Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran

Environmental Pollution xxx (2017) 1e29

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Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran* Ranjbar Jafarabadi Ali a, Riyahi Bakhtiari Alireza b, *, Aliabadian Mansour c, Shadmehri Toosi Amirhossein d a

Department of Environmental Sciences, Faculty of Natural Resources and Marine Sciences, TarbiatModares University(TMU), Noor, Mazandaran, Iran Department of Environmental Sciences, Faculty of Natural Resources and Marine Sciences, TarbiatModares University, Noor, Mazandaran, Iran Department of Biology, Faculty of Sciences, Ferdowsi University of Mashhad (FUM), Mashhad, Khorasan Razavi, Iran d Department of Civil & Environmental Engineering, Faculty of Engineering, Ferdowsi University of Mashhad (FUM), Mashhad, Khorasan Razavi, Iran b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 18 October 2016 Received in revised form 16 January 2017 Accepted 31 January 2017 Available online xxx

This study is the first quantitative report on petroleum biomarkers from the coral reefs systems of the Persian Gulf. 120 reef surface sediment samples from ten fragile coral reef ecosystems were collected and analyzed for grain size, biogenic elements, elemental ratios, and petroleum biomarkers (n-alkanes, PAHs1 and Hopanes) to assess the sources and early diagenesis of sedimentary organic matter. The mean grain size of the reef sediments ranged from 13.56 to 37.11% (Clay), 26.92 to 51.73% (Sand) and 35.97 to 43.85% (Silt). TOC2 (3.35e9.72 mg.g
1) and TON3 (0.4e1.10 mg.g
1) were identified as influencing factors on the accumulation of petroleum hydrocarbons, whilst BC4 (1.08e3.28 mg.g
1) and TIN5 (0.13e0.86) did not exhibit any determining effect. Although BC and TIN demonstrated heterogeneous spatial distribution, TOC and TON indicated homogenous distribution with continually upward trend in concentration from the east to west ward of the Gulf. The mean calculated TOC/TN ratios vacillated according to the stations (p < 0.05) from 2.96 at Shidvar Island to 8.64 at Hengam Island. The high TOC/TN ratios were observed in the Hengam (8.64), Kharg (8.04) and Siri (6.29), respectively, suggesting a predominant marine origin. P P P The mean concentrations of C11e35n-alkanes, 30 PAHs and 9Hopanes were found in the ranges of 385e937 mg.g
1dw, (overall mean:590 mg.g
1dw), 326e793 ng.g
1dw (499 ng.g
1dw), 88 to 568 mg.g
1 d (258 ng.g
1dw), respectively. Higher concentrations of detected petroleum biomarkers in reef sediments were chiefly distributed near main industrial areas, Kharg, Lavan and Siri, whilst the lower concentrations were in Hormoz and Qeshm. In addition, one-way ANOVA6 analysis demonstrated considerably significant differences (p < 0.05) among concentration of detected total petroleum hydrocarbons between most sampling locations. Some sampling sites especially Kharg, Lavan, Siri and Lark indicated higher concentration of n-alkanes due to the higher maintenance of organic matter by high clay content in the sediments. Furthermore, most sediment samples, except for Hormoz, Qeshm and Hengam showed an even carbon preference for n-alkanes which could be correlated to bacterial input.

Keywords: Petroleum biomarkers Spatial distribution Source identification PCA HCA NPMDS Persian Gulf

*

This paper has been recommended for acceptance by Maria Cristina Fossi. * Corresponding author. E-mail addresses: [email protected] (R.J. Ali), [email protected] (R.B. Alireza). 1 Polycyclic Aromatic Hydrocarbons. 2 Total Organic Carbon. 3 Total Organic Nitrogen. 4 Black Carbon. 5 Total Inorganic Nitrogen. 6 Analysis of variance. 7 Non Parametric Multi-Dimensional Scale Analysis. 8 Phenanthrene. 9 Naphthalene. 10 Principal Component Analysis. 11 Aliphatic Hydrocarbons. 12 Unresolved Complex Mixture. http://dx.doi.org/10.1016/j.envpol.2017.01.080 0269-7491/© 2017 Published by Elsevier Ltd.

Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080

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NPMDS7 analysis also demonstrated that among the congeners of petroleum biomarkers, n-C12,n-C14, nC16,n-C18 and n-C20 for n-alkanes, Phe8 and Naph9 along with their Alkyl homologues for PAHs (2e3 rings accounted for 60%) and C30ab and C29ab for Hopanes were discriminated from their other congeners in the whole study area. Our results based on the PCA10 analysis and diagnostic indices of AHs11 and PAHs along with ring classification of PAHs, in addition, the ubiquitous presence of UCM,12 and Hopanes revealed that the main sources of the pollution were petroleum and petroleum combustion mainly from offshore oil exploration and extraction, discharge of pollutants from shipping activities. © 2017 Published by Elsevier Ltd.

1. Introduction Sediments are great representative factor to explore the fate of pollutants in the environment (Guo et al., 2011; Maciel et al., 2016; Zanardi-Lamardo et al., 2013). The aliphatic hydrocarbons, which consist of about 80% of crude oil (Colombo et al., 1989; Maciel et al., 2016; Martins et al., 2004; Sanches Filho et al., 2013; Simpson et al., 2005) are broadly applied as geochemical markers of oil contamination (Bícego et al., 2009; Maciel et al., 2016; Volkman et al., 1992). Numerous studies have reported various origins of AHs from a variety of allochthonous and autochthonous sources (biogenic origin) by Biosynthesisof higher plants, certain algae and bacteria to marine oil and gas exploration, accidental spills, municipal and industrial discharges along with riverine input and waste incineration anthropogenic origins (Akhbarizadeh et al., 2016; Companioni Damas et al., 2009; Cranwell et al., 1987; de Souza et al., 2011; Ficken et al., 2000; Gelpi et al., 1970; Guigue et al., 2014; Nicolaus et al., 2015; Rieley et al., 1991; Sanches Filho et al., 2013; Schintu et al., 2015; Sojinu et al., 2012; Wakeham, 1996; Wang et al., 2013; Zhou et al., 2014). Among the biogenic hydrocarbons, n-alkanes are the ones predominant in plants and animals (Nishigima et al., 2001; Sanches Filho et al., 2013). Analysis of individual n-alkanes has been demonstrated to be robust for deciphering their sources in superficial sediments. The hydrophobic features of AHs are caused to create a great tendency to be adsorbed to particulate materials and eventually deposit in different fractions of sediments. This characteristic has made the distribution of nalkanes an effective biomarker tool for evaluating biogenic and anthropogenic origins of OM14 in aquatic ecosystems (Fang et al., 2014). PAHs, which illustrate some of the most toxic constituents of light crude oil, often subtend more than 10% of the organic compounds in crude oil (Sammarco et al., 2013). Since these compounds are widespread throughout the marine environment and provide insight into the general distribution of petroleum hydrocarbons in the environment associated with a spill (Sammarco et al., 2013; ~ as et al., 2010), they have been used in detecting oil pollution Vin in the environment due to their relatively longer persistence than aliphatic compounds (Adhikari et al., 2015; Adhikari et al., 2016; Alimi et al., 2003; Asia et al., 2009; Dachs et al., 2002; de AbreuMota et al., 2014; Wang et al., 1999; White et al., 2004; Zhang et al., 2013). Due to low aqueous solubility of PAHs, it is not surprising to get easily sorbed onto sediments to deposit in bed sediment with dazzling velocity and eventually cause bioconcentrate (Meador, 2003; Sammarco et al., 2013) and bioaccumulate (Cave et al., 2010; Ko et al., 2014; Mici c et al., 2013; Oren et al., 2006)in marine organism along with impairing the benthic communities (Adhikari et al., 2016). Although PAHs can be generated by the natural emissions including volcanoes, forest and prairie fires, natural petroleum seeps, degradation of biomass, and

14

Organic Matter.

biogenic formation especially post-depositional transformations of biogenic pre-cursors over relatively short period of time, the main origins of releasing PAHs to the marine environments are anthropogenic sources, particularly as a result of fossil fuels and their derivatives, incomplete combustion or pyrolysis of organic material, vehicles emissions, industrial activities such as the release of hydrocarbons related to the petroleum industry, accidental oils spills and the disposal of domestic and industrial effluents (Achten and Hofmann, 2009; Akhbarizadeh et al., 2016; Albuquerque et al., 2016; Bakhtiari et al., 2010b; Bakhtiari et al., 2009a; Cristale et al., 2012; de Abreu-Mota et al., 2014; de Souza Pereira et al., 2007; Galarneau, 2008; Hofmann et al., 2007; Kaiser et al., 2014; Katsoyiannis and Breivik, 2014; Laumann et al., 2011; Manoli et al.,  ski et al., 2004; Monzer et al., 2008; Ratola et al., 2012; Tronczyn 2004; Turner et al., 2014; Vasilakos et al., 2007; Wilcke, 2000; Wlodarczyk-Makula, 2005; Zhang and Tao, 2009; Zhao et al., 2014; Zheng et al., 2012). This suggests that the PAHs occur in the environment as a combination of emissions from various sources, characterized by spatial and temporal differences and also differences in strength and duration. The varying sources of PAHs result in distinctive chemical patterns that may indicate the origin of PAH pollution. Despite most PAHs investigations have concentrated on the distribution, source identification, transformation, and risk assessment in sediments, biota or water (Barbee et al., 2008; Bouloubassi et al., 2012; Chen et al., 2013; Dai et al., 2011; Dissanayake and Bamber, 2010; Gaspare et al., 2009; Guo et al., 2011; Olson et al., 2016; Oros et al., 2007; Ratola et al., 2012; Tairova et al., 2012; Yu et al., 2015; Zhang et al., 2016),a few studies have worked on bed sediments of coral reefs (Akhbarizadeh et al., 2016; Burns and Jones, 2016; Ko et al., 2014). It has been reported that Hopanes are useful criterion for OM source identification and could be utilized to finger print spilled oil (Hu et al., 2009; Shirneshan et al., 2016a; Zaghden et al., 2007). Hopanes sources could be ascribable to petrogenic origin, microbial as well as its diagenetic transformation products (Resmi et al., 2016). Since Hopanoids preserve membrane fluidity in prokaryotes and are well impounded over the long times of years (Pearson and Rusch, 2009; Resmi et al., 2016), they can effectively be applied as a bacterial marker because of their abundance in geological materials (Belin, 2009; Resmi et al., 2016). Petroleum biomarkers, including isoprenoid alkanes, PAHs and Hopanesare fossil molecules that are unambiguously linked to biological precursors (Mici c et al., 2013; Peters et al., 2005). The Persian Gulf, a semi-enclosed body of water with an average depth of 35 m, only can be connected to the open waters through the Strait of Hormoz (Freije, 2015; Khan, 2002; Massoud et al., 1996; Reynolds, 1993; Sheppard, 1993), It is well known that coral reefs in the Persian Gulf play key and invaluable roles for both local consumption and export revenue. Therefore, maintaining good marine environmental quality is crucial for several socioeconomic reasons (Freije, 2015; Price and Robinson, 1993; Sheppard et al., 2010). This Gulf is comprising of a great deal of comparatively frail ecosystems that are associated with a surrounding that is highly influenced by

Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080

R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

man-made disturbances including offshore oil exploration and extraction, oil terminals, tanker collisions, spills due to wars, land based industrial activities along with the recreational development which can considerably leave overwhelming effects on such a pristine ecosystems and their severe consequences could become a global calamity (Al-Saleh et al., 1999; Freije, 2015; Madany et al., 1996; Sheppard et al., 2010). It is reported that this gulf includes 800 offshore oil and gas platforms and 25 main terminals along with some of the largest oil infrastructures and fields for producing oil all over the world (Albano et al., 2016; Sheppard et al., 2010). This Gulf is thronged with ship congestions which along with its coastal areas are the world's single largest source of crude oil, keeping an evaluated 57e66% and 45% of the world's known reserves of oil and natural gas respectively (Saleh et al., 2016). The Gulf retains a considerable proportion of the world's oil reserves, and the Strait of Hormuz is considered a critical point for energy security; it is estimated that more than 17 million barrels of crude oil per day passed through the straits in 2011 (Liao and Kaihatu, 2016; Outlook, 2012). It is also reported that during peak periods of oil shipping, approximately 60% of the world's oil transportation pass through this region (Rezaei-Latifi, 2016). Recent studies have examined the hydrocarbon status in coastal areas of the Persian Gulf focusing on the sources, compositions, and distributions of petroleum hydrocarbons (Abdollahi et al., 2013; Akhbarizadeh et al., 2016; Khazaali et al., 2016; Lübeck et al., 2016; Mehdinia et al., 2015; Mohebbi-Nozar et al., 2015). However, limited attention has been paid to hydrocarbon concentration and origins in coral reefs, thus, to our knowledge, no comprehensive information is available. With regard to this fact, this paper explores the concentration of detected hydrocarbons and also the potential sources of pollution of the reef surface sediments in the fragile coral reefs of the Persian Gulf, Iran. To provide a wider perspective of the interaction between natural and anthropogenic processes and enable the identification of the most proper indicator for the environmental assessment of the area, a multi-parameter approach including biomarkers, geochemical compositions, biogenic elements (TC,15TOC, BC, TN, TON, TIN) and total sulphate (TS16) and also multivariate statistical analyses were utilized. What is more, the occurrence, composition, spatial distribution and sources of these material in the reef sediments were delineated to elucidate the understanding of the mechanisms controlling the burial of these materials in our study area. The main objectives of this investigation were: 1) to obtain detailed information on the spatial distribution and abundance patterns of the different hydrocarbons: n-alkanes, PAHs and Hopanes, 2) to find the relationship between examined biomarkers, biogenic elements and grain size of reef surface sediments. This study offers a unique opportunity to prepare data for understanding the status of petroleum contamination, and aiding in decision makings related to ecological restoration in coral ecosystems. 2. Material and methods 2.1. Study area and sampling strategy The Persian Gulf, which is one of the most critical water-bodies and important waterways in the world, is located between 24 and 30  N and 48e57  E in the heart of the middle east and separates the Arabian Peninsula from Iran (Daliri et al., 2016; Saleh et al., 2016). It is finally conjoined to the Indian Ocean by the Strait of Hormuz. Its whole area is nearly 226,000 km2 (Emery, 1956). The

15 16

Total Carbon. Total Sulphate.

