Oil Pollution Sources In Surface Sediments Biology Essay

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Oil pollution has been introduced into South China Sea aquatic environment through three anthropogenic sources which are by discharging the oil during extraction, transportation and consumption. In order to determine the source of oil pollution in South China Sea, 30 surface sediment samples were collected in 2008 and were analyzed for pentacyclic triterpanes (hopane) by GCMS with m/z 191. The total concentrations of hopane compounds were ranging from 1.50 to 1331.74 µg/g which indicate South China Sea have faced various types of oil pollution sources. This study also investigate the utilities and limitation of hopane as oil pollution source identification for surface sediment samples collected from South China Sea and the applicability of the biomarker approach to determine the origin of oil-derived sediment. 17α(H),21β(H)- norhopane and C31-C 35 homohopane were found to be abundant in Middle East crude oil and also can be found in some of the surface sediment samples in this study. The diagnostic ratio of 17α(H),21β(H)- norhopane to 17α(H),21β(H)- hopane (C29/C30) and sum of 17α(H),21β(H)-C31 homohopane to 17α(H),21β(H)-C35 homohopane relative to 17α(H),21β(H)-hopane (∑C31-C35/C30) that have been used as biomarker signatures in this study have identified those samples number 6 , 4 and 1 out of 30 surface sediment samples were originated from the USA, Middle East and Sumatera respectively which suggesting sea-based and land-based sources and thus significantly contribute to the oil pollution on that particular area.

Keywords: Oil pollution sources; Biomarker; Hopane; South China Sea; Surface sediment

______________________________________________________________________________*Corresponding author. Tel.:(603)8946-8024; Fax: (603)8946-8075. E-mail address: mpauzi@env.upm.edu.my (M.P. Zakaria)

1. Introduction

The South China Sea (Figure 1a) has an area of approximately 3.3 million km2 to cover 270 million people population. The most important countries that surround the circle of South China Sea is China in north, The Philippines in the East, Malaysia in the south and Vietnam in the west (Morton and Blackmore, 2001). The environmental conditions of the South China Sea are extremely threatened by a high rate of population growth, urbanization, fishing, habitat modification and also petroleum pollution. The petroleum pollution in South China Sea is not a new thing since the production of oil has increased dramatically all over the world since …. (put a year, century if you have any info about this). This problem is usually related to the increasing of traffics especially area that facing the East Coast of Peninsular Malaysia (Chandru et al., 2008). Generally the total concentration of petroleum hydrocarbon introduced into the sea is difficult to be quantified due to its nature. However the source or activities of hydrocarbon inputs into the sea can be still identified.

In the National Research Council (NRC) report, oil pollution can be entered into marine aquatic environment via four main categories of sources: discharges through natural seeps, discharges of oil during extraction, transportation and consumption (including both sea-based and land-based sources). However, oil pollution always been conceptualized as a human activity and hence all natural activities that could potentially have damaging effect on the ocean eco-system have been omitted (Somchit et al., 2009). Therefore this study tends to focus on the last three sources due to the fact that natural seeps are not classified as anthropogenic sources.

In a report published in 2002 by NRC of the U.S. National Academy of Sciences, discharges during petroleum extraction or production tend to be restricted to areas of exploration and extraction and are mostly due to the release of "produced waters" (water extracted with petroleum from the reservoir). This is a common phenomenon in areas where there is an extensive oil exploration such as in the South China Sea (Chandru et al., 2008 and Asuquo, 1991). These contribute about 5% of the petroleum reaching the sea from human sources whereas spillage of petroleum during transportation, refinement, and distribution are most common along shipping routes and pipelines and make up about 22% of human-caused petroleum inputs. Discharges during petroleum consumption (i.e., use of automobiles and boats) tend to be small in quantity but are so numerous and widespread that they contribute the vast majority (about 70%) of human-caused petroleum pollution in the sea.

