Environ Monit Assess (2016) 188:107 DOI 10.1007/s10661-016-5117-6
Assessment of bed sediment metal contamination in the Shadegan and Hawr Al Azim wetlands, Iran Hassan Nasirian & K. N. Irvine & Sayyed Mohammad Taghi Sadeghi & Amir Hossein Mahvi & Shahrokh Nazmara
Received: 30 September 2015 / Accepted: 12 January 2016 # Springer International Publishing Switzerland 2016
Abstract The Shadegan and Hawr Al Azim wetlands are important natural resources in southwestern Iran, yet relatively little work has been done to assess ecosystem health of the wetlands. Bed sediment from both wetlands was sampled in individual months between October, 2011 and December, 2012 and analyzed for As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Pb, and Zn using inductively coupled plasma optical emission spectrometry (ICP-OES). The metals data were evaluated using a combination of sediment quality guidelines from the Ontario Ministry of Energy and Environment (MOEE, Canada), enrichment factors (EFs), and a geoaccumulation index (Igeo) approach. The sediments exceeded MOEE Lowest Effect Levels (LELs) consistently for Cr and Cu and a small proportion of samples (5 %) for Hg. Levels of As, Cd, Fe, Pb, and Zn did not H. Nasirian (*) : S. M. T. Sadeghi Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran e-mail: [email protected] K. N. Irvine National Institute of Education, Nanyang Technological University, Singapore, Singapore A. H. Mahvi : S. Nazmara Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran A. H. Mahvi Center for Solid Waste Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
exceed LELs and none of the samples exceeded the Severe Effect Levels (SELs). In addition to the sediment guidelines, both the EF and Igeo calculations suggested levels of Mn and Fe were severely enriched, while the EF indicated Cd was slightly enriched. Metal levels in the Shadegan wetland exhibited both spatial and seasonal trends. Metal levels were greater near input areas from agricultural, urban, and industrial discharges and runoff as compared to the more remote and quiescent central part of the wetland. Except for Fe, the metal levels were greater in the wet season as compared to the dry season, perhaps due to greater stormwater runoff and sediment loads. This study provides baseline data which can be used to support development of appropriate contaminant source management strategies to help ensure conservation of these valuable wetland resources. Keywords Assessment . Contamination . Metal . Bed sediment . Wetland . Shadegan . Hawr Al Azim
Introduction Wetlands provide a variety of ecosystem and economic services including enhanced biodiversity, peri-urban agricultural and aquaculture production, hunting opportunities, hydrologic regulation (both flood and drought protection), erosion control, water treatment, carbon sequestration, personal and community well-being and security, transportation, and recreation (Tiner, 1984; Bergstrom et al., 1990; Barbier, 1994; Ghosh, 1999;
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2014; Mitsch and Gosselink, 2000; Zedler and Kercher, 2005; Brauman et al., 2007; Irvine et al., 2008; Visoth et al., 2010; Turner et al., 2011). For the entire global biosphere, Costanza et al. (1997) concluded the value of ecosystem services averaged USD$33 trillion per year (1994 dollars), of which $6.5 trillion was ascribed to wetlands, tidal marshes, and mangroves. In comparison, the global GNP was around USD$18 trillion per year in 1994. The USA has recognized the value of wetlands through its no net loss of wetland policy under the Clean Water Act (La Peyre et al., 2001; Boyd and Wainger, 2002). Globally, the Ramsar Convention, Ban intergovernmental treaty that provides the framework for national action and international cooperation for the conservation and wise use of wetlands and their resources^ (http://www.ramsar.org/), was first ratified in 1971 and currently has 168 contracting parties representing 2208 sites with a total area of 211 million ha. The contracting parties agree to develop and maintain these wetlands as a policy of preservation. Despite the apparent value of wetlands (and recent programs to preserve them), some estimates suggest the world has lost approximately 50 % of its wetlands due to human activities since the early 1900s (Zedler and Kercher, 2005; Davidson, 2014). One of the functions that frequently is identified as a beneficial ecosystem service, the ability to filter contaminants and purify water, also can lead to wetland degradation when the system is overloaded by anthropogenic inputs (Booth and Reinelt, 1993; Brinson and Malvarez, 2002; Lopez-Flores et al., 2003; Faulkner, 2004; Lee et al., 2006; Boone et al., 2007; Nabulo et al., 2008). Given the challenges that human activities present to the preservation and management of wetlands, it is important to develop monitoring and assessment programs to identify baseline conditions and track changes in environmental quality over time. Unfortunately, in many areas of Asia, programs to conduct such monitoring are not in place. One approach to assessing wetland ecosystem health is through the analysis of bed sediment as they are an integral part of metal cycling in the aquatic environment and can provide vital information on the sources, distribution, and potential degree of pollution (HudsonEdwards et al. 2001; Liu et al. 2008; Jain et al. 2008; N’Guessan et al. 2009). In the USA, concern about contaminated sediment in the Great Lakes Areas of Concern (AOCs) led to the development of the Assessment and Remediation of Contaminated Sediment (ARCS) program in the early 1990s. This 5-
year program conducted under the auspice of the US EPA’s Great Lakes National Program Office had the mandate to study ecosystem impacts, control, and removal of contaminated bed sediment from the AOCs (Ross et al., 1992; Irvine et al., 2003; Hartig, 2010). In Iran, studies have been conducted on different aspects of environmental contamination by metals (Diagomanolin et al., 2004; Bigdeli and Seilsepour, 2008; Jalali and Khanlari, 2008; Saeedi et al., 2009; Esfandbod et al., 2011; Nasirian, 2013), but relatively few studies have examined metal levels in wetland sediments (e.g., Farrokhian et al., 1997; Hosseini Alhashemi et al., 2012). The objective of this study, then, is to examine contamination of bed sediment by arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), manganese (Mn), lead (Pb), and zinc (Zn) in the Shadegan and Hawr Al Hawizea (or Hawr Al Azim) wetlands in Khuzistan Province, southwestern Iran. The metal levels were assessed in comparison to sediment quality guidelines, but in addition, two different indices of sediment contamination were calculated and compared: the enrichment factor (EF) and the geo-accumulation index (Igeo).
