1 2
Title: Source and spatial distribution of polycyclic aromatic hydrocarbon contamination in coastal sediments of the Basque Country (Bay of Biscay).
3 4 5
Authors: Irati Legorburu*a, José Germán Rodrígueza, Victoriano Valenciaa, Oihana Solauna, Ángel Borjaa, Esmeralda Millánb, Ibon Galparsoroa, Joana Larretaa.
6 7
Affiliation:
8
a
9 10
b
AZTI-Tecnalia; Marine Research Division; Herrera Kaia z/g; 20110 Pasaia (Spain).
Departamento de Química Aplicada (Química Analítica); Facultad de Química, Universidad del País Vasco, Apartado 1072; 20080 Donostia (Spain).
11 12 13
*corresponding author:
[email protected]. Tel: (+34) 667174453; Fax: (+34) 946572555.
14 15
Abstract
16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Current European marine legislation requires the identification and control of human derived contaminant sources in the environment. In this contribution the source characterization and distribution of Polycyclic Aromatic Hydrocarbons (PAHs) in sediments within the Basque coast have been investigated. The combination of different source characterization approaches (i.e., GIS assisted-chemometrics, PAH diagnostic ratios and analyses of composition patterns) has provided a successful identification of the processes determining the PAH origin and distribution. Results highlight the role of urban/industrial combustion processes as the main PAH sources. However, the influence of additional secondary PAH sources (e. g. fires, runoff or coking activities) has also been identified. PAH concentrations ranged from 8 to 145445 µg/kg (d.w.) and varied at different spatial scales: estuarine systems and harbors showed significantly higher concentrations than shelf areas. Hence, the Ibaizabal estuary, which supports most of the anthropogenic PAH sources (i.e. industrialization, commercial and recreational harbors, etc.) in the region, showed also the highest PAH concentrations. Within the continental shelf, PAH concentrations also showed spatial differences: offshore locations were characterized by significantly higher concentrations, whilst the lowest values were found within the mid and most eastern sectors.
33 34 35
Keywords: Polycyclic Aromatic Hydrocarbon characterization, GIS, Basque Country, Bay of Biscay.
(PAH),
Sediment,
Source 1
36
1. Introduction
37
Current European marine legislation deals with the protection and restoration of aquatic
38
systems (EC, 2000; 2008a). Both the Water Framework Directive (WFD) and Marine
39
Strategy Framework Directive (MSFD), define the quality of aquatic systems in an
40
integrative way, considering together biological, hydro-morphological and physico-
41
chemical elements (Borja et al., 2008; Borja et al., 2010). Thus, in order to accomplish
42
with WFD and MSFD requirements, a good comprehension of the processes occurring
43
at different ecosystem components is needed (Borja et al., 2009). Moreover, considering
44
the Ecosystem-based approach adopted by the MSFD to the management of human
45
activities, the assessment of impacts derived from human actions in the oceans is
46
necessary (Bertram and Rehdanz, 2013). Therefore, in order to ensure the good
47
ecological functioning of these systems, the identification, control or even removal of
48
anthropogenic pollution sources is required (EC, 2000; 2008a). In this context,
49
sediments are good indicators of human contaminant inputs, as they provide time-
50
integrated information about the contamination of a particular location (e.g., Ridgway
51
and Shimmield, 2002; Rodríguez et al., 2007).
