Pollution, sources and environmental risk assessment of heavy metals in the surface AMD water, sediments and surface soils around unexploited Rona Cu deposit, Tibet, China

Journal Pre-proof Pollution, sources and environmental risk assessment of heavy metals in the surface AMD water, sediments and surface soils around unexploited Rona Cu deposit, Tibet, China Donghai Qiao, Gaoshang Wang, Xiaosai Li, Song Wang, Yuanyi Zhao PII:

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DOI:

https://doi.org/10.1016/j.chemosphere.2020.125988

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CHEM 125988

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Received Date: 11 July 2019 Revised Date:

6 January 2020

Accepted Date: 20 January 2020

Please cite this article as: Qiao, D., Wang, G., Li, X., Wang, S., Zhao, Y., Pollution, sources and environmental risk assessment of heavy metals in the surface AMD water, sediments and surface soils around unexploited Rona Cu deposit, Tibet, China, Chemosphere (2020), doi: https://doi.org/10.1016/ j.chemosphere.2020.125988. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.

Donghai Qiao: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data Curation, Writing Original Draft, Writing, Review and Editing, Visualization. Gaoshang Wang: Supervision, Funding acquisition. Xiaosai Li: Validation, Investigation. Song Wang: Validation, Investigation. Yuanyi Zhao: Conceptualization, Methodology, Investigation, Writing, Review and Editing, Supervision, Project administration, Funding acquisition.

1

Pollution, sources and environmental risk assessment of heavy metals in the

2

surface AMD water, sediments and surface soils around unexploited Rona Cu

3

deposit, Tibet, China

4

Donghai Qiaoa,b, Gaoshang Wangb, Xiaosai Lia, Song Wanga, Yuanyi Zhaoa,*

5

a

＞

China

7

b

8

*

9

E-mail addresses: [email protected]

MNR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, CAGS, Beijing, 100037,

Global Mineral Resources Strategic Research Center, Institute of Mineral Resources, CAGS, Beijing, 100037, China

Corresponding authors: Yuanyi Zhao

10

ABSTRACT: The pollution by heavy metals (HMs) of mining is a widespread problem in the world. However, the

11

pollution by HMs around unexploited deposits (virgin fields) has been studied rarely, especially in Tibet, China.

12

Water, sediments and surface soils were collected to investigate the concentrations of HMs around unexploited

13

Rona Cu deposit in Tibet, China. Furthermore, geochemical fractions of these elements were also analyzed.

14

Pollution and environmental risk introduced by HMs accumulation were assessed using pollution indices,

15

geo-accumulation (Igeo), potential ecological risk index and risk assessment code (RAC). Results indicated that the

1＞

pH values of Rona tributary river ranged from 2.70 to 3.08, and the average concentrations of Cu and Zn were

17

2114.00±65.89 and 1402.14±27.36 µg L-1, respectively, exceeding their standard limits. The concentrations (mg

18

kg-1) of Cu, Zn and As ranged in 19.01-1763.10, 62.00-543.06 and 11.12-61.78 for sediments, respectively, and

19

154.60-1489.35, 55.38-344.74 and 10.05-404.03 for surface soils, respectively, exceeding their standard limits.

20

According to RAC, almost all Cu, Zn and As near low risk status. However, Cd ranged from medium to very high

21

risk in sediments, and low to high risk in surface soils. Statistical analysis suggested that Cu, Pb, Zn, As and Cd in 1 / 29

22

sediments and surface soils may mainly derive from Rona deposit, whereas Cr and Hg may primarily originate

23

from lithogenic sources. The results indicated that very high concentrations of HMs could be occurred in surface

24

water, sediments and surface soils around unexploited deposits. Especially at high-altitude Tibet, the high

25

environmental risk of HMs deserves more attention.

2＞

Keywords: Heavy metals; Unexploited deposit; Environmental risk; Tibet; Geochemical fraction; Pollution

27

assessment

28

1. Introduction

29

Human activities, such as mining, smelting, traffic and machinery manufacturing, have been recognized as

30

major contributors to environmental pollution by HMs (Mostert et al., 2010). Mining activities, especially for

31

non-ferrous metal mines, can generate and lead to the leaching of large quantities of HMs into environment

32

inducing adverse influence on plants and human health (Ding et al., 2018). Previous researches have suggested that

33

in most cases, water, sediments and soils in the vicinity of mines are polluted severely. For example, Local water

34

supplies around Kilembe Cu mine in Western Uganda were contaminated with Co (Mwesigye et al., 2016). The

35

concentrations of Pb in sediments around a Pb/Zn mine in NE Morocco, are expected to cause harmful effects on

3＞

sediment-dwelling organisms (Azhari et al., 2017). Liu et al. (2013) reported that soils pollution by HMs was very

