Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia

Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia

Marine Pollution Bulletin xxx (2014) xxx–xxx Contents lists available at ScienceDirect Marine Pollution Bulletin journal homepage: www.elsevier.com/...

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Marine Pollution Bulletin xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul

Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia Shoffian Amin Jaafar a, Mohd Talib Latif a,b,⇑, Chong Woan Chian a, Wong Sook Han a, Nurul Bahiyah Abd Wahid a,c, Intan Suraya Razak a, Md Firoz Khan a,b, Norhayati Mohd Tahir d,e a

School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia Centre for Tropical Climate Change System, Institute for Climate Change (IKLIM), Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia Department of Biology, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim, Perak, Malaysia d Institute of Oceanography and Environment, Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Terengganu, Malaysia e Environmental Research Group, School of Marine Science and Environment, Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Terengganu, Malaysia b c

a r t i c l e

i n f o

Article history: Available online xxxx Keywords: Sea-surface microlayer Marine aerosols Surfactants compositions Source apportionment

a b s t r a c t 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. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction The sea-surface microlayer (SML) is defined as a layer of the ocean’s surface, tens to hundreds of lm deep, which is in direct contact with the atmosphere and where the transfer of chemical compounds is controlled by complex physicochemical processes (Liss and Duce, 2005; Guitart et al., 2007; Cunliffe et al., 2013). According to García-Flor et al. (2005), the SML is enriched by the accumulation of organic compounds such as proteins, carbohydrates, surfactants, lipids, pollutants and other organic residues. These organic compounds have the potential to change the surface properties of the ocean, for example the hydrophobicity (Olkowska et al., 2013). The SML also plays an important role in coastal and eutrophic oceanic regions due to the increased concentration of organic materials with surfactant properties in these areas. These materials have been shown to originate from both anthropogenic and natural sources (Frew et al., 1990; Brinis et al., 2004). A study by Wurl and Obbard (2004) has shown that the amount of dis⇑ Corresponding author at: School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia. Tel.: +60 3 89213822; fax: +60 3 89253357. E-mail address: [email protected] (M.T. Latif).

solved organic matter (DOM) in the SML that has surface-active substances (i.e. surfactants) will influence the energy and mass exchange processes between sea and atmosphere, which may in turn lead to climatic changes (Sukhapan and Brimblecombe, 2002; Mazurek et al., 2008; Schwier, 2012). One proposed mechanism for climatic change is if aerosol particles gain a coating of surfactants, the particles are more likely to initiate cloud droplet formation (Sareen et al., 2012), therefore increasing cloud cover. Increased cloud cover has been shown to result in global temperature changes (Gorbunov et al., 1998; McNeill et al., 2014). Surfactants in the SML will affect the solubility of compounds in the ocean by altering the surface tension of water (Andrews and Larson, 1993; Frew et al., 2004; Laha et al., 2009). As a consequence, the presence of surfactants will influence the distribution of pollutants dissolved in the SML. Organic pollutants, such as polycyclic aromatic hydrocarbons (PAHs), will have elevated solubility in the presence of surfactants, leading to increased concentrations in seawater and negatively affecting water quality (Cincinelli et al., 2001). Studies have shown that the accumulation of surfactants in the SML has a negative effect on aquatic species in both marine and freshwater ecosystems (Olkowska et al., 2014). As shown by previous studies, surfactants are toxic to marine and freshwater species and induce oestrogenic responses in fish

http://dx.doi.org/10.1016/j.marpolbul.2014.05.047 0025-326X/Ó 2014 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Jaafar, S.A., et al. Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia. Mar. Pollut. Bull. (2014), http://dx.doi.org/10.1016/j.marpolbul.2014.05.047

