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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.

This study aims to determine the concentrations of surfactants on the sea-surface microlayer and in atmospheric aerosols from several coastal areas along the Malacca Straits. The concentrations of surfactants from the sea-surface microlayer (collected using rotation drum) and aerosols (collected using HVS) were analysed as Methylene Blue Active Substances (MBAS) and Disulphine Blue Active Substances (DBAS) by colorimetric method using a UV–visible spectrophotometer. The results of this study show the average concentrations of surfactants in the sea-surface microlayer ranged between undetected and 0.36 ± 0.34 μmolL−1 for MBAS and between 0.11 ± 0.02 and 0.21 ± 0.13 μmolL−1 for DBAS. The contribution of surfactants from the sea-surface microlayer to the composition of surfactants in atmospheric aerosols appears to be more dominant in coarse mode aerosols. Other anthropogenic sources such as regional biomass burning can also contribute to the amount of atmospheric surfactants as MBAS.

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.

A study has been conducted to determine the composition of surfactants in runoff water in the semi-urban area of Bandar Baru Bangi, Selangor, Malaysia. Runoff samples were collected from five different locations with contrasting functional activities and the colorimetric method was used to analyze the concentrations of surfactants as methylene blue active substances (MBAS) for anionic surfactants and as disulphine blue active substances (DBAS) for cationic surfactants. The results showed that the highest surfactant concentrations of MBAS and DBAS in runoff water were recorded in the samples collected at the residential area, with the concentrations of 3.192 ± 0.727 and 0.170 ± 0.028 μmol/L, respectively. Anionic surfactants as MBAS were found to dominate the concentration of surfactants in both runoff and rainwater. The concentrations of both anionic and cationic surfactants in runoff water were recorded as being higher than in rainwater.

In recent years, the arisen of air pollution in urban area address much attention globally. The air pollutants has emerged detrimental effects on health and living conditions. Time series forecasting is the important method nowadays with the ability to predict the future events. In this study, the forecasting is based on 10 years monthly data of Air Pollution Index (API) located in industrial and residential monitoring stations area in Malaysia. The autoregressive integrated moving average (ARIMA), fuzzy time series (FTS) and artificial neural network (ANNs) were used as the methods to forecast the API values. The performance of each method is compare using the root mean square error (RMSE). The result shows that the ANNs give the smallest forecasting error to forecast API compared to FTS and ARIMA. Therefore, the ANNs could be consider a reliable approach in early warning system to general public in understanding the air quality status that might effect their health and also in decision making processes for air quality control and management.

Air quality studies were carried out in the towns of Putrajaya, Petaling Jaya and Nilai in the Malaysian Peninsular. In this study, the variations of Ozone (O3) concentrations over a four year period (2008-2011) were investigated using data obtained from the Malaysian Department of the Environment (DOE). This study aims to identify and describe the daily and monthly variations of O3 concentrations at the monitoring sites mentioned. The SPPS program (Statistical Package for the Social Science) was used to analyze this data in order to obtain the variations of O3 and also to clarify the relationship between the stations. The findings of the study revealed that the highest concentration of O3 occurred during the midday and afternoon (between 13:00-15:00 hrs). The comparison between stations also showed that highest O3 concentrations were recorded in Putrajaya. The comparisons of average and maximum concentrations of O3 for the three stations showed that the strongest significant correlation was recorded in the Petaling Jaya station with the value R2= 0.667. Results from this study indicate that in the urban areas of Peninsular Malaysia, the concentration of O3 depends on the concentration of NOx. Furthermore, HYSPLIT back trajectories (-72h) indicated that air-mass transport patterns can also influence the O3 concentration in the areas studied.

Prediction of ozone (O3) is very important because O3 gives effects on human health, human activities and more. Nonlinear prediction method, a method which was developed based on the idea comes from chaos theory is used to predict the concentrations of O3. There are two steps in the nonlinear prediction method. First is the reconstruction of the observed data from the form of a one-dimensional to multi-dimensional phase space. Second is the prediction of the reconstructed phase space through local linear approximation method. Hourly O3 concentrations observed in Shah Alam city located in the state of Selangor, Malaysia were studied. Predictions found in a close agreement with those observed ones. The value of the correlation coefficient obtained in this study is 0.9097. This demonstrates the suitability of the nonlinear prediction method to predict the hourly concentrations of O3. At the end of this paper, suggestions were made for better prediction in the future.

