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Particulate metal distribution in Tagus estuary (Portugal) during a flood episode
Marine Pollution Bulletin 64 (2012) 2109–2116
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Particulate metal distribution in Tagus estuary (Portugal) during a flood episode B. Duarte ⇑, I. Caçador Center of Oceanography of the Faculty of Sciences of the University of Lisbon (CO), Campo Grande, 1749-016 Lisbon, Portugal
a r t i c l e
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Keywords: Tagus estuary Particulate metals Flood events SPM
a b s t r a c t Particulate metal concentrations were assessed before, during and after a flood episode in the Tagus estuary. Particulate metal concentrations showed a decrease during the flood period and very similar values in the months before and after the flood event. Before this period, sampling station characteristics were verified to be homogenous during the peak of the flooding event, as all of the sampling stations assumed very specific characteristics. One of the main consequences from the flood, concurrent with a decrease in particulate metal concentrations, was the high input of SPM into the estuarine area. This finding indicates higher levels of heavy metals in fine-sized particles at low SPM concentration than those present in coarser particles at high SPM levels. These periodic flood events can be considered as estuarine contamination masks and should be interpreted as periods of dilution in heavy metal contamination rather than as an estuarine cleansing process. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Coastal ecosystems are greatly affected by human activities of environmental concern and public interest (Cohen et al., 2001). Increasing anthropogenic loads of trace elements in coastal ecosystems are one of the most significant inputs of allochthonous matter into the ocean via river discharges into the estuarine mixing zone. As a consequence of these mixing processes, estuaries are often considered to be filters of river-derived signals (Zhou et al., 1998). Several studies (Morris et al., 1986; Bewers and Yeats, 1989; Vale, 1990) describe estuaries as efficient filters of suspended particulate matter (SPM) and heavy metals (Caçador et al., 1996), primarily through particle-solute interactions, flocculation processes and the settling of metal-charged particles. In contrast, there are also inverse processes, such as the re-suspension of riverbed sediments, the desorption of metals from SPM and sediments and the diffusion processes between sediment pore water and the overlying water (Liu, 1996). As a consequence of such a complex network of mechanisms, heavy metals tend to display what is known as either conservative or non-conservative behavior, depending on the factors (physical or chemical) that affect their distribution (Liu et al., 1998; Turner et al., 1998). The metal transport mechanisms from the river to the estuary and from the estuary to the ocean depend on the links established between metals and the organic ligands present in the dissolved phase, as well as on the nature and amount of mineral and organic particles in suspension (Viers et al., 2009). Since the industrial revolution, large amounts of contaminants have been released to the ⇑ Corresponding author. Tel.: +351 21 75 00000x20319; fax: +351 21 75 00009. E-mail address: [email protected] (B. Duarte). 0025-326X/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.marpolbul.2012.07.016
atmosphere, soil and waterways. Most of these emissions will ultimately be transferred into a water matrix, either by atmospheric deposition or by soil erosion, where they will remain dissolved or will attach to sediment particles (Nriagu, 1988; Viers et al., 2009). This dynamic mechanism is greatly influenced by a river’s hydrological conditions. The Tagus estuary is one of the largest estuaries in Europe and has historically received effluents from agricultural, industrial, and urban sources. This system has been contaminated mainly by two industrial areas that are located along the northern and southern perimeters (Bettencourt, 1988; Vale, 1990; Cotté-Krieff et al., 2000; Canário et al., 2005) and by domestic effluents from the metropolitan area of Lisbon (Canário and Vale, 2007). Apart from being the site of a major seaport, the commercial and fishing activities in the estuary are adversely affected by the inflow of untreated effluents from approximately 2.5 million Greater Lisbon inhabitants, together with contaminants from the area’s industry (e.g., chemicals, petrochemicals, metallurgic industries, shipyards and cement manufacturing) and agriculture (e.g., fertilizers and pesticides). The Tagus River is frequently punctuated by flood events upstream in its drainage basin, with predictable consequences in terms of river flow and discharges into the estuary. These flood events have numerous consequences, not only by introducing abnormally high amounts of fresh water into the estuary but also by affecting the estuarine chemistry and hydrology. Because the Tagus estuary has historically been a sink for accumulated metals (Caçador et al., 1996), these extreme episodic events can greatly affect the storage capacity of the estuary in addition to temporarily modifying the chemistry of the estuary. In this study, the authors examined the effects of a flood event in the Tagus drainage basin
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on its estuary, particularly focusing on the consequences of water chemistry changes and their impact on contaminant levels and circulation in the estuarine area.