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(Comber et al., 1993; Jobling and Sumpter, 1993; Ivankovic´ and Hrenovic´, 2010). Surfactants in aerosol have been found to affect human health and, at high concentrations, surfactants can disrupt the stability of the human respiratory system and lead to asthma, allergies and dry eyes (Vejrup and Wolkoff, 2002; Zimmer et al., 2002). Surfactants in SML and atmospheric aerosols as methylene blue active substances (MBAS) and disulphine blue active substances (DBAS) can be categorised as several types of organic substances based on their hydrophilic groups. MBAS represents surfactant compounds with a negative charge (anionic) group, such + as carbonyl (RCOOM+), sulfonate (RSO or sulphate 3M )  + (ROSO3 M ). DBAS represents surfactant compounds with a positive charge (cationic) group, such as quaternary ammonium chloride (RN(CH3)3+Cl) (Myers, 1988; Jones-Hughes and Turner, 2005). Environmetric methods are statistical procedures used to determine the complex relationships between a variety of environmental processes (Brown et al., 1994; Alberto et al., 2001). Principal component analysis (PCA), multiple linear regression analysis (MLR), factor analysis (FA), chemical mass balance (CMB) and a combination of these methods have been used to estimate the source apportionment of aerosol composition (Gupta et al., 2006; Srivastava et al., 2008; Mansha et al., 2012). Wahid et al. (2013) used PCA–MLR analysis to determine the source apportionment of surfactants in urban and sub-urban areas and found anthropogenic sources such as motor vehicle emissions and biomass burning, as well as the marine environment, contributed to the amount of surfactants in atmospheric aerosol. The levels of surfactants in atmospheric aerosol was also found to be influenced by the location of sampling stations and associated meteorological factors such as wind direction, temperature and rainfall. The aim of this study was to determine the concentration of surfactants in atmospheric aerosol and the SML in the southern region of Peninsular Malaysia, an area which is influenced by various anthropogenic sources. The surfactants in atmospheric aerosol have been separated into coarse (diameter size, d > 1.5 mm) and fine (diameter size, d < 1.5 mm) mode aerosols. PCA–MLR, based on the anionic and elemental compositions of atmospheric aerosol, has been used to determine the possible sources of surfactants found in atmospheric aerosol. 2. Materials and methods 2.1. Sampling sites Ten sampling stations were chosen to collect samples of the SML, located in the Johor coastal area of Malaysia, facing the Straits of Malacca. From among the ten sampling stations, two nearby locations were also selected for aerosol sampling: Tanjung Piai (T1) and Pontian Kechil (T2). The Tanjung Piai area covers the southernmost tip of Peninsular Malaysia, facing Singapore. This area is affected by shipping, tourism and industrial activities. It is also exposed to emissions from two major ports (Tanjung Pelepas and Singapore Port) and the Tanjung Bin coal-fired power plant. Pontian Kechil is located on the West Coast of Johor, close to the small town of Pontian. The Pontian Kechil coastal area is influenced by shipping, settlements, recreational activities and small-scale fishery activities. Table 1 and Fig. 1 show the sampling locations of the SML (S1–S10) and aerosol (T1–T2). 2.2. Sampling procedures 2.2.1. Sea-surface microlayer (SML) The SML samples were collected between December 2012 and March 2013. About 50–500 mL of the SML were collected at high tide using a glass rotation drum method (Harvey, 1966). Samples

were then kept in the 500 mL glass bottles (Schott, Germany) at 4 °C prior to analysis to prevent the evaporation of the volatile components. 2.2.2. Atmospheric aerosol The aerosol samples were collected between December 2012 and March 2013, using a high volume air sampler (HVAS) (Thermo Scientific Model GS2313-105, USA) in combination with a twostage cascade impactor (Staplex, USA). Slotted filter papers (Westech Instrument, UK) were used to collect coarse mode aerosols (d > 1.5 lm) and backup filter papers (Whatman EPM 2000) were used to collect fine mode aerosols (d < 1.5 lm). The filter papers were wrapped in aluminium foil and pre-heated in a muffle furnace (Carbolite, England) (500 °C, 4 h) to remove any organic contaminants. The filters were then conditioned in a desiccator for at least 24 h, then weighed with an electronic balance (Shimadzu AUX220, Japan) and placed in the HVAS. After installation, the HVAS was placed in an open field near to the sea to avoid any disturbance to the flow of aerosol entering the instrument. The sampling continued for 24 h over a two day campaign at a flow rate of 1.13 m3 min1, giving a total of 18 samples. After sampling, the filter papers were wrapped with aluminium foil and conditioned in desiccators (24 h) before weighing. For quality control purposes, the blank filter papers were prepared in the same way as the filter papers for sampling without turning on the HVAS. 2.3. Sample preparation 2.3.1. Sea-surface microlayer The SML samples were filtered using cellulose acetate filter papers (Whatman, Germany – 47 mm/0.2 lm pore size) and a vacuum filter pump (Millipore, USA). The filtration process was conducted in the clean room. 20 mL of the filtered sample were put into a 40 mL vial for surfactant analysis. 2.3.2. Aerosol sample extraction For the determination of surfactants from the coarse mode aerosol samples, half of the filter papers were used in the extraction processes. For the fine mode samples, a quarter of the filter papers were needed. The filter papers were cut into 1 cm2 pieces and put into a centrifuge tube. 40 mL of ultra-pure water were added to the samples before they were sonicated for 45 min, as undertaken by Roslan et al. (2010), Razak et al. (2013) and Wahid et al. (2013). The ultra-pure water had a resistivity of less than 18.2 MX m and was prepared using an Arium 611DI deionised water system (Sartorius, Germany). The samples were then filtered using cellulose acetate filter papers (Whatman, Germany – 47 mm/0.2 lm pore size) and a vacuum filter pump (Millipore, USA). Samples were diluted to 100 mL with ultra-pure water in a volumetric flask and then stored in glass bottles. Samples for anions and major elements were stored in polyethylene bottles. Both samples were kept in a refrigerator (<4 °C) until further analyses. 2.4. Surfactant analysis 2.4.1. Anionic surfactants as methylene blue active substances (MBAS) The sample solution (20 mL) was put into a 40 mL vial (vial A) equipped with a screw cap and Teflon liner. The alkaline buffer (2 mL) and neutral methylene blue solution (1 mL), followed by chloroform (5 mL), were added to vial A in that order. The vial was closed tightly and was vigorously shaken for two minutes using a vortex mixer. After shaking, the vial was left to allow phase separation and the screw-cap was loosened to release the pressure inside. Once the two phases had separated, a Pasteur pipette was used to transfer the chloroform layer into a new vial (vial B) that contained ultra-pure water (22 mL) and the acid methylene blue