Measurements of PM10 and water-soluble ions were carried out on indoor and outdoor PM10 (particles > 10 μm in aerodynamic diameter) aerosols sampled at selected primary schools of Kuala Lumpur (S1) and Putrajaya (S2), respectively. Samples were collected using a low volume sampler on Teflon filters. The water-soluble ions chloride (Cl−), nitrate (NO3−), sulfate (SO42−), calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+) and ammonium (NH4+) was analyzed using ion chromatography. The results showed that the indoor PM10 mass concentrations in S1 and S2 were 96.6 and 69.5 μg/m3, while the outdoor PM10 mass concentrations were 80.1 and 85.2 μg/m3, respectively. This indicated that NO3− were the most dominant ions, followed by SO42−, Ca2+, K+ and Na+, while Cl−, Mg2+ and Na+ were present at low concentrations. Pearson's correlation test applied to all the data showed high correlation between SO42− and NO3−, indicating a common anthropogenic origin. In addition, the correlations between Na+ and Ca2+ ...

Surfactant in marine environment has been recognized to influence the biogeochemical cycle in atmosphere. This study aims to determine the concentration of surfactants in sea-surface microlayer (SML) and atmospheric aerosol at selected coastal area of Peninsular Malaysia. The sampling activities has been carried out between February 2012 and January 2013 using rotation drum to collect SML samples and a High Volume Sampler (HVS) equipped with two cascade impactor to collect fine and coarse mode aerosols. The Colorimetric method has been applied to determine surfactants as MBAS and DBAS using UV-Vis Spectrophotometer. Trajectory analysis was done using online-based HYSPLIT model in order to determine the influence of wind direction on surfactants concentrations. Overall, anionic surfactant as MBAS was dominated in SML with a range 0.19–0.24 μmolL−1. Surfactants in atmospheric aerosol was found to be dominant in fine mode aerosol (MBAS = 62.79−171.30 pmolm−3, DBAS = 29.41–182.86 pmolm−3) influenced by northeast monsoon.

This study was conducted to determine the composition and source apportionment of surfactant in atmospheric aerosols around urban and semi-urban areas in Malaysia based on ionic compositions. Colorimetric analysis was undertaken to determine the concentrations of anionic surfactants as Methylene Blue Active Substances (MBAS) and cationic surfactants as Disulphine Blue Active Substances (DBAS) using a UV spectrophotometer. Ionic compositions were determined using ion chromatography for cations (Na(+), NH4(+), K(+), Mg(2+), Ca(2+)) and anions (F(-), Cl(-), NO3(-), SO4(2-)). Principle component analysis (PCA) combined with multiple linear regression (MLR) were used to identify the source apportionment of MBAS and DBAS. Results indicated that the concentrations of surfactants at both sampling sites were dominated by MBAS rather than DBAS especially in fine mode aerosols during the southwest monsoon. Three main sources of surfactants were identified from PCA-MLR analysis for MBAS in fine mode samples particularly in Kuala Lumpur, dominated by motor vehicles, followed by soil/road dust and sea spray. Besides, for MBAS in coarse mode, biomass burning/sea spray were the dominant source followed by motor vehicles/road dust and building material.

In this study, rhizobacteria were isolated from the roots of Scirpus mucronatus grown in diesel-contaminated soil. In a range finding test, microorganisms were isolated from soils contaminated with diesel in concentrations of 0, 10, 20, 100, and 200 g/kg. The number of colonies isolated was 38. After morphological and chemical tests, the number of bacteria colonies isolated was reduced from 38 to 35 bacteria. Of these, 23 bacterial isolates survived on 9 and 15% diesel-spiked mineral salt medium (MSM) after 5 days of exposure. Vitek® 2 Compact (France) identified three species of bacteria that could survive in the diesel-spiked plates, namely, Sphingomonas paucimobilis, Rhizobium radiobacter, andBacillus pumilus. Key words: Rhizobacteria, diesel-tolerant, Scirpus mucronatus, phytoremediation, range finding test.

