Identification of Tsunami deposits has long been a controversial issue among geologists. Although there are many identification criteria based on the sedimentary characteristics of unequivocal Tsunami deposits, the concept still remains ambiguous. Apart from relying on some conventional geological, sedimentological, and geoscientific records, geologists need some alternative “proxies” to identify the existence of Tsunami backwash in core sediments. Polycyclic aromatic hydrocarbons (PAHs) are a class of very stable organic molecules, which can usually be presented as complex mixtures of several hundred congeners; one can assume that the “Tsunami backwash deposits” possess different fingerprints of PAHs apart from those of “typical marine sediments.” In this study, three-dimensional plots of PAH binary ratios successfully identify the Tsunami backwash deposits in comparison with those of global marine sediments. The applications of binary ratios of PAHs coupled with HCA are the basis for developing site-specific Tsunami deposit identification criteria that can be applied in paleotsunami deposits investigations.
Polycyclic aromatic hydrocarbons (PAHs), usually acknowledged as a group of persistent organic pollutants (POPs), have been comprehensively investigated in the past decades because these congeners have a profound association with a wide range of adverse health effects and other respiratory diseases [
PAHs and other semivolatile organic compounds (SVOCs) have also been applied as chemical tracers to discriminate marine deposits from terrigenous components [
Recently, Tipmanee et al. [
In contrast to multivariate techniques such as PCA, visual comparison of PAH fingerprints and diagnostic binary ratios are preferable since they require no environmental insights of interpreting correlation coefficients of certain variables in each principal component and thus overcome the limitations of PCA. Overall, the main purposes of this study are to comprehensively investigate the fingerprints and diagnostic binary ratios of PAH aerosols from various emission sources in Songkhla province with marine deposits in Tsunami 2004 affected coastal area of Thailand. These findings will open a new window in applying PAHs as a “chemical proxy” to identify Tsunami backwash deposits and thus enhance the knowledge of Tsunami impacts on surficial sediment distribution in Khao Lak coastal area of the Andaman Sea.
The research area is governed by the northeast monsoon from mid-October until March and the southwest monsoon from May to September and the intermonsoon phases. This study was carried out offshore along the west coast of Phang Nga province, Thailand, which was heavily affected by the 2004 Tsunami [
The first observatory station, Site-1, was placed at Novotel Centara Hat-Yai Hotel (7°00′20.65′′N 100°28′15.65′′E) at 30 m above the building basement and influenced mainly by transported pollution from traffic jams in the city center. Site-3 was positioned at Lee Gardens Grand Plaza Hotel (7°00′21.39′′N 100°28′15.94′′E) at 125 m above the ground level. Site-2, which was situated at Lee Gardens Grand Plaza Hotel at 60 m above the ground level, appears to be affected by a mixture of air masses including vehicular emissions, long-range transportation of aged particles and maritime aerosols. Intensive monitoring campaigns were conducted at all observatory stations simultaneously from December 17 to 20, 2007, in the relatively cold period. PM10 samples were collected every three hours continuously from 21:00 h December 17 to 21:00 h December 20 by using Graseby-Andersen.
Population of Songkhla Province is about 1.32 million occupying an area of approximately 7,394 km2. Songkhla is located 950 km south of Bangkok, situated on the eastern side of the Malayan Peninsula, bordering on Nakhon Sri Thammarat and Phatthalung to the north; Yala, Pattani, and States of Kedah (Sai Buri) and Perlis of Malaysia to the south; the Gulf of Thailand to the east; and Satun and Phatthalung to the west (Figure S4). Hat-Yai, a district of Songkhla, is better known than the provincial capital itself as an economic and tourism zone of Songkhla and thus many industrial factories and stores are located in this area. Sampling site descriptions are given in detail as follows.
In this study, Graseby-Anderson high volume air sampler (PM10-TE6001) was used to collect PM10 samples every 3 h consecutively with the flow rate of 1.132 m3 min−1. To avoid any contaminations, tweezers and aluminum foils were cleaned by dichloromethane (DCM) prior to use. All quartz fiber filters (47 mm Whatman quartz microfibre filters (QM/A)) were weighed gravimetrically on a microbalance Mettler Toledo AB204-S (Columbus, Ohio, USA) before and after sampling to quantify PM10 mass load. It is also worth mentioning that all filters were precleaned by DCM using Soxhlet extraction for 8 h prior to use to avoid any potential contamination. During the intensive monitoring campaign, all filters were kept in refrigerator at 4°C to minimize the loss of PAHs during sample preservation. Detailed description of sample collection has been published in Pongpiachan [
During the research cruises in November-December 2007 with RV CHAKRATONG TONGYAI and November-December 2008 with RV BOONLERT PASOOK, approximately 1500 nautical miles of hydroacoustic profiles (side scan sonar, multibeam echo sounder, and shallow reflection seismic with a boomer system) were recorded offshore Pakarang Cape. Based on these data sediment distribution maps were compiled. The grab samples discussed in this study were taken with a Van-Veen-type grab sampler, which was used to collect 70 surface sediment samples during 1–8 December 2007. Sediment samples were wrapped in clean aluminum foil, placed in a glass bottle, and kept frozen at −20°C. They were freeze-dried prior to being grounded and sieved to homogenize the samples and then kept in the refrigerator at −4°C until analysis.
