Contamination, toxicity and speciation of heavy metals in an industrialized urban river: Implications for the dispersal of heavy metals.

MPB-07444; No of Pages 9 Marine Pollution Bulletin xxx (2016) xxx–xxx

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Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul

Contamination, toxicity and speciation of heavy metals in an industrialized urban river: Implications for the dispersal of heavy metals Qihang Wu a,b,c, Haichao Zhou c, Nora F.Y. Tam c, Yu Tian c, Yang Tan c, Song Zhou d, Qing Li d, Yongheng Chen a,b,⁎, Jonathan Y.S. Leung e,⁎⁎ a

Collaborative Innovation Center of Water Quality Safety and Protection in Pearl River Delta, Guangzhou University, Guangzhou 510006, China Key Laboratory of Water Quality Safety and Protection in Pearl River Delta (Ministry of Education), Guangzhou University, Guangzhou 510006, China Department of Biology and Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China d School of Civil Engineering, Guangzhou University, Guangzhou 510006, China e School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, Australia b c

a r t i c l e

i n f o

Article history: Received 24 November 2015 Received in revised form 22 January 2016 Accepted 25 January 2016 Available online xxxx Keywords: Contamination Dispersal Heavy metal Speciation Toxicity Urban river

a b s t r a c t Urban rivers are often utilized by the local residents as water source, but they can be polluted by heavy metals due to industrialization. Here, the concentrations, toxicity, speciation and vertical profiles of heavy metals in sediment were examined to evaluate their impact, dispersal and temporal variation in Dongbao River. Results showed that the sediment in the industrialized areas was seriously contaminated with Cr, Cu and Ni which posed acute toxicity. Heavy metals, except Cr and Pb, were mainly associated with non-residual fractions, indicating their high mobility and bioavailability. The non-industrialized areas were also seriously contaminated, suggesting the dispersal of heavy metals along the river. The surface sediment could be more contaminated than the deep sediment, indicating the recent pollution events. Overall, when the point sources are not properly regulated, intense industrialization can cause both serious contamination and dispersal of heavy metals, which have farreaching consequences in public health and environment. © 2016 Published by Elsevier Ltd.

1. Introduction Despite the advance in sewage treatment technologies, water pollution caused by sewage discharge has still been a serious problem in many developing countries due to the high operating cost of sewage treatment facilities as well as lack of effective management and enforcement (e.g. Singh et al., 2002; Ikenaka et al., 2010; Louhi et al., 2012; Chen et al., 2015). Therefore, regular monitoring is indispensable to evaluate the impact of pollutants on public health and environment. Among various pollutants, heavy metals are of special concern because of their toxicity, persistence and bioavailability (Montouris et al., 2002). In the aquatic environment, heavy metals can readily accumulate in sediment through adsorption, and thus sediment per se is a good monitoring tool for heavy metals (Soares et al., 1999). Nevertheless, solely measuring the total concentration of heavy metals in sediment is still insufficient to accurately evaluate their impact because they can be released from the sediment to the water column upon disturbance or alteration in the physico-chemical conditions (de Miguel et al.,

⁎ Correspondence to: Y. Chen, Collaborative Innovation Center of Water Quality Safety and Protection in Pearl River Delta, Guangzhou University, Guangzhou 510006, China. ⁎⁎ Corresponding author. E-mail addresses: [email protected] (Y. Chen), [email protected] (J.Y.S. Leung).

2005). The remobilized heavy metals are subsequently dispersed by water current and potentially contaminate the pristine areas, such as estuaries and wetlands (Williams et al., 1994; Li et al., 2007; Bai et al., 2011; Wu et al., 2016). In addition, the mobility, toxicity and bioavailability of heavy metals depend on the physico-chemical form rather than total concentration (Tack and Verloo, 1995). As such, studying the speciation of heavy metals is crucial to fathom their behavior and biological risk in sediment. Compared to other developing countries, China suffers the most from water pollution due to rapid economic growth and intense industrialization. In particular, the Pearl River Delta is one of the most urbanized and industrialized regions, accounting for more than 10% of the National Gross Domestic Product (National Bureau of Statistics of China, http://data.stats.gov.cn). The intense industrialization inevitably leads to heavy metal pollution in this region primarily due to sewage discharge from the factories (e.g. metal and electronics industries) (Cheung et al., 2003; Liu et al., 2011; Ye et al., 2012; Wu et al., 2014). To date, heavy metal pollution in the Pearl River Estuary has been well-studied (Wang et al., 2013), while substantially overlooked is heavy metal pollution in urban rivers. As the Pearl River Estuary is connected to numerous urban rivers, studying heavy metal pollution in these urban rivers can provide vital information for identifying the pollution sources in this region. More importantly, as urban rivers are often utilized, either purposely or accidentally, by local residents as

http://dx.doi.org/10.1016/j.marpolbul.2016.01.043 0025-326X/© 2016 Published by Elsevier Ltd.

