Ecological Risk of Heavy Metals in Sediment Around Techeng Island Special Marine Reserves in Zhanjiang Bay

ZHANG Cuiping, ZHENG Zhaoyong, YAO Shaohui, JIA Houlei, XIAN Xianheng, and WANG Liang,

Ecological Risk of Heavy Metals in Sediment Around Techeng Island Special Marine Reserves in Zhanjiang Bay

ZHANG Cuiping1), ZHENG Zhaoyong1), YAO Shaohui2), JIA Houlei1), XIAN Xianheng1), and WANG Liang1),*

1),,510300,2),510301,

The concentrations of five metals (Cu, Pb, Zn, Cd and Hg) were measured in sediments obtained before and after the establishment of Techeng Island Special Marine Reserves (TCISMR) in Zhanjiang Bay to evaluate the ecological risk of heavy metals. The results showed that average values of potential ecological risk indexes of heavy metals at all stations increased slightly from 32.09 to 30.54 after establishment of TCISMR. Optimal semivariance simulation showed that the contents of five heavy metals have strong spatial correlations in August 2010 (before), while this correlations weakened in April 2013 (after establishment of TCISMR), suggesting that the main sources of heavy metals changed. The Hakanson Risk Index (HRI) values in Donghai levee, central and southern parts of Zhanjiang harbor were high up to 60.13 and 46.46, respectively. And Zhanjiang Bay Channel, the areas around special marine reserves, the artificial reef areas and mangrove areas at south of Techeng Island are the areas with low ecological risk and high ecological value, which should be treated as the prior ecological protection areas. Our study provided a priority control pattern of heavy metal pollution in TCISMR, which greatly benefits the sustainable development and resource protection in Zhanjiang Bay.

Techeng Island Special Marine Reserves; surface sediment; heavy metals; potential ecological risk; prior conservation area

1 Introduction

Mangrove wetland is an important habitat and food source for aquatic organisms and birds, which is a typical ecological system and needs special protection (Yu, 2015; Conrad, 2017). According to the State Oceanic Administration, Techeng Island Special Marine Reserves (TCISMR) of Guangdong is the first approved ma- rine park as special protection areas. The distribution and toxicity of heavy metals have great influence on the construction and development of mangrove wetland habitat (Ramesh., 2009; Niu., 2018), which has also attracted great attentions in the TCISMR in recent years. For example, the decomposition of mangrove plant residue under anaerobic condition releases the heavy metals such as mercury, which can be transported among aquatic organisms, thus threatening human health (Kehrig., 2003; Liang., 2013; Creswell., 2015). The assessment of ecological risk of heavy metal pollution including geochemical cycles, evaluation of human disturbance and bioaccumulation toxicology, has become a hotspot in coastal zone studies (Tarradellas., 2000; Boekhold, 2008; Thomas., 2009; Zhao., 2015).

Pollutants generated by human activities enter the marine environment through various paths. Marine sediments are the main sink and source of heavy metals in the marine ecosystem, which has great influenceon the transport and transformation process of potential toxic heavy metals (Guevara., 2005; Mason., 2006; Armid., 2014). The study done by Srinivasa Reddy (2004) showed the enrichment of heavy metals in the sediments from the Sosiya region in Arun. The sediment enrichment of Pb, Cu, and Zn in Piratininga Lake was consistently correlated with anthropogenic discharge (Huang., 1994). Heavy metals in the marine surface sediments can be released through the water-rock reaction into the bottom water (Feng., 2004), which can produce toxic effects on the benthic organisms, and even endanger the health of the marine ecosystem. The heavy metal content in the sea area around the Techeng Island was relatively high, and the survey in 2009 showed that the exceeded amount of Pb in the southern sea area of Techeng Island was up to 86%. At present, the priority control pattern of heavy metal pollution in the surrounding areas of the special island and marine special protection area is still in blank.

Distribution and toxicity of heavy metals in surface se- diments adversely affected the mangrove wetland habitats and even the development of TCISMR. In this study, we conducted ecological risk analysis based on two sets of data for five heavy metals obtained before and after the establishment of TCISMR, and gave the effective control model, which will benefit the sustainable development and resource protection in Zhanjiang Bay.