2. Material and methods 2.1. Sampling sites and sample collection The Tagus River, which is the main source of freshwater to the Tagus estuary, drains an area of 86,629 km2, representing the second most important hydrological basin in the Iberian Peninsula. Inflow fluctuates seasonally, with an average monthly value varying from 120 m3 s1 in the summer to 653 m3 s1 in winter (from the last 30 years of the Water National Institute public database, INAG). Estimated water residence times range from 6 to <65 days for winter and summer average river discharges, respectively (Vale and Sundby, 1987). Sampling was conducted during high tide to benefit from high water stability. The four sites were sampled at the surface (approximately 1 m from the water surface) to take into account the absence of stratification of the water column previously reported at these sampling sites (Gameiro et al., 2004). All the sampling sites were upstream of the Vasco da Gamma bridge (Fig. 1). Three of the sites (S1, S3 and S4) were located along a longitudinal axis, and the fourth site (S2) was located in the North Cala. The North Cala is a channel between the airfield and Alverca and the Olivais Dock, a distance of 14 km. This channel is bound on the northern side by the Tagus River and the small island of Póvoa; the channel has a low hydrodynamic characteristic, and its sediments are mainly of fluvial origin (Vale and Sundby, 1987). The location of these sites facilitated the study of the physical-chemical differ-
ences resulting from their specific longitudinal positions within the estuary. Site S1 (38°520 39.4900 N, 9°10 26.9900 W), located between the southern tip of the small island of Alhandra and the northern tip of the small island of Povoa, was the site located the furthest upstream; therefore, it was the site that was most impacted by the Tagus River. Site S2 (38°490 38.3900 N, 9°40 42.3600 W), located in the North Cala channel in front of the Lisbon Solid Waste Treatment Plant, is also the section that flows from the Trancão River and has large quantities of pollutants and suspended particulate matter (Araújo et al., 1998). Situated between the bank and the slope of the small island of Povoa was site S3 (38°490 18.4500 N, 9°30 9.6300 W). Site S4 (38°460 35.7800 N, 9°20 29.7100 W) was the furthest downstream, closest to the strait where seawater enters into the estuary. Samples were collected once a month during a three-month period in 2010 (February, March and April). February was considered to be the period before the flooding took place, March sampling occurred during the peak of the flood event and April sampling was carried out during the period of resettling after the flood event. For all of the sampling dates, the tidal amplitude was nearly constant (2.33–2.5 m). Water temperature, salinity, suspended particulate matter (SPM), and pH values were determined using the water samples. The water temperature, salinity, and pH were measured in situ using a thermometer, an ATAGO S/Mill-E refractometer, and a HI9813 pH meter (Hanna Instruments), respectively. To determine the concentration of SPM, the water samples were filtered through pre-weighed GF/C Whatman filters, which were subsequently dried at 80 °C for approximately 24 h and were then reweighed. 2.2. Hydrodynamic parameters To verify that the sample collections were taken during appropriate periods (i.e., pre-flood, flood and post-flood), the National Institute of Water database (www.snirh.pt) was consulted and the datasets corresponding to the months of February, March and April were retrieved. Hydrodynamic level was used as a proxy for river discharge to confirm the river’s hydrodynamic state (Fig. 2). 2.3. Heavy metal analysis For heavy metal analysis, the filters described above were used for SPM quantification. After accurate re-weighing, the filters were placed inside Teflon reactors with a 2 mL of solution of HNO3:HCl (3:1) and mineralized in an oven for 3 h at 110 °C (Wiese et al., 1997). After cooling, the mixture was filtered through Whatman N° 42 filters. Heavy metal concentrations were determined by Flame Atomic Absorption Spectrometry (SpectraAA 50, VARIAN). Blank filters were also subjected to the same procedure, and its metals content used to correct the metal concentration of the SPM filters. The accuracy of the results was checked by processing CRM 145 and CRM 146 reference materials. Trace metal concentrations in the reference materials determined by FAAS were not significantly different from the certified concentrations (Student’s ttest; a = 0.05). 2.4. Data processing and statistical analysis
Fig. 1. Map of Portugal with the Tagus estuary area enlarged. The sampling points are marked with numbers (Gameiro et al., 2004).
Mapping of the analysed parameters was performed using Ocean Data View 4.3.7 software using the MedHR (Mediterranean High Resolution) package to input the bathymetric, shoreline and hydrological characteristics of the study area. Spearman correlations were attained using Statasoft Inc., Statistica version 7.0 software. Resemblance and ANOSIM analyses were accomplished with PRIMER 6 software (Clarke and Gorley, 2006).
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Fig. 2. River discharge (www.snirh.pt) from February to April 2010, with black marks representing the sampling periods.
3. Results
Table 1 Water column characterization during the study period (mean ± standard deviation).
3.1. Water column characterization The period with the highest river flow in 2010 occurred between February 17th and March 17th (Fig. 2). The sampling in flood conditions took place on March 9th, with a mean river discharge of 750.74 m3/s. The sampling in the normal river flow occurred one month before and one month after this period (February 8th and April 8th, respectively), with a mean river discharge of 180.24 m3/s in pre-flood sampling and 265.53 m3/s in post-flood sampling (Fig. 2). The pH (Table 1) was relatively constant in February (mean = 8.3) and April (mean = 8.3), decreasing with salinity during the flood period (March), when it registered the lowest values (mean = 7.9). The salinity of water column (Table 1) was also lower in March (mean = 4.3) than in February (mean = 11.5) and April (mean = 13.3). The concentration of suspended matter (Table 1) in the river was highly correlated to the river’s flow, and the concentration showed an inverse relation to the pH and salinity, with higher values (mean = 47.13 mg/L) registered during the flood period (March) that decreased by 50% both before and after the flood event (February and April). 3.2. Particulate heavy metal With the exception of Cu and Cr, all heavy metals showed a similar pattern (Fig. 3). The assessed metal concentrations showed a decrease in particulate metal concentration during the flood period and in their approximated values in the months before and after the flood event. Cu exhibited exactly the opposite pattern, with an increase in the concentration of suspended particulate matter during the flood period. Cr had very similar behavior to that observed for Cu, although its behavior was not as pronounced. This result can also be observed based on the Spearman correlation coefficients (Table 2), which showed positive correlations between all metals, except when tested against Cu or Cr. There was no significant correlation between the Cu and Cr concentrations, although there were similar patterns of concentrations during the study period. The ANOSIM analysis confirmed the variation observed in the interpolation graphs. Considering the sampling period as a factor for comparison, there was a high significance (r = 0.866, p = 0.001) between the water column characteristics and the sample collection month.