All organic solvents (i.e., DCM and Hexane) are of HPLC grade and are purchased from Fisher Scientific. A cocktail of 15 PAHs as determined by Norwegian Standard (NS 9815: S-4008-100-T) (phenanthrene (Phe), anthracene (An), fluoranthene (Fluo), pyrene (Pyr), 11 h-benzo[a]fluorene (11H-B[a]F), 11 h-benzo[b]fluorene (11H-B[b]F), benz[a]anthracene (B[a]A), chrysene (Chry), benzo[b]fluoranthene (B[b]F), benzo[k]fluoranthene (B[k]F), benzo[a]pyrene (B[a]P), benzo[e]pyrene (B[e]P), indeno[1,2,3-cd]pyrene (Ind), dibenz[a,h]anthracene (D[a,h]A), benzo[g,h,i]perylene (B[g,h,i]P), each 100
Standard deviations of a data set comprised of triplicate PM10 bound PAH samples (
Table
Diagnostic binary ratios of PAHs, together with average, standard deviation, minimum and maximum of PAH concentrations (ng g−1 dry weight) in marine sediments collected at the study sites.
Number of rings | Molecular formula | Molecular mass | Average ( |
Standard deviation | Minimum | Maximum | Percentage contribution | |
---|---|---|---|---|---|---|---|---|
Phe | 3 | C14H10 | 178 | 15.77 | 6.19 | 4.33 | 37.17 | 22.71 |
An | 3 | C14H10 | 178 | 1.94 | 1.26 | 0.28 | 7.92 | 2.79 |
11H-B[a]F | 4 | C17H12 | 216 | 1.40 | 2.50 | N.D. | 12.82 | 2.02 |
11H-B[b]F | 4 | C17H12 | 216 | 0.82 | 1.31 | N.D. | 9.62 | 1.18 |
Fluo | 4 | C16H10 | 202 | 6.19 | 4.32 | 1.04 | 21.86 | 8.92 |
Pyr | 4 | C16H10 | 202 | 11.46 | 7.26 | 1.63 | 37.58 | 16.51 |
B[a]A | 4 | C18H12 | 228 | 0.69 | 0.86 | 0.13 | 4.84 | 0.99 |
Chry | 4 | C18H12 | 228 | 0.72 | 1.12 | 0.11 | 5.76 | 1.04 |
B[b]F | 5 | C20H12 | 252 | 2.10 | 3.28 | 0.05 | 16.06 | 3.02 |
B[k]F | 5 | C20H12 | 252 | 3.17 | 4.12 | 0.05 | 18.10 | 4.57 |
B[e]P | 5 | C20H12 | 252 | 2.93 | 4.33 | 0.05 | 20.55 | 4.22 |
B[a]P | 5 | C20H12 | 252 | 2.66 | 3.08 | 0.06 | 11.15 | 3.83 |
Ind | 6 | C22H12 | 276 | 3.30 | 5.21 | 0.04 | 22.32 | 4.75 |
D[a,h]A | 5 | C22H14 | 278 | 9.86 | 17.93 | 0.10 | 117.46 | 14.20 |
B[g,h,i]P | 6 | C22H12 | 276 | 6.42 | 7.90 | 0.15 | 48.02 | 9.25 |
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Ind/(Ind + B[g,h,i]P) | Diesel: 0.35–0.70 [ |
0.34 | 0.87 | |||||
B[a]A/Chry | Coal: 1.0–1.2 [ |
0.96 | 1.91 | |||||
B[a]P/B[g,h,i]P | Coal: 0.9–6.6, vehicles: 0.3–0.78, oil burning: >2 [ |
0.41 | 0.7 | |||||
Fluo/(Fluo + Pyr) | Coal: 0.53 [ |
0.35 | 0.41 | |||||
B[k]F/Ind | Diesel: 0.5 [ |
0.96 | 1.96 | |||||
An/(Phe + An) | Petroleum: <0.1, combustion: >0.1 [ |
0.11 | 0.11 | |||||
B[a]P/ |
0.13 | 0.45 |
Diagnostic binary ratios of PAHs in Andaman marine sediments in comparison with those of particulate PAHs from other emission sources.
