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Heavy metal fractionation and ecological risk implications in the intertidal surface sediments of Zhelin Bay, South China
Marine Pollution Bulletin xxx (xxxx) xxx–xxx
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Heavy metal fractionation and ecological risk implications in the intertidal surface sediments of Zhelin Bay, South China Yang-Guang Gu South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China Key laboratory of Fishery Ecology and Environment, Guangdong Province, Guangzhou 510300, China Key Laboratory of Open-Sea Fishery Development, Ministry of Agriculture, Guangzhou 510300, China
A R T I C L E I N F O
A B S T R A C T
Keywords: Heavy metals Fractionation Intertidal sediments Risk assessment Zhelin Bay
Intertidal surface sediments collected from Zhelin Bay, the largest mariculture base of eastern Guangdong Province of China, were analyzed for total metal concentrations and chemical speciation. Average total metal concentrations (mg/kg) were 0.063 (Cd), 35.69 (Pb), 23.07 (Cr), 7.50 (Ni), 7.95 (Cu), 74.95 (Zn), and 751.32 (Mn). Concentrations of Cd, Cu, Zn, and Mn were significantly higher than the corresponding background values of Zhelin Bay. All studied metals were dominated by residual fractions, whereas the second relatively higher average portions of Cd (24.10%) and Mn (15.17%) were strongly associated with the acid-soluble fraction. Overall, the intertidal surface sediments of Zhelin Bay were only slightly polluted based on the pollution load index (PLI), with a 21% probability of toxicity based on the mean effects range–median quotient. The metals Cd and Mn posed medium to high risk levels based on the method of risk assessment code (RAC).
Estuarine and marine embayments supporting different habitats and providing significant economic benefits are complex and dynamic aquatic environments. (Thrush et al., 2004; Morelli and Gasparon, 2014; Jonsson et al., 2017). Heavy metals used in all kinds of human activities are one of the main ecosystem threats for estuarine waters, and often associated with sediments transported from the catchments (Ip et al., 2007; Souza Machado et al., 2016). Heavy metals are associated with sediments by means of particle surface adsorption, ion exchange, co-precipitation, and complexation with organic matter (Peng et al., 2009; Passos et al., 2010; Dong et al., 2014). In intertidal zones, physical, chemical, and biological interactions between terrestrial and marine systems have a profound influence on the transport and fate of heavy metals (Spencer, 2002; Ip et al., 2007; Trant et al., 2016). Compared with that of other marine areas, the distribution of heavy metals in estuaries and their surrounding tidal areas is generally heavily affected by various human activities, riverine and atmospheric inputs, coastal and seafloor erosions, and biological activities (Zhang and Gao, 2015; Trant et al., 2016). Some of the sediment-bound metals can be released into the water column, thereby becoming bioavailable and potentially toxic to marine organisms (Macdonald et al., 1996; Teuchies et al., 2012; Gu et al., 2015). A complete assessment of the anthropogenic metal contribution to the environment should therefore consider both the total and the exchangeable metal concentrations. Guangdong, located in South China, is the province with the most highly developed economy and the largest aquaculture production in
China (Gu et al., 2017; NBSC, 2017). Zhelin Bay, covering an area of about 70 km2, is a bay of the South China Sea on the northeastern coast of Guangdong (Fig. 1). It is the largest mariculture zone and the most intensively managed coastal aquaculture pond areas in eastern Guangdong (Gu et al., 2017; Fig. S1). Mariculture has taken up half areas of the seawater in Zhelin Bay and substantially promoted the local economy; however, its development has also caused rapid deterioration of the aquatic ecosystem in recent years. Besides pollution associated with aquaculture, rapid economic development and urbanization in recent decades have deteriorated the bay environment by increased industrial pollution, agricultural activities, and domestic sewage discharge (Gu et al., 2014b; Gu et al., 2017). There is evidence that the concentrations and potential mobility of some heavy metals in the surface sediments from some spots of the fish cage culture areas of in the Bay adversely impact marine organisms (Wang et al., 2013; Gu et al., 2014b; Gu and Lin, 2016). However, there is currently no information be found about the heavy metal concentrations in the intertidal sediments of this area. In this context, we investigated the intertidal zone of Zhelin Bay in regard to the concentrations of heavy metals. The objectives of this study were to evaluate concentrations of Cd, Pb, Cr, Ni, Cu, Zn, and Mn in the intertidal surface sediments of the bay, establish their exchangeable fractions to assess their potential bioavailability, and estimated their pollution degree and ecological risk assessment. Based on the extent of intertidal areas and the physical property of
E-mail address: [email protected]. http://dx.doi.org/10.1016/j.marpolbul.2017.10.047 Received 22 August 2017; Received in revised form 6 October 2017; Accepted 20 October 2017 0025-326X/ © 2017 Elsevier Ltd. All rights reserved.
Please cite this article as: Gu, Y.-G., Marine Pollution Bulletin (2017), http://dx.doi.org/10.1016/j.marpolbul.2017.10.047
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Fig. 1. Intertidal surface sediment sampling sites in the Zhelin Bay, South China.
Concentrations of Cd, Pb, Cr, Ni, Cu, Zn, and Mn were determined using an atomic absorption spectrometer (AAS, Z2000, Hitachi, Japan). The Chinese national standard sediment sample GBW07436 was analyzed to check the accuracy of the sequential extraction procedure and to monitor the performance of the analytical method. The Cd, Pb, Cr, Ni, Cu, Zn, and Mn recovery rates were 87–92% in the acid-soluble fraction, 89–97% in the reducible fraction, 88–103% in the oxidizable fraction, and 91–107% in the residual fraction. The distribution of particle size and SOM content are two important factors influencing metal distributions in sediments (Gu et al., 2016b; Zhang et al., 2017). In addition, CaCO3, Eh, and pH also play a role in metal distribution (Nielsen et al., 2010; Gu et al., 2016b). Our results show that the sediment texture follows a distinct spatial distribution pattern (Fig. 2). Generally, sites Z1–Z6, Z8–Z9, and Z11–Z12 were predominated by sand, while silt was the main component at Z7 and Z10. The average sand content of Z1–Z6, Z8–Z9, and Z11–Z12 was 58.81%, while the average silt composition of Z7 and Z10 was 73.62%. The SOM content varied from 1.07 to 6.34% of the dry sediment weight, with an average of 2.68%, and was more variable than the CaCO3 content, which accounted for 1.24 to 3.42% of the dry sediment weight, with an average of 2.22%. The Eh varied from 265.00 to 977.40 mV, with an average of 362.55 mV. The pH was slightly alkaline, ranging from 7.22 to 7.47, with an average of 7.35. Mean, standard deviation (SD), median, and ranges of the heavy metal concentrations in the intertidal surface sediments of the Zhelin Bay are summarized in Table 1, while the spatial distributions of metals are illustrated in Fig. 3. Generally, total metal concentrations decreased in the order Mn > Zn > Pb > Cr > Cu > Ni > Cd. Relatively higher heavy metal concentrations were found at sites Z7 and Z2, with Mn having the highest concentrations in the sediment samples. Mean total Ni concentration was 7.50 mg/kg, while the mean total Cd concentration was below 0.063 mg/kg. The Cd, Cu, Zn, and Mn concentrations were significantly higher than their corresponding background values (p < 0.01; determined using the one-sample t-test), which strongly suggests that sediment enrichment due to human activities has taken place. The relatively higher metal concentrations at Z7 are probably due to runoffs and sewage discharges into the rivers, in addition to industrialization and other human activities (Figs. 1 and 3). The high metal concentrations at site Z2, near the fish cage culture areas, may be ascribed to fish farming (Gu et al., 2014b; Gu et al., 2017).
