Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China

MPB-07205; No of Pages 9 Marine Pollution Bulletin xxx (2015) xxx–xxx

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Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China Rongyu Li a, Ruili Li a, Minwei Chai b,⁎, Xiaoxue Shen a, Hualin Xu c, Guoyu Qiu a,⁎⁎ a b c

Key Laboratory for Urban Habitat Environment Science and Technology, School of Environment and Energy, Shenzhen Graduate School of Peking University, Shenzhen 518055, China Shenzhen Key Laboratory of Environment Simulation and Pollution Control, PKU–HKUST Shenzhen–Hong Kong Institute, Shenzhen 518057, China Guangdong Neilingding Futian National Nature Reserve, Shenzhen 518000, China

a r t i c l e

i n f o

Article history: Received 24 July 2015 Received in revised form 25 September 2015 Accepted 28 September 2015 Available online xxxx Keywords: Ecological risk assessment Heavy metal Mangrove Sediment

a b s t r a c t Surface sediments in the Futian mangrove forest (South China) were analyzed for heavy metals including cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb) and zinc (Zn). The heavy metal distributions varied greatly in surface sediments, reflecting some sediment heterogeneity. The heavy metal concentrations decreased in the order of Zn N Cr N Pb N Cu N Cd. According to the mean probable effects level quotient, the combination of studied metals had a 21% probability of being toxic. The potential ecological risk index and geo-accumulation index also revealed high metal contamination. Cd was of primary concern due to its higher assessment values and potential for adverse biological effects. Multivariate analysis implied that clay and silt played a significant role in raising the levels of Cr, Cu and Zn. The percentage of mobile heavy metals was relatively higher, without considerable ecological risk to the biota based on the risk assessment code. © 2015 Elsevier Ltd. All rights reserved.

Mangrove forests are vital coastal ecosystems that occur in circumtropical regions and cover an area of approximately 1.7 × 105 km2 along the shorelines of the world (Sandilyan and Kathiresan, 2014). Mangrove forests provide various ecological services; however, they are being exposed to increasing pollution from human activities due to rapid urban development and industrialization in coastal areas (MacFarlane et al., 2007; Krauss et al., 2008; Farley et al., 2010; Sandilyan and Kathiresan, 2012; Wu et al., 2014). Among these pollutants, heavy metals have received significant attention due to their toxicity, non-biodegradability and biological accumulation (Nath et al., 2013; Chaudhuri et al., 2014). Generally, the pollution of mangroves with heavy metals is associated with anthropogenic-related processes via such sources as untreated industrial wastewater, municipal sewage effluent and surface run-off (Bodin et al., 2013). Considering the anoxic nature of mangrove sediment, heavy metals from incoming tidal waters and fresh water sources can be rapidly removed from the waterbody and deposited in the sediment, making it a depository for metals (Yan et al., 2015). However, chemical and biological processes may allow heavy metals to be desorbed from sediments, upon which they are released into the water column (Hill et al., 2013; Wang et al., 2013). Sediments act as both final sinks and potential secondary sources for heavy metals, and regular monitoring and assessment of heavy metals in mangrove sediment is necessary to evaluate their ecological risk. ⁎ Correspondence to: M. Chai, Tel.: +86 755 26033141; fax: +86 755 26032078. ⁎⁎ Correspondence to: G. Qiu, Tel.: +86 755 26033141; fax: +86 755 26035332. E-mail addresses: [email protected] (M. Chai), [email protected] (G. Qiu).