As land-based sources, oil discharged with untreated or insufficiently treated municipal sewage and storm water - urban runoff - comes from cars, machinery, spills at filling stations and garages, flushed-out residues of lubricants, etc. The storm water contains waterborne and airborne pollutants; everything that is flushed onto or falls down upon the hard surface will become constituents of the contaminated storm water for example car exhausts, particles from worn tires, small spills of oil from engines, garages, workshops, residues of oils and lubricants that we want to get rid of. Oil also enters the marine environment with untreated or insufficiently treated waste water or storm water from various coastal facilities such as coastal industries, coastal refineries, coastal oil storage facilities, oil terminals, and reception facilities. Untreated waste water and residues usually have been dumped before the pollutant come to the sea. Consequently, a lot of oil goes literally down the drain from our towns and cities into the sea - either through a municipal sewage treatment plant, where it will harm the treatment process, or more or less untreated.

In other hands, discharges of oil from shipping, offshore extraction of oil, and transport of oil in pipelines is the result of either accidents or "normal", deliberate operational discharges. There will always be unfortunate circumstances and situations that cause accidents to happen. Accidental discharges occur when vessels collide or come in distress at sea (engine breakdown, fire, explosion) and break open (Chua et al., 2000 and Yamamoto et al., 2003).

As soon as oil is discharged, it starts to spread out over the sea surface, initially as a single slick. The speed at which this takes place depends to a great extent upon the viscosity of the oil. Spreading is rarely uniform and large variations in the thickness of the oil are typical. After a few hours, the slick will begin to break up and, because of winds, wave action and water turbulence, will then form narrow bands or windrows parallel to the wind direction. The rate at which the oil spreads is also determined by the prevailing conditions such as temperature, water currents, tidal streams and wind speeds (Jordan and Payne, 1980). The more severe the conditions, the more rapid the spreading and breaking up of the oil. Some heavy refined products have densities greater than one and so will sink in fresh or brackish water. However sea water has a density of approximately 1.025 and very few types of crude are dense enough or weather sufficiently, so that their residues will sink in the marine environment. Sinking usually occurs due to the partitioning of particles of sediment or organic matter to the oil (Baudo et al., 1990). Shallow waters are often laden with suspended solids providing favorable conditions for sedimentation. Oil stranded on sandy shorelines often becomes mixed with sand and other sediments. If this mixture is subsequently washed off the beach back into the sea it may then sink. In addition, if the oil catches fire after it has been spilled, the residues that sometimes form can be sufficiently dense to sink. Contaminated sediment was interesting since its play an important role both as sink as a source of contaminants to the overlying water and biota. Therefore, sediment can be used as a tool to monitor marine pollution as well as for identifying the possible source of pollutants in the surrounding environment.

In order to identify the source of oil pollution, hopanes (Figure 2) has been extensively used. It is considered as a biological marker since they were derived from multiple sources of petroleum. Recently, Zakaria et al. (2001); Wang et al., 2006 and Chandru et al., 2008 have reviewed the applications of pentacyclic triterpanes as a biomarker for fingerprinting. Detail discussion on the biomarker concept, criteria and information has been extensively reviewed by Wang et al. (2007). Hopanes are pentacyclic triterpanes commonly containing 27-35 carbon atoms in a naphthenic structure composed of four six-membered rings and one five-membered ring (Wang et al., 2007). Hopanes with the 17α(H),21β(H) configuration in the range C27 - C35 are characteristic of petroleum because of their large abundance and thermodynamic stability compared to other epimeric (ββ, αα) series. Previously, hopanes were considered to exist as three stereoisomers: 17α(H),21β(H)- hopane, 17β(H),21β(H)-hopane and 17β(H),21α(H)-hopane (Peters and Moldowan, 1993; Waples and Machihara 1991).

