210Pb dating to investigate the historical variations and identification of different sources of heavy metal pollution in sediments of the Pearl River Estuary, Southern China

Marine Pollution Bulletin 150 (2020) 110670

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Pb dating to investigate the historical variations and identification of different sources of heavy metal pollution in sediments of the Pearl River Estuary, Southern China

T

Zhiping Yea, Jianyao Chena,∗, Lei Gaoa,∗∗, Zuobing Lianga, Shaoheng Lia, Rui Lia, Guangzhe Jinb, Yuta Shimizuc, Shin-ichi Onoderad, Mitsuyo Saitoe, Gnanachandrasamy Gopalakrishnana a

Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-Sen University, Guangzhou, 510275, China Guangdong Ocean University, Huguangyan, Zhanjiang, Guandong Province, 524088, China Western Region Agricultural Research Center, National Agriculture and Food Research Organization, 6-12-1 Nishi-Fukatsu-cho, Fukuyama, 721-8514, Japan d Graduate School of Integrated Arts and Sciences, Hiroshima University, 1-7-1Kagamiyama, Higashi-Hiroshima, 739-8521, Japan e Graduate School of Environmental and Life Science, Okayama University, 1-1-1 Tsushima-naka, Kita-ku, Okayama, 700-8530, Japan b c

A R T I C LE I N FO

A B S T R A C T

Keywords: Sediment Heavy metal Temporal change Lead isotopes Pearl river estuary

In this study, we investigated the historical variation, source identification, and distribution of heavy metal pollution in sediments of the Pearl River Estuary (PRE) using 210Pb dating. Our results suggest that the heavy metal concentrations were higher in the western part of the estuary. For all heavy metals, Cd was significantly enriched in the sediments. The Pearl River Delta (PRD) has experienced rapid economic development in the past 40 years, a decreasing trend in heavy metal fluxes after 2004 was identified, which suggests a reduction in heavy metal concentrations due to the removal of heavy polluting industries and the effective control of sewage discharge. A binary mixing model reveals that the contributions of anthropogenic Pb ranged from 45.4 to 64%. Based on lead isotopic ratios (206/207Pb and 208/206Pb), it was found that geologic materials and industrial pollution were the main sources of heavy metals in the PRE sediments.

1. Introduction Since the 1980s, rapid industrialization and economic development have generated significant economic growth in China, but the resulting anthropogenic activities have caused severe pollution that has damaged the country's fragile ecosystems (Li et al., 2014; Gao and Chen, 2012; Yuan et al., 2014). Toxic pollutants, such as heavy metals originating from human activities, have been introduced to estuarine areas via surface runoff, waste disposal, and atmospheric processes, and have subsequently been adsorbed onto particles and accumulated in sediments (Chakraborty et al., 2014a,b; Li et al., 2001; Jha et al., 2003). One of the most serious problems associated with the persistence of heavy metals is that residues in contaminated habitats may accumulate in the food chain and generate health problems (Chakraborty et al., 2014, 2016; Chen et al., 2017; Copat et al., 2012; Liu et al., 2017; Singh and Kumar, 2017). In estuaries and coastal areas, sediments are regarded as the main sink for various pollutants following the largely uncontrolled discharge

∗

of contaminants during anthropogenic and natural processes (Liu et al., 2016; Gan et al., 2013). Pollutants in marine sediments may be released to seawater if environmental conditions change, such as pH, Eh, bioturbation, or resuspension (Simpson and Batley, 2009; Sin et al., 2001; Valdés et al., 2005; Hill et al., 2013). Compared to materials with a lithogenic origin, anthropogenic heavy metals in the sediment have high bioavailability and mobility, and can have an adverse effect on the aquatic environment (Lin et al., 2016; BirchandApostolatos, 2013). Consequently, the source identification of heavy metals by differentiating the anthropogenic contribution to metal accumulation in sediments is critical to assess aquatic environmental protection and environmental processes. However, metal concentrations or the results of a principal component analysis (PCA) provide little information on environmental behavior and source identification of heavy metals. Because natural and anthropogenic sources have different lead (Pb) isotopic signatures, stable Pb isotopes can be used to trace the origin of Pb pollution (Hu et al., 2014). Each Pb source has a distinct or overlapping isotopic ratio range. Biological fractionation and physico-

Corresponding author. Corresponding author. E-mail addresses: [email protected] (J. Chen), [email protected] (L. Gao).