Please cite this article as: Wu, Q., et al., Contamination, toxicity and speciation of heavy metals in an industrialized urban river: Implications for the dispersal of heavy m..., Marine Pollution Bulletin (2016), http://dx.doi.org/10.1016/j.marpolbul.2016.01.043

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Q. Wu et al. / Marine Pollution Bulletin xxx (2016) xxx–xxx

water source, noxious effects on human health could be incurred due to heavy metal pollution (e.g. Singh et al., 2002; Islam et al., 2015). Furthermore, physico-chemical properties and hydrological conditions in riverine sediment are more prone to drastic changes than those in marine sediment owing to human disturbance; therefore, the impact of remobilization and dispersal of heavy metals cannot be overlooked. Here, we chose Dongbao River in Shenzhen (commonly known as Maozhou River or Black River by the local residents) as the model site to illustrate the impact and dispersal of heavy metals. From the early 1980s to 1990s, Shenzhen was urbanized and industrialized rapidly, and has become the first Special Economic Zone in China. Industrialization is extremely intense in the catchment area of Dongbao River, where more than 7000 factories from metal and electronics industries can be found. As most of the factories are primitive and the sewage is discharged without proper treatment, Dongbao River is regarded as one of the most polluted urban rivers in China. To mitigate this problem, the Shenzhen government has amended the regulations and made more inspections in recent years, but the effectiveness of these measures remains unknown. In the present study, the concentrations and speciation of heavy metals in the surface sediment along the river were determined to elucidate their toxicity, biological risk and dispersal. Their correlation with sediment properties, including pH, total organic matter and particle size was also studied. Furthermore, the vertical profiles of heavy metals were examined to estimate the effectiveness of the mitigation measures taken by the Shenzhen government. The findings are not only vital for protecting public health and environment in this region, but also valuable to understand the impact and behavior of heavy metals due to intense industrialization. 2. Materials and methods 2.1. Study site and sampling method Dongbao River (22°46′N, 113°47′E), which is connected to the Pearl River Estuary, was selected as the study site. Based on our observation, factories mainly from metal and electronics industries were ubiquitous on both flanks of the river. The water in the river was dark and stinky, and the flow rate was low. Sewage discharged from the drainage pipes was commonly observed. Sampling was conducted in December 2013 during low tide. A total of seven sampling points along the river were chosen: (1–4) Points A–D located in the industrialized area; (5) confluence; (6) outlet where a mangrove is found; (7) mudflat located at the lower intertidal of the mangrove (Fig. 1). At each sampling point, three random replicates of surface sediment (ca. 8 cm from the top) were collected by a spade. To study the vertical profile, three random replicates of core sediment were collected by a PVC core sampler (10 cm in diameter × 48 cm deep) at Point A, Point C, confluence and outlet. The sediment sample in each core was cut into six layers from the top at 8 cm depth interval by a PVC knife.

spectrometer (AAnalyst 800, Perkin-Elmer Instruments, USA). To estimate the accuracy of this method, a certified reference material from the State Oceanic Administration of China (GBW 07334) was used for recovery test. The recoveries for all heavy metals ranged from 89.6 to 98.5% (RSD: 5.65–8.53%). 2.3. Sequential extraction of heavy metals The method proposed by Rauret et al. (1999) with minor modifications was applied for the three-step sequential extraction of heavy metals, which is summarized as follows: (1) Acid soluble fraction: Approximately 0.5 g freeze-dried sediment was transferred into a 50 ml polyethylene centrifuge tube, followed by adding 20 ml 0.11 M acetic acid for extraction. The mixture was then sonicated for 30 min. (2) Reducible fraction: Heavy metals in the residue after the first step were extracted by 20 ml 0.5 M hydroxylamine hydrochloride, followed by 30 min sonication. (3) Oxidizable fraction: The residue after the second step was digested by 5 ml 30% hydrogen peroxide (pH 2.2) at room temperature for 1 h. The centrifuge tube was stoppered and shaken occasionally. Then, another 5 ml 30% hydrogen peroxide was added to the centrifuge tube which was then heated up to 85 °C with occasional shaking for 1 h. After cooling at room temperature, heavy metals in the residue were extracted by 25 ml 1.0 M ammonium acetate (pH 2.0), followed by 30 min sonication. (4) Residual fraction: Heavy metal concentrations in the residue after the third step were measured using the method described in Section 2.2. Between each extraction step, the supernatant used for heavy metal analysis was separated from the solid residue by centrifugation at 3500 rpm for 15 min. The residue was then rinsed with 10 ml deionized water twice and shaken for 15 min, followed by centrifugation at 3500 rpm for 15 min so that the supernatant was discarded.