Please cite this article in press as: Jaafar, S.A., et al. Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia. Mar. Pollut. Bull. (2014), http://dx.doi.org/10.1016/j.marpolbul.2014.05.047

S.A. Jaafar et al. / Marine Pollution Bulletin xxx (2014) xxx–xxx

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Table 1 Sampling stations for the sea-surface microlayer (S) and atmospheric aerosol (T). Station

Station name

S1 (T1)

Tanjung Piai Resort

S2

Tanjung Piai National Park

S3

Perpat Timbul

S4

Tanjung Bin Power Station

S5

Kukup Port

S6 S7

Sungai Rambah Recreational Beach Pontian Trade Center Shoreline

S8

Sungai Pontian Kecil

S9 (T2)

SK Tengku Mahmood Iskandar Shah I Shoreline Sungai Pontian Besar

S10

Coordinate 0

00

01°16 56.8 N, 103°300 36.300 E 01°160 06.400 N, 103°300 31.200 E 01°170 44.700 N, 103°260 28.800 E 01°200 30.400 N, 103°320 00.400 E 01°190 33.500 N, 103°260 28.800 E 01°250 38.700 N, 103°240 38.500 E 01°280 39.500 N, 103°230 15.200 E 01°290 05.700 N, 103°230 14.400 E 01°290 21.800 N, 103°230 08.400 E 01°300 28.900 N, 103°220 42.800 E

Description of sampling point One of the main resorts in Tanjung Piai serving tourists Large coastal mangrove reserve area and inter-tidal mudflats Mangrove area near the local settlement The power station is a conventionally designed pulverized coal fired power station A small harbour and port area for transit to Indonesia by ferry Recreational park that is located near the sea, facing the Straits of Malacca and acts as a popular tourist spot A harbour and port area near the town where boats and ships from the north to the south stop to load and unload cargo, leaving for Singapore or Malacca An area near a town and local settlement A small primary school area that is near to the sea and surrounded by mangroves Populated residential area close to the coast with houses built on stilts along the shoreline

Fig. 1. Location of sampling stations.

Please cite this article in press as: Jaafar, S.A., et al. Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia. Mar. Pollut. Bull. (2014), http://dx.doi.org/10.1016/j.marpolbul.2014.05.047