Materials and methods Study sites This study was carried out in two wetlands, the Shadegan and Hawr Al Hawizea or Hawr Al Azim, located in Khuzistan Province, southwestern Iran (Fig. 1). The climate of this region is a desert (BWh) to semi-arid (BSh) type, based on the Koppen classification system. Ahvaz, the capital and largest city of the province (population approximately 1.3 million in 2011, http://english.ahvaz. ir/Default.aspx?tabid=2434), experienced an annual mean rainfall of 209.2 mm and annual mean temperature of 25.4 °C for the period 1951–2010 (http://www.chaharmahalmet.ir/stat/archive/iran/khz/ AHWAZ/5.asp; http://www.chaharmahalmet.ir/stat/ archive/iran/khz/AHWAZ/25.asp). Shadegan wetland The Shadegan wetland (Fig. 2), located 40 km south of Ahvaz, is the largest wetland in Iran covering an area of 537,700 ha. The wetland was registered as a Ramsar Site in 1975. The delta of the Marun River forms the
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Fig. 1 Location of the study wetlands (black circle); Hawr Al Azim is the northwest site and Shadegan is the southeast site
eastern, crescent-shaped boundary of the wetland and is clearly visible in Fig. 2. The wetland is bounded to the west by the natural levee system created by the Karun River, which is the largest river in Iran. Monthly mean flow rate (1965–1984) is highest on the Karun River in April, averaging 853 m3 s−1, and lowest in October, averaging 279 m3 s−1 (http://www.iranicaonline.org/ articles/karun_1_2). Meijerink et al. (2005) examined the wetland’s water balance using remote sensing techniques because they noted the difficulty of obtaining quality-assured, in situ, hydrologic data. They found that in wet years, the wetland is fully inundated and water drains to the tidal area in the south, while in dry years, the wetland is only partly inundated and it becomes a terminal basin (Nasirian, 2013; 2014). Water depth in the wetland during wet years typically ranges between 0.5 and 1.5 m, although some deeper pools and channels may have depths of up to 3 m, while in dry years, the depth normally is less than 0.8 m. Kaffashi et al. (2011) noted that 110 plant species have been identified, making Shadegan one of Iran’s most diverse wetlands, while Nasirian (2013) found that
although diverse, the wetland is covered mainly by Echinochloa crus-galli (Poaceae), and secondly by Phragmites communis (Poaceae), Typha latifolia (Typhaceae), and Carex brunnra (Cyperaceae) (Fig. 3). Kaffashi et al. (2011) also reported the wetland to be habitat for 40 species of mammals, 3 species of amphibians, 8 species of reptiles, 90 species of fish, and 174 species of birds. The wetland is a particularly important wintering habitat for migratory birds, and 13 species of globally threatened birds have been observed here. In a study conducted to monetize the socioeconomic value of the wetland, Kaffashi et al. (2011) reported 90 villages and more than 400,000 households around the wetland were highly dependent on its resources and 300 households were located directly inside the wetlands. Services provided by the wetland included commercial fishing; vegetation for livestock grazing; reeds for handicrafts, fencing, and roof covering; and hunting (mostly birds). Meijerink et al. (2005) also noted that crops of vegetables, cereals, and small orchards (fruits and date palms) are found within the wetland area. The area between Ahvaz and the wetland is extensively irrigated
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Fig. 2 Satellite image of the Hawr Al Azim and Shadegan wetlands. The bed sediment sample area for the Hawr Al Azim wetland is enclosed by the red circle
using water extracted primarily from the Karun River (Fig. 2), although return flow and discharges from the agriculture land do reach the wetland. Crops grown in Fig. 3 Shadegan wetland showing a mix of open water and Echinochloa crus-galli (Poaceae)
this area mainly are sugarcane and date palms, with some wheat, watermelon, and corn. Karimi et al. (2012) analyzed samples of water, phytoplankton,
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zooplankton, benthic macroinvertebrates, insects, and fish, for pesticides collected at five locations in the wetland, and found elevated ecological risk quotients for some macroinvertebrate and fish species. Pesticides posing the greatest risk appeared to be DDT and lindane, although aldrin and dieldrin also approached the highrisk categories for some samples. The presence of the pesticides was attributed to agricultural runoff and agricultural wastewater discharges (Karimi et al., 2012). Other sources of organic contaminants and metals to the wetland include landfill leachate, highway traffic and municipal truck and bus terminals, a petrochemical company that has constructed a facility within the Ramsar-designated area, steel-related industries, oil pipeline leakage, some municipal wastewater sourced at Ahvaz that is discharged to the Karun River initially, wastewater discharges from the city of Shadegan, and military waste from the Iran–Iraq war, 1980–1988 (Kaffashi et al., 2011; Karimi et al., 2012; Hosseini Alhashemi et al., 2012; Nasirian, 2013).
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the water supply of the Hawr Al Azim wetland is mainly through the Karkheh River which has a total catchment area of about 50,700 km2 (Hessari et al., 2012). There appears to be relatively less published research about the Hawr Al Azim wetland as compared to the Shadegan wetland, perhaps because it is more remote in general, or perhaps because of isolation as the result of the Iran–Iraq war. Initially during the war, an embankment road was constructed, with no culverts, which effectively bisected the wetland (Mirzaei et al., 2010). Other road and dyke systems subsequently were constructed through the wetlands, draining portions and fragmenting the ecosystem. The water depth is about 0.1–0.2 m on the Iranian side, and the surface is covered mainly by P. communis (Poaceae) (Nasirian, 2013; Fig. 4). Like the Shadegan wetland, Hawr Al Azim is a habitat for migratory birds and also provides agricultural, fishing, and hunting opportunities for the local population. However, to our knowledge, this is the first study to document sediment quality in the Hawr Al Azim wetland and there is little quantitative information on contaminant sources.