the sediments due to hydrodynamics, 12 sampling sites were selected along the Zhelin Bay (Fig. 1). Among these sites, some have a wider intertidal zone and demonstrated notably differences in sediment texture and composition. Based on the greater sediment heterogeneity, more stations were selected in these sites. In contrast, other sites are narrow and the sediments are more homogenous and fewer stations in these narrow intertidal area sites were selected. On 9 and 10 May 2017, sediment samples from the surface layer (0–5 cm) were collected during ebb tide in the intertidal areas. Sediment redox potential (Eh) and pH were measured in situ immediately after sampling with redox and pH electrodes (FJA-6 ORP depolarization method automatic measuring system, Nanjing Chuan-Di Instrument & Equipment CO., LTD, China), respectively. At each site, five surface sediment (0–5 cm) samples were collected using a plastic spatula within an area of 2.5 m2 and mixed thoroughly to get a representative sample. The samples were placed in clean polyethylene bags, preserved with ice during transport to the laboratory, and stored at −20 °C until further analysis. Each sample was divided into two sub-samples. One was defrosted the determination of particle size, the other one was oven-dried at 50 °C, large calcareous debris and rock and plant fragments were removed, and carefully homogenized, sieved through a 200-mesh stainless steel mesh (< 74 μm), and stored for determination of sediment organic matter (SOM), inorganic carbonate (CaCO3), and heavy metals. Pretreatments for the determination of particle size were undertaken in accordance with our previous study (Gu et al., 2016a), and the particle size of each sample was determined with a Malvern Mastersizer 2000 (Malvern Instruments Co., Ltd. UK). Concentrations of SOM and CaCO3 were measured by the loss-on-ignition method. Specifically, the samples were placed in a muffle furnace (CWF1100, Carbolite, UK) and heated to 550 °C for SOM and, for a further 2 h, at 950 °C for CaCO3 determination (Gu et al., 2016b). Each sediment sample was sequentially extracted to achieve information about the heavy metal speciation, following an optimized BCR procedure (Sutherland, 2010; Gu et al., 2014b). In this procedure, the heavy metals are separated into four operationally defined geochemical fractions, the acid-soluble, reducible, oxidizable, and residual fractions. The optimized microwave-assisted sequential extraction method applied in this study has been described in our previous study (Li et al., 2017). The metals remaining in a sample residue were digested following the United States Environmental Protection Agency (USEPA) method 3050B (microwave digestion). 2
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Fig. 2. Spatial variations of grain size composition, sediment organic matter (SOM), CaCO3, redox potential (Eh), and pH in intertidal surface sediments from the Zhelin Bay.
the source and pathways of the heavy metals. Positive correlations were detected between Cd and Cu, Pb and Cr, Pb and Cu, Cr and Zn, Cr and Mn, and Zn and Mn. These findings could be a result of the same sources of pollution (Gu et al., 2014a; Yi et al., 2011). The other metals were not significantly correlated, suggesting they may have different origins. The Ni concentration appears to have been influenced by grain size composition. In contrast, concentrations of Pb, Cu, and Zn appear to be more influenced by SOM than by grain size composition, CaCO3, Eh, and pH. The Cd, Cr, and Mn concentrations were most likely more influenced by SOM than by the other evaluated physicochemical parameters. Metal fractionation is of critical importance to potential toxicity and mobility of metals (Sundaray et al., 2011; Thanh et al., 2016; Hudspith et al., 2017). It is no doubt that total metal concentration analysis is the most fundamental technique in sediment quality assessment. Therefore,
The mean total concentrations of Pb, Zn, and Mn were clearly higher with respect to the average crust values, while the mean total concentrations of the remaining metals were below the average crust values (Table 1). We compared our results with those from other bays/ estuaries in China (Li et al., 2007; Xu et al., 2016; Yu et al., 2016; Zhang and Gao, 2015; Zhang et al., 2009). Those areas had been polluted by heavy metals (Li et al., 2007; Zhang et al., 2009; Zhang and Gao, 2015; Xu et al., 2016; Yu et al., 2016). The mean concentrations of Cd, Cr, Ni, Cu, and Mn were lower than those in the Pearl River Estuary, Jiazhou Bay, Yangtze River Estuary, and Laizhou Bay. However, the mean concentration of Pb was higher than that at PRE, YRE, and LZB, while the average concentration of Zn was higher than that at Laizhou Bay (Fig. 4). The Spearman's correlation coefficients among total contents of heavy metals and sediment physicochemical properties are listed in Table S1. Inter-element relationships provided valuable insights about
Table 1 Heavy metal concentrations in the intertidal surface sediments from Zhelin Bay (mg/kg dry weight). Cd This study
Mean, SD Median Range
BVa UCCb TELc PELc
mean mean
Pb ⁎⁎
0.063 ± 0.030 0.06 0.030 − 0.140 0.03 0.102 0.68 4.21
35.69 ± 11.96 31.96 23.03 − 59.41 40.3 17 30.2 112
Cr 23.07 ± 9.27 20.76 11.16 −45.82 28.6 35 52.3 160
Ni 7.50 ± 3.65 6.81 3.68 −16.69 14.9 18.6 15.9 42.8
Cu
Zn ⁎⁎
7.95 ± 4.11 6.92 2.05 − 16.43 11.8 14.3 18.7 108
Mn ⁎⁎
74.95 ± 9.79 72.33 54.47 − 87.18 38 52 124 271
751.32⁎⁎ ± 147.43 798.79 459.77 − 911.53 343 527 460d 1100d
“n.a.” means not available. ⁎⁎ p < 0.01 significant level. a Background Values (BVs) of Zhelin Bay (Wang et al., 2013). b Upper Continental Crust (Wedepohl, 1995). c A threshold effects level (TEL) and a probable effects level (PEL), and these two values defined three ranges of chemical concentrations, including those that were (1) rarely, (2) occasionally or (3) frequently associated with adverse effects (Macdonald et al., 1996)). d Dagnino et al., 2013.
3
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Fig. 3. Spatial variations of heavy metals in total concentrations and their distributions in different geochemical phases of the intertidal surface sediments from the Zhelin Bay, China.
