Distribution and Source of Main Contaminants in Surface Sediments of Tidal Flats

LIU Zhijie, LI Peiying, ZHANG Xiaolong, LI Ping, and XU Yuanqin

1) College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, P. R. China

2) National Marine Data and Information Service, Tianjin 300171, P. R. China

3) First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, P. R. China

4) Environmental College, Yantai University, Yantai 264005, P. R. China

Distribution and Source of Main Contaminants in Surface Sediments of Tidal Flats in the Northern Shandong Province

LIU Zhijie1),2),*, LI Peiying3), ZHANG Xiaolong4), LI Ping3), and XU Yuanqin3)

1) College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, P. R. China

2) National Marine Data and Information Service, Tianjin 300171, P. R. China

3) First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, P. R. China

4) Environmental College, Yantai University, Yantai 264005, P. R. China

Twenty-nine samples of surface sediments from tidal flats in the Northern Shandong Province were collected for grain size, heavy metal (Hg, Cu, Pb, Zn, Cd, and Cr), and oil pollution analyses. The geoaccumulation index (Igeo) and factor analysis were introduced to evaluate sediment quality and source of contaminants. The mean concentrations of Hg, Cu, Pb, Zn, Cd, Cr, and oil in the surface sediments in the study area are 0.033, 17.756, 19.121, 55.700, 0.291, 59.563, and 14.213 μg g-1, respectively. The heavy metal contamination in the old delta lobe is slightly higher than that in the abandoned delta lobe; however, the opposite was observed for oil pollution. The Igeoresults revealed that the overall quality of the surface sediments in the study area is in good condition. The heavy metal pollution levels show a descending order: Cd> Hg> Cr> Cu> Zn> Pb, Cd being the main pollutant. The contamination level for in the study area is relatively lower than those for China’s other tidal flats. Heavy metals are mainly derived from natural sources of rock weathering and erosion, partly influenced by industrial and agricultural discharge. However, oil pollution is mainly from runoff input, motorized fishing boat sewage, and oil exploitation.

tidal flat sediments; heavy metals; quality evaluation; factor analysis; source of contaminants; Northern Shandong Province

1 Introduction

Tidal flats are the major geomorphic units of muddy coasts, as well as one of the important types of coastal wetlands. They are located in the sensitive areas with the land-ocean interaction and are highly vulnerable to disturbance and destruction under the impact of anthropogenic activities and natural processes. Acting as the main way for land-source contaminants to enter the sea, tidal flats are threatened by both coastal sewage and effluents carried by rivers (Luo et al., 2011). The tidal flat sediments are both a sink and a source for contaminants (Li et al., 2010), which can absorb, fix, and transform heavy metals as well as organic and other toxic pollutants through physical, chemical, and biological actions. On the other hand, under the condition of changed environments, contaminants may be released from suspended matters or sediments, forming secondary pollution. Once contaminants accumulated in the surface sediments of tidal flats reach a certain degree, they may threaten the security of the coast wetland ecosystem, and moreover, affect the health of mankind through the food chain (Wang et al., 2002; Liu et al., 2004; Hu et al., 2013). Therefore, problems of tidal flat pollution, especially heavy metal pollution, have caused widespread concern among domestic and foreign scholars. Previous studies on tidal flat pollution primarily involved the distribution of pollutants (Zhou et al., 2007; Quan et al., 2006; Yin et al., 2007; Liu et al., 2010; Morse et al., 2004), characteristics of heavy metal accumulation (Reddy et al., 2004; Pardue et al., 1988; Attrill et al., 1995; Li et al., 2007; Bai et al., 2011; Chen et al., 2000), and quality evaluation of sediments (Nobi et al., 2010; Liu et al., 2012; Yu et al., 2011; Wang et al., 2011; Zhang et al., 2011). In China, many scholars have investigated the pollution status of estuaries (Wang et al., 2009; Zhang et al., 2007; Li et al., 2007), gulfs (Yin et al., 2007; Li et al., 2010; Zhou et al., 2004), and tidal flats (Chen et al., 2000; Quan et al., 2006; Xia et al., 2008). Out of numerous contaminants, heavy metals have been widely studied because of their toxicity, persistence, and bio-accumulative effect (Zhang et al., 2011; Kaushik et al., 2009). However, the sources of different contaminants are complicated. The increase of pollutant contents in sediments may be the synthetic re-sults of many sources including natural weathering and erosion of rocks, as well as industrial and agricultural wastes from anthropogenic activities (Karageorgis et al., 2011; Cai et al., 2010). Thus, identifying the sources of tidal flat pollutants is important for environmental protection.