In South China, the health and integrity of mangroves are aggravated due to substantial discharge of industrial sewage into the Pearl River Estuary (PRE) from the coastal cities (Chen et al., 2006, 2013). On the east side of the PRE and Shenzhen Bay, the Futian mangrove forest is the only mangrove forest located in the middle of Shenzhen, China (adjacent to the Mai Po Nature Reserve, Hong Kong) and has suffered serious heavy metal pollution since the early 1990s (Xie et al., 2010; He et al., 2014). Lin et al. (1997) reported heavy metal contents—such as copper (Cu), zinc (Zn), chromium (Cr), lead (Pb) and nickel (Ni)—in surface sediments of the Avicennia marina community of Futian mangroves, and B.S. Wang et al. (2003), S.H. Wang et al. (2003) focused on the Sonneratia apetala, Sonneratia caseolaris and Kandelia candel communities. Up to now, no systematic and specialized research has focused on ecological risk assessment of heavy metal contamination in the Futian mangrove forest, in spite of their significance in determining mangrove function and productivity (Lin et al., 1997; B.S. Wang et al., 2003; S.H. Wang et al., 2003; He et al., 2014). Such data are also important for designing long-term management and conservation policies. Therefore, this study aimed to (1) quantify the concentrations of heavy metals in mangrove sediments, (2) assess the potential ecological risk and sources of heavy metals, and (3) identify the speciation of heavy metals. Futian Nature Reserve (22°32ʹN, 114°03ʹE) is a mangrove forest area of 304 ha located in the Guangdong Province, China. The mangrove forest is mainly dominated by native, true mangrove plants, such as K. candel, A. marina, and Aegiceras corniculata, and exotic mangrove species, such as S. apetala and S. caseolaris. The mean annual temperature is 23.0 °C, with the maximum in July (36.1 °C) and the minimum in January (3.9 °C). The mean annual precipitation is 1935.8 mm mostly

http://dx.doi.org/10.1016/j.marpolbul.2015.09.048 0025-326X/© 2015 Elsevier Ltd. All rights reserved.

Please cite this article as: Li, R., et al., Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China, Marine Pollution Bulletin (2015), http://dx.doi.org/10.1016/j.marpolbul.2015.09.048

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R. Li et al. / Marine Pollution Bulletin xxx (2015) xxx–xxx

during May–September, and the mean annual relative moisture is 74%. The tides in Shenzhen Bay are semidiurnal, with an average range of 1.9 m. In July 2014, a total of 16 sites along the mangrove forest were selected (Fig. 1). In the west of Fengtanghe River estuary, one study site was uniformly divided into 11 sampling points along the mangrove forest, with a distance of about 200 m between two consecutive sampling points; while the five other sites were evenly distributed in the east of Fengtanghe River estuary. At each sampling point, three random samples (0–20 cm depth) of surface sediment were collected using acidwashed PVC pipes of length 40 cm and internal diameter 7.5 cm. The sediment cores were immediately sliced at 0–10 cm and 10–20 cm using a plastic cutter, after which the subsamples were immediately sealed in plastic bags and transported back to the laboratory on the same day. They were stored at −20 °C until further analysis. The TOC content of sediment was determined by the potassium dichromate oxidation–colorimetric method (Lu, 2000). The particle size distribution was measured with a particle size analyzer (Mastersizer 2000, Malvern, UK). The total heavy metal concentrations were determined by subjecting the sediment samples to microwave digestion in a mixture of 9 ml of nitric acid (HNO3), 3 ml of hydrofluoric acid (HF) and 1 ml of hydrochloric acid (HCl). The concentrations were analyzed using inductively coupled plasma-atomic emission spectrometry (ICPAES). In this study, the threshold effect level (TEL) and probable effect level (PEL) of heavy metals have been applied to facilitate the interpretation of sediment quality (MacDonald et al., 1996, 2000). Pollution levels of heavy metals can also be characterized by the geo-accumulation index (Igeo), proposed by Müller (Müller, 1969). As shown in Table 1, there are seven classes of Igeo (Müller, 1981). The potential ecological risk coefficient (Eir) was calculated to evaluate the ecological risk of each heavy metal using the following formula (Hakanson, 1980). The background value of heavy metals was adopted from Li and Zheng (1988). The degree of ecological risk can be categorized as follows: Eir b 40: low risk, 40 ≤ Eir b 80: moderate risk, 80 ≤ Eir b 160: considerable risk, 160 ≤ Eir b 320: high risk and Eir ≥ 320: very high risk.

Table 1 Pollution grades of geo-accumulation index of the metals. Igeo class

Igeo value

Pollution quality

0 1 2 3 4 5 6

Igeo ≤ 0 0 b Igeo b 1 1 b Igeo b 2 2 b Igeo b 3 3 b Igeo b 4 4 b Igeo b 5 5 b Igeo

Uncontaminated Uncontaminated to moderately contaminated Moderately contaminated Moderately to heavily contaminated Heavily contaminated Heavily to extremely contaminated Extremely contaminated

Note: Igeo was classified by Müller (1981). Igeo can be defined as Igeo = log2(Cn / 1.5Bn). Cn is the measured content of the metal n; Bn is the background or pristine value of the metal. The constant factor 1.5 is introduced to analyze natural fluctuations in the contents of a given substance in the environment and very small anthropogenic influences (Loska et al., 2004).