percentages of Cd and Mn in the reducible fraction were 6.05% and 7.01%, while 2.85% and 3.01% in the oxidizable fraction. The reducible fraction was the most abundant fraction of non-residual Pb (7.04%). The percentages of Pb and Cr in the acid-soluble fraction were negligible. For Ni and Zn, acid-soluble and oxidizable fractions were the predominant forms of the non-residual fractions. For Cu, reducible and oxidizable fractions were two the major forms of non-residual fractions. According to previous studies, the metals in the extractable fractions, namely non-residual fractions, are more or less available to aquatic biota and may correlate with their concentrations in microorganisms (Roosa et al., 2016; Rosado et al., 2016; Yıldırım and Tokalıoğlu, 2016). The high proportions of Pb and Ni in the residual fraction indicated that they pose a minor potential threat to biota. The geo-accumulation index (Igeo), originated by Müller (1969), was applied to compare current and pre-industrial metal concentrations in sediments. It can be calculated according to the following formula:
other methods are required to understand potential mobility, bioavailability, and toxicity of metals in sediments, because the properties of metals in sediments depend largely on their specific chemical forms in which they occur, besides their total contents (Filgueiras et al., 2002; Gleyzes et al., 2002; Kartal et al., 2006). The sequential extraction technique is recommended to obtain information on the mechanisms and strength of sediment-metal associations (Usero et al., 1998; Sutherland, 2010). The contributions (in percent) of the concentrations in the four metal forms to the total Cd, Pb, Cr, Ni, Cu, Zn, and Mn concentrations are illustrated in Fig. 3. Mean, standard deviation (SD), median, and ranges of the metal concentrations in each fraction are summarized in Table 2. On average, all the studied metals were dominated by residual fractions, with mean values of 65.21%, 91.26%, 95.09%, 87.04%, 76.89%, 88.54%, and 74.81% of the mean total concentration for Cd, Pb, Cr, Ni, Cu, Zn, and Mn, respectively. For Cd and Mn, the acid-soluble fraction was the second abundant form, on average accounting for 24.10% and 15.17% of the mean total concentration, which can be ascribed to the high concentrations of HCO3— in the sediments (Balistrieri et al., 2007; Li et al., 2007; Yang et al., 2009). The mean
C Igeo = log 2 ⎛ n ⎞, ⎝ 1.5Bn ⎠ ⎜
⎟
where Cn is the concentration of metals (n) in the sediment and Bn is the 4
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Fig. 4. Average metal concentrations in the intertidal surface sediments from Zhelin Bay (this study) and in other Chinese intertidal sediments of other bays/estuaries (a, b, c) and showing our compared studied areas and our study area in China coast (d); Pearl River Estuary (PRE) (Li et al., 2007), Jiaozhou Bay (JZB) (Xu et al., 2016), Quanzhou Bay (QZB) (Yu et al., 2016), Yangtze River Estuary (YRE) (Zhang et al., 2009), and Laizhou Bay (LZB) (Zhang and Gao, 2015).
strongly to extremely polluted (4 < Igeo ≤ 5); extremely polluted (Igeo > 5). The metal concentration in ‘extremely polluted’ sediment may be 100-fold greater than the background value (Müller, 1979). Based on the above categories, the Igeo was negative for four metals (Pb, Cr, Ni, and Cu) and above 1.0 for Cd at sites Z7 and Z8. None of the Igeo values was over 2.0. The Igeo of Cd, Zn, and Mn in sediments from
background concentration of the metal (n). Factor 1.5 is the background matrix correction factor due to lithospheric effects. According to Muller (1981), the Igeo for each metal can be computed and classified as: unpolluted (Igeo ≤ 0); unpolluted to moderately polluted (0 < Igeo ≤ 1); moderately polluted (1 < Igeo ≤ 2); moderately to strongly polluted (2 < Igeo ≤ 3); strongly polluted (3 < Igeo ≤ 4);
Table 2 Concentrations of Cd, Pb, Cr, Ni, Cu, Zn, and Mn in each fraction. Metal Cd
Pb
Cr
Ni
Cu
Zn
Mn
Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range
Acid soluble
Reducible
Oxidizable
Residual
0.014 ± 0.008 0.014 0.003–0.028 0.15 ± 0.08 0.15 0.02–0.28 0.09 ± 0.07 0.08 0.03–0.27 0.19 ± 0.09 0.17 0.04–0.42 0.23 ± 0.15 0.20 0.02–0.54 1.92 ± 0.81 1.73 0.41–3.39 105.87 ± 47.57 90.98 25.98–189.25
0.004 ± 0.005 0.003 0.001–0.020 2.56 ± 1.12 2.35 1.27–4.63 0.37 ± 0.16 0.30 0.18–0.61 0.22 ± 0.13 0.23 0.05–0.42 0.74 ± 0.59 0.50 0.14–2.00 2.48 ± 1.15 2.28 1.00–4.41 55.38 ± 36.87 49.01 8.73–127.81
0.003 ± 0.002 0.002 0.001–0.007 0.46 ± 0.32 0.37 0.17–1.03 0.68 ± 0.37 0.55 0.31–1.34 0.43 ± 0.09 0.46 0.25–0.53 0.87 ± 0.70 0.49 0.14–2.08 4.23 ± 1.59 4.28 1.69–6.99 22.65 ± 10.81 22.26 6.45–39.57
0.042 ± 0.023 0.045 0.014–0.093 32.51 ± 10.68 29.06 21.34–53.66 21.94 ± 8.84 19.86 10.56–43.85 6.66 ± 3.61 5.91 3.03–15.85 6.12 ± 3.17 5.74 1.35–12.41 66.33 ± 8.75 62.85 50.19–80.54 567.42 ± 144.10 595.47 268.25–756.96
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Table 3 Geo-accumulation index (Igeo) values and pollution load index (PLI) for metals at each site. Sites
Igeo (Cd)
Igeo (Pb)
Igeo (Cr)
Igeo (Ni)
Igeo (Cu)
Igeo (Zn)
Igeo (Mn)
PLI
Z1 Z2 Z3 Z4 Z5 Z6 Z7 Z8 Z9 Z10 Z11 Z12 Average
−0.79 0.59 0.15 0.34 0.69 0.48 1.59 1.00 0.85 0.03 −0.17 −0.74 0.34
− 0.76 − 0.02 − 0.58 − 0.96 − 1.02 − 1.16 − 0.04 − 0.88 − 0.75 − 1.25 − 1.39 − 1.09 − 0.82
− 0.42 0.10 − 0.91 − 0.92 − 1.23 − 1.38 − 0.47 − 1.29 − 1.13 − 1.29 − 0.97 − 1.94 − 0.99
− 1.62 − 0.42 − 1.76 − 2.45 − 2.24 − 1.67 − 0.89 − 1.89 − 2.60 − 1.55 − 1.95 − 1.41 − 1.70
− 1.52 − 0.11 − 1.38 − 1.90 − 1.70 − 0.94 − 0.38 − 1.15 − 0.63 − 1.98 − 1.34 − 3.11 − 1.34
0.54 0.59 0.50 0.24 0.32 0.33 0.61 0.36 0.29 0.29 0.60 −0.07 0.38
0.83 0.70 0.81 0.66 0.61 0.04 0.79 0.46 − 0.16 0.43 0.72 0.33 0.52
1.04 1.73 1.10 0.92 0.95 0.98 1.69 1.07 1.00 0.89 0.96 0.68 1.08
The values higher than 1 are shown in bold.