52
Due to their potential toxicity, polycyclic aromatic hydrocarbons (PAHs) are ubiquitous
53
contaminants of environmental concern (e.g., EC, 2008b). Once PAHs enter the aquatic
54
environment, they are easily adsorbed by suspended particles until their deposition into
55
seabed sediments (Boulobassi et al., 2006). In fact, due to their hydrophobic and
56
persistent nature, sediments have been described as an important reservoir for PAHs
57
(e.g., Alebic-Juretic, 2011). Thus, sediments constitute an appropriate matrix for the
58
PAH sources characterization in the aquatic environment (e.g., Commendatore et al.,
59
2012). Although naturally occurring processes release PAHs into the environment
60
(forest fires, volcanic eruptions, diagenetic processes of organic matter), sources from
61
anthropogenic origin prevail (Deyme et al., 2011). PAHs from anthropogenic origin are
62
usually classified into two main groups (Barakat et al., 2011): (i) pyrolytic PAHs,
63
formed during the incomplete combustion of organic matter (e.g. petroleum, coal, grass,
64
wood) and; (ii) petrogenic PAHs, derived from unburnt petroleum products (e.g. oil
65
exploitation activities, urban runoff, accidental spills). Depending on their source, PAHs
66
show characteristic composition patterns that can be used as fingerprints of the
67
processes responsible of their formation (Culotta et al., 2006). Although diagnostic
68
ratios have been commonly used as PAH source discrimination tools (Tobiszewski and 2
69
Namiesnik, 2012), the co-existence of multiple sources, could make difficult the source
70
apportionment process (Soclo et al., 2000). Hence, the solely reliance on diagnostic
71
ratios, could led into misleading interpretations of the obtained results during PAH
72
sources characterization (Yunker et al., 2002). In this sense, analyses of PAH
73
composition patterns or GIS-assissted chemometric techniques resulted in effective
74
complementary source characterization approaches (Khalili et al., 1995; Mostert et al.,
75
2010; Li et al., 2012).
76
Within this context, the main objectives of this contribution are: (i) to determine the
77
spatial distribution of PAH accumulation areas, over the Basque coast; (ii) to integrate
78
different PAH source apportionment approaches (i.e. PAH diagnostic ratios, analyses of
79
composition patterns, and GIS assisted-chemometrics) in order to obtain an accurate
80
source identification; and, (iii) to determine the applicability of the used methodology in
81
the assessment process needed for the achievement of legislative environmental goals.
82 83
2. Material and Methods
84
2.1. Study area
85
The study area covers the whole Basque coast, from the estuaries to the continental
86
shelf (ca.100 m water depth). The Basque coastal area is located in the southeastern Bay
87
of Biscay and has an approximate length of 150 km. It is drained by 12 main rivers
88
corresponding to the “upland” classification (Milliman and Syvitski, 1992), which are
89
responsible for the supply of 1.57 x 106 ton·yr-1 of suspended material into the Bay of
90
Biscay (Uriarte et al., 2004a) (Fig. 1). Basque estuaries are small in size and almost all
91
of them can be considered shallow systems (excepting Ibaizabal and Oiartzun estuaries).
92
However, they show strong differences in terms of geomorphological and hydrological
93
features (Valencia et al., 2004).
94
The Basque continental shelf is characterized by its narrowness and by the large number
95
of submarine canyons that intersect it (Uriarte et al., 2004b). Considering differences in
96
geomorphological and morphosedimentary features (Galparsoro et al., 2010), and in
97
human pressures (Borja et al., 2006), the Basque coast was divided into four water
98
bodies, according to the Water Framework Directive terminology: (i) the West Sector
99
(Cantabria-Matxitxako water body), characterized by a predominant rocky seafloor,
100
with the exception of the Ibaizabal estuary mouth (where sandy sediments are
101
dominant); (ii) the Mid Sector (Matxitxako-Getaria water body), where sedimentary 3
102
features are predominant; (iii) the East Sector (Getaria-Higer water body), characterized
103
by the presence of a flat rocky seafloor covered by a thin sedimentary layer; and (iv) the
104
Mompás-Pasaia water body (termed as east-MP) sector, where the presence of a large
105
submarine outfall (Borja et al., 2006), could give rise to increased PAH levels (Fig. 1).
106
In addition to these water bodies, a fifth area (the offshore sector; Fig. 1), has been
107
added; here, due to lower hydrodynamic conditions, particle associated contaminant
108
accumulation processes are likely to occur (Legorburu et al., 2013a).
109
Industrial concentration and population density have been identified as the main drivers
110
responsible for the most important pressures affecting to the Basque estuaries (Borja et
111
al., 2006). In addition to the high industrial development, untreated domestic and
112
industrial wastewaters have been directly dumped for many years, degrading seriously
113
the environmental quality of the area (Cearreta et al., 2004). However, over the last
114
years, the general decay and changing practices of the heaviest industrial activities,
115
added to the development of water treatment schemes, has led to an overall
116
improvement in the quality of these systems (Borja et al., 2009; Tueros et al., 2009;
117
Pascual et al., 2012). In contrast, riverine suspended inputs, dredged sediment disposal
118
activities or submarine outfalls are considered the main contaminant entrance pathways
119
to the continental shelf (Borja et al., 2006; Legorburu et al., 2013a).
