Arsenic pollution of sediments in China: An assessment by geochemical baseline

Science of the Total Environment 651 (2019) 1983–1991

Contents lists available at ScienceDirect

Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Arsenic pollution of sediments in China: An assessment by geochemical baseline Lanfang Han a,b, Bo Gao a,b,⁎, Hong Hao b, Jin Lu a,b, Dongyu Xu a,b a b

State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China Department of Water Environment, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• A national-scale assessment and a review were conducted on As in sediments in China • The PRB showed high As levels, with 64.4% from human contributions. • The RGB values in the SRB, YtRB, and PRB were higher than the corresponding RSB. • As contamination was significant even in undeveloped southwestern river basins. • Temporal changes of As in three major basins matched with that of As in wastewater.

a r t i c l e

i n f o

Article history: Received 25 August 2018 Received in revised form 29 September 2018 Accepted 29 September 2018 Available online 02 October 2018 Editor: Jay Gan Keywords: Arsenic (As) Sediment China River basins Geochemical baseline National-scale assessment

a b s t r a c t Arsenic (As) contamination in sediments has been reported worldwide. However, few studies have investigated As contamination on a national scale in China. This study aims to address this gap by analyzing the existing literature on As contamination and sediment samples collected from ten main river basins: the Songhua River Basin (SRB), Liao River Basin (LRB), Hai River Basin (HRB), Yellow River Basin (YRB), Huai River Basin (HuRB), Yangtze River Basin (YtRB), Pearl River Basin (PRB), Southeastern River Basin (SeRB), Southwestern River Basin (SwRB), and Northwestern River Basin (NwRB). Regional geochemical baseline (RGB) values of As in the sediments of river basins were calculated to estimate human contributions of As using normalization and cumulative frequency distribution curves. The established RGB values in the SRB, YtRB, and PRB were higher than the corresponding regional soil background (RSB), possibly because of the high intensity of human activities in the SRB, YtRB, and PRB. Taking RGB and RSB values as the background references, contamination assessment yielded important information on As contamination in China. With high As contributions from Yunnan province, the PRB suffered from the highest level of contamination, and the mean human contribution of As in the PRB was 64.4%. The contamination levels in the less developed southwestern regions were even higher than in some river basins in economically developed regions (e.g., YRB). In addition, As in the PRB and YtRB was found to be partially contributed by industrial wastewater discharge, and the response of As contamination in sediments to industrial wastewater discharge was analyzed. The temporal change (2004–2016) of As in sediments from the PRB, YtRB, and YRB corresponded well with that of As discharged in wastewater within the corresponding river basins. This study thus serves as a valuable foundation for policies focused on ameliorating As contamination in China. © 2018 Elsevier B.V. All rights reserved.

⁎ Corresponding author at: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China. E-mail address: [email protected] (B. Gao).

https://doi.org/10.1016/j.scitotenv.2018.09.381 0048-9697/© 2018 Elsevier B.V. All rights reserved.

1984

L. Han et al. / Science of the Total Environment 651 (2019) 1983–1991

1. Introduction Arsenic (As) contamination is of great environmental concern owing to its high toxicity, many sources, non-biodegradable properties, elevated concentrations in the environment, and accumulative behavior (Garelick et al., 2009). High As concentrations in the environment are attributed to both natural factors, such as release following weathering and erosion of arsenic-bearing rocks and soils, and human activities, such as historic and recent gold- and base-metal processing, use of arsenical pesticides and wood preservatives, thermal and coal-fired power generation, and improper disposal of domestic and industrial waste materials (Wang and Mulligan, 2006). Acute or chronic exposure to elevated As concentrations has harmful effects on human health and ecosystems (Kapaj et al., 2006). Moreover, As levels are sustained and difficult to be eliminated in the short-term (Hall, 2002). It has been estimated that the population of China exposed to elevated As ranges from 0.58 million (Yu et al., 2007) or 1.85 million (He and Charlet, 2013) to as many as 19.6 million (Rodríguez-Lado et al., 2013). Substantial amounts of As in aquatic environments are deposited into the sediment (Ruilian et al., 2008). However, sediment-bound As can be recycled back into the water column through chemical and biological processes (Guo et al., 1997; Sun et al., 2016). Therefore, sediments serve as the main repository and source of As in aquatic environments (Wei et al., 2016). In this sense, As contents in sediment can, to some extent, reflect the historical information and general contamination status of As in a water body. At present, several studies have reported As contamination levels in the sediments of various river basins in China. For instance, Wei et al. (2016) investigated the distribution of As in the sediments from the Three Gorges Reservoir section of the Yangtze River, and found that the concentrations of As fluctuated near background levels. Zhai et al. (2017) reported the spatial distribution and assessed the risk of As in mainstream sediments of the Yangtze River. Zhao et al. (2016) focused on the Yellow River, and observed that As contributed to 29.54% of the total potential ecological risk of heavy metals in the sediments. Wang et al. (2010) revealed that As in the sediments of the Guangzhou section of the Pearl River was generally higher than the probable effect level (i.e., the concentration above which adverse effects are likely to occur). However, most investigations have been conducted at the basin scale. Further, inconsistent sampling procedures and different sampling depths of sediments across studies have rendered the direct comparison of As contamination among different basins difficult. Moreover, data on As contamination in river basins in the southeastern, southwestern, and northwestern regions of China remain limited. Thus, an assessment of As contamination on a national scale is not possible using currently available data. A national survey utilizing standard and consistent sampling procedures is urgently needed to acquire a comprehensive perspective of As contamination in basin sediments throughout China. This information, once collected, will provide a valuable scientific basis for the future policy formulation. In traditional contamination assessments of metals in river basins, the background value in the sediment or soil for the province, state, or the national background value has often been chosen as the reference. However, the natural background does not consider the natural variation of metals in the environment. Moreover, due to the increasing intensity of human activities, a “natural background” that strictly refers to the pristine geochemical composition does not exist. Estimation of an “anthropic background” of As in a given river basin is fundamentally important for the scientific assessment of As contamination. A “geochemical baseline” represents the background conditions that contain a certain degree of human impact on the environment (Wei and Wen, 2012; Tian et al., 2017). It can be used to distinguish between the natural concentrations and anthropogenic concentrations within each sample. Therefore, the determination of a regional geochemical baseline (RGB) helps researchers to more scientifically evaluate the contamination of As in river basins in both China and worldwide.