Hawr Al Azim Wetland The Hawr Al Azim wetland is part of the Mesopotamian marshland system, the largest such ecosystem in Southwest Asia. Located mostly in southern Iraq, Partow (2001) estimated that the Mesopotamian marshland covered an area of 15,000–20,000 km2 in 1970, being fed by the waters of the Tigris and Euphrates rivers (Fig. 1). Based on satellite image analysis, by 2000, the surface area of the Mesopotamian marshland was only 14.5 % of its 1973–1976 area, which negatively impacted habitat and the traditional Arab communities that have occupied the region in relative isolation for more than 5000 years (Partow, 2001). More recently, Richardson (2010) reported that in 2003, local farmers and government ministries began to remove dikes and earthen dams, thereby releasing water back into the former marsh areas, and by 2008, 55 % of the original marsh was reflooded or was covered by marsh vegetation, based on UNEP satellite analysis. However, fragmentation of the ecosystem remains a barrier to full recovery. The Hawr Al Azim wetland (Fig. 2) straddles the border of Iran and Iraq, being 80 km west of Ahvaz. Partow (2001) noted that the wetland has been relatively less impacted by drainage works as compared to the larger marshland, but nonetheless its area decreased by 2000 km2 between 1973–1976 and 2000. The Iraqi side of the wetland was designated a Ramsar site in 2008. In Iran,
Bed sediment sample sites and sample collection Samples were collected from five different sites in the Shadegan wetland and in a wide area of the Hawr Al Azim wetland (Figs. 2 and 5). Specifically for the Shadegan wetland (Fig. 5), the sample locations can be characterized as follows: 1. SW1: Water canal entrance to the Shadegan wetland between Darkhovien City and wetland kilometer 15 along the Shadegan-Darkhovien Road where waste output from the sugarcane fields and factories is discharged into the wetland. 2. SW2: Middle of Shadegan wetland which is an area that is isolated from the other parts of the wetland. The volume of incoming water is restricted and the rate of evaporation is high. 3. SW3: Western side of the Shadegan wetland at kilometer 5 along the Shadegan-Darkhovien Road. Ragbeh and Sarakhieh villages and tourism area and livestock wastewaters are released into the wetland in this area. 4. SW4: North section of Shadegan wetland where a waste discharge canal from the sugarcane fields and factories is located, about kilometer 40 of the Ahvaz-Abadan Road.
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Fig. 4 Dense stands of phragmites in the Hawr Al Azim wetland
5. SW5: Near the Shadegan City wastewater outfall as it discharges to the eastern part of the wetland. Industrial and urban wastewaters are released into the wetland in this area.
Samples were collected from the middle area of the Hawr Al Azim wetland (Fig. 2). This area is relatively unaffected by human activity (Nasirian, 2014; Fig. 4).
Fig. 5 Sample site locations in the Shadegan wetland. Black arrows indicate locations of important inflow areas to the wetland, where the arrow in the north represents a canal draining sugarcane fields and factories and impacting SW4, the arrow near the middle of the wetland represents a canal also draining sugarcane fields and
factories and impacting SW1, and the bottom two arrows represent canal discharges that include Shadegan City wastewater as well as industrial effluent, impacting SW5. The red circle indicates the general area of Ragbeh and Sarakhieh villages
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At each of the five sites in the Shadegan wetland and within the broad general area of the Hawr Al Azim wetland, sediment was collected from ten subsites. All sites in the two wetlands were inundated by water during sample collection, with depths ranging from approximately 0.2 to 1 m. Samples were collected as simple grabs that were gently removed to minimize loss of fine sediment. The samples from the ten subsites were then mixed using an acid-washed (10 % nitric acid) watchglass and stored in 50-ml acid-washed (10 % nitric acid) polypropylene tubes. The samples were maintained at 0 °C and transported to the laboratory in Tehran. Sampling was done at each site in the months of October and December, 2011, and March, April, June, July, and September, 2012. Sample preparation The bed sediment samples were oven-dried at 60 °C for 24 h to prevent the loss of possible volatile metallic compounds and to facilitate sample grinding (mortar and pestle) and sieving. Digestion and analyte extraction for inductively coupled plasma optical emission spectrometry (ICP-OES) analysis were done using an acid mixture procedure (Creed et al. 1994). One gram of each sediment sample was precisely measured and delivered into a 50-ml glass beaker, and then 4 ml of HNO3 (HNO3 1 part + DDI water 1 part) and 10 ml of HCl (HCl 1 part + DDI water 4 part) were subjoined and the solution was lidded with a watch glass. The beaker was then put on a hotplate for extraction of the metals at an adjusted reflux temperature of 95 °C. The sample was warmed for 2 h while avoiding vigorous boiling of the solution (although very slight boiling could be tolerated) under a fume hood. The solution was then decreased to 10 ml by boiling, followed by cooling. The cooled solutions were transited through a 0.2-μm membrane filter into polyethylene bottles and diluted with DDI water to various volumes within the linear range of the inductively coupled plasma (ICP) instrumentation for analysis. Samples were analyzed immediately to minimize the effect of the various matrices on the stability of the diluted samples. All glassware and equipment were precleaned with 10 % nitric acid and then rinsed with high-purity DDI water before and after each grinding and digestion process to avoid cross-contamination of samples and biasing of the results.