Hopane ratios involving C29/C30 (17α(H),21β(H)- norhopane to 17α(H),21β(H)- hopane), ∑C31-C35/C30 (ratio of sum 17α(H),21β(H)-C31 homohopane to 17α(H),21β(H)-C35 homohopane relative to 17α(H),21β(H)-hopane), Tm/Ts (ratio of 17α-22,29,30-trisnorhopane relative to 18α-22,29,30-trisnorhopane) and Oleanane/C30 (ratio of Oleanane relative to 17α(H),21β(H)-hopane) were used by Chandru et al. (2008) in their study as source identifiers and weathering assessment tools in order to determine the oil pollution sources of 17 tar balls samples collected from East Coast of peninsular Malaysia. Before that, Zakaria et al. (2001) was pioneered to this study in Malaysia. In the study conducted by using hopanes on stranded tar balls from east coast of Peninsular Malaysia as an application of biomarkers for identifying the source of oil pollution, Zakaria et al. (2001) and Chandru et al. (2008) also used the same ratio as above. The ratios for the crude oil samples are depicted. A consistent pattern of higher for both C29/C30 and ΣC31-C35/ C30 ratios were observed for Middle East crude oil (MECO), with lower ratios for SEACO oil. As they compared the chromatograms (Figure 3) of crude oils with collected samples, all show the positive feedback, where most of the tar balls samples were originated from SEACO. Figure 4 showed the cross plots of ΣC31-C35/ C30 vs C29/C30 for some references. More than 60 crude oils and tar balls samples were depicted and by cross plotting their ratios, tight cluster has been produced on the plot. The cluster has been drawn as different boxes where each box indicates a range for Indonesia, Norway, USA, East Malaysia and Middle East origin. This implies that particular diagnostic ratios are very useful to isolate different oils and to identify the source of oil pollution sources. The characteristics can be distinguished by a different geological conditions during petroleum formation. Middle East petroleum were derived from marine carbonate source rocks and abundant in 17α(H),21β(H)-C29 and17α(H),21β(H)-C31-C35 (Zakaria et al., 2000; Volkman et al., 1997). However, most of oils originated in South East Asian were derived from nonmarine carbonate source shale source rock (Zakaria et al., 2000; Zin, 1996; Sapawi, 1990) which are characterized by low content of tricyclic terpanes and homohopanes (Okui et al., 1997; 1998) and by lower C29/C30 ratio (Murray et al, 1993)

Before achieving the objective of this study, statistical analysis needs to be done on this quantitative dataset in order to treat and discover its underlying causes, patterns, relationships, and trends. Descriptive statistic has been applied on the data as a purpose to identify an extreme value(s) of generated data if presence. This extreme value is also best known as outlier where it would be an observation which deviates so much from other observations as to arouse suspicious that it was generated by a different mechanism (Hawkins et al., 1980). An inspection of a sample containing outliers would show up such characteristics as large gaps between 'outlying' and 'inlying' observations and the deviation between the outliers and the group of inliers, as measured on some suitably standardized scale. As an impact, outlier would give different value on mean and standard deviation as compared to the value it supposed to have.

2. Experimental

2.1 Sampling collection

Figure 1b and Table 1 showed the locations and sampling details in this study. Thirty core sediments were collected from the east coast of Peninsular Malaysia area onward to South China Sea region in June 2008. This study only focused onto the top sediment of 0-5 cm layer which were taken by using pre-cleaned stainless steel scoop and placed on a stainless steel pan. The sediment samples were kept in an ice box and transported back to the laboratory and stored at -20°C until further analysis.

2.2 Chemical analysis

Organic solvents such as methanol, acetone, isooctane, n-hexane, dichloromethane (DCM) and authentic standard solutions for hopanes were purchased from Wako Pure Chemical (Japan), Chiron (Norway) and Sigma (US). DCM, n-hexanes and isooctane were distilled before use. Glass wares were washed by using a series of soap, tab water and Millipore- Q water system. Then, all the glass wares were rinsed respectively with methanol, acetone and n-hexane (HPLC Grade) and baked 60°C for several hours in order to remove any organic contaminants (Chandru et al., 2007).

The hopanes standard mixtures contains 17β(H),21α(H)- norhopane (C29 17b), 17α(H)-22,29,30-trisnorhopane (Tm), 17α(H),21β(H)-hopane (C30 17α), 17β(H),21α(H)-hopane (C30 17b) and for IIS 17β,21(H)β-hopane was used (as a standard reference material?). Activated silica gel was prepared by heating at 400°C in muffle furnace for 4 hours to remove organic contaminants and then further heated at 200°C for 5 hours, cooled and deactivated with 5% (w/w) distilled water.

Twenty grams of surface sediment samples were accurately measured, dried with pre-heated anhydrous sodium sulphate and extracted by using Soxhlet extraction. The extract was purified and fractionated by method described elsewhere in Zakaria et al. (2000) where it was transferred onto the top of a 5% water deactivated silica gel column chromatography. Hydrocarbons ranged from alkanes to polycyclic aromatic hydrocarbons compound (PAHs), with seven rings were eluted with 20 ml of DCM/n-hexane (1:3, v/v). The hydrocarbon was fractionated further with fully activated silica gel column chromatography to obtain hopane fractions by eluting 4 ml n-hexane. Hopane compounds were detected using mass spectrometer integrated with gas chromatograph (GC-MS) with m/z 191. Details of quantitative and qualitative measures for GC-MS conditions were explained (Zakaria et al., 2000; 2001).