This study used consistent sampling procedures to collect 881 sediment samples from ten river basins in China; these were: the Songhua River Basin (SRB), Liao River Basin (LRB), Hai River Basin (HRB), Yellow River Basin (YRB), Huai River Basin (HuRB), Yangtze River Basin (YtRB), Pearl River Basin (PRB), Southeastern River Basin (SeRB), Southwestern River Basin (SwRB), and Northwestern River Basin (NwRB). The basins under investigation covered 30 provinces and most of the water systems across the country. The RGB values of As in river basins were determined using normalization and cumulative frequency curves. Taking the regional soil background (RSB) and RGB as the reference values, three commonly used contamination assessment methods, namely, sediment quality guidelines (SQGs), the contamination factor (CF), and the geo-accumulation index (Igeo), were obtained to evaluate As contamination levels in the river basins. Furthermore, results were compared with data from previous years to identify and explain temporal variations in As concentrations in the river basins. 2. Materials and methods 2.1. Sample collection and analysis of as contents Samples were collected from 881 sites across 30 provinces between 2003 and 2004 year. Seven major river basins and three river basins in the interior of the southeastern, northwestern, and southwestern regions were covered. Fig. S1 illustrates the geographic distribution of these basins. Sampling sites were located by using Global Positioning System (GIS) data. Hydrological Bureau personnel used the same sediment sampler to collect all of the sediment samples following procedures designed to obtain representative samples. Before use, all of the sediment sampling containers and equipment were acid-cleaned. Three sub-samples were collected at each sampling site using a grab sampler and mixed to gain a homogeneous representative sediment sample, which was stored in plastic containers. During transport, the containers were kept in an icebox. After removing large stones and detritus, samples were freeze-dried. Subsequently, the sediments were ground and passed through a 180 μm mesh sieve to make sure the consistency of physical properties for further analyses. An inductively coupled plasma-mass spectrometer (ICP-MS; Elan DRC-e, Perkin Elmer, USA) was adopted to determine the total As concentrations in samples. Quality controls for the strong acid digestion method included reagent blanks, duplicate samples, and standard reference materials. Controls show that there were no signs of contamination in the analyses. The accuracy of the procedures employed to analyze As in the sediments was evaluated using a certified stream-sediment reference material (GSD-12, GBW07312), which delivered a recovery of 99.3%. 2.2. Total organic carbon (TOC) analysis and pH measurement Total organic carbon (TOC) of the sediments was determined according to the national standard method of China (GB7857–1987). The pH values of the sediments were measured with the use of a pH meter with a sediment to deionized water ratio of 1:5. 2.3. Establishment of regional geochemical baselines (RGBs) The RGBs of As in seven river basins (the SRB, LRB, HRB, YRB, HuRB, YtRB, and PRB) at which many sediment samples (N N 50) were collected, were determined according to the methods described in previous studies (Ramos-Miras et al., 2011; Karim et al., 2015; Tian et al., 2017). The cumulative frequency distribution (CFD) was plotted on the x-axis and the As concentration was plotted on the y-axis. Prior to plotting the CFD curves, a Kolmogorov-Smirnov (K-S) test was conducted to evaluate the As concentration distributions. For the CFD curves, extreme values were deleted until the remaining data met the criteria for linear regression (P b 0.05 and R2 N 0.95) (Fig. S2), and the minimum and maximum values within the regression line were used

L. Han et al. / Science of the Total Environment 651 (2019) 1983–1991

to represent the lower and upper inflexions (i.e., the ranges of RGBs). The remaining data were then averaged as RGBs. 2.4. Assessment of As contamination Assessment of As contamination levels was performed by calculating the contamination factor (CF) (Hakanson, 1980) and geo-accumulation index (Igeo) (Antoniadis et al., 2017; Müller, 1969). Both the RGB and RSB (CNEMC, 1990) were selected as background references when calculating CF and Igeo. The details on the calculation of CF and Igeo are shown in the supplementary materials. 2.5. Compilation of historical data International literature published from 1990 to 2017 was searched using keywords that included “arsenic”, “sediment”, and “PRB/YRB/ YtRB/SRB/LRB/HuRB/HRB.” We identified several publications during the period of 2004–2016 with substantial research focused on the YRB, YtRB, and PRB (Fig. S3). Due to the relatively high availability of data on the YRB, YtRB, and PRB, published data on their As concentrations from 2004 to 2016 were further gleaned from the Institute for Scientific Information (ISI) Web of Science and Google Scholar. Studies that did not include quality controls in analytical procedures were excluded to guarantee data quality. All collected data are listed in Tables 1–3. 2.6. Statistical analysis All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) version 16.0. The Pearson's correlation coefficient was used at significance levels of P b 0.05 and P b 0.01. 3. Results and discussion 3.1. Assessment of As contamination in sediments on a national scale 3.1.1. As concentrations in sediments Table 4 lists the descriptive statistics of As concentrations in the sediments of the examined river basins. As contents presented considerable variation (0.29–333.04 mg/kg) among different river basins, with an average ± standard deviation (S.D.) of 13.99 ± 11.17 mg/kg. As data from all the river basins followed normal distributions, they satisfied the criteria of the K-S test for normality (P N 0.05). Average As concentrations occurred in the sequence: SwRB N PRB N YtRB N NwRB N LRB N HRB N YRB N SRB N SeRB N HuRB, and only three river basins, the YtRB, PRB, and SwRB, registered As contents higher than the mean of the ten basins (Table 4 and Fig. 1a). Specifically, As concentrations of the PRB and SwRB were 2–3 times higher than the mean of the ten

Table 1 Arsenic concentration (mg/kg) in the sediment of the Pearl River Basin in China during 2004–2016. Year

Sampling site

No.

As

References

2004 2004 2005 2006 2007 2007 2008 2009 2009 2010 2010 2011 2011 2012 2013

Guangzhou section Upper, middle and lower reaches Guangdong section Estuary Guangzhou section Estuary Estuary Estuary Zhuhai section Guangdong section Guangdong section Estuary Lower reaches Guangdong section Mainstream

91 120 77 16 15 36 8 21 8 9 4 31 39 10 27

25 23.2 17.8 ± 7.5 33.1 24.6 3.0 29.8 17.4 6.8 9.5 19.6 14.1 22.9 14.5 56.7

Niu et al. (2006) Present study Woods et al. (2012) Yang et al. (2009a) Wang et al. (2010) Zhang et al. (2013) Du (2013) Ye et al. (2012) Wang et al. (2015b) Cai et al. (2011) Duan et al. (2014) Wang et al. (2014a) Chen et al. (2012) He and Yuan (2014) Liu et al. (2015)

1985

Table 2 Arsenic concentration (mg/kg) of the sediment in the Yangtze River Basin in China during 2004–2016. Year

Sampling site

No.