2 Materials and Methods

2.1 Geological Setting and Sample Collecting

Investigations were conducted in August 2010 and April 2013, and data in 2010 were used as the background before the establishment of TCISMR. Twelve valid stations were set around TCISMR, most of which were located in Zhanjiang bay (Fig.1). The stations were near the waterways due to the fact that the main contamination is from the lanes of Zhanjiang Harbor. Considering the entire region, survey results were collected in March 2014.

Samples were collected according to national standard methods. Sediment samples were collected from the top 5 cm surface sediments by using box dredging. Values of pH and Eh for sediments were measured immediately in situ and the collected samples were stored in a plastic bag at −18℃.

2.2 Sample Analytical Methods

Samples were measured according to national standard test methods. The sediment samples were measured after digesting by nitric acid-perchloric acid. Hg was measured by using atomic fluorescence spectrophotometer AFS-2201. Cu, Pb, Zn and Cd were detected with atomic absorption spectrophotometer of Hitachi.

2.3 Risk Assessment Methods

Five heavy metals (Cu, Pb, Zn, Cd and Hg) in the waters surrounding TCISMR were assessed according to the ecological risk index assessment method proposed by Hakanson (1980).

Fig.1 Sampling stations in August 2010 (left) and April 2013 (right).

Single heavy metal pollution factor was calculated by the equation:

whereCis the measured concentration of heavy metal;Cis itsreference value for the background (Table 1).

Single potential ecological risk index of heavy metal was calculated:

where Tis response factor of heavy metal toxicity coefficient, reflecting the level of heavy metal toxicity and biological sensitivity to heavy metal pollution; Cis pollution factor acquired by Eq. (1) .

Potential risk factors index (RI) of sediments were cal- culated (Hansen., 1980; Ma., 2008):

Table 1 Background reference value (Cni) and toxicity coefficienct (Tri) of the heavy metals

2.4 Analysis of Ecological Hotspots and Prior Ecosystem Hotspots

The areas with high primary productivity are defined as ecological hotspots (Myers., 2000). Through simplifying the actual situation, areas with abundant biological diversity are considered because they play great roles in the protection of biodiversity in marine ecosystems. The primary productivity was determined by chlorophyllme-thod. Areas with primary productivity above 400mgCm−2d−1are defined as the ecological hotspots in this study (Hansen., 1987).

Ecological risk level was determined by the potentialvalues of five heavy metals (Table 2). Firstly, the area was classified into regions with low, middle and high ecological risk levels, and heavy metal ecological risk was assessed. Secondly, ArcGIS software was used to interpolate Hakanson Risk Index (HRI) within the study area to obtain the HRI distribution grid map in the entire region. According to the HRI values and ecological hotspots, areas with low to middle heavy metal ecological risk level and high ecological value were filled out, and then the prior areas with high heavy metal potential ecological risks were obtained. Finally, control and protection strategies in TCISMR were proposed according to the prior areas of heavy metal ecological risks.

Table 2 The contamination degree and potential ecological risk

3 Results and Discussion

3.1 Contents of Heavy Metals in Sediments

As shown in Table 3, before the establishment of TCI- SMR, the lowest and the highest values of heavy metal contents were around Zhanjiang Bay mouth and the Dong-hai levee, respectively. After the establishment of TCISMR, the minimum contents of heavy metals appeared around Guangdu town and the maximum values were in the middle part of Zhanjiang channel. Except Cd, four other heavy metals (Cu, Pb, Zn, and Hg) were detected at stations along the Zhanjiang Harbor Lanes in summer 2010. Among those, the content of Zn was the highest (115.2mgkg−1). After the establishment of TCISMR, the concentration of Cd showed an increasing trend in the Zhanjiang Bay. The maximum concentrations of Cd appeared in Zhanjiang Port waterway and nearby waters, which may be due to ship pollution from the Zhanjiang Harbor Lanes to the west. Compared to other Gulfs in China, Pb content in sediments around Techeng Island was at a high level and Cu, Cdand Zn were lower (Hu., 2008; An., 2010). Therefore, more attention should be paid to Pb sources in the northern part of waters around the island. Different from other heavy metals, Cu content increased after the establishment of marine protected areas. The average contents of Cu, Pb, Zn, Cd and Hg in surface sediments monitored in March 2008 were 12.37, 27.61, 41.0, 0.35, 0.035mgkg−1, respectively, indicating that the heavy metal pollution increased by 11% year by year.