2.4. Statistical analyses Toxic unit (TU), defined as the ratio of heavy metal concentration to probable effects level (PEL), was calculated to evaluate the toxicity of each heavy metal (Pedersen et al., 1998). The potential acute toxicity of heavy metals was estimated by the sum of individual TU. Permutational analysis of variance (PERMANOVA), followed by a pairwise test, was applied to determine the spatial variation in sediment properties and heavy metals using software PRIMER 6.0 with PERMANOVA + add-on. Pearson correlation analysis was applied to correlate heavy metals with sediment properties using software SPSS 20.0 for Windows.

2.2. Analyses of sediment properties and heavy metals

3. Results

The sediment samples were freeze-dried, ground into powder and passed through a 2 mm sieve, after measuring the particle size using a particle size analyzer (S3500, Microtrac, USA). For pH, the sediment sample was mixed with deionized water (1:5, w/v), followed by measuring the pH of the mixture using a pH meter (pH 3000, STEP Systems, Germany). Total organic matter (TOM) was determined by mass loss upon ignition at 550 °C for 6 h. To extract heavy metals, ca. 0.3 g sediment was digested by a mixture of concentrated hydrochloric acid and nitric acid (3:1, v/v) using automatic digestion block (ST40, Beijing Polytech Instrument Ltd., China). The concentrations of heavy metals in the extract, including chromium (Cr), copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn), were determined by inductively coupled plasma-optima emission spectrometry (Optima 5300DV, Perkin-Elmer Instruments, USA), while cadmium (Cd) by atomic absorption

3.1. Sediment properties and concentrations of heavy metals The pH of sediment ranged from 6.90 to 7.40, except Point A (5.97) and Point B (6.16) at which the sediment was slightly acidic (Table 1). Total organic matter was generally low at all sampling points, ranging from 0.87% to 1.87%. Significantly higher TOM was found at Points A, B and C than that at other sampling points. The sediment was generally sandy in the region, except Point D at which the sediment was relatively silty. Compared to the guideline values in China (GB 18668-2002), heavy metal pollution was very severe in Dongbao River (Table 2). At all sampling points, the concentration of Cd (0.61–1.33 mg kg − 1) exceeded the Grade I guideline value which aims to protect mariculture and marine protected areas. The concentrations of Cr (350–



3

Fig. 1. The sampling map in the present study. Three random replicates were collected at each sampling point for surface sediment, while another three were for core sediment at Point A, Point C, confluence and outlet. The arrows indicate the direction of water current.

1086 mg kg− 1) and Cu (825–2937 mg kg− 1) even exceeded their respective Grade III guideline values. However, the concentration of Pb (47.8–96.5 mg kg − 1 ) was low enough to meet the Grade II guideline value and even Grade I guideline value at Points C and D. The concentration of Zn at Points A, B, C and confluence (646– 725 mg kg− 1 ) slightly exceeded the Grade III guideline value. To evaluate the biological risk, threshold effects level (TEL) and probable effects level (PEL) were used where adverse biological effects are frequently observed if the concentrations of heavy metals exceed their respective PEL (Macdonald et al., 1996). In this regard, adverse biological effects were frequently observed due to Cr, Cu, Ni and Zn (Table 2). Considering the toxic units, ∑TU was primarily contributed by Cu, followed by Ni (Fig. 2). According to Pedersen et al. (1998), acute toxicity of heavy metals in the surface sediment in the region was found as ∑TU was greater than 6 at all sampling points. In short, the surface sediment at Points B, C, confluence and outlet generally had higher concentrations of heavy metals and hence biological risk than other sampling points. The correlations between sediment properties and heavy metals are shown in Table 3. Total organic matter was positively correlated with Cr, Pb and Zn, while pH was negatively correlated with Zn. Clay fraction was negatively correlated with Cd, Cr, Pb and Zn. The heavy metals

were positively correlated with each other with few exceptions (Table 3). 3.2. Speciation of heavy metals The speciation of each heavy metal is illustrated in Fig. 3. Cd was highly associated with acid soluble fraction (N 35%, except Point B), followed by reducible and oxidizable fractions (Fig. 3a). Residual fraction only contributed less than 12% to the total concentration. Cr existed mostly in residual fraction (N 55%, except Point A) (Fig. 3b), but oxidizable fraction was more dominant at Point A (ca. 80%). Reducible and acid soluble fractions only contributed less than 15% in total. The acid soluble, oxidizable and residual fractions of Cu had similar proportion, but varied spatially (Fig. 3c). For example, higher proportion of residual fraction and lower proportion of acid soluble fraction were found at Point D. The speciation of Ni also varied spatially, where residual fraction was highly dominant at Point D (N60%), but its contribution was less than 4% at the confluence and outlet (Fig. 3d). Acid soluble fraction was generally more dominant than other fractions. Pb was mainly associated with residual fraction, followed by reducible fraction (Fig. 3e). Oxidizable and acid soluble fractions had limited contribution at most of the sampling points. Zn