3

basin width of the Gulf shifts from 56 to 338 km and its central axis is approximately 990 km long (Emery, 1956). Reef surface sediments were collected from 10 sampling sites with 12 repetitions per station, from the upper 5 cm using a grab sampler in July 2014 with the sampling map and stations being demonstrated and presented in Fig. 1 and Table 1. Reef sediment layers were carefully taken to prevent from any disturbance. The upper 5 cm layer of reef surface sediment was considered due to its chemically and biologically activeness relative to the deeper layers. Sampling was conducted at specific intervals throughout the sea to ensuring the representative of the reef sediment samples and the homogeneous distribution in the entire study area from the east to the west part of the Gulf. A total of 120 samples were collected and transferred into a stainless steel container to reduce any contamination. The containers were labeled and placed in an icebox at 4  C then transported to the laboratory for further analysis. The samples were stored in a cold room (
20  C) until further analysis. All sampling sites were not directly affected by local anthropogenic emissions except for Kharg, Lavan, and Siri and to some extent Lark Islands. To span the water content of the reef sediments, nearly 5 g of the sediment samples was put in a pre-weighed crucible, and the overall mass was calculated. To gain a constant weight, the sample in the container was dried at 65  C for three days in an oven. The sample was re-weighed after cooling for relatively 30 min in a desiccator. The water content of the reef sample was computed according to the following equation (Gouleau et al., 2000):

 WC ¼

 mw
md  100% md

Where wc is the water content (%), mw indicates net mass of the wet sample (g), and md represents net mass of the dry sample (g). Grain size was analyzed by way of a laser particle size analyzer (Malvern Mastersizer 300). Freeze dried and homogenized reef sediment samples were used for the analysis of general geochemical parameters. TOC, TN and TS were determined using Vario EL III CHNS Analyzer. For total inorganic and organic nitrogen, the method of Ray et al. (2014) was used. Thermal oxidation method linas et al., (the GBC17 method) was performed to extract BC (Ge nchez-García et al., 2013). This technique relies on the 2001; Sa differential thermal resistance of BC and non-BC organic components in the sample, which is heated in an O2-rich atmosphere to volatilizeeoxidize the most labile organic moieties and measure the remaining residue as BC.

2.2. Sample preparation and analysis The method described by (Zakaria et al., 2000)and (Bakhtiari et al., 2009a; Bakhtiari et al., 2011)were considered for reef sediment preparation, extraction (by Soxhlet method for 12 h for each reef sediment sample), and biomarker analysis and this method has been described in numerous references (Azimi Yancheshmeh et al., 2014; Shirneshan et al., 2016a; Varnosfaderany et al., 2014). In summary, this method is composed of a two-step silica gel chromatography and gas chromatography-mass spectrometry (GCeMS). To eliminate any organic pollutants, organic solvents were distilled in glass before usage and glasswares were rinsed consecutively with methanol, acetone and distilled hexane, respectively, and kept in an oven at 60  C for 2 h. Standard solutions of targeted petroleum hydrocarbons were purchased from Sigma Chemical Company.

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Graphic Black Carbon.

Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080

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R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

Fig. 1. Location of the sampling stations of reef surface sediments in the Persian Gulf, Iran.

2.3. Quality control In the present study, all samplers were controlled and cleaned daily during sampling. As a background check for the organic compounds, blank filters were performed. By comparison of GC-MS peak area with that of internal standards, the quantification of the detected compounds was carried out. During the GCeMS analysis, three samples were indiscriminately selected from each group of

eight for a replicate analysis. Compound identifications were based on comparisons with authentic standards and GC retention time. To determine the standard curves, GC-MS with the standard concentration known was used. Detection limit, recovery and relative standard deviation (RSD18) were applied to evaluate our method. To

18

Relative Standard Deviation.

Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080

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Table 1 Geochemical parameters in the reef surface sediments from sampling sites in the Persian Gulf on July 2014. Physio-chemical Parameters

Hormoz Island Lark Island

Qeshm Island

Hengam Island

Siri Island

Kish Island Hendurabi Island

Shidvar Island

Latitude Longitude Code TC (mg.g
1)

27 40 000 N 56 280 000 E ST1 4.09e5.16 4.84 0.75 2.95e3.58 3.35 0.44 1.14e1.58 1.49 0.31 0.83e0.98 0.91 0.10 0.74e0.78 0.78 0.02 0.09e0.2 0.13 0.07 0.52e0.72 0.65 0.14 5.32 7.45 19.16 13.56 34.71 51.73

26 410 4300 N 55 370 600 E ST3 4.19e5.11 4.69 0.65 3.40e3.81 3.51 0.28 0.79e1.3 1.18 0.36 1.13e1.85 1.50 0.50 0.61e0.81 0.75 0.14 0.52e1.04 0.75 0.36 0.91e1.15 1.08 0.16 3.13 4.34 27.13 16.02 43.23 40.75

26 380 000 N 55 520 000 E ST4 4.31e5.89 5.27 1.11 3.16e3.97 3.92 0.57 1.15e1.92 1.35 0.54 0.57e0.68 0.61 0.07 0.37e0.47 0.40 0.07 0.2e0.21 0.21 0.00 0.32e0.54 0.44 0.15 8.64 11.98 29.65 23.04 40.19 36.77

25 540 3400 N 54 320 2200 E ST5 6.59e7.34 7.11 0.53 5.43e6.07 5.86 0.45 1.16e1.27 1.25 0.07 0.88e1.49 1.13 0.28 0.59e0.84 0.77 0.17 0.29e0.65 0.37 0.11 0.85e1.2 0.94 0.24 6.29 7.56 36.24 28.33 39.95 31.72

26 320 000 N 53 580 000 E ST6 5.51e6.43 6.02 0.65 4.53e5.17 4.84 0.45 0.98e1.26 1.18 0.19 1.05e1.49 1.2 0.31 0.73e0.92 0.83 0.13 0.32e0.57 0.37 0.17 0.89e1.14 1.00 0.17 5.02 6.02 31.58 23.98 41.89 34.13

26 470 2800 N 26 480 3500 N 53 240 4000 E 53 160 800 E ST8 ST9 4.58e7.19 8.68e10.59 4.67 9.85 1.84 1.35 5.43e6.07 6.83e7.92 5.59 7.87 1.79 0.77 1.05e1.12 1.85e2.67 1.08 1.98 0.04 0.57 0.89e1.69 1.46e1.85 1.58 1.67 0.49 0.18 0.73e1.14 0.93e1.14 1.1 1.06 0.21 0.14 0.16e0.55 0.53e0.71 0.48 0.62 0.27 0.03 0.85e1.08 0.91e1.1 0.91 0.97 0.1626 0.13 2.96 5.90 5.13 10.15 34.5 31.17 26.83 29.58 41.2 36.07 31.97 34.35

Range Mean SD TOC(mg.g
1) Range Mean SD BC(mg.g
1) Range Mean SD TN (mg.g
1) Range Mean SD TON(mg.g
1) Range Mean SD
1 TIN(mg.g ) Range Mean SD TS (mg.g
1) Range Mean SD
1 TOC/TN (mg.g )
1 TOC/TS (mg.g ) Water % Grain Size (%) Clay Silt Sand

26 510 000 N 56 210 000 E ST2 6.59e7.34 6.96 0.53 3.50e3.96 3.68 0.32 2.89e3.41 3.28 0.20 1.37e2.11 1.96 0.52 1.03e1.2 1.10 0.12 0.34e0.91 0.86 0.40 1.1e1.37 1.23 0.19 3.55 5.66 23.58 27.78 41.19 31.03

calculate the recoveries, spiking a known concentration of SIIS19 mixture into the sample followed by performing the entire analytical procedure was implemented. The recoveries of individual spiked SIIS were between 88 and 103% for n-alkanes, 84e107% for PAHs and 89e111% for Hopanes. The results were exhibited that the standard deviation for the replicate analyses for each compound was between 1 and 10%, and the uncertainties in the concentrations were between 0.0040 and 0.009 ng.g
1. Detailed quality assurance/quality control (QA/QC) procedures for analyses have been elucidated elsewhere (Azimi Yancheshmeh et al., 2014; Cao et al., 2010; Ho et al., 2006; Shirneshan et al., 2016a; Varnosfaderany et al., 2014).

2.4. Statistical analysis Descriptive statistics were calculated for data, including mean, standard deviation, 95% confidence limits, and minimum and maximum values for petroleum concentrations in the marine reef sediments. All statistical analyses were conducted using the statistical environment R3.1.1 (Dray and Dufour, 2007; Team, 2014) and CANOCO version 4.5 for Windows. The ShapiroeWilks was utilized to find normality among determined parameters (significance level was considered at P-value  0.05). In the present investigation, the sums of the total 25 n-alkanes, total 30 PAHs, US EPA 16 priority PAHs, Alkyl PAHs and parent PAHs and total 8 P P P Hopanes were defined as 25n-alkanes, 30 PAHs, 16 PAHs, P P P Alkyl PAHs, Parent PAHs, and 8 Hopanes, respectively. In statistical analysis, significant differences between the obtained results from petroleum biomarkers among different stations were estimated on the basis of analysis of variance method (ANOVA, 95%

19

26 400 000 N 53 370 000 E ST7 5.46e6.49 5. 91 0.72 3.47e4.31 3.81 0.59 1.99e2.18 2.10 0.13 1.10e1.62 1.21 0.36 0.82e0.97 0.86 0.10 0.28e0.65 0.35 0.26 0.74e0.93 0.81 0.13 4.88 7.30 35.95 24.18 43.85 31.97

Lavan Island Kharg Island 29.235481 N 50.31 E ST10 10.13e12.91 12.55 1.96 7.36e9.95 9.72 1.83 2.77e2.96 2.83 0.13 1.03e1.63 1.56 0.42 0.76e0.82 0.80 0.04 0.27e0.81 0.76 0.38 1.10e1.29 1.17 0.13 8.04 10.73 29.87 37.11 35.97 26.92

confidence intervals test). Tukey's honestly significant difference test with a P < 0.05 was carried out to find the multiple comparisons of data means. The differences in examined petroleum hydrocarbon concentrations or proportions were estimated by ANOVA, and the significant level was set at P < 0.05. Multivariate statistical methods including linear regression, PCA, NPMDS and HCA were utilized to analyze the co-variation in petroleum biomarkers concentrations and compositional patterns among the reef surface sediment samples. NPMDS was carried out to specify further the spatial variability in the aliphatic, aromatic and Hopane congeners and grouping the sampling sites pertaining to their position and assessing the individual petroleum hydrocarbon concentrations (Ju et al., 2016; Maciel et al., 2016). Besides, to quantify the significance of variables that elucidate the observed groupings and patterns of the inherent properties of the monitoring stations, PCA with varimax normalized rotation was performed (Hammer et al., 2001; Kim et al., 2013; Pop et al., 2009; Sarbu and Pop, 2005). HCA with Ward's method with Squared Euclidean distances as a measure of similarity was applied to the aliphatic, aromatic and Hopane concentrations data set to specify the group monitoring stations for the whole study area (Kim et al., 2013; Shrestha and Kazama, 2007; Singh et al., 2004). Linear regression P was conducted to analyze plausible association between the 25nP P alkanes, 30 PAHs, and 8 Hopanes, TOC, TN, TS and grain size. In P order to investigate the spatial distribution of the 25n-alkanes, P P 30PAHs, and 8 Hopanes in the reef sediments, the obtained data were calculated by ordinary kriging (OK) equations with the second order stationary hypothesis. Source identification of detected petroleum biomarkers were conducted based on reported chemical markers, diagnostic measures and indices from related investigations (Azimi Yancheshmeh et al., 2014; Bakhtiari et al., 2010b; Bakhtiari et al., 2009b; Resmi et al., 2016; Shahbazi et al., 2010; Shirneshan et al., 2016a; Varnosfaderany et al., 2014).

Surrogate Internal Injection Standard.

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3. Results 3.1. Sediment characterization 3.1.1. Spatial distribution of grain particle-size The Summary of analytical results regarding grain size and spatial distribution for the reef surface sediments are presented in Table 1and Fig. 2a. Textural characteristics exhibited significant spatial variation (p < 0.05), and the relative abundance of the reef sediments ranged from 13.56 to 37.11 (clay) and 26.92 to 51.73%

(sand). The obtained results demonstrated that the average wetness of the reef sediments collected in the Persian Gulf varied from 19.16% to 36.24% (with an overall mean value of 29.88%). In addition to the smallest particles where observed in west part of the study area, Kharg Island oscillated as the clay (37.11%)>, silt (35.97%)>, sand (26.92%), whilst the biggest ones were recorded in east section of the Gulf, Hormoz Island, which varied as follow: sand (51.73)>silt (34.71%)>clay (13.56%). Nonetheless, fine fractions of silt and clay particles were comparatively predominant in most sample sediments collected particularly at sites of Kharg,

Fig. 2. Spatial variations and distributions of geochemical characterization of the reef surface sediments including, grain size* (a) TC, TOC, BC (b), TN, TIN, TON(c), TOC/TN (d), TOC/ TS (e) and TS (f) from sampling sites in the Persian Gulf on July 2014.*note that greater circle shows higher amount of sand in samples in comparison to others.

Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080

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Table 2 Concentrations, indices and ratios of n-alkanes in reef surface sediments from the coral reefs in the Persian Gulf, July 2014 (mg.g
1, dw).Related parameters are calculated based on reported studies (Aboul-Kassim and Simoneit, 1996; Bakhtiari et al., 2010b; Commendatore et al., 2000; Gao and Chen, 2008; Gao et al., 2007; Gogou et al., 2000; Harji et al., 2008; Hu et al., 2009; Li et al., 2015a; Meyers, 1997; Meyers and Ishiwatari, 1993; Mille et al., 2007; Ou et al., 2004; Punyu et al., 2013; Resmi et al., 2016; Wang and Fingas, 2003; Xing et al., 2011)1. Sampling station

Hormoz Island (ST1)

Lark Island (ST2)

Qeshm Island (ST3)

Hengam Island (ST4)

Siri Island (ST5)

Parameters P 25n-alkanes P 25n-alkanes þ Pri þ Phy Pri Phy Overall CPI(n-C11-n-C35) High CPIa Low CPIb LMW/HMW Pri/Phy n-C17/Pri n-C18/Phy n-C29/n-C17 n-C31/n-C19 ACL TAR OEP20 P 25n-alkanes/n-C16 PLK TRE PETRO

Range

Mean

Range

Mean

Range

Mean

Range

Mean

Range

Mean

361e397 396e448 15e23 18e27 2.65e5.95 2.56e3.96 2.88e5.95 0.39e0.61 0.73e0.96 3.65e4.89 1.29e2.34 1.75e4.05 1.92e2.79 27.36e28.97 2.50e2.85 1.079e2.10 9.86e10.80 31e37 18e21 29e31

385 429 19 24 4.37 3.26 4.24 0.53 0.85 4.81 1.92 3.45 2.31 28.77 2.60 2.07 10.11 34 19 30

479e549 708e826 119e139 109e137 1.05e1.20 0.97e1.13 1.04e1.16 1.76e2.13 0.95e1.09 1.03e1.16 3.66e3.90 1.10e1.23 0.90e0.99 28.10e28.93 1.10e1.29 1.06e1.08 7.50e7.76 49e51 81e82 104e109

527 784 128 129 1.17 1.08 1.13 1.92 0.99 1.11 3.79 1.16 0.96 28.88 1.21 1.02 7.69 50 82 105

449e549 495e601 21e24 24e27 4.19e4.56 3.15e3.65 4.21e4.72 0.50e0.86 0.73e0.93 5.17e5.99 1.29e2.72 3.10e3.86 2.13e2.90 28.10e28.59 2.45e2.92 2.10e2.90 8.06e8.75 41e44 21e24 41e46

452 500 22 25 4.46 3.31 4.38 0.52 0.88 5.81 1.94 3.23 2.40 28.38 2.67 2.21 8.12 43 22 42

479e549 529e608 23e27 26e31 4.06e4.39 4.12e5.94 3.06e4.19 0.43e0.74 0.76e0.89 4.12e5.31 1.40e1.79 2.16e3.10 5.95e7.69 27.16e28.77 2.39e2.96 1.65e1.82 5.70e6.34 57e65 40e47 51e64

523 575 25 29 4.15 4.98 3.88 0.57 0.86 4.93 1.61 2.79 6.98 28.42 2.50 1.76 5.81 62 43 57

679e749 1022-1112 170e177 172e186 1.10e2.75 1.23e3.12 1.10e2.77 1.49e3.26 1.20e2.95 1.41e3.74 2.01e4.31 1.09e2.34 0.42e1.73 27.10e29.57 0.96e1.11 0.89e1.20 7.86e9.80 103e108 146e159 261e279

711 1067 174 181 1.15 1.52 1.17 1.66 0.96 1.75 2.32 1.15 0.54 28.38 1.01 1.04 8.09 106 152 277

Sampling Station

Kish Island (ST6)

Hendurabi Island(ST7)

Shidvar Island(ST8)

Lavan Island(ST9)

Kharg Island(ST10)

Parameters P 25n-alkanes P 25n-alkanes þ Pri þ Phy Pri Phy Overall CPI(n-C11-n-C35) High CPIa Low CPIb LMW/HMW Pri/Phy n-C17/Pri n-C18/Phy n-C29/n-C17 n-C31/n-C19 ACL TAR OEP P 25n-alkanes/n-C16 PLK TRE PETRO

Range

Mean

Range

Mean

Range

Mean

Range

Mean

Range

Mean

410e503 620e726 102e109 104e113 1.22e1.40 1.86e2.03 1.12e1.31 1.32e1.59 0.92e0.1.02 1.46e1.59 1.40e1.53 1.19e1.36 0.60e0.73 28.31e28.90 0.96e1.08 0.93e1.05 10.13e10.89 54e59 74e79 99e110

441 652 104 107 1.32 1.97 1.17 1.41 0.97 1.50 1.47 1.28 0.65 28.78 1.02 0.96 10.78 56 76 100

490e509 746e799 125e141 130e148 1.10e1.46 2.10e2.95 1.05e1.26 1.13e1.66 0.91e0.94 1.16e1.46 1.43e1.63 1.10e1.39 0.60e0.86 27.86e28.99 0.86e1.06 0.92e0.97 9.68e11.30 68e70 97e103 110e120

497 766 132 135 1.26 2.51 1.14 1.24 0.95 1.26 1.52 1.22 0.68 28.95 0.99 0.94 10.95 69 98 115

580e594 977e1061 196e220 200e246 1.09e1.26 2.03e2.65 1.06e1.29 1.20e1.23 0.82e1.35 1.10e1.39 1.10e1.39 1.06e1.20 0.75e0.92 26.95e28.10 0.89e1.20 0.89e1.16 9.6e11.65 94e98 124e149 130e154

587 992 201 203 1.16 2.53 1.11 1.10 0.99 1.20 1.22 1.14 0.81 27.57 1.01 1.00 10.82 95 135 138

810e870 1321e1433 241e290 270e302 1.01e1.19 2.01e2.95 0.69e1.26 1.29e1.53 0.85e1.06 1.06e1.62 1.86e2.09 0.92e1.06 0.72e0.92 27.10e27.93 0.88e1.06 0.89e1.06 9.35e10.32 132e143 190e210 306e339

839 1411 284 288 1.11 2.57 1.06 1.40 0.99 1.24 2.06 0.98 0.80 27.60 0.99 0.99 9.95 139 194 328

903e977 1524e1691 310e352 310e361 1.02e1.20 2.10e3.12 1.01e1.10 1.26e1.56 0.83e1.08 1.10e1.35 1.21e1.42 0.89e1.10 0.78e0.90 27.19e27.82 0.89e1.10 0.98e1.13 9.65e10.35 160e170 220e240 359e372

937 1632 346 348 1.13 2.98 1.08 1.36 0.99 1.23 1.39 1.03 0.82 27.55 0.98 1.00 9.91 164 231 363

CPI25
33 ¼

  1 ðnC25 þ nC27 þ nC 29 þ nC31 þ nC33 Þ ðnC25 þ nC27 þ nC29 þ nC31 þ nC33 Þ þ 2 ðnC24 þ nC26 þ nC28 þ nC30 Þ ðnC26 þ nC28 þ nC30 þ nC32 þ nC34 Þ P

Overall CPI15
35 ¼

P  Odds C17
35 Odds C15
33 þ P 2ð Evens C16
34 Þ

LOW CPI ¼

P P  1 ðodd carbonÞ ðodd carbonÞ C C P 15
21 þ P 15
21 2 C14
20 ðeven carbonÞ C16
22 ðeven carbonÞ

High CPI ¼

P P  1 ðodd carbonÞ ðodd carbonÞ C C P 25
35 þ P 25
35 2 C24
34 ðeven carbonÞ C26
36 ðeven carbonÞ

P LMW ðC eC Þ ¼ P 11 20 HMW ðC21 eC35 Þ Pri ¼ ratio of pristane to phytane Phy P½27ðnC Þ þ 29ðnC ÞÞ þ 31ðnC ÞÞ þ 33ðnC Þ 27 29 31 33 P ACL ¼ ½nC27 þ nC29 þ nC31 þ nC33 

Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080

8

R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

OEP ¼

NAR ¼

TAR ¼

ðnC21 þ 6 nC23 þ nC25 Þ 4ðnC22 þ nC24 Þ ½

P P ðC19 eC35 Þ
2 EvenðnC20 e nC34 Þ P ½ ðnC19 e nC35 Þ

ðnC27 þ nC29 þ nC31 Þ ðnC15 þ nC17 þ nC19 Þ

PLK ðPlanktonicÞ ¼ ðnC15 þ nC17 þ nC19 þ nC21 Þ TRE ðTerrigenousÞ ¼ ðnC23 þ nC25 þ nC27 þ nC29 þ nC31 þ nC33 Þ PETRO ðPetrogenicÞ ¼ ðnC12 þ nC14 þ nC16 þ nC18 þ nC20 Þ

Lavan, Siri and Lark reefs, accounting for 48.27e73.08%, which were of a gravelly nature. The variation of the clay content in the reef sediments demonstrated a major correlation with silt (r ¼ 0.71, p < 0.05). 3.1.2. Spatial distribution of biogenic elements The summary of obtained results from biogenic elements is presented in Table 1. The spatial distribution of TOC, BC, TN, TIN, TON, TOC/TN, TOC/TS and TS is depicted in Fig. 2b, c, d, e, f. Spatial variation (p < 0.05) was observed for all measured biogenic elements. Except for Lark Island, which demonstrated high TC concentrations between 6.59 and 7.34 mg.g
1 with a mean value of 6.96 mg.g
1, TC concentrations varied from 4.09 to 5.16 (4.84 mg.g
1) in Hormoz Island (ST1, in the northern east part of the Gulf) as the lowest concentration and 10.13e12.91 mg.g
1 (12.55 mg.g
1)in Kharg Island (ST10, in the northwestern part of the Gulf) as the highest concentration and were significantly (p < 0.05) and regularly elevated from the east toward the west part of the Gulf (Fig. 2b). Similarly, the highest TOC concentrations were observed at Kharg Island, which varied from 7.36 to 9.95 mg.g
1 with mean concentration of 9.72 mg.g
1, followed by Lavan and Siri and ranged from 6.83 to 7.92 mg.g
1 (7.87 mg.g
1) and 5.43e6.07 mg.g
1 (5.86 mg.g
1), respectively. These Islands are clearly under the influence of numerous industrial activities particularly oil extraction from oilfields, petrochemical factories, and refineries. Lowest concentration was spanned for Hormoz Island, varied from 2.95 to 3.58 mg.g
1 (3.35 mg.g
1), followed by Qeshm (ST3) and ST4 which ranged 3.40e3.81 mg.g
1 (3.51 mg.g
1) and 3.16e3.97 mg.g
1 (3.92 mg.g
1), respectively, as it is indicated in Table 1 and Fig. 2b. Although TOC concentrations exhibited high oscillation over the study area and revealed comparatively ascending spatial distribution from the east to the west part of Gulf, BC exhibited heterogeneous spatial pattern (except for Lark Island) and ranged from 1.03 to 3.41 (Fig. 2b). By contrast to TOC, the highest and lowest BC concentrations were determined for Lark (2.89e3.41 mg.g
1 (3.28 mg.g
1)) and Hormoz (1.14e1.58 mg g
1 (1.49 mg.g
1) Islands. As observed for TC, there were significantly considerable differences (p < 0.05) for TOC and BC among all sampling sites. By contrast what was observed for TC, TN, which is composed of organic nitrogen (ON) and inorganic nitrogen (IN), showed fluctuations in two different ways (Fig. 2c). For instance, Lark reefs demonstrated strong tendency in accumulating TN, varying from 1.37 to 2.11 mg.g
1 (1.96 mg.g
1), while Kharg reefs exhibited ambiguous tendency in accumulation (1.03e1.63 mg.g
1 (1.56 mg.g
1) as this site is more influenced by industrial activities

20

oddeeven carbon number preference.

such as Lavan (1.46e1.85 mg.g
1 (1.67 mg.g
1) and Siri (0.88e1.49 mg.g
1 (1.13 mg.g
1) (Table 1, Fig. 2c). The lowest concentration of TN was also determined for Hengam and Hormoz reefs and varied from 0.57 to 0.68 mg.g
1 (0.61 mg.g
1) and 0.83e0.98 mg.g
1 (0.91 mg.g
1),respectively. However, regarding the heterogeneous distribution of TN (Fig. 2c), it could be inferred that TN distribution was different from TC and the regular trend was not found as what observed for TC (Fig. 2b). Interestingly, the mean concentration of TON and TIN revealed similar spatial distribution with TN, which oscillated from 0.40 to 1.10 mg.g
1 for TON and from 0.13 to 0.86 mg.g
1 for TIN (Table 1, Fig. 2c). The mean concentration of TS (Table 1), ranging from 0.44 to 1.23, indicated different trend from TC and TN. The mean maximum concentrations were for Lark (1.23), followed by Kharg (1.17 mg g
1), Qeshm (1.08 mg.g
1), Kish (1.00 mg.g
1) and Lavan (0.97 mg.g
1), respectively, whilst the minimum was for Hengam (0.44 mg.g
1) followed by Hormoz (0.65 mg.g
1) (Table 1,Fig. 2f). The mean C/N values oscillated from 2.96 to 8.64 with the overall mean of 3.99 and were generally under 10. The mean calculated TOC/TN ratios vacillated according to the stations (p < 0.05) from 2.96 at Shidvar Island to 8.64 at Hengam Island (Table 1, Fig. 2d). The high TOC/TN ratios were observed in the Hengam (8.64), Kharg (8.03) and Siri (6.29), while the lower values were Lark (3.35), Qeshm (3.13) and Shidvar (2.96) reef sediments. The minimum and maximum of TOC/TS ratio were calculated for Qeshm (4.34) and Hengam (11.98), respectively (Table 1, Fig. 2e). It is noteworthy to point out that Lark Island (ST2) indicated the highest values of BC, TON, TIN, TOC/TN and TOC/TS compared to other stations and significant differences (p < 0.05) were observed. One-way ANOVA well revealed significant difference from calculated concentration of TC, TN and TS among all sampling stations and significantly this trend was spanned among all sites for other examined biogenic elements (Fig. 2). 3.2. Spatial distribution of n-alkanes A set of 25 n-alkanes (n-C11en-C35), isoprenoids, UCMs, carbon preference indices (overall CPI, CPIa, CPIb) and other deterministic ratios of isoprenoids and n-alkanes in the reef surface sediments are demonstrated in Table 2. The averaged sums of the measured nalkane concentrations (Sn-alkanes) varied from 385 to 937 mg.g
1dw, with an overall mean for the entire study of 590 mg.g
1dw. The mean concentration of S25n-alkanes) along with the isoprenoids of pristine and phytan ranged from 429 to 1632 mg.g
1dw with total average for the whole study area of 880 mg.g
1dw. The highest mean of S25 n-alkanes was measured in Kharg coral reef, which ranged from 903 to 977 with mean value of 937 mg.g
1dw, followed by Lavan 810 to 870 (839 mg.g
1dw), Siri

Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080

R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

9

Fig. 3. 3D and 2D spatial distributions of petroleum biomarkers: S25n-alkanes (a), S30PAHs (b) and S9 Hopanes (c) of the reef surface sediments of the coral reefs in the Persian Gulf on July 2014.

Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080

10

R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

Fig. 4. Non-parametric MDS ordination plots of n-alkanes (a), PAHs (c) and Hopanes (d) congeners and sampling sites (b)based on concentrations) in the reef surface sediments of the Persian Gulf.

679 to 749 (711 mg.g
1dw) and Lark 479 to 549 (527 mg.g
1dw) coral reefs, respectively, while the lowest values of mean concentration were calculated in Hormoz Island, which varied from 361 to 397 mg.g
1dw with average concentration of 385 mg.g1dw followed respectively by Qeshm 449 to 549 (452 mg.g
1dw) and Kish 410 to 503 (441 mg.g
1dw) coral reefs (Fig. 3a). The spatial variation of the mean concentrations of the Sn-alkanes is presented in Fig. 3a. As can be seen, with exception of Lark and Siri reefs, the concentrations of the Sn-alkanes increased from the east (Hormoz reefs) toward the west (Kharg reefs) part of the Persian Gulf. Compared to other sampling sites, concentrations in most samples of Kharg, Lavan, Siri and Lark coral reefs were significantly higher (P < 0.05) and these results were consistent with prominence of hydrocarbon inputs into these sites. This disperse distribution of n-alkanes concentrations demonstrate that oil contamination was not P deposited uniformly. 25 n-alkanes concentrations disturbed heterogeneity in Kharg, Lavan, Siri and Lark sites due to their specific location, if these sites are ignored, the homogenous distribution is dominant in the whole study area because these specific sites exhibit almost identical n-alkanes concentrations. Results of NPMDS of the 25 n-alkanes congeners in the reef sediment for each sampling location demonstrated that n-C16, n-C14, n-C12, n-C18 and n-C20 were the most influential congeners in most sampling sites (Fig. 4a) and sites of Kharg, Lavan and Siri were distinguished from other stations (Fig. 4b) as the most affected sites by anthropogenic activities. 3.3. Spatial distribution of PAHs In this investigation, the PAHs refer to the sum of 30 PAHs, 20 parent PAHs and 10 Alkyl PAHs analyzed. The arithmetic means, P P P P and ranges of the 30 PAHs, 16 PAHs, Alkyl PAHs and Parent

P P P 25n-alkanes, 30 PAHs and 9 Hopanes

PAHs in reef sediments are depicted in Table 3. Results elucidated that the free concentrations of the determined total mean concentrations of PAHs varied greatly, ranging from 326 to 793 ng.g
1dw with overall mean concentration of 499 ng.g
1dw in the reef sediments of the whole study area. In addition, the highest P and lowest concentration of 30 PAHs were appraised in Kharg and Hormoz coral reefs, which ranged from 769 to 813 ng.g
1dw (mean 793 ng.g
1dw) and from 289 to 345 ng.g
1dw (mean 326 ng.g
1dw), respectively. Fig. 3b indicates the spatial variation of the detected total concentration of PAHs at various sampling P sites and reveals that 30 PAHs in Kharg and followed by Lavan from 700 to 761 (mean 710), Siri from 589 to 634 (mean 601) and Lark from 429 to 479 (mean 446) coral reefs were higher than other P sampling sites. The 30 PAHs concentration in sediment samples of Kharg, Lavan and Siri coral reefs were 2 times higher than that of the other sites (except Lark site), and one-way ANOVA analysis demonstrated considerably significant difference (p < 0.05) among P concentration of 30 PAHs at all sampling locations. The distriP bution of 30 PAHs concentration in the Gulf was fairly unsimilar in different sampling sites which this heterogeneous spatial variation of PAHs could be explained in terms of site characteristics. Moreover, alike to n-alkanes, NPMDS analysis exhibited four clusters of sampling sites based on the intensity of anthropogenic activities (Fig. 4b). As being demonstrated in Table 3, the mean P P concentrations of parent and Alkylated PAHs varied from 158
1 to 364 ng.g dw and 167e428 ng.g
1dw with overall mean values P of 272 and 226 ng.g
1dw, respectively. parent PAHs attributed P 45.95e65.75% of the 30 PAHs in the reef sediments of the entire P study areas, while Alkylated PAHs accounted for 34.48e51.28% of P P the 30 PAHs. The concentrations of 16 PAHs varied from 127 to P
1 444 ng.g dw, which attributed 39.23e55.97% of the 30 PAHs in P the reef sediments. Analogous to the spatial distribution of 30

Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080

R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

11

Table 3 Concentrations, indices and ratios of PAHs in reef surface sediments from the coral reefs in the Persian Gulf, July 2014 (ng.g
1, dw). related parameters are calculated based on reported studies (Azimi Yancheshmeh et al., 2014; Bakhtiari et al., 2010a; Bakhtiari et al., 2009a; Resmi et al., 2016; Shahbazi et al., 2010; Shirneshan et al., 2016a; Varnosfaderany et al., 2014). Sampling Station

Hormoz Island (ST1)

Lark Island (ST2)

Qeshm Island (ST3)

Hengam Island (ST4)

Siri Island (ST5)

Parameters P 30PAHs P 16PAHs P APAHs P PPAHs P C. PAHs P P 16PAHs/ 30PAHs (%) P P APAHs/ 30PAHs (%) P P PPAHs/ 30PAHs (%) P P C.PAHs/ 30PAHs (%) P 2 ring PAHs (%) P 3 ring PAHs (%) P 4 ring PAHs (%) P 5 ring PAHs (%) P 6 ring PAHs (%) P MP/P LMW/HMW Phe/Ant BaA/Chr Flu/Pyr P P 4,5,6 rings/ 30PAHs Flu/Flu þ Pyr BaA/BaA þ Chr Ant/Ant þ Phe InP/InP þ Bghi P 9 Hopanes Ts/Tm S/(S þ R)

Range

Mean

Range

Mean

Range

Mean

Range

Mean

Range

Mean

289e345 120e134 161e172 140e163 74e81 37.16e41.30 47.69e53.89 47.19e52.36 21.36e27.59 16.39e21.16 32.60e41.69 20.36e26.49 17.36e21.36 4.96e7.69 3.89e5.10 1.29e1.62 26.06e27.65 0.80e0.92 0.81e0.92 0.18e0.22 0.47e0.53 0.17e0.22 0.03e0.08 0.16e0.21 83e94 0.27e0.31 0.51e0.62

326 127 167 158 78 39.23 51.28 48.72 24.04 17.02 36.15 21.69 18.95 6.18 4.14 1.43 26.23 0.87 0.85 0.20 0.51 0.19 0.06 0.18 88 0.30 0.57

429e479 410e223 191e207 231e256 110e129 41.69e52.36 40.29e51.19 51.35e61.10 23.65e28.69 24.36e33.71 42.16e49.10 10.36e13.20 8.10.10.11 6.10e7.12 4.26e5.10 1.09e1.22 38.96e42.31 0.89e0.99 0.92e0.98 0.13e0.23 0.41e0.53 0.17e0.26 0.01e0.05 0.11e0.22 317e322 0.41e0.50 0.56e0.63

446 215 198 247 115 48.39 44.44 55.56 25.91 26.88 46.36 11.01 9.37 6.38 4.70 1.18 40.11 0.96 0.94 0.18 0.49 0.21 0.03 0.20 320 0.43 0.59

342e410 191e243 124e146 241e275 83e106 50.36e54.69 30.269e46.89 60.59e72.19 17.69e29.69 15.12e19.62 30.26e41.62 18.69e23.62 17.29e22.16 4.69e7.26 4.10e5.12 1.13e1.85 36.59e38.95 0.71e0.82 1.10e1.27 0.13e0.23 0.36e0.53 0.09e0.13 0.03e0.09 0.12e0.19 119e134 0.37e0.42 0.53e0.64

382 200 131 250 95 52.38 34.48 65.52 25.00 16.97 36.23 21.46 19.09 6.25 4.32 1.51 37.01 0.75 1.20 0.19 0.42 0.10 0.07 0.15 123 0.39 0.57

409e489 210e251 143e177 279e312 112e119 43.59e59.10 30.16e41.36 61.10e69.29 21.20e31.19 14.36e21.65 31.29e44.36 17.69e23.26 15.85e23.62 5.96e7.95 4.13e5.95 1.10e1.36 27.69e28.92 0.87e0.93 0.77e0.93 0.13e0.23 0.41e0.53 0.13e0.23 0.02e0.08 0.12e0.21 140e153 0.47e0.54 0.51e0.64

442 232 151 291 114 52.56 34.25 65.75 25.91 16.83 36.43 20.78 19.52 6.44 4.41 1.27 28.87 0.91 0.88 0.20 0.47 0.17 0.05 0.19 149 0.50 0.58

589e634 310e346 279e310 302e310 162e172 51.03e57.62 42.36e51.62 43.19e53.85 27.16e28.62 21.62e29.32 42.19e52.36 9.36e12.30 9.19e10.32 6.10e7.32 4.13e5.10 1.09e1.29 33.46e39.10 0.89e0.99 0.92e0.97 0.16e0.21 0.43e0.52 0.19e0.23 0.01e0.05 0.17e0.23 316e356 0.43e0.51 0.60e0.66

601 327 293 308 169 54.35 48.78 51.22 28.09 26.85 46.40 10.88 9.45 6.41 4.74 1.17 36.67 0.96 0.95 0.19 0.49 0.20 0.04 0.20 335 0.48 0.61

Sampling Station

Kish Island(ST6)

Parameters P 30PAHs P 16PAHs P APAHs P PPAHs P C.PAHs P P 16PAHs/ 30PAHs (%) P P APAHs/ 30PAHs (%) P P PPAHs/ 30PAHs (%) P P C.PAHs/ 30PAHs (%) P 2 ring PAHs (%) P 3 ring PAHs (%) P 4 ring PAHs (%) P 5 ring PAHs (%) P 6 ring PAHs (%) P MP/P LMW/HMW Phe/Ant BaA/Chr Flu/Pyr P P 4,5,6 rings/ 30PAHs Flu/Flu þ Py BaA/BaA þ Chr Ant/Ant þ Phe InP/InP þ Bghi P 9 Hopanes Ts/Tm S/(S þ R)

Range

Mean

Range

348e401 170e189 140e157 210e246 91e110 43.62e49.16 38.13e41.16 57.36e62.15 21.62e27.16 13.16e18.95 34.16e39.12 18.36e22.19 17.92e22.34 5.16e7.32 3.19e5.16 1.20e1.40 1.10e1.31 0.92e1.06 1.01e1.09 0.11e0.21 0.45e0.62 0.12e0.19 0.39e0.54 0.70e0.74 154e173 0.40e0.47 0.62e0.71

373 181 146 226 96 48.68 39.22 60.78 25.91 16.81 36.46 20.70 19.57 6.47 4.34 1.32 1.15 1.01 1.04 0.17 0.51 0.17 0.47 0.71 162 0.43 0.65

410e446 188e210 164e179 240e258 103e112 43.59e51.19 37.65e43.19 54.38e61.28 21.34e27.19 15.27e18.34 34.28e38.19 17.36e23.65 17.69e23.15 5.16e7.95 3.28e5.69 1.10e1.34 27.19e28.75 0.82e0.96 0.87e0.95 0.17e0.23 0.45e0.49 0.15e0.23 0.01e0.06 0.18e0.23 167e192 0.53e0.62 0.53e0.62

P

P

P

Fluoranthene Pyrene

APAHs ¼ Sum of alkylated PAHs

Flu=Pyr ¼

PPAHs ¼ Sum of parental PAHs

BaA=Chr ¼

C:PAHs ¼ Sum of carsinogenic PAHs

Hendurabi Island(ST7)

Ant=Ant þ Phe ¼

BenzoðaÞanthracene Chrysene

ðFluÞ=ðFlu þ PyrÞ ¼

Shidvar Island(ST8)