The indoor and outdoor air quality at four residential buildings in Shah Alam, Selangor was investigated. The concentrations of carbon monoxide (CO), carbon dioxide (CO 2 ), and particulate matters (PM 10 ) in outdoor and indoor of the houses were determined for 8 hour period. The mean concentration of CO, CO 2 and PM 10 indoor was in the range 0.24–0.31 ppm, 437.18–549.57 ppm and 94.00–124.00 μg/m3 respectively. The results indicated that all of the average indoor concentrations of CO, CO 2 , and PM 10 were below the limit of Malaysian guideline standards. The indoor/outdoor concentration ratios of all air pollutants were found to be below one, except for CO 2 which seems to be affected by outdoor sources of origin.

This study investigated the relationship between urban and rural ozone concentrations and quantified the extent to which ambient rural conditions and the concentrations of other pollutants can be used to predict urban ozone concentrations. The study describes the variations of ozone in weekday and weekends as well as the daily maximum recorded at selected monitoring stations. The results showed that Putrajaya station had the highest concentrations of O3 on weekend due the titration of NO during the weekday. Additionally, Jerantut had the lowest average concentration with a reading value high on Wednesdays. The comparisons of average and maximum concentrations of ozone for the three stations showed that the strongest significant correlation is recorded in Jerantut station with the value R2= 0.769. Ozone concentrations originating from a neighbouring urban site form a better predictor to the urban ozone concentrations than widespread rural ozone at some levels of temporal averaging. It is found that in urban and rural of Malaysian peninsular, the concentration of ozone depends on the concentration of NOx and seasonal meteorological factors. The HYSPLIT Model (the northeast monsoon) showed that the wind direction can also influence the concentration of ozone in the atmosphere in the studied areas., {"references":["Y.N. Ahammed, R.R. Reddy, K.R. Gopal, K. Narasimhulu, D.B. Basha,\nL.S.S. Reddy, and T.V.R. Rao, \"Seasonal variation of the surface ozone\nand its precursor gases during 2001-2003 measured at Anantapur\n(14.628N), a semi-arid site in India,\" Atmospheric Research, Vol. 80\npp.151-164, 2006.","R. Atkinson,\"Atmospheric chemistry of VOCs and NOx,\" Atmospheric\nEnvironment, Vol. 34, pp. 2063-2101, 2000.","G. Beaney, and W.A. Gough, \"The influence of tropospheric ozone on\nthe air temperature of the city of Toronto, Ontario, Canada,\"\nAtmospheric Environment, Vol. 36, pp. 2319-2325, 2002.","G. Chand, and S. 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Khoder, \"Diurnal, seasonal and weekdays-weekends variations of\nground level ozone concentrations in an urban area in greater Cairo,\"\nEnvironmental Monitoring and Assessment, Vol.149, pp. 349-362, 2009.\n[15] S. Lal, M. Naja, and B.H. Subbaraya, \"Seasonal variations in surface\nozone and its precursors over an urban site in India,\" Atmos. Environ,\nVol. 34, pp. 2713-2724, 2000.\n[16] Y.C. Lee, M. Wenig, and X. Yang, \"The emergence of urban ozone\nepisodes in autum and air temperature rise in Hong Kong,\" Air Quality.\nAtmosphere Health, Vol. 2, pp. 111-121, 2009.\n[17] L.C. Marr, and R.A. Harley, \"Modeling the Effect of Weekday Weekend\nDifferences in Motor Vehicle Emissions on Photochemical Pollution in\nCentral California,\" Environ. Sci. Technol, Vol. 36, pp. 4099-4106,\n2002a.\n[18] L.C. Marr, and R.A. Harley, \"Spectral Analysis of Weekday Weekend\nDifferences in Ambient Ozone, Nitrogen Oxide and Non-methane\nHydrocarbon Time Series in California,\" Atmos. 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Surfactants in atmospheric aerosols determined as methylene blue active substances (MBAS) and ethyl violet active substances (EVAS). The MBAS and EVAS concentrations can be correlated with surface tension as determined by pendant drop analysis. The effect of surface tension was more clearly indicated in fine mode aerosol extracts. The concentration of MBAS and EVAS was determined before and after ultrafiltration analysis using AMICON centrifuge tubes that define a 5000 Da (5 K Da) nominal molecular weight fraction. Overall, MBAS and to a greater extent EVAS predominates in fraction with molecular weight below 5 K Da. In case of aerosols collected in Malaysia the higher molecular fractions tended to be a more predominant. The MBAS and EVAS are correlated with yellow to brown colours in aerosol extracts. Further experiments showed possible sources of surfactants (e.g. petrol soot, diesel soot) in atmospheric aerosols to yield material having molecular size below 5 K Da except for humic acid. The concentration of surfactants from these sources increased after ozone exposure and for humic acids it also general included smaller molecular weight surfactants.