River discharge (m3/s)
Salinity (PSU)
pH
SPM (mg/L)
February Site 1 Site 2 Site 3 Site 4
236.58 225.01 234.65 230.79
7.0 ± 0.00 12.5 ± 0.00 14.0 ± 0.00 12.5 ± 0.00
8.21 ± 0.00 8.04 ± 0.00 8.13 ± 0.00 8.26 ± 0.00
15.60 ± 0.40 22.47 ± 0.64 18.87 ± 5.37 16.73 ± 0.58
March Site 1 Site 2 Site 3 Site 4
899.67 864.97 888.10 878.47
5.0 ± 0.00 3.0 ± 0.00 4.0 ± 0.00 5.00 ± 0.00
7.88 ± 0.00 8.19 ± 0.00 7.82 ± 0.00 7.80 ± 0.00
47.13 ± 4.05 44.60 ± 5.56 35.73 ± 10.77 30.73 ± 1.75
April Site 1 Site 2 Site 3 Site 4
294.40 268.69 292.48 290.55
7.0 ± 0.00 16.0 ± 0.00 13.5 ± 0.00 16.5 ± 0.00
8.42 ± 0.00 8.21 ± 0.00 8. 26 ± 0.00 8. 35 ± 0.00
11.73 ± 0.95 26.07 ± 1.53 18.87 ± 0.99 23.27 ± 0.81
To understand the source of these variations, additional posthoc tests were performed. Observing the resemblance cluster (Fig. 4) and considering the sampling month, there was a clear separation observed in the two main branches (second division) of the cluster, distinguishing the samples collected during the flooding period from the samples collected before and after the flooding period. Only the sample collected at Site 3 during April (the postflood period) provided an exception to this pattern of similarity, creating the first main separation in the cluster analysis. By examining the Multi-Dimensional Scaling (MDS) plot analysis (stress factor 0.08), it was observed that not only were the flood stage samples completely separated from the pre- and post-flood samples, as observed in the resemblance cluster, but also that there were sub-groups within both groups of samples. In regard to the samples collected during the flood period, there was a noticeable separation between the sampling stations; the samples collected before and after the flood indicated a separation only between Station 2 and the remaining stations (Fig. 5). Performing a Principal Components Analysis (PCA) using principal components 1 and 2 (71% of cumulative variation), this distribution was confirmed by the environmental and physical– chemical drivers (Fig. 6). As previously observed in the interpolation maps (Fig. 3), SPM and metal concentrations drove the sample distribution in opposite directions, thus an increase in particulate
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Fig. 3. Interpolation maps of particulate heavy metal concentrations (lg/g SPM) for February, March and April as generated by the ODV software.
metal concentrations was not concomitant with an increase in SPM in the water column.
4. Discussion Metal concentrations in the Tagus estuary are largely influenced by external contributors, including industrial activities, harbor pollution and agricultural pollution (Vale et al., 1990; Vale et al., 2008; Duarte et al., 2010). Additionally, SPM may originate either inside the estuary (through shoreline erosion and re-suspension of bottom sediments) or outside the estuary and can be transported to
the inner bay via downstream river flow or from upstream by way of tidal flooding (Viers et al., 2009). During the study period of February to April 2010, the Tagus estuary experienced the effects of a flood event that occurred along the river course, leading to a large input of river water discharged into the estuary that had very different characteristics compared to the normal estuarine water. Before this period of high discharge from the river, the sampling station characteristics were very similar, making it very difficult to establish a distinction between them; however, during the peak flooding event, the stations assumed very specific characteristics (Fig. 5). This finding was most likely due to their specific location downstream and their vulnerability to the influence of
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Fig. 3 (continued)
the river discharge. This effect was most evident in the case of sampling Station 4, which was located further down in the estuary and was more greatly influenced by the sea at high tide. Additionally,
Stations 1 and 2 showed very similar characteristics due to their locations in the channel between the river margins and Povoa Island. All of these differences were amplified by the high discharge
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Table 2 Spearman correlation coefficients between the physical–chemical characteristics and the particulate heavy metal in the water column. Salinity Salinity pH SPM HL Pb Cd Cu Zn Ni Co Cr
pH
SPM
0.66 0.66** 0.46** 0.66** 0.49** 0.48** 0.67** 0.40* 0.10 0.38* 0.21
**
0.32 0.40* 0.38* 0.32 0.36* 0.24 0.01 0.37* 0.09
HL **
0.46 0.32
0.66** 0.86** 0.80** 0.42** 0.85** 0.65** 0.85** 0.04
Pb **
0.66 0.40* 0.66** 0.68** 0.69** 0.36 0.65** 0.57** 0.67** 0.29
Cd **
0.49 0.38* 0.86** 0.68** 0.93** 0.42** 0.88** 0.76** 0.93** 0.14
Cu **
0.48 0.32 0.80** 0.69** 0.93** 0.30 0.80** 0.75** 0.92** 0.19
Zn **
0.67 0.36* 0.42** 0.36* 0.42** 0.30 0.34* 0.17 0.28 0.01
Ni *
0.40 0.24 0.85** 0.65** 0.88** 0.80** 0.34*
0.10 0.01 0.65** 0.57** 0.76** 0.75** 0.17 0.73**
0.73** 0.86** 0.12
0.81** 0.14
Co
Cr *
0.38 0.37* 0.85** 0.67** 0.93** 0.92** 0.28 0.86** 0.81**
0.21 0.09 0.04 0.29 0.14 0.19 0.01 0.12 0.14 0.12
0.12
HL – hydrometric level. p < 0.05. p < 0.01).
*
**
Fig. 4. Resemblance cluster analysis of the sample collection months.
Fig. 5. MDS plot of the sampling sites grouped by period of sampling according to the ordination.
during the river’s flooding, yielding a very distinct pattern in terms of water chemistry parameters compared to those occurring under normal conditions. The river flooding differentially affected the sampling sites due to their geographic positions within the estuary. Observing the entire estuary during both a flood event and a nor-
mal period, one of the most noticeable effects of flooding was the high input of SPM into the estuarine area, although this high river input verified that the concentrations of most of the trace metals were greatly diminished. This result has been previously reported in similar studies (Benoit et al., 1994; Turner et al., 2006; Zhou
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Fig. 6. PCA diagram of the samples and correspondent variability vectors for all studied samples (sample codes stand for e.g.,: APRS23 stands for April Site 2 Replicate 3).