As

Reference

2004 2005 2005 2005 2005 2006 2006 2006 2006 2007 2007 2007 2007 2007 2008 2009 2009 2010 2010 2010 2010 2010 2010 2010 2011 2011 2011 2011 2012 2012 2012 2013 2014 2015

Upper, middle and lower reaches Upper, middle and lower reaches Estuary Wuhan section Wuhan section Upper, middle and lower reaches Middle reaches Shanghai section Estuary Upper, middle and lower reaches Lower reaches Upper, middle and lower reaches Upper, middle and lower reaches Jiangsu section Three Gorges Reservoir Estuary Three Gorges Reservoir Three Gorges Reservoir Estuary Three Gorges Reservoir Three Gorges Reservoir Shanghai section Shanghai section Estuary Estuary Jiangsu section Shanghai section Three Gorges Reservoir Estuary Upper reaches Three Gorges Reservoir Anhui section Three Gorges Reservoir Shanghai section

193 10 49 36 36 21 13 22 35 59 6 17 59 83 24 22 26 1 27 73 15 30 33 13 30 10 30 84 20 NG 21 15 18 43

14.9 25.1 9.9 15.4 15.6 31 ± 28 14.4 11.6 10.5 19.3 66.8 25.9 19.3 13.5 18.1 11.4 12.3 16.6 14.5 14.1 30.0 9.0 10.1 8.2 9.1 16.0 10.0 8.9 9.4 7.2 4.0 10.6 14.3 ± 2.3 13.5

Present study Liu and Li (2011) Fang et al. (2012) Wang et al. (2011) Yang et al. (2009b) Müller et al. (2008) Yi et al. (2008) An et al. (2009) Sheng et al. (2008) Song et al. (2010) Yi et al. (2008) Yi et al. (2011) Song et al. (2010) Song et al. (2011) Wang et al. (2012) Sun et al. (2011) Gao et al. (2014) Xiao et al. (2011) Fang et al. (2013) Gao et al. (2015) An et al. (2012) Wang et al. (2014b) Li et al. (2013) Zhao et al. (2012) Wang et al. (2015a) Fu et al. (2013) Liu et al. (2016) Feng et al. (2016) Li et al. (2014) Shi et al. (2015) Ao et al. (2014) Qin et al. (2015) Wei et al. (2016) Hu et al. (2015)

NG: Not given.

basins. In addition, As in the PRB and SwRB was significantly higher than that in the Mekong River (Hoang et al., 2010) and Red River (Berg et al., 2007). Thus, As was relatively abundant in the sediments of the PRB and SwRB. Two independent samples tested via MannWhitney U further validated that As concentrations in the PRB and SwRB were statistically significantly higher than in the other eight basins (P b 0.05). Table 3 Arsenic concentration (mg/kg) of the sediment in the Yellow River Basin in China during 2004–2016. Year

Sampling site

No.

As

References

2004 2004 2004 2005 2005 2007 2007 2008 2008 2008 2008 2009 2010 2011 2011 2012 2012 2014 2014 2015 2015 2016

Estuary Upper, middle and lower reaches Upper, middle and lower reaches Estuary Estuary Shandong section Estuary Upper reaches Inner Mongolia section Henan section Shandong section Estuary Lower reaches Estuary Estuary Estuary Lower reaches Estuary Estuary Henan section Shandong section Middle reaches

11 15 95 8 8 15 31 9 9 7 40 34 15 7 5 17 48 18 6 14 6 14

12.6 ± 3.8 12.9 9.9 7.9 ± 0.9 6.5 ± 0.5 22.4 13.1 27.1 11.3 17.8 13.9 7.7 ± 2.3 8.6 6.5 10.2 9.1 15.8 12-18 10.5 8.7 10.5 9.1

Wu et al. (2007) Yuan et al. (2008) Present study Wu et al. (2007) Wu et al. (2007) Nie et al. (2010) Hu et al. (2011) Cui et al. (2011) Zhao et al. (2008) Luo et al. (2008) Wang et al. (2017) Zhang (2010) Luo et al. (2011) Zhang (2013) Zhang (2013) Zhang et al. (2014) Zhao et al. (2016) Li et al. (2016) Lin et al. (2016) Yan et al. (2016) Lin et al. (2016) Yan et al. (2016)

1986

L. Han et al. / Science of the Total Environment 651 (2019) 1983–1991

Table 4 Concentration of As in the sediment of the ten river basins examined in this study. Basin

No.

SRB LRB HRB YRB YtRB PRB HuRB SeRB SwRB NwRB

59 74 71 95 193 140 175 39 6 29

Concentration Min.

Max.

Mean

S.D. a

CV (%) b

K-S test

2.26 1.80 1.85 1.67 0.74 0.58 0.29 2.08 6.92 3.89

19.14 68.88 41.57 41.35 114.28 333.04 34.00 19.76 79.97 38.02

8.93 10.34 10.34 9.87 14.90 23.24 5.35 7.52 36.15 13.25

3.98 12.14 6.55 4.76 13.82 32.01 3.98 4.22 32.84 8.15

44.54 117.38 63.36 48.17 92.73 137.72 74.41 56.10 90.83 61.50

0.90 2.41 1.42 1.94 2.84 2.76 2.33 0.70 0.47 1.24

RSB c

RGB d

6.70 8.20 9.80 9.40 9.30 6.80 8.90 5.10 10.80 10.00

8.76 8.11 9.01 8.77 11.64 8.35 8.03 – – –

CF e

Igeo f

Ranthropogenic g

RSB

RGB

RSB

RGB

1.33 1.26 0.91 1.05 1.59 3.42 0.89 1.47 3.35 1.33

1.02 1.45 1.15 1.13 1.27 2.64 1.11 – – –

−0.32 −0.74 −1.11 −0.64 −0.28 0.39 −1.12 −0.25 0.60 −0.39

−0.71 −0.54 −0.61 −0.54 −0.60 0.091 −0.93 – – –

1.96 45.43 14.75 12.56 28.01 64.44 11.18 – – –

a Standard deviation; b Coefficient of variation; c Regional soil background (RSB) cited from the study of CNEMC (1990); d Regional geochemical baselines (RGB); e Contamination factor (CF) was calculated on the basis of RSB and RGB; f Geo-accumulation index (Igeo) was calculated on the basis of RSB and RGB; g Contribution rate of anthropogenic activities. The abbreviations represent the following: Songhua River Basin (SRB), Liao River Basin (LRB), Hai River Basin (HRB), Yellow River Basin (YRB), Huai River Basin (HuRB), Yangtze River Basin (YtRB), Pearl River Basin (PRB), Southeastern River Basin (SeRB), Southwestern River Basin (SwRB), and Northwestern River Basin (NwRB).

Co nc entratio n (mg/kg)

For all of the river basins, the sediments showed significant heterogeneity in As concentrations, as evidenced by their large coefficient of variation (CV) values (Table 4). Previous studies have suggested that organic carbon plays an important role in controlling the distribution of heavy metals (Sun et al., 2013; Han et al., 2017). Like As, TOC contents in the sediments of the ten river basins varied notably, ranging from 0.005–50.00% (average value: 3.779%) (Table S1). TOC was correlated with As, and a significantly positive relationship was observed in the sediments of four river basins (HRB, YtRB, HuRB, and SeRB) (Fig. 4a and b). This highlights the fact that the heterogeneous concentration of As in the sediments of the four river basins was partly driven by their TOC contents (14% for HRB, 10% for YtRB, 12% for HuRB, and 14% for SeRB). Additionally, pH has been proposed as an important factor