37

high, and the concentrations of Cu and Cd were up to 426.15 and 2.55 mg kg-1, respectively, around Dexing Cu

38

mine in China. When HMs in sediments or soils have been transformed from stable fractions into susceptible,

39

bioavailable and mobile existence, they could have caused threat to the health of animals and human beings

40

(Madrid et al., 2002). For instance, Cd exposure can increase the chance of osteoporosis and lung cancer (Khan et

41

al., 2015), while chronic exposure to As dust can lead to peripheral vascular disease (Rehman et al., 2019). The

42

excessive intake of Pb adversely affect the central nervous system (Kaufmann et al., 2003). Zn may result infertility

43

and kidney disease. Cu induces depression and Cr may cause tumor of respiratory organs (Sani et al., 2017). The 2 / 29

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toxicity of HMs is not obvious at the initial stage of accumulation, but it is difficult to eliminate when toxicity is

45

shown (Lü et al., 2018). Due to their potential toxic, persistent and irreversible characteristic, the HMs such as Cu,

4＞

Pb, Zn, As, Cd, Cr and Hg have been listed as priory control pollutants by the United States Environmental

47

Protection Agency (USEPA) and caused more and more attention in many part of the world (Lei et al., 2008). China

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is one of the largest global producers and consumers of metals (Gunson and Jian, 2001). Especially, since the 21st

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century, continuously expanding industrialization has drastically increased extensive metal mining and smelting

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activities, causing the significant enrichment of HMs in soils and other environment medias (Kang et al., 2017).

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Therefore, assessment of HMs pollution is very essential to be carried out for chinese mines.

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The HMs pollution around mines has been reported extensively, and most of the pollution sediments, soils or

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water column by HMs are attributed to the generation and release of acid mine drainage (AMD) from mines,

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containing high concentrations of HMs (Ramirez et al., 2005). Oxidation of sulphide ores, particularly those rich in

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pyrite, introduces high concentrations of HMs, sulphuric acid (hydrogen ions) and sulphate ions into waters and

5＞

therefore generates AMD (Nordstrom et al., 2000). Anthropogenic activities such as mining and smelting of metal

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ores have greatly increased the generation of AMD (Mostert et al., 2010). During mining and smelting progresses,

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mine tailings, wastewaters and dusts could release a substantial amount of HMs to surrounding environment

59

through surface runoff and aerial dust transport by wind (Rodríguez et al., 2009). Specifically, opencast mining and

＞0

smelting activities have a relatively more serious environmental impact on soils and water streams, especially the

＞1

pollution of environment by mine tailings (Yin et al., 2018), which was different from the causes of pollution in

＞2

unexploited deposits (no tailings). For example, the concentrations of HMs in AMD can reach 41740 µg L-1 for Cu,

＞3

and 265 µg L-1 for As in Jiama and Deerni Cu mines (being mined), respectively, in Tibetan plateau, China (Liu et

＞4

al., 2018), heavily polluted. Additionally, natural sources are also responsible for the production of HMs (Shah et

＞5

al., 2010). Previous research works have investigated the natural sources of HMs enrichment in ecosystems (Del Rı 3 / 29

＞＞

´o et al., 2002). The results showed that the accumulation of HMs in sediments or soils depends on the type of

＞7

weathered rocks and climatic environment in the area concerned (Kafayatullah et al., 2001; Khan et al., 2017).

＞8

However, all of the previous researches are about the environmental pollution for non-mining areas or the deposits

＞9

that have been mined or are being mined, and it is unclear for the generation of AMD for unexploited deposits, and

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the adverse influence on environment is rarely concerned.

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According to the field geological work experience, ore body is the section where the available elements are

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abundant, and the primary halos of the surface are a good sign of ore prospecting, as well as an abnormal part of

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geochemistry. However, ore bodies with enriched useful elements and geochemical anomalies would produce

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pollution to the surrounding environment, which are the main sources of pollution. Therefore, even if these deposits

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are not mined, they also cause harm to the surrounding environment (Wang et al., 2006). Under favorable

7＞

conditions, the sulphide ores in unexploited non-ferrous deposits, which are exposed, could be oxidized in natural

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condition as well to produce AMD (Nasrabadi et al., 2010). In consequence, it is significant to research the HMs

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pollution for unexploited deposits. Rona Cu deposit (unexploited) is polymetallic sulfide deposit, and the major ore

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minerals are pyrite (FeS2), chalcopyrite (CuFeS2), covellite (CuS), digenite (4Cu2S·CuS), bornite (Cu5FeS4),

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chalcocite (Cu2S) and enargite (Cu3AsS4) (Tang et al., 2016). Rona river flows south of the Rona deposit and the

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flow is 39 L/s. A tributary river (natural spring water) in the middle of Rona deposit (Fig. 1a) flows down slope and

82

into Rona river (Fig. 1b) and the flow is 0.8 L/s, accompanied by a large amount of ore leaching materials, resulting

83

in a noticeable impact on the surrounding environment. The seriousness of this environmental hazard can be seen

84

from the obvious changes in riparian vegetation (Fig. 1c). Before tributary water inflows, the vegetation on both

85

sides of Rona valley is lush, and after water inflows, there is almost no vegetation distribution on both sides of the

8＞

valley. Field observation showed that the water in some sections of Rona river was yellowish brown (Fig. 1d), with

87

abundant yellow foam on ice sheet (Fig. 1e), and the adjacent hillside were covered by large areas of oxidized ores 4 / 29

88

(Fig. 1f).