The potential ecological risk index (RI), represents the overall ecological risk of multiple heavy metals in the sediment. RI was classified into four levels: RI b 150: low risk, 150 ≤ RI b 300: moderate risk, 300 ≤ RI b 600: considerable risk and RI ≥ 600: very high risk. The sequential extraction procedure (SEP) used to analyze heavy metal speciation was the improved BCR (Community Bureau of Reference) three-step scheme (Guillén et al., 2012). The four fractions were defined as acid-soluble fraction (F1), reducible fraction (F2), oxidizable fraction (F3) and residual fraction (F4). A risk assessment code (RAC) was applied to evaluate the environmental risk of heavy metal pollution in mangrove sediment (Ghrefat and Yusuf, 2006; Huang et al., 2011; Zhou et al., 2013; Zhai et al., 2014; Yuan et al., 2015). RAC assesses the availability of heavy metal (F1 fraction) in sediment by applying a scale to the percentage of the total heavy metal. A five-level risk classification has been categorized in terms of RAC: no risk (b1%), low risk (1%–10%), medium risk (11%– 30%), high risk (31%–50%), and very high risk (N50%) (Perin et al., 1985). Linear regression analysis was conducted to examine the correlations among TOC, particle size and heavy metals. Principal component analysis (PCA) was used to investigate the potential pollution sources

Fig. 1. The 16 sampling points, shown by ● in the Futian mangroves in the present study. At each sampling point, three replicates of surface sediments were collected.

Please cite this article as: Li, R., et al., Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China, Marine Pollution Bulletin (2015), http://dx.doi.org/10.1016/j.marpolbul.2015.09.048

R. Li et al. / Marine Pollution Bulletin xxx (2015) xxx–xxx

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Fig. 2. Concentrations of Cd, Cr, Cu, Pb and Zn (μg g−1) of the surface sediment in the Futian mangrove forest, South China (mean ± standard deviation). The dashed line indicates the background level of each heavy metal according to Li and Zheng (1988). The dotted line indicates the guideline level of each heavy metal based on the Class I marine sediment quality standards in China (GB 18668-2002).

(natural or anthropogenic) and characteristics. Hierarchical cluster

analysis (HCA) of the normalized data set was conducted using Ward's

Table 2 The heavy metals (μg g−1) in the collected samples of mangrove sediments of this study and some mangrove wetlands around the world. Location

Futian Deep Bay Mai Po Pearl River Nansha Zhanjiang Taishan Hainan Island Punta Portete Payardia Galetea Toro Pointa Buffalo River Guanabara Bay Cienaga Grande Estero Salado Pichavaram South Port Klang Sungei Buloh Fadiouth

Heavy metal (μg g−1)

Country/area

China Hong Kong, China Hong Kong, China China China China China China Costa Rica Panama Panama Panama Brazil Brazil Colombia Ecuador India Malaysia Singapore Senegal

References

Cd

Cr

Cu

Pb

Zn

2.3 3.0 2.6 1.2 0.8 0.2 0.1 0.1 7.3 7.5 7.2 6.6 3.6 1.3 1.9 1.9 6.6 1.5 0.2 0.0

55.4 40.0 39.2 104.7 155.0 5.12 19.9 40.0 22.6 10.0 12.8 13.7 118.0 42.4 13.2 94.5 141.2 60.2 16.6 28.8

31.7 80.0 78.5 51.5 113.0 16.9 30.9 18.0 8.4 4.0 4.0 4.9 76.0 98.6 23.3 253.8 43.4 24.9 7.1 3.5

47.8 80.0 79.2 32.2 55.3 32.8 67.7 19.0 34.5 33.3 32.5 38.0 131.0 160.8 12.6 81.3 11.2 96.0 12.3 2.4

296.3 240.0 240.0 127.4 159.0 49.0 79.9 57.0 14.7 16.1 10.9 19.9 479.0 483.0 91.0 678.3 93.0 72.2 51.2 5.4

In this study Tam and Yao (1998) Tam and Wong (2000) Bai et al. (2011) Wu et al. (2014) Li (2008) Li (2008) Qiu et al. (2011) Guzman and Jimenez (1992) Guzman and Jimenez (1992) Guzman and Jimenez (1992) Guzman and Jimenez (1992) Kehrig et al. (2003) Kehrig et al. (2003) Perdomo et al. (1998) Fernandez-Cadena, et al. (2014) Ramanathan et al. (1999) Sany et al. (2013) Cuong et al. (2005) Bodin et al. (2013)

Table 3 Heavy metal guidelines of some different criteria used to distinguish marine quality (μg g−1).