The Yellow River Delta, like other river deltas, is a hot area of research both at home and abroad. It is also a typical area for the study of environmental changes. In recent years, with the rapid economic development of the Yellow River Delta, the contradiction between regional economic development and ecological protection has become increasingly severe. Many pollutants produced by human activities enter the sea through rivers, causing the degradation of the regional ecological environment. Several studies have demonstrated the pollution status of the Yellow River Delta; however, they mainly focused on the newborn estuarine wetlands (Li et al., 2001; Wang et al., 2009; Yu et al., 2011; Ling et al., 2010). Thus, contamination studies of tidal flats in the Northern Shandong Province are rarely reported. This study took the tidal flats of the old delta lobe and the abandoned delta lobe of Diaokou River in the Yellow River Delta as the typical study areas. The distribution and concentrations of heavy metals and oil were analyzed, and the sources of contaminants were estimated in tidal flat sediments using correlation analysis and factor analysis.

2 Materials and Methods

2.1 Study Area

The Yellow River Delta, a compound of old and modern deltas (Cheng and Xue, 1997), is located in the north of Shandong Province, the southern coast of the Bohai Bay, and the southwest coast of Laizhou Bay; this delta runs in a roughly northwest-southeast direction. The study area ranges from the Dakou River estuary, passes the border between Hebei and Shandong Provinces in the northwest, and ends at the Yellow River Harbor in the east. Based on the evolutionary history of the Yellow River Delta, two typical study areas were selected for this study (Fig.1). One is the old delta lobe situated in the old Yellow River Delta tidal flats starting from Dakou River to the west of the Taoer estuary and being formed during AD11 to 1128 (Satio et al., 2000; Xue, 2011). The other is the abandoned delta lobe, that is, the abandoned delta tidal flat of Diaokou River, being fromed 1855 to 1976 (Satio et al., 2000).

Fig.1 Locations of study areas and sampling sites. a) the old delta lobe; b) the abandoned delta lobe.

2.2 Sampling and Methods

A total number of 17 surface samples (0-10 cm) was collected from a survey of six sections in the old delta lobe in September 2005, and 12 surface samples (0-10 cm) were collected alone from the four sections in the abandoned lobe. The sections were mainly laid out along the upper, middle, and lower tidal flats. Sediment samples were used for heavy metal (Cu, Pb, Zn, Cr, Cd, and Hg) and oil tests as well as for grain size analysis. The field survey and the collection, pretreatment, and determination of samples were conducted according to the Marine Chemistry Survey Technology Regulations (908 Special Office of State Oceanic Administration, 2006). Atomic fluorescence, ultraviolet spectroscopy, and inductively coupled plasma mass spectrometry were used to determine Hg, oil, and Cd, Cr, Cu, Pb, and Zn (Liu et al., 2010), respectively. As a quality control, duplicate analyses were performed for 20% of total samples (i.e., 6 selected samples). The relative standard deviations for theheavy metals and oil were less than 10%. The grain sizes of sediments were measured with Malvern Mastersizer 2000 instrument (Malvern Instruments Ltd., UK). The relative errors of repeated measures for grain size were less than 3%.

The computer software package SPSS13.0 was used to perform multivariate statistical analyses. Pearson correlation analysis was conducted to reveal the relationships between pollutants and sediment components. Factor analysis was applied to confirm the source of pollutants.

3 Results and Discussion

3.1 Regional Distribution Characteristics of Pollutants

The statistical values of six heavy metals and oil of the surface sediments in the Northern Shandong tidal flat are shown in Table 1. In the whole area, the mean values of Hg, Cu, Pb, Zn, Cd, and Cr were 0.033, 17.756, 19.121, 55.700, 0.291, and 59.563 μg g-1, respectively. The mean value of oil pollution was 14.213 μg g-1. Judging from the statistic values of the pollutants contents, the concentration of Hg changed least (standard deviation: 0.042), followed by Cd (standard deviation: 0.1). The standard deviation of other pollutants changed significantly (standard deviations: 4.141 to 24.665). This shows that the concentrations of different pollutants are with a large regional difference. The mean concentration of pollutants in the old delta lobe is greater than that in the abandoned delta lobe. The abnormally high value of Hg is 0.25 μg g-1in the vicinity of the Taoer River Estuary (D5 section). Higher concentrations of Zn and Cr are observed at the upper tidal flat of Dakou River Island (D1 section) and Wangzi Island (D3 section) in the old delta lobe. However, in the upper tidal flat of section D14, oil pollution is very serious, with a content of 108.06 μg g-1.