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ICP-OES metal analysis Samples were analyzed for arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), manganese (Mn), lead (Pb), and zinc (Zn) using ICP-OES (Germany SPECTRO Company, Spectro ARCOS Model) following US EPA Method 200.7 and also as described by Nasirian et al. (2014). For instrument calibration, we used Trace CERT® FLUKA analytical BMultielement standard solution 4 for ICP^ (catalogue no. 51844, Lot & Pcod: BCBC8119 100976806) for all elements except Hg (Certipur® ICP standard of Hg, Order no. 1.70333.0100, Hg (NO3)2 in HNO3 10 %) in which we made serial dilutions that were measured by the same ICP unit. The calibration standards were run immediately prior to each round of sample analysis. Method blanks also were run at the beginning and end of reach round of sample analysis. Bed sediment contamination levels of investigated metals The level of bed sediment contamination was assessed using three approaches: i) comparison with sediment quality standards from the Ontario Ministry of Energy and Environment Ministry of Environment and Energy (MOEE) (1993), (ii) an enrichment factor (EF), and (iii) the geo-accumulation index (Igeo). The MOEE guidelines are based on the potential impact to sedimentdwelling organisms, where the Lowest Effect Level (LEL) indicates a level of contamination below which there is no effect on the majority of such organisms (i.e., it is clean to marginally polluted) and the Severe Effect Level (SEL) indicates heavily polluted sediment. The MOEE guidelines were used here because the LEL levels tend to be lower than the consensus-based guidelines often used by agencies in the USA (cf., MacDonald et al., 2000). Enrichment factors have long been used worldwide to evaluate the level of sediment contamination as well as identify the potential source of the contamination (Solomons and Forstner, 1984; Vermette et al., 1987; Irvine et al., 1989; Morillo et al. 2004; Selvaraj et al. 2004; Adamo et al. 2005; Vald’es et al. 2005; Chen et al., 2007; Abrahim and Parker, 2008; Sekabira et al., 2010). The EF approach normalizes the metal level to a common element which is compared to the typical level found either in the Earth’s crust or in shale (i.e., the
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background or natural level, Cevik et al., 2009; Devesa-Rey et al., 2011). The EF is calculated as E F ¼ ðM = M Reference Þ sample = ðM = M Reference ÞBackground
where M⁄MReference is the ratio of the metal (M) to the normalizing reference metal found in the sediment sample and (M/MReference)Background is the ratio of the metal to the normalizing reference metal found in the Earth’s crust or in shale. The most commonly used normalizing reference metals are aluminum (Al) or iron (Fe) because of their abundance in nature and the general lack of anthropogenic source enrichment (Chen et al., 2007; Zhang et al., 2007; Karageorgis et al., 2009 Sekabira et al., 2010). Although less common, others also have used gallium (Ga), rubidium (Rb), strontium (Sr), niobium (Nb), zicronium (Zr), scandium (Sc), and titanium (Ti) as the reference metal (Devesa-Rey et al., 2011; Uduma and Jimoh 2014). While the EF approach seems quite straightforward, in fact there is considerable debate on what to use as the background reference (typical crustal value, typical value for shale, local soils, or sediments from an uncontaminated site) and what to use as the normalizing metal. Some have suggested that the EF is not sensitive to the choice of background reference and normalizing metal, while others have found interpretation of results can be affected by the background reference and normalizing metal (Rubio et al., 2000; Abrahim and Parker, 2008; Devesa-Rey et al., 2011). In this study, EF values for the investigated metals were calculated using baseline values of the average upper continental crust (Taylor and McLennan, 1985; Taylor and McLennan, 1995; Rudnick and Gao, 2003). There seems to be general agreement that an EF ≤ 1 represents no enrichment, EF < 3 is minor enrichment, EF = 3–5 is moderate enrichment, EF = 5–10 is moderately severe enrichment, EF = 10–25 is severe enrichment, EF = 25–50 is very severe enrichment, and EF > 50 is extremely severe enrichment (Birth, 2003; Chen et al., 2007; Cevik et al., 2009). The Igeo index also is commonly used to assess metal pollution (Muller, 1979; Rubio et al. 2000; Ghrefat and Yusuf, 2006; Zhang et al., 2007; Praveena et al. 2008; Abrahim and Parker 2008) and can be calculated as I geo ¼ log2 ðC n =ð1:5 Bn ÞÞ where Cn is the measured concentration of the investigated metal in the environment, Bn is the soil (or shale)
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geochemical background value, and 1.5 is the background matrix correction factor due to lithogenic effects (Cevik et al., 2009). In this study, data from Taylor and McLennan (1985), Taylor and McLennan (1995), and Rudnick and Gao (2003) were used to define Bn. Igeo values are categorized as uncontaminated (Igeo ≤ 0), uncontaminated to moderately contaminated (0 < Igeo ≤ 1), moderately contaminated (1 < Igeo ≤ 2), moderately to heavily contaminated (2 < Igeo ≤ 3), heavily contaminated (3 < Igeo ≤ 4), heavily to extremely contaminated (4 < Igeo ≤ 5), and extremely contaminated (Igeo ≥ 5) (Muller, 1979). Statistical analysis All data were maintained in Excel spreadsheet format, and Excel was used to calculate summary statistics, the EF, and Igeo factors. Excel also was used to conduct Ftests to determine if the sample variances could be considered equal or not, thereby identifying the appropriate form of the t test to be used (pooled or nonpooled). The data were assumed to be approximately normally distributed, although Mendenhall (1979) noted that if a distribution has a mound shape, t tests are not especially sensitive to the normality assumption.