74.95 ± 9.79 (Zn), and 751.32 ± 147.43 (Mn), respectively. The mean concentrations of Pb and Mn were all higher than TELs and lower than PELs, indicating that adverse effects on benthic organisms are occasionally observed, whereas the remaining metals were lower than TELs, suggesting that adverse effects on benthic organisms are rare. To further estimate the potential risk of combined metal groups in the study, the mean probable-effects-levels (PEL) quotient approach were conducted to determine the potential biological effects of combined toxicant groups via computing mean quotients for a large range of contaminants, mainly because metals always occur in sediments as complex mixtures. The formula was applied as follows (Carr et al., 1996; MacDonald et al., 2004; Long, 2006):
mean PEL quotient =
∑ (Cx/PELx)/n,
where Cx is the measured concentration of metal x, PELx is the PEL for metal x, and n is the number of metal species. The PEL values of Cd, Pb, Cr, Ni, Cu, Zn, Co, V, and Mn are shown in Table 1. According to classifying probabilities of acute toxicity in marine sediments (Long et al., 2000), mean PEL quotients of < 0.1, 0.11–1.5, 1.5–2.3, and > 2.3 have an 8, 21, 49, and 73% incidence of adverse biological effects, respectively. As shown in Fig. 5, PEL quotients varied from 0.19 to 0.35, with a mean of 0.1–1.5. This suggests that a combination of the eight studied metals had a 21% incidence of adverse biological effects. A risk assessment code (RAC) is a common ecological risk assessment index based on the content of a substance in the acid-soluble fraction. The RAC assesses the availability of metals in sediments by estimating the percentage of metals in the acid-soluble form. This is important because the fractions introduced by anthropogenic activities are generally adsorptive, exchangeable, and bound to the acid-soluble fraction. These characteristics are weakly associated with metals that can equilibrate with the aqueous phase and become more rapidly bioavailable (Li et al., 2017; Zhang et al., 2017). According to Jain (2004), sediments can be classified into five classes: class I, RAC ≤ 1%, no risk; class II, 1% ≤ RAC < 10%, low risk; class III, 10% ≤ RAC < 30%, medium risk; class IV, 30% ≤ RAC < 50%, high risk; and class V, RAC ≥ 50%, extremely high risk. As shown in Fig. 6, Cd and Mn posed a high risk at four sites (33.33%) of Cd and one site (8.33%) of Mn; Cd and Mn posed a medium risk at six sites (50%) of Cd and six sites (50%) of Mn; Cd, Ni, Cu, Zn, and Mn posed a low risk at two sites (16.67%) of Cd, 11 sites (91.67%) of Ni, 10 sites (83.33%) of Cu, nine sites (75%) of Zn, and five sites (41.67%) of Mn; Pb, Cr, Ni, Cu, and Zn posed no risk in 12 sites (100%) of Pb, 12 sites (100%) of Cr, 12 sites (100%) of Ni, two sites (16.67%) of Cu, and three sites (25%) of Zn. Gernally, Cd and Mn posed medium to high risk levels, Ni, Cu, Zn mainly posed a low risk, and Pb posed no risk. At these levels, these metals can easily enter the food chain and threaten the aquatic ecosystem (Sundaray et al., 2011; Gu et al., 2012). In conclusion, the concentrations of Cd, Cu, Zn, and Mn in intertidal
Fig. 5. Spatial distribution of mean PEL quotient values in the intertidal surface sediments from the Zhelin Bay, China; Incidence of adverse biological effects (IABE).
58.33%, 91.67%, and 91.67% of the sites, respectively, were ‘unpolluted to moderately polluted’ (Table 3). To further assess the integrative pollution of metals in the study area, the pollution load index (PLI), as proposed by Tomlinson et al. (1980), was used to calculate pollution based on each metal concentration. The PLI is described as nth root of multiplication of the concentration factors (CF):
PLI = (CF1 × CF2…CFn )1/n , where CF is the ratio between the concentration of each metal and its corresponding background value. According to Zhu et al. (2013), the PLI can be classified into the following categories: unpolluted (0 < PLI ≤ 1); slightly polluted (1 < PLI ≤ 2); moderately polluted (2 < PLI ≤ 3); moderately to highly polluted (3 < PLI ≤ 4); highly polluted (4 < PLI ≤ 5); extremely highly polluted (PLI > 5). The PLI varied within the range of 0.68–1.73, and 50% of sites had 1 < PLI ≤ 2, indicating that the intertidal sediments of Zhelin Bay were slightly polluted with the considered metals (Table 3). The threshold effect levels (TELs) and probable effect levels (PELs) are the main parameters for estimating the adverse biological effects of metals in marine and estuary sediments (Macdonald et al., 1996; Long et al., 1998; Long and MacDonald, 1998). These two values defined three ranges of chemical concentrations, including those that were (1) rarely, (2) occasionally, or (3) frequently associated with adverse effects (Macdonald et al., 1996; Long et al., 1998). The values of TELs and PELs are listed in Table 1. The average concentrations of heavy metals in our study were (mg/kg): 0.063 ± 0.030 (Cd), 35.69 ± 11.96 (Pb), 23.07 ± 9.27 (Cr), 7.50 ± 3.65 (Ni), 7.95 ± 4.11 (Cu), 6
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Fig. 6. Risk assessment code (RAC) for metals in intertidal sediments from Zhelin Bay.
sediment samples from the Zhelin Bay were significantly higher than their corresponding background values. Positive correlations were detected between Cd and Cu, Pb and Cr, Pb and Cu, Cr and Zn, Cr and Mn, and Zn and Mn. Significant relationships were detected between P and Cd and Cu, Pb and Cr, Pb and Cu, Cr and Zn, Cr and Mn, and Zn and Mn. All the studied metals were predominately associated with the residual fraction; the relatively higher average portions of Cd (24.10%) and Mn (15.17%) were bound to the acid-soluble fraction. The mean concentrations of Pb and Mn were all higher than the TELs and lower than the PELs, indicating adverse effects on benthic organisms; consequently, further studies or management programs should give more attention to these two metals. The mean ERM quotient indicates that the intertidal sediments from Zhelin Bay had a 21% incidence rate of adverse biological effects. The metals Cd and Mn were associated with medium or high risk levels; they easily enter the food chain and poses serious threats to aquatic ecosystems. Therefore, effective measures are urgently required to control Cd and Mn inputs into the Zhelin Bay. Acknowledgements This work was supported by the Guangdong Natural Science Foundation, China (2014A030310220), the Special Scientific Research Funds for Central Non-profit Institutes, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences (2016TS13), and the joint fund of the National Natural Science Foundation of China and Guangdong Province (U1301235). Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.marpolbul.2017.10.047. References Balistrieri, L.S., Seal Ii, R.R., Piatak, N.M., Paul, B., 2007. Assessing the concentration, speciation, and toxicity of dissolved metals during mixing of acid-mine drainage and ambient river water downstream of the Elizabeth Copper Mine, Vermont, USA. Appl. Geochem. 22, 930–952. Carr, S.R., Chapman, D.C., Long, E.R., Windom, H.L., Thursby, G., Sloane, G.M., Wolfe, D.A., 1996. Sediment quality assessment studies of Tampa bay, Florida. Environ. Toxicol. Chem. 15, 1218–1231. Dagnino, A., Bo, T., Copetta, A., Fenoglio, S., Oliveri, C., Bencivenga, M., Felli, A., Viarengo, A., 2013. Development and application of an innovative expert decision support system to manage sediments and to assess environmental risk in freshwater ecosystems. Environ. Int. 60, 171–182. Dong, X.D., Wang, C., Li, H., Wu, M., Liao, S.H., Zhang, D., Pan, B., 2014. The sorption of heavy metals on thermally treated sediments with high organic matter content. Bioresour. Technol. 160, 123–128. Filgueiras, A.V., Lavilla, I., Bendicho, C., 2002. Chemical sequential extraction for metal partitioning in environmental solid samples. J. Environ. Monit. 4, 823–857.