Vetiver grass and it usages have been widely investigated in many researches as the preferred plant species due to its known efficiency, low cost, the ease of availability and spread. This research aimed to use four different vetiver grass (Vetiveria zizanioides) ecotypes to remove cyanide (CN-)-contaminated water for improve its quality. Growth capability, tolerance and removal efficiency were evaluated. The results showed that the vetiver grass had a 100% survival rate for one month after planting. Songkhlar3 had the longest leaves, followed by Surat-Thani, Sri Lanka and Monto, respectively. Root lengths of all ecotypes showed no significant differences (p ≤ 0.05). All vetiver grass ecotypes could potentially purify CN--contaminated water at lower concentrations of ≤ 35 mg CN-/L. The Monto ecotype had the highest CN- removal efficiency at all CN- concentration levels, showing 100% CN- removal from the 5-45 mg CN-/L contaminated water samples within 2-5 weeks growth. The tolerance of vetiver grass to CN- was a more important factor than growth rate when selecting a vetiver grass ecotype for CN- phytoremediation.

The concentration and characteristics of anionic and cationic aerosol surfactants at a range of locations were determined as methylene blue active substances (MBAS) and ethyl violet active substances (EVAS) for anionic surfactants and as disulfine blue active substances (DBAS) for the cationic surfactants. Results showed that the anionic surfactants (in the pmol m(-3) range) dominated the concentration of surfactant in atmospheric aerosols. The concentration of both MBAS and EVAS is typically higher on the finer aerosol fractions. Further study on the aerosols found both MBAS and EVAS had the ability to reduce the surface tension of aqueous extracts of the aerosol. MBAS were more readily destroyed on exposure to a high intensity of UV light than were EVAS. The source of these seemingly ubiquitous compounds is not clear, but we note that anionic surfactants are easily derived from degraded or oxidized soots, especially that from diesel engines.

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.

Environmental Context.Surfactants are present in all atmospheric aerosols with potential effects on surface tension, cloud droplets and even human health. They appear to be anionic and associated with yellow aqueous extracts, suggesting a humic-like character. These surfactants are probably derived from the oxidation of combustion-generated soot (from vehicles and forest fires). Abstract.The concentration of surfactants in aerosols was determined at several sites in South East Asia, Bangi, Penang and Kota Kinabalu in Malaysia and Bangkok, Thailand, as methylene blue active substances (MBAS) and ethyl violet active substances (EVAS) for anionic surfactants and disulphine blue active substances (DBAS) for cationic surfactants. The methodology used is based on the formation of extractable ion-association complexes of surfactants and dye in organic solvents followed by spectrometric measurement of the intensity of the extracted coloured complex. Results showed surfactants in aerosols are mostly in the anionic form as MBAS and EVAS, and higher in aerosols collected in congested areas, especially in times of forest fires. Concentrations are in the range of 34.6 to 285.0 pmol m−3 for MBAS and 129.9 to 932.2 pmol m−3 for EVAS. Several different types of soot and humic acid seem possible sources of surfactants in atmospheric aerosols. Laboratory experiments suggested that combustion products, especially from motor vehicles, are important primary sources of surfactants in aerosols. There is also some laboratory evidence that there are secondary sources for these surfactants in aerosols, possibly humic-like substances (HULIS) from the oxidation and photochemical reaction of soots and humic acid.