et al., 1998). This relationship can be explained by the relative enrichment of metals in SPM at low SPM concentrations and the depletion of metals from SPM in inverse conditions. This effect is most likely due to higher levels of heavy metals in fine-sized particles (<0.45 lm) at low SPM concentration than those present in coarser particles at high SPM levels (Zhou and Liu, 2000). The analysis of organic carbon (OC) of the colloids in previous work (Benoit et al., 1994) indicated higher amounts of OC in these small particles than in coarser particles. This effect can also be shown by the behavior observed for Cu and Cr. Both of these metals have a high affinity for organic particles because their speciation is predominantly associated with the organic fraction of sediments (Duarte et al., 2008; Reboreda and Caçador, 2007). This SPM distribution pattern was also previously observed in the Guadiana River (Caetano et al., 2006). In this work, it was verified that during a flooding event, large amounts of sand were transported downstream by the river discharge and deposited away from the mouth of the river. These sands contained a higher inorganic fraction and lower trace metal content than estuarine sediments and SPM. During the flood, two main characteristics were observed: a large input of fresh water to the entire estuarine zone (Ferreira et al., 2000) and a decrease in the residence time of the water and SPM. These conditions are not favorable to chemical alterations in the elemental composition of the SPM, either from shoreline erosion or from river transport, resulting in a homogenous spatial distribution of the SPM chemical composition. As previously confirmed by Caetano et al. (2006) in the Guadina estuary, the heavy metal concentrations in the particulate matter transported during flooding events were up to one order of magnitude lower than the SPM values in normal conditions. This difference agrees with the absence of industrial activities in the drainage basin (in this case, more than 100 km upstream of the Greater Lisbon area) and contrasts with the findings of other highly urbanized river drainage basins (Vale, 1990; Pohl et al., 2002). Thus, the flood event masked the signal of local anthropogenic sources in the estuary, which, under normal circumstances, would be detected within the SPM. Observing the significant positive correlation between heavy metal concentrations, this finding also reinforces the role of river drivers in the circulation of particulate heavy metals. This result indicates the
Table 3 Average SPM concentration (mg/L) and particulate heavy metal concentration (lg/g) in and after flood period in 19791980 and 2010. 1979–1980a
SPM Zn Cu Pb Cd Co Ni Cr a b
2010b
Normal flow
Flood
Normal flow
Flood
5.6 520 57.2 197.6 2.6 n.a. n.a. n.a.
Variable (400-40) 400 56 56 1.6 16 64 128
18.4 8689 16 157 26 41 50 15
39.5 3597 36 79 12 24 32 19
Data from Vale (1986). This study.
strong influence of river flow and physical–chemical factors as environmental drivers that affect the SPM concentrations in the water column of estuaries. These correlations also suggest that all of the heavy metals examined had the same origin, as they simultaneously varied in concentration. Vale (1986) also studied a 1979 flood event and its impact on the particulate metal concentrations in the Tagus estuary. Comparing those values with the present study, there are some differences (Table 3). Vale (1986) found an increase, although to a much higher degree, in the SPM concentration during flood conditions, which occurred simultaneously with a decrease in the particulate metal concentration. Another interesting point when comparing both periods (1979–1980 and 2010) was the observation of non-homogenous fluctuations in estuary contamination, even at normal flow conditions. Although Zn, Cd and Co had higher concentrations, as noted in the 1979– 1980 study, all the other analysed elements showed a reduction in concentration. The decrease in concentration of Cu, Pb, Ni and Cr was concomitant with the de-activation of a large number of metallurgic industrial areas along the estuarine shoreline (Caçador et al., 2009). Cobalt concentrations, however, presented some differences between both time periods (1979–1980 and 2010); these were very minor in their extent, not reaching a significant order of magnitude. As for Cd and Zn, inversely to what was recorded for
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the other metals, the present study found a significant increase in these metals. Not only do both of these metals have very similar chemistry and normally compete for the same binding sites (Marschner, 1995) but their presence in fertilizers is also well known (Eisler, 1986a,b). The increase in the concentration of these metals was concomitant with the intensification of agricultural activities throughout the Tagus basin. The findings from this work and the data put forward by Vale (1986) for the 1979 flood indicate that the environmental drivers controlling the flow of particulate heavy metals into the estuary change the SPM chemistry, thereby affecting all of the elements rather than having a metal-specific effect. 5. Conclusion Episodic river floods in the Tagus drainage basin punctuate the normal river flow and have consequences at the estuarine level. Along with all the changes in water chemistry, a primary physical event of these river floods is the transport of elevated levels of inert sand material downstream. This combination of factors that affect water chemical characteristics, along with a decrease in the estuarine water residence time, make these flood events conceal estuarine contamination and can therefore be interpreted as periods of heavy metal contamination dilution rather than an estuarine cleansing process. Acknowledgments: The authors would like to thank to the ‘‘Fundação para a Ciência e Tecnologia’’ for funding the research in the Centre of Oceanography throughout the project PEst-OE/MAR/UI0199/2011. This work was funded by VALORSUL, S.A. throughout its estuarine environmental monitoring program. The authors would also like to thank to the ECOSAM project (PTDC/AAC-CLI/104085/2008) for funding B. Duarte investigation grant. References Araújo, F., Pinheiro, T., Alves, L.C., Valério, P., Gaspar, F., Alves, J., 1998. Elemental composition in sediments and water in the Trancão river basin. A preliminary study. Nuclear Instruments and Methods in Physics Research B 136, 1005–1012. Benoit, G., Oktay-Marshall, S., Cantu II, A., Hood, E., Coleman, C., Corapcioglu, M., Santschi, P., 1994. Partitioning of Cu, Pb, Ag, Zn, Fe, Al, and Mn between filterretained particles and solution in six Texas estuaries. Marine Chemistry 45, 307–336. Bettencourt, A., 1988. On arsenic speciation in the Tagus Estuary. Netherlands Journal of Sea Research 22, 205–212. Bewers, J., Yeats, P., 1989. Transport of river-derived trace metals through the coastal zone. Netherlands Journal of Sea Research 23, 359–368. Caçador, I., Vale, C., Catarino, F., 1996. The influence of plants on concentration and fractionation of Zn, Pb, and Cu in salt marsh sediments (Tagus Estuary, Portugal). Journal of Aquatic Ecosystem Health 5, 193–198. Caçador, I., Caetano, M., Duarte, M., Vale, C., 2009. Stock and losses of trace metals from salt marsh plants. Marine Environmental Research 67, 75–82. Caetano, M., Vale, C., Falcão, M., 2006. Particulate metal distribution in Guadina estuary punctuated by flood episodes. Estuarine, Coastal and Shelf Science 70, 109–116. Canário, J., Vale, C., 2007. Monitoring program for the Tagus Estuary and tributaries, Scientific Report, IPIMAR, June 2007, p. 78. Canário, J., Vale, C., Caetano, M., 2005. Distribution of monomethylmercury and mercury in surface sediments of the Tagus Estuary (Portugal). Marine Pollution Bulletin 50, 1142–1145.