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Baseline
Heavy metal fractionation and ecological risk implications in the intertidal surface sediments of Zhelin Bay, South China Yang-Guang Gu South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China Key laboratory of Fishery Ecology and Environment, Guangdong Province, Guangzhou 510300, China Key Laboratory of Open-Sea Fishery Development, Ministry of Agriculture, Guangzhou 510300, China
A R T I C L E I N F O
A B S T R A C T
Keywords: Heavy metals Fractionation Intertidal sediments Risk assessment Zhelin Bay
Intertidal surface sediments collected from Zhelin Bay, the largest mariculture base of eastern Guangdong Province of China, were analyzed for total metal concentrations and chemical speciation. Average total metal concentrations (mg/kg) were 0.063 (Cd), 35.69 (Pb), 23.07 (Cr), 7.50 (Ni), 7.95 (Cu), 74.95 (Zn), and 751.32 (Mn). Concentrations of Cd, Cu, Zn, and Mn were significantly higher than the corresponding background values of Zhelin Bay. All studied metals were dominated by residual fractions, whereas the second relatively higher average portions of Cd (24.10%) and Mn (15.17%) were strongly associated with the acid-soluble fraction. Overall, the intertidal surface sediments of Zhelin Bay were only slightly polluted based on the pollution load index (PLI), with a 21% probability of toxicity based on the mean effects range–median quotient. The metals Cd and Mn posed medium to high risk levels based on the method of risk assessment code (RAC).
Estuarine and marine embayments supporting different habitats and providing significant economic benefits are complex and dynamic aquatic environments. (Thrush et al., 2004; Morelli and Gasparon, 2014; Jonsson et al., 2017). Heavy metals used in all kinds of human activities are one of the main ecosystem threats for estuarine waters, and often associated with sediments transported from the catchments (Ip et al., 2007; Souza Machado et al., 2016). Heavy metals are associated with sediments by means of particle surface adsorption, ion exchange, co-precipitation, and complexation with organic matter (Peng et al., 2009; Passos et al., 2010; Dong et al., 2014). In intertidal zones, physical, chemical, and biological interactions between terrestrial and marine systems have a profound influence on the transport and fate of heavy metals (Spencer, 2002; Ip et al., 2007; Trant et al., 2016). Compared with that of other marine areas, the distribution of heavy metals in estuaries and their surrounding tidal areas is generally heavily affected by various human activities, riverine and atmospheric inputs, coastal and seafloor erosions, and biological activities (Zhang and Gao, 2015; Trant et al., 2016). Some of the sediment-bound metals can be released into the water column, thereby becoming bioavailable and potentially toxic to marine organisms (Macdonald et al., 1996; Teuchies et al., 2012; Gu et al., 2015). A complete assessment of the anthropogenic metal contribution to the environment should therefore consider both the total and the exchangeable metal concentrations. Guangdong, located in South China, is the province with the most highly developed economy and the largest aquaculture production in
China (Gu et al., 2017; NBSC, 2017). Zhelin Bay, covering an area of about 70 km2, is a bay of the South China Sea on the northeastern coast of Guangdong (Fig. 1). It is the largest mariculture zone and the most intensively managed coastal aquaculture pond areas in eastern Guangdong (Gu et al., 2017; Fig. S1). Mariculture has taken up half areas of the seawater in Zhelin Bay and substantially promoted the local economy; however, its development has also caused rapid deterioration of the aquatic ecosystem in recent years. Besides pollution associated with aquaculture, rapid economic development and urbanization in recent decades have deteriorated the bay environment by increased industrial pollution, agricultural activities, and domestic sewage discharge (Gu et al., 2014b; Gu et al., 2017). There is evidence that the concentrations and potential mobility of some heavy metals in the surface sediments from some spots of the fish cage culture areas of in the Bay adversely impact marine organisms (Wang et al., 2013; Gu et al., 2014b; Gu and Lin, 2016). However, there is currently no information be found about the heavy metal concentrations in the intertidal sediments of this area. In this context, we investigated the intertidal zone of Zhelin Bay in regard to the concentrations of heavy metals. The objectives of this study were to evaluate concentrations of Cd, Pb, Cr, Ni, Cu, Zn, and Mn in the intertidal surface sediments of the bay, establish their exchangeable fractions to assess their potential bioavailability, and estimated their pollution degree and ecological risk assessment. Based on the extent of intertidal areas and the physical property of
E-mail address: [email protected]. http://dx.doi.org/10.1016/j.marpolbul.2017.10.047 Received 22 August 2017; Received in revised form 6 October 2017; Accepted 20 October 2017 0025-326X/ © 2017 Elsevier Ltd. All rights reserved.
Please cite this article as: Gu, Y.-G., Marine Pollution Bulletin (2017), http://dx.doi.org/10.1016/j.marpolbul.2017.10.047
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Fig. 1. Intertidal surface sediment sampling sites in the Zhelin Bay, South China.
Concentrations of Cd, Pb, Cr, Ni, Cu, Zn, and Mn were determined using an atomic absorption spectrometer (AAS, Z2000, Hitachi, Japan). The Chinese national standard sediment sample GBW07436 was analyzed to check the accuracy of the sequential extraction procedure and to monitor the performance of the analytical method. The Cd, Pb, Cr, Ni, Cu, Zn, and Mn recovery rates were 87–92% in the acid-soluble fraction, 89–97% in the reducible fraction, 88–103% in the oxidizable fraction, and 91–107% in the residual fraction. The distribution of particle size and SOM content are two important factors influencing metal distributions in sediments (Gu et al., 2016b; Zhang et al., 2017). In addition, CaCO3, Eh, and pH also play a role in metal distribution (Nielsen et al., 2010; Gu et al., 2016b). Our results show that the sediment texture follows a distinct spatial distribution pattern (Fig. 2). Generally, sites Z1–Z6, Z8–Z9, and Z11–Z12 were predominated by sand, while silt was the main component at Z7 and Z10. The average sand content of Z1–Z6, Z8–Z9, and Z11–Z12 was 58.81%, while the average silt composition of Z7 and Z10 was 73.62%. The SOM content varied from 1.07 to 6.34% of the dry sediment weight, with an average of 2.68%, and was more variable than the CaCO3 content, which accounted for 1.24 to 3.42% of the dry sediment weight, with an average of 2.22%. The Eh varied from 265.00 to 977.40 mV, with an average of 362.55 mV. The pH was slightly alkaline, ranging from 7.22 to 7.47, with an average of 7.35. Mean, standard deviation (SD), median, and ranges of the heavy metal concentrations in the intertidal surface sediments of the Zhelin Bay are summarized in Table 1, while the spatial distributions of metals are illustrated in Fig. 3. Generally, total metal concentrations decreased in the order Mn > Zn > Pb > Cr > Cu > Ni > Cd. Relatively higher heavy metal concentrations were found at sites Z7 and Z2, with Mn having the highest concentrations in the sediment samples. Mean total Ni concentration was 7.50 mg/kg, while the mean total Cd concentration was below 0.063 mg/kg. The Cd, Cu, Zn, and Mn concentrations were significantly higher than their corresponding background values (p < 0.01; determined using the one-sample t-test), which strongly suggests that sediment enrichment due to human activities has taken place. The relatively higher metal concentrations at Z7 are probably due to runoffs and sewage discharges into the rivers, in addition to industrialization and other human activities (Figs. 1 and 3). The high metal concentrations at site Z2, near the fish cage culture areas, may be ascribed to fish farming (Gu et al., 2014b; Gu et al., 2017).