89

In this paper, the total concentrations of HMs and pH values of water, sediments and surface soils were

90

determined to assess the pollution and environmental risk by pollution indices, Igeo, ecological risk indices and

91

RAC. The objectives of this study were (i) to investigate the occurrence of Cu, Pb, Zn, As, Cd, Cr and Hg in water,

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sediments and surface soils and to determine the speciation of these elements using sequential extraction procedure;

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(ii) to assess the environmental risk of HMs pollution; and (iii) to define the sources of HMs preliminarily in the

94

study area. The research results have important reference significance for the environmental protection and

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governance of Rona deposit. Given the fragile setting in the study area and its less external disturbance conditions,

9＞

outcomes from this study can provide a unique perspective to understand the environmental pollution for

97

unexploited deposits in other countries or regions with similar or the same geographical environment.

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2. Materials and methods

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2.1. Study area and sampling

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Rona Cu deposit is located in the Tibet, China (N 32°47 00 -32°50 00″; E 83°23 00 -83°27 00″), about 100

101

km northwest of Gaize County, northeast of Samalong village (Fig. 2). At present, it is the first

102

Porphyry-Epithermal deposit in Tibetan plateau and is currently the largest porphyry Cu deposit with single ore

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body in China. The Cu resources of the deposit are about 11 million tons, with an average Cu grade of 0.51% (Tang

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et al., 2016). In September 2012, Aluminum Corporation of China entered the study area to conduct ore prospecting,

105

and discovered the Rona deposit in 2013. Rona deposit is currently in the scientific research and technical reserve

10＞

stage, not mining. Compared with most parts of the China, the environmental characteristics on the study area is

107

very special. The terrain of the study area is mainly mountain and valley, about 5000 meters above sea level, and

108

the average days with annual wind speed of 17 m/s are 200 d. The climate of the study area is Plateau subtropical

109

arid monsoon climate and the annual mean temperature ranges from -0.1 °C to -2.5 °C, with the highest and lowest 5 / 29

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temperature 26.0 °C and -44. 6 °C, respectively. Annual total precipitation in the study area is 308.3 mm, of which

111

more than 70.0% concentrated in July and August (Qiao, 2018).

112

A total of 22 surface water samples at depths of 0-5 cm were collected from Rona river (R1-R15) and its

113

tributary (Z1-Z7) (Fig. 2). For locating the sample sites, a portable global positioning system (GPS) was used. All

114

samples were filtered using pre-weighted glass fiber filters (0.45 µm) to remove suspended particles. Samples were

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acidified to a pH of<2 using nitric acid to analyze the concentration of elements. pH of surface water was measured

11＞

using Hanna multi-parameter instrument (Model HI9828, American) during sampling. All samples were kept at a

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temperature below 5 °C in sealed containers and transported back to laboratory. The Samalong river located in the

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adjacent valley of Rona river, is an ideal control river, and three surface water samples at depths of 0-5 cm were

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collected from the river (L1-L3) (Fig. 2). In addition, three well water samples (V1-V3) were collected from

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Samalong village.

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A total of 58 sediment samples at depths of 30-50cm were collected with the help of stainless steel hand spade

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(Fig. 2). From top to bottom, take a sediment sample every 10 cm deep, and 3-5 samples were collected at each

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point. For locating the sample sites, a portable global positioning system (GPS) was used. Sediment samples from

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Rona riverbed were taken from three sections of the riverbed: 20 samples from S-S’, 19 from Z-Z’ and 19 from

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X-X’, and each section was sampled from five points at a certain distance from each other (Fig. 2). The collected

12＞

samples were air-dried, ground, sieved through 2 mm sized sieve to remove debris, stones and other coarse

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structures and carefully stored in clean polyethylene bags, labelled and then transported to the laboratory. The

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sampling locations of local background sediment samples from the upstream of Rona river are detailed in our

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previous study (Luo, 2017). Because of the hard bedrock beneath Rona tributary river, sediment samples cannot be

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collected.