Table 1 Statistics of pollutant contents in different regions of the tidal flats in the Northern Shandong Province (μg g-1)

To eliminate the differences among different elements, the data were dealt with through a normalization process, i.e., the data were transferred into the range of [0, 1]. The concentrations of different pollutants and clay contents varied in different sections of tidal flats (Fig.2). The clay content of tidal flat sediments in the old delta lobe was zoned clearly with increasing clay content from the upper tidal flat to the lower tidal flat. In the abandoned delta lobe, the zonation of clay content in tidal flat was not significant. Except for the abnormally high or low values, the concentration of pollutants in the upper tidal flat was lower than that in the middle and lower tidal flats in the old delta lobe, whereas the varying trend of pollutants was not significant.

Correlation analysis was performed between the pollutant content and the sediment component content (Table 2). As shown in Table 2, With the exception of Hg, the correlations of Cu, Pb, Zn, Cd, Cr, and oil pollution with clay content were obviously higher than those with silt content. This result indicates that the clay content of sediments plays a controlling role in the enrichment and distribution of heavy metals (Bao and Fu, 1994; Fang et al., 2005; Wang et al., 2009). But not all elements are under a grain-controlling effect (Luo et al., 2011), for example, Hg and Cd have poor correlation with the clay content of sediments. Cr and Cu are highly correlated, with a correlation coefficient of 0.91. Zn, Cu, and Pb show pairwise correlation because they are pro-copper elements with similar geochemical behavior during migration and transformation (Kaushik et al., 2009). Hg and oil pollution are almost irrelevant to other heavy metals, which is significantly affected by human activities.

The distribution characteristics of pollutants in tidal flat indicate that they are affected by sediment componentsand also associated with regional hydrodynamic conditions. Yin et al. (2004) pointed out that the abandoned delta lobe belongs to the strong erosion coast, under strong hydrodynamic conditions, where the components of tidal flat sediments are mainly silt (Fig.3). Therefore, it is difficult for heavy metals and other pollutants to be rich in this area. The old delta lobe is in a relatively balanced state of erosion and deposition, and the content of fine particles is higher than that in the abandoned delta lobe. The fine sediments tend to adsorb heavy metals and accelerate condensation and deposition (Zhang et al., 2011), which does not benefit the migration and transformation of pollutants. Besides the effect of natural factors, runoff transport is important for industrial and agricultural pollutants. Several rivers such as Dakouhe River, MajiaheRiver, and Taoerhe River flow in the old delta lobe, which is one of the reasons for its higher concentration of pollutants than that in the abandoned delta lobe.

Fig.2 Diagrams of pollutant contents of typical sections in Northern Shandong Province. U, Upper tidal flat; M, Middle tidal flat; L, Lower tidal flat.

Table 2 Pearson’s correlation matrix for elemental concentrations and sediment properties (n=29)

Fig.3 Number of stations for different sediment types in the Northern Shandong Province.

3.2 Quality Evaluation of Tidal Flat Pollutants

Based on the concentration of heavy metals and oil in the surface sediments of tidal flats in the Northern Shandong Province, except for Cr with three samples higher than the Class I criteria of Chinese Marine Sediment Quality (National Standard of P. R. China, 2002), the concentrations of other elements were lower than the Class I criteria. The mean value of oil pollutants was 14.213 μg g-1, which is significantly lower than the Class I criterion value of 500 μg g-1. This result indicates that the environmental quality of the study area is in good condition. Compared with other China’s tidal flats, the pollutant concentration in the study area is lower (Table 3). The concentration of Zn is slightly higher than that in the tidal flat sediments in Liaoning Province and the Yellow River estuary. The concentration of Cd is slightly higher than that of the tidal flats of Hebei, the Yellow River estuary, and Tianjin. The concentrations of Hg, Cu, Pb, and Cr are significantly lower than in Liaoning, Tianjin, Hebei, the Yangtze River Estuary, and Pearl River Estuary.