Table 1 The physico-chemical properties of sediment at different sampling points (mean ± S.D., n = 3). The same superscript letter within each sediment property indicates no significant difference according to PERMANOVA (p N 0.05). Sampling point

pH

Total organic matter (%)

Sand (%)

Silt (%)

Clay (%)

A B C D Confluence Outlet Mudflat

5.97 ± 0.19c 6.16 ± 0.12c 6.90 ± 0.04b 6.98 ± 0.09b 7.29 ± 0.08a 7.07 ± 0.38ab 7.40 ± 0.10a

1.83 ± 0.68ab 1.87 ± 0.18a 1.71 ± 0.19a 0.87 ± 0.21c 1.23 ± 0.11bc 1.19 ± 0.14bc 1.15 ± 0.26bc

64.4 ± 3.63a 56.9 ± 9.30bc 61.4 ± 6.32ab 44.4 ± 1.24c 71.0 ± 6.16a 65.0 ± 4.12a 57.8 ± 1.49b

35.3 ± 3.42b 42.4 ± 8.67ab 36.8 ± 5.93b 51.9 ± 2.52a 28.3 ± 6.27b 32.3 ± 3.79b 38.9 ± 0.94b

0.29 ± 0.30c 0.72 ± 0.67bc 1.85 ± 0.41ab 3.73 ± 1.28a 0.70 ± 0.15c 2.65 ± 1.19a 3.30 ± 0.60a


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Table 2 The concentrations of heavy metals (mg kg−1) at different sampling points (mean ± S.D., n = 3). The same superscript letter within each heavy metal indicates no significant difference according to PERMANOVA (p N 0.05). Sampling point

Cd

Cr

Cu

Ni

Pb

Zn

A B C D Confluence Outlet Mudflat Background⁎

1.10 ± 0.11ab 1.33 ± 0.22a 1.24 ± 0.29ab 0.61 ± 0.09c 1.27 ± 0.16a 1.19 ± 0.17ab 0.81 ± 0.05b 0.056 0.5 1.5 5 0.68 4.21

556 ± 43b 1086 ± 278a 704 ± 87b 350 ± 11c 713 ± 169ab 510 ± 87bc 368 ± 64c 50.5 80 150 270 52.3 160

825 ± 19d 2937 ± 78a 2517 ± 266ab 889 ± 180d 2602 ± 336ab 2010 ± 369bc 1422 ± 334cd 17 35 100 200 18.7 108

285 ± 96ab 362 ± 29a 393 ± 203a 205 ± 19b 412 ± 93a 312 ± 47a 222 ± 39b 18.2 – – – 15.9 42.8

72.1 ± 5.96b 96.5 ± 11.3a 59.3 ± 11.0bc 47.8 ± 8.01c 69.9 ± 6.17b 63.9 ± 7.20b 63.7 ± 5.82b 36 60 130 250 30.2 112

693 ± 95a 725 ± 46a 649 ± 52a 363 ± 62bc 646 ± 30a 413 ± 26b 286 ± 22c 47.3 150 350 600 124 271

Grade I^ Grade II^ Grade III^ TEL# PEL#

⁎ Background level in Guangdong Province (Wei et al., 1990). ^ National Standard of PR China (GB 18668-2002). # Sediment quality guideline levels (Macdonald et al., 1996).

existed mostly in acid soluble fraction, followed by reducible fraction (Fig. 3f). Residual fraction had higher contribution in the mudflat. In short, Cd and Zn were the two most mobile heavy metals, while Pb and Cr were the least mobile based on their speciation. The generally low proportion of residual fraction (except Pb and Cr) also indicated that the sediment in Dongbao River was heavily contaminated with heavy metals. The spatial variation in speciation of heavy metals was not discernible and consistent.

3.3. Vertical profiles of heavy metals In general, the concentrations of heavy metals along the depth gradient were not obvious at the confluence and outlet, except that the concentrations of Cd, Cr Ni and Pb suddenly increased from −40 to −48 cm at the confluence (Fig. 4a, b, d and e). In contrast, the variation along the depth gradient was obvious at Points A and C. At Point A, the concentrations of heavy metals decreased from the surface to −24 cm and then increased from −24 cm to −32 cm. Then, the concentrations of Cd, Pb and Zn remained more or less the same from −33 cm to −48 cm (Fig. 4a, e and f), while Cr, Cu and Ni gradually decreased with depth (Fig. 4b, c and d). At Point C, the concentrations of all heavy metals also decreased from the surface to − 24 cm, but increased gradually with depth thereafter.