Threshold effect level (TEL) Probable effect level (PEL)

Cd

Cr

Cu

Pb

Zn

References

0.99 4.98

43.40 111.00

31.60 149.00

35.80 128.00

121.00 459.00

MacDonald et al. (2000) MacDonald et al. (2000)

Note: TEL, threshold effect level, indicates concentrations below which adverse effects on biota are rarely observed. PEL, probable effects level, indicate concentrations above which adverse effects on biota are frequently observed.

Please cite this article as: Li, R., et al., Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China, Marine Pollution Bulletin (2015), http://dx.doi.org/10.1016/j.marpolbul.2015.09.048

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R. Li et al. / Marine Pollution Bulletin xxx (2015) xxx–xxx

Fig. 3. The mean PEL quotient values in surface sediments in the Futian mangrove forest.

method with Euclidean distances as a measure of similarity. The classification is based on visual observation of the dendrogram. Pearson's correlation analysis was conducted to identify the relationships among TOC, particle size and heavy metals, as well as to support the results of the multivariate analysis. There were four distinct patterns in the spatial variation of heavy metal concentrations in the surface sediment (Fig. 2). Pattern 1 (Cd): a dramatic fluctuation in concentration appeared from site 1 to site 16 with an overall slightly decreasing trend. Pattern 2 (Cr and Cu): concentrations were similar from site 1 to site 13, but decreased from site 14 to site 16. Pattern 3 (Pb): concentrations were similar from site 1 to site 16. Pattern 4 (Zn): concentrations decreased from site 1 to site 7, and

fluctuated from site 7 to site 16. According to the backgrounds of the five heavy metals, Cr, Cu, Pb and Zn concentrations were mostly above their respective background level (and all for Cd), indicating that anthropogenic activities had a direct impact on concentrations of heavy metals in sediments. Furthermore, Cd concentrations were too high to meet their respective guideline values of Class I marine sediment quality standards in China (GB 18668-2002), which aim to protect human health and the natural environment. The concentrations of Cu and Zn roughly meet Class I, and Cr and Pb were below Class I. Compared with other mangrove wetlands in the world, the mean concentrations of the five heavy metals in Futian mangrove were high (Table 2). The Cd concentration in this study was comparable to those recorded in Hong Kong (Tam and Yao, 1998; Tam and Wong, 2000); lower than that recorded for sediments of Punta Portete in Costa Rica, Galetea in Panama (Guzman and Jimenez, 1992), Pichavaram in India (Ramanathan et al., 1999) and Buffalo River in Brazil (Kehrig et al., 2003); and higher than other mangrove wetlands worldwide. Meanwhile, the average Cr, Cu, Pb and Zn concentrations were in the middle-levels compared to other mangrove wetlands around the world. The concentration of Cd in most mangroves in Central and South American and India is high and thus the ecological risk in these mangroves must be high. In contrast, mangroves in Singapore, Malaysia and Senegal are much less contaminated with heavy metals, probably due to better management of anthropogenic sources. The sediment in the Futian mangrove was more contaminated with Cd, Pb, and Zn than other areas in China—such as Nansha, Zhanjiang, Taishan and Hainan Island—likely owing to the rapid socio-economic development in the region of Shenzhen Bay. Similarly, Hong Kong suffers from serious contamination of Cd, Cr, Cu, Pb and Zn due to discharge of industrial sewage and poor water circulation in the bottle-neck of Shenzhen Bay.

Fig. 4. The potential ecological risk coefficients (Eir) of Cd, Cr, Cu, Pb and Zn, as well as the potential ecological risk index (RI) of the surface sediment in the Futian mangrove forest (mean ± standard deviation). Eir = Tir · Cif = Tir · Cis / Cin. Where Tir is the toxic-response factor of heavy metal i, Cif is the contamination factor of heavy metal i, Cis is the measured concentration of heavy metal i in the sediment and Cin is the background value of heavy metals i, adopted from Li and Zheng (1988). The toxic-response factors for Cd, Cr, Cu, Pb and Zn was 30, 2, 5, 5 and 1, n

respectively (Hakanson, 1980). RI = ∑ Eir , where n is the number of heavy metals analyzed in the sample (i.e., n = 5 in the present study). i¼1

Please cite this article as: Li, R., et al., Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China, Marine Pollution Bulletin (2015), http://dx.doi.org/10.1016/j.marpolbul.2015.09.048

R. Li et al. / Marine Pollution Bulletin xxx (2015) xxx–xxx

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Fig. 5. The geo-accumulation index (Igeo) of heavy metals in the Futian mangrove forest (mean ± standard deviation).