∗∗

https://doi.org/10.1016/j.marpolbul.2019.110670 Received 22 July 2019; Received in revised form 10 October 2019; Accepted 15 October 2019 Available online 25 October 2019 0025-326X/ © 2019 Elsevier Ltd. All rights reserved.

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(Song et al., 2016).

chemical processes do not significantly alter isotopic Pb ratios (Yip et al., 2008). Hence, Pb isotope ratios can be used as a ‘fingerprint’ to identify lead sources in different environments such as sediments, soils, and atmospheric particles (Cloquet et al., 2006; Townsend et al., 2009). As one of the main estuary systems in the world, the Pearl River Delta has undergone rapid economic development over the past four decades. Recently, the region has become a Great Bay Area at the national-level, as promoted by China's state council. The rapid urbanization and economic growth of the area has resulted in large amounts of hazardous materials, including heavy metals generated during industrial processes, being released into the Pearl River Estuary (PRE) (Zhao et al., 2011). Heavy metal pollution has attracted the attention of both the scientiKita-kuc and regulatory communities. In recent years, numerous studies of heavy metals have been conducted in the PRE(Li et al., 2000, 2001; Zhou et al., 2004; Ip et al., 2007; Shi et al., 2010). Although these studies have assessed the levels of heavy metal pollution in the PRE, temporal variations and source identification of heavy metals in sediments remain poorly documented. In this study, surface and core sediment samples from the PRE were analyzed with the following specific objectives: (1) to investigate the spatial distribution of heavy metals in surface sediments; (2) to establish a historical record of heavy metal pollution by investigating the profiles of high-resolution sediment cores; and (3) to evaluate the intensity of heavy metal pollution using enrichment factors (EFs) and fluxes. Additionally, changes in the historical sources and anthropogenic contributions of Pb in the PRE were investigated.

2.2. Sampling program Ten surface sediments and one core (51 cm long) sediment were collected from the PRE using a gravity sampler in August 2016 (Fig. 1). The core taken at K3 was sectioned at 1-cm intervals, with the sections placed into polyethylene bags and frozen at 4–6 °C. All samples were weighed twice to determine the water content before and after being freeze-dried at −80 °C. The dried bulk samples were ground with an agate mortar and passed through a 100-mesh sieve for further geochemical and radionuclide analysis. 2.3. Laboratory analysis Sediment grain size was measured using a laser granulometer (Mastersizer, 2000; Malvern Instruments, Malvern, UK) after the destruction of organic matter with hydrogen peroxide and dispersion with Calgon. The samples were differentiated into three classes: < 4 μm (clay), 4–63 μm (silt), and > 63 μm (sand) (Shepard, 1954; Wu et al., 2017). Total heavy metal content was determined as follows Loring and Rantala (1992). First, 0.5-g sediment samples were digested in Teflon tubes with a mixture of1 mL HNO3 and 1 mL HF at 190 ± 50 °C for 48 h. Next, 1 mL HNO3 was added and the mixture was evaporated to dryness at 150 °C on a heating plate. These digestion steps were repeated with an additional acid until only a negligible amount of digestive solutions remained. Samples were dissolved with diluted HNO3, and then the solutions were analyzed for major elements of manganese (Mn), iron (Fe), and aluminum (Al) and trace elements of chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), and Pb using inductively coupled plasma-atomic emission spectroscopy (ICP-AES) and inductively coupled plasma-mass spectrometry (ICPMS), respectively. The quality assurance of the analytical results were verified using the standard reference materials GBW07312 (GSD12, stream sediments) and GBW07445 (GSF-5, Soil) from the Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Science. The recoveries obtained in the above mentioned reference materials ranged from 88.2 to 111.9%. One standard for each ten samples was randomly chosen to analysis in duplicate.The standard deviation of the duplicates was < 10%. The blank samples were also prepared and analyzed. Samples were analyzed for total organic carbon (TOC) and total nitrogen (TN) using 0.5 M HCl to remove inorganic carbon. The samples were neutralized by rinsing with deionized water before being freeze-