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solution (1 mL). Vial B was shaken for two minutes in a vortex mixer, and then the cap was loosened for few seconds and retightened. Once the chloroform had completely separated from the water (after two minutes) the chloroform layer was collected using a Pasteur pipette and put into a 10 mm quartz cell. The absorbance of the chloroform phase was measured using an UV spectrophotometer (Labomed, Inc., USA) at a wavelength of 650 nm. The limit of detection was 0.05 lM Sodium Dodecyl Sulphate (SDS) (Sigma– Aldrich, USA) and a linear calibration curve was calculated from 0.05 to 2.00 lM SDS (Wahid et al., 2013). The average recovery value for anionic surfactants as MBAS was 87%. 2.4.2. Cationic surfactants as disulphine blue active substances (DBAS) 20 mL of the sample solution were put into a 40 mL vial equipped with a screw cap and Teflon liner. The acetate buffer (2 mL) and disulphine blue solution (1 mL), followed by chloroform (5 mL), were added in that order. The vial was closed tightly and then shaken vigorously for two minutes using a vortex mixer. The cap was loosened for a few seconds to release the pressure and then re-tightened. The vial was left for approximately two minutes until the two phases had completely separated. The chloroform layer was then removed from the vial using a Pasteur pipette and placed into a 10 mm quartz cell. The light absorbance was measured at a wavelength of 628 nm. The lower limit of detection was 0.04 lM Zephiramine (benzyl–dimethyl–tetradecyl– ammonium chloride dehydrate) (Sigma–Aldrich, USA) and a linear calibration curve was formed from 0.05 to 2.00 lM Zephiramine. The average recovery value for cationic surfactants as DBAS measured was 89%. 2.5. Ionic and major element composition Ion Chromatography (Metrohm, 881 Compact IC Pro, USA) was used to determine the anion composition of the aerosol samples. Standards were prepared with four individual standard anion solutions (Merck, USA). A Metrosep A-Supp 5-150/4.0 column, with a flow rate of 0.7 mL min1, was used for ion determination. 6.4 mmol L1 sodium carbonate (Na2CO3) (Merck, Germany) and 2.0 mmol L1 sodium bicarbonate (NaHCO3) (Merck, Germany) were used as eluents, while 100 mmol L1 SuprapurÒsulfuric acid (H2SO4) (Merck, Germany) was used as the suppressor regenerant. 2 F, Cl , NO 3 and SO4 were detected by a conductivity detector with method detection limits of 0.005 lg m3 for F, 0.005 lg m3 3 for Cl, 0.005 lg m3 for NO for SO2 3 and 0.001 lg m 4 . Inductively coupled plasma mass spectrometry (ICP-MS) (PerkinElmer ELAN 9000, USA) was used to determine the major element composition of the aerosol samples. The ICP-MS was calibrated using the PerkinElmer multi-element ICP-MS Standard 3 atomic spectrometry standard. In this study four major elements were analysed: Na, K, Mg and Ca. The detection limits for those major elements are 0.003 lg m3, 0.003 lg m3, 0.004 lg m3 and 0.002 lg m3 respectively with the flow rate of 0.01–0.3 ml min1. 2.6. Quality control Glassware was washed with hexane followed by acetone and deionised water before use. The vials were dipped in a 20% nitric acid bath for 24 h before being heated in a furnace (500 °C, 3 h). Non-powdered gloves were worn and care was taken during the experiment and the handling of filter papers in order to avoid contamination. In addition, all kinds of detergents were avoided in any cleansing purposes. Blank filter papers (the field blanks) were analysed as the control samples for all of the laboratory analyses in this study. The recovery tests for the anions measured were in the range of 96–120% and the recoveries for all major elements measured were recorded in the range of 81–115%.

2.7. Statistical analysis Statistical Package for the Social Sciences (SPSS version 18) was used to analyse all data collected. Several analyses, such as the paired t-test, ANOVA and Pearson correlation, were carried out after the data was found to be normally distributed. Correlation tests were conducted to examine the relationship between the concentrations of anionic and cationic surfactants in the SML. XLSTAT 2012 software was used to obtain the source apportionment of surfactants in the atmosphere, combining principal component analysis (PCA) with multiple linear regressions (MLR). In order to confirm the variables were optimally correlated with one component but had the least correlation with other components, the varimax rotation method from PCA was used (Singh et al., 2004, 2005; Shrestha and Kazama, 2007; Dominick et al., 2012; Wahid et al., 2013). In order to obtain the significant value for the principal component, an eigenvalue greater than one was chosen while the analyses ran. The factor loading after rotation can be classified as strong (>0.75), moderate (0.50–0.75) or weak (<0.50). A factor loading of more than 0.75 was chosen for the MLR for the analysis of source apportionment (Liu et al., 2003). Studies by Chatterjee et al. (1999) and Petrie and Sabin (2000) have suggested that in order to calculate the contribution of each parameter to the level of pollution, prediction of the variability between independent and dependant variables using MLR should be undertaken. Two variables, the factor scores and the anion and elemental concentrations from each sampling site, were used in the MLR models. Both variables were then compared based on the modelling performance referring to the coefficient of determination, R2. According to Norusis (1990), in this technique, the largest R2 value indicates the best linear model. In this study, each anion and elemental concentration variable was independently introduced to a linear regression model with the surfactant concentrations as the dependent variable. After the sources of surfactants were obtained, the contribution of each source was calculated based on the R2 value (Ilten and Selici, 2008; Dominick et al., 2012). 2.8. Trajectory analysis The analysis of the 72 h backward trajectories for wind direction was undertaken using the Hybrid-Single Particle Lagrangian Integrated Trajectory (HYSPLIT 4.9 2009 version) model to determine simulations of pollutant transport in the atmosphere. The wind directions are shown in Fig. 2, indicating the prevailing wind direction (mean and major clusters) at the sampling stations during the sampling period between December 2012 and March 2013. 3. Results and discussion 3.1. Surfactants in the sea-surface microlayer The concentrations of both anionic and cationic surfactants as MBAS and DBAS in the SML are summarised in Table 2. Overall, the concentrations of anionic surfactants were higher compared to cationic surfactants. The concentrations of anionic surfactants ranged between 0.22 lmol L1 and 0.39 lmol L1 and the concentrations of cationic surfactants ranged between 0.18 lmol L1 and 0.35 lmol L1 for all sampling stations. Sampling station S8 was shown to have the highest concentrations of anionic surfactants, whilst the lowest concentrations were recorded at S3. The location of S8 is within an estuarine area that acts as the main sink of pollutants originating from surrounding anthropogenic activities, which may explain the higher levels. The shoreline at S3 is located within a pristine area with minimal human activities, and therefore less