2.3 Statistical analysis

There were several other useful measures where percentiles were points that divide the data. The 25th percentile of first quartile, denoted as Q1, marks the point below which 25% of the data lie. The 75th percentile or third quartile denoted as , Q3 was defined similarly (Buncher and Tsay, 2006). The method of identifying the outliers was due to Mosteller and Tukey, 1997. This method has been performed by identifying outside values as those that are less than Q1-(1.5 X IQR) or greater than Q3+(1.5 X IQR), where Q1 and Q3 was the lower and upper quartiles and IQR= Q3-Q1, the inter-quartile range. It should be noted that for Gaussian population, only 0.7% of the values lies outside those (population) limits. Any value that equal or less than Q1-(1.5 X IQR) has been considered as outliers and it should be omitted. Same goes to the value from the dataset which having same or greater than Q3+(1.5 X IQR) value.

3. Results and discussions

After the outlier analysis has been performed, four surface sediment samples have been neglected for further analysis. They were a surface sediment samples coded SF03, SF06, SF08 and SF22 where the value of C29/C30 has been given by 0.59, 1.83, 2.73 and 4.00 respectively, while for ΣC31-C35/C30 ratio has been calculated as 8.41, 23.32, 12.07 and 10.64 following the order. Calculated Q1-(1.5 X IQR) for C29/C30 and ΣC31-C35/C30 was -0.91 and -1.24 respectively whereas the value of Q3+(1.5 X IQR) for both ratios were identified as 3.00 and 7.01. After conducting the outlier analysis, only 26 surface sediments samples out of 30 samples can be used for further analysis. Outliers arose due to changes in system behavior, fraudulent behavior, human error, instrument error or simply through natural deviations in populations. A sample may have been contaminated with elements from outside the population being examined. Alternatively, an outlier could be the result of a flaw in the assumed theory, resulting for further calling f investigation in this study. However, in this study, Hideshige Takada in his personal communication suggesting that an extreme value of ΣC31-C35/C30 ratio might due to the natural diagenesis during petroleum production where the homohopane distributions are distributed by thermal maturity (Peters and Moldowan, 1991) and hence, the depletion of homohopane (C31-C35) index might be very high or very low depending on maturity in a suite rocks that derived the oil. So, all extreme values in this study were not reliable to be considered since it is represent natural occurring that was happened thousand years ago instead of recent input after World War II era.

The origin of the 26 surface sediments were examined using the molecular marker approach which has been well established for source-identification of tar balls by Zakaria et al. (2000). Table 2 shows us the total hopanes, C29/C30 and ΣC31-C35/ C30 diagnostic ratio for both reference materials and present study of surface sediment samples. Hopane composition for 26 surface sediments was presented in Table 2 and visualized in Figure 5. Six surface sediments samples namely SF01, SF10, SF14, SF17, SF24, and SF25 showed certain value of both ΣC31-C35/ C30 and C29/C30 ratio. The samples present with range 0.501-0.789 and 1.610-2.222 respective to C29/C30 and ΣC31-C35/ C30 diagnostic ratio. This indicates that those samples were derived from USA petroleum as expressed by cluster box on a diagram as shown in Figure 2. The presence of USA origin-pollution in South China Sea carries several possible explanations. Some of them could have been transported via sea currents from discharge or water ballast from tanker that carrying crude oil. The tankers that carry USA crude oil to other counties could have accidentally spilt the oil as well.

A part of that, four samples of SF15, SF20, SF21 and SF29 were falling into Middle East categories with the values of diagnostic ratio are ranging from 1.679 - 2.065 and 1.480- 2.696 for C29/C30 and ΣC31-C35/ C30 respectively. All four points located near to east coast of Peninsular Malaysia; hence the contribution of Middle East derived petroleum came from that particular area. Zakaria et al. (2002) discovered that Middle East petroleum has been used in formulating Malaysia lubricating oils which are the source of oil found in sediment. It is interesting to note that some of the stations located nearby to the coastal waters of east coast of Peninsular Malaysia thus we implies that the probable source pathway of the pollution is from land- based activities which might come from flushed-out residues of lubricants from east coast of Peninsular Malaysia.