Results and discussion Bed sediment metal concentrations and analyses Table 1 shows values and means (μg/g, per dry mass of sediment) of the investigated metals in the bed sediment samples from the Shadegan and Hawr Al Azim wetlands, October 2011 to September 2012. Instrumental detection limit and the MOEE LEL and SEL values also are shown at the bottom of Table 1. The Cr and Cu levels of more than half of all samples reported in Table 1 exceeded the MOEE LEL level, and 5 % (2 of 42) of the samples exceeded the MOEE LEL for Hg. No sample exceeded MOEE SEL levels. Based on MOEE guidelines for protection of benthic organisms, the elements of some concern are Cr and Cu and, possibly, Hg. The data in Table 1 also suggest there may be both spatial and temporal trends in the metal levels. For the Shadegan wetland, site SW2 might be considered a relatively unimpacted control site since it is located in a central area of the wetland, distant from source inputs. Site SW 5 is impacted by urban and industrial
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Table 1 Concentrations of investigated metals (μg/g, per dry mass of sediment) in the bed sediment from the Shadegan and Hawr Al Azim wetlands (2011–2012) Site Month
SW1 October December March April June July September SW2 October December March April June July September SW3 October December March April June July September SW4 October December March April June July September SW5 October December March April June July September HH December March April June July September Mean (Std. deviation) IDL MOEE LEL MOEE SEL
Metal As
Cd
Coa
Cr
Cu
Fe
Hg
Mn
Pb
Zn
2.12 2.26 2.79 1.78 2.92 0.58 1.61 1.45 0.83 1.58 0.52 1.32
Assessment of bed sediment metal contamination in the Shadegan and Hawr Al Azim wetlands, Iran Hassan Nasirian & K. N. Irvine & Sayyed Mohammad Taghi Sadeghi & Amir Hossein Mahvi & Shahrokh Nazmara
Received: 30 September 2015 / Accepted: 12 January 2016 # Springer International Publishing Switzerland 2016
Abstract The Shadegan and Hawr Al Azim wetlands are important natural resources in southwestern Iran, yet relatively little work has been done to assess ecosystem health of the wetlands. Bed sediment from both wetlands was sampled in individual months between October, 2011 and December, 2012 and analyzed for As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Pb, and Zn using inductively coupled plasma optical emission spectrometry (ICP-OES). The metals data were evaluated using a combination of sediment quality guidelines from the Ontario Ministry of Energy and Environment (MOEE, Canada), enrichment factors (EFs), and a geoaccumulation index (Igeo) approach. The sediments exceeded MOEE Lowest Effect Levels (LELs) consistently for Cr and Cu and a small proportion of samples (5 %) for Hg. Levels of As, Cd, Fe, Pb, and Zn did not H. Nasirian (*) : S. M. T. Sadeghi Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran e-mail: [email protected] K. N. Irvine National Institute of Education, Nanyang Technological University, Singapore, Singapore A. H. Mahvi : S. Nazmara Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran A. H. Mahvi Center for Solid Waste Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
exceed LELs and none of the samples exceeded the Severe Effect Levels (SELs). In addition to the sediment guidelines, both the EF and Igeo calculations suggested levels of Mn and Fe were severely enriched, while the EF indicated Cd was slightly enriched. Metal levels in the Shadegan wetland exhibited both spatial and seasonal trends. Metal levels were greater near input areas from agricultural, urban, and industrial discharges and runoff as compared to the more remote and quiescent central part of the wetland. Except for Fe, the metal levels were greater in the wet season as compared to the dry season, perhaps due to greater stormwater runoff and sediment loads. This study provides baseline data which can be used to support development of appropriate contaminant source management strategies to help ensure conservation of these valuable wetland resources. Keywords Assessment . Contamination . Metal . Bed sediment . Wetland . Shadegan . Hawr Al Azim
Introduction Wetlands provide a variety of ecosystem and economic services including enhanced biodiversity, peri-urban agricultural and aquaculture production, hunting opportunities, hydrologic regulation (both flood and drought protection), erosion control, water treatment, carbon sequestration, personal and community well-being and security, transportation, and recreation (Tiner, 1984; Bergstrom et al., 1990; Barbier, 1994; Ghosh, 1999;
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2014; Mitsch and Gosselink, 2000; Zedler and Kercher, 2005; Brauman et al., 2007; Irvine et al., 2008; Visoth et al., 2010; Turner et al., 2011). For the entire global biosphere, Costanza et al. (1997) concluded the value of ecosystem services averaged USD$33 trillion per year (1994 dollars), of which $6.5 trillion was ascribed to wetlands, tidal marshes, and mangroves. In comparison, the global GNP was around USD$18 trillion per year in 1994. The USA has recognized the value of wetlands through its no net loss of wetland policy under the Clean Water Act (La Peyre et al., 2001; Boyd and Wainger, 2002). Globally, the Ramsar Convention, Ban intergovernmental treaty that provides the framework for national action and international cooperation for the conservation and wise use of wetlands and their resources^ (http://www.ramsar.org/), was first ratified in 1971 and currently has 168 contracting parties representing 2208 sites with a total area of 211 million ha. The contracting parties agree to develop and maintain these wetlands as a policy of preservation. Despite the apparent value of wetlands (and recent programs to preserve them), some estimates suggest the world has lost approximately 50 % of its wetlands due to human activities since the early 1900s (Zedler and Kercher, 2005; Davidson, 2014). One of the functions that frequently is identified as a beneficial ecosystem service, the ability to filter contaminants and purify water, also can lead to wetland degradation when the system is overloaded by anthropogenic inputs (Booth and Reinelt, 1993; Brinson and Malvarez, 2002; Lopez-Flores et al., 2003; Faulkner, 2004; Lee et al., 2006; Boone et al., 2007; Nabulo et al., 2008). Given the challenges that human activities present to the preservation and management of wetlands, it is important to develop monitoring and assessment programs to identify baseline conditions and track changes in environmental quality over time. Unfortunately, in many areas of Asia, programs to conduct such monitoring are not in place. One approach to assessing wetland ecosystem health is through the analysis of bed sediment as they are an integral part of metal cycling in the aquatic environment and can provide vital information on the sources, distribution, and potential degree of pollution (HudsonEdwards et al. 2001; Liu et al. 2008; Jain et al. 2008; N’Guessan et al. 2009). In the USA, concern about contaminated sediment in the Great Lakes Areas of Concern (AOCs) led to the development of the Assessment and Remediation of Contaminated Sediment (ARCS) program in the early 1990s. This 5-
year program conducted under the auspice of the US EPA’s Great Lakes National Program Office had the mandate to study ecosystem impacts, control, and removal of contaminated bed sediment from the AOCs (Ross et al., 1992; Irvine et al., 2003; Hartig, 2010). In Iran, studies have been conducted on different aspects of environmental contamination by metals (Diagomanolin et al., 2004; Bigdeli and Seilsepour, 2008; Jalali and Khanlari, 2008; Saeedi et al., 2009; Esfandbod et al., 2011; Nasirian, 2013), but relatively few studies have examined metal levels in wetland sediments (e.g., Farrokhian et al., 1997; Hosseini Alhashemi et al., 2012). The objective of this study, then, is to examine contamination of bed sediment by arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), manganese (Mn), lead (Pb), and zinc (Zn) in the Shadegan and Hawr Al Hawizea (or Hawr Al Azim) wetlands in Khuzistan Province, southwestern Iran. The metal levels were assessed in comparison to sediment quality guidelines, but in addition, two different indices of sediment contamination were calculated and compared: the enrichment factor (EF) and the geo-accumulation index (Igeo).