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A total of 22 surface soil samples at depths of 0-10cm were collected from A-B hillside profile (Fig. 2). For ＞ / 29

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locating the sample sites, a portable global positioning system (GPS) was used. Samples were collected from top of

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the mountain to a position near Rona river valley. The surface soil samples were air dried at room temperature,

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grounded and sieved through a 2 mm nylon mesh, and the coarse materials were removed. Then the samples were

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stored in zip-lock polyethylene bags for subsequent analysis. The sampling locations of local background surface

13＞

soil samples are detailed in our previous study (Luo, 2017).

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2.2. Chemical analysis

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2.2.1. Analysis of surface and well water samples

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In case of water samples, 100 mL from each water sample was taken in a beaker and 10 mL HNO3 (65.0%)

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was added. The contents of the beakers were evaporated at 90 °C till the volume of the water to be digested

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remained 40 mL, filtered in 100 mL volumetric flask and volume was made up to the mark with deionized water.

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The concentrations of Cu, Pb, Zn, Cd and Cr were analyzed by inductively coupled plasma mass spectrometry

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system (ICP-MS) (Elan DCR-e, American), and As and Hg were analyzed by Atomic fluorescence spectrometry

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(AFS) (ASF 2202, China).

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2.2.2. Analysis of sediment and surface soil samples

14＞

pH was measured (soil: water in the ratio 1:2, agitated for about an hour) using a pH meter (Mettler Toledo

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FE20, Switzerland) (Saleem et al., 2018). The sieved sediment and surface soil samples was ground with mortar

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and pestle until fine particles (<200 µm). For metal concentration, the sediment and surface soil samples were

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weighed (0.25 g) into clean, dry, numbered and acid-washed poly tetrafluoro ethylene (PTFE) beakers, respectively.

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HNO3 (3.0 mL) followed by HClO4 (3.0 mL) and then HF (10.0 mL) was added to each beaker and heated on hot

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plate at 180 °C for about 1-1.5 h (Cantle, 1986). HCl (10.0 mL) was added to each beaker and warmed gently. At

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last, the materials were transferred to 100 mL volumetric flask and made the volume up to the mark with double

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de-ionized water. After acid digestion, Graphite furnace atomic absorption spectroscopy (AA-1800E, China) was 7 / 29

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used to determine Cd concentration; flame atomic absorption spectrometry (AAS novAA 400, Germany) was used

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to determine the concentrations of Cr, Cu, Zn and Pb. Reduction gasification atomic fluorescence spectrometry

15＞

(PF6-3, China) was used to determine the concentrations of Hg and As.

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A modified Tessier sequential extraction procedure (Tessier et al., 1979) was performed to separate HMs to

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water-soluble (F1), exchangeable (F2), carbonate-associated (F3), humic acid-associated (F4), Fe-Mn

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oxide-associated (F5) and strong organic-associated (F6), which were extracted by water, magnesium chloride

1＞0

solution (1.0 M), sodium acetate solution (1.0 M), sodium pyrophosphate solution (0.1 M), hydroxylamine

1＞1

hydrochloride solution (0.25 M) and hydrogen peroxide (30.0%), respectively. To give a check on the recovery of

1＞2

the whole procedure in comparison to the total concentration, the residual fraction (F7) was measured.

1＞3

2.2.3. Quality control

1＞4

In the experiment process, standard operating procedures, standard reference materials, reagent blanks, spiked

1＞5

samples recovery and analysis of replicates were implemented to check the consistency of the results. Precision and

1＞＞

accuracy for HMs analysis are validated using standard reference materials from Center of National Standard

1＞7

Reference Material of China [water, GSB04-1767-2004; sediment, GBW07459 (GSS-22) and GBW07460

1＞8

(GSS-25); soil, GBW07458 (GSS-17)]. Blanks and standard reference materials digestion and measurement was

1＞9

conducted as described for the above method. Accepted recovery rates for all HMs range from 93.0% to 109.0%.

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Differences in HMs concentrations between the determined and certified values are less than 10.0% and the

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deviation of duplicate samples was less than 5.0%, indicated that the results obtained were within the detectable

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range of the certified values. To ensure an adequate extraction efficiency, the standard reference material (GBW

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07437) was carried out to test the accuracy of the sequential procedure. The recovery rates for all metals ranged

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from 80.4% to 104.9%, within the detectable range of the verification values.

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2.3. Geochemical and environmental risk assessment 8 / 29

17＞

In recent years, different metal pollution indices have been applied for geochemical and environmental risk

177

assessment (Praveena et al., 2007; Gong et al., 2008). In order to comprehensively evaluate pollution degree of

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water, sediments and surface soils, this paper employed different types of indices to determine the current pollution

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status of HMs in Rona Cu deposit area. In this study, five parameters including single pollution index (Pi), Nemrow

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integrated pollution index (Pn), Igeo, potential ecological risk of individual factor (Eir) and Potential ecological risk

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index (RI) were calculated. These indices allow the assessment of metal pollution by individual elements (Pi and

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Igeo), holistic evaluation of the water, sediments and surface soils pollution (Pn) as well as the assessment of the

183

ecological risk (Eir and RI). Rodríguez et al (2009) indicated that an adequate criterion for environmental risk

184

assessment must include both total metal concentration and bioavailable metal fraction. Thus, RAC was used to

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assess the environmental risk of HMs. The selected indices are explained below.