Please cite this article in press as: Jaafar, S.A., et al. Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia. Mar. Pollut. Bull. (2014), http://dx.doi.org/10.1016/j.marpolbul.2014.05.047

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(a) T1

(b) T2 Fig. 2. Prevailing wind direction (mean and major clusters) at the sampling stations (T1 and T2) during the sampling period between December 2012 and March 2013.

Table 2 Concentrations of surfactants in the sea-surface microlayer (n = 9). Stations

Station name

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10

Tanjung Piai Resort Tanjung Piai National Park Perpat Timbul Tanjung Bin Power Station Kukup Port Sungai Rambah Recreational Beach Pontian Trade Centre Shoreline Sungai Pontian Kecil SK Tengku Mahmood Iskandar Shah I Shoreline Sungai Pontian Besar

Concentration of surfactant (lmol L1) MBAS

anthropogenic sources of surfactants, leading to the lower concentrations seen here. For cationic surfactants, S6 recorded the highest values and S1 the lowest values. S6 is located downstream of a river affected by pollutants originating from the surrounding residential and recreational areas. S1 is within a mangrove reserve area that was found to contain less cationic surfactants from anthropogenic sources. The analysis of one-way ANOVA revealed there was no significant difference between the sampling stations (p > 0.05) for both anionic and cationic surfactants in the SML. The correlation analysis also revealed no significant relationship (p > 0.05) between anionic and cationic surfactants in the sea-surface microlayer.

0.27 ± 0.02 0.26 ± 0.01 0.26 ± 0.02 0.27 ± 0.02 0.27 ± 0.02 0.29 ± 0.04 0.28 ± 0.03 0.30 ± 0.05 0.28 ± 0.03 0.27 ± 0.02

DBAS (0.25–0.31) (0.25–0.29) (0.23–0.31) (0.24–0.30) (0.24–0.30) (0.24–0.35) (0.25–0.34) (0.25–0.39) (0.22–0.31) (0.24–0.32)

0.23 ± 0.03 0.24 ± 0.02 0.23 ± 0.03 0.23 ± 0.03 0.23 ± 0.02 0.27 ± 0.05 0.26 ± 0.04 0.24 ± 0.04 0.25 ± 0.03 0.26 ± 0.04

(0.18–0.29) (0.19–0.26) (0.20–0.29) (0.19–0.27) (0.20–0.28) (0.21–0.35) (0.20–0.33) (0.19–0.34) (0.22–0.30) (0.23–0.33)

Anionic surfactant concentrations in the SML at each station were higher compared to cationic surfactant concentrations. This is probably due to the wide use of anionic surfactants in various manufacturing industries (Myres, 2006; Khan et al., 2010; Olkowska et al., 2011). The average concentration of anionic surfactants in the samples from the study area is much higher than in studies conducted by Roslan et al. (2010), Hanif et al. (2011) and Latif et al. (2012) (Table 3). This is probably because this study area is exposed to anthropogenic sources from industrial activities, shipping activities and domestic cleaning activities within residential areas. According to Scott and Jones (2000), surfactants were

Please cite this article in press as: Jaafar, S.A., et al. Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia. Mar. Pollut. Bull. (2014), http://dx.doi.org/10.1016/j.marpolbul.2014.05.047

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Table 3 Comparison of surfactant concentrations in the SML between this study and previous studies in Peninsular Malaysia. Location

Tanjung Piai Pontian Lake Chini Lake Kenyir Bayan Lepas Port Dickson Muar Kapas Island