Table 3 Comparison of mean contents of pollutants in surface sediments of tidal flats in the Northern Shandong Province and other areas (μg g-1)

Among many pollutants in tidal flat sediments, the total amount of heavy metal elements is an important indicator of the pollution degree (Chen, 2009). In this study, geoaccumulation index (Igeo) was used to evaluate the heavy metal pollution in the Northern Shandong tidal flats. Igeo, which was proposed by Prof. Müller at the Sediment Research Institute in University of Heidelberg in Germany, is a quantitative index of heavy metal pollution in the sediments of the water environment (Müller, 1969). Igeois calculated with the following formula:

where Cnis the concentration of the element n in sediments (μg g-1), Bnis the geochemical background value of the element in the sediment, and k is a coefficient (usually 1.5). However, different rocks in various regions may cause the background value to change. In accordance with Igeo, heavy metal pollution in the sediments was divided into seven levels (Table 4).

This study adopted the background values of soil environment in Shandong Province as the reference values (Liu et al., 2008), i.e., the values of Hg, Cu, Pb, Zn, Cd, and Cr are 0.016, 21.7, 24.3, 61.9, 0.079, and 65.2 μg g-1, respectively. The measured concentration of heavy metals was used in Formula (1) to calculate the Igeostatistical values (Table 5) of each area and the number of samples in different pollution levels (Fig.4).

The Igeovalues of Hg, Cu, Pb, Zn, Cd, and Cr varied from -0.42 to 3.38, -2.87 to 0.31, -2.39 to -0.09, -2.73 to 0.19, 0.60 to 2.63, and -1.38 to 0.53, respectively (Table 5). Igeoanalysis shows that the tidal flat sediments in the Northern Shandong Province can still be consideredunpolluted or slightly polluted. In addition, the Igeomean value of every heavy metal in the old delta lobe is greater than that in the abandoned delta lobe. Comparing the Igeovalues of heavy metals, the contamination degree of Cd is the most serious, for 27 samples are at the level of mod-erate pollution. For Hg, only one sample was highly polluted, with an Igeovalue of 3.38. The pollution levels of the heavy metals are arranged from strong to weak as follows: Cd> Hg> Cr> Cu> Zn> Pb.

Table 4 Grades of heavy metal pollution based on Igeo

Table 5 Igeo statistical values of heavy metals

Fig.4 Number of stations for different Igeovalues.

3.3 Factor Analysis of the Pollutant Sources

Pollutants are influenced by many factors. Thus, determining the pollutant source results in multiple solutions. Factor analysis is a multivariate statistical analysis method to study how numerous original variables can be concentrated into a few factor variables with the least loss of information and how factor variables with strong interpretability can be determined (Li, 2007). Varimax rotation makes factor variables more interpretable; thus, factor analysis is a common method for analysis of pollutant sources (Ma et al., 2012; Wang et al., 2008; Maiz et al., 2000). Factor analysis was performed separately on the tidal flat pollutants in the old delta lobe and the abandoned delta lobe of the Yellow River delta to determine the pollutant sources. KMO and Bartlett’s sphericity tests were used on the data of the two areas. The KMO test values of the pollutants in the old delta lobe and the abandoned delta lobe were both greater than 0.5 (0.51 and 0.69, respectively). This indicates that a certain information overlap exists in different variables, which is suitable for factor analysis. The concomitant probability of the Bartlett sphericity test of the two areas is 0.000, which is lower than the significance level of 0.05. Therefore, the independence hypothesis of each variable was rejected and was available for factor analysis. Principal component analysis was used to extract the common factors by calculating the correlation coefficient matrix to obtain the factor loading matrix of pollutants (Table 6). An Eigen value greater than 1 was taken as the standard. Thus, the main information of the seven types of pollutants can be explained by three main factors in the two typical areas, respectively.