18＞

2.3.1. Pollution indices

187 188

Pi (Hakanson, 1980) and Pn (Chen et al., 2015) were used to assess the pollution of HMs in water, sediments and surface soils. The Pi is defined as:

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Pi=Ci/Si

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where Ci represents the concentration of metal i in samples, and Si is its reference concentration. In this paper,

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the water, sediments, and surface soils reference concentrations are Chinese quality criterion of class III for surface

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water (GB 3838-2002) and Soil quality Grade II standards of China (CEPA, 1995), respectively. The Pn can be

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calculated using:

(1)

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Pn=[0.5×(IAvg2+IMax2)]1/2

195

where IAvg is the mean value of all pollution indices of the HMs considered, IMax is the maximum value. The

(2)

19＞

evaluated criteria of Pi and Pn are shown in Liu et al. (2018) and Chen et al. (2015).

197

2.3.2. Geo-accumulation index 9 / 29

198 199

Igeo is a geochemical criterion to evaluate pollution levels and has been used since the late 1960s (Muller, 1969). It can be calculated using:

200

Igeo=log2 (Cn/1.5Bn)

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where Cn is the measured concentration of metal n in soils or sediments and Bn is the geochemical background

202

value of the corresponding metal. In this study, the background values were calculated from the local average

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background values (ABVs). The factor 1.5 is introduced to minimize the possible variations in the background

204

values due to lithogenic effects. The category of Igeo is shown in Chen et al. (2015).

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2.3.3. Potential ecological risk index

(3)

20＞

To estimate the comprehensive risks from the HMs, the potential ecological risk index (RI) developed by

207

Hakanson (1980) was applied in this study. RI reflects the collective effects of different pollutants in the sediments

208

or soils and quantitatively measure the ecological risk caused by different pollutants. The RI is calculated by the

209

following formulas:

210

Cf = Cn/Cb

(4)

211

Eir = Cf · Tr

(5)

212

RI = ∑ Eir

(6)

213

where Cf is the contamination factor of a HM, Cn is the concentration of metal n in the sediments or soils, and

214

Cb is the baseline value of that metal in the sediments or soils. In this study, the local ABVs were used as the

215

baseline values, since using the earth crust levels can be inappropriate due to geogenic differences (Matys Grygar

21＞

and Popelka, 2016). Eir is the potential risk of a HM, Tr is the toxic response factor for a HM. Finally, RI is the sum

217

of the Eir calculated for each HM. The Tr for Cu, Pb, Zn, As, Cd, Cr and Hg are 5, 5, 1, 10, 30, 2 and 40,

218

respectively. The evaluated criteria of RI is shown in Hakanson (1980).

219

2.3.4. Risk Assessment Code 10 / 29

220

The RAC was useful to assess the environmental risk using sequential extraction as a characterization method

221

(Liu et al., 2018). Several authors have determined the speciation of sediments or soils HMs to better inform the

222

environmental risk assessment (Perin et al., 1985; Jain, 2004). According to RAC, the metals in the sediments or

223

soils are bound with different strengths to the different geochemical fractions, which leads to differences in the

224

ability of metals to be released and enter into the environment. The RAC is assigned by taking into account the

225

percentage of HMs associated with sediments or soils in the F2+F3 fraction; thus, there is no risk (N) when the

22＞

F2+F3 is lower than 1.0%, there is low risk (L) for a range of 1.0-10.0%, medium risk (M) for a range of

227

11.0-30.0%, high risk (H) from 31.0 to 50.0% and very high risk (VH) for higher F2+F3 percentages (Perin et al.,

228

1985).

229

2.4. Statistical analysis

230

Statistical analyses were performed with the statistical software package SPSS version 22.0 software (IBM,

231

Chicago, IL). Principal component analysis (PCA) and cluster analysis (CA) was employed to analyze the

232

relationships and sources of HMs (Chabukdhara and Nema, 2012). The association coefficient between variables

233

and factors reflect the degree of proximity between them. In the PCA, the principal components were calculated

234

based on the correlation matrix, and VARIMAX normalized rotation was used.