Lavan Island(ST9)

Island Island(ST10)

Mean

Range

Mean

Range

Mean

Range

Mean

421 198 173 247 109 47.16 41.15 58.85 25.91 16.80 36.47 20.64 19.60 6.48 4.55 1.16 28.62 0.94 0.92 0.19 0.48 0.17 0.04 0.20 186 0.57 0.59

479.35e510 210e241 207e226 271e290 120e134 37.19e51.29 36.59e55.12 51.28e61.38 20.16e29.90 14.36e24.59 34.16e49.26 10.34e21.57 13.16e19.21 4.69e7.85 3.16e5.17 1.10e1.31 25.14e28.39 0.90e0.97 0.91e0.98 0.10e0.18 0.43e0.49 0.17e0.19 0.01e0.06 0.16e0.24 231e257 0.54e0.62 0.56e0.62

497 229 211 285 128 46.06 42.55 57.45 25.91 20.76 40.54 15.43 16.73 6.54 4.64 1.17 27.49 0.95 0.93 0.17 0.48 0.18 0.05 0.20 246 0.59 0.58

700e761 307e411 351e410 312e358 175e196 39.51e56.49 47.36e54.40 43.64e51.36 23.15e32.20 14.36e19.20 47.32e53.19 9.15e13.25 13.19e17.59 5.21e7.69 4.61e5.94 0.29e0.36 15.49e17.31 0.85e1.09 0.89e1.07 0.18e0.23 0.53e0.58 0.04e0.09 0.03e0.09 0.12e0.19 390e419 0.57e0.63 0.70e0.73

710 378 364 345 188 53.31 51.28 48.72 26.60 16.99 50.21 11.52 15.05 6.23 5.25 0.35 16.79 0.99 1.00 0.20 0.50 0.08 0.06 0.15 404 0.61 0.71

769e813 429e457 420e431 361e372 210e224 51.39e62.18 51.34e57.95 43.15e48.64 21.69e34.52 17.34e23.50 57.29e63.18 10.48e11.39 5.98e6.75 5.17e5.45 5.18e5.88 1.16e1.35 30.17e30.95 0.94e0.98 0.97e1.08 0.12e0.19 0.45e0.59 0.12e0.25 0.06e0.09 0.10e0.17 513e584 0.81e0.92 0.71e0.78

793 444 428 364 216 55.97 54.05 45.95 27.32 20.23 60.82 11.08 6.68 5.20 5.79 1.25 30.69 0.97 1.01 0.16 0.49 0.14 0.07 0.13 568 0.89 0.74

ðAnthaceneÞ ðAnthacene þ PhenanthreneÞ

InP ðIndeno½1; 2; 3
cdpyreneÞ ¼ InP þ Bghi ð Indeno½1; 2; 3
cdpyrene þ Benzo½ghiperyleneÞ

ðFluorantheneÞ ðFluoranthene þ PyreneÞ

Ts : 18a ðHÞ
22; 29; 30
trisnorhopane

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12 P

R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

MP=P ¼

Phe=Ant ¼

Sum of methylated Phenanthrene Phenanthrene Phenanthrene Anthracene

ðBaAÞ=ðBaA þ ChrÞ ¼

ðBenzoðaÞanthraceneÞ ðBenzoðaÞanthraceneÞ þ ðChryseneÞ

P 4; 5; 6 rings Sum of 4; 5 and 6 ringed hydrocarbons P ¼ 30PAHs sum of 30PAHs

P PAHs in reef sediments, the mean maximum values of 16 PAHs were found in Kharg and Lavan Island, respectively, and followed by Siri and Lark reefs (Table 3). Nonetheless, for the other sampling P sites, the concentrations of 16 PAHs were as low as those in the Kish, Hengam, Qeshm and Hormoz Islands, except for Shidvar and Henduarabi. 3.4. Spatial distribution of Hopanes 9 Hopanes, another persistent petroleum biomarker, were also identified and analyzed from the study area under observation and the statistical results of the sediments samples are depicted in Table 3and Fig. 4d. The concentrations of these biomarkers were not below detection limit in most reef sediment samples. Mean P concentration of 9 Hopanes exhibited remarkable oscillation, P P similar to what was observed for 25 n-alkanes and 30PAHs, with significantly considerable differences (p < 0.05) between stations, these discrepancies varied from 88 to 568 with overall mean concentration of 258 ng.g
1dw. The highest concentration was in Kharg reefs, where the maximum of other petroleum hydrocarbons were spanned, and fluctuated from 513 to 584 ng.g
1dw (mean:568 ng.g
1dw) followed by Lavan 390e4419 ng.g
1dw (404 ng.g
1dw), Siri 316e356 ng.g
1dw (335 ng.g
1dw) and Lark 317e322 ng.g
1dw (320 ng.g
1dw), whereas the minimum was in Hormoz Island (similar to n-alkanes and PAHs), ranged from 83 to 94 ng.g
1dw (88 ng.g
1dw). Except for superficial sediments of Lark reefs, a continually upward trends in concentration of Hopanes from the east to the west part of study area is observable. However, heterogamous spatial distribution was observed for Hopanes as shown for n-alkanes and PAHs (Fig. 3c).

Tm : 17a ðHÞ
22; 29; 30
trisnorhopane

S=ðS þ RÞ ¼ ab C31

sediments and the clay content in sediments. From the east to the west part, as the particle size decreased, the TOC and TN contents gradually increased. It is reported that silt is dominated by quartz particles and has a surface area/volume ratio orders of magnitude less than clay (Szava-Kovats, 2008), giving silt a far lower adsorption capacity than clay. However, the silt and clay contain most of the organic materials due to interaction between the clay mineral and sorption on the particles that have large surface areas (Song et al., 2011). It is also shown that fine-grain substances had a large surface area and could thus absorb and preserve more carbon  and nitrogen elements (Alvarez and Wendel, 2003; Ye et al., 2013; Yu and Wang, 1988). Biotic exclusion relates to the enclosure of OMin clay minerals that prevents the access of organism or their digestive enzymes (Mayer, 2004). Clay can sorb OM onto its mineral surfaces through van der walls interactions, ligands exchange, divalent cation bridging, electrostatic and hydrophobic bonding (Clemente and Simpson, 2013; Feng et al., 2005; Mikutta et al., 2007) and this interaction has a stabilization effect on the organic matter. Therefore, particle size has an integral and key effect on the storage of OC in sediments (Wang et al., 2007; Ye et al., 2013; Zhou et al., 2007). Our results were similar to those studies conducted which exhibited TOC and TN contents which had a better positive correlation with the clay content relative to other particle sizes in sediments (Chen et al., 2007; Gao et al., 2007; Ye et al., 2013). In the silty sediments, the TOC and TN of sediments were restricted to their sources, so that although the particle sizes of the sediments were smaller, they did not adsorb more TOC and TN than clay. The results of this paper indicated that the TOC and TN were chiefly deposited in fine particles (clay) in our sampling sites. 4.2. Interaction between biogenic elements

4. Discussion 4.1. The effect of particle size in reef surface sediments on pollution load Textural characteristics displayed spatial variation in the whole study region. Hormoz and Qeshm were sandy, while clay was dominant in most polluted sites particularly Kharg, Lavan and Siri and to some extent Lark. Fig. 2a exhibits the spatial distribution of grain size in the whole study area. As can be seen, the heterogeneous distribution is dominant on the whole study area, but it is apparently obvious that there is an accelerating increase on sand particles from the west toward the east, while the predominance of clay can fairly observed form the east toward the west. Grain size data from present investigation is relatively identical and consistent with other investigations carried out all over the world (Andersson et al., 2014; Cattaneo et al., 2007; Costa et al., 2016; Frignani et al., 2005; Hu et al., 2009; Li et al., 2015c; Maciel et al., 2016; Micic et al., 2013; Ogrinc et al., 2005; Oyo-Ita et al., 2010; Pisani et al., 2013; Romano et al., 2013; Sanches Filho et al., 2013; Tesi et al., 2013; Tesi et al., 2007; Wang et al., 2016; Wang et al., 2013). The interaction between clay and OM has received the most attention and research has shown that clay and OM form strong association on both coastal and marine sediments (Hedges and Keil, 1995; Mayer, 1994). Fig. 5g, h and j indicates that there was a significant positive correlation between the TOC and TN in reef

OM in marine sediments represents a range of precursor organic materials and is composed of a broad spectrum of organic constituents from a variety of sources such as terrestrial, riverine and estuarine environments (Bouillon and Boschker, 2006). Terrestrial OM inputs are remarkably more in coastal regions and this OM can often retained in the sediments for a while and gradually transform by the time and reaches the sea (Bouillon and Boschker, 2006). The concentrations of TN in the Gulf were much lower, compared to the sediments in other worldwide areas (Hu et al., 2014; Kigoshi et al., 2014; Resmi et al., 2016; Ye et al., 2013), while TOC exhibited a relatively low to moderate content and a significant variability (percentage) (<0.05) in sediments of the Gulf. These levels were comparable with data on OC content found in sediments from another part of the world (Azimi Yancheshmeh et al., 2014; Bakhtiari et al., 2010b; Bakhtiari et al., 2009a; Hu et al., 2014; Kigoshi et al., 2014; Resmi et al., 2016; Shahbazi et al., 2010; Shirneshan et al., 2016b; Tesi et al., 2013; Tesi et al., 2007; Turchetto et al., 2007; Ye et al., 2013). C/N (TOC/TN) weight ratio is a determining criterion to discern source identification of OM nchez-García et al., 2013; (Kigoshi et al., 2014; Meyers, 1997; Sa TONG et al., 2010; Wang et al., 2016; Yamamuro, 2000; Ye et al., 2013). A number of studies have reported that the range 5e7 is for marineOM(Redfield et al., 1963), while values > 15 is for terrestrial organic matter (Mengchang et al., 2008; Meyers, 1997). In another studyGiovanela et al. (2010)have suggested that high C/

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R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

13

Fig. 5. The relationships between: Clay% and TOC%(a); Clay% and TN%(b); TN and TOC (c); TSand TOC(d); totaln-alkanes with TOC, TON and clay% (e, f), total PAHs with TOC, TON, Clay% (g, h) and total Hopanes with TOC, TON and Clay (i, j) in reef surface sediments in the Persian Gulf.

N values (>20) indicate terrestrial OM inputs such as lignin, tannins, cellulose, whereas values < 10 are indicative of non-vascular plants. In the present study, the mean C/N values were generally under 10 suggesting a large influence from marine organisms (Mayer, 1994; TONG et al., 2010) (Table 1, Fig. 2d). This may indicate that the marine OM is more recalcitrant and less soluble in the water column during early diagenesis, relative to the terrestrial OM (Giovanela et al., 2010; Mengchang et al., 2008). A strong positive correlation between TOC and TN in reef sediments were found according to the linear regression results (r ¼ 0.72) (Fig. 5h), which

suggested that TN was predominantly organic nitrogen. This was agreeable with the studies from the sediments of the Zhujiang (Pearl River) and Changjiang (Yangtze River) estuaries (Yang et al., 2011); a tidal wetland of Luoyuan Bay(Ye et al., 2013); lake sediments of the Yangtze River Basin, China (Gui et al., 2013); Sishili Bay, northern Yellow Sea, China (Wang et al., 2013); the central Ulleung Basin, East Sea, China (Kim et al., 2014); in mangrove ecosystems of northern Kerala, India (Resmi et al., 2016). Besides TN was remarkably correlated with clay (r ¼ 0.74) (Fig. 5j), there was a positive correlation between the TOC and clay of reef sediments in

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R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

the Gulf (r ¼ 0.75) (Fig. 5g), and such a correlation was more considerably significant in the sediment of sampling sites with higher accumulation of detected petroleum biomarkers. This result was consistent with the investigations conducted in all over the world (Chen et al., 2007; Resmi et al., 2016; Ye et al., 2013). TOC was remarkably correlated with TS (Fig. 5i). It is reported that TOC/TS ratio under and above normal marine line (2.8) could indicate the deposition of organic matter under anoxic and oxygenated conditions (Lyons and Berner, 1992; Resmi et al., 2016). With regard to this fact, TOC/TS ratio in mostly all samples ascend above normal marine line, and varies from 4.34 to 11.98 (7.63), reflecting the deposition under anoxic bottom-water conditions. Generally speaking, with regard to the mentioned facts, there is no doubt that the sediments from the stations in the eastern of the Gulf (ST1, ST3, ST4, ST5) had at least two times lower total carbon (especially TOC) and nitrogen content (in particular TON) compared to western (particularly ST9 and ST10). Despite the very similar spatial distribution of biogenic elements from the east to the west part of the Gulf, significant differences were observed. TC, TN, TS, TOC and TON demonstrated approximately homogenous spatial distribution which is elevated from the east to the west regularly, whist BC and TIN exhibited heterogeneous spatial distribution with irregular decrease from the east to the west. 4.3.