Generally, below the TEL, adverse biological effects are rarelyexpected, whereas the PEL is defined as the level above which adverse biological effects are expected to occur more often than not (Long et al., 1998; Yang et al., 2012). In the present study, mean concentrations of Cd, Cr, Pb and Zn at all sampling sites were higher than the TEL value, but below PEL benchmarks (Tables 2 and 3), suggesting that advers biological effects caused by these metals may be observed occasionally. Mean Cu levels at all sampling sites were slightly higher/comparable to the TEL value, and far lower than the PEL values. In fact, heavy metals always occur in sediments as complex mixtures. To determine the possible biological effects of combined metals,

Table 4 Rotated factor loading of the variables. Variable

TOC Sand Silt Clay Cd Cr Cu Pb Zn Initial eigenvalue % of variance Cumulative %

Factors Factor 1

Factor 2

Factor 3

−0.747 −0.786 0.758 0.838 0.309 0.741 0.770 0.320 0.755 4.362 48.465 48.465

0.132 0.571 −0.579 −0.456 0.287 0.629 0.563 −0.067 0.531 1.969 21.873 70.338

0.029 0.144 −0.175 0.052 −0.826 −0.079 0.082 0.876 0.256 1.584 17.598 87.936

Note: sand, silt and clay represent percentage of sand, silt and clay (%), TOC, total organic carbon (%). Extract method: principal component analysis.

mean PEL quotients (m-P-Q) for the five heavy metals were calculated using the following formula: m‐P‐Q ¼ ΣðCx =PELx Þ=n where Cx is the sediment concentration of component x, PELx is the PEL for compound x and n is the number of components. Four classes of toxicity probability for biota were defined as follows (Long et al., 1998): mP-Q b 0.1 (8% probability of being toxic); 0.11–1.5 (21% probability of being toxic); 1.51–2.3 (49% probability of being toxic); and N2.3 (73% probability of being toxic). In the present study, the mean PEL quotients were in the range 0.11–1.5 at all sampling sites (Fig. 3), indicating that the combination of the five studied metals had a 21% probability of being toxic. Analogous results were observed for surface sediments of the intertidal Bohai Bay and the coastal Shandong Peninsula (Yellow Sea), where the combination of studied heavy metals had a 21% probability of being toxic (Gao and Li, 2012; Li et al., 2013; Chai et al., 2014). The patterns of Eir for each heavy metal were similar to their concentrations (Fig. 4). The Eir of Cd was very high (Eir ≥ 320) for all sampling sites, and potentially posed a very high ecological risk. Cr, Cu, Pb and Zn had Eir b 40 for all sampling sites, suggesting low potential ecological risk. For integrated metals, the ecological risk of heavy metals in the Futian mangrove was very high (RI ≥ 600) for all sampling sites, largely due to Cd contamination. Igeo is a normalization technique that has been widely applied to the assessment of heavy metal contamination in soils and sediments (Varol, 2011; Zhuang and Gao, 2014). In the present study, background values were selected as the reference for assessment of heavy metal pollution (Li and Zheng, 1988). In Fig. 5, the mean Igeo values of the five metals were in increasing order: Cr (− 0.06) b Pb (0.39) b Cu (1.12) b Zn

Please cite this article as: Li, R., et al., Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China, Marine Pollution Bulletin (2015), http://dx.doi.org/10.1016/j.marpolbul.2015.09.048

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Table 5 Pearson correlation matrix among TOC, sand, silt, clay, and heavy metals in surface sediments from the Futian mangrove forest, South China. TOC TOC Sand Silt Clay Cd Cr Cu Pb Zn

1 0.561⁎ −0.529⁎ −0.674⁎⁎ −0.135 −0.457 −0.428 −0.131 −0.466

Sand

Silt

Clay

Cd

1 −0.997⁎⁎ −0.887⁎⁎ −0.210 −0.231 −0.305 −0.184 −0.257

1 0.846⁎⁎ 0.230 0.202 0.288 0.156 0.225

1 0.073 0.364 0.358 0.321 0.404

1 0.434 0.298 −0.517⁎ 0.201

Cr

Cu

Pb

Zn

1 0.926⁎⁎ 0.097 0.836⁎⁎

1 0.268 0.858⁎⁎

1 0.433

1

⁎ Correlation is significant at 0.05 level (2-tailed). ⁎⁎ Correlation is significant at 0.01 level (2-tailed).