235

3. Results and discussion

23＞

3.1. Descriptive statistical analysis of HM concentrations

237

3.1.1. Surface and well water

238

The concentrations of HMs and pH in surface and well water samples and permissible values of class III for

239

surface water are shown in Table 1. The pH values of Rona tributary water ranged from 2.70 to 3.08, and fall

240

outside the permissible values, acid water, whereas the values of all other samples ranged in 7.08-8.16. Surface

241

water acidification may have various causes, but the main source so far is ore mining, which has been confirmed by 11 / 29

242

a large number of literatures (Akabzaa et al., 2007). However, the Rona deposit has never been mined and the

243

causes of surface water acidification would be discussed in the following section. Hammarstrom et al. (2003)

244

showed that the diffusion degree of HMs pollution in mines was enhanced under acidic conditions, and acid water

245

is an important carrier of HMs through diffusion. Therefore, the HMs pollution around Rona deposit may be

24＞

affected seriously by acid water. The concentrations of Pb, Cd and Cr in Rona river and its tributary water all lower

247

than their standard limits, and the concentrations of Hg and As all lower than their detection limits. Notably, the

248

concentrations of Cu and Zn in tributary water ranged in 1977.00-2168.00 and 1361.00-1434.00 µg L-1, respectively,

249

exceeding their standard limits, indicating polluted by Cu and Zn. In addition, the maximum concentrations of Cu

250

and Zn were 10.84 and 1.43 times than their standard limits set by Emission standard of pollutants for Cu, Ni and

251

Co industry (GB25467-2010), respectively.

252

In comparison with the ABVs, represented by Samalong river, the sites where Cu and Zn exceeding the

253

maximum values of their corresponding ABVs are R5-R12 for Cu and R5-R10 for Zn, respectively, located

254

downstream of the tributary acid water inflow (R5 is intersection) (Fig. 2), and maximum multiples are 8.35 and

255

15.78 for Cu and Zn, respectively, suggesting that Rona river was polluted by acid water. Noteworthily, the

25＞

concentrations of Cd in Rona tributary water samples exceeded its ABV, and maximum multiple was 108 as many,

257

indicating high environmental risk. For Samalong village well water, the concentrations of elements all lower than

258

their standard limits set by Drinking Water Health Standards (GB 5749-2006), suggesting that the acid water had no

259

effect on groundwater. Moreover, the mean concentrations of Cu, Pb and Zn in upper Rona river surface water

2＞0

(R1-R4) were 2.40, 0.18 and 2.78 µg L-1, respectively, lower than their ABVs, indicating that the natural weathering

2＞1

of rocks could not pollute the surface water.

2＞2

3.1.2. Sediments and surface soils

2＞3

The descriptive statistics of HMs concentrations and pH of sediments and surface soils, ABVs (Luo, 2017) and 12 / 29

2＞4

the threshold values (Grade II) for protecting human health are presented in Table 1. The average concentrations of

2＞5

HMs in sediments and surface soils showed trends: Cu>Zn>Cr>Pb>As>Cd>Hg and Cu>Zn>Pb>As>Cr>Cd>Hg,

2＞＞

respectively. The pH values of surface soil samples ranged from 5.00 to 8.65 with a mean value of 7.48±1.07. The

2＞7

soil samples in low pH may be impacted by hydrogen ions resulted from sulfide minerals oxidation. The solubility

2＞8

and migration of HMs are related to pH values and the HMs are generally more mobile at soil pH 7 as compared

2＞9

to high pH (Ma et al., 2016). Given that pH is crucial factor controlling bioavailability and mobility of HMs in

270

sediments or soils, thus, the tested metal fractions in these samples would vary (Hu et al., 2008). The pH values in

271

sediment samples ranged from 7.10 to 9.52 with a mean value of 8.50±0.42, less affected by acid water, which may

272

be attributed to mineral characteristics (e.g. Clay minerals neutralize acids) in sediments (Rodríguez L et al., 2009).

273

The concentrations of Pb, Cd, Cr and Hg in sediments and surface soils all lower than their standard limits

274

(Grade II). However, the concentrations of Cu, Zn and As in sediments and surface soils all exceeded their

275

corresponding standard limits (Table 1). The proportions of sediments and surface soils in which the concentrations

27＞

exceeded the standard limits of Grade II were 56.9% and 95.5% for Cu, 34.5% and 9.1% for Zn, and 50.0% and

277

59.1% for As, respectively, indicating polluted by Cu, Zn and As. Compared with previous researches on the soils

278

from Jiama and Deerni Cu deposits with similar geographic and geological characteristics in China, it is

279

significantly apparent that the average concentrations of Cu, As and Zn in the soils of Rona deposit are higher than

280

that of the Jiama (141.50, 30.40 and 89.80 mg kg-1, respectively) and Deerni Cu deposits (47.30, 24.50 and 89.50

281

mg kg-1, respectively) (Liu et al., 2018), indicating polluted by Cu, Zn and As seriously in the study area. In

282

comparison with the ABVs, the mean concentrations of Cu, Zn and As in sediments and surface soils all significant

283

higher than their ABVs. Tremendous amounts of HMs have been added to the sediments and surface soils in the

284

study area, suggesting that all these metals are heavily impacted by Rona Cu deposit. The concentrations of Cr and

285

Hg in the sediments and surface soils are lower than their ABVs, suggested controlled by natural factors. It can be 13 / 29

28＞

seen that the total concentrations of Cu, Zn and As were partly different between the sediments and surface soils.