Materials and methods Study sites This study was carried out in two wetlands, the Shadegan and Hawr Al Hawizea or Hawr Al Azim, located in Khuzistan Province, southwestern Iran (Fig. 1). The climate of this region is a desert (BWh) to semi-arid (BSh) type, based on the Koppen classification system. Ahvaz, the capital and largest city of the province (population approximately 1.3 million in 2011, http://english.ahvaz. ir/Default.aspx?tabid=2434), experienced an annual mean rainfall of 209.2 mm and annual mean temperature of 25.4 °C for the period 1951–2010 (http://www.chaharmahalmet.ir/stat/archive/iran/khz/ AHWAZ/5.asp; http://www.chaharmahalmet.ir/stat/ archive/iran/khz/AHWAZ/25.asp). Shadegan wetland The Shadegan wetland (Fig. 2), located 40 km south of Ahvaz, is the largest wetland in Iran covering an area of 537,700 ha. The wetland was registered as a Ramsar Site in 1975. The delta of the Marun River forms the
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Fig. 1 Location of the study wetlands (black circle); Hawr Al Azim is the northwest site and Shadegan is the southeast site
eastern, crescent-shaped boundary of the wetland and is clearly visible in Fig. 2. The wetland is bounded to the west by the natural levee system created by the Karun River, which is the largest river in Iran. Monthly mean flow rate (1965–1984) is highest on the Karun River in April, averaging 853 m3 s−1, and lowest in October, averaging 279 m3 s−1 (http://www.iranicaonline.org/ articles/karun_1_2). Meijerink et al. (2005) examined the wetland’s water balance using remote sensing techniques because they noted the difficulty of obtaining quality-assured, in situ, hydrologic data. They found that in wet years, the wetland is fully inundated and water drains to the tidal area in the south, while in dry years, the wetland is only partly inundated and it becomes a terminal basin (Nasirian, 2013; 2014). Water depth in the wetland during wet years typically ranges between 0.5 and 1.5 m, although some deeper pools and channels may have depths of up to 3 m, while in dry years, the depth normally is less than 0.8 m. Kaffashi et al. (2011) noted that 110 plant species have been identified, making Shadegan one of Iran’s most diverse wetlands, while Nasirian (2013) found that
although diverse, the wetland is covered mainly by Echinochloa crus-galli (Poaceae), and secondly by Phragmites communis (Poaceae), Typha latifolia (Typhaceae), and Carex brunnra (Cyperaceae) (Fig. 3). Kaffashi et al. (2011) also reported the wetland to be habitat for 40 species of mammals, 3 species of amphibians, 8 species of reptiles, 90 species of fish, and 174 species of birds. The wetland is a particularly important wintering habitat for migratory birds, and 13 species of globally threatened birds have been observed here. In a study conducted to monetize the socioeconomic value of the wetland, Kaffashi et al. (2011) reported 90 villages and more than 400,000 households around the wetland were highly dependent on its resources and 300 households were located directly inside the wetlands. Services provided by the wetland included commercial fishing; vegetation for livestock grazing; reeds for handicrafts, fencing, and roof covering; and hunting (mostly birds). Meijerink et al. (2005) also noted that crops of vegetables, cereals, and small orchards (fruits and date palms) are found within the wetland area. The area between Ahvaz and the wetland is extensively irrigated
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Fig. 2 Satellite image of the Hawr Al Azim and Shadegan wetlands. The bed sediment sample area for the Hawr Al Azim wetland is enclosed by the red circle
using water extracted primarily from the Karun River (Fig. 2), although return flow and discharges from the agriculture land do reach the wetland. Crops grown in Fig. 3 Shadegan wetland showing a mix of open water and Echinochloa crus-galli (Poaceae)
this area mainly are sugarcane and date palms, with some wheat, watermelon, and corn. Karimi et al. (2012) analyzed samples of water, phytoplankton,
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zooplankton, benthic macroinvertebrates, insects, and fish, for pesticides collected at five locations in the wetland, and found elevated ecological risk quotients for some macroinvertebrate and fish species. Pesticides posing the greatest risk appeared to be DDT and lindane, although aldrin and dieldrin also approached the highrisk categories for some samples. The presence of the pesticides was attributed to agricultural runoff and agricultural wastewater discharges (Karimi et al., 2012). Other sources of organic contaminants and metals to the wetland include landfill leachate, highway traffic and municipal truck and bus terminals, a petrochemical company that has constructed a facility within the Ramsar-designated area, steel-related industries, oil pipeline leakage, some municipal wastewater sourced at Ahvaz that is discharged to the Karun River initially, wastewater discharges from the city of Shadegan, and military waste from the Iran–Iraq war, 1980–1988 (Kaffashi et al., 2011; Karimi et al., 2012; Hosseini Alhashemi et al., 2012; Nasirian, 2013).
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the water supply of the Hawr Al Azim wetland is mainly through the Karkheh River which has a total catchment area of about 50,700 km2 (Hessari et al., 2012). There appears to be relatively less published research about the Hawr Al Azim wetland as compared to the Shadegan wetland, perhaps because it is more remote in general, or perhaps because of isolation as the result of the Iran–Iraq war. Initially during the war, an embankment road was constructed, with no culverts, which effectively bisected the wetland (Mirzaei et al., 2010). Other road and dyke systems subsequently were constructed through the wetlands, draining portions and fragmenting the ecosystem. The water depth is about 0.1–0.2 m on the Iranian side, and the surface is covered mainly by P. communis (Poaceae) (Nasirian, 2013; Fig. 4). Like the Shadegan wetland, Hawr Al Azim is a habitat for migratory birds and also provides agricultural, fishing, and hunting opportunities for the local population. However, to our knowledge, this is the first study to document sediment quality in the Hawr Al Azim wetland and there is little quantitative information on contaminant sources.