In recent decades there has been surprisingly little research on surface-active compounds in the atmosphere. Why should we care, you ask? Are surfactants such a big deal? We know how anthropogenic surfactants in sea spay in some areas led to the death of long-established beach front pines, but is there a broader impact of atmospheric surfactants? Well, indeed there is, and it is the subject of continuing discussion and speculation. In the 1970s, a number of investigators studying organic micropollutants considered the existance of surface-active compounds in the atmosphere. Long-chain carboxylic acids were seen as a likely source of surface activity. There was also a growing interest in the potential of the sea surface microlayer to accumulate organic compounds and complexed metals, and to possibly transport the materials into the atmosphere during bubble bursting.[1,2] Appel et al. found some two thirds of the non-carbonate carbon in aerosols to be surface active.[3] By the early 1980s Seidl and Hanel[4] and Gill et al.[5] had established the presence of surface-active substances in both rainwater and aerosols, but only at some 50 picomoles per cubic metre, or 10% of total aerosol mass.This was so low that there was little chance that these compounds would play an important role in reducing droplet size or altering the rate of transfer of water to and from droplets. Despite this, Winfried Seidl[6] retained an interest in surfactants into the current millennium reasserting the point that soluble surfactants in rainwater behaved as if they were the expected long-chain carboxylic acids, recently identified using TOF-SIMS.[7] The early 21st century has seen a re-emergence of research on atmospheric surfactants along with a great deal of speculation about the potential role they might play. This interest has paralleled a rising number of papers on water-soluble organic materials and the awareness of the ubiquitous presence of humic-like substances (HULIS) in the atmosphere. Thus atmospheric surfactants have recently re-emerged with much of the enthusiasm they found among marine aerosol chemists a quarter-century ago. The current work on atmospheric surfactants now seems far-reaching and imaginative. Dobson et al.[8] have championed a role for such compounds in the origin of life. They propose an inverted micelle model for aerosol structure where the surfactants coat the aqueous core. The surfaceactive organic compounds have their hydrocarbon tails facing into the atmosphere and more polar ends in the water. In this way organic materials that accumulated at the surface of an early ocean would, once ejected as aerosols, have the high concentrations of materials necessary for the origin of life. Evidence of this process would have long been lost, but not the excitement such speculation has brought in allowing aerosol science to interact with exobiology. An equally broad vision comes from Cristina Facchini and her colleagues, who conceived that surface activity may play a role in controlling global climate. It had long been clear that surface tension was an important control on droplet size and aerosol activation,[9] but the re-interest in surfactants reminds us that the small changes in droplet populations they induce could alter cloud albedo and as well as the formation of precipitation;[10,11] yet another mechanism for natural and anthropogenic climate forcing. The sea surface microlayer is once again of interest. Caterina Oppo has, for some years, been studying the potential of the ocean surface to redistribute trace substances, through bubble bursting. This could be important in the mobilization of micropollutants at a global level. In an era where it is no longer generally believed that metals are strongly bound within the sea surface microlayer, attention has turned more towards the organic materials here as a mode of transfer to the atmosphere. Thus we have seen studies of the accumulation of polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and tributyltin at the sea surface.[12] Surfactants can certainly solubilize materials, so they might also increase the bioavailability, especially that of relatively non-polar compounds. However atmospheric scientists are not always aware of the relevance of lipids as surfactants in biological systems. The pulmonary surfactant that coats the human lung is much affected by air pollutants. Ozone and trace metals can oxidize this material, reducing gas exchange.[13] Although particles are known to interact with pulmonary surfactants,[14] the effect of