287

This is because they suffered from pollution of HMs to different extents. Sediments were polluted with acid water,

288

whereas HMs in surface soils come from the oxidation of surface sulfide ores.

289

The highest concentration sites for Cu in sediments and surface soils are S11 and T7 (position not shown),

290

8.82 and 7.45 times than its standard limit, respectively; S11 and T7 for Zn, 2.17 and 1.38 times than its standard

291

limit, respectively; and S11 and T21 for As (position not shown), 2.06 and 13.50 times than its standard limit,

292

respectively. Accordingly, S11 is the most polluted site, located in the center of riverbed, suggesting that the

293

sediments pollution by acid water is mainly concentrated near the riverbed. The orders of pollution for the highest

294

concentration sites for Cu in sediments were S11

295

in water gradually fade away along the flow direction (Gaur et al., 2005). The highest concentration of As is 13.50

29＞

times higher than its standard limit, which may be related to the geological characteristics of Rona deposit. Rona

297

deposit is rich in enargite (Cu3AsS4) (Li et al., 2015), exposure of the mineral to atmospheric oxygen and moisture

298

resulting in release of high level of As.

Z16 X9, likely because adsorption and deposition of Cu ions

299

Although total metal concentration is useful in identifying the pollution source and the potential for pollution,

300

the mobility and bioavailability of metals not only depend on the total concentration of metals, but also on their

301

specific chemical fraction (Tessier et al., 1979). For example, the fractions of F1, F2 and F3 are considered as the

302

most bioavailable. HMs in F4, F5 and F6 fractions may be potentially bioavailable, while F7 fraction is not

303

bioavailable (Tessier et al., 1979; Rauret et al., 1999). The percentages of HMs fractions in sediments and surface

304

soils are shown in Fig. 3. As the figure shows, there were different patterns of fraction distributions of the HMs in

305

sediments and surface soils. It was observed that in the sediments, the F1+F2+F3 proportions of Pb, As and Cr were

30＞

small, with mean percentages of 2.07% for Pb, 0.38% for As and 0.63% for Cr. In contrast, large amounts of Pb, As

307

and Cr were mainly associated with the F7 fraction, 80.7% for Pb, 86.7% for As and 86.3% for Cr of the total 14 / 29

308

fractions, respectively. In the surface soils, the F1+F2+F3 proportions of Cu, Pb, Zn, As and Cr were small, with

309

mean percentages of 1.13% for Cu, 1.07% for Pb, 1.04% for Zn, 0.25% for As and 0.41% for Cr. However, the F7

310

fraction was predominant for these HMs, 84.0% for Cu, 87.7% for Pb, 87.0% for Zn, 91.6% for As and 84.0% for

311

Cr of the total fractions, respectively. Although the concentrations of Cu, Zn and As in surface soils were as high as

312

1489.35, 344.74 and 404.03 mg kg-1, respectively, and As in sediments was as high as 61.78 mg kg-1, these HMs

313

would be unlikely to pose a direct and significant threat to the surrounding environment since HMs in F7 fraction

314

are held within crystal structures of some primary and secondary minerals (Rodríguez et al., 2009), and elements in

315

F7 fraction are difficult to leach out (Lei et al., 2014), suggesting that the environmental risk of Pb, As and Cr in

31＞

sediments and Cu, Pb, Zn, As and Cr in surface soils may be low in the study area. However, as mentioned above,

317

dominant pollutions of HMs in sediments and surface soils came from Cu, Zn and As, therefore, the environmental

318

risks of these elements still have to be highly focused.

319

In sediments, the average Cu fractions followed the order of F7

F5

F4

F6

F3

F1

F2; the order of Zn

320

was F7

321

the order of Hg was F7

322

Cu, Zn and Hg in sediments and Hg in surface soils were high, the percentages of F4+F5+F6 were significant

323

(40.8% for Cu, 35.9% for Zn and 30.4% for Hg in sediments, respectively; 46.2% for Hg in surface soils). Cu, Zn

324

and Hg in F4+F5+F6 could be released when the redox potential was changed (Rinklebe and Shaheen, 2017),

325

implying potentially environmental risk. Compared with surface soils (7.0%), Cu related to organic matter (F4+F6)

32＞

in sediments (16.6%) were significantly higher (Lei et al., 2014). In addition, compared with surface soils, the

327

average percentage contents of Cu and Zn in sediments in F7 were significantly low, indicating relatively high

328

mobility and bioavailability. As shown in Fig. 3, the total proportions of Cd in F1+F2+F3 were 38.4% and 33.7%

329

for sediments and surface soils, respectively, and F1, F2 and F3 fractions of elements were of stronger mobility and

F5

F6

F4

F3 F6

F2 F4

F1; and the order of Hg was F7 F5

F2

F3

F6

F4

F5

F2

F3

F1. In surface soils,

F1. With respect to these HMs, although the F7 proportions of

15 / 29

330

bioavailability (Ma et al., 2016); additionally, for Cd mobility and bioavailability, Elliott, Liberati and Huang.