(2.05) b Cd (5.38). The samples were extremely contaminated by Cd, and moderately to heavily contaminated by Zn; the mean Igeo values of Cu were in the range of 1–2, indicating moderate contamination; while the mean Igeo of Pb and Cr were 0–1 and b0, respectively, suggesting non-moderate Pb pollution and no Cr contamination, respectively. Factor analysis (FA) was performed on the correlation matrix between the different parameters, followed by varimax rotation. Table 4 showed the results of principal component analysis (PCA) by applying varimax rotation for TOC, particle sizes and heavy metals. It gave three factors with eigenvalue of N1, explaining 87.936% of the total variance. The first factor accounted for 48.465% of the total variance and was mainly characterized by high positive loadings of silt, clay, Cr, Cu and Zn — showing that clay and silt content played a significant role in raising the levels of Cr, Cu and Zn. The second factor accounted for 21.873% of the total variance and mainly consisted of sand, Cr, Cu and Zn with moderate positive loadings. The third factor accounted for 17.598% of the total variance and mainly consisted of Pb. To determine the impact of sediment characteristics on heavy metal concentration, a correlation coefficient matrix was constructed (Table 5). Previous studies have shown that heavy metal concentrations are positively correlated with fine-grained sediments contents, and organic matter plays an important role in controlling heavy metal concentrations (Schmitt et al., 2002; Gomes et al., 2009; Gan et al., 2013). In the present study, contents of TOC, sand, silt and clay were not significantly related to heavy metal content as shown by their low correlations with heavy metal contents (Table 5). However, there were significant (P b 0.01) positive correlations between several heavy metal pairs—between Cu–Cr (0.926), Zn–Cr (0.836) and Cu–Zn (0.858)—indicating that these metals were associated with each other and may have had common sources in the sediments. Notably, Cd–Pb had a significant negative correlation (− 0.517; P b 0.05), and deserves further investigation.

A dendrogram of heavy metal contents using complete linkage was constructed to analyze relationships among the heavy metals (Fig. 6A). In the dendrogram of mangrove sediment, all heavy metals were grouped into three significant clusters based on the similarities between them. Cluster A consisted of Cr, Cu and Zn. Clusters B and C consisted of Cd and Pb, respectively. Furthermore, the dendrogram of the site observations (Fig. 6B) helped to group the samples with similar characteristics according to their spatial distribution and allowed the three groups to be distinguished from one another. Cluster-1 (CLR-1 in Fig. 6B) grouped samples 1–13; Cluster-2 grouped samples 15 and 16; and Cluster-3 contained only sample 14. The toxicity and mobility of heavy metals in sediments vary greatly among different geochemical forms, and heavy metal fractionation offers a more realistic evaluation of their actual environmental impact (Gao and Chen, 2012; Zhang et al., 2013). Generally, the metals in acid-soluble fraction are mainly introduced by anthropogenic activities, and are more rapidly bioavailable and easily cause environmental toxicity (Fan et al., 2009; Jiang et al., 2010). The reducible fraction can be mobilized when environmental conditions become increasingly reducing, and the oxidizable fraction can be mobilized when environmental conditions become oxidizing (Karbassi and Shankar, 2005). The residual fraction is composed of metals present in an inert condition, being of lattice origin or primary mineral phases, and can be regarded as a measure of contribution by natural sources (Salmonas and Förstner, 1980). In the present study, the percentages of heavy metals from each extraction step are shown in Fig. 7. The heavy metal contents in the fractions were evaluated based on comparison with the sum of the metal contents in the sequential extraction steps, which represented 100%. The percentages of extracted metal varied for the different heavy metal species. Cd, Cu, Pb and Cr had similar distributions of fractions: residual N oxidizable N reducible N water/acid-soluble. The distribution of Zn fractions follows: residual N reducible N oxidizable N water/acidsoluble. Additionally, Cd and Zn had similar S1 fractions (8.06% and

Fig. 6. (A) Dendrogram of selected metals in surface sediment using complete linkage method. (B) Dendrogram of the hierarchical cluster analysis of the heavy metals in the Futian mangrove forest.