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Particulate metal distribution in Tagus estuary (Portugal) during a flood episode B. Duarte ⇑, I. Caçador Center of Oceanography of the Faculty of Sciences of the University of Lisbon (CO), Campo Grande, 1749-016 Lisbon, Portugal
a r t i c l e
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Keywords: Tagus estuary Particulate metals Flood events SPM
a b s t r a c t Particulate metal concentrations were assessed before, during and after a flood episode in the Tagus estuary. Particulate metal concentrations showed a decrease during the flood period and very similar values in the months before and after the flood event. Before this period, sampling station characteristics were verified to be homogenous during the peak of the flooding event, as all of the sampling stations assumed very specific characteristics. One of the main consequences from the flood, concurrent with a decrease in particulate metal concentrations, was the high input of SPM into the estuarine area. This finding indicates higher levels of heavy metals in fine-sized particles at low SPM concentration than those present in coarser particles at high SPM levels. These periodic flood events can be considered as estuarine contamination masks and should be interpreted as periods of dilution in heavy metal contamination rather than as an estuarine cleansing process. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Coastal ecosystems are greatly affected by human activities of environmental concern and public interest (Cohen et al., 2001). Increasing anthropogenic loads of trace elements in coastal ecosystems are one of the most significant inputs of allochthonous matter into the ocean via river discharges into the estuarine mixing zone. As a consequence of these mixing processes, estuaries are often considered to be filters of river-derived signals (Zhou et al., 1998). Several studies (Morris et al., 1986; Bewers and Yeats, 1989; Vale, 1990) describe estuaries as efficient filters of suspended particulate matter (SPM) and heavy metals (Caçador et al., 1996), primarily through particle-solute interactions, flocculation processes and the settling of metal-charged particles. In contrast, there are also inverse processes, such as the re-suspension of riverbed sediments, the desorption of metals from SPM and sediments and the diffusion processes between sediment pore water and the overlying water (Liu, 1996). As a consequence of such a complex network of mechanisms, heavy metals tend to display what is known as either conservative or non-conservative behavior, depending on the factors (physical or chemical) that affect their distribution (Liu et al., 1998; Turner et al., 1998). The metal transport mechanisms from the river to the estuary and from the estuary to the ocean depend on the links established between metals and the organic ligands present in the dissolved phase, as well as on the nature and amount of mineral and organic particles in suspension (Viers et al., 2009). Since the industrial revolution, large amounts of contaminants have been released to the ⇑ Corresponding author. Tel.: +351 21 75 00000x20319; fax: +351 21 75 00009. E-mail address: [email protected] (B. Duarte). 0025-326X/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.marpolbul.2012.07.016
atmosphere, soil and waterways. Most of these emissions will ultimately be transferred into a water matrix, either by atmospheric deposition or by soil erosion, where they will remain dissolved or will attach to sediment particles (Nriagu, 1988; Viers et al., 2009). This dynamic mechanism is greatly influenced by a river’s hydrological conditions. The Tagus estuary is one of the largest estuaries in Europe and has historically received effluents from agricultural, industrial, and urban sources. This system has been contaminated mainly by two industrial areas that are located along the northern and southern perimeters (Bettencourt, 1988; Vale, 1990; Cotté-Krieff et al., 2000; Canário et al., 2005) and by domestic effluents from the metropolitan area of Lisbon (Canário and Vale, 2007). Apart from being the site of a major seaport, the commercial and fishing activities in the estuary are adversely affected by the inflow of untreated effluents from approximately 2.5 million Greater Lisbon inhabitants, together with contaminants from the area’s industry (e.g., chemicals, petrochemicals, metallurgic industries, shipyards and cement manufacturing) and agriculture (e.g., fertilizers and pesticides). The Tagus River is frequently punctuated by flood events upstream in its drainage basin, with predictable consequences in terms of river flow and discharges into the estuary. These flood events have numerous consequences, not only by introducing abnormally high amounts of fresh water into the estuary but also by affecting the estuarine chemistry and hydrology. Because the Tagus estuary has historically been a sink for accumulated metals (Caçador et al., 1996), these extreme episodic events can greatly affect the storage capacity of the estuary in addition to temporarily modifying the chemistry of the estuary. In this study, the authors examined the effects of a flood event in the Tagus drainage basin
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on its estuary, particularly focusing on the consequences of water chemistry changes and their impact on contaminant levels and circulation in the estuarine area.