Hawr Al Azim Wetland The Hawr Al Azim wetland is part of the Mesopotamian marshland system, the largest such ecosystem in Southwest Asia. Located mostly in southern Iraq, Partow (2001) estimated that the Mesopotamian marshland covered an area of 15,000–20,000 km2 in 1970, being fed by the waters of the Tigris and Euphrates rivers (Fig. 1). Based on satellite image analysis, by 2000, the surface area of the Mesopotamian marshland was only 14.5 % of its 1973–1976 area, which negatively impacted habitat and the traditional Arab communities that have occupied the region in relative isolation for more than 5000 years (Partow, 2001). More recently, Richardson (2010) reported that in 2003, local farmers and government ministries began to remove dikes and earthen dams, thereby releasing water back into the former marsh areas, and by 2008, 55 % of the original marsh was reflooded or was covered by marsh vegetation, based on UNEP satellite analysis. However, fragmentation of the ecosystem remains a barrier to full recovery. The Hawr Al Azim wetland (Fig. 2) straddles the border of Iran and Iraq, being 80 km west of Ahvaz. Partow (2001) noted that the wetland has been relatively less impacted by drainage works as compared to the larger marshland, but nonetheless its area decreased by 2000 km2 between 1973–1976 and 2000. The Iraqi side of the wetland was designated a Ramsar site in 2008. In Iran,
Bed sediment sample sites and sample collection Samples were collected from five different sites in the Shadegan wetland and in a wide area of the Hawr Al Azim wetland (Figs. 2 and 5). Specifically for the Shadegan wetland (Fig. 5), the sample locations can be characterized as follows: 1. SW1: Water canal entrance to the Shadegan wetland between Darkhovien City and wetland kilometer 15 along the Shadegan-Darkhovien Road where waste output from the sugarcane fields and factories is discharged into the wetland. 2. SW2: Middle of Shadegan wetland which is an area that is isolated from the other parts of the wetland. The volume of incoming water is restricted and the rate of evaporation is high. 3. SW3: Western side of the Shadegan wetland at kilometer 5 along the Shadegan-Darkhovien Road. Ragbeh and Sarakhieh villages and tourism area and livestock wastewaters are released into the wetland in this area. 4. SW4: North section of Shadegan wetland where a waste discharge canal from the sugarcane fields and factories is located, about kilometer 40 of the Ahvaz-Abadan Road.
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Fig. 4 Dense stands of phragmites in the Hawr Al Azim wetland
5. SW5: Near the Shadegan City wastewater outfall as it discharges to the eastern part of the wetland. Industrial and urban wastewaters are released into the wetland in this area.
Samples were collected from the middle area of the Hawr Al Azim wetland (Fig. 2). This area is relatively unaffected by human activity (Nasirian, 2014; Fig. 4).
Fig. 5 Sample site locations in the Shadegan wetland. Black arrows indicate locations of important inflow areas to the wetland, where the arrow in the north represents a canal draining sugarcane fields and factories and impacting SW4, the arrow near the middle of the wetland represents a canal also draining sugarcane fields and
factories and impacting SW1, and the bottom two arrows represent canal discharges that include Shadegan City wastewater as well as industrial effluent, impacting SW5. The red circle indicates the general area of Ragbeh and Sarakhieh villages
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At each of the five sites in the Shadegan wetland and within the broad general area of the Hawr Al Azim wetland, sediment was collected from ten subsites. All sites in the two wetlands were inundated by water during sample collection, with depths ranging from approximately 0.2 to 1 m. Samples were collected as simple grabs that were gently removed to minimize loss of fine sediment. The samples from the ten subsites were then mixed using an acid-washed (10 % nitric acid) watchglass and stored in 50-ml acid-washed (10 % nitric acid) polypropylene tubes. The samples were maintained at 0 °C and transported to the laboratory in Tehran. Sampling was done at each site in the months of October and December, 2011, and March, April, June, July, and September, 2012. Sample preparation The bed sediment samples were oven-dried at 60 °C for 24 h to prevent the loss of possible volatile metallic compounds and to facilitate sample grinding (mortar and pestle) and sieving. Digestion and analyte extraction for inductively coupled plasma optical emission spectrometry (ICP-OES) analysis were done using an acid mixture procedure (Creed et al. 1994). One gram of each sediment sample was precisely measured and delivered into a 50-ml glass beaker, and then 4 ml of HNO3 (HNO3 1 part + DDI water 1 part) and 10 ml of HCl (HCl 1 part + DDI water 4 part) were subjoined and the solution was lidded with a watch glass. The beaker was then put on a hotplate for extraction of the metals at an adjusted reflux temperature of 95 °C. The sample was warmed for 2 h while avoiding vigorous boiling of the solution (although very slight boiling could be tolerated) under a fume hood. The solution was then decreased to 10 ml by boiling, followed by cooling. The cooled solutions were transited through a 0.2-μm membrane filter into polyethylene bottles and diluted with DDI water to various volumes within the linear range of the inductively coupled plasma (ICP) instrumentation for analysis. Samples were analyzed immediately to minimize the effect of the various matrices on the stability of the diluted samples. All glassware and equipment were precleaned with 10 % nitric acid and then rinsed with high-purity DDI water before and after each grinding and digestion process to avoid cross-contamination of samples and biasing of the results.