80

affecting the distribution of As in aquatic environments (Masscheleyn et al., 1991). However, no significant correlation was observed between pH and As (P N 0.1) in any of the river basins examined. Thus, the impact of pH on the distribution of As was not evident in this study. 3.1.2. Determination of regional baseline values The estimated RGB values of As in the seven major river basins were as follows: SRB, LRB, HRB, YRB, YtRB, PRB, and HuRB were 8.76, 8.11, 9.01, 8.77, 11.64, 8.35, and 8.03 mg/kg, respectively (Table 4). The RGB values were comparable with the corresponding RSB values of the LRB, HRB, YRB, and HuRB, but higher than the RSB values of the SRB, YtRB, and PRB (CNEMC, 1990), and this discrepancy may be due to the high intensity of human activities (e.g., coal-fired power generation,

a

60 40 20 0

B B B B B B B B B B SR LR HR YR YtR PR HuR SeR SwR NwR

6

8

b

5 4

CF

CF

6 4

1 0

B B B B B B B B B B SR LR HR YR YtR PR HuR SeR SwR NwR

3

d

2

B SR

B LR

B HR

B B YR YtR

B B PR HuR

B LR

B HR

B B YR YtR

B B PR HuR

e

1

Igeo

Igeo

3 2 1 0 -1 -2 -3 -4

3 2

2 0

c

0

-1 -2 B B B B B B B B B B SR LR HR YR YtR PR HuR SeR SwR NwR

-3

B SR

Fig. 1. Concentrations (a), contamination factor (CF) based on regional soil background (RSB) (b) and regional geochemical baseline (RGB) as the reference (c), and geo-accumulation index (Igeo) based on RSB (d) and RGB (e) of arsenic in the sediments of the ten river basins examined in the study. Boxes mark the 5th and 95th percentiles; red line within the box indicates the average value of each river basin. The abbreviations represent the following: Songhua River Basin (SRB), Liao River Basin (LRB), Hai River Basin (HRB), Yellow River Basin (YRB), Huai River Basin (HuRB), Yangtze River Basin (YtRB), Pearl River Basin (PRB), Southeastern River Basin (SeRB), Southwestern River Basin (SwRB), and Northwestern River Basin (NwRB). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

L. Han et al. / Science of the Total Environment 651 (2019) 1983–1991

Fig. 2. Pie chart illustrating arsenic concentration in the sediments of the ten river basins in comparison with threshold effect concentration (TEC) and probable effect concentration (PEC).

and improper discharge of domestic and industrial wastewater) in the SRB, YtRB, and PRB. In general, the mean value of As in the studied river basins was higher than the corresponding RGB value. More specifically, 47.46% of SRB, 41.89% of LRB, 50.70% of HRB, 52.63% of YRB, 49.74% of YtRB, 68.57% of PRB, and 47.43% of HuRB sampling sites exhibited As contents higher than the corresponding RGB values. 3.1.3. Contamination assessment The contamination level in each river basin was comprehensively assessed by comparing As levels in the river basins with the threshold effect concentration (TEC; adverse effects are not expected to occur below this level) and probable effect concentration (PEC; adverse

1987

effects are expected to occur above this level) (MacDonald et al., 2000). The basins were accordingly divided into three groups (see pie chart in Fig. 2). The first group, wherein over half of the sampling sites recorded As concentrations lower than the TEC, was composed of the SRB, LRB, HRB, YRB, HuRB, and SeRB. The second group, wherein over half of the sampling sites recorded As concentrations between the TEC and PEC, included the YtRB, PRB, and NwRB. The third group included the SwRB, wherein over half of the sampling sites recorded As concentrations higher than the PEC. Thus, As content in the YtRB, PRB, NwRB, and SwRB basins could potentially adversely affect their corresponding aquatic ecosystems (MacDonald et al., 2000). In addition, the CF and Igeo index were calculated (Table 4 and Fig. 1). When using the RSB as the reference value to obtain CF results, low As contaminations were recorded for the HRB and HuRB, moderate contaminations were recorded for the SRB, YRB, YtRB, LRB, SeRB, and NwRB, and the PRB and SwRB were considerably contaminated by As. In contrast, when taking the RGB as the reference value, the SRB, LRB, HRB, YRB, YtRB, PRB, and HuRB were all moderately contaminated. Despite this difference, the CF results calculated from both the RSB and RGB suggested that the highest contamination level was found in the PRB. Based on the Igeo results estimated from both the RSB and RGB, the ten basins were divided into two groups. The first group consisted of basins that were uncontaminated and included the SRB, LRB, HRB, YRB, YtRB, HuRB, SeRB, and NwRB. The second group was uncontaminated to moderately contaminated and included the PRB and SwRB. Further, Igeo values of all of the river basins were exhibited in the form of a heat map (Fig. 3) to illustrate different degrees of As contamination. When large number of samples were collected from some basins, such as the YRB and HuRB, fifty random samples were included in the generation of the heat map. Evidently, the PRB and SwRB were different from the other basins, as

Fig. 3. Hot-map of Igeo of arsenic in the sediments of the ten river basins. The abbreviations represent the following: Songhua River Basin (SRB), Liao River Basin (LRB), Hai River Basin (HRB), Yellow River Basin (YRB), Huai River Basin (HuRB), Yangtze River Basin (YtRB), Pearl River Basin (PRB), Southeastern River Basin (SeRB), Southwestern River Basin (SwRB), and Northwestern River Basin (NwRB). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

1988

L. Han et al. / Science of the Total Environment 651 (2019) 1983–1991

most of the sampling sites registered Igeo values close to the maximum (2.5). Based on the above analysis, we inferred that the PRB and SwRB suffered from higher levels of As contamination. Further, the contribution rate from human activities was estimated using the equation shown below: Rð%Þ ¼

ðC‐C baseline Þ  100 C baseline

ð1Þ

where R is the contribution rate, C is the measured metal concentration in the sediment of each river basin, and Cbaseline is the RGB value. As summarized in Table 4, the mean human contributions of As were: 1.96% in the SRB, 45.43% in the LRB, 14.75% in the HRB, 12.56% in the YRB, 28.01% in the YtRB, 64.44% in the PRB and 11.18% in the HuRB. Clearly, human influence was relatively intensive in the PRB, which is in accordance with CF and Igeo results. However, the human contribution was negligible in the SRB. Since the PRB registered higher contamination levels and a large amount of samples were collected from the PRB, we assessed the distribution of As in the surrounding provinces to identify the province that made the largest contribution to As contamination of the PRB. Four

provinces (Hainan, Yunnan, Guangdong, and Guangxi) were included in the sampling sites of the PRB. Among these four provinces, Yunnan registered significantly higher As concentrations (P b 0.01) (Fig. 4c), which corresponded with the fact that As contents discharged in the wastewater were higher in Yunnan (see China Environmental Statistics at http://www.stats.gov.cn/tjsj/ndsj/). Fig. 4d illustrates the As contents in the wastewater of the four provinces in 2014. The content of As in the wastewater of Yunnan was two times higher than that in Guangxi, ten times higher than that in Guangdong, and two orders of magnitude higher than that in Hainan. Therefore, we suggest that As discharge in Yunnan province should be effectively regulated as a high priority to control As contamination in the PRB. In particular, the local government should strictly regulate As concentrations in the wastewater discharged into the river basin. 3.2. Temporal changes in As concentrations in China As illustrated in Fig. 5a–c, except for the extremely high As concentration in the PRB in 2013 and 2014, As concentrations exhibited a descending trend with time in the PRB, YtRB, and YRB. Further, this decreasing tendency was statistically significant (P b 0.05) in the YtRB.