Surfactant concentration (lmol L1) MBAS

DBAS

0.28 ± 0.07 0.29 ± 0.04 0.15 ± 0.13 0.01 ± 0.04 0.30 ± 0.05 0.36 ± 0.34 0.15 ± 0.03 0.05 ± 0.02

0.23 ± 0.03 0.26 ± 0.04 0.10 ± 0.02 n.d 0.13 ± 0.07 0.21 ± 0.13 0.11 ± 0.04 0.11 ± 0.02

Table 6 Average concentration (n = 9) of anion and major element compositions in aerosols. Elements

Source

This study This study Latif et al. (2012) Hanif et al. (2011) Roslan et al. (2010) Roslan et al. (2010) Roslan et al. (2010) Roslan et al. (2010)

n.d = Not detected.

found to be increased by the dispersal of oil spills resulting from boats and ships. This implies that shipping would have a large impact on the surfactant levels found in this study. For cationic surfactants, a major contributor could be decaying plant matter from the mangrove area. According to Miller (1982) the decay of plant matter can convert a large amount of organic nitrogen to the water-soluble salts containing ammonium ions. As cationic surfactants have positive charges such as the ammonium ion, it can be concluded that cationic surfactants can come from decaying plants (Kristensen et al., 2008; Ke et al., 2009). 3.2. Aerosol and surfactants in the marine atmosphere Table 4 shows the average concentrations of anionic and cationic surfactants (as MBAS and DBAS) in aerosol for Tanjung Piai (T1) and Pontian (T2). The total concentrations of coarse and fine mode aerosols are below the concentration for total suspended particulate (TSP) suggested by the Recommended Malaysian Air Quality Guideline (260 lg m3). Generally, the concentrations of surfactants in atmospheric aerosol were also dominated by anionic rather than cationic surfactants. The range of anionic surfactants was between 39 pmol m3 and 63 pmol m3 for coarse mode aerosol and between 80 pmol m3 and 200 pmol m3 for fine mode aerosol. The concentration of cationic surfactants in coarse mode

Concentration (lg m3) Coarse

Fine

Anions F Cl NO 3 SO2 4

0.07 ± 0.12 (0.03–0.39) 1.6 ± 0.76 (0.55–2.8) 1.4 ± 1.1 (0.40–3.2) 1.2 ± 0.57 (0.41–2.3)

0.07 ± 0.04 (0.02–0.12) 0.57 ± 0.23 (0.32–1.0) 1.0 ± 0.59 (0.57–2.1) 11 ± 7.5 (1.4–21)

Major Elements K Ca Mg Na

0.18 ± 0.04 0.08 ± 0.02 0.08 ± 0.08 1.3 ± 0.47

0.13 ± 0.06 (0.07–0.24) 0.25 ± 0.10 (0.12–0.40) 0.16 ± 0.19 (0.02–0.49) 6.9 ± 6.6 (1.3–6.6)

(0.13–0.24) (0.05–0.10) (0.01–0.19) (0.67–1.9)

aerosol ranged between 22 pmol m3 and 54 pmol m3, and in fine mode aerosol ranged between 42 pmol m3 and 54 pmol m3. The concentration of anionic surfactants in the aerosol was found to be higher at T1 compared with T2. This may be due to the location of T1, which is near to an industrial area and port. According to Ying (2006), higher concentrations of anionic surfactants in the air are caused by the chemicals used by industry and motor vehicles. Anionic surfactants also potentially originate from humus materials (Scott and Jones, 2000; Ying, 2006). For cationic surfactants at T1, the concentrations were higher in fine mode aerosol. A study by Latif (2006) has shown that cationic surfactants usually originate from soil emissions where there are abundant nitrogen substances. This is due to the degradation of plant and insect matter, which convert to water-soluble salts containing ammonium ions (Miller, 1982). It is interesting to note that, even though the distance between sampling points and the sea was considerable, the SML can also be considered as one of the possible sources surfactants in the aerosol samples. A study by Smoydzin and von Glasow (2006) showed that a proportion of the surfactants in the SML can originate from bubbles bursting on the ocean surface, where the organic matter can be directly incorporated into marine particles. In terms of particle size, surfactant concentrations in fine mode aerosol are found to be higher compared to those in coarse mode

Table 4 Average concentration of aerosol and surfactants (n = 9) recorded at Tanjung Piai (T1) and Pontian (T2) stations. Values in parentheses show the range of minimum and maximum. Stations

Mode

Aerosol concentration (lg m3)

MBAS (pmol m3)

DBAS (pmol m3)

Tanjung Piai (T1)

Coarse Fine Total

16 ± 4.1 (10-23) 26 ± 6.0 (19–36) 43 ± 9.2 (30–56)