One sample namely SF09 plotted within the Sumatera oil category. There are a variety of potential sources of petroleum pollution that may lead into Indonesian origin petroleum pollution. For example, in Sumatera, offshore oil production has been very active (Zakaria et al., 2001). Oils spilled from Sumatera's platform may be transported as far as to the South China Sea area via sea current. A part of that, there are also many inland and offshore oil-fields in the Indonesia that may contribute the oil pollution in the South China Sea. The rest of 15 surface sediments were unidentified their origin because all of them were distributed out of cross plot boxes and hence we cannot identify the source of oil pollution on that particular area.

The unique characteristic of crude oil has been explained by a difference geological condition of their chronostratigraphy (Zakaria et al., 2001) where the California Province includes several small late tertiary basins which are regarded as among the richest petroliferous regions known (TBPCL, 1997). In other part, the Gulf and Arabian Peninsula, the geological succession comprises a thick section of Mesozoic and tertiary sediments where carbonate with some intervals of shale sandstone and salt source rock was very dominant in generating the crude oil. Crude oil originate from Sumatera Island comes from multiple sand reservoirs of lower Miocene age where the characteristic of it is a bit sweet with Oleanane contain.

4. Conclusions and recommendations

As a conclusion, statistical analysis confirmed that four surface sediments were significantly excluded from the dataset of its extreme value due to the natural occurring contribution. The diagnostic ratios of C29/C30 and ΣC31-C35/C30 provide a useful method for distinguishing the origin of surface sediments in this study. The cross plots in Figure 2 distinguish different crude oils and tar balls samples origin and successfully been applied in present study in order to determine the source of oil pollution.

It has been shown clearly in Figure 3 that oil pollution that happened in South China Sea was caused by crude oil from Middle East, USA and Indonesia. Here, it is suggested that South China Sea faced both sea-based and land based petroleum activities which might contribute into the pollution. Contribution from tank washing and ballasting discharges from the tankers transporting the crude oils could affect significantly to the overall surface sediments in this study. A part of that, the source of oil pollution such as petroleum product that been used by population near to the particular area also might derived from respective crude oil where it has been used or dumped into local drain and hence introduced into an aquatic environment via subsequent washout of heavy rainfall or street runoff. Continued experiment in that particular area should be done, so that the distribution and contribution from petroleum extraction, transportation and consumption via intense land-based and sea-based activities that affect the sedimentation from time to time can be clearly identified.

Specifically, further extensive research is needed in order to exactly confirm these suspicious. More new tight crude oil clusters from different origin need to be done so that we can identify the origin of petroleum crude before determining the possible source of petroleum. Generally, the effluents discharged from tankers must meet the ever more stringent requirement of Internal Government Maritime Consultative Organization (IMCO) often in advance of ratified convention so that the unnecessary discharge into the ocean of contaminated ballast water, or of tanker washings is reduced. System such as 'load on top' in which contaminated water is kept on board, and ballast must be segregated to avoid admixture of water and oil, and new tank washing technique, are increasingly preventing deterioration of the quality of the high seas. In other hands, federal agencies, oil related industries, environmental groups and others must work hard to turn the statue's promises into workable law for a clean marine environment

References

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Baudo, R., Giesy, J.P., Muntau, H., 1990. Sediment: Chemistry and toxicity of in-place pollutants. Lewis Publisher, Inc.

Buncher, C.R., Tsay, J.Y., 2006. Statistics in the pharmaceutical industry, third ed. Chapman & Hall, New York.

Chua, T.E., Ingrid, R.L.G., Adrian, R., Stella, R.B., Gervacio, B., Ebarvia, M.C., 2000. The Melacca Straits. Marine Pollution Bulletin, 41:160-737

Chandru, K., Zakaria, M.P., Anita, S., Shahbazi, A., Sakari, M., Bahry, P.S., Mohamed, C.A.R., 2008. Characterization of alkanes, hopanes, PAH in tar balls collected from the East Coast of Peninsular Malaysia. Marine Pollution Bulletin, 56:950-962.

Hawkins, D.M., 1980. Identification of outliers: Monographs on applied probability and statistics. Chapman and Hall Ltd., New York.