4. Discussion 4.1. Heavy metal pollution in Dongbao River It is well-documented that heavy metal pollution is a serious problem in the Pearl River Estuary, which is caused by the influx from the distributaries in the region (Cheung et al., 2003; Li et al., 2007; Bai et al., 2011; Wu et al., 2016); however, the major pollution sources are not clearly identified. Here, we reveal the extreme contamination of heavy metals in Dongbao River given their concentrations and toxicity. Particularly, the concentrations of Cr, Cu and Ni reached the alarming level. For example, the concentration of Cr at Points B, C and confluence was N2 times higher than the Grade III guideline value and N 4 times higher than PEL; the concentration of Cu at Points B, C, confluence and outlet was N10 times higher than the Grade III guideline value and N 20 times higher than PEL; the concentration of Ni was N 5 times higher than PEL. The serious contamination of heavy metals results in extreme acute toxicity in the sediment (i.e. high ∑TU), primarily due to Cu. This finding was expected since factories from metal and electronics industries are numerous in the catchment area of Dongbao River. For instance, metallurgy and print circuit board manufacturing are prevalent in the region and regarded as the major sources of Cu; mechanical engineering and steel industry are the sources of Cr, Ni and Zn (Cheung et al., 2003). More importantly, it is not uncommon to observe that sewage is discharged without proper treatment. The low flow rate in the river, which allows more time for adsorption of heavy metals and deposition of suspended particles, also causes the serious contamination. Interestingly, Cd is usually highly contaminated in the Pearl River Estuary

Table 3 The correlation coefficients between sediment properties and heavy metals (n = 21).

pH TOM Sand Silt Clay Cd Cr Cu Ni Pb Zn

Fig. 2. The toxicity unit (∑TU) of heavy metals at different sampling points (mean, n = 3).

Cd

Cr

Cu

Ni

Pb

Zn

−0.265 0.423 0.447⁎ −0.387 −0.555⁎⁎

−0.418 0.745⁎⁎⁎ 0.322 −0.260 −0.620⁎⁎

0.060 0.348 0.164 −0.143 −0.296

−0.090 0.190 0.379 −0.352 −0.414

−0.336 0.500⁎ 0.291 −0.187 −0.643⁎⁎⁎

−0.670⁎⁎⁎ 0.740⁎⁎⁎ 0.319 −0.238 −0.724⁎⁎⁎

– 0.701⁎⁎⁎ 0.709⁎⁎⁎ 0.856⁎⁎⁎ 0.616⁎⁎⁎ 0.534⁎

– 0.730⁎⁎⁎ 0.549⁎⁎ 0.721⁎⁎⁎ 0.757⁎⁎⁎

– 0.653⁎⁎⁎ 0.495⁎ 0.362

– 0.475⁎ 0.383

– 0.426

–

⁎ p ≤ 0.05. ⁎⁎ p ≤ 0.01. ⁎⁎⁎ p ≤ 0.001.



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Fig. 3. The chemical fractionation of (a) Cd, (b) Cr, (c) Cu, (d) Ni, (e) Pb and (f) Zn (%) in the surface sediment at different sampling points (mean, n = 3).

due to the prevalence of electroplating industry in the region (Cheung et al., 2003; Li et al., 2007), but it was only slightly contaminated in Dongbao River. This unexpected finding could be due to its high mobility in the sediment (see Section 4.3 for more discussion). Compared to other rivers in the Pearl River Delta, which are also impacted by urbanization and industrialization, the concentrations of Cr, Cu, Ni and Zn in Dongbao River are much higher (Table 4). As the catchment area of Dongbao River is the largest manufacturing base of metal and electronics industries in the Pearl River Delta (Mai et al., 2005), we suggest that the degree of heavy metal pollution in urban rivers increases with the degree of industrialization. This proposition is underpinned by the fact that the highest concentrations of Cr, Cu and Ni were found in Dongbao River, compared to the less industrialized urban rivers in China and other developing countries (with the only exception of Cr in Buriganga River in Bangladesh). In other words, Dongbao River is probably the primary contributor of heavy metal pollution in the Pearl River Estuary.