54 ± 4.2 (50–63) 134 ± 33 (94–200) 188 ± 31 (149–250)

27 ± 3.2 (22–32) 49 ± 3.2 (42–54) 76 ± 6.0 (64–85)

Pontian (T2)

Coarse Fine Total

10 ± 3.2 (5.8–17) 17 ± 3.2 (11–23) 21 ± 6.8 (17–40)

46 ± 6.6 (39–46) 85 ± 10 (80–94) 130 ± 12 (120–140)

27 ± 1.6 (27–54) 50 ± 4.7 (47–54) 78 ± 5.1 (47–83)

Table 5 Comparison of surfactant concentrations in aerosol between this study and previous studies in Peninsular of Malaysia. Location

Surfactant concentration (pmol m3) MBAS

Tanjung Piai (T1) Pontian (T2) Tasik Chini Bayan Lepas Port Dickson Muar Pulau Kapas

Source DBAS

Coarse mode

Fine mode

Coarse mode

Fine mode

54 ± 4.2 46 ± 6.6 51 ± 0.0 53 ± 25 50 ± 26 45 ± 20 15 ± 1.6

134 ± 33 85 ± 10 82 ± 14 171 ± 56 229 ± 155 220 ± 56 36 ± 12

27 ± 3.2 27 ± 1.6 51 ± 0.10 26 ± 21 46 ± 26 29 ± 6.1 52 ± 7.7

49 ± 3.2 50 ± 4.7 30 ± 18 33 ± 4.8 52 ± 16 46 ± 6.3 130 ± 59

This study This study Latif et al. (2012) Roslan et al. (2010) Roslan et al. (2010) Roslan et al. (2010) Roslan et al. (2010)

Please cite this article in press as: Jaafar, S.A., et al. Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia. Mar. Pollut. Bull. (2014), http://dx.doi.org/10.1016/j.marpolbul.2014.05.047

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S.A. Jaafar et al. / Marine Pollution Bulletin xxx (2014) xxx–xxx Table 7 The factor loading after varimax rotation using PCA. Elements

F Cl NO 3 SO2 4 K Ca Mg Na Eigenvalue Variability (%) Cumulative (%) a

Coarse

Fine

F1 Sea spray/combustion of biomass

F2 Fossil fuel combustion/dust

F1 Burning of fossil fuels

F2 Sea spray/combustion of biomass

0.56 0.83a 0.01 0.22 0.95a 0.22 0.73a 0.96a 3.53 44.13 44.13

0.35 0.21 0.98a 0.95a 0.12 0.89a 0.62 0.20 3.18 39.71 83.84

0.97a 0.95a 0.96a 0.94a 0.17 0.67 0.56 0.28 4.54 56.73 56.73

0.03 0.01 0.05 0.24 0.97a 0.57 0.80a 0.95a 2.84 35.45 92.18

Factors in bold indicated as strong factors.

aerosol in both areas studied. These finding are similar to those of Roslan et al. (2010) and Latif et al. (2012) (Table 5). According to Cincinelli et al. (2001), fine mode aerosol disperses over greater distances than coarse mode aerosol. A study by Latif et al. (2005) showed that the combustion of fossil fuels, especially diesel, contributed to most of the surfactant content in the fine mode aerosol. This indicates that the sampling area was likely to have been affected by the combustion of diesel as the sampling area is in close proximity to extensive shipping activities. 3.3. Anionic and major elemental compositions of aerosol The anion and major element concentrations in aerosol are shown in Table 6. Concentrations of anions were in the following    2 order: SO2 concentrations may 4 > NO3 > Cl > F . The high SO4 originate from the coal-fired power generation plant located northeast (8 km) of the sampling station (T1). This is supported by the HYSPLIT modelling (Fig. 2) which indicates that the wind came from the northeast during the sampling period. According to Querol et al. (1999) the major pollutants resulting from coal-fired power plants were suspended particles containing SO2 4 ions. The sequence for the major elements concentration was Na > Mg >

(a) Source of MBAS in coarse mode aerosol

(c) Source of DBAS in coarse mode aerosol

Ca > K. The high Na concentrations were probably due to the proximity of the sampling stations to the sea, contributing to the high concentration of sea salt. According to Whipkey et al. (2000), a large amount of suspended particles originating from the sea can be blown inland.