2. Materials and methods 2.1. Description of the study area The Pearl River is the second largest river in China in terms of discharge flow. It delivers an average annual volume of 3.26 × 1011 m3 of fresh water and 8.9 × 107 tons of sediment into the PRE (Chen et al., 2001). The catchment is located in a typical subtropical climate regime, with an annual average temperature and rainfall of 22 °C and 1690 mm, respectively (Callahan et al., 2004). The PRD is situated in the southern part of Guangdong Province (Fig. 1), with a total area of 41,600 km2and population of more than 50 million. Approximately 80% of its precipitation is received during the period from April to September (Xia, 2005). The PRD has experienced rapid socio-economic change in the last four decades, including population growth, industrialization, and urbanization. Over this period, large amounts of domestic, industrial, and agricultural effluents have been discharged into the river system and the estuary, causing severe pollution of the aquatic environment

Fig. 1. Schematic map of the sampling locations and study area. 2

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rate of 210Pb over time at core K3. Attempts were made to measure Cs activity at K3, but the values obtained did not exceed the background level. The mean sedimentation rate was calculated to be 1.24 cm/a at this site using the constant initial concentration (CIC) model (Oldfield et al., 1978), yielding a corresponding chronology of approximately 1975–2016. As shown in Fig. 2c, the sedimentary section had composition ratios of 2.16–27.15%, 55.37–75.99%, and 17.47–28.34% for clay, silt, and sand, respectively. Silt was dominant throughout the core, while sand was more abundant at the bottom at a depth of around 35–51 cm. The high sand content at the bottom of the core corresponded to flooding events in 1982 and 1988 (Luo and Le, 1996). The surface sediment samples were classified using a ternary textural diagram (Fig. 2d), which indicated a spatial variation in terms of grain size and texture in the PRE. A higher sand content was found at S10 and S4 than at the other sites, suggesting relatively large coarsegrained fractions deposited on the eastern side of the PRE. These results agree with other study in the PRE (Xiao et al., 2011).

dried. The TN and TOC contents were determined using an elemental analyzer (Vario EL Cube, Elementar, Langenselbold, Germany). The total phosphorus (TP) content was determined using a spectrophotometer (UV-2600, Shimadzu, Kyoto, Japan) after digestion by alkaline potassium persulfate. The 210Pb activities were analyzed in dry samples (2∼5 g) with a high-purity germanium (HPGe) detector (GWL-120-15; ORTEC, Atlanta, GA, USA)after 10 days of storage in sealed containers to allow for radioactive equilibration (Farkas et al., 2007). The excess 210Pb activity (210Pbex) of the sediment samples was determined by subtracting 226Ra activity from total 210Pb (210Pbtot) activity (San Miguel et al., 2004). The whole analysis was performed with an standard operation procedures (GB/T11743) (Standardization Administration of China, 2013) according to the National Standard of the People's Republic of China. All sediment radionuclide concentrations are described in Bq/kg dry weight. The radioisotope activity determination of the sediment samples was conducted at the Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences. The Pb isotopic (206Pb, 207Pb and 208Pb) composition of samples was measured by a thermal ionization mass spectrometer (Iso Probe-T, G.V. Instruments, Ltd, Manchester, UK). The radiogenic ratios of 206 207 / Pb and 206Pb/207Pb were used to determine significant variability between different samples. Stable Pb isotopic compositions were measured at the Beijing Research Institute of Uranium Geology, China National Nuclear Corp, Beijing, China. The radiogenic ratios of 206/ 207 Pb and 208Pb/206Pb were used to determine significant variability between different samples. The procedural blank for the bulk samples was < 100 pg Pb, and a standard reference material NBS 981 from National Institute of Standards and Technology, USA was used for the calibration and normalization of the sediment samples.