P

25 n-alkanes in reef surface sediment

The overall average S25n-alkane concentration in this investigation were higher than those found in other studies all over the world such as KrishnaeGodavari Basin, India (269.50e449.90 mg.g
1 (Mani et al., 2016)); Kharg Island, SW, Iran (19.75e49.25 mg.g
1(Akhbarizadeh et al., 2016)); Capibaribe Estuarine System, Brazil (ND- 9.47 mg.g
1 (Maciel et al., 2016)); BohaiSea, China (0.88e3.48 mg.g
1, (Li et al., 2015a)); Northern Persian Gulf (ND to 1.71 mg.g
1 for costal sediments and 0.2e0.63 mg.g
1 for mangrove sediments (Mohebbi-Nozar et al., 2015)); Bohai Bay, China (6.3e535 mg.g
1 (Zhou et al., 2014)); Lake Dianchi, China (119.4e417.3 mg.g
1 (Fang et al., 2014)). On the other hand, the average total n-alkane concentrations were comparatively low compared to heavily contaminated sites, such as Barataria Bay, Gulf of Mexico (77399 mg.g
1 (Kırman et al., 2016)); River sediments in Vietnam (1056e34794 mg.g
1 (Duong et al., 2014)); Gulf of Mexico (0.050e535000 mg.g
1 (Sammarco et al., 2013)); Khniss TunisianCoast, Mediterranean Sea (1020e2320 mg.g
1 (Ines et al., 2013)); Cross River and estuary system, SE Nigeria (0.05e1179 mg.g
1 (Pisani et al., 2013)). It has been reported that determining indices of fit to specify the goodness of fit of an MDS model are Young's stress and RSQ (Ju et al., 2016), which low values of <0.1(Young's stress) and high values of >0.6 (RSQ) totally exhibit a good ordination (Clarke and Warwick, 1994; Ju et al., 2016). In the current study, the Young's stress 0.09 and RSQ were 0.99 suggesting a good ordination with a small chance of misinterpretation (Ju et al., 2016). NPMDS analysis revealed four clusters of sampling sites (Fig. 4b). This four groups were distinguished by the intensity of anthropogenic activities and industrialization including Siri (ST5), Lavan (ST9) and Kharg (ST10) Islands with high industrial activities, Shidvar, Lark and to some extent Hengam Islands with moderate anthropogenic activities and Hendurabi, Kish and Qeshm with low industrial activities and Hormoz with no to very slight activities. Similarly, the highest Snalkane concentrations were observed in Kharg, Lavan, Siri and to some extent Lark coral reefs. In comparison, the concentrations of Sn-alkanes in another sampling sites were lower than those sites, suggesting that these four reefs are more polluted by pollution events e.g. oil spills, oil transportation, oil extraction and exploitation and another industrial activity. NPMDS analysis also

demonstrated that among the n-alkanes congeners, n-C16, n-C14, nC12, n-C18 and n-C20 were discriminated from other congeners (Fig. 4a), inferring that they are the most influential congeners in the grouping based on sampling sites.

4.3.1. Source apportionment with aliphatic biomarkers Saturated hydrocarbons in the marine environments have intricated and diverse origins. Some general criteria to determine the possible origins (anthropogenic or natural) of organic compounds have been used (de Souza et al., 2011; Mille et al., 2007). GC traces revealed regular distribution ranged from n-C11 to n-C35 alkanes with equivalent distribution pattern of both odd-carbonnumbered alkanes and even-carbon-numbered alkanes (Fig. 6). As a matter of fact, GC trace analysis exhibited a unimodal and bimodal n-alkane distribution at most sampling sites (Fig. 7a and b), whereas three-modal distribution was found in Kharg, Lavan Siri and Lark Islands (Fig. 7a). Total n-alkane concentration in this marine system was high in the study area especially in sites with higher anthropogenic activities, which could be ascribable to the massive proportions of lower chain n-alkanes than their higher homologues. The domination of odd-short chain alkanes could be ascribable to higher planktonic (PLK21) abundance, whilst evenshort chain alkanes are attributed to higher bacterial activities (Resmi et al., 2016; Wu et al., 2001). Even chain alkanes in many parts of the study area (except for Hormoz, Qeshm and Hengam) were dominated, which might be interpreted by the overwhelming bacterial activities particularly at higher temperatures (Alongi et al., 2005; Resmi et al., 2016). It has been reported that higher abundance of OM could assist to accelerate propagation of bacterial community (Resmi et al., 2016). In addition, it has been shown that bacterial lipids have even-carbon preference for short-chain-length alkanes i.e., n-C25) in sediments of Hormoz, Qeshm and

21

Planktonic.

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R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

15

Fig. 6. Distribution of n-alkanes (n-C11en-C35) in the reef surface sediments in the Persian Gulf.

Hengam reefs, suggesting the strong influence of OM from biological materials, especially epicuticular waxes from higher plant, because long-chain n-alkanes (n-C25 to n-C33) with odd chain carbon preference are abundant in vascular plants (Collister et al., 1994; Resmi et al., 2016; Simoneit, 2002). Carbon preference Index (CPI) values, defined by a value close to 1 for petroleum-derived hydrocarbon rich samples (Aboul-Kassim and Simoneit, 1997; Liu et al., 2012; Maciel et al., 2016), had values ranged from 1.05 to 1.95 for most sites (except for Hormoz, Qeshm and Hengam coral reefs) in particular for Kharg,Lavan, Siri and Lark coral reefs over the course of the study (Table 2,Fig. 8a), suggesting that there were analogous effects from petroleum sources and more likely from oil pollution (Bakhtiari et al., 2010b; Resmi et al., 2016). Fig. 8b illustrates the calculated mean values for overall CPI(n-C11-n-C35) for the whole study area. In Hormoz

reefs, the overall CPI varied from 2.65 to 5.95 (4.37), while in Qeshm and Hengam coral reefs ranged from 4.19 to 4.56 (4.46) and 4.06 to 4.39 (4.15), respectively (Table 2). In Hormoz, Qeshm and Hengam coral reefs, the CPI values were found to be significantly greater than 1.0, in the range of n-C25-n-C34 indicative of land plants (Bakhtiari et al., 2010b; Resmi et al., 2016) and the dominance of nC27, n-C29 and n-C31n-alkanes was pronounced (Fig. 8b. The high values for CPI(n-C11-n-C35) exhibit a robust contribution of terrestrial plant waxes (Peters et al., 2005). Consistent with the high wax mass contribution in sampling sites noted above, the highest overall CPI also occurred in those coral reefs (3.63), and supports the conclusion that the largest effect from biogenic sources occurred in these sampling locations. Because it is well-known that n-C27,n-C29 and n-C31n-alkanes are formed by land plants (Bianchi and Canuel, 2011; Peters and Moldowan, 1993). In addition to

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R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

Fig. 7. Capillary gas chromatograms of distribution of individual n-alkanes in the reef surface sediments of the Kharg(a), Lavan(b) and Lark(c) from the Persian Gulf. Capillary gas chromatograms of distribution of individual n-alkanes (d) and Hopanes (e) in the reef surface sediments of the Hormoz (a) and Kharg (b) from the Persian Gulf.

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R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

17

Fig. 7. (continued).

Fig. 8. Calculated overall CPI (a) and overall CPI versus high CPI (CPIa) (b) plots in the reef surface sediments of the Persian Gulf.

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R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

land plants, phytoplankton, animals, bacteria, and microalgae could be biological sources of n-alkanes (Wang and Fingas, 2003). Low values of CPI close to 1 in most reef sediment samples demonstrated the impact of petroleum products in these stations and several studies have confirmed oil CPI values to be around 1.0 (Kalaitzoglou et al., 2004; Wang and Fingas, 2003; Zheng et al., 2000). With regard to this fact, this is an indication that the nalkane loadings were affected by petrogenic emissions and to some extent by biomass burning in most parts of the study area (Rogge et al., 1993a; Rogge et al., 1993b; Schauer et al., 1996). Although the mean CPI was lower than those reported for several studies all around the world (Hu et al., 2009; Maciel et al., 2016; Sojinu et al., 2012; Wang and Kawamura, 2005; Zheng et al., 2000), it was consistent with a number of studies (Li et al., 2015c; Zhao et al., 2016), which have reported the domination of petrogenic origins. CPIa varied from 0.56 to 2.36 over the course of the study (Table 2), and the fact that all of the mean values were greater than unity indicates that anthropogenic sources affected the n-alkanes throughout the study area. CPIb ranged from 1.27 to 1.44, implying analogous contributions from petrogenic sources throughout the study area, and these were most likely associated with the oil transportation and also oil spillages. CPIb was more variable compared with CPIa: CPIb exhibited a range of 0.98e4.68 (Table 2), and this variability indicates that the influence of biogenic emissions changed remarkably from site to site. Ranges of CPIa and CPIb, demonstrate a strong odd-to-even carbon preference in the long chain n-alkanes. In general, the low CPI (CPIa), Overall CPI15-35 and High CPI (CPIb) reflected the multiple sources for n-alkanes (petrogenic and natural) (Fig. 8b). UCM22 is a mixture of structurally complex isomers of homologous branched/cyclic hydrocarbons that cannot be resolved by capillary columns. Nevertheless, it is an effective indicator to assess petroleum contamination from anthropogenic sources (Gogou et al., 2000; Ou et al., 2004; Volkman et al., 1992), specially pertinent to unburned petroleum emissions from vehicular traffic (Simoneit, 1989). It could be also indication of weathered petroleum (Brassell and Eglinton, 1980), chronically degraded intricate mixture of hydrocarbons (Frysinger et al., 2003; Gough and Rowland, 1990; Mille et al., 2007; Tolosa et al., 2004) and GC traces of lubricating oils and in volatile organics of diesel. The presence of UCMs in sediments is an indicator of chronic/degraded petroleum contamination, although bacteria-derived UCMs cannot be ignored (Bouloubassi et al., 2001). The hump of UCM was evident in mostly chromatograms except for Hormoz, Qeshm and Hengam reefs. UCM concentrations varied from 0 to 4651.67 mg.g
1dw with overall mean of 1676.46 which the maximum values were spanned for Kharg followed by Siri and Lavan Islands. UCM also occurred as short-chain n-alkanes with a mean response factor of n-C16 n-alkanes (Fig. 9d). In addition, linear regression revealed that the significantly positively correlation (r ¼ 0.85) was among concentrations of n-C16 n-alkane and UCMs (Fig. 9g). Fig. 7 illustrates the TIC23 of the aliphatic fraction of the extracts from the reef sediments in some sampling sites in the Gulf. In most of the samples a bimodal and three-modal (at Kharg Island) UCM of branched and cyclic hydrocarbons with maximum at n-C16 (Fig. 7a,b,c) were observed and UCM were skewed toward the heavier molecular weight compounds in reef surface sediment samples. Presence of hump in the area of the gas chromatogram can be associated with petroleum hydrocarbons, chronic pollution, because with weathering the oil, UCM will be moved to heavier

22 23

Unresolved Complex Mixture. Total Ion Chromatogram.

carbon compounds (HMWs) (Jacquot et al., 1999; Lima et al., 2012). These are characteristics of contamination by light and heavy petroleum fractions respectively (Kennicutt et al., 1994; Mazurek and Simoneit, 1984; Simoneit, 1985). In this study, all affected areas with petroleum hydrocarbons samples demonstrated significant UCMs, including short-chain n-alkanes by GCeMS, since the UCMs of non-oil seepage contamination sediments usually include longchain n-alkanes. The absence of UCM in TIC of reef sediments in Hormoz, Qeshm and Hengam reefs might be an indicative of lacking petroleum hydrocarbons contamination in these sites. U/R ratio, generally defined as the ratio of unresolved to resolved n-alkanes (UCM/Rn-alkanes), is a useful tool to identify the presence of degraded petroleum hydrocarbons. The low values for UCM/Rn-alkane (<10) ratios indicate a pollution diluted by natural input (Silva et al., 2012). Significant contamination by petroleum products exists when the value is > 2.0(Simoneit and Mazurek, 1982) (Gogou et al., 2000; Ou et al., 2004). The mean UCM/R ratio ranged from 0 to 5.34, with an overall average of 2.38, suggesting high petroleum contamination in that area. The U/R ratio values showing an important biodegradation of petroleum related input. Similar distribution of UCMs with this study is also reported in another investigation all around the world (Abrams, 2005; Harji et al., 2008; Hu et al., 2009; Li et al., 2015b; Maciel et al., 2016; Zhao et al., 2014). The mean ACL24 values determined in the reef sediments varied from 27.55 to 28.95 with an overall mean of 28.12 (Table 2, Fig. 9e). Numerous studies have reported the variation of ACL in sediments: Bakhtiari et al. (2011) reported an average of 29.68 ± 0.15 for ACL values of Chinilake sediment core samples; Wang et al. (2013) reported ACL values 28.2 to 29.6 (28.38 ± 0.11) in sediments from subtropical lake in China; recently, Gireeshkumar et al. (2015), surveyed n-alkane distribution in Cochin estuary, and reported ACL in the range 21e28; Resmi et al. (2016) studied bulk characterization and hydrocarbon biomarkers in sediments from mangrove ecosystems of northern Kerala, India, and ACL in the range 25.75e29.10 was reported. Similarly, ACL did not show high oscillation in our study, but was higher 28 in most stations suggesting the presence of terrestrial derived OM particularly in Hormoz, Qeshm and Hengam Islands (Fig. 9e). Some studies have reported that the relative constancy of ACL values in an uncontaminated area could not be possible, unless natural sources remains unchanged and varies with plant species. Plausible cause for spatial distribution of ACL might be attributed to shifts of plant species in each ecosystem (Jeng, 2006; Resmi et al., 2016). Apart from the mentioned cause, litter fall, allochthonous marine material, autochthonous production by benthic or epiphytic micro- or macroalgae, and production by phytoplankton and the geographical distribution of fluvial and eolian inputs and source regions (Alongi et al., 2005; Bakhtiari et al., 2011; Bouillon et al., 2004; Poynter and Eglinton, 1990) might as well seem inevitable. Linear regression analysis between ACL and CPI values of sediments were tested and presented in Fig. 9f. The results did not show strong correlation among the variation trend of ACL and CPI. As strong correlation among them suggesting n-alkanes data derived from higher plants (Bakhtiari et al., 2011), nonlinear variation could be interpreted as mixed ratios (Jeng, 2006; Resmi et al., 2016). It could be inferred that our study area has been more affected by petrogenic source, however the inputs of OM from higher plants of some islands could be considered. To clarify more the origins of hydrocarbons, the sum of n-alkanes of phytoplanktonic (n-C15, n-C17, n-C19 and n-C21), terrestrial (n-C23, n-C25, n-C27, n-C29, n-C31, n-C33), and petroleum

24

Average Chain Length.