120 121
2.2. Sample collection
122
In this contribution, data from different research projects carried out between 2009 and
123
2012 have been used. The spatial cover of the samples ranged from the estuaries to the
124
continental shelf (up to c.a. 100 m water depth). A total of 375 samples were obtained:
125
25 in harbors; 237 in estuaries; 103 in shallow coastal areas (i.e., 0-80m depth); and 10
126
in offshore locations (i.e., 80-115m depth) (Fig. 1).
127
Sampling was undertaken using either Day, Van Veen or Shipek grabs in the subtidal
128
area; meanwhile, intertidal sediments were sampled directly. For all samples, the upper
129
10 cm sediment layer was collected.
130 131
2.3. Sample analysis
132
2.3.1. Sedimentological parameters
133
Grain size distribution of samples with a low fine sediment content (10 %), were analyzed by the Laser Diffraction Particle Size
136
Analyzer (LDPSA) method. As LDPSA method underestimates the mud content of the
137
sediments (Campbell, 2003), results obtained by LDPSA were transformed, in order to
138
homogenize and make comparable both analytical procedures (Rodríguez and Uriarte,
139
2009). Organic matter content of the sediments was determined by loss of weight on
140
ignition at 450 ºC during 6 h (Dean, 1974). Redox potential (Eh) was measured with a
141
combined Pt-ring electrode (Langmuir, 1971).
142 143
2.3.2. PAH analysis
144
Prior to PAH analysis, samples were freeze-dried using a CHRIST Alpha 1-4 LDplus
145
freeze dryer (Fisher Bioblock Scientific). PAH extraction was performed using
146
Accelerated Solvent Extraction (ASE) method (ASE 200 system, DIONEX). From
147
bottom to top, the extraction cell was packed by: a cellulose filter; 1g of Florisil topped
148
by another cellulose filter; 1g of anhydrous sodium sulphate; and finally, 5 to 10g of
149
lyophilized sample. PAHs were eluted using a pentane/dichloromethane mixture (50:50
150
v/v; 15min, 100 ºC, 1750 psi). Then, collected extracts were concentrated with a
151
TurboVap rotary evaporator (25 ºC, 6 psi). Extract clean-up procedure was performed
152
as follows: first, the extract was diluted to a total volume of 15 mL with
153
dichloromethane; second, it was filtered using standard MF Millipore membranes (0.45
154
µm pore size); third, 4 mL of the filtered extract were purified by means of Gel
155
Permeation Chromatography (GPC; Envirogel column, Waters); and finally, the
156
obtained elutriate was evaporated (TurboVap rotary evaporator; 25 ºC, 6 psi) and
157
reconstituted with 1 mL of dichloromethane.
158
Selected parent PAHs (Table 1) were quantitatively determined by GC-MS with an
159
Agilent 6890 GD coupled with an Agilent 5973 MSD instrument. A Meta X5 capillary
160
column was used (Teknokroma, 30 m, 0.25 mm i.d., 0.25 µm thick phase film). Helium
161
was used as carrier gas at a constant flow of 1.6 mL/min. Oven temperature program
162
was set as follows: after 1 min at an initial temperature of 80 ºC, it was set to 200 ºC at a
163
rate of 20 ºC/min. Then, it was increased to 315 ºC, at a rate of 6 ºC/min, with a final
164
isothermal period of 1 min. The MSD ion source temperature was fixed at 320 ºC. Ions
165
were monitored in the SIM mode. The certified IAEA-417 sediment reference material
166
(International Atomic Energy Agency, Austria) was used to check the accuracy of the
167
analytical procedures. Mean recoveries for almost all the certified PAHs were between 5
168
80-90%. IP and BGHIP showed lower recovery rates: these were between 60% and
169
70%.