Table 6 Matrix of rotated factor loadings

The contribution rates of the three main factors in the old delta lobe are 51.16%, 16.73%, and 15.82%, with the cumulative contribution rate of 83.71%. Thus, the three main factors cover the most information of the seven pollution indicators (Table 6). The first main factor has a high positive load on the concentrations of Cu, Pb, Zn, Cd, and Cr. The correlation analysis of the heavy metal contents in Table 2 indicates strong correlations between the metal elements (Cu, Pb, Zn, Cd, and Cr) and low positive correlations with the clay content, implying that these elements may have similar origins and laws of migration and transformation. Based on the Igeostatistical values of heavy metals (Table 5) and the grades of heavy metal pollution (Table 4), heavy metals Cu, Pb, Zn, and Cr were in the unpolluted to moderately polluted or unpolluted level, except that element Cd was in the moderately to highly polluted level. Therefore, Cu, Pb, Zn, Cd, and Cr mainly originate from geochemical changes and intrinsic pollution, partly affected by the industrial and agricultural pollutant discharges. Oil pollution is closely related to the second principal factor. Oil is a carbon-containing organic compound. In oil-contaminated soil, organic matter content increases significantly, which has a weak correlation with the clay content. The bulletin of marine environment quality from Binzhou City, China (2008) reported that a large amount of industrial effluents and municipal sewage were discharged from river to the near shore. And the excessive pollutants in river water mainly included chemical oxygen demand (COD), volatile phenol and oil. Furthermore, the number of fishing vessel was increased with the construction of channel and dock and the rapid development of offshore aquiculture and fishing industry. Thus, oil pollution in this area is mainly from the input of industrial and mining pollutants carried by the rivers and the sewage of motorized fishing boats. The positive loading of the third principal factor on Hg concentration is 0.92. Element Hg is mainly from the discharges of agricultural pesticides and electron industrywastewater (Zhang et al., 2003). Thus, the third principal factor cha- racterizes pollution from industrial and agricultural sewage along the coast.

The contribution rates of the three main factors in the abandoned delta lobe are 48.19%, 25.47%, and 15.54%, and their cumulative contribution rate is 89.20%. The three main factors provide the most information on the seven pollution indicators (Table 6). The first main factor has high positive loadings on the concentrations of Cu, Pb, Cd, and Cr, but a low loading of 0.40 on Zn, indicating a similar source of heavy metals in the old delta lobe. The second main factor has the highest loading of 0.960 on Hg and partly dominates the source of Zn. This indicates that aside from the natural weathering of parent rock, Zn is also related to regional industrial and agricultural sewages. This result is consistent with the characterization information of the third main factor for the old delta lobe. The third main factor has a higher loading of 0.99 on oil pollutants. It is well known that the modern Yellow River Delta is one of the bases for the development of the petroleum industry. Shengli oilfield as the second largest oilfield of China is located here. Studies showed that the range of oil concentration is 9.2 - 180.9 μg g-1(He, 2006). Thus, oil exploitation activities such as mining, transporting, storing, etc., have become the main factor resulting in oil contamination in this area, which causes the degradation of wetland ecological system (Yu et al., 2012).

Based on the aforementioned analysis, the sources of heavy metals in the tidal flats in the Northern Shandong Province are mainly natural processes of rock weathering and erosion, which are partly affected by industrial and agricultural pollution. Oil pollution in tidal flats is mainly from land-based pollutants carried by rivers, motorized fishing boat sewage, and the exploitation of the petroleum industry. The statistical results of this study (Table 1), compared with the findings on the Yellow River Delta by Li et al. (2001) shows that the tidal flat surface sediment pollution levels of Hg, Cu, and Pb change slightly but those of Zn, Cr, and Cd are higher in recent years. Although the sediment pollution degree in the Yellow River Delta is less than that in some other regions, it still shows human activity traces. Therefore, strengthening monitoring and control of pollutants in tidal flat sediments is necessary to ensure the security of the regional ecosystem.

4 Conclusions

1) The mean concentrations of Hg, Cu, Pb, Zn, Cd, Cr, and oil in the tidal flats of the Northern Shandong Province are 0.033, 17.756, 19.121, 55.700, 0.291, 59.563, and 14.213 μg g-1, respectively. The distribution characteristics show that pollutant concentration in the old delta lobe is slightly higher than that in the abandoned delta lobe. Regional hydrodynamic conditions, components of tidal flat sediments, and exogenous pollutant transportation are the main factors for the pollutant distribution of tidal flat sediments in the study area.

2) The results of Igeoanalysis show that the sediments in the Northern Shandong tidal flat are unpolluted and /or slightly polluted. The order of pollution level of the heavy metals from strong to weak is: Cd> Hg> Cr> Cu> Zn> Pb. Element Cd is partially moderately to highly polluting, whereas Hg in one sample is highly polluting. Most of the pollutant concentrations of the surface sediments in the Northern Shandong tidal flat are lower compared with those in other tidal flats in China. The mean value of oil pollution is 14.213 μg g-1, which is significantly lower than the Class I criteria of the National Marine Sediment Quality Standards.