Jordan, R.E., Payne, J.R., 1980. Fate and weathering of petroleum spills in the marine environment. Ann Arbor, Michigan.

Morton, B. and Blackmore, G., 2001. South China Sea. Marine Pollution Bulletin, 42:1235-1263.

Mosteller, F. and Tukey, J.W., 1977. Data analysis and regression: A second course in statistics, Reading Mass.: Addison- Wesley.

Murray, A.P., Summons, R.E., Boreham, C.J., Dowling, L.M., 1993. Organic Geochemistry, 22, 535-544.

Okui, A., Koshikawa, K., Yokoyama, Y., Yokoi, K., 1997. Abstract 18th International Meeting On Organic Geochemistry, Maastricht, The Netherland.

Okui, A., Yokoyama,, Y., Yokoi, K., 1998. Res, Organic Geochemistry, 13, 5-12.

Peters, K.E. and Moldowan, J.M., 1991. Effects of source, thermal maturity, and biodegradation on the distribution and isomerization of homohopanes in petroleum. Organic. Geochemistry (17), 1:47-51.

Peters, K.E., Moldowan, J.M., 1993. The biomarker guide: Interpreting molecular fossils in petroleum and ancient. N.J Prentile-Hall: Eaglewood Cliffs.

Sapawi, A., Jamil, A., Annuar, M.L., Seah, E.P.K., 1990. Warta geologi, 16, 278.

Somchit, N., Somchit, M.N., Hadi, S.A., Zakaria, M.P., 2009. Persistent organic chemicals in Malaysian Waters: A review. Research Journal of Environmental Toxicology (2), 3: 101-112.

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Volkman, J.K., Revill, A.T., Murray, A.P., 1997. Molecular markers in environmental geochemistry. Eganhaouse, R.P., Ed, American Chemical Society, Washigton DC, 83-99.

Wang, Z., Stout, S., Fingas, M., 2006. Forensic Fingerprinting of Biomarkers for Oil Spill Characterization and Source Identification. Environmental Forensics, (7) 42:105-146.

Wang, Z., Yang, C., Fingas, M., Hollebone, B., Yim, U.H., Oh, J.R., 2007. Petroleum biomarker fingerprinting for oil spill characterization and source identification: Oil Spill Environmental Forensics, 73-14.

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Zakaria, M.P., Horinouchi, A., Tsutsumi, S., Takada, H., Tanabe, Ismail, A., 2000. Oil pollution in the Straits of Malacca, Malaysia: Application of molecular markers for source identification. Environmental Science and Technology, 34:1189-1196.

Zakaria, M.P., Okuda, T., Takada, H., 2001. Polycyclic aromatic hydrocarbon (PAHs) and hopanes in stranded tar-balls on the coasts of Peninsular Malaysia: applications of biomarkers for identifying sources of oil pollution. Marine Pollution Bulletin 42, 1357-1366.

Zin, I.C.M., 1996. Abstrak, Petroleum Geology Conference, Kuala Lumpur.

Figures and Tables

a)

b)

Figure 1: (a) The map of South China Sea which with shipping routes in Asian waters. (b) The sampling location of sediment samples in South China Sea for present study.

Figure 2: Molecular Structure of hopane. R is an alkyl group.

Figure 3: Chromatogtram of pentacyclic triterpane

Figure 4: Cross plots between ∑C31-C35/C30 vs C29/C30 of crude oil and tar ball references. (adapted from Zakaria et al.,2000; Wang and Stout, 2007; Chandru et al., 2007; Anita, 2009).

Figure 5: Scattered chart between ∑C31-C35/C30 vs C29/C30 of sediment samples from South China Sea.

Table 1:

Locations and sampling details in this study.