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3.2. Profile and surface distribution of heavy metals The profile distributions of seven heavy metals (Cr, Ni, Cu, Zn, As, Cd, and Pb) in core K3 are shown in Fig. 3, indicating historical changes of varied pollutants associated with sources. The average concentration of heavy metals followed a decreasing order as follows: Zn > Cr > Cu > Pb > Ni > As > Cd. The heavy metal concentrations in core K3 fluctuated, with the highest and the lowest concentrations at a depth of around 40 and 30 cm respectively. However, the Pb concentration was highest at a depth of 15 cm, suggesting that there may have others potential source of Pb, probably due to large amounts of coal combustion lead to increasing the heavy metals content insoil via atmospheric deposition. As one of the most important industrial cities in PRD, Dongguan city's coal consumption increased from 4.20 million tons to 17.80 million tons with the rapid industrial development during 1990–2015 (Dongguan Bureau of Statistics, 1978–2014). The variation of heavy metal concentrations was generally consistent with socio-economic development in the PRD. There were significantly high heavy metal concentrations at the depth interval of 51–39 cm corresponding to the time period of 1975–1985. Since 1978, coastal areas in China, particularly the PRD, have undergone rapid development due to China's reform and opening-up policy. The continuous increase in heavy metal concentrations could be attributed to the increased volumes of industrial, agricultural, and domestic wastewater. Over the period of 1986–1992, heavy metal concentrations displayed a downward trend at a depth of 40–30 cm, which could be related to economic adjustment and the prevailing political situation (He et al., 2000). The high heavy metal concentrations after 1992 were related to a new economic reform driven by economic transitionin 1992 (Gao et al., 2017). The Cr, Ni, Cu, and Zn concentrations tended to be

2.4. Statistical analysis Pearson correlation analysis was applied to assess element and geochemical associations. Principal component analysis (PCA) is widely used to simplify multivariate data and extract a small number of latent factors from eigenvalues and eigenvectors. In this study, PCA has been carried out to ascertain the factors that control the geochemical origin and behavior in the estuarine sediments. The above mentioned statistical calculations were conducted by using the SPSS 12.0. 3. Results and discussion 3.1. Core chronology and grain size The profie distributions of 226Ra, 10Pb and 210Pbex activity in core K3 are shown in Fig. 2a and Fig. 2b. The 210Pbex activity decreased (from surface 149.12 Bq/kg to 54.42 Bq/kg bottom) significantly with depth (Fig. 2b), indicating historic changes and a constant deposition

Fig. 2. Profile distributions of (a) 226Ra and sediments of the Pearl River Estuary (PRE).

210

Pbtot(b)

210

Pbex activity, and (c) grain size fractions at K3, and (d) a ternary diagram of grain size in the surface

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Fig. 3. Heavy metal concentrations in the sediment of core K3.

lower than the PEL, indicating that a certain degree of potential ecological risk was associated with the PRE sediments.

lower in the top layers, which could be explained by the strengthening environmental controls imposed by the local governments in the PRD. According to the Guangdong Provincial Marine Environmental Quality Bulletin (GPMEQ, 2009; GPMEQ, 2013), the total amount of heavy metals carried by the Pearl River from 2008 to 2012 decreased year by year. Another important reason for the lower heavy metal concentrations in the top sediment layers is industrial transformation and upgrading, which has forced heavily polluting industries to relocate to areas with less stringent environmental regulations in recent years. The spatial distribution of heavy metals in the surface sediments in the PRE is shown in Table 1 and Fig. 4. Among the six heavy metals measured in the sediments, Zn and Cr had the highest concentrations at 144.6 and 91 mg kg−1, respectively. At all sampling sites, the metal with the lowest concentration was Cd at 0.21 mg kg-1. All heavy metals were more highly concentrated in the western side of the PRE (Fig. 5). The result agreed with those of other studies in the PRE (Zhang et al., 2016; Xiao et al., 2010). The relatively low concentrations of these elements in the eastern side of the estuary were related to the hydraulic conditions driven by the Coriolis force (Cui et al., 2015). The heavy metals pollution in surface sediments (S1–S10) of the PRE was also compared with levels in other estuaries reported in the literature (Table 2). The average heavy metal concentrations in the PRE was higher than in any of the other areas chosen for comparison, suggesting severe pollution in the PRE. Moreover, the heavy metal concentrations were also compared with the threshold effect level (TEL) and probable effect level (PEL) values (Table 2). The TEL represents a threshold concentration below and above which adverse biological effects rarely and frequently occur, respectively (MacDonald et al., 2000). The mean Cr, Ni, Cu, and Pb concentrations exceeded the TEL, but were