Before the establishment of special marine reserves, Cu, Pb, Zn, Cd and Hg in sediments surrounding the Techeng Island showed significant spatial distribution characteristics. Except Cu, the spatial variation coefficient of various metal elements was higher than 0.36. And the maximum variation was observed for Cd element, suggesting its un- even spatial distribution. After the establishment of special marine reserves, the coefficient of variation () of most heavy metals increased, which may be due to the navigational dredging in Zhanjiang channel which took the surface sediments away (Wasserman., 2016). Due to various factors, the overall spatial distribution of heavy metals in surface sediments reflected a mix of terrestrial component and biological component. Abnormal high contents of heavy metals may indicate the worsening of anthropogenic pollution.

Table 3 Concentration of heavy metals in surface sediments around Techeng Island obtained before and after establishment of TCISMR

3.2 Spatial Distribution of the Heavy Metals Before and After Establishment of TCISMR

The output of the optimal semivariogram theoretical model was shown in Table 4 by using software GS 9.2 before the establishment of TCSMR. Models listed in the table were the best fit models that were automatically selected by the software. Gaussian model was the best to simulate the behaviors of Pb, Zn, Cd and Hg. Normal distribution model was the best to simulate special distribution of Cu, but failure when using semivariogram (the value of2was 0.07, close to 0).

Table 4 Isotropic semivariogram theoretical model of heavy metals in surface sediments around TCISMR

Notes:0as nugget,0+as the base value, A0for the change process.

The spatial correlation is strong when the ratio of structure coefficient () to the base value (0+) is larger than 75%, weak when less than 25%. Semivariogram results indicated that Pb, Zn, Cd and Hg have strong spatial correlation. The ranges of Pb and Cd were similar, suggesting that they have similar mechanism of migration and transformation in sediments. The structure coefficient of Cu was close to zero, indicating its weak spatial correlation.

After the establishment of TCSMR, the optimal semi- variogram of spatial distribution of heavy metals changed. Gaussian model was the best for the spatial simulation of Cu and Hg, while half variogram model was the best for Pb and Zn and exponential model was best for Cd. Results showed Pb and Hg had strong spatial correlation and the other three heavy metals cannot be simulated with the optimal semivariance function even after the logarithmic transfer.

3.3 Heavy Metals Pollution and Potential Ecological Risk

The average values for single element pollution coefficient in sediments before and after establishment of TCI- SMR were compared in Fig.2. In addition to Pb, the single pollution coefficients for five heavy metals were less than 1. Comprehensive pollution index (C) at all the stations decreased slightly from 3.07 to 2.94 after establishment of TCISMR (less than 8), indicating the low contamination level of heavy metals. The contamination degree of heavy metals decreased as the following: Pb>Zn> Cu>Hg>Cd. The relative pollution degree of heavy metals did not change much within monitoring period. Comprehensive analysis showed that Pb contamination was more serious.

As shown in Fig.3, potential ecological risk coefficients for five heavy metals were far less than 40 and the average values of potential ecological risk index of heavy metals at all stations were 32.09 and 30.54 before and after establishment of TCISMR. This indicated that TC- ISMR was under low ecological hazard and its ecological condition was improved in recent years. Hg accounted for 57% of ecological risk index, suggesting the potential risk of the TCISMR can be effectively reduced by controlling the Hg pollution. The potential ecological risk index of heavy metals showed the following order: Hg>Pb>Cu>Cd>Zn, which was inconsistent with pollution degree of heavy metal. This could be attributed to the different eco- toxicity of heavy metals. Besides, some elements with high pollution degree were buried and mineralized, which consequently reduced their harmfulness (Xu., 2015).

Fig.2 The single pollution coefficient of heavy metal before and after establishment of TCISMR.