4.2. Spatial variation of heavy metals The spatial pattern of heavy metals can provide an important insight into their potential sources and dispersal in the region. Within the industrialized region (i.e. Points A–D and confluence), the concentrations of heavy metals showed remarkable fluctuations. For example, Point B had significantly higher concentrations than Point A, despite their close proximity; similar observation was found between Points C and D. In addition, we expected that the concentrations of heavy metals at the confluence would be the highest due to the heavy metal input from both tributaries, but the results did not evidently support this prediction. Instead, the results suggest that heavy metal pollution in Dongbao River is primarily influenced by point sources, while dispersal by water current only plays a secondary role. The contribution of the latter is manifested by the significant positive correlations among heavy metals in the region, implying that they originated from the same sources. Moreover, if heavy metals are dispersed by water current,


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Fig. 4. The concentrations of (a) Cd, (b) Cr, (c) Cu, (d) Ni, (e) Pb and (f) Zn (mg kg−1) along the depth gradient at Point A, Point C, confluence and outlet (mean ± S.D., n = 3).

their concentrations along the river should decrease with the distance from the point sources in view of dilution effect (Zheng et al., 2008). Our results substantiate this prediction as the concentrations of heavy metals gradually decreased from the confluence to the mudflat. Nevertheless, the extreme acute toxicity and concentrations of heavy metals in the outlet and mudflat indicate that the dilution effect was inadequate to minimize their impact (Xiao et al., 2013). Consequently, the mangrove suffers from heavy metal contamination, whereas the water containing heavy metals enters and contaminates the Pearl River Estuary.

Sediment properties have been used to decipher the spatial variation of heavy metals (Du Laing et al., 2009; Wang et al., 2011; Xiao et al., 2013). The positive correlation between TOM and heavy metals is due to the fact that organic matter provides sorption sites to complex with heavy metals (Du Laing et al., 2009). The negative correlation between pH and heavy metals is probably attributed to discharge of sewage, which usually contains heavy metals in acidic solution. In contrast to a previous study (Zhao et al., 2013), an unexpected positive (negative) correlation was found between sand (clay) fraction and heavy metals. The reasons are still unclear and further investigation is needed.



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Table 4 The mean concentrations of heavy metals (mg kg−1) in the riverine sediment from different developing countries. Location

Country

Dongbao River

South China 1.08 (0.61–1.33) 612 (350–1086)

Cd

Cr

Cu

Shiqiao River Shawan River Shenzhen River Beijiang River

South China 2.79 South China 2.99 South China 0.61–7.78 South China 0.41 (0.18–2.86)

Ni

133 109 1.99–230 200 (14.8–348)

1886 (825–2937) 100 75 2.85–925 116 (36.6–243)

Pearl River, Guangzhou South China 1.80 (0.52–4.17) 97.4 (11.1–215) Ganjiang River South China 17.3 18.3 Xiangjiang River China 13.4 (0.96–55.1) 65.7 (27.1–110)

352 (102–828) 48.3 60.9 (19.3–187)

Xiawangang River Lianshan River Wuli River

China 13.8–173 North China 53.2 (25.5–98.8) North China 11.1 (8.04–17.8)

N.A. N.A. N.A.

50.2–173 116 (67.0–187) 50.6 (32.2–85.5)

Hun River

North China

95.9 (63.8–137)

289 (13.8–2391)

Hong River

North China 1.08 (0.17–4.22) 86.6 (42.2–127)

23.2 (9.09–34.8)

Yinge River

North China 0.80 (0.26–2.27) 94.2 (66.9–145)

25.6 (13.5–41.6)

Buriganga River Korotoa River Yamuna River Gomati River Day River Seybouse River

Bangladesh Bangladesh India India Morocco Algeria

225 82 160 63 109 (32.7–741) 9.50

13.1 (0.15–135)

5.90 1.50 2.82 0.82 1.27 (0.67–6.27) N.A.

709 118 342 158 102 (52.3–312) 145

313 (205–412) 66 53 N.A. 36.7 (10.0–49.5) N.A. 32.0 39.5 (18.0–65.1) N.A. 57.4 (35.7–110) 31.5 (28.3–35.9) 40.5 (22.3–76.8) 35.8 (15.8–51.7) 36.9 (25.9–58.2) 137 103 111 63 N.A. 16.8

Pb 67.6 (47.8–96.5) 96 86 11.2–206 189 (81.8–341) 104 (43.9–220) 61.9 112 (33.0–312) 308–1050 112 (62.6–185) 57.6 (40.2–98.5) 64.0 (2.07–380) 23.3 (2.54–99.5) 20.4 (4.67–71.4) 478 63 55 37 109 (72.9–140) 476

Zn

Reference

539 (286–725)

The present study

327 253 23.3–605 189 (41.2–289)

Xiao et al., 2013 Xiao et al., 2013 Huang et al., 2012 He et al., 2014

387 (173–561) 130 390 (42.1–1208) 1898–5076 634 (471–965) 257 (154–474)

Wang et al., 2011 Ji et al., 2014 Jiang and Sun, 2014

886 (41.9–6485) 472 (69.7–2558) 470 (31.0–2042) 958 N.A. 366 161 100 (49.8–149) 1141

Jiang et al., 2013 Li et al., 2012 Li et al., 2012 Guo and He, 2013 Guo and He, 2013 Guo and He, 2013 Mohiuddin et al., 2011 Islam et al., 2015 Singh et al., 2002 Singh et al., 2002 Barakat et al., 2012 Louhi et al., 2012

N.A.: not available.