170 171
2.4. PAH sources characterization
172
In order to characterize the PAH sources, and their spatial occurrence along the Basque
173
coast, different approaches have been combined:
174 175
2.4.1. PAHs diagnostic ratios
176
The identification of anthropogenic PAH sources in the environment can be performed
177
using diagnostic ratios of specific compounds. In this contribution cross-plots of
178
BaA/(BaA+CHR) vs. F/(F+Py) and IP/(IP+BGHIP) vs. F/(F+Py) ratios have been used
179
to discriminate among the different origins of the PAHs (Yunker et al., 2002; Viñas et
180
al., 2010; Wagener et al., 2010; Tobiszewski and Namiesnik, 2012).
181 182
2.4.2. PAHs composition
183
The relative abundance of certain PAH congeners have been used to distinguish
184
different pollution sources (e.g., Baumard et al., 1998). Hence, the spatial distribution of
185
samples, according to their PAH composition, was evaluated using 3 different
186
representations/graphs: (i) triplots representing the relative abundance of the 3 different
187
PAH groupings (Graham and Midgley, 2000), which were made according to the
188
number of rings (3-ring PAHs, 4-rings PAHs, and (5+6)-rings PAHs; Table 1); (ii)
189
graphs representing the average concentration for each parent PAH on each of the
190
considered areas; and (iii) the average PAH distribution, based on the isomeric
191
composition of the samples (178, 202, 228, 252, and 276 mass isomers; Table 1).
192 193
2.4.3. Partial ReDundancy Analysis (pRDA)
194
In order to determine the specific PAH sources, and based on previous knowledge
195
(Borja et al., 2006), an analysis of the human pressures likely to cause PAHs
196
contamination in the Basque estuaries was performed. Considered pressures are listed in
197
Table 1 in Supplementary Material (hereafter, SM). In the case of jetties,
198
industrial/urban/storm-water dumpings and harbor oil pumps, the pressure effect was
199
calculated as the geographical distance between the pressures and the sample location.
200
A path distance algorithm implemented in the Spatial Analyst extension of ArcGIS 6
201
9.3.1 software (ESRI) was used to determine the corresponding distances. Population,
202
industrial establishment and driveway densities, and the industrial/urban land surfaces
203
were determined in relation to the total area of the municipalities around the estuaries.
204
Vehicle float was measured in relation to the total driveway length of the municipalities
205
around the estuaries; and finally, harbor surface was determined in relation to the total
206
estuarine surface. Moreover, sedimentological parameters of the samples (mud and
207
organic matter percentages and redox potential), were also considered in the sources
208
characterization. Once all the information was gathered together, outliers were removed
209
following Box-Plot method (Tukey, 1977). Finally, the pRDA analysis permitted the
210
determination of the relationship between independent variables and the PAH
211
distribution in sediments (Legendre et al., 2005). The performed analysis determined
212
the PAH variability with: (i) considered human pressures; and (ii) sediment properties.
213
The significance of independent variables was tested using Monte Carlo permutation
214
tests. Furthermore, the partialling out procedure of the explained variance determined
215
the percentage of variance explained by each group of independent variables by
216
themselves, and that explained by interactions between both groups (Borcard et al.,
217
1992). Canoco software was used in the pRDA performance.
218 219
2.4.4. PAH spatial distribution
220
After data integration into the GIS environment, a spline with barriers interpolation
221
algorithm was used to create PAH distribution maps (ArcGIS 9.3.1 software, ESRI).
222
That interpolation method permitted the differentiation of the main seabed
223
geomorphological features and physical barriers of the coastline that could influence
224
sediment distribution and transport patterns.
225 226
3.Results
227
3.1. PAH diagnostic ratios
228
Considering the total of the samples, obtained mean F/(F+Py), BaA/(BaA+CHR) and
229
IP/(IP+BGHIP) ratios (0.56 ± 0.10,
230
underlined the importance of combustion-related processes in the PAH derived
231
contamination (Figs. 1, 2SM). Despite of such a relatively homogeneous range of
232
values, some areas showed more scattered values (e.g., Ibaizabal, Oka , Oiartzun and
0.55 ± 0.13 and 0.52 ± 0.14, respectively)
7
233
Bidasoa estuaries and the coastal areas). This higher variability could be related with the
234
occurrence of multiple PAH sources, as discussed in following sections.