Fig.3 Ecological risk factor of heavy metals in surface sediment around Techeng Island.

The ecological risk of single or multiple heavy metals decreased in the following regions: Donghai levee>the west side of Zhanjiang Harbor Lanes>near the sea of Zhanjiang Bay. Heavy metals accumulated easily in the Zhangjiang Bay because of the low water exchange capacity. After the construction of embankment in the east water near Donghai levee in 1958, the half water exchange time extended from 12 days to more than 100 days (Li, 2008).

3.4 Prior Control Pattern of Ecological Risk

The major pollution element was Pb in sediments of Zhanjiang Bay before and after the establishment of the TCISMR. Zhanjiang Bay was under low ecological risk for five heavy metals before and after establishment of TCISMR. Spatial distribution pattern of HRI value changed a little (Figs.4 and 5), and the area near the Donghai levee was under the potential risk of heavy metals due to its weak hydrodynamic conditions. Heavy metals from other areas can be easily accumulated and precipitated in this area. In addition, the Zhanjiang Port Channel was another important source of heavy metal contamination to this area.

To figure out the main source of heavy metals in sediments around TCISMR, spatial distribution of HRI value in Zhanjiang Harbor Lanes was shown in Fig.6. The risk factor was mainly impacted by the supply of port and land pollution sources. Ports, shipyards and culture areas with high human activity intensity were the main sources. The increasing enrichment coefficient of heavy metals reflected the progressive human activities in the Zhanjiang Bay.

Fig.5 HRI space distribution after establishment of TCISMR.

As displayed in Fig.6, ecological risk of heavy metals in the sediments of the Zhanjiang port showed a graded distribution of low-high-low pattern from north to south. The values of ecological risk of heavy metals are high in middle area due to the transport and accumulation of heavy metals in the waterway. The maximum value of ecological risk appeared where the land pollution was the most serious. The differences of human activities were the important reasons for the discrepancy of ecological risk of heavy metals from the north to the south (Fang., 2010).

Fig.6 HRI value distribution in Zhanjiang Harbor Lanes.

According to the above, ecological risk of heavy metals in sediments from the region of Zhanjiang Port Channel and Donghai levee was relatively high. Therefore, these two areas should be special priority areas to be controlled for heavy metals surrounding the TCISMR.

3.5 Prior Protection Areas

Since the areas with high ecological value and higher ecological risk were the coastal regions that have a long development history, which made the management is difficult to apply. In this study, the areas with a relatively low ecological risk and high ecological value were treated as prior management areas.

According to the analysis, low ecological hazard of heavy metals in sediments around TCISMR were observed.For the evaluation of ecological value, the factors included ocean primary productivity, light, nutrients, temperature, vertical mixing and critical depth and grazing role. The high primary productivity in the water around the Oliyou plant may be caused by the high temperature and abundant nutrients, which promoted the phytoplankton photosynthesis. Software GS 9.2 was used for spatial interpolation analysis (Fig.7), and the prior conservation area of heavy metals in sediments of northern Zhanjiang port fairway was shown in Fig.8. Zhanjiang Bay Channel, the areas around special marine reserves, the artificial reef areas and mangrove areas to the south of Techeng Island are the areas with low ecological risk of heavy metals and high ecological value (Li., 2012).

Food supply service was the most prominent feature of Zhanjiang Bay ecosystem, which accounted for 79.23% of all the values. However, the effect of pollutant treat- ment in Zhanjiang Bay is very limited, only accounting for 1.3% of the total service function. The discharge of large amount of land pollutants would damage the self- purification capacity of water and made the Zhanjiang Bay ecosystem worse. Thus, reducing the discharge of the land pollutants is the key point to keep the ecological system developing healthily in Zhanjiang Bay. In addition, more scientific researches are in urgent need.

古典诗文是我国历史长河中一颗璀璨的明珠，从诸子散文到楚词汉赋再到唐诗宋词元曲，诗风词韵陶冶了一代又一代的华夏儿女。那千百年来，经过大浪淘沙，流行至今的经史子集，唐诗宋词、格言警句，已成为世界文化的瑰宝。其情韵之美和语言之美，滋养着一代又一代的龙的传人，炎黄子孙。

Fig.7 Prior conservation pattern of ecological risk of TCISMR.