Fig. 4. Correlation between arsenic and total organic carbon (TOC) concentration in the sediments of Hai River Basin (HRB), Yangtze River Basin (YtRB), Huai River Basin (HuRB) and Southeastern River Basin (SeRB) (a and b); arsenic concentrations in the sediments of Hainan, Yunnan, Guangdong and Guangxi province (c); arsenic content discharged in wastewater in Hainan (13 kg), Yunnan (7354 kg), Guangdong (856 kg) and Guangxi (4012 kg) province (d); correlation between arsenic and lead concentration in the sediment of the Pearl River Basin (PRB) and Yangtze River Basin (YtRB) (e and f); correlation between arsenic and mercury concentration in the sediment of the PRB (g).

L. Han et al. / Science of the Total Environment 651 (2019) 1983–1991

In addition, data from the Guangzhou section of the PRB and Three Gorges Reservoir section of the YtRB over different years (Tables 1 and 2) were compared (Figs. 5d–e). Consistently, a generally decreasing trend in As concentrations with time was observed. These yearly comparisons suggested that As contamination in the PRB, YtRB, and YRB has improved over the years. 3.3. Response of As contamination to industrial wastewater discharge The national survey and temporal changes found in As of river basin sediments indicated that the PRB suffers from higher levels of As contamination, and that As contamination in the PRB, YtRB, and YRB has tended to improve over the years. Our previous studies have identified industrial wastewater as one of the main anthropogenic sources of Hg and Pb in the PRB, YtRB, and YRB (Gao et al., 2016; Han et al., 2018).

1989

Further, As concentration was correlated with Pb and Hg concentrations in the three river basins (i.e., the PRB, YtRB, and YRB). We found a significantly positive relationship between As and Pb concentrations in the sediments of the PRB and YtRB (P b 0.001) and a positive relationship between As and Hg concentrations in the sediments of the PRB (P b 0.001) (Fig. 4e–g). These results imply a common origin for As, Hg, and Pb, suggesting that industrial wastewater discharge was possibly one of the major contributors of As contamination in the PRB, YtRB, and YRB. Following this assumption, the improvement in As contamination in the three river basins (the PRB, YtRB, and YRB) over time was likely related to informed policy-making and stricter regulations with respect to contamination prevention and abatement of wastewater discharge. As seen in Fig. 5f–h, the As contents discharged in the wastewater in provinces around the three basins generally decreased with time due to improvements in wastewater treatment. For example, As

Fig. 5. Temporal change in arsenic concentration in the sediment of the Pearl River Basin (PRB), Yellow River Basin (PRB), Yangtze River Basin (YtRB), Guangdong section of the PRB, and Three Gorges Reservoir section of the YtRB from 2004 to 2016 (left); red line highlights the arsenic concentration in 1990 year; historical changes in arsenic concentration discharged in wastewater in the provinces around PRB, PRB and YtRB (right). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

1990

L. Han et al. / Science of the Total Environment 651 (2019) 1983–1991

contents of the wastewater in the PRB sharply declined from 140.59 tons in 2005 to 56.65 tons in 2014. This decrease in As in the wastewater corresponded with the As decrease tendency found in the sediments, further supporting that industrial wastewater discharge was likely one of the main driving forces of As contamination in the PRB, YtRB, and YRB. This conclusion was consistent with the study of Wang et al. (2010) and Yang et al. (2009b) who also reported the contribution of industrial wastewater to As in the PRB and YtRB, respectively. The national survey further suggested a high As contamination level in the SwRB. The economy in the southwestern regions of China has rapidly developed in recent years. According to the information provided by the National Bureau of Statistics of China (http://www.stats. gov.cn/tjsj/ndsj/2017/indexch.htm), the growth rates of the gross domestic product in most provinces (e.g., Yunnan, Guizhou, Sichuan, and Chongqing) in the southwestern regions were higher than the national average over the past three years. However, corresponding environmental protections have not been given enough attention. As mentioned above, the As content in industrial wastewater in Yunnan is very high (around 7.5 tons in 2014). Thus, current As contamination in the SwRB might become more serious than that revealed in this study and requires urgent attention. 4. Conclusions and suggestions This study assessed As contamination in sediments on a national scale in China. Ten river basins in 30 provinces were included in this survey. The RGB values of As were determined for each of the river basins; these were: 8.76 mg/kg in the SRB, 8.11 mg/kg in the LRB, 9.01 mg/kg in the HRB, 8.77 mg/kg in the YRB, 11.64 mg/kg in the YtRB, 8.35 mg/kg in the PRB, and 8.03 mg/kg in the HuRB. The mean human contributions of As were: 1.96% in the SRB, 45.43% in the LRB, 14.75% in the HRB, 12.56% in the YRB, 28.01% in the YtRB, 64.44% in the PRB, and 11.18% in the HuRB. Among the ten river basins, the PRB and SwRB were exposed to the highest As contamination levels. Compared with Hainan, Guangdong, and Guangxi, Yunnan contributed more to the contamination of the PRB, possibly as a result of higher As contents in its industrial wastewater. Comparison of As concentration data in the PRB, YtRB, and YRB in our study with data from other periods (2004–2016) revealed that As contamination in the three river basins has potentially improved, corresponding well with decreases in As discharged in the wastewater in the surrounding sites. The results suggest that the government should particularly focus on As contamination in the PRB. High priority should be assigned to strictly control As discharge in Yunnan to effectively regulate As contamination in the PRB. In addition, although As levels have tended to improve in the PRB, YtRB, and YRB, As levels in the wastewater and the total volume of wastewater discharge should also be stringently controlled in these regions. This can be partly achieved by advocating for local industries to introduce advanced and effective techniques for As removal or providing financial and technical support to assist the development of pollutant control technologies. Besides river basins in relatively developed regions, As contamination in the river basins of less developed regions (e.g., the SwRB identified in this study) should also be addressed. Institutions such as the National Nature Science Foundation of China (NSFC) should fund projects to investigate heavy metal contamination in these regions. Finally, as current research on As in sediments in China is limited to case studies at the basin scale, we recommend that the Ministry of Environmental Protection (MEP) develops a standard system to conduct national sediment surveys every three to five years. This will contribute to a comprehensive understanding of the evolution of As contamination over time, thereby assisting policy makers in updating relevant regulations over time. Acknowledgments This work was jointly supported by the Special Program of Comprehensive Planning for Water Resources of China (HJ030074) and the