Please cite this article as: Li, R., et al., Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China, Marine Pollution Bulletin (2015), http://dx.doi.org/10.1016/j.marpolbul.2015.09.048

R. Li et al. / Marine Pollution Bulletin xxx (2015) xxx–xxx

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Fig. 7. Percentages of heavy metals extracted in each step of the BCR-modified sequential extraction procedure in the Futian mangrove at different sampling sites.

8.35%), which were higher than for other heavy metals (Cu, 0.87%; Pb, 0.91%; and Cr, 0.28%). The potentially mobile fraction is considered the sum of the first three steps from the SEP: acid-soluble, reducible, and the oxidizable fractions (Guillén et al., 2012). In the present study, the percentage of mobile heavy metal fractions increased in the order of Cr (30.72%) b Cd (31.99%) b Cu (42.68%) b Pb (58.45%) b Zn (62.93%). The RAC was first proposed by Perin et al. (1985) and has been widely applied (Huang et al., 2011; Sundaray et al., 2011; Kumar et al., 2012) to evaluate heavy metal pollution in sediments by labeling the percentage of the water/acid-soluble fraction. The environmental risk assessment results according to RAC were shown in Fig. 8. It can be seen that the percentages of heavy metals in the 16 sediment sites associated with the water/acid-soluble fraction (F1) varied within the range of 0.14%–12.70%. In detail, the environmental risk values for Cr in all sites were b 1%, indicating no risk for Cr in this mangrove ecosystem. Similarly, there were no risks of Cu except for site 13, which was of low risk to the environment. Pb in sites 3–5 and 9 showed low risk, with no Pb risk for all other sites. Cd in all sites had b 10% bound to the F1 fraction, reflecting a low risk to the environment. Generally, there was medium risk for some metals with F1 proportions in the range of 11%–30%. In this study, Zn in sites 5, 9, 12 and 13 showed medium risk, with low Zn risk for all other sites. Overall, heavy metals introduced by anthropogenic activities did not pose a considerable ecological risk to biota in terms of the speciation. This study analyzed the spatial distribution and ecological risks of heavy metals in surface sediments of the Futian mangrove, South China. The heavy metals distributions were not uniform due to some sediment heterogeneity. The concentrations of Cr, Cu, Pb and Zn were

mostly above their respective background values, particularly for Cd. The sediments had a 21% probability of toxicity based on the mean PEL quotient. Both the Eir and Igeo demonstrated that sediments were contaminated by heavy metals, and Cd was identified as the major heavy metal pollutant in surface sediments. Multivariate analyses (PCA and HCA) suggested that heavy metals were influenced by anthropogenic inputs. All heavy metals were mainly in the non-residual fraction (68.75%–89.35%), without considerable ecological risk to the biota based on RAC.

Acknowledgments This study is supported by the Program of Science and Technology of Shenzhen (JCYJ20120829170028566, JCYJ20140903101847739, JCYJ20130331145022339), and the Program of National Natural Science Foundation of China (31400446). Rongyu Li is responsible for the operation of this research and writing this article. Minwei Chai and Guoyu Qiu are the instructors for this research, and provided many useful suggestions. Ruili Li, Xiaoxue Shen and Hualin Xu made a great contribution to the revision of this article, and provided much help in the operation of this research.

References Bai, J., Xiao, R., Cui, B., Zhang, K., Wang, Q., Liu, X., Gao, H., 2011. Assessment of heavy metal pollution in wetland soils from the young and old reclaimed regions in the Pearl River Estuary, South China. Environ. Pollut. 159, 817–824.

Please cite this article as: Li, R., et al., Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China, Marine Pollution Bulletin (2015), http://dx.doi.org/10.1016/j.marpolbul.2015.09.048

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Fig. 8. RAC values for heavy metals in the surface sediments in the Futian mangrove forest. The dashed line indicates a RAC value of 1%. The dotted line indicates RAC value of 10%.

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Please cite this article as: Li, R., et al., Heavy metal contamination and ecological risk in Futian mangrove forest sediment in Shenzhen Bay, South China, Marine Pollution Bulletin (2015), http://dx.doi.org/10.1016/j.marpolbul.2015.09.048