Fig.8 Prior conservation pattern of ecological risk in the north of Zhanjiang Bay where TCISMR is located.

4 Conclusions

The results of this study show that except Cd, the highest contents of other heavy metals in the sea area around TCISMR tend to increase year by year, and it is easy to form heavy metal pollution. According to the simulation results of semi-variogram, the optimal semi-variogram model functions for the five heavy metals have changed after the establishment of TCISMR, and the spatial correlation of five heavy metals in Zhanjiang Bay has weakened. This requires more precise technical means to understand the migration, complexation and transformation of heavy metals in coastal zones. In addition, in order to effectively control the pollution of heavy metals, determing the quantitative relationship between the input flux of heavy metals and the corresponding human activities will be helpful to control the ecological risk of heavy metals. The potential ecological risk index of heavy metals in surface sediment around TCISMR are far less than 150, indicating Zhanjiang Bay was at a low-range ecological harm level. The ecological risk of heavy metals was most serious in the surface sediments near Donghai levee, followed by the west side of Zhanjiang Port and Zhangjiang Harbor Lanes. So the priority areas for the heavy metal controlling in TCISMR were Donghai levee and Zhangjiang Harbor Lane. While the regions with high ecological value and low ecological risk were the mangrove wetland on the south side of the Techeng Island and Zhanjiang Port Channel. Key protected areas of artificial reefs have the potential ecological risk and have a great significance for the management of Techeng Island marine specially protected areas.

Acknowledgements

The study was jointly funded by the Research Fund Program of Guangdong Provincial Key Laboratory of En- vironmental Pollution Control and Remediation Technology (No. 2013K0011), the State Oceanic Administration Key Laboratory of Sea area Management Technology Fund (No. 201711), the Guangdong MEPP Fund (No. GDOE [2019]A46), the GDNRC (No. [2020]067), and the South China Sea Branch Secretary fund (No. 1673).

An, L. H., Zheng, B. H., Zhang, L., Jia, N., Qin, Y. W., Zhao, X. R., and Jia, J., 2010. Occurrence of heavy metals in surface sediments from estuaries in Bohai Bay and their ecological risk assessment., 30 (5): 666- 670 (in Chinese with English abstract).

Armid, A., Shinjo, R., Zaeni, A., Sani, A., and Ruslan, R., 2014. The distribution of heavy metals including Pb, Cd and Cr in Kendari Bay surficial sediments., 84 (1-2): 373-378.

Boekhold, A. E., 2008. Ecological risk assessment in legislation on contaminated soil in the Netherlands., 406 (3): 518-522.

Conrad, S. R., Santos, I. R., Brown, D. R., Sanders, L. M., van Santen, M. L., and Sanders, C. J., 2017. Mangrove sediments reveal records of development during the previous century (Coffs Creek Estuary, Australia)., 122: 441-445.

Creswell, J. E., Kerr, S. C., and Meyer, M. H., 2015. Factors controlling temporal and spatial distribution of total mercury and methylmercury in hyporheic sediments of the Allequash Creek wetland, northern Wisconsin., 113 (G2): 544-544.

Fang, S. B., Xu, C., Jia, X. B., Wang, B. Z., and An, S., 2010. Using heavy metals to detect the human disturbances spatial scale on Chinese Yellow Sea coasts with an integrated analysis., 184: 375-385.

Feng, H., Han, X., Zhang, W., and Yu, L., 2004. A preliminary study of heavy metal contamination in Yangtze River intertidal zone due to urbanization., 49 (1112): 910-915.

Guevara, S. R., Rizzo, A., and Sanchez, R., 2005. Heavy metal inputs in northern Patagonia Lakes from short sediment core analysis., 265: 481-493.

Hakanson, L., 1980. An ecological risk index for aquatic pollution control sediment logical approach., 14: 975-1001.