Special Fund Projects of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research (Grant no. 2014QN02, 2014RC08). Appendix A. Supplementary data Supplementary data associated with this article can be found in the online version, at http://www.sciencedirect.com. References An, Q., Wu, Y., Wang, J., Li, Z., 2009. Heavy metals and polychlorinated biphenyls in sediments of the Yangtze river estuary, China. Environ. Earth Sci. 59, 363. An, L., Zhang, Y., Zheng, B., Liu, d., Song, S., Li, Z., Chen, H., Zhao, X., Lin, J., 2012. Distribution characteristics of heavy metal in Daning River and Modao stream of the Three Gorges Reservoir Area. Acta Sedimentol. Sin. 2592–2598, 33 (In Chinese). Antoniadis, V., Levizou, E., Shaheen, S.M., Ok, Y.S., Sebastian, A., Baum, C., Prasad, M.N., Wenzel, W.W., Rinklebe, J., 2017. Trace elements in the soil-plant interface: Phytoavailability, translocation, and phytoremediation-a review. Earth-Sci. Rev. 171, 621–645. Ao, Y., Lei, Y., Wang, Y., Zhou, Y., Zhang, Y., 2014. Heavy metal risk assessment and sources distinguishing in town polluted river sediment at the Three Gorges Reservoir. J. Beijing Univ. Technol. 2, 100–134 (In Chinese). Berg, M., Stengel, C., Trang, P.T.K., Viet, P.H., Sampson, M.L., Leng, M., Samreth, S., Fredericks, D., 2007. Magnitude of arsenic pollution in the Mekong and Red River Deltas-Cambodia and Vietnam. Sci. Total Environ. 372, 413–425. Cai, J., Cao, Y., Tan, H., Wang, Y., Luo, J., 2011. Fractionation and ecological risk of metals in urban river sediments in Zhongshan City, Pearl River Delta. J. Environ. Monit. 13, 2450–2456. Chen, B., Liang, X., Xu, W., Huang, X., Li, X., 2012. The changes in trace metal contamination over the last decade in surface sediments of the Pearl River Estuary, South China. Sci. Total Environ. 439, 141–149. CNEMC (China National Environmental Monitoring Center), 1990. Chinese Soil Element Background Content. Chinese Environment Science Press, Beijing (In Chinese). Cui, B., Zhang, Q., Zhang, K., Liu, X., Zhang, H., 2011. Analyzing trophic transfer of heavy metals for food webs in the newly-formed wetlands of the Yellow River Delta, China. Environ. Pollut. 159, 1297–1306. Du, S., 2013. Pollution assessment of heavy mtals in the sediment of Pearl River Estuary. Pearl River. 34, pp. 42–44 (In Chinese). Duan, D., Ran, Y., Cheng, H., Chen, J.a., Wan, G., 2014. Contamination trends of trace metals and coupling with algal productivity in sediment cores in Pearl River Delta, South China. Chemosphere 103, 35–43. Fang, T., Li, D., Tang, J., Feng, Z., 2012. Environmental assessment of heavy metal in the sediment of Yangtze River Estuary and its adjacent area. Yangtze River. 43, pp. 68–71 (In Chinese). Fang, M., Wu, Y., Liu, H., Jia, Y., Zhang, Y., Wang, X., Wu, M., Zhang, C., 2013. Distribution, source and potential ecological risk of heavy metal in the sediment of Yangtze River. Acta Sedimentol. Sin. 33, 563–569 (In Chinese). Feng, L., Li, C., Hu, B., Zhang, X., Huang, J., Zhang, J., 2016. Pollution characteristics of sediments in the tributary of Three Gorges Reservoir after impoundment. Res. Environ. Sci. 29, 353–359 (In Chinese). Fu, J., Hu, X., Tao, X., Yu, H., Zhang, X., 2013. Risk and toxicity assessments of heavy metals in sediments and fishes from the Yangtze River and Taihu Lake, China. Chemosphere 93, 1887–1895. Gao, B., Zhou, H., Huang, Y., Wang, Y., Gao, J., Liu, X., 2014. Characteristics of heavy metals and Pb isotopic composition in sediments collected from the tributaries in Three Gorges Reservoir, China. Sci. World J. 2014, 149–168. Gao, B., Zhou, H., Yu, Y., Wang, Y., 2015. Occurrence, distribution, and risk assessment of the metals in sediments and fish from the largest reservoir in China. RSC Adv. 5, 60322–60329. Gao, B., Han, L., Hao, H., Zhou, H., 2016. Pollution characteristics of mercury (Hg) in surface sediments of major basins, China. Ecol. Indic. 67, 577–585. Garelick, H., Jones, H., Dybowska, A., Valsami-Jones, E., 2009. Arsenic Pollution Sources, Reviews of Environmental Contamination. 197. Springer, pp. 17–60. Guo, T., DeLaune, R., Patrick Jr., W., 1997. The influence of sediment redox chemistry on chemically active forms of arsenic, cadmium, chromium, and zinc in estuarine sediment. Environ. Int. 23, 305–316. Hakanson, L., 1980. An ecological risk index for aquatic pollution control. A sedimentological approach. Water Res. 14, 975–1001. Hall, A.H., 2002. Chronic arsenic poisoning. Toxicol. Lett. 128, 69–72. Han, L., Sun, H., Ro, K.S., Sun, K., Libra, J.A., Xing, B., 2017. Removal of antimony (III) and cadmium (II) from aqueous solution using animal manure-derived hydrochars and pyrochars. Bioresour. Technol. 234, 77–85. Han, L., Gao, B., Hao, H., Zhou, H., Lu, J., Sun, K., 2018. Lead contamination in sediments in the past 20 years: a challenge for China. Sci. Total Environ. 640, 746–756. He, J., Charlet, L., 2013. A review of arsenic presence in China drinking water. J. Hydrol. 492, 79–88. He, G., Yuan, G., 2014. Environmental quality of sediment heavy metals in Jitimen Estuarine Bay of Pearl River. Trans. Oceanol. Limnol. 2, 132–140 (In Chinese). Hoang, T., Bang, S., Kim, K., Nguyen, M., Dang, D., 2010. Arsenic in groundwater and sediment in the Mekong River delta, Vietnam. Environ. Pollut. 158, 2648–2658. Hu, N., Shi, X., Liu, J., Huang, P., Yang, G., Liu, Y., 2011. Distribution characteristics and environmental impact of heavy metal in the surface sediment of Laizhou Bay. Adv. Mar. Sci. 29, 63–72.