4.3. Speciation of heavy metals Heavy metals are not permanently bound to sediment as they can exist in different physico-chemical forms, depending on the environmental conditions. As such, human disturbance can potentially remobilize heavy metals, causing contamination in the surrounding areas. Studying the speciation of heavy metals can shed light on their toxicity, bioavailability and distribution (Tack and Verloo, 1995). In the present study, more than 90% of Cd was associated with non-residual fractions, indicating its high mobility which is also demonstrated in previous studies (Man et al., 2004; Yuan et al., 2004; Li et al., 2007; Wang et al., 2011). In particular, the high proportion of acid soluble fraction could be ascribed to the presence of chloride in water, which can readily complex with Cd and thus increase its mobility and bioavailability (Norvell et al., 2000). The high mobility of Cd could, at least partly, explain why it was relatively less contaminated than other heavy metals in Dongbao River, despite the prevalence of electroplating industry in the region. However, the high mobility of Cd also implies that it is more difficult to avoid its dispersal than other heavy metals, explaining why Cd is generally regarded as one of the most contaminated heavy metals in the Pearl River Estuary. Furthermore, since the sediment was anoxic (ca. –200 mV by in situ measurement), Cd can be remobilized upon re-oxygenation (e.g. dredging) in light of its considerable oxidizable fraction in the sediment (Petersen et al., 1995), potentially causing further contamination. Cu existed mostly in non-residual fractions, which is contradictory to some previous studies (Fernandes, 1997; Ramos et al., 1999; Li et al., 2001, 2007; Gao et al., 2010). The unexpected high mobility or low proportion of residual fraction of Cu is probably by virtue of its severe contamination in Dongbao River. On the other hand, the high proportion of oxidizable fraction is due to the fact that Cu is readily bound to clay or organic matter (Pardo et al., 1993; Fytianos and Lourantou, 2004; Li et al., 2007). Cr was mainly associated with residual fraction, indicating its low mobility. The higher proportion of oxidizable fraction at Points A and B indicates that Cr prefers to form complexes with organic matter. Same as Cd, the considerable proportion of oxidizable fraction of Cr and Cu implies that they can be remobilized upon re-oxygenation of sediment, potentially causing more harmful effects

to the environment. In contrast to previous studies (Li et al., 2001; Yuan et al., 2004; Gao et al., 2010), Zn and Ni were mobile, indicated by the low proportion of residual fraction. The high mobility of Ni and Zn is probably attributed to their serious contamination in Dongbao River. As also shown in previous studies (Fernandes, 1997; Li et al., 2001; Yuan et al., 2004), Pb was largely associated with residual fraction. The dominance of residual fraction is in agreement with the relatively low contamination of Pb in Dongbao River. The considerable proportion of reducible fraction in Ni, Pb and Zn suggests that they can form a stable complex with Fe/Mn oxides (Pardo et al., 1993; Fernandes, 1997; Ramos et al., 1999). 4.4. Vertical profiles of heavy metals Vertical profiles of heavy metals can provide a quick insight into their degree of pollution over time (Xiao et al., 2013; Wu et al., 2014). The concentrations of heavy metals at the confluence and outlet were more or less the same along the depth gradient, meaning that the degree of pollution remains similar over time. Distinct vertical profiles were observed at Points A and C where the concentrations of heavy metals decreased from the surface to − 24 cm, indicating the recent pollution events. Nevertheless, the increase in concentrations from −24 cm to −48 cm could be explained by either more severe pollution events in the past or downward movement of heavy metals due to chemical exchange of soluble fraction (Man et al., 2004; Yuan et al., 2004; Li et al., 2007, 2011). If the latter is true, heavy metals with higher mobility should have higher concentration in the deep sediment. The concentrations of mobile metals (i.e. Cu, Ni and Zn), however, did not show the gradual increase with depth, except Cd. Moreover, opposite trends were observed between Points A and C, implying that downward movement of heavy metals is unlikely. Therefore, we conclude that the vertical profiles of heavy metals are mainly influenced by point sources and can be used to generally reflect the degree of industrial activities over time. Given the vertical profiles, the management efforts to alleviate heavy metal pollution in the region were still inadequate. We recommend building effective sewage treatment plants and constructed wetlands to immobilize and extract heavy metals so that the impact and dispersal of heavy metals can be minimized. More inspections should