Andaman |
Hat-Yai |
Emission sources |
|
|
|
---|---|---|---|---|---|
Andaman versus Hat-Yai | Andaman versus emission sources | ||||
An/(An + Phe) | 0.11 ± 0.11 | 1.16 ± 0.134 | 0.13 ± 0.11 | S* | NS** |
Fluo/(Fluo + Pyr) | 0.35 ± 0.41 | 0.72 ± 0.120 | 0.50 ± 0.053 | NS | S |
B[a]A/(B[a]A + Chry) | 0.96 ± 1.91 | 1.16 ± 0.053 | 0.51 ± 0.098 | S | NS |
B[a]P/(B[a]P + B[e]P) | 0.48 ± 1.05 | 0.88 ± 0.13 | 0.41 ± 0.15 | S | NS |
Ind/(Ind + B[g,h,i]P) | 0.34 ± 0.87 | 0.46 ± 0.13 | 0.46 ± 0.074 | S | S |
B[k]F/Ind | 0.96 ± 1.96 | 0.68 ± 0.13 | 0.22 ± 0.16 | S | S |
Box plots of PAHs in global marine and Andaman Sea sediments.
Distribution patterns of PAHs at the Tsunami affected coastal areas of Andaman Sea.
Distribution pattern of PAHs at the Tsunami affected coastal areas of Andaman Sea.
As illustrated in Table
Six PAH congeners have been selected and categorized into three-dimensional plots of molecular diagnostic binary ratios of Fluo/(Fluo + Pyr), Ind/(Ind + B[g,h,i]P), and B[a]P/Chry, which represents
Diagnostic binary ratios of PAHs in Andaman Sea sediments and various types of PM10 collected in Songkhla province, Thailand.
Three-dimensional plots of molecular diagnostic binary ratios of B[a]P/Chry, Ind/(Ind + B[g,h,i]P), and Fluo/(Fluo + Pyr) of Pakarang group and Non-Pakarang group in comparison with those of other global marine sediments
Three-dimensional plots of molecular diagnostic binary ratios of B[a]P/Chry, Ind/(Ind + B[g,h,i]P), and Fluo/(Fluo + Pyr) of Pakarang group and Non-Pakarang group in comparison with those of PM10 collected from various emission sources in Songkhla province
Further attempts were examined to investigate the reliability of binary ratios in order to characterize the origins of sediment samples. Statistical descriptions of six binary ratios were illustrated in Table
Thirdly, several studies report the importance of marine organisms for bioaccumulation of PAH compounds from dredged sediments [
Cluster analysis (CA) seeks to identify homogeneous subgroups of cases in a population which both minimize within-group variation and maximize between-group variation. In this study, CA was conducted using SPSS 13.0 for Windows through Ward linkage on the correlation coefficient distance. Through the application of three diagnostic binary ratios, it seems reasonable to represent original PAHs data set in three dimensions and thus visualize key information that was hidden in the table, while working with only B[a]A/Chry, Fluo/(Fluo + Pyr), and Ind/(Ind + B[g,h,i]P) of the original data (see Figure
Hierarchical dendrogram for PAHs using average linkage between groups.
HCA of world marine sediments in comparison with those of Andaman Sea sediments
HCA of PM10 from various emission sources in comparison with those of Andaman Sea sediments
Figure
The Indian Ocean Tsunami of 2004 was only overshadowed by the 2011 Great East Japan Earthquake and Tsunami with more than 15,000 fatal casualties, but also the nuclear accidents and meltdowns in the Fukushima Daiichi Nuclear Power Plant. Apart from investigating significant concerns about the effect of PAH aerosols on human health, the comprehensive investigation of the “fingerprints” of PAH aerosols from marine deposits in 2004 Tsunami affected coastal areas of Thailand may contribute to the science leading to better Tsunami prediction.
Molecular diagnostic binary ratios of PAHs in Tsunami 2004 affected coastal sediments, Hat-Yai urban aerosols, and PM10 from various sources in Songkhla province were comprehensively investigated and compared. Three-dimensional plots of molecular diagnostic binary ratios successfully discriminate “Pakarang group” from other global marine sediment samples. Since hydroacoustic profiles show the impact of terrestrial deposits adjacent to “Pakarang Cape” coastal area [
The author declares that there is no conflict of interests regarding the publication of this paper.
This work was performed with the approval of National Institute of Development Administration (NIDA) and financial support from National Research Council of Thailand (NRCT). The author acknowledges Assistant Professor Dr. Charnwit Kositanont, Assistant Professor Dr. Surat Bualert, and Ms. Teeta Intasaen from Inter-Department of Environmental Science, Faculty of Graduate Studies, Chulalongkorn University, for their contributions to filed samplings and laboratory works. The author would like to express his deepest gratitude to Ms. Woranuch Deelaman, Ms. Jitlada Muprasit, Dr. Peter Feldens, and Dr. Klaus Schwarzer for their kind assistance.