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ICP-OES metal analysis Samples were analyzed for arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), manganese (Mn), lead (Pb), and zinc (Zn) using ICP-OES (Germany SPECTRO Company, Spectro ARCOS Model) following US EPA Method 200.7 and also as described by Nasirian et al. (2014). For instrument calibration, we used Trace CERT® FLUKA analytical BMultielement standard solution 4 for ICP^ (catalogue no. 51844, Lot & Pcod: BCBC8119 100976806) for all elements except Hg (Certipur® ICP standard of Hg, Order no. 1.70333.0100, Hg (NO3)2 in HNO3 10 %) in which we made serial dilutions that were measured by the same ICP unit. The calibration standards were run immediately prior to each round of sample analysis. Method blanks also were run at the beginning and end of reach round of sample analysis. Bed sediment contamination levels of investigated metals The level of bed sediment contamination was assessed using three approaches: i) comparison with sediment quality standards from the Ontario Ministry of Energy and Environment Ministry of Environment and Energy (MOEE) (1993), (ii) an enrichment factor (EF), and (iii) the geo-accumulation index (Igeo). The MOEE guidelines are based on the potential impact to sedimentdwelling organisms, where the Lowest Effect Level (LEL) indicates a level of contamination below which there is no effect on the majority of such organisms (i.e., it is clean to marginally polluted) and the Severe Effect Level (SEL) indicates heavily polluted sediment. The MOEE guidelines were used here because the LEL levels tend to be lower than the consensus-based guidelines often used by agencies in the USA (cf., MacDonald et al., 2000). Enrichment factors have long been used worldwide to evaluate the level of sediment contamination as well as identify the potential source of the contamination (Solomons and Forstner, 1984; Vermette et al., 1987; Irvine et al., 1989; Morillo et al. 2004; Selvaraj et al. 2004; Adamo et al. 2005; Vald’es et al. 2005; Chen et al., 2007; Abrahim and Parker, 2008; Sekabira et al., 2010). The EF approach normalizes the metal level to a common element which is compared to the typical level found either in the Earth’s crust or in shale (i.e., the
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background or natural level, Cevik et al., 2009; Devesa-Rey et al., 2011). The EF is calculated as E F ¼ ðM = M Reference Þ sample = ðM = M Reference ÞBackground
where M⁄MReference is the ratio of the metal (M) to the normalizing reference metal found in the sediment sample and (M/MReference)Background is the ratio of the metal to the normalizing reference metal found in the Earth’s crust or in shale. The most commonly used normalizing reference metals are aluminum (Al) or iron (Fe) because of their abundance in nature and the general lack of anthropogenic source enrichment (Chen et al., 2007; Zhang et al., 2007; Karageorgis et al., 2009 Sekabira et al., 2010). Although less common, others also have used gallium (Ga), rubidium (Rb), strontium (Sr), niobium (Nb), zicronium (Zr), scandium (Sc), and titanium (Ti) as the reference metal (Devesa-Rey et al., 2011; Uduma and Jimoh 2014). While the EF approach seems quite straightforward, in fact there is considerable debate on what to use as the background reference (typical crustal value, typical value for shale, local soils, or sediments from an uncontaminated site) and what to use as the normalizing metal. Some have suggested that the EF is not sensitive to the choice of background reference and normalizing metal, while others have found interpretation of results can be affected by the background reference and normalizing metal (Rubio et al., 2000; Abrahim and Parker, 2008; Devesa-Rey et al., 2011). In this study, EF values for the investigated metals were calculated using baseline values of the average upper continental crust (Taylor and McLennan, 1985; Taylor and McLennan, 1995; Rudnick and Gao, 2003). There seems to be general agreement that an EF ≤ 1 represents no enrichment, EF < 3 is minor enrichment, EF = 3–5 is moderate enrichment, EF = 5–10 is moderately severe enrichment, EF = 10–25 is severe enrichment, EF = 25–50 is very severe enrichment, and EF > 50 is extremely severe enrichment (Birth, 2003; Chen et al., 2007; Cevik et al., 2009). The Igeo index also is commonly used to assess metal pollution (Muller, 1979; Rubio et al. 2000; Ghrefat and Yusuf, 2006; Zhang et al., 2007; Praveena et al. 2008; Abrahim and Parker 2008) and can be calculated as I geo ¼ log2 ðC n =ð1:5 Bn ÞÞ where Cn is the measured concentration of the investigated metal in the environment, Bn is the soil (or shale)
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geochemical background value, and 1.5 is the background matrix correction factor due to lithogenic effects (Cevik et al., 2009). In this study, data from Taylor and McLennan (1985), Taylor and McLennan (1995), and Rudnick and Gao (2003) were used to define Bn. Igeo values are categorized as uncontaminated (Igeo ≤ 0), uncontaminated to moderately contaminated (0 < Igeo ≤ 1), moderately contaminated (1 < Igeo ≤ 2), moderately to heavily contaminated (2 < Igeo ≤ 3), heavily contaminated (3 < Igeo ≤ 4), heavily to extremely contaminated (4 < Igeo ≤ 5), and extremely contaminated (Igeo ≥ 5) (Muller, 1979). Statistical analysis All data were maintained in Excel spreadsheet format, and Excel was used to calculate summary statistics, the EF, and Igeo factors. Excel also was used to conduct Ftests to determine if the sample variances could be considered equal or not, thereby identifying the appropriate form of the t test to be used (pooled or nonpooled). The data were assumed to be approximately normally distributed, although Mendenhall (1979) noted that if a distribution has a mound shape, t tests are not especially sensitive to the normality assumption.
Results and discussion Bed sediment metal concentrations and analyses Table 1 shows values and means (μg/g, per dry mass of sediment) of the investigated metals in the bed sediment samples from the Shadegan and Hawr Al Azim wetlands, October 2011 to September 2012. Instrumental detection limit and the MOEE LEL and SEL values also are shown at the bottom of Table 1. The Cr and Cu levels of more than half of all samples reported in Table 1 exceeded the MOEE LEL level, and 5 % (2 of 42) of the samples exceeded the MOEE LEL for Hg. No sample exceeded MOEE SEL levels. Based on MOEE guidelines for protection of benthic organisms, the elements of some concern are Cr and Cu and, possibly, Hg. The data in Table 1 also suggest there may be both spatial and temporal trends in the metal levels. For the Shadegan wetland, site SW2 might be considered a relatively unimpacted control site since it is located in a central area of the wetland, distant from source inputs. Site SW 5 is impacted by urban and industrial
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Table 1 Concentrations of investigated metals (μg/g, per dry mass of sediment) in the bed sediment from the Shadegan and Hawr Al Azim wetlands (2011–2012) Site Month
SW1 October December March April June July September SW2 October December March April June July September SW3 October December March April June July September SW4 October December March April June July September SW5 October December March April June July September HH December March April June July September Mean (Std. deviation) IDL MOEE LEL MOEE SEL
Metal As
Cd
Coa
Cr
Cu
Fe
Hg
Mn
Pb
Zn
2.12 2.26 2.79 1.78 2.92 0.58 1.61 1.45 0.83 1.58 0.52 1.32