3.3. Enrichment factors and fluxes To assess the status of heavy metal contamination and distinguish between anthropogenic and natural sources, it is useful to calculate the non-dimensional EF, which is defined by the following equation (Rule, 1986):

EF =  

(Csed/ CFe ) sample (Csed/ CFe )background

where (Csed/ CFe ) sample is the ratio of the concentration of the heavy metal concentration Csed and that of a reference element of Fe (CFe ) in the sampled sediment, while (Csed/ CFe )background is the natural background ratio. The results of a recent background study (Ma et al., 2014) in the PRE were used to assess heavy metal enrichment and contamination. To compensate for the grainsize and mineralogical variations of heavy metals in sediment, a common approach is to normalize the geochemical data using one conservative element as a grainsize proxy, e.g., Al, Fe, scandium (Sc), Mn, or lithium (Li) (Pan and Wang, 2012; Huh et al., 1998). In this study, we adopted Fe as the normalizing element for the following reasons: (a) Fe is a better predictor of background levels than Al and Sc due to the similarities in the geochemistry of Fe and many other heavy metals under both oxic and anoxic conditions, which can compensate for the diagenetic mobility of heavy metals to some extent (Xia et al., 2011; Summers et al., 1996; Schiff and Weisberg, 1999); and (b) Fe in core K3 had a stronger positive correlation with the heavy metals than Al and Sc. Heavy metal EFs were divided into five classes:

Table 1 Heavy metal concentrations in the surface sediments of the Pearl River Estuary (unit: mg·kg−1). Heavy metals

Cr Ni Cu Zn Cd Pb

Sampling sites S1

S2

S3

S4

S5

S6

S7

S8

S9

S10

85.7 41.1 39.7 131.7 0.4 45

88.2 42.1 42.9 140.4 0.51 50

84 39.19 47.03 132.5 0.59 49.9

68.67 27.2 26 85.8 0.29 36.1

78.5 33.3 26.41 107.8 0.38 43.2

91 40.1 42.3 144.6 0.82 50.8

88.8 42.1 43.1 132.1 0.53 44.7

83.3 37.2 47.7 128.9 0.6 38.6

86 39.1 35.3 130.4 0.21 51.2

43.4 19.6 30.4 83.2 0.34 37.9

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Fig. 4. Spatial distribution of heavy metals in the Pearl River Estuary (PRE).

where MFx is the heavy metal flux at the ‘x'th depth interval (mg cm−2y−1), R is the 210Pb sedimentation rate (cm y−1), Cx is the metal concentration at the ‘x’ th interval (mgg−1), and ρd is the dry bulk density at the ‘x’ th interval (gcm−3). Heavy metal fiuxes in vertical sediment profiles are shown in Fig. 5b. The variations in heavy metal fluxes were generally similar to those of the metal concentrations. The concentration profiles, Fe-normalized EFs, and fiuxes obtained from core K3 indicated that the heavy metals were strongly accumulated from1975–1986, reflecting the impacts of early urban and economic development in the PRD. The decrease in the heavy metal fluxes after 2004 (except Cd) could be related to the relocation of heavily polluting industries and the effective control of the amount of sewage discharged into the estuary.