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Fig. 9. Indices calculated from n-alkane biomarkers in the reef surface sediments of the Persian gulf.

origin (n-C12, n-C14, n-C16, n-C18, n-C20) were plotted to distinguish the dominant origins, and the order of their abundance (Fig. 9a and b). The dominance of petrogenic n-alkanes were evident in the reef sediments of the most sampling sites, whilst in Hormoz, Hengam and Qeshm phytoplankton and terrestrial n-alkanes were dominant (Fig. 6 and Fig. 9a and b). In the current study, to distinguish pollution sources in addition to represented indices, the LMW/HMW (Commendatore et al., 2000; Doskey, 2001; Harji et al., 2008; Hu et al., 2009; Pearson and Eglinton, 2000; Prahl et al., 1994), Pri/Phy (Bianchi and Canuel, 2011; Gireeshkumar et al., 2015; Killops and Killops, 2005; Resmi et al., 2016; UNEp and IEA, 1995), n-C29/n-C17 and nau et al., 1997; Maciel et al., 2016; Yusoff et al., C31/n-C19 (Le Dre 2012), OEP (Meyers and Ishiwatari, 1993; Wang et al., 2013), TAR (Bourbonniere and Meyers, 1996; De Luca et al., 2004; Mille et al., P 2007; Witt, 1995) and finally 25n-alkanes/n-C16 (Gao et al., 2007; Gogou et al., 2000; Ou et al., 2004) indices were calculated and their values confirm the stated results (Fig. 14) (For more information see Table 2 and Fig.14 in supplementary section). PCA also performed and demonstrated significantly a high positive loading of the mixture variables of short-chain or lower molecular weight n-alkanes and UCM, ascribable to petrogenic and slightly terrestrial sources. All together all the result obtained from analysis confirmed the high petrogenic footprint in all study area (Grimalt

s, 1987; Harji et al., 2008; Kang et al., 1999) (Fig. 13). and Albaige 4.4.

P 30PAHs in reef surface sediment

The same as n-alkanes the highest PAHs concentrations at Kharg, Lavan and Siri coral reefs can be attributed to the heavy petroleum load and robust transportation of crude oil and importantly oil spillage in particular at Kharg reefs. As well as Low PAH concentrations at site Hormoz, Qeshm and Hengam coral. The P observed 30 PAHs concentrations in sediments of current study were 2e3 orders of magnitude higher than those in the reef sediments of Timor Sea, Australia (1.8e11.2 ng.g
1dw (Burns and Jones, 2016); Luan River Estuary, China (5.1 to 545.12 ng.g
1dw (Zhang et al., 2016)); Kharg Island, SW, Iran (29.50e253.30 ng.g
1dw (Akhbarizadeh et al., 2016)); Northern Gulf of Mexico (68e158 ng.g
1dw (Adhikari et al., 2016)); Yangtze River Estuary, China (27.2e621.6 (158.2 ng.g
1dw) (Wang et al., 2016)); South China Sea (24e647 ng.g
1dw (Kaiser et al., 2015)); Barataria Bay, Gulf of Mexico (233e390835 ng.g
1dw (Kırman et al., 2016)); Poland (239e1310 ng.g
1dw (Kusmierz et al., 2016)); Pearl River Estuary, China (126.08e3828.58 (563.52 ng.g
1dw) (Zhang et al., 2015)); Pearl River Estuary, Daya Bay and northern South China Sea (248e2089 ng.g
1dw (Yuan et al., 2015)); Imam Khomeini Port, the Persian Gulf, Iran (2885.80e5482.23 ng.g
1dw (Abdollahi et al.,

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Fig. 10. PAH relative abundance of the reef sediments based on sampling stations grouped by ring numbers.

2013)). By comparing these studies, it seems that the contamination of 30 PAHs in this investigation was fairly at a moderate to high P level on a global scale. Analogous to the spatial distribution of 30 P PAHs in reef sediments, the mean maximum values of 16 PAHs were found in Kharg and Lavan Island, respectively, and followed by Siri and Lark reefs (Table 3). Nonetheless, for the other sampling P sites, the concentrations of 16 PAHs were as low as those in the Kish, Hengam, Qeshm and Hormoz Islands, except for Shidvar and P Hendurabi. The plausible cause was that the 16 PAHs in the western part of the study area which was emanated from largely industrial infrastructures especially petroleum fields are mainly less in these areas, and it might be probably said that the residence time of PAHs in sampling sites with lower concentrations is less than those with higher concentrations. Hereupon, it could be claimed that less depositional PAHs were accumulated in the sediments. The Alkyl homologues were more abundant than the parent PAHs of the total PAHs in Kharg and Lavan sites relative to P other sites (p < 0.05). Compared to 30PAHs in the sampling sites, P P P analogous distribution of Alkyl, Parent, Carcinogenic and P 16 PAHs were observed. However, it was figured out that the P P P P P ratios of Alkyl, Parent, Carcinogenic and 16 PAHs to 30 PAHs (Table 1) were relatively higher (<0.05) in Kharg, Lavan, Siri and Lark relative to those in other sampling sites particularly Hengam, Hormoz, and Qeshm. As mentioned above for n-alkanes, MDS model revealed four groups which were distinguished by the intensity of anthropogenic activities. As shown in Fig. 3b, most sampling sites, especially Hormoz, Qeshm and Hengam (the southern east part of the Persian Gulf) had no prominent local input or less influenced by polluted inputs and consequently were less contaminated by PAHs by comparing with Kharg, Lavan, Siri and to some extent lark coral reefs. 4.4.1. Compositional pattern of PAHs The compositional profile of PAHs by ring number is depicted in Fig. 10a. The reef sediment PAH profiles were significantly dominated by 2e3 ringed LMW-PAHs (62.22± 18% of the total PAHs) followed by MMW-PAHs (4 rings, 16.52± 17%) and HMW-PAHs (>4 rings, 21.26± 3%) (p < 0.05). The Percentage contribution of LMW PAHs with 2e3 rings in the reef sediments of northern Persian Gulf, varied from 53.18 to 81.05% (2 rings from 17.02 to 26.85% and 3 rings from 36.15 to 60.82) Fig. 10b and were the highest at sites Kharg, Lavan, Siri and Lark, while the percentage of MMW-PAHs ranged from 10.88 to 21.69% (with overall mean percentage of

16.52). The percentages of HMW PAHs with 5e6 rings (5 rings from 6.68 to 19.57% and 6 rings from 5.20 to 6.54%), and the lowest and highest values were in Kharg and Hormoz sites, respectively (Fig. 10a). There was no substantial shift for the MMW PAHs (4rings) in reef sediments in all of the sites, but the LMW and HMWPAHs revealed a contrary tendency. The 5e6 rings PAHs demonstrated explicit deceasing tendency from the east to the west part of the Persian Gulf, and the highest concentration was around the Hendurabi (followed by Kish, Hengam and Hormoz) (Fig. 10a), while the 2e3 rings exhibited considerably increasing tendency from the east to the west part of the whole study area which the maximum concentrations were in Kharg Island. Similar spatial distribution of 5e6 rings PAHs was observed for MMW-PAHs. The observed pattern may be elucidated in terms of physicochemical properties of PAHs and adjacency to the source. On the one hand, noticeable predominance of LMW PAHs is comprehensible for some specific Islands such as Siri, Lavan and Kharg since they are subject to chiefly petrochemical and petroleum transport by huge ships to remote areas which is considered as a core of industrial activities. On the other hand, HMW PAHs associated with islands with very slight anthropogenic activities affected by adjacent Islands. Not only were overall PAH concentrations higher in Kharg, Lavan and Siri reefs in the Gulf (p < 0.05), the distributions of individual PAH concentrations in the whole study area were discretely various from other sampling sites. The lowest and highest concentrations of 2ringed hydrocarbons were Naphthalene (Naph) and 2,3,5TMNaphtalene (TM-Naph), whereas Phenanthrene (Phe) and Anthacene (Ant) were for 3- ringed PAHs, respectively. Benzo(a)anthracene (BaA) had the minimum concentration of 4-ringed hydrocarbons, whilst Pyrene (Pyr) (7e10% of the total PAHs) exhibited the maximum concentration. The most enriched 5 and 6rings PAH were perylene (9%e12% of the total PAHs) and Benzo[ghi] perylene (BghiP) (6%e10% of the total PAHs)respectively, while Benzo(e) pyrene (BeP) and Indeno [1,2,3-cd]pyrene (InP) had the lowest concentrations, respectively. The congeners of PAHs were found in 80e100% of the samples. In addition, concentrations of unsubstituted and substituted naphthalenes were considerably augmented in the Kharg, Lavan and Siri Islands compared to the other sampling sites (p < 0.05) (Table 3). This increasing trend relatively observed was common for approximately most sites. In parallel, NPMDS analysis also indicated that among PAHs congeners, Phe and Ant were discriminated from other congeners followed by Naph, Flu and substituted homologues of Phe and Naph (Fig. 11c),

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Fig. 11. Diagnostic ratios of PAH parents and isomers for source appointment in the reef surface sediment of the Persian Gulf.

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R.J. Ali et al. / Environmental Pollution xxx (2017) 1e29

inferring that they are the most influential congeners in the grouping based on sampling sites. The results also exhibited Phe accounted for over 20% of the concentrations of S30PAHs, whereas Ant accounted for less than 2.0%. The subsequence of mean value of thirty kinds of PAHs congeners was Phenanthrene>Naphtalene>3Methylphenanthrene>2-Methylphenanthrene>9-Methylohenanthracene>1-Methylphenanthrene>3,6DM-Phenanthrene>Benzo(a) fluorine>2M-Naphtalene>1M-Naphtalene>Pyrene>Fluoranthene>Perylene>Benzo(a)pyrene>1M-Pyrene>Chrysene>Acenaphthylene>Acenaphthene>2,3,5TM-Naphtalene>Fluorene>Dibenzothiophen>Benzo(a)pyrene>Benzo[ghi]perylene>Benzo [ghi]perylene>ndeno[1,2,3-cd]pyrene>Benzo(b)fluoranthene>Benzo[k]fluoranthene>Benzo(e) pyrene>Benzo (a) anthracene>Anthacene. 4.4.2. Source identification 4.4.2.1. Individual PAH ratios. There is no doubt that individual compound ratios are alternative indicators used to identify the sources of PAHs in the environment which is considered as a general rule (Yunker et al., 2002b) and could provide precise and reliable evaluation of the emission sources of PAHs (Kendall et al., 2001). Molecular indices based on the ratios of selected PAHs have been extensively used to differentiate PAHs from pyrogenic and petrogenic origins (Aichner et al., 2007; Chen et al., 2005; Peng et al., 2011). In the current study, to distinguish petrogenic sources P from other ones, the MP/P,LMW/HMW, Phe/Ant, BaA/Chr and P 2,5,6 rings PAHs/ 30 PAHs molecular indices were estimated and their values against the Flt/Pyr index values were plotted (Fig. 11). It P has been reported that Methyl phenanthrenes to phenanthrene P ( MP/P) ratio is the most leading index to discriminate the petrogenic origin from pyrogenic one and the values < 1 indicates the pyrogenic source, while values 2e6 is an indicative of petrogenic (Prahl and Carpenter, 1983; Zakaria et al., 2002). Mean value of this ratio ranged from 4.14 to 5.79 with an overall mean value of 4.68 and the highest values were spanned in Kharg reefs (Table 3, P Fig. 11a). MP/P were found to be greater than two in 94% of the sediment samples, distinguishing the PAHs of petroleum origin (Prahl and Carpenter, 1983; Sporstol et al., 1983; Zakaria et al., 2002). In order to differentiate PAHs in our samples from petroleum and combustion sources, we also applied four isomeric ratios Fig. 11f,g,h; [Ant/(Ant þ Pyr)], [Flu/(Flu þ Pyr)], [BaA/(BaA þ Chr)] and [InP/(InP þ BghiP)], the ratios less than 0.1, 0.4, 0.2, and 0.2 respectively, it illustrates strong pyrogenic origin, while values higher than these commonly demonstrate biomass and coal combustion sources (Budzinski et al., 1997; Yunker et al., 2002a). Flu/ (Flu þ Pyr) ratio between 0.4 and 0.5 represented petroleum combustion and Flu/(Flu þ Pyr) > 0.5 suggests the source of biomass and coal combustion (Dvorsk a et al., 2011; Yunker et al., 2002b; Zhang et al., 2004). BaA/(BaA þ Chr) ratio between 0.2 and 0.35 and IP/(IP þ BgP) ratio between 0.2 and 0.5 describes petroleum combustion, including liquid fossil fuels, vehicle, and crude oil combustion. It is noteworthy to point out here that these source recognition ratios come with different caveats and their interpretation can be sophisticated (Yunker et al., 2002a). Calculated source recognition ratios exhibited mixed consequences and were unable to precisely specify the origin of PAHs in the Gulf's reef sediments. The [An/(An þ Phe)], [BaA/(BaA þ Chr)] and [InP/ (InP þ BghiP)] ratios were found to be petroleum origin of PAHs in 90% of the sediment samples, characterizing the PAHs of petroleum origin, whereas the [Flu/(Flu þ Pyr)] ratio exhibited mixed and combustion origin (Table 3, Fig. 11f,g,h). Furthermore, the ratios of Alkylated PAHs to parent PAHs without perylene (A-PAH/P-PAHs) was 3.89implicating the dominance of Alkyl homologous over unsubstituted PAHs (Prahl and Carpenter, 1983). With regard to the fact that the exuberance of LMW-PAHs and Alkyl homologues

relative to parental compounds reverberates a leading allotments of unburned fossil sources (Bence et al., 2007; Sporstol et al., 1983), the sources discernment indices, totally, portends a petrogenic origin for PAHs in the most reef sediments in the whole study area. The obtained consequences of these ratios demonstrated that the petroleum and combustion of biomass, and coal are the major sources of PAHs in the Gulf. From the above results, it may be subsumed that the Gulf comes under the region of biomass and coal and petroleum combustion. This may be reiterated as in the Gulf, various anthropogenic infrastructure importantly petroleum industries are situated which utilize oil and natural gas and also to some extent coal and biomass for combustional purposes. In this study many indices was calculated, such asthe LMW/ HMW(Baumard et al., 1998; Budzinski et al., 1997; Sicre et al., 1987; Soclo, 1986; Yunker et al., 2002b), Phe/Ant (Parlanti, 1990; Soclo P et al., 2000), BaA/Chr and 2,5,6 rings PAHs/ 30PAHs(Parlanti, 1990; Soclo et al., 2000; Yan et al., 2009) to strengthen the hypothesis of petrogentc source comparing to other ones (Table 3,Fig. 11). Alike to n-alkane, PCA also performed for PAHs. The obtained result confirmed petrogenic source of PAHs which were intelligibly sequestered from pyrogenic one in terms of PAHs composition along PC1 and PC2(Fig.13 in supplementary section) performed and demonstrated significantly a high positive loading of the mixture variables of lower molecular weight PAHs, ascribable to petrogenic sources. All together all the result obtained from analysis confirmed the high petrogenic footprint in all study area. 4.5.