3) Factor analysis results indicate that heavy metals are mainly derived from the natural sources of rock weathering and erosion, mixing partly with industrial and agricultural pollutants. The oil pollution in the old delta lobe mainly comes from the river pollutants and the sewage of motorized fishing boats, whereas that in the abandoned delta lobe mainly comes from the development of the petroleum industry.

Acknowledgements

This study was supported by the 908 Special Coastal Surveys of Shandong Province Project (No. SD908-01-03) and the Ocean Public Welfare Scientific Research Project (No. 201005029). We are also grateful to the reviewers of the paper.

908 Special Office of State Oceanic Administration, 2006. Marine Chemistry Survey Technology Regulations. Ocean Press, Beijing, 74-102.

Attrill, M. J., and Thomesm, R. M., 1995. Heavy metal concentrations in sediment from the Thames Estuary UK. Marine Pollution Bulletin, 30 (11): 742-744.

Bai, J. H., Huang, L. B., Yan, D. H., Wang, Q. G., Gao, H. F., Xiao, R., and Huang, C., 2011. Contamination characteristics of heavy metals in wetland soils along a tidal ditch of the Yellow River Estuary, China. Stochastic Environmental Research and Risk Assessment, 25: 671-676.

Bao, Y. N., and Fu, W. X., 1994.Control function of sediment to heavy metals accumulation. Acta Oceanologica Sinica, 16 (3): 139-142.

Cai, L. Y., 2010. Analysis of the source of heavy metal contamination in surface sediments of Quanzhou Bay based on principal component analysis (PCA). Journal of Oceanography in Taiwan Strait, 29 (3): 325-331.

Chen, Z. L., Xu, S. Y., Liu, L., Yu, J., and Yu, L. Z., 2000. Spatial distribution and accumulation of heavy metals in tidal flat sediments of Shanghai coastal zone. Acta Geograohica Sinica, 55 (6): 641-650.

Chen, M. R., 2009, The Study on Heavy Metals Pollution in Tidal Flat Sediments in the Yangtze Estuary. East China Normal University Press, Shanghai, 51-62.

Cheng, G. D., and Xue, C. T., 1997. Sediment Geology in the Yellow River Delta. Geology Press, Beijing, 108-109.

Fang, S. Q., Hu, X. F., and Xu, W., 2005. Influence of properties of sediments from tidal flat in the Yangtze River Estuary to heavy metal accumulation. Environmental Chemistry, 24 (5): 586-589.

He, Q. C., 2006. The Geological Environment and Sustainable Development in the Yellow River Delta. Geology Press, Beijing, 1-22.

Hu, X. F., Du, Y., Feng, J. W., Fang, S. Q., Gao, X. J., and Xu, S. Y., 2013.Spatial and seasonal variations of heavy metals in wetland soils of the tidal flats in the Yangtze Estuary, China: Environmental implications. Pedosphere, 23 (4): 511- 522.

Karageorgis, A. P., Sioulas, A., Krasakopoulou, E., Anagnostou, C. L., Hatiris, G. A., Kyriakidou, H., and Vasilopoulos, K., 2011. Geochemistry of surface sediments and heavy metal contamination assessment: Messolonghi Lagoon complex, Greece. Environmental Earth Sciences, DOI: 10.1007/ s12665-011-1136-3.

Kaushik, A., Kansal, A., Santosh, M., Kumari, S., and Kaushik, C. P., 2009. Heavy metal contamination of river Yamuna, Haryana, India: Assessment by metal enrichment factor of the sediments. Journal of Hazardous Materials, 164: 265- 270.

Li, Q. S., Wu, Z. F., Chu, B., Zhang, N., Cai, S. S., and Fang, J. H., 2007. Heavy metals in coastal wetland sediments of the Pearl River Estuary, China. Environmental Pollution, 149: 158-164.

Li, X. R., 2007. Compare and application of principal component analysis, factor analysis and clustering analysis. Journal of Shandong Institute of Education, 6: 23-26.

Li, R. W., and Li, Y., 2007. Environmental and sedimentological survey along the coast of Bohai Gulf. Acta Sedimentologica Sinica, 26 (1): 128-138.

Li, R. W., Li, H., Li, Y., Qian, Z., Ma, Z. P., and Jiang, Z. X., 2001. Study of the heavy metals, nitrogen and phosphorus in the sediments of the Yellow River Delta. Acta Sedimentologica Sinica, 19 (4): 622-629.

Li, Y. H., Chen, J., Huang, C. B., Wang, A. J., and Li, D. Y., 2010. Distribution patterns of heavy metals in surface sediments of the Quanzhou Bay and environmental quality assessment. Environmental Science, 31 (4): 931-938.