indicating that the metals could be primarily adsorbed by fine particles in sediment. Conversely, the sand content was significantly and negatively correlated with the metals. The Sc concentration was correlated neither with the heavy metals nor the silt content, indicating that it could have different transfer processes under acid and alkaline conditions (Gonzalez et al., 2006). The high correlation coefficients among most heavy metals indicated that they originated from similar sources or were incorporated in sediments in a similar way. The results of a principal component analysis (PCA) indicated that three factors described 80.22% of the total variance. The heavy metals were assembled around each factor with significant loadings. The three main groups of elements were indicative of three diverse sources (Table 4). The first factor accounted for 55.5% of the total variance and accounted for most of the heavy metals (i.e., Cr, Ni, Cu, Zn, As, Cd, Pb, Mn, Fe, and Al) and TOC, with high loadings (0.61–0.97). This group includes the main heavy metals that are typically considered to be anthropogenic pollutants (Cr, Ni, Cu, Zn, As, Cd, and Pb), originating mainly from industrial and untreated sewage (Ip et al., 2004; Wang, 2004). Factor 2 had high loadings of Sc and accounted for 14.3% of the total variance. As a trace element in sediments, Sc is released from rockforming elements and minerals during weathering and is only minimally affected by human activities (Zhang et al., 1988). Although Sc had the highest loadings in factor 2, there were also relatively large loadings of Mn, Fe, and Al (0.27–0.55). Al is a typical lithogenic element that is extremely inert in the marine environment and is usually held in the lattice of aluminosilicate minerals (Audry et al., 2004; Price et al., 1999). Based on relatively large loadings of Sc, Mn, Fe, and Al (0.27–0.55) in factor 2, these metals could be derived from natural source. The third factor accounted for 10.4% of the total variance and included TN, TP, and TOC, with high loadings (0.52–0.66), indicating domestic wastewater and agricultural sources.

3.4. Provenance tracing

3.5. Source identification of heavy metals in the sediment

A correlation analysis revealed that except for Sc, the metals in coreK3 sediments were positively correlated with each other (Table 3). TOC was positively correlated with most of the heavy metals. Likewise, silt also has a positive correlation with the most of the metals,

Usually, the 206Pb/207Pb ratio for materials with natural sources is higher than 1.20, while for anthropogenic sources it ranges from 0.96 to 1.20 (Wang et al., 2006). The ratios of 206Pb/207Pb in core K3 are shown in Fig. 6. Most of the isotope ratios were less than 1.20,

EF < 2 slight or no enrichment, 2 ≤ EF < 5 moderate enrichment, 5 ≤ EF < 20 severe enrichment, 20 ≤ EF < 40 very severe enrichment, EF > 40 extremely severe enrichment (Sutherland, 2000). The EFs for Cr, Ni, Zn, and As were relatively low over the entire profile (Fig. 5a). Values for those metals were relatively close to the natural background, suggesting they were not significantly affected by anthropogenic activities. Among the metals investigated, Cd and Cu had the highest EF values, indicating the effects of human activities that have released huge amounts of Cd and Cu into the PRE. Cd was significantly enriched in the sediments, with a high EF of over 5. Despite the EF values of Cr, Zn, and As being lower than 2, a slight but consistently increasing trend from a depth of 7 cm up to the surface was observed. It is therefore necessary to continuously monitor the levels of these heavy metals to fully assess the ecological risks in this region. The heavy metal and nutrient fluxes in core K3 were calculated as follows (Dai et al., 2007; Wang et al., 2015):

M Fx = R ⋅Cx ⋅ ρd

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Fig. 5. Profile distributions of (a) heavy metal enrichment factors (EFs) and (b) heavy metal fluxes (MFx) from the core K3.

1980, the Pb isotopic ratios reduced due to the rapid urbanization and industrialization in the PRD. However, the 206Pb/207Pb ratios increased again after 2006, mainly due to stringent environmental protection measures regarding the discharge of heavy metals. In general, the low

indicating that they were affected by human activities. Before 1980, the Pb isotopic ratios of the sediments were relatively high because the PRD was mainly an agricultural area with few industrial facilities, and the PRE primarily received sediment inputs from natural sources. After

Table 2 Comparison of heavy metal concentrations in the surface sediments of the Pearl River Estuary and other areas (unit: mg·kg−1). Samples

Cr

Ni

Cu

Zn

Cd

Pb

References

Mean conc. Pearl River Estuary, China Liaodong Bay, Bohai Sea, China North Yellow Sea South China Sea Yellow River Estuary, China Changjiang Estuary, China Changhua Estuary, Hainan Egypt Bay, USA 14.2 Masan Bay, Korea Black Water Estuary, UK Threshold effect level (TEL) Probable effect level (PEL)