3.4. Source apportionment of surfactants The factor loading, after varimax rotation using PCA, is tabulated in Table 7. The analyses have extracted two strong factors for each data set analysed in this study. In the fine mode aerosol,  the first factor (F1) is dominated by F, followed by NO 3 , Cl and 2 SO4 . A study by Ando et al. (2001) states that the burning of coal is the main source of F. The high levels of F in the samples analysed in this study was probably due to the coal-fired power generation plant near the sampling station. Both the first factor (F1) in coarse mode aerosol and second factor (F2) in fine mode aerosol are dominated by Na, Mg and K. These are believed to result from sea spray and biomass burning (Cheng et al., 2000; Viana et al., 2008). The second factor (F2) for coarse mode aerosol is dominated 2 by NO 3 and SO4 , stemming from the combustion of fossil fuels

(b) Source of MBAS in fine mode aerosol

(d) Source of DBAS in fine mode aerosol

Fig. 3. Contributions of possible sources of surfactants in atmospheric aerosol.

Please cite this article in press as: Jaafar, S.A., et al. Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia. Mar. Pollut. Bull. (2014), http://dx.doi.org/10.1016/j.marpolbul.2014.05.047

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S.A. Jaafar et al. / Marine Pollution Bulletin xxx (2014) xxx–xxx

(Querol et al., 1999), and Ca, possibly originating from crustal dust (Viana et al., 2008). Fig. 3 shows the distribution of sources of pollutants contributing to surfactants in aerosol. Overall, the concentrations of surfactants in the study area were influenced by four main factors: fossil fuel combustion, sea spray, biomass burning and crustal dust. Referring to Fig. 3(a), the main factor affecting anionic surfactants in coarse mode aerosol was fossil fuel combustion and crustal dust (67%) whilst the secondary factor was sea spray and biomass burning (33%). In fine mode aerosol (Fig. 3(b)) fossil fuel combustion was the key factor affecting the concentration of anionic surfactants (99%) compared with other sources (1%). This is likely to be caused by the nearby power plant and shipping activities (Querol et al., 1999). The sources for cationic surfactants in coarse mode aerosol are shown in Fig. 3(c). These results show that the dominant source for cationic surfactants was fossil fuel combustion and crustal dust (92%). The crustal dust is believed to originate from coastal areas to the east of the sampling stations as dust is easily transported to other areas by the wind. Fig. 3(d) shows that the main factors influencing cationic surfactants in fine mode aerosol are the combustion of biomass burning and sea spray (36%) and fossil fuels (64%). The sea spray factor is higher than any other factor, most likely due to the sampling stations close proximity to the sea, resulting in high concentrations of Na and Mg in the aerosol samples (Cheng et al., 2000). 4. Conclusions This study has shown the levels of anionic and cationic surfactants from the SML and atmospheric aerosol samples collected in the southern coastal area of Peninsular Malaysia. Anionic surfactants as MBAS were dominant over cationic surfactants as DBAS in both the SML and aerosol. In the SML, the average concentration of anionic surfactants was 0.28 lmol L1 and the average concentration of cationic surfactants was 0.24 lmol L1. In aerosol, the average concentration of anionic surfactants was 188 pmol m3 at Tanjung Piai (T1) and 130 pmol m3 at Pontian (T2), while the average concentrations of cationic surfactants were 76 pmol m3 and 78 pmol m3 respectively. No significant difference (p > 0.05) was found between sampling stations for both surfactants in the SML and aerosol. This may be due to similar sources influencing the level of surfactants around the area. The Principal Component Analysis with Multiple Linear Regression (PCA–MLR) showed that the source apportionment of surfactants in both fine and coarse mode aerosols was dominated by fossil fuel combustion (64– 99%) and sea spray (8–33%). Coal fired power plant nearby, diesel exhaust from ships, as well as small fuel leakages, were also shown to be sources of surfactants both in the SML and aerosol. Due to the negative impacts of surfactants in the environment – they can solubilise pollutants in the ocean and affect human health we recommend that comprehensive and regular monitoring is carried out, covering a wider area. We also recommend that the emissions from the coal-fired power plant and shipping activities are monitored and new technologies proposed to minimise the affect of these anthropogenic surfactants have on the marine environment. As the sampling was carried out in a coastal area, future research could include the effect of meteorological factors such as wind speed, wind direction, temperature and pressure as well as considering the effects of monsoon in Malaysia. Acknowledgements We are very thankful to the Ministry of Science, Technology and Innovation of Malaysia (MOSTI) and Universiti Kebangsaan Malaysia

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Please cite this article in press as: Jaafar, S.A., et al. Surfactants in the sea-surface microlayer and atmospheric aerosol around the southern region of Peninsular Malaysia. Mar. Pollut. Bull. (2014), http://dx.doi.org/10.1016/j.marpolbul.2014.05.047