235 236
3.2. PAH composition
237
Obtained mean parent PAH concentrations and mean isomeric PAH composition
238
profiles are shown in Fig. 2. Ranging in most cases between 15-20% of the total PAH
239
concentration, benzofluoranthenes were the most abundant compounds (Figs 2a-f). A
240
was the lowest contributor, accounting in all cases for less than 5% of the total PAH
241
concentration (Figs. 2a-f). Considering isomeric composition profiles, mass 202 and
242
252 compounds predominated, whilst lowest concentrations were observed for mass
243
178 and 276 compounds (Fig. 2g). 4- and (5+6)-ring compounds (high molecular
244
weight, HMW) were the most abundant, whilst 3-ring compounds (low molecular
245
weight, LMW) accounted for less than 25% of the PAH composition in all cases (Fig.
246
3SM).
247
Despite of the similarities in the composition patterns, PAH groupings distributed
248
inhomogeneusly: generally, HMW compounds were more abundant within the eastern
249
third of the coast, whilst for the western and middle thirds an increase in the relative
250
contribution of LMW compounds was observed (Figs. 3a,b).
251 252
3.3. Partial Redundancy Analysis
253
According to pRDA results (Fig. 3c-e), independent variables explained 46.7% of the
254
variability in the PAH concentration of estuarine sediments (F-ratio=30.07; p-
255
value=0.002). From the total of considered pressures and sedimentological parameters,
256
those showing a significant effect in the global PAH variability were: mud content;
257
harbor and urban land surface percentages; driveway density; vehicle float; and the
258
industrial establishment density. The partialling out procedure of the variance
259
determined that 23.1% of the variance was explained by the mud content of sediments,
260
and 13.9%, by the significant pressures. Explained variance derived from interactions
261
between both groups accounted for 9.7% (Fig. 3e).
262
Angles formed between variables are representative of the correlation found between
263
them: angles close to 90º indicate no correlation, angles close to 0º are indicative of a
264
strong positive correlation and angles close to 180º indicate a strong negative
265
correlation. All PAHs correlated positively with both the harbor surface percentage and 8
266
the mud content of the samples. Except A and BkF, all PAHs correlated positively with
267
driveway density, vehicle float and the industrial establishment density. Finally, whilst
268
the correlation between the urban surface percentage with A and BkF was negative, no
269
correlation was found with the rest of PAHs.
270 271
3.4. PAH distribution
272
Minimum, maximum and mean parent PAH concentrations for each of the studied
273
estuaries and coastal areas, are shown in Table 2SM. In all cases, parent PAHs showed
274
lowest mean concentrations in the east sector, whilst the highest corresponded to
275
Ibaizabal estuary. The ∑12 PAH distribution over the whole study area is shown in Fig.
276
4a. The ∑12 PAH distribution pattern showed differences at different spatial levels:
277
harbor domains and estuarine water courses showed significantly higher ∑12 PAH
278
concentrations than coastal areas (Fig. 4b).
279
At coastal locations, ∑12 PAH concentrations also varied spatially (Fig. 4c): the
280
offshore sector, with a mean value of 4,927 µg/kg d.w., showed significantly higher
281
∑12 PAH concentrations than the mid, east and east-MP sectors (655, 95, 240 µg/kg
282
d.w., respectively). Finally, with a mean value of 2,284 µg/kg d.w., the western sector
283
showed intermediate ∑12 PAH concentrations.
284
In estuaries (Fig. 4d), mean ∑12 PAH concentrations in Ibaizabal (18,369 µg/kg d.w.)
285
were significantly higher than in the rest of estuaries, that ranged from 527 µg/kg d.w.
286
in Barbadun to 4,814 µg/kg d.w. in Oiartzun.
287
Finally, samples were classified according to the sediment quality guideline values
288
(SQGs) proposed for North America by Long et al (1995) (Table 3SM). Due to the
289
higher PAH concentrations measured, a greater probability of adverse biological effects
290
was observed in estuaries than in coastal areas. However, most of the samples
291
(excepting those from Ibaizabal estuary), were classified in the