79.77 89 46.4 48.9 57.9 63.7 97.8 53.1 0.39 67.1 48 52.3 160.4

36.14 41.7 21.6 22 n.a. 71.3 40.2 23 n.a. 28.8 68 15.9 42.8

38.1 46.2 15.8 14.44 34 21.5 37.68 15 14.2 43.4 45 18.7 108.2

121.77 150.1 57.8 57.3 108 71.3 98.65 73.7 77.5 206.3 95 124 271

0.46 n.a. 0.1 0.09 0.25 n.a. 0.19 0.09 0.44 n.a. 0.3 0.68 4.21

44.77 59.3 31.8 24.1 24.1 21.6 36.86 27 27 44 42 30.2 112.2

This study Zhou et al. (2004) Hu et al. (2010) Huang et al. (2013) Zhang and Du (2005) Wang and Zhang (2002) Sheng et al. (2008) Hu et al. (2013) Osher et al. (2006) Hyun et al. (2007) Emmerson et al. (1997) MacDonald et al. (2000) MacDonald et al. (2000)

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Table 3 Pearson's correlation coefficients for the metal concentrations in core K3.

K3(N=51) Cr Ni Cu Zn As Pb Cd Mn Fe Al Sc TN TOC TP Clay Silt Sand

Cr

Ni

Cu

Zn

As

Pb

Cd

Mn

Fe

Al

Sc

TN

TOC

TP

Clay

Silt

Sand

1 .835** .916** .875** .819** .584** .781** .734** .619** .383** -.006 .268 .502** .219 -.195 .290* -.226

1 .941** .909** .884** .665** .511** .841** .795** .736** .091 .378** .564** .211 -.173 .413** -.374**

1 .957** .885** .642** .692** .784** .679** .520** .020 .378** .506** .237 -.265 .348* -.255

1 .915** .738** .719** .795** .673** .546** .001 .307* .467** .279* -.266 .405** -.315*

1 .670** .606** .847** .652** .580** .059 .234 .443** .170 -.122 .369** -.373**

1 .525** .473** .401** .514** -.052 .197 .358** .554** -.147 .578** -.568**

1 .404** .234 -.040 -.252 .092 .212 .206 -.271 .103 .048

1 .793** .675** .204 .263 .438** .029 -.031 .228 -.274

1 .832** .384** .249 .475** .006 -.051 .263 -.280*

1 .393** .234 .498** .110 .089 .443** -.563**

1 -.090 -.018 -.291* .078 .037 -.090

1 .527** .379** -.232 .122 -.012

1 .322* .060 .189 -.289*

1 -.278* .350* -.225

1 -.463** -.151

1 -.801**

1

respectively. The anthropogenic contribution (%) of heavy metals in sediment samples was calculated using the following equation (Hansmann et al., 2000):

Table 4 Total variance of heavy metals in sediments explained by PCA matrices. Heavy metals

PC1

PC2

PC3

Cr Ni Cu Zn As Cd Pb Sc Mn Fe Al TOC TN TP Total variance % Cumulative variance %

.89 .97 .95 .96 .92 .62 .73 .09 .86 .79 .69 .61 .40 .30 55.5 55.5

-.17 .09 -.10 -.13 .00 -.53 -.27 .79 .27 .49 .55 -.02 -.17 -.57 14.3 69.7

-.23 .01 -.13 -.16 -.19 -.46 .08 -.03 -.12 .05 .29 .52 .66 .54 10.41 80.11

Fig. 6. Anthropogenic contribution of Pb and the Pearl River Estuary (PRE).