the sediments due to hydrodynamics, 12 sampling sites were selected along the Zhelin Bay (Fig. 1). Among these sites, some have a wider intertidal zone and demonstrated notably differences in sediment texture and composition. Based on the greater sediment heterogeneity, more stations were selected in these sites. In contrast, other sites are narrow and the sediments are more homogenous and fewer stations in these narrow intertidal area sites were selected. On 9 and 10 May 2017, sediment samples from the surface layer (0–5 cm) were collected during ebb tide in the intertidal areas. Sediment redox potential (Eh) and pH were measured in situ immediately after sampling with redox and pH electrodes (FJA-6 ORP depolarization method automatic measuring system, Nanjing Chuan-Di Instrument & Equipment CO., LTD, China), respectively. At each site, five surface sediment (0–5 cm) samples were collected using a plastic spatula within an area of 2.5 m2 and mixed thoroughly to get a representative sample. The samples were placed in clean polyethylene bags, preserved with ice during transport to the laboratory, and stored at −20 °C until further analysis. Each sample was divided into two sub-samples. One was defrosted the determination of particle size, the other one was oven-dried at 50 °C, large calcareous debris and rock and plant fragments were removed, and carefully homogenized, sieved through a 200-mesh stainless steel mesh (< 74 μm), and stored for determination of sediment organic matter (SOM), inorganic carbonate (CaCO3), and heavy metals. Pretreatments for the determination of particle size were undertaken in accordance with our previous study (Gu et al., 2016a), and the particle size of each sample was determined with a Malvern Mastersizer 2000 (Malvern Instruments Co., Ltd. UK). Concentrations of SOM and CaCO3 were measured by the loss-on-ignition method. Specifically, the samples were placed in a muffle furnace (CWF1100, Carbolite, UK) and heated to 550 °C for SOM and, for a further 2 h, at 950 °C for CaCO3 determination (Gu et al., 2016b). Each sediment sample was sequentially extracted to achieve information about the heavy metal speciation, following an optimized BCR procedure (Sutherland, 2010; Gu et al., 2014b). In this procedure, the heavy metals are separated into four operationally defined geochemical fractions, the acid-soluble, reducible, oxidizable, and residual fractions. The optimized microwave-assisted sequential extraction method applied in this study has been described in our previous study (Li et al., 2017). The metals remaining in a sample residue were digested following the United States Environmental Protection Agency (USEPA) method 3050B (microwave digestion). 2
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Fig. 2. Spatial variations of grain size composition, sediment organic matter (SOM), CaCO3, redox potential (Eh), and pH in intertidal surface sediments from the Zhelin Bay.
the source and pathways of the heavy metals. Positive correlations were detected between Cd and Cu, Pb and Cr, Pb and Cu, Cr and Zn, Cr and Mn, and Zn and Mn. These findings could be a result of the same sources of pollution (Gu et al., 2014a; Yi et al., 2011). The other metals were not significantly correlated, suggesting they may have different origins. The Ni concentration appears to have been influenced by grain size composition. In contrast, concentrations of Pb, Cu, and Zn appear to be more influenced by SOM than by grain size composition, CaCO3, Eh, and pH. The Cd, Cr, and Mn concentrations were most likely more influenced by SOM than by the other evaluated physicochemical parameters. Metal fractionation is of critical importance to potential toxicity and mobility of metals (Sundaray et al., 2011; Thanh et al., 2016; Hudspith et al., 2017). It is no doubt that total metal concentration analysis is the most fundamental technique in sediment quality assessment. Therefore,
The mean total concentrations of Pb, Zn, and Mn were clearly higher with respect to the average crust values, while the mean total concentrations of the remaining metals were below the average crust values (Table 1). We compared our results with those from other bays/ estuaries in China (Li et al., 2007; Xu et al., 2016; Yu et al., 2016; Zhang and Gao, 2015; Zhang et al., 2009). Those areas had been polluted by heavy metals (Li et al., 2007; Zhang et al., 2009; Zhang and Gao, 2015; Xu et al., 2016; Yu et al., 2016). The mean concentrations of Cd, Cr, Ni, Cu, and Mn were lower than those in the Pearl River Estuary, Jiazhou Bay, Yangtze River Estuary, and Laizhou Bay. However, the mean concentration of Pb was higher than that at PRE, YRE, and LZB, while the average concentration of Zn was higher than that at Laizhou Bay (Fig. 4). The Spearman's correlation coefficients among total contents of heavy metals and sediment physicochemical properties are listed in Table S1. Inter-element relationships provided valuable insights about
Table 1 Heavy metal concentrations in the intertidal surface sediments from Zhelin Bay (mg/kg dry weight). Cd This study
Mean, SD Median Range
BVa UCCb TELc PELc
mean mean
Pb ⁎⁎
0.063 ± 0.030 0.06 0.030 − 0.140 0.03 0.102 0.68 4.21
35.69 ± 11.96 31.96 23.03 − 59.41 40.3 17 30.2 112
Cr 23.07 ± 9.27 20.76 11.16 −45.82 28.6 35 52.3 160
Ni 7.50 ± 3.65 6.81 3.68 −16.69 14.9 18.6 15.9 42.8
Cu
Zn ⁎⁎
7.95 ± 4.11 6.92 2.05 − 16.43 11.8 14.3 18.7 108
Mn ⁎⁎
74.95 ± 9.79 72.33 54.47 − 87.18 38 52 124 271
751.32⁎⁎ ± 147.43 798.79 459.77 − 911.53 343 527 460d 1100d
“n.a.” means not available. ⁎⁎ p < 0.01 significant level. a Background Values (BVs) of Zhelin Bay (Wang et al., 2013). b Upper Continental Crust (Wedepohl, 1995). c A threshold effects level (TEL) and a probable effects level (PEL), and these two values defined three ranges of chemical concentrations, including those that were (1) rarely, (2) occasionally or (3) frequently associated with adverse effects (Macdonald et al., 1996)). d Dagnino et al., 2013.
3
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Fig. 3. Spatial variations of heavy metals in total concentrations and their distributions in different geochemical phases of the intertidal surface sediments from the Zhelin Bay, China.
percentages of Cd and Mn in the reducible fraction were 6.05% and 7.01%, while 2.85% and 3.01% in the oxidizable fraction. The reducible fraction was the most abundant fraction of non-residual Pb (7.04%). The percentages of Pb and Cr in the acid-soluble fraction were negligible. For Ni and Zn, acid-soluble and oxidizable fractions were the predominant forms of the non-residual fractions. For Cu, reducible and oxidizable fractions were two the major forms of non-residual fractions. According to previous studies, the metals in the extractable fractions, namely non-residual fractions, are more or less available to aquatic biota and may correlate with their concentrations in microorganisms (Roosa et al., 2016; Rosado et al., 2016; Yıldırım and Tokalıoğlu, 2016). The high proportions of Pb and Ni in the residual fraction indicated that they pose a minor potential threat to biota. The geo-accumulation index (Igeo), originated by Müller (1969), was applied to compare current and pre-industrial metal concentrations in sediments. It can be calculated according to the following formula:
other methods are required to understand potential mobility, bioavailability, and toxicity of metals in sediments, because the properties of metals in sediments depend largely on their specific chemical forms in which they occur, besides their total contents (Filgueiras et al., 2002; Gleyzes et al., 2002; Kartal et al., 2006). The sequential extraction technique is recommended to obtain information on the mechanisms and strength of sediment-metal associations (Usero et al., 1998; Sutherland, 2010). The contributions (in percent) of the concentrations in the four metal forms to the total Cd, Pb, Cr, Ni, Cu, Zn, and Mn concentrations are illustrated in Fig. 3. Mean, standard deviation (SD), median, and ranges of the metal concentrations in each fraction are summarized in Table 2. On average, all the studied metals were dominated by residual fractions, with mean values of 65.21%, 91.26%, 95.09%, 87.04%, 76.89%, 88.54%, and 74.81% of the mean total concentration for Cd, Pb, Cr, Ni, Cu, Zn, and Mn, respectively. For Cd and Mn, the acid-soluble fraction was the second abundant form, on average accounting for 24.10% and 15.17% of the mean total concentration, which can be ascribed to the high concentrations of HCO3— in the sediments (Balistrieri et al., 2007; Li et al., 2007; Yang et al., 2009). The mean
C Igeo = log 2 ⎛ n ⎞, ⎝ 1.5Bn ⎠ ⎜
⎟
where Cn is the concentration of metals (n) in the sediment and Bn is the 4
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Fig. 4. Average metal concentrations in the intertidal surface sediments from Zhelin Bay (this study) and in other Chinese intertidal sediments of other bays/estuaries (a, b, c) and showing our compared studied areas and our study area in China coast (d); Pearl River Estuary (PRE) (Li et al., 2007), Jiaozhou Bay (JZB) (Xu et al., 2016), Quanzhou Bay (QZB) (Yu et al., 2016), Yangtze River Estuary (YRE) (Zhang et al., 2009), and Laizhou Bay (LZB) (Zhang and Gao, 2015).