L. Han et al. / Science of the Total Environment 651 (2019) 1983–1991 Hu, G., Bi, S., Xu, G., Zhang, Y., Mei, X., Li, A., 2015. Distribution and assessment of heavy metals off the Changjiang River mouth and adjacent area during the past century and the relationship of the heavy metals with anthropogenic activity. Mar. Pollut. Bull. 96, 434–440. Kapaj, S., Peterson, H., Liber, K., Bhattacharya, P., 2006. Human health effects from chronic arsenic poisoning-a review. J. Environ. Sci. Health 41, 2399–2428. Karim, Z., Qureshi, B.A., Mumtaz, M., 2015. Geochemical baseline determination and pollution assessment of heavy metals in urban soils of Karachi, Pakistan. Ecol. Indic. 48, 358–364. Li, X., Wang, Y., Li, B., Feng, C., Chen, Y., Shen, Z., 2013. Distribution and speciation of heavy metals in surface sediments from the Yangtze estuary and coastal areas. Environ. Earth Sci. 69, 1537–1547 (In Chinese). Li, T., Wang, J., Wang, Y., Li, L., Yin, S., 2014. Content, chemical form and distribution characteristics of heavy metal on the shore of Yangtze River estuary. J. Agro-Environ. Sci. 33, 1189–1196 (In Chinese). Li, M., Yang, W., Sun, T., Jin, Y., 2016. Potential ecological risk of heavy metal contamination in sediments and macrobenthos in coastal wetlands induced by freshwater releases: a case study in the Yellow River Delta, China. Mar. Pollut. Bull. 103, 227–239. Lin, H., Sun, T., Xue, S., Jiang, X., 2016. Heavy metal spatial variation, bioaccumulation, and risk assessment of Zostera japonica habitat in the Yellow River Estuary, China. Sci. Total Environ. 541, 435–443. Liu, H., Li, W., 2011. Dissolved trace elements and heavy metals from the shallow lakes in the middle and lower reaches of the Yangtze River region, China. Environ. Earth Sci. 62, 1503–1511 (In Chinese). Liu, B., Zhang, H., Xie, L., Wang, Y., Wang, X., Zhao, L., 2015. Pollution characteristics and potential ecological risk of heavy metals in the surface sediments of the mainstream of Pearl River. J. Northeast Normal Univ. 2, 141–147 (In Chinese). Liu, R., Men, C., Liu, Y., Yu, W., Xu, F., Shen, Z., 2016. Spatial distribution and pollution evaluation of heavy metals in Yangtze estuary sediment. Mar. Pollut. Bull. 110, 564–571. Luo, W., Jin, M., He, Q., Tong, C., Zhang, Y., 2008. Distribution of heavy metals in the sediment cores of flood plain deposit in the Henan section of the Yellow River. Yellow River. 30, pp. 53–60 (In Chinese). Luo, X., Tian, J., Yang, J., Zhang, J., 2011. Distribution characteristics of heavy metals and nuitrients in the surface sediments of intertidal zone in the Yellow River Estuary. Ecol. Environ. 20, 892–897 (In Chinese). MacDonald, D., Ingersoll, C., Berger, T., 2000. Development and evaluation of consensusbased sediment quality guidelines for freshwater ecosystems. Arch. Environ. Contam. Toxicol. 39, 20–31. Masscheleyn, P., Delaune, R., Patrick, W., 1991. Arsenic and selenium chemistry as affected by sediment redox potential and pH. J. Environ. Qual. 20, 522–527. Müller, G., 1969. Index of geoaccumulation in sediments of the Rhine River. GeoJournal 2, 108–118. Müller, B., Berg, M., Yao, Z.P., Zhang, X.F., Wang, D., Pfluger, A., 2008. How polluted is the Yangtze river? Water quality downstream from the Three Gorges Dam. Sci. Total Environ. 402, 232–247. Nie, M., Xian, N., Fu, X., Chen, X., Li, B., 2010. The interactive effects of petroleumhydrocarbon spillage and plant rhizosphere on concentrations and distribution of heavy metals in sediments in the Yellow River Delta, China. J. Hazard. Mater. 174, 156–161. Niu, H., Wu, Q., Chen, X., 2006. Distribution characteristics and correlations of heavy metals in the surface sediments in Guangzhou section of the Pearl River. Ecol. Environ. 15, 954–959 (In Chinese). Qin, Y., Cao, W., Ma, Y., Zhang, L., Liu, Z., Chang, X., 2015. Pollution characteristic and standardized analysis of heavy metal in water, suspended particle and surface sediment in the water diversion from Yangtze river to Taihu lake. Environ. Pollut. Cont. 37, 5–9 (In Chinese). Ramos-Miras, J., Roca-Perez, L., Guzmán-Palomino, M., Boluda, R., Gil, C., 2011. Background levels and baseline values of available heavy metals in Mediterranean greenhouse soils (Spain). J. Geochem. Explor. 110, 186–192. Rodríguez-Lado, L., Sun, G., Berg, M., Zhang, Q., Xue, H., Zheng, Q., Johnson, C.A., 2013. Groundwater arsenic contamination throughout China. Science 341, 866–868. Ruilian, Y., Xing, Y., Yuanhui, Z., Gongren, H., Xianglin, T., 2008. Heavy metal pollution in intertidal sediments from Quanzhou Bay, China. Acta Sedimentol. Sin. 20, 664–669. Sheng, J., Fan, D., Yang, D., Qi, H., Xu, L., 2008. Distribution patterns of heavy metals in surface sediments of the Yangtze Estuary and its adjacent areas and environmental quality assessment. Acta Sedimentol. Sin. 29, 2405–2412 (In Chinese). Shi, Z., Wang, X., Ni, S., 2015. Metal contamination in sediment of one of the upper reaches of the Yangtze River: Mianyuan River in Longmenshan Region, Southwest of China. Soil Sediment Contam. 24, 368–385 (In Chinese). Song, Y., Ji, J., Mao, C., Yang, Z., Yuan, X., Ayoko, G.A., Frost, R.L., 2010. Heavy metal contamination in suspended solids of Changjiang River-environmental implications. Geoderma 159, 286–295. Song, Y., Ji, J., Yang, Z., Yuan, X., Mao, C., Frost, R.L., Ayoko, G.A., 2011. Geochemical behavior assessment and apportionment of heavy metal contaminants in the bottom sediments of lower reach of Changjiang River. Catena 85, 73–81. Sun, Y., Mu, Q., She, Y., Wang, J., Wang, Y., 2011. Distribution patterns of heavy metals in surface sediments of the Yangze River estuary and its adjacent areas and environmental quality assessment. J. Zhejiang Ocean Univ. 30, 107–112 (In Chinese). Sun, C., Liu, J., Wang, Y., Sun, L., Yu, H., 2013. Multivariate and geostatistical analyses of the spatial distribution and sources of heavy metals in agricultural soil in Dehui, Northeast China. Chemosphere 92, 517–523. Sun, Q., Ding, S., Wang, Y., Xu, L., Wang, D., Chen, J., Zhang, C., 2016. In-situ characterization and assessment of arsenic mobility in lake sediments. Environ. Pollut. 214, 314–323. Tian, K., Huang, B., Xing, Z., Hu, W., 2017. Geochemical baseline establishment and ecological risk evaluation of heavy metals in greenhouse soils from Dongtai, China. Ecol. Indic. 72, 510–520.