P 9 Hopanes in reef surface sediment

It has been reported that there are four plausible Hopane stereoisomers including 17b(H), 21b(H) (living organism), 17a(H), 21a(H) (not present in fossil fuels), 17b(H), 21a(H) (pyrolysates-also called moretanes), 17a(H), 21b(H) (natural fossil fuels) (Resmi et al., 2016; Seifert, 1978). Demonstrated that Hopanes from natural fossil fuels (17a(H), 21b(H)) and pyrolysates (17b(H), 21a(H)) are the most stabilized Hopanes in the nature. Fig. 7e demonstrates the Fragmentogrammes of Hopanes (m/z ¼ 191) from the reef surface sediments at Kharg site in our study area. In the current study, Hopanes, as it has indicated in Fig. 9e are composed of a series of 17a(H), 21b (H)-compounds (C27 to C34). The C30 homologues (17a(H), 21b(H)-hopane (C30ab); 17b(H), 21a(H)-hopane(C30ba)) followed by C29 homologues (17a(H), 21b(H)-30-norhopane (C29ab)); 17b(H), 21a(H)-30-norhopane (C29ba)) were the most abundant Hopanes in mainly sediment samples (particularly those collected from industrial activities), whilst the lowest one was Gammacerane(G) and this trend was observed in the whole study area. Pairs of the C22 diastereoisomers (22R, 22S), extended Hopanes (>C30) were also observed with predominance of 22S isomers Fig. 7e. It has been reported that Hopanes in the range C31eC35 indicated doublets (22S and 22R) in which the biologically generated precursors carry 22R configuration that undergo epimerisation favouring an inconsiderable preference for the 22S epimer (Aboul-Kassim and Simoneit, 1996; Resmi et al., 2016). Some studies have also exhibited that Hopane could be found in the sediments from fossil fuels of nearby road transport systems (Resmi et al., 2016; Yunker et al., 1994). A number of researchers has investigated that17b(H), 21b(H)-hop-22 (29)-ene (Diploptene) could be pertaining to cyanobacteria, methylotrophic bacteria using carbon sources and specified species of ferns (Gireeshkumar et al., 2015; Ourisson et al., 1987; Resmi et al., 2016; Rohmer et al., 1984; Yunker et al., 1994). Other investigation shave demonstrated that homohopanes (C31eC35) may be pertinent to the bacterio hopane polyols, while lower hopanepseudohomologsmaybe pertaining to C30 precursors such as Diploptene and Diplopterol (Peters and Moldowan, 1993; Resmi et al., 2016). Our obtained results also

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revealed that the mean value of Ts (18a (H)-22, 29, 30trisnorhopane) to Tm (17a (H)- 22, 29, 30-trisnorhopane) ratios oscillated predominantly mostly in sediment samples, from 0.30 to 0.89 (Table 3). This could be inferred by the presence of mature petroleum in the surface sediments (Hu et al., 2009). The relative content of Ts was also rather higher in more matured and stable homologues. A number of studies have suggested that Ts is a useful criterion which has been applied to specify the source and the probable degree of maturation of crude oil (Hostettler et al., 1999; Hu et al., 2009; Louati et al., 2001; Shirneshan et al., 2016a). The ratio of 22S/(22S þ 22R) has been also proven to be an effective evidence of fossil fuel input (Hu et al., 2009). Our findings, as observed for Ts/Tm, have also revealed broad fluctuations for 22S/ (22S þ 22R), varied from 0.43 to 0.74 indicating full maturity of oil (Mackenzie, 1984). Our results are consistent with other investigations all over the world (Bigot et al., 1989; Hu et al., 2009; Pang et al., 2003). To sum up, higher abundance of Hopanes observed in some sampling sites especially Kharg, Lavan, Siri and Lark Islands could be probably interpreted by The composition patterns of Hopanes and PAHs combining with the ubiquitous presence of UCM which demonstrates that petroleum is the most probable origin of contamination and as well chiefly from the oil extraction mainly oil spillages from transportation with huge oil tankers, sewage discharges, offshore oilfields as well slightly generating bacteria with probably anoxic settings (Dahl et al., 1993; Resmi et al., 2016) in the Persian Gulf.

4.6. Relationships between hydrocarbon biomarkers, biogenic elements and particle size in reef sediments To acquire the interaction among biomarkers and detected bulk physical data in the whole study, PCA was conducted to diminish the intricate interactions between the biomarkers and determined biogenic elements along with particle size data and prepare intuitions into commonalities and discrepancies in the total study area and also between sampling stations. The obtained consequences from data were plotted in a PCA scatter diagram to discern potential geochemical relevancies between n-alkanes, PAHs, Hopanes, particle size, TC, TOC, BC, TN, TON and TIN in reef sediments of the Gulf (Fig. 12a). PC1 elucidated 87% of the total variP 25n-alkanes, ance. The resultant data also revealed that P P 30PAHs and 9 Hopanes accounted for 69% of the total variance from PC1 (25.57%, 32.19%, and 11.25 respectively), whilst other bulk physical data explained 18% of the total variance. In general, three segregated loadings from PCA analysis was observed:total n-

23

alkanes, total PAHs, total Hopanes along with percentage of TC, TOC, TN, clay, and silt are loaded simultaneously towards the top right of the plot, while BC, TIN and TS are closely grouped to the top left of plot. Sand also was discriminated from other biogenic elements and was occurred to the top left of plot, far away of BC, TIN and TS(Fig. 12a). To distinguish the individual stations based on concentration of n-alkanes, PAHs, Hopanes, TC, TOC, BC, TN, TON, TIN and amounts of clay, silt sand, HCA was also conducted. The results indicated four groups: group1includes Siri and Lavan with approximately high concentration of n-alkanes, PAHs, Hopanes along with biogenic elements, plus higher values of clay, silt. Group 2 contains only Kharg Island along with high amounts of biogenic elements and petroleum hydrocarbons in particular PAHs and undergoing more anthropogenic effects. Group 3 belonged to only Shidvar Island with medium to high concentration of detected petroleum compounds and also dominance of silt. Lark and Qeshm plus Hengam and Hendurabi were classified in group 4 and 5, respectively, and group 6 was for Kish Island with low to some extent medium concentrations of biomarkers and biogenic elements and as well as lower influence of industrial activities. Variations in concentrations of biomarkers could be interpreted by numerous factors including the affinity of the sampling sites to contaminated sources, sediment properties, grain size and as well as biogenic elements such as TOC (Kucklick et al., 1997). It seems that considerable differences, which were observed for various concentration of petroleum hydrocarbons among different sampling sites, could be due to the differences in particle size of their sediments. Although numerous investigations have reported no correlation (P > 0.05) between the compositions of particle size and petroleum pollutants (Kucklick et al., 1997; Ou et al., 2007), some researchers, for instance (Zhang et al., 2009)reported that the plausibility of finding petroleum hydrocarbons in finer portion of sediments are more than bigger sizes and their concentrations could be decreased steadily with the increasing of size. Our study revealed that despite significantly robust positive correlation P among clay portion of reef sediments with 25 n-alkanes (Fig. 5a P P and 12a), 30PAHs (Figs. 5d and 12a) and 9 Hopanes (Figs. 5e and 12a), all detected biomarkers were not significantly associated with sand sediment type (p > 0.05). Total PAHs, n-alkanes and Hopanes indicated a negative correlation with BC(Fig. 12a), while they were significantly correlated to TOC and TON(Fig. 12a). Similar to studies, which have widely demonstrated the relationship between TOC and PAHs concentrations (Guo et al., 2011; Kang et al., 2009; Knezovich et al., 1987; Neff, 1979; Wang et al., 2014), total PAHs in our study are all strongly correlated with TOC, and this

P P P Fig. 12. Ordination diagram from PCA based on the concentration of 25n-alkanes, 30PAHs, 9 Hopanes plus biogenic element (TON, TIN,TOC,BC,TS) and grain size (clay, silt and P P P sand) (a) along with categorization of sampling sites based on HCA(b) according to concentrations of 25n-alkanes, 30 PAHs, 9 Hopanes in the reef surface sediments in the Persian Gulf.

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trend was considerably observed for TON (p < 0.05) (Fig. 12a). In general, although marine environment is a complex ecosystem, and could be greatly influenced by anthropogenic activities. There were many potential petroleum pollution sources in marine ecosystem such as the Persian Gulf, obvious correlation between biomarkers and some physicochemical properties of sediments were observed in this study. In addition, finer fractions contained more OC and also nitrogen could be leading factors to control the enrichment of petroleum hydrocarbon in reef surface sediments. 5. Conclusion Reef surface sediment samples from a matrix of ten coral reef ecosystems in the Persian Gulf, Iran, were analyzed for TOC, TN, elemental ratios, hydrocarbon biomarkers (n-alkanes, PAHs and Hopanes) and UCM to evaluate the sources and early diagenesis of sedimentary organic matter, and as well as PCA along with NPMS were conducted for source apportionment of OM and to specify further the spatial variability in the aliphatic, aromatic and Hopane congeners. Based on HCA and NPMS, the sampling sites pertaining to their position were grouped. The elemental ratios indicated substantial contribution of planktonic OM apart from terrestrial derived OM. The sources of OM demonstrated variability in relation to the geographical setting of coral reef systems. The distribution of TOC correlated well with reef sediment grain size with the finest sediments having the highest concentration, reflected the effect of hydrodynamics on the accumulation of OM. The TOC/TN ratios indicated mixed marine and to some extent terrestrial origins of OM. Total n-alkane, PAH and Hopanes concentrations in sediments oscillated from Hormoz, Qeshm and Hengam with the lowest concentration to Lavan and Kharg with highest values reflected a continually upward trends in concentration from the east to the west part of the Persian Gulf. The presence of UCM, biomarkers and PCA consequences exhibited the presence of petroleum contamination in most sampling sites, mainly from anthropogenic activities such as offshore oil exploration and extraction along with shipping. Acknowledgements This investigation was supported by the Academy of Environment Science, Tarbiyat Modares University of Tehran, Iran, Thanks are also extended to Iranian Oil Terminal Company for facilitating the field work. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.envpol.2017.01.080. References Abdollahi, S., Raoufi, Z., Faghiri, I., Savari, A., Nikpour, Y., Mansouri, A., 2013. Contamination levels and spatial distributions of heavy metals and PAHs in surface sediment of Imam Khomeini Port, Persian Gulf, Iran. Mar. Pollut. Bull. 71, 336e345. Aboul-Kassim, T.A., Simoneit, B.R., 1996. Lipid geochemistry of surficial sediments from the coastal environment of Egypt I. Aliphatic hydrocarbonsdcharacterization and sources. Mar. Chem. 54, 135e158. Aboul-Kassim, T., Simoneit, B., 1997. Lipid geochemistry of surficial sediments from the coastal environment of Egypt: I. Aliphatic hydrocarbons-characterization and sources. Oceanogr. Lit. Rev. 6, 568. Abrams, M.A., 2005. Significance of hydrocarbon seepage relative to petroleum generation and entrapment. Mar. Petroleum Geol. 22, 457e477. Achten, C., Hofmann, T., 2009. Native polycyclic aromatic hydrocarbons (PAH) in coalsea hardly recognized source of environmental contamination. Sci. Total Environ. 407, 2461e2473. Adhikari, P.L., Maiti, K., Overton, E.B., 2015. Vertical fluxes of polycyclic aromatic hydrocarbons in the northern Gulf of Mexico. Mar. Chem. 168, 60e68. Adhikari, P.L., Maiti, K., Overton, E.B., Rosenheim, B.E., Marx, B.D., 2016.

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Please cite this article in press as: Ali, R.J., et al., Spatial distribution and composition of aliphatic hydrocarbons, polycyclic aromatic hydrocarbons and hopanes in superficial sediments of the coral reefs of the Persian Gulf, Iran, Environmental Pollution (2017), http:// dx.doi.org/10.1016/j.envpol.2017.01.080