strongly to extremely polluted (4 < Igeo ≤ 5); extremely polluted (Igeo > 5). The metal concentration in ‘extremely polluted’ sediment may be 100-fold greater than the background value (Müller, 1979). Based on the above categories, the Igeo was negative for four metals (Pb, Cr, Ni, and Cu) and above 1.0 for Cd at sites Z7 and Z8. None of the Igeo values was over 2.0. The Igeo of Cd, Zn, and Mn in sediments from
background concentration of the metal (n). Factor 1.5 is the background matrix correction factor due to lithospheric effects. According to Muller (1981), the Igeo for each metal can be computed and classified as: unpolluted (Igeo ≤ 0); unpolluted to moderately polluted (0 < Igeo ≤ 1); moderately polluted (1 < Igeo ≤ 2); moderately to strongly polluted (2 < Igeo ≤ 3); strongly polluted (3 < Igeo ≤ 4);
Table 2 Concentrations of Cd, Pb, Cr, Ni, Cu, Zn, and Mn in each fraction. Metal Cd
Pb
Cr
Ni
Cu
Zn
Mn
Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range Mean, SD Median Range
Acid soluble
Reducible
Oxidizable
Residual
0.014 ± 0.008 0.014 0.003–0.028 0.15 ± 0.08 0.15 0.02–0.28 0.09 ± 0.07 0.08 0.03–0.27 0.19 ± 0.09 0.17 0.04–0.42 0.23 ± 0.15 0.20 0.02–0.54 1.92 ± 0.81 1.73 0.41–3.39 105.87 ± 47.57 90.98 25.98–189.25
0.004 ± 0.005 0.003 0.001–0.020 2.56 ± 1.12 2.35 1.27–4.63 0.37 ± 0.16 0.30 0.18–0.61 0.22 ± 0.13 0.23 0.05–0.42 0.74 ± 0.59 0.50 0.14–2.00 2.48 ± 1.15 2.28 1.00–4.41 55.38 ± 36.87 49.01 8.73–127.81
0.003 ± 0.002 0.002 0.001–0.007 0.46 ± 0.32 0.37 0.17–1.03 0.68 ± 0.37 0.55 0.31–1.34 0.43 ± 0.09 0.46 0.25–0.53 0.87 ± 0.70 0.49 0.14–2.08 4.23 ± 1.59 4.28 1.69–6.99 22.65 ± 10.81 22.26 6.45–39.57
0.042 ± 0.023 0.045 0.014–0.093 32.51 ± 10.68 29.06 21.34–53.66 21.94 ± 8.84 19.86 10.56–43.85 6.66 ± 3.61 5.91 3.03–15.85 6.12 ± 3.17 5.74 1.35–12.41 66.33 ± 8.75 62.85 50.19–80.54 567.42 ± 144.10 595.47 268.25–756.96
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Table 3 Geo-accumulation index (Igeo) values and pollution load index (PLI) for metals at each site. Sites
Igeo (Cd)
Igeo (Pb)
Igeo (Cr)
Igeo (Ni)
Igeo (Cu)
Igeo (Zn)
Igeo (Mn)
PLI
Z1 Z2 Z3 Z4 Z5 Z6 Z7 Z8 Z9 Z10 Z11 Z12 Average
−0.79 0.59 0.15 0.34 0.69 0.48 1.59 1.00 0.85 0.03 −0.17 −0.74 0.34
− 0.76 − 0.02 − 0.58 − 0.96 − 1.02 − 1.16 − 0.04 − 0.88 − 0.75 − 1.25 − 1.39 − 1.09 − 0.82
− 0.42 0.10 − 0.91 − 0.92 − 1.23 − 1.38 − 0.47 − 1.29 − 1.13 − 1.29 − 0.97 − 1.94 − 0.99
− 1.62 − 0.42 − 1.76 − 2.45 − 2.24 − 1.67 − 0.89 − 1.89 − 2.60 − 1.55 − 1.95 − 1.41 − 1.70
− 1.52 − 0.11 − 1.38 − 1.90 − 1.70 − 0.94 − 0.38 − 1.15 − 0.63 − 1.98 − 1.34 − 3.11 − 1.34
0.54 0.59 0.50 0.24 0.32 0.33 0.61 0.36 0.29 0.29 0.60 −0.07 0.38
0.83 0.70 0.81 0.66 0.61 0.04 0.79 0.46 − 0.16 0.43 0.72 0.33 0.52
1.04 1.73 1.10 0.92 0.95 0.98 1.69 1.07 1.00 0.89 0.96 0.68 1.08
The values higher than 1 are shown in bold.
74.95 ± 9.79 (Zn), and 751.32 ± 147.43 (Mn), respectively. The mean concentrations of Pb and Mn were all higher than TELs and lower than PELs, indicating that adverse effects on benthic organisms are occasionally observed, whereas the remaining metals were lower than TELs, suggesting that adverse effects on benthic organisms are rare. To further estimate the potential risk of combined metal groups in the study, the mean probable-effects-levels (PEL) quotient approach were conducted to determine the potential biological effects of combined toxicant groups via computing mean quotients for a large range of contaminants, mainly because metals always occur in sediments as complex mixtures. The formula was applied as follows (Carr et al., 1996; MacDonald et al., 2004; Long, 2006):
mean PEL quotient =
∑ (Cx/PELx)/n,
where Cx is the measured concentration of metal x, PELx is the PEL for metal x, and n is the number of metal species. The PEL values of Cd, Pb, Cr, Ni, Cu, Zn, Co, V, and Mn are shown in Table 1. According to classifying probabilities of acute toxicity in marine sediments (Long et al., 2000), mean PEL quotients of < 0.1, 0.11–1.5, 1.5–2.3, and > 2.3 have an 8, 21, 49, and 73% incidence of adverse biological effects, respectively. As shown in Fig. 5, PEL quotients varied from 0.19 to 0.35, with a mean of 0.1–1.5. This suggests that a combination of the eight studied metals had a 21% incidence of adverse biological effects. A risk assessment code (RAC) is a common ecological risk assessment index based on the content of a substance in the acid-soluble fraction. The RAC assesses the availability of metals in sediments by estimating the percentage of metals in the acid-soluble form. This is important because the fractions introduced by anthropogenic activities are generally adsorptive, exchangeable, and bound to the acid-soluble fraction. These characteristics are weakly associated with metals that can equilibrate with the aqueous phase and become more rapidly bioavailable (Li et al., 2017; Zhang et al., 2017). According to Jain (2004), sediments can be classified into five classes: class I, RAC ≤ 1%, no risk; class II, 1% ≤ RAC < 10%, low risk; class III, 10% ≤ RAC < 30%, medium risk; class IV, 30% ≤ RAC < 50%, high risk; and class V, RAC ≥ 50%, extremely high risk. As shown in Fig. 6, Cd and Mn posed a high risk at four sites (33.33%) of Cd and one site (8.33%) of Mn; Cd and Mn posed a medium risk at six sites (50%) of Cd and six sites (50%) of Mn; Cd, Ni, Cu, Zn, and Mn posed a low risk at two sites (16.67%) of Cd, 11 sites (91.67%) of Ni, 10 sites (83.33%) of Cu, nine sites (75%) of Zn, and five sites (41.67%) of Mn; Pb, Cr, Ni, Cu, and Zn posed no risk in 12 sites (100%) of Pb, 12 sites (100%) of Cr, 12 sites (100%) of Ni, two sites (16.67%) of Cu, and three sites (25%) of Zn. Gernally, Cd and Mn posed medium to high risk levels, Ni, Cu, Zn mainly posed a low risk, and Pb posed no risk. At these levels, these metals can easily enter the food chain and threaten the aquatic ecosystem (Sundaray et al., 2011; Gu et al., 2012). In conclusion, the concentrations of Cd, Cu, Zn, and Mn in intertidal
Fig. 5. Spatial distribution of mean PEL quotient values in the intertidal surface sediments from the Zhelin Bay, China; Incidence of adverse biological effects (IABE).