Code

Origin

Sampling date

References

 

 

 

Crude oil

MECO 1 (Marban)

Middle East

*nd

Zakaria et al., 2000

MECO 2 (Arabian Lights)

Middle East

*nd

Zakaria et al., 2000

MECO 3 (Umm Shaif)

Middle East

*nd

Zakaria et al., 2000

SEACO 1 (Labuan)

East Malaysia

*nd

Zakaria et al., 2000

SEACO 2 (Miri)

East Malaysia

*nd

Zakaria et al., 2000

SEACO 3 (Tapis)

East Malaysia

*nd

Zakaria et al., 2000

Dumai

Sumatera

18-Aug-05

Anita, 2009 (unpublished data)

Duri

Sumatera

7-Nov-05

Anita, 2009 (unpublished data)

Minas

Sumatera

30-May-05

Anita, 2009 (unpublished data)

NO1 (North Sea Oil 1)

Norway

*nd

Wang and Stout, 2007

ANS 1 (Alaska North Slope)

USA

*nd

Wang and Stout, 2007

CALI 1 (California 1)

USA

*nd

Wang and Stout, 2007

Sockeye

USA

*nd

Wang and Stout, 2007

Platform Elly

USA

*nd

Wang and Stout, 2007

Scotia Light

USA

*nd

Wang and Stout, 2007

South Louisiana

USA

*nd

Wang and Stout, 2007

Tar ball

Sampling location

KETR-T2

Tanjung Rhu, Kedah

25-Dec-97

Zakaria et al., 2000

KETR-T1

Tanjung Rhu, Kedah

9-Sep-98

Zakaria et al., 2000

KEPK

Pantai Kok, Kedah

18-Jan-99

Zakaria et al., 2000

SESB

Sekinchan Beach, Selangor

15-Oct-99

Zakaria et al., 2000

SESD

Sungai Dorani, Selangor

15-Oct-99

Zakaria et al., 2000

SESK

Sungai Kajang, Selangor

15-Oct-99

Zakaria et al., 2000

SETK

Tanjung Karang, Selangor

28-Dec-97

Zakaria et al., 2000

Table 1 (continued)

Code

Origin

Sampling date

References

 

 

 

NSPD

Port Dickson, Negeri Sembilan

14-Aug-99

Zakaria et al., 2000

METB

Tanjung Bidara, Malacca

23-Sep-99

Zakaria et al., 2000

MEKU

Pantai Kundur, Malacca

9-Sep-99

Zakaria et al., 2000

MESM

South Malacca, Malacca

11-Sep-98

Zakaria et al., 2000

MAMC-T2

Malacca City, Malacca

23-Sep-98

Zakaria et al., 2000

JBPP

Pasir Puteh, Kelantan

28-May-98

Zakaria et al., 2000

PAPK

Kuantan Port, Pahang

17-Jan-99

Zakaria et al., 2000

PATB

Tanjung Batu, Pahang

17-Jan-99

Zakaria et al., 2000

TRMT

Mengabang Telipot,Terengganu

20-Sep-98

Zakaria et al., 2000

TRME-1

Merang, Terengganu

28-May-98

Zakaria et al., 2000

KETB

Tok Bali, Kelantan

19-Jan-99

Zakaria et al., 2000

KETB-2

Tok Bali, Kelantan

5-Jul-00

Chandru et al., 2007

KEPP

Pasir putih, Kelantan

5-Jul-00

Chandru et al., 2007

TRKB

Kuala besut, Terengganu

5-Jul-00

Chandru et al., 2007

TRPE

Penarik, Terengganu

6-Jul-00

Chandru et al., 2007

TRME-2

Merang, Terengganu

30-Sep-04

Chandru et al., 2007

TRKP

Kampung panjang, Terengganu

6-Jul-00

Chandru et al., 2007

TRKPB

Kampung Pagar Besi, terengganu

3-Jan-05

Chandru et al., 2007

TRPM

Pengkalan Maras, terengganu

3-Jan-05

Chandru et al., 2007

TRTK

Teluk ketapang, Terengganu

6-Jul-00

Chandru et al., 2007

TRBB

Batu Buruk, Terengganu

6-Jul-00

Chandru et al., 2007

TRMA

Marang, Terengganu

6-Jul-00

Chandru et al., 2007

TRDU

Dungun, Terengganu

7-Jul-00

Chandru et al., 2007

TRKE

Kemasik, Terengganu

11-Mar-06

Chandru et al., 2007

TRKM

Kemaman, Terengganu

4-Jul-00

Chandru et al., 2007

PATC

Teluk Chempedak, Pahang

11-Dec-05

Chandru et al., 2007

IDACBR1

Biruen, Acheh

27-Nov-06

Anita, 2009 (unpublished data)

IDNSKP1

Kuala Putri, North Sumatera

30-Aug-06

Anita, 2009 (unpublished data)