206

206

[Pb]contribution anthropogenic  % =

206

Pb ⎛ 207Pb ⎞  −     ⎛ 206 ⎞ ⎝ Pb ⎠anthropogenic ⎝ Pb ⎠natural 206

206

Pb ⎛ 207Pb ⎞              −     ⎛ 207 ⎞ ⎝ Pb ⎠sample ⎝ Pb ⎠natural

× 100 The proportions of anthropogenic Pb in the sediment core are shown in Fig. 7. The anthropogenic contribution of Pb increased from 45.4% to 64% in the PRE over the past 40 years. This was consistent with the fact that the estuary received increasing amounts of anthropogenic Pb from the PRD. The stable Pb isotopic ratios of 206Pb/207Pb and 208Pb/207Pb are robust tools that can be used to differentiate between Pb sources and their biological availability in the aquatic system (Teutsch et al., 2001). In core K3, the 206Pb/207Pb and 208Pb/206Pb ratios displayed similar patterns to those of river surface sediments and geological materials in the north of the region, but they were very different from aerosol and automobile exhaust sources (Fig. 7). As one of three tributaries of the Pearl River, the North River, which flows through the most important Pb–Zn mine in southern China (Fankou Mine), has been used to transport Pb and Zn to the industries in the PRD (Ip, 2005). Therefore, Fankou Pb–Zn ores could be a potential source of anthropogenic Pb in the PRE. Additionally, the values of the206Pb/207Pb and 208Pb/206Pb

Pb/207Pb ratios in core K3 of

206 Pb/207Pb ratios of less than 1.2 for most samples indicated that the sediments had been affected by anthropogenic inputs over the last 40 years. We assessed the contribution of anthropogenic and natural sources in the sediment cores based on two end-member mixing models. This approach has been shown to be effective in assessing the relative proportions of anthropogenic and natural sources in marine sediments (Hu et al., 2012). In our study area, we adopted 1.181 and 1.219 as the 206 Pb/207Pb values of the anthropogenic and natural end-members,

Fig. 7. The208Pb/206Pb ratios versus the 206Pb/207Pb ratios in core K3 and other relevant sites in the Pearl River Delta (PRD). 7

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ratios were also similar to those of contaminated soils in the PRD, suggesting that the anthropogenic sources of Pb could also include polluted soils.

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4. Conclusions We determined the spatial distribution, historical variability and source identification of heavy metals using surface and core sediments collected from the PRE in southern China. A high-resolution sedimentary record was obtained from a sediment core using the 210Pb chronology. From the reconstruction and spatial distribution of heavy metals, the following conclusions were drawn: 1. The history of heavy metal concentrations was found to be generally consistent with socio-economic changes in the PRD. There was a lower heavy metal concentrations in sediment could be affected by higher sand content in the eastern side of the estuary. 2. For all heavy metals, except Cd and Cu, there was only slight pollution in the core sediments. Cd was enriched in the sediments, with a high EF of over 5.0, due mainly to human activities. Despite low EFs of less than 2 for Cr, Zn, and As, the core profile showed a slight but consistently increasing trend from a depth of 7 cm up to the core surface. It is therefore necessary to continuously monitor these heavy metals to fully understand the metal accumulation processes and assess the ecological risks in this region. 3. Although the PRD has experienced rapid economic development in the past 40 years, the heavy metal flux (except Cd) decreased after 2004, which suggests a reduction in pollutant emissions due to the relocation of heavily polluting industries and the effective control of sewage discharge. 4. Three principal groups of elements were identified: (1) Cr, Ni, Cu, Zn, As, Cd, and Pb; (2) Sc, Mn, Fe, and Al; and (3) nutrients, indicating industrial sources, lithogenic sources, and domestic wastewater and agricultural discharges, respectively. The206Pb/207Pb vs 208 Pb/206Pb ratios in the sediments reflected a mixture of different sources from geological materials and industrial pollution. The contributions of anthropogenic sources increased over time from 45.4% to 64% in the sediment cores based on the results of a two end-member mixing model. This was consistent with the fact that the estuary received increasing levels of anthropogenic Pb from the PRD. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgement This work was Supported by the National Natural Science Foundation of China (41771027 and 41701585), the Fundamental Research Fund for the Central Universities of China (17lgpy40), and the Natural Science Foundation of Guangdong, China (2017A030310309), Provincial Special Fund for Economic Development (Marine Economic Development) (GDME2018E005), the Scientifc and Technological Innovation Project of the Water Sciences Department of Guangdong Province (2018–2021), Asia Pacific Network for Global Change Research (APN) (CRRP2019-09MY-Onodera) and 1616FG@GPS INQUA. References Audry, S., Schäfer, J., Blanc, G., Jouanneau, J.M., 2004. Fifty-year sedimentary record of heavymetal pollution (Cd, Zn, Cu, Pb) in the Lot River reservoirs (France). Environ. Pollut. 132 (3), 413–426.

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