58.33%, 91.67%, and 91.67% of the sites, respectively, were ‘unpolluted to moderately polluted’ (Table 3). To further assess the integrative pollution of metals in the study area, the pollution load index (PLI), as proposed by Tomlinson et al. (1980), was used to calculate pollution based on each metal concentration. The PLI is described as nth root of multiplication of the concentration factors (CF):
PLI = (CF1 × CF2…CFn )1/n , where CF is the ratio between the concentration of each metal and its corresponding background value. According to Zhu et al. (2013), the PLI can be classified into the following categories: unpolluted (0 < PLI ≤ 1); slightly polluted (1 < PLI ≤ 2); moderately polluted (2 < PLI ≤ 3); moderately to highly polluted (3 < PLI ≤ 4); highly polluted (4 < PLI ≤ 5); extremely highly polluted (PLI > 5). The PLI varied within the range of 0.68–1.73, and 50% of sites had 1 < PLI ≤ 2, indicating that the intertidal sediments of Zhelin Bay were slightly polluted with the considered metals (Table 3). The threshold effect levels (TELs) and probable effect levels (PELs) are the main parameters for estimating the adverse biological effects of metals in marine and estuary sediments (Macdonald et al., 1996; Long et al., 1998; Long and MacDonald, 1998). These two values defined three ranges of chemical concentrations, including those that were (1) rarely, (2) occasionally, or (3) frequently associated with adverse effects (Macdonald et al., 1996; Long et al., 1998). The values of TELs and PELs are listed in Table 1. The average concentrations of heavy metals in our study were (mg/kg): 0.063 ± 0.030 (Cd), 35.69 ± 11.96 (Pb), 23.07 ± 9.27 (Cr), 7.50 ± 3.65 (Ni), 7.95 ± 4.11 (Cu), 6
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Gleyzes, C., Tellier, S., Astruc, M., 2002. Fractionation studies of trace elements in contaminated soils and sediments: a review of sequential extraction procedures. TrAC Trends Anal. Chem. 21, 451–467. Gu, Y.G., Lin, Q., 2016. Trace metals in a sediment core from the largest mariculture base of the eastern Guangdong coast, South China: vertical distribution, speciation, and biological risk. Mar. Pollut. Bull. 113, 520–525. Gu, Y.G., Yang, Y.F., Lin, Q., Li, Q.S., Wang, Z.H., Wang, X.N., 2012. Spatial, temporal, and speciation variations of heavy metals in sediments of Nan'ao Island, a representative mariculture base in Guangdong coast, China. J. Environ. Monit. 14, 1943–1950. Gu, Y.G., Li, Q.S., Fang, J.H., He, B.Y., Fu, H.B., Tong, Z.J., 2014a. Identification of heavy metal sources in the reclaimed farmland soils of the pearl river estuary in China using a multivariate geostatistical approach. Ecotoxicol. Environ. Saf. 105, 7–12. Gu, Y.G., Lin, Q., Jiang, S.J., Wang, Z.H., 2014b. 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Fig. 6. Risk assessment code (RAC) for metals in intertidal sediments from Zhelin Bay.
sediment samples from the Zhelin Bay were significantly higher than their corresponding background values. Positive correlations were detected between Cd and Cu, Pb and Cr, Pb and Cu, Cr and Zn, Cr and Mn, and Zn and Mn. Significant relationships were detected between P and Cd and Cu, Pb and Cr, Pb and Cu, Cr and Zn, Cr and Mn, and Zn and Mn. All the studied metals were predominately associated with the residual fraction; the relatively higher average portions of Cd (24.10%) and Mn (15.17%) were bound to the acid-soluble fraction. The mean concentrations of Pb and Mn were all higher than the TELs and lower than the PELs, indicating adverse effects on benthic organisms; consequently, further studies or management programs should give more attention to these two metals. The mean ERM quotient indicates that the intertidal sediments from Zhelin Bay had a 21% incidence rate of adverse biological effects. The metals Cd and Mn were associated with medium or high risk levels; they easily enter the food chain and poses serious threats to aquatic ecosystems. Therefore, effective measures are urgently required to control Cd and Mn inputs into the Zhelin Bay. Acknowledgements This work was supported by the Guangdong Natural Science Foundation, China (2014A030310220), the Special Scientific Research Funds for Central Non-profit Institutes, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences (2016TS13), and the joint fund of the National Natural Science Foundation of China and Guangdong Province (U1301235). Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.marpolbul.2017.10.047. References Balistrieri, L.S., Seal Ii, R.R., Piatak, N.M., Paul, B., 2007. Assessing the concentration, speciation, and toxicity of dissolved metals during mixing of acid-mine drainage and ambient river water downstream of the Elizabeth Copper Mine, Vermont, USA. Appl. Geochem. 22, 930–952. Carr, S.R., Chapman, D.C., Long, E.R., Windom, H.L., Thursby, G., Sloane, G.M., Wolfe, D.A., 1996. Sediment quality assessment studies of Tampa bay, Florida. Environ. Toxicol. Chem. 15, 1218–1231. Dagnino, A., Bo, T., Copetta, A., Fenoglio, S., Oliveri, C., Bencivenga, M., Felli, A., Viarengo, A., 2013. Development and application of an innovative expert decision support system to manage sediments and to assess environmental risk in freshwater ecosystems. Environ. Int. 60, 171–182. Dong, X.D., Wang, C., Li, H., Wu, M., Liao, S.H., Zhang, D., Pan, B., 2014. The sorption of heavy metals on thermally treated sediments with high organic matter content. Bioresour. Technol. 160, 123–128. Filgueiras, A.V., Lavilla, I., Bendicho, C., 2002. Chemical sequential extraction for metal partitioning in environmental solid samples. J. Environ. Monit. 4, 823–857.
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