2. Material and methods 2.1. Sampling sites and sample collection The Tagus River, which is the main source of freshwater to the Tagus estuary, drains an area of 86,629 km2, representing the second most important hydrological basin in the Iberian Peninsula. Inflow fluctuates seasonally, with an average monthly value varying from 120 m3 s1 in the summer to 653 m3 s1 in winter (from the last 30 years of the Water National Institute public database, INAG). Estimated water residence times range from 6 to <65 days for winter and summer average river discharges, respectively (Vale and Sundby, 1987). Sampling was conducted during high tide to benefit from high water stability. The four sites were sampled at the surface (approximately 1 m from the water surface) to take into account the absence of stratification of the water column previously reported at these sampling sites (Gameiro et al., 2004). All the sampling sites were upstream of the Vasco da Gamma bridge (Fig. 1). Three of the sites (S1, S3 and S4) were located along a longitudinal axis, and the fourth site (S2) was located in the North Cala. The North Cala is a channel between the airfield and Alverca and the Olivais Dock, a distance of 14 km. This channel is bound on the northern side by the Tagus River and the small island of Póvoa; the channel has a low hydrodynamic characteristic, and its sediments are mainly of fluvial origin (Vale and Sundby, 1987). The location of these sites facilitated the study of the physical-chemical differ-
ences resulting from their specific longitudinal positions within the estuary. Site S1 (38°520 39.4900 N, 9°10 26.9900 W), located between the southern tip of the small island of Alhandra and the northern tip of the small island of Povoa, was the site located the furthest upstream; therefore, it was the site that was most impacted by the Tagus River. Site S2 (38°490 38.3900 N, 9°40 42.3600 W), located in the North Cala channel in front of the Lisbon Solid Waste Treatment Plant, is also the section that flows from the Trancão River and has large quantities of pollutants and suspended particulate matter (Araújo et al., 1998). Situated between the bank and the slope of the small island of Povoa was site S3 (38°490 18.4500 N, 9°30 9.6300 W). Site S4 (38°460 35.7800 N, 9°20 29.7100 W) was the furthest downstream, closest to the strait where seawater enters into the estuary. Samples were collected once a month during a three-month period in 2010 (February, March and April). February was considered to be the period before the flooding took place, March sampling occurred during the peak of the flood event and April sampling was carried out during the period of resettling after the flood event. For all of the sampling dates, the tidal amplitude was nearly constant (2.33–2.5 m). Water temperature, salinity, suspended particulate matter (SPM), and pH values were determined using the water samples. The water temperature, salinity, and pH were measured in situ using a thermometer, an ATAGO S/Mill-E refractometer, and a HI9813 pH meter (Hanna Instruments), respectively. To determine the concentration of SPM, the water samples were filtered through pre-weighed GF/C Whatman filters, which were subsequently dried at 80 °C for approximately 24 h and were then reweighed. 2.2. Hydrodynamic parameters To verify that the sample collections were taken during appropriate periods (i.e., pre-flood, flood and post-flood), the National Institute of Water database (www.snirh.pt) was consulted and the datasets corresponding to the months of February, March and April were retrieved. Hydrodynamic level was used as a proxy for river discharge to confirm the river’s hydrodynamic state (Fig. 2). 2.3. Heavy metal analysis For heavy metal analysis, the filters described above were used for SPM quantification. After accurate re-weighing, the filters were placed inside Teflon reactors with a 2 mL of solution of HNO3:HCl (3:1) and mineralized in an oven for 3 h at 110 °C (Wiese et al., 1997). After cooling, the mixture was filtered through Whatman N° 42 filters. Heavy metal concentrations were determined by Flame Atomic Absorption Spectrometry (SpectraAA 50, VARIAN). Blank filters were also subjected to the same procedure, and its metals content used to correct the metal concentration of the SPM filters. The accuracy of the results was checked by processing CRM 145 and CRM 146 reference materials. Trace metal concentrations in the reference materials determined by FAAS were not significantly different from the certified concentrations (Student’s ttest; a = 0.05). 2.4. Data processing and statistical analysis
Fig. 1. Map of Portugal with the Tagus estuary area enlarged. The sampling points are marked with numbers (Gameiro et al., 2004).
Mapping of the analysed parameters was performed using Ocean Data View 4.3.7 software using the MedHR (Mediterranean High Resolution) package to input the bathymetric, shoreline and hydrological characteristics of the study area. Spearman correlations were attained using Statasoft Inc., Statistica version 7.0 software. Resemblance and ANOSIM analyses were accomplished with PRIMER 6 software (Clarke and Gorley, 2006).
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Fig. 2. River discharge (www.snirh.pt) from February to April 2010, with black marks representing the sampling periods.
3. Results
Table 1 Water column characterization during the study period (mean ± standard deviation).
3.1. Water column characterization The period with the highest river flow in 2010 occurred between February 17th and March 17th (Fig. 2). The sampling in flood conditions took place on March 9th, with a mean river discharge of 750.74 m3/s. The sampling in the normal river flow occurred one month before and one month after this period (February 8th and April 8th, respectively), with a mean river discharge of 180.24 m3/s in pre-flood sampling and 265.53 m3/s in post-flood sampling (Fig. 2). The pH (Table 1) was relatively constant in February (mean = 8.3) and April (mean = 8.3), decreasing with salinity during the flood period (March), when it registered the lowest values (mean = 7.9). The salinity of water column (Table 1) was also lower in March (mean = 4.3) than in February (mean = 11.5) and April (mean = 13.3). The concentration of suspended matter (Table 1) in the river was highly correlated to the river’s flow, and the concentration showed an inverse relation to the pH and salinity, with higher values (mean = 47.13 mg/L) registered during the flood period (March) that decreased by 50% both before and after the flood event (February and April). 3.2. Particulate heavy metal With the exception of Cu and Cr, all heavy metals showed a similar pattern (Fig. 3). The assessed metal concentrations showed a decrease in particulate metal concentration during the flood period and in their approximated values in the months before and after the flood event. Cu exhibited exactly the opposite pattern, with an increase in the concentration of suspended particulate matter during the flood period. Cr had very similar behavior to that observed for Cu, although its behavior was not as pronounced. This result can also be observed based on the Spearman correlation coefficients (Table 2), which showed positive correlations between all metals, except when tested against Cu or Cr. There was no significant correlation between the Cu and Cr concentrations, although there were similar patterns of concentrations during the study period. The ANOSIM analysis confirmed the variation observed in the interpolation graphs. Considering the sampling period as a factor for comparison, there was a high significance (r = 0.866, p = 0.001) between the water column characteristics and the sample collection month.