Hansen, L. A., Alongi, D. M., and Moriarty, D. J. W., 1987. The dynamics of benthic microbial communities at Davies Reef, central Great Barrier Reef., 6 (2): 63-70.

Huang, W., Camperdom, R., Abrao, J. J., Bernat, M., and Latouche, C., 1994. Variation of heavy metals in recent sediments from Piratininga lagoon (Brazil): Interpretation of geochemical data with the aid of multivariate analysis., 36 (4): 241-247.

Hu, Z. H., Li, P., Xu, W. H., and Zhang, G., 2008. Distribution and ecological risk assessment of heavy metals in surface se- diments from Shekou fishing harbor, Shenzhen, China., 17 (6): 2145-2149 (in Chinese with English abstract).

Kehrig, H. A., Pinto, F. N., Moreira, I., and Malm, O., 2003. Heavy metals and methylmercury in a tropical coastal estuary and a mangrove in Brazil., 34 (5): 661- 669.

Li, X. B., 2008. Research on the effects of Donghai dam on the hydrodynamic environment of the Zhanjiang Bay. Master the- sis. Ocean University of China.

Li, Z. Y., Xu, S. J., Xu, H. Y., and Cai, X., 2012. Value assessment of marine ecosystem service in Zhanjiang Bay., 31 (4): 567-571.

Liang, Y., Yuan, D., Chen, Y., and Liu, X., 2013. Vertical distribution of total mercury and methylmercury in sediment of the Fugong mangrove area at Jiulong River Estuary, Fujian, China., 85 (6): 522-529.

Ma, X. J., Lu, Z. H., and Cheng, J. L., 2008. Ecological risk assessment of open coal mine area., 147: 471-481.

Mason, R. P., Kim, E. H., Cornwell, J., and Heyes, D., 2006. An examination of the factors influencing the flux of mercury, methylmercury and other constituents from estuarine sediment., 102: 96-110.

Myers, N., Mittermeier, R. A., Mittermeier, C. G., and Kent, J., 2000. Biodiversity hotspots for conservation priorities.,403 (24): 853-858.

Niu, Z. Y., Cao, Y., Zhao, W. L., and Li, R. L., 2018. Distribution and assessment of mercury (Hg) in surface sediments of Futian mangrove forest, China., 41: 125-134.

Ramesh, R., Purvaja, R., and Lakshmi, A., 2009. South Asia Basins: LOICZ global change assessment and synthesis of river catchment: Coastal sea interaction and human dimensions. GKSS Research Center, Geesthacht, 121.

Srinivasa Reddy, M., Basha, S., Sravan Kumar, V. G., Joshi, H. V., and Ramachandraiah, G., 2004. Distribution, enrichment and accumulation of heavy metals in coastal sediments of Alang- Sosiya ship scrapping yard, India., 48: 1055-1059.

Tarradellas, J., Bitton, G., and Rossel, D., 2000.. CRC Lewis, Boca Raton, 1-386.

Thomas, D. J. L., Tyrrel, S. F., Smith, R., and Farrow, S., 2009. Bioassays for the evaluation of landfill leachate toxicity., 12 (1): 83-105.

Wasserman, J. S., Wasserman, M. A. V., Barrocas, P. R. G., and Almeida, A. M., 2016. Predicting pollutant concentrations in the water column during dredging operations: Implications for sediment quality criteria., 108: 24-32.

Xu, G., Liu, J., Pei, S. F., Gao, M. S., Hu, G., and Kong, X. H., 2015. Sediment properties and trace metal pollution assessment in surface sediments of the Laizhou Bay, China., 22: 11634-11647.

Yu, X. Q., Yang, J., Liu, L., Tian, Y., and Yu, Z., 2015. Effects ofinvasion on biogenic elements in a subtropical coastal mangrove wetland., 22 (4): 3107-3115.

Zhao, L., Mi, D., Chen, Y., Wang, L., and Sun, Y., 2015. Ecological risk assessment and sources of heavy metals in sediment from Daling River Basin., 22: 5975-5984.

. Tel: 0086-20-34115051

E-mail: yjywangliang@126.com

December 22, 2018;

January 9, 2019;

March 15, 2019

(Edited by Chen Wenwen)