Ling, M, Liu, R. H., Wang, Y., Tang, A. K., Yu, P., and Luo, X. X, 2010. The spatial distribution of heavy metals in the soil of Tamarix chinensis forest farm in Yellow River Delta wetland and its ecological significance. Transactions of Oceanology and Limnology, 4: 41-46.

Liu, J. S., Wang, R. Q., Dai, J. L., Zhang, Y. L., and Wang, Q., 2008, Soil environmental background contaminations in old course of the Yellow River in Shandong Province, Environmental Science, 29 (6): 1699-1704.

Liu, Y. F., Wu, S. Y., Chen, Y., and Tian, Z. W., 2010. Sources and distributions of main pollutants in the intertidal sediments of the Jiaozhou Bay. Advances in Marine Science, 28 (2): 163-169.

Liu, F., Wang, H. T., and Wang, D. L., 2004. Spatial distributions of heavy metals from the Laizhou Bay littoral wetland. Advances in Marine Science, 22 (4): 486-492.

Liu, Z. J., Li, P. Y., Zhang, X. L., Li, P., and Zhu, L. H., 2012. Regional distribution and ecological risk evaluation of heavy metals in surface sediments from coastal wetlands of the Yellow River Delta. Environmental Science, 33 (4): 1182-1188.

Luo, X. X., Tian, J., Yang, J. Q., and Zhang, J., 2011. Distribution characteristics of heavy metals and nutrient elements in inter-tidal surface sediments of Yellow River Estuary. Ecology and Environmental Sciences, 20 (5): 892- 897.

Ma, L. J., Cui, Y. C., and Wang, H. R., 2012. Source of heavy metal contamination in Heini Bay sediments: A case study using factor analysis. Marine Geology Frontiers, 28 (4): 57-61.

Maiz, I., Arambarri, I., Garcia, R., and Millán, E., 2000. Evaluation of heavy metal availability in polluted soils by two sequential extraction procedures using factor analysis. Environmental Pollution, 110: 3-9.

Morse, J. L., Megonigal, J. P., and Walbridge, M. R., 2004. Sediment nutrient accumulation and nutrient availability in two tidal freshwater marshes along the Mattaponi River, Virginia, USA. Biogeochemistry, 69: 175-206.

Müller, G., 1969. Index of geoaccumulation in sediments of Rhine River. Geojournal, 2: 108-118

National Standard of P. R. China, 2002. Marine Sediment Quality (GB 1868-2002). China Standard Press, Beijing, 243-345.

Nobi, E. P., Dilipan, E., Thangaradjou, T., Sivakumar, K., Kannan L., 2010. Geochemical and geo-statistical assessment of heavy metal concentration in the sediments of different coastal ecosystems of Andaman Islands, India. Estuarine, Coastal and Shelf Science, 87 (2): 253-264.

Pardue, J. H., DeLaune, R. D., Smith, C. J., and Patrick, W. H., 1988. Heavy metal concentrations along the Louisiana coastal zone. Environment International, 14 (5): 403-406.

Quan, W. M., Li, C. J., Shen, A. L., Qian, B. L., Ping, X. W., Han, J. D., Shi, L. Y., and Chen, Y. Z., 2006. Distribution and accumulation of nutrients and heavy metals in Dongtan wetlands on Chongming Island, China. Acta Ecologica Sinica, 26 (10): 3324-3331.

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

Saito, Y., Wei, H. L., Zhou, Y. Q., Nishimura, A., Sato, Y., and Yokota, S., 2000. Delta progradation and chenier formation in the Huanghe (Yellow River) Delta, China. Journal of Asian Earth Sciences, 18: 489-497.

Wang, T. W., Cai, C. F., Li, Z. X., Shi, Z.H., and Liu, G. H., 2009. Simulation of distribution pattern of heavy metals in road verge soils using neural network：A case study of modern Yellow River Delta. Acta Ecological Sinica, 29 (6): 3154-3162.

Wang, W. L., Geng, A. C., Liu, H. T., and Gao, A. G., 2009. Distribution and potential ecological risk evaluation of heavy metals in the surface sediments from the Jiulongjiang river estuary. Advances in Marine Science, 27 (4): 502-508.

Wang, X. J., Lai, J. Q., Lu, Y. H., Li, D. S., Zhou, J. H., and Wang, J. W., 2008. Main source of soil heavy metal pollution based on factor analysis in Taiyuan. Ecology and Environment, 17 (2): 671-676.