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be made to penalize those factories without proper treatment of sewage. Regular monitoring is still necessary to evaluate the effectiveness of the management measures. 5. Conclusion Industrialization is prevalent in the developing countries and its impact due to heavy metal pollution on human health and environment cannot be ignored. This study unraveled that intense industrialization in Dongbao River can lead to serious contamination and acute toxicity of heavy metals (especially Cr, Cu and Ni) in sediment. Moreover, heavy metals, except Cr and Pb, were mainly associated with non-residual fractions, meaning that they were mobile and bioavailable. Although Cd and Zn were less contaminated, their high mobility implies their high dispersal ability, explaining why they are highly contaminated in the Pearl River Estuary. Therefore, if management efforts are inadequate to control the point sources, intense industrialization not only results in heavy metal contamination on local scale, but regional scale due to dispersal. Acknowledgments The project is supported by Guangdong Province Public Welfare Research and Capacity Building Project (2015 A020215036), Science and Technology Planning Project of Guangdong Province (No. 2012B061700058) and Collaborative Innovation Major Projects of Guangzhou Education Bureau (13xt02), Educational System Innovation Team Project of Guangzhou Education Bureau (13C02) and the National Natural Science Foundation of China (Nos. 41573119, 41373118 and 21307120). References Bai, J.H., Xiao, R., Cui, B.S., Zhang, K.J., Wang, Q.G., Liu, X.H., Gao, H.F., Huang, L.B., 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. Barakat, A., Baghdadi, M.E., Rais, J., Nadem, S., 2012. Assessment of heavy metal in surface sediments of Day River at Beni-Mellal region, Morocco. Res. J. Environ. Earth Sci. 4, 797–806. Chen, M., Zeng, G., Zhang, J., Xu, P., Chen, A., Lu, L., 2015. Global landscape of total organic carbon, nitrogen and phosphorus in lake water. Sci. Rep. 5, 15043. Cheung, K.C., Poon, B.H.T., Lan, C.Y., Wong, M.H., 2003. Assessment of metal and nutrient concentrations in river water and sediment collected from then cities in the Pearl River Delta, South China. Chemosphere 52, 1431–1440. de Miguel, E., Charlesworth, S., Ordóñez, A., Seijas, E., 2005. Geochemical fingerprints and controls in the sediments of an urban river: River Manzanares, Madrid (Spain). Sci. Total Environ. 340, 137–148. Du Laing, G., Rinklebe, J., Vandecasteele, B., Meers, E., Tack, F.M.G., 2009. Trace metal behaviour in estuarine and riverine floodplain soils and sediments: a review. Sci. Total Environ. 407, 3972–3985. Fernandes, H.M., 1997. Heavy metal distribution in sediments and ecological risk assessment: the role of diagenetic processes in reducing metal toxicity in bottom sediment. Environ. Pollut. 97, 317–325. Fytianos, K., Lourantou, A., 2004. Speciation of elements in sediment samples collected at lakes Volvi and Koronia, N. Greece. Environ. Int. 30, 11–17. Gao, X., Chen, C.T.A., Wang, G., Xue, Q., Tang, C., Chen, S., 2010. Environmental status of Daya Bay surface sediments inferred from a sequential extraction technique. Estuar. Coast. Shelf Sci. 86, 369–378. Guo, R., He, X., 2013. Spatial variations and ecological risk assessment of heavy metals in surface sediments on the upper reaches of Hun River, Northeast China. Environ. Earth Sci. 70, 1083–1090. He, J., Zhang, H., Zhang, H., Guo, X., Song, M., Zhang, J., Li, X., 2014. Ecological risk and economic loss estimation of heavy metals pollution in the Beijiang River. Ecol. Chem. Eng. 21, 189–199. Huang, Y., Zhu, W., Le, M., Lu, X., 2012. Temporal and spatial variations of heavy metals in urban riverine sediment: an example of Shenzhen River, Pearl River Delta, China. Quat. Int. 282, 145–151. Ikenaka, Y., Nakayama, S.M.M., Muzandu, K., Choongo, K., Teraoka, H., Mizuno, N., Ishizuka, M., 2010. Heavy metal contamination of soil and sediment in Zambia. Afr. J. Environ. Sci. Technol. 4, 729–739. Islam, M.S., Ahmed, M.K., Raknuzzaman, M., Habibullah-Al-Mamun, M., Islam, M.K., 2015. Heavy metal pollution in surface water and sediment: a preliminary assessment of an urban river in a developing country. Ecol. Indic. 48, 285–291. Ji, Y., Zhang, J., Huang, X., Bai, C., Chen, X., 2014. Investigation and assessment of heavy metals in surface sediments of Ganjiang River, China. J. Environ. Biol. 35, 1173–1179.

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