1991

Wang, S., Mulligan, C.N., 2006. Occurrence of arsenic contamination in Canada: sources, behavior and distribution. Sci. Total Environ. 366, 701–721. Wang, S., Cao, X., Lin, C., Chen, X., 2010. Arsenic content and fractionation in the surface sediments of the Guangzhou section of the Pearl River in Southern China. J. Hazard. Mater. 183, 264–270. Wang, Y., Yang, Z., Shen, Z., Tang, Z., Niu, J., Gao, F., 2011. Assessment of heavy metals in sediments from a typical catchment of the Yangtze River, China. Environ. Monit. Assess. 172, 407–417. Wang, J., Gao, B., Zhou, H., Lu, J., Wang, C., Yin, S., Hao, H., Yuan, H., 2012. Heavy metal pollution and its potential ecological risk of the sediments in three gorges reservoir during its impounding period. Acta Sedimentol. Sin. 33, 1693–1699. Wang, J., Huang, C., Ni, Z., Jin, G., Cao, L., Chen, H., 2014a. Analysis on distribution, speciation and source of heavy metals in superficial sediments in the Pearl River Estuary. Mar. Sci. Bull. 33, 259–267. Wang, J., Liu, R., Zhang, P., Yu, W., Shen, Z., Feng, C., 2014b. Spatial variation, environmental assessment and source identification of heavy metals in sediments of the Yangtze River Estuary. Mar. Pollut. Bull. 87, 364–373. Wang, H., Wang, J., Liu, R., Yu, W., Shen, Z., 2015a. Spatial variation, environmental risk and biological hazard assessment of heavy metals in surface sediments of the Yangtze River estuary. Mar. Pollut. Bull. 93, 250–258. Wang, Z., Feng, J., Nie, X., 2015b. Recent environmental changes reflected by metals and biogenic elements in sediments from the Guishan Island, the Pearl River Estuary, China. Estuar. Coast. Shelf Sci. 164, 493–505 (In Chinese). Wang, Y., Ling, M., Liu, R., Yu, P., Tang, A., Luo, X., Ma, Q., 2017. Distribution and source identification of trace metals in the sediment of Yellow River Estuary and the adjacent Laizhou Bay. Phys. Chem. Earth A/B/C 97, 62–70. Wei, C., Wen, H., 2012. Geochemical baselines of heavy metals in the sediments of two large freshwater lakes in China: implications for contamination character and history. Environ. Geochem. Health 34, 737–748. Wei, X., Han, L., Gao, B., Zhou, H., Lu, J., Wan, X., 2016. Distribution, bioavailability, and potential risk assessment of the metals in tributary sediments of Three Gorges Reservoir: the impact of water impoundment. Ecol. Indic. 61, 667–675. Woods, A., Lloyd, J., Zong, Y., Brodie, C., 2012. Spatial mapping of Pearl River Estuary surface sediment geochemistry: influence of data analysis on environmental interpretation. Estuar. Coast. Shelf Sci. 115, 218–233 (In Chinese). Wu, X., Liu, R., Qin, J., Sun, P., Gao, Z., Jia, Y., 2007. Investigation on change in concentration of heavy metal in the sediment of Yellow River Estuary. Trans. Oceanol. Limnol. 69–74. Xiao, S., Liu, D., Wang, C., Gao, B., Wang, L., Duan, Y., 2011. Distribution characteristics of heavy metals in the sediment of Xiangxi River of the Three Gorges Reservoir Area. Resour. Environ. Yangtze Basin 20, 983–989 (In Chinese). Yan, N., Liu, W., Xie, H., Gao, L., Han, Y., Wang, M., Li, H., 2016. Distribution and assessment of heavy metals in the surface sediment of Yellow River, China. Acta Sedimentol. Sin. 39, 45–51. Yang, W., Lai, Z., Wei, T., Pang, S., 2009a. Pollution and ecological hazard evaluation of sediment heavy metals in Pearl River Estuary. J. Zhejiang Ocean Univ. 28, 188–232 (In Chinese). Yang, Z., Wang, Y., Shen, Z., Niu, J., Tang, Z., 2009b. Distribution and speciation of heavy metals in sediments from the mainstream, tributaries, and lakes of the Yangtze River catchment of Wuhan, China. J. Hazard. Mater. 166, 1186–1194. Ye, F., Huang, X., Zhang, D., Tian, L., Zeng, Y., 2012. Distribution of heavy metals in sediments of the Pearl River Estuary, Southern China: implications for sources and historical changes. Acta Sedimentol. Sin. 24, 579–588. Yi, Y., Wang, Z., Kang, Z., Yu, G., Duan, X., 2008. Sediment pollution and its effect on fish through food chain in the Yangtze River. Int. J. Sediment Res. 23, 338–347 (In Chinese). Yi, Y., Yang, Z., Zhang, S., 2011. Ecological risk assessment of heavy metals in sediment and human health risk assessment of heavy metals in fishes in the middle and lower reaches of the Yangtze River basin. Environ. Pollut. 159, 2575–2585. Yu, G., Sun, D., Zheng, Y., 2007. Health effects of exposure to natural arsenic in groundwater and coal in China: an overview of occurrence. Environ. Health Perspect. 115, 636. Yuan, H., Wang, C., Gu, S., Lu, J., Zhou, H., Wan, X., 2008. Chemical forms and pollution characteristics of heavy metals in Yellow River sediments. Chin. J. Ecol. 27, 1966–1971. Zhai, W., Ouyang, X., Zhou, W., Yu, D., Zheng, H., 2017. Spatial distribution and risk assessment of heavy metals in the near shore sediments in main stream of Yangtze River. Acta Sedimentol. Sin. 37, 4195–4201 (In Chinese). Zhang, X., 2010. Variation Characteristics of Heavy Metals in the Water of Lower Reaches and Estuarine Wetland of Yellow River. Ocean University of China (In Chinese). Zhang, X., 2013. Distribution Characteristic of Heavy Metal and its Influencing Factors in the Estuary of Yangtze River and Yellow River. Ocean University of China (In Chinese). Zhang, Y., He, Q., Chen, J., Lin, C., Ji, W., 2013. Heavy metal's process in water and pollution risk assessment in surface sediments of the Zhujiang River Estuary. Acta Oceanol. Sin. 35, 178–186. Zhang, J., Liu, J., Zhang, H., He, L., 2014. Lead isotope tracing of heavy metal in the wetland of the Yellow River Estuary. Adv. Mar. Sci. 32, 491–500. Zhao, S., Liu, L., Wang, X., Li, S., Zhu, S., Zheng, P., Zhang, Q., Zhang, B., Meng, G., 2008. Characteristics and ecological risk of heavy metals in overlying water, suspended particles and bed mud in the Inner Mongolia stretch of the Yellow River. Geoscience 22, 304–312. Zhao, S., Feng, C., Yang, Y., Niu, J., Shen, Z., 2012. Risk assessment of sedimentary metals in the Yangtze Estuary: new evidence of the relationships between two typical index methods. J. Hazard. Mater. 241, 164–172. Zhao, M., Wang, C., Sun, Z., Sun, W., Lv, Y., Zhao, H., Lu, Y., 2016. Concentration, distribution, and ecological risk assessment of heavy metals in sediments from the tail reaches of the Yellow River Estuary. Mar. Sci. 40, 68–75.