Wang, Y., Yang, Z. F., Shen, Z., Tang, Z., Niu, J., and Gao, F., 2011. Assessment of heavy metals in sediments from a typical catchment of the Yangtze River, China. Environmental Monitoring and Assessment, 172: 407-417.

Wang, Y. H., Zhang, J., and Shen, H. T., 2002. Review of accumulation features study of features study of heavy metal in sediment of tidal flat. Advance in Earth Sciences, 17 (1): 69-77.

Xia, P., Meng, X. W., Yin, P., and Liu, L. J., 2008. Heavy metal pollution and its potential ecological risk in the sediments from the Beihai intertidal zone of Guangxi Zhuang Autonomous Region. Advances in Marine Science, 26 (4): 471-477.

Xue, C. T., 2011. Origin of coastal landforms from the Zhangweixin River mouth to the Tuhai River mouth along the West Coast of the Bohai Sea. Advances in Marine Science, 29 (3): 330-338.

Yang, Y. Q., 2007. The distribution, speciation and the potentialecological risk assessment of heavy metals in the Pearl River estuary and adjacent shelf. PhD dissertation, Graduate School of the Chinese Academy of Sciences, 1-55.

Yin, W. H., Cao, Z. M., Lan, D, Z., Zhai, B., Li G. M., and Wang, S. S., 2007. Distribution characteristics and controlling factors of nutrients in surface sediments in Xiangshan Bay. Environmental Chemistry, 126 (3): 388-391.

Yin, Y. H., Zhou, Y. Q., and Ding, D., 2004. Evolution of modern Yellow River Delta coast. Maine Science Bulletin, 23 (2)：32-39.

Yu, J. B., Dong, H. F., Wang, H. B., Chen, X. B., Xie, W. J., Mao, P. L., Gao, Y. J., Shan, K., Chen, J. C., and Ma, X. M., 2011. Spatial distribution characteristics of metals in newborn coastal wetlands in the Yellow River Delta. Wetland Science, 9 (4): 297-304.

Yu, J. B., Kan, X. Y., Wang, X. H., Han, G. X., Guan, B., Xie, W. J., and Lin, Q. X., 2012. Simulative study on effects of petroleum contamination on seedling growth of phragmites australis and suaeda salsa in coastal wetland of Yellow River Delta. Scientia Geographica Sinica, 32 (10): 97-104.

Zhang, L. J., Wang, G., Yao, D., and Duan, G. Z., 2003. Heavy mental study and environment significance of offshore sediments. Marine Geology Letter, 19 (3): 6-9.

Zhang, L. X., Jiang, X. S., Zhao, M., and Li, Z. E., 2007. Pollution of surface sediments and its assessment of potential ecological risk in the Yangtze Estuary. Ecology and Environment, 6 (2): 389-393.

Zhang, L., Qin, Y. W., Zheng, B. H., Jia, J., and Lei, K., 2011. Distribution and pollution assessment of heavy metals in sediments from typical areas in the Bohai Sea. Acta Scientiae Circumstantiae, 31 (8): 1676-1684.

Zhang, Q. G., Kang, S. C., Li, C. L., Chen, F., Boukalova, Z., and Cerný, I., 2011. Assessment of elemental distribution and trace element contamination in surficial wetland sediments, Southern Tibetan Plateau. Environmental Monitoring and Assessment, 177: 301-313.

Zhou, J. L., Wu, Y., Kang, Q. S., and Zhang, J., 2007. Spatial variations of carbon, nitrogen, phosphorous and sulfur in the salt marsh sediments of the Yangtze Estuary in China. Estuarine Coastal and Shelf Science, 71: 47-59.

Zhou, X. Y., Li, Y. B., Wang, E. D., and Liu, X. Y., 2004. Heavy metal pollution and its assessment of potential ecological risk in the coastal wetland of Liaodong Bay. Environmental Science and Technology, 24 (1): 60-62.

The Bulletin of marine environment quality from Bin Zhou city in 2008, China. http://www.coi.gov.cn/gongbao/huanjing/ yanhai/ 2008/ 201107/t20110729_17610.html.

(Edited by Ji Dechun)

(Received May 9, 2013; revised December 20, 2013; accepted January 4, 2014)

© Ocean University of China, Science Press and Springer-Verlag Berlin Heidelberg 2014

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