was found to be slightly higher than the acceptable level of 1, indicating that inhalation exposure to particle-bound non-carcinogenic metals of PM10, particularly Cr exposure by children and adults occupying the school environment, was far from negligible.
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 sampler. 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.
This study aims to determine the concentration of sterols used as biomarkers in the surface microlayer (SML) in estuarine areas of the Selangor River, Malaysia. Samples were collected during different seasons through the use of a rotation drum. The analysis of sterols was performed using gas chromatography equipped with a flame ionisation detector (GC-FID). The results showed that the concentrations of total sterols in the SML ranged from 107.06 to 505.55 ng L(-1). The total sterol concentration was found to be higher in the wet season. Cholesterol was found to be the most abundant sterols component in the SML. The diagnostic ratios of sterols show the influence of natural sources and waste on the contribution of sterols in the SML. Further analysis, using principal component analysis (PCA), showed distinct inputs of sterols derived from human activity (40.58%), terrigenous and plant inputs (22.59%) as well as phytoplankton and marine inputs (17.35%).
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 samples were collected using a high volume sampler equipped with quartz filters. Ion chromatography was used to determine the ionic composition of the samples 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.
This study was conducted to determine the composition of surfactants in atmospheric aerosols and rainwater in the vicinity of Lake Chini, Malaysia. Samples of atmospheric aerosol and rainwater were collected between March and September 2011 using a high volume air sampler (HVAS) and glass bottles equipped with funnel. Colorimetric analysis was undertaken to determine the concentration of anionic surfactants as methylene blue active substances (MBAS) and cationic surfactants as disulphine blue active substances (DBAS). The water-soluble ionic compositions were determined using inductively coupled plasma mass spectrometry for cations (Na, K, Mg and Ca) and ion chromatography equipped with a conductivity detector for anions (F(-), Cl(-), NO3(-), and SO4(2-)) and the Nessler Method was used to obtain the NH4(+) concentrations. The source apportionment of MBAS and DBAS in atmospheric aerosols was identified using a combination of principal component analysis (PCA) and multiple linear regression (MLR). The results revealed that the concentrations of surfactants in atmospheric aerosols and rainwater were dominated by anionic surfactants as MBAS. The concentration of surfactants as MBAS and DBAS was dominated in fine mode compared to coarse mode aerosols. Using PCA/MLR analysis, two major sources of atmospheric surfactants to Lake Chini were identified as soil dust (75 to 93%) and biomass burning (2 to 22%).
This study was conducted to determine the composition of surfactants in the sea-surface microlayer (SML) and atmospheric aerosol around the southern region of the Peninsular Malaysia. Surfactants in samples taken from the SML and atmospheric aerosol were determined using a colorimetric method, as either methylene blue active substances (MBAS) or disulphine blue active substances (DBAS). Principal component analysis with multiple linear regressions (PCA-MLR), using the anion and major element composition of the aerosol samples, was used to determine possible sources of surfactants in atmospheric aerosol. The results showed that the concentrations of surfactants in the SML and atmospheric aerosol were dominated by anionic surfactants and that surfactants in aerosol were not directly correlated (p>0.05) with surfactants in the SML. Further PCA-MLR from anion and major element concentrations showed that combustion of fossil fuel and sea spray were the major contributors to surfactants in aerosol in the study area.
Rural background stations provide insight into seasonal variations in pollutant concentrations and allow for comparisons to be made with stations closer to anthropogenic emissions. In Malaysia, the designated background station is located in Jerantut, Pahang. A fifteen-year data set focusing on ten major air pollutants and four meteorological variables from this station were analysed. Diurnal, monthly and yearly pollutant concentrations were derived from hourly continuous monitoring data. Statistical methods employed included principal component regression (PCR) and sensitivity analysis. Although only one of the yearly concentrations of the pollutants studied exceeded national and World Health Organisation (WHO) guideline standards, namely PM10, seven of the pollutants (NO, NO2, NOx, O3, PM10, THC and CH4) showed a positive upward trend over the 15-year period. High concentrations of PM10 were recorded during severe haze episodes in this region. Whilst, monthly concentrations of most air pollutants, such as: PM10, O3, NOx, NO2, CO and NmHC were recorded at higher concentrations between June and September, during the southwest monsoon. Such results correspond with the mid-range transport of pollutants from more urbanised and industrial areas. Diurnal patterns, rationed between major air pollutants and sensitivity analysis, indicate the influence of local traffic emissions on air quality at the Jerantut background station. Although the pollutant concentrations have not shown a rapid increase, an alternative background station will need to be assigned within the next decade if development projects in the surrounding area are not halted.
This study aims to determine the source apportionment of surfactants in marine aerosols at two selected stations along the Malacca Straits. The aerosol samples were collected using a high volume sampler equipped with an impactor to separate coarse- and fine-mode aerosols. The concentrations of surfactants, as methylene blue active substance and disulphine blue active substance, were analysed using colorimetric method. Ion chromatography was employed to determine the ionic compositions. Principal component analysis combined with multiple linear regression was used to identify and quantify the sources of atmospheric surfactants. The results showed that the surfactants in tropical coastal environments are actively generated from natural and anthropogenic origins. Sea spray (generated from sea-surface microlayers) was found to be a major contributor to surfactants in both aerosol sizes. Meanwhile, the anthropogenic sources (motor vehicles/biomass burning) were predominant contributors to atmospheric surfactants in fine-mode aerosols.
This study aims to determine the levels of methylene blue active substances (MBAS) and ethyl violet active substances (EVAS) as anionic surfactants and of disulphine blue active substances (DBAS) as cationic surfactants in the surface microlayer (SML) around an estuarine area using colorimetric methods. The results show that the concentrations of surfactants around the estuarine area were dominated by anionic surfactants (MBAS and EVAS) with average concentrations of 0.39 and 0.51 μmol L⁻¹, respectively. There were significant between-station differences in surfactant concentrations (p<0.05) with higher concentrations found at the stations near the sea. The concentration of surfactants was higher during the rainy season than the dry season due to the influence of runoff water. Further investigation using total organic carbon (TOC) and total organic nitrogen (TON) shows that there is a significant correlation (p<0.05) between both anionic and cationic surfactants and the TON concentration.