River discharge (m3/s)
Salinity (PSU)
pH
SPM (mg/L)
February Site 1 Site 2 Site 3 Site 4
236.58 225.01 234.65 230.79
7.0 ± 0.00 12.5 ± 0.00 14.0 ± 0.00 12.5 ± 0.00
8.21 ± 0.00 8.04 ± 0.00 8.13 ± 0.00 8.26 ± 0.00
15.60 ± 0.40 22.47 ± 0.64 18.87 ± 5.37 16.73 ± 0.58
March Site 1 Site 2 Site 3 Site 4
899.67 864.97 888.10 878.47
5.0 ± 0.00 3.0 ± 0.00 4.0 ± 0.00 5.00 ± 0.00
7.88 ± 0.00 8.19 ± 0.00 7.82 ± 0.00 7.80 ± 0.00
47.13 ± 4.05 44.60 ± 5.56 35.73 ± 10.77 30.73 ± 1.75
April Site 1 Site 2 Site 3 Site 4
294.40 268.69 292.48 290.55
7.0 ± 0.00 16.0 ± 0.00 13.5 ± 0.00 16.5 ± 0.00
8.42 ± 0.00 8.21 ± 0.00 8. 26 ± 0.00 8. 35 ± 0.00
11.73 ± 0.95 26.07 ± 1.53 18.87 ± 0.99 23.27 ± 0.81
To understand the source of these variations, additional posthoc tests were performed. Observing the resemblance cluster (Fig. 4) and considering the sampling month, there was a clear separation observed in the two main branches (second division) of the cluster, distinguishing the samples collected during the flooding period from the samples collected before and after the flooding period. Only the sample collected at Site 3 during April (the postflood period) provided an exception to this pattern of similarity, creating the first main separation in the cluster analysis. By examining the Multi-Dimensional Scaling (MDS) plot analysis (stress factor 0.08), it was observed that not only were the flood stage samples completely separated from the pre- and post-flood samples, as observed in the resemblance cluster, but also that there were sub-groups within both groups of samples. In regard to the samples collected during the flood period, there was a noticeable separation between the sampling stations; the samples collected before and after the flood indicated a separation only between Station 2 and the remaining stations (Fig. 5). Performing a Principal Components Analysis (PCA) using principal components 1 and 2 (71% of cumulative variation), this distribution was confirmed by the environmental and physical– chemical drivers (Fig. 6). As previously observed in the interpolation maps (Fig. 3), SPM and metal concentrations drove the sample distribution in opposite directions, thus an increase in particulate
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Fig. 3. Interpolation maps of particulate heavy metal concentrations (lg/g SPM) for February, March and April as generated by the ODV software.
metal concentrations was not concomitant with an increase in SPM in the water column.
4. Discussion Metal concentrations in the Tagus estuary are largely influenced by external contributors, including industrial activities, harbor pollution and agricultural pollution (Vale et al., 1990; Vale et al., 2008; Duarte et al., 2010). Additionally, SPM may originate either inside the estuary (through shoreline erosion and re-suspension of bottom sediments) or outside the estuary and can be transported to
the inner bay via downstream river flow or from upstream by way of tidal flooding (Viers et al., 2009). During the study period of February to April 2010, the Tagus estuary experienced the effects of a flood event that occurred along the river course, leading to a large input of river water discharged into the estuary that had very different characteristics compared to the normal estuarine water. Before this period of high discharge from the river, the sampling station characteristics were very similar, making it very difficult to establish a distinction between them; however, during the peak flooding event, the stations assumed very specific characteristics (Fig. 5). This finding was most likely due to their specific location downstream and their vulnerability to the influence of
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Fig. 3 (continued)
the river discharge. This effect was most evident in the case of sampling Station 4, which was located further down in the estuary and was more greatly influenced by the sea at high tide. Additionally,
Stations 1 and 2 showed very similar characteristics due to their locations in the channel between the river margins and Povoa Island. All of these differences were amplified by the high discharge
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Table 2 Spearman correlation coefficients between the physical–chemical characteristics and the particulate heavy metal in the water column. Salinity Salinity pH SPM HL Pb Cd Cu Zn Ni Co Cr
pH
SPM
0.66 0.66** 0.46** 0.66** 0.49** 0.48** 0.67** 0.40* 0.10 0.38* 0.21
**
0.32 0.40* 0.38* 0.32 0.36* 0.24 0.01 0.37* 0.09
HL **
0.46 0.32
0.66** 0.86** 0.80** 0.42** 0.85** 0.65** 0.85** 0.04
Pb **
0.66 0.40* 0.66** 0.68** 0.69** 0.36 0.65** 0.57** 0.67** 0.29
Cd **
0.49 0.38* 0.86** 0.68** 0.93** 0.42** 0.88** 0.76** 0.93** 0.14
Cu **
0.48 0.32 0.80** 0.69** 0.93** 0.30 0.80** 0.75** 0.92** 0.19
Zn **
0.67 0.36* 0.42** 0.36* 0.42** 0.30 0.34* 0.17 0.28 0.01
Ni *
0.40 0.24 0.85** 0.65** 0.88** 0.80** 0.34*
0.10 0.01 0.65** 0.57** 0.76** 0.75** 0.17 0.73**
0.73** 0.86** 0.12
0.81** 0.14
Co
Cr *
0.38 0.37* 0.85** 0.67** 0.93** 0.92** 0.28 0.86** 0.81**
0.21 0.09 0.04 0.29 0.14 0.19 0.01 0.12 0.14 0.12
0.12
HL – hydrometric level. p < 0.05. p < 0.01).
*
**
Fig. 4. Resemblance cluster analysis of the sample collection months.
Fig. 5. MDS plot of the sampling sites grouped by period of sampling according to the ordination.
during the river’s flooding, yielding a very distinct pattern in terms of water chemistry parameters compared to those occurring under normal conditions. The river flooding differentially affected the sampling sites due to their geographic positions within the estuary. Observing the entire estuary during both a flood event and a nor-
mal period, one of the most noticeable effects of flooding was the high input of SPM into the estuarine area, although this high river input verified that the concentrations of most of the trace metals were greatly diminished. This result has been previously reported in similar studies (Benoit et al., 1994; Turner et al., 2006; Zhou
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Fig. 6. PCA diagram of the samples and correspondent variability vectors for all studied samples (sample codes stand for e.g.,: APRS23 stands for April Site 2 Replicate 3).