Table 1 (continued)

Code

Origin

Sampling date

References

 

 

IDNSPC2

Pantai Cermin, North Sumatera

30-Aug-06

Anita, 2009 (unpublished data)

IDRIBP2

Batu Panjang, Riau

27-Oct-06

Anita, 2009 (unpublished data)

IDRIDM1

Dumai, Riau

7-Nov-05

Anita, 2009 (unpublished data)

IDRABT3

Batam, Riau Archipelago

28-Mar-06

Anita, 2009 (unpublished data)

IDRABP2

Batang Padang, Riau Archipelago

29-Mar-06

Anita, 2009 (unpublished data)

IDRABP1

Batang Padang, Riau Archipelago

28-Mar-06

Anita, 2009 (unpublished data)

IDRAKR1

Karimun, Riau Archipelago

30-Nov-05

Anita, 2009 (unpublished data)

Sediment (present study)

Sampling location

Sampling date

Longitude (E)

Latitude (N)

Distance (Nautical miles)

Water depth (meter)

SF01

South China Sea 1

18-Jun-08

102 19.00'

06 13.99'

2.7

13

SF02

South China Sea 2

17-Jun-08

102 47.04'

06 50.04'

50

46.5

SF03

South China Sea 3

17-Jun-08

103 04.99'

07 05.03'

73

50

SF04

South China Sea 4

17-Jun-08

103 26.01'

07 25.98'

100

61

SF05

South China Sea 5

16-Jun-08

103 56.04'

06 56.09'

108

52

SF06

South China Sea 6

16-Jun-08

103 35.17'

06 42.14'

80

52

SF07

South China Sea 7

16-Jun-08

103 01.00'

06 10.00'

40

45

SF08

South China Sea 8

18-Jun-08

102 51.92'

05 52.10'

15

34

SF09

South China Sea 9

20-Jun-08

103 21.97'

05 22.06'

14

47

SF10

South China Sea 10

14-Jun-08

103 48.98'

05 48.20'

48

55

SF11

South China Sea 11

14-Jun-08

104 09.11'

06 06.16'

75

72

SF12

South China Sea 12

14-Jun-08

104 22.11'

06 32.01'

101

59

SF13

South China Sea 13

13-Jun-08

105 16.99'

06 16.98'

139

55

SF14

South China Sea 14

13-Jun-08

104 58.13'

05 57.15'

115

56

SF15

South China Sea 15

12-Jun-08

104 29.02'

05 29.08'

80

60.7

SF16

South China Sea 16

12-Jun-08

104 12.60'

05 18.50'

56

60

SF17

South China Sea 17

20-Jun-08

103 42.98'

04 54.12'

17

54

SF18

South China Sea 18

11-Jun-08

103 49.98'

04 28.14'

20

40

SF19

South China Sea 19

22-Jun-08

103 41.08'

03 37.07'

15

23

Table 1 (continued)

Sediment (present study)

Sampling location

Sampling date

Longitude (E)

Latitude (N)

Distance (Nautical miles)

Water depth (meter)

SF20

South China Sea 20

22-Jun-08

104 00.05'

03 55.10'

40

50

SF21

South China Sea 21

23-Jun-08

104 22.07'

04 22.16'

52

65

SF22

South China Sea 22

23-Jun-08

104 38.44'

04 44.19'

70

66

SF23

South China Sea 23

12-Jun-08

105 12.9'

05 08.10'

109

67.2

SF24

South China Sea 24

23-Jun-08

104 36.00'

03 32.08'

70

62

SF25

South China Sea 25

24-Jun-08

104 09.04'

03 09.14'

42

41

SF26

South China Sea 26

26-Jun-08

103 49.97'

02 56.13'

24

20

SF27

South China Sea 27

24-Jun-08

104 16.97'

02 16.94'

19.5

30

SF28

South China Sea 28

24-Jun-08

104 38.91'

02 39.18'

47

58

SF29

South China Sea 29

25-Jun-08

104 41.97'

02 00.55'

35

46

SF30

South China Sea 30

25-Jun-08

104 15.03'

01 48.04'

4.5

14

*nd= Not determine

Table 2:

Data of pentacyclic triterpanes (m/z=191) for references materials and sediment sample of present study.

CODE

∑Hopanes

aC29/C30

b∑C31-C35/C30

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