et al., 1998). This relationship can be explained by the relative enrichment of metals in SPM at low SPM concentrations and the depletion of metals from SPM in inverse conditions. This effect is most likely due to higher levels of heavy metals in fine-sized particles (<0.45 lm) at low SPM concentration than those present in coarser particles at high SPM levels (Zhou and Liu, 2000). The analysis of organic carbon (OC) of the colloids in previous work (Benoit et al., 1994) indicated higher amounts of OC in these small particles than in coarser particles. This effect can also be shown by the behavior observed for Cu and Cr. Both of these metals have a high affinity for organic particles because their speciation is predominantly associated with the organic fraction of sediments (Duarte et al., 2008; Reboreda and Caçador, 2007). This SPM distribution pattern was also previously observed in the Guadiana River (Caetano et al., 2006). In this work, it was verified that during a flooding event, large amounts of sand were transported downstream by the river discharge and deposited away from the mouth of the river. These sands contained a higher inorganic fraction and lower trace metal content than estuarine sediments and SPM. During the flood, two main characteristics were observed: a large input of fresh water to the entire estuarine zone (Ferreira et al., 2000) and a decrease in the residence time of the water and SPM. These conditions are not favorable to chemical alterations in the elemental composition of the SPM, either from shoreline erosion or from river transport, resulting in a homogenous spatial distribution of the SPM chemical composition. As previously confirmed by Caetano et al. (2006) in the Guadina estuary, the heavy metal concentrations in the particulate matter transported during flooding events were up to one order of magnitude lower than the SPM values in normal conditions. This difference agrees with the absence of industrial activities in the drainage basin (in this case, more than 100 km upstream of the Greater Lisbon area) and contrasts with the findings of other highly urbanized river drainage basins (Vale, 1990; Pohl et al., 2002). Thus, the flood event masked the signal of local anthropogenic sources in the estuary, which, under normal circumstances, would be detected within the SPM. Observing the significant positive correlation between heavy metal concentrations, this finding also reinforces the role of river drivers in the circulation of particulate heavy metals. This result indicates the
Table 3 Average SPM concentration (mg/L) and particulate heavy metal concentration (lg/g) in and after flood period in 19791980 and 2010. 1979–1980a
SPM Zn Cu Pb Cd Co Ni Cr a b
2010b
Normal flow
Flood
Normal flow
Flood
5.6 520 57.2 197.6 2.6 n.a. n.a. n.a.
Variable (400-40) 400 56 56 1.6 16 64 128
18.4 8689 16 157 26 41 50 15
39.5 3597 36 79 12 24 32 19
Data from Vale (1986). This study.
strong influence of river flow and physical–chemical factors as environmental drivers that affect the SPM concentrations in the water column of estuaries. These correlations also suggest that all of the heavy metals examined had the same origin, as they simultaneously varied in concentration. Vale (1986) also studied a 1979 flood event and its impact on the particulate metal concentrations in the Tagus estuary. Comparing those values with the present study, there are some differences (Table 3). Vale (1986) found an increase, although to a much higher degree, in the SPM concentration during flood conditions, which occurred simultaneously with a decrease in the particulate metal concentration. Another interesting point when comparing both periods (1979–1980 and 2010) was the observation of non-homogenous fluctuations in estuary contamination, even at normal flow conditions. Although Zn, Cd and Co had higher concentrations, as noted in the 1979– 1980 study, all the other analysed elements showed a reduction in concentration. The decrease in concentration of Cu, Pb, Ni and Cr was concomitant with the de-activation of a large number of metallurgic industrial areas along the estuarine shoreline (Caçador et al., 2009). Cobalt concentrations, however, presented some differences between both time periods (1979–1980 and 2010); these were very minor in their extent, not reaching a significant order of magnitude. As for Cd and Zn, inversely to what was recorded for
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the other metals, the present study found a significant increase in these metals. Not only do both of these metals have very similar chemistry and normally compete for the same binding sites (Marschner, 1995) but their presence in fertilizers is also well known (Eisler, 1986a,b). The increase in the concentration of these metals was concomitant with the intensification of agricultural activities throughout the Tagus basin. The findings from this work and the data put forward by Vale (1986) for the 1979 flood indicate that the environmental drivers controlling the flow of particulate heavy metals into the estuary change the SPM chemistry, thereby affecting all of the elements rather than having a metal-specific effect. 5. Conclusion Episodic river floods in the Tagus drainage basin punctuate the normal river flow and have consequences at the estuarine level. Along with all the changes in water chemistry, a primary physical event of these river floods is the transport of elevated levels of inert sand material downstream. This combination of factors that affect water chemical characteristics, along with a decrease in the estuarine water residence time, make these flood events conceal estuarine contamination and can therefore be interpreted as periods of heavy metal contamination dilution rather than an estuarine cleansing process. Acknowledgments: The authors would like to thank to the ‘‘Fundação para a Ciência e Tecnologia’’ for funding the research in the Centre of Oceanography throughout the project PEst-OE/MAR/UI0199/2011. This work was funded by VALORSUL, S.A. throughout its estuarine environmental monitoring program. The authors would also like to thank to the ECOSAM project (PTDC/AAC-CLI/104085/2008) for funding B. Duarte investigation grant. References Araújo, F., Pinheiro, T., Alves, L.C., Valério, P., Gaspar, F., Alves, J., 1998. Elemental composition in sediments and water in the Trancão river basin. A preliminary study. Nuclear Instruments and Methods in Physics Research B 136, 1005–1012. Benoit, G., Oktay-Marshall, S., Cantu II, A., Hood, E., Coleman, C., Corapcioglu, M., Santschi, P., 1994. Partitioning of Cu, Pb, Ag, Zn, Fe, Al, and Mn between filterretained particles and solution in six Texas estuaries. Marine Chemistry 45, 307–336. Bettencourt, A., 1988. On arsenic speciation in the Tagus Estuary. Netherlands Journal of Sea Research 22, 205–212. Bewers, J., Yeats, P., 1989. Transport of river-derived trace metals through the coastal zone. Netherlands Journal of Sea Research 23, 359–368. Caçador, I., Vale, C., Catarino, F., 1996. The influence of plants on concentration and fractionation of Zn, Pb, and Cu in salt marsh sediments (Tagus Estuary, Portugal). Journal of Aquatic Ecosystem Health 5, 193–198. Caçador, I., Caetano, M., Duarte, M., Vale, C., 2009. Stock and losses of trace metals from salt marsh plants. Marine Environmental Research 67, 75–82. Caetano, M., Vale, C., Falcão, M., 2006. Particulate metal distribution in Guadina estuary punctuated by flood episodes. Estuarine, Coastal and Shelf Science 70, 109–116. Canário, J., Vale, C., 2007. Monitoring program for the Tagus Estuary and tributaries, Scientific Report, IPIMAR, June 2007, p. 78. Canário, J., Vale, C., Caetano, M., 2005. Distribution of monomethylmercury and mercury in surface sediments of the Tagus Estuary (Portugal). Marine Pollution Bulletin 50, 1142–1145.
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