331

(1986) also observed that activity of Cd tends to bind to more mobile and bioavailable fractions, indicating high

332

environmental risk. However, the concentrations of Cd in sediments and surface soils were slightly lower or close

333

to their ABVs, environmental risk of Cd do not need to pay too much attention. Moreover, the F3 fraction of HMs

334

can become exchangeable easily with conditions such as pH change (Gimeno-Garcia et al., 1995) and Kong and

335

Bitton (2003) reported that HMs in F3 fraction are more toxic compared with other fractions. However, the F3

33＞

fraction in the study area was relatively low, probably because of hence absence of carbonates in the study area.

337

Besides, surface soil sample T13 (pH=5.40) has a lower percentage of F3 fraction than other surface soil samples

338

(pH>7) due to lower pH. This results agreed with that of Wang and Wei. (1995), who found that when acidic

339

condition increased after acid water inflow, the HMs in F3 fraction would be released, causing greater harm to the

340

environment.

341

3.2. Pollution characteristics

342

Fig. S1a indicated the numbers of different Pi levels of each element according to the category of the Pi values.

343

The 100% of Pb, Cd and Cr in Rona river and its tributary water were unpolluted. The numbers of Cu reached the

344

pollution levels of unpolluted, slightly polluted and moderately polluted were 15, 1 and 6, respectively, and Zn

345

reached the levels of unpolluted and slightly polluted were 15 and 7, respectively. Fig. S1b indicated that the range

34＞

of Pn was from 0.006 to 1.63. According to the category of Pn, 15 samples were unpolluted, and 7 samples were

347

slightly polluted in tributary water.

348

Fig. S2 indicated the numbers of different Pi levels of each element in sediments and surface soils according to

349

the category of the Pi values. The 100% samples of Pb, Cd, Cr and Hg in sediments and surface soils were

350

unpolluted. The numbers of sediment and surface soil samples for Cu in heavily polluted were 22 and 15,

351

respectively; for Zn in moderately polluted and slightly polluted were 2 and 2, respectively; and As in moderately 1＞ / 29

352

polluted and heavily polluted were 1 and 4, respectively. Fig. 4 indicated that the range of Pn was 0.30-9.78.

353

According to the category of Pn, 13 samples were safety; 18 were precaution level; 8 were slightly polluted; 18

354

were moderately polluted; and 23 samples were heavily polluted.

355

Fig. S3 indicated the proportions of different Igeo levels of each element in all sediments and surface soils

35＞

according to the category of the Igeo values. More than half of the sediment and surface soil samples were

357

moderately polluted (29.3% and 0%), moderately to heavily polluted (5.2% and 4.6%), heavily polluted (32.8% and

358

4.6%), heavily to extremely polluted (6.9% and 31.8%) or extremely polluted (0% and 59.1%) by Cu, respectively.

359

The pollution level of Zn in sediment and surface soil samples with 8.6% and 18.2% of moderately polluted and

3＞0

0% and 4.6% of moderately to heavily polluted, respectively. The As pollution in surface soil samples reached the

3＞1

levels of moderately polluted, moderately to heavily polluted, heavily to extremely polluted which took up 9.1%,

3＞2

18.2% and 4.6% of all samples, respectively. The pollution of Cu, Zn, As, Cd, Cr and Hg in all other remaining

3＞3

sediment and surface soil samples remained unpolluted to moderately polluted or practically unpolluted.

3＞4

Accordingly, it could be concluded that the dominant pollutions of HMs in sediments and surface soils came from

3＞5

Cu, Zn and As. Notably, Pb pollution in surface soil samples reached the levels of moderately polluted, moderately

3＞＞

to heavily polluted and heavily polluted which took up 40.9%, 18.2% and 13.6% of all samples, respectively,

3＞7

different from the assessment results using Pi, and it may be the reason of that the Igeo considered all HMs as

3＞8

pollution contribution, overestimating the real pollution levels (Li and Yang, 2008).

3＞9

3.3. Identification of pollution sources

370

3.3.1. Principal component analysis

371

The results of PCA for the HMs concentration in sediments are tabulated in Table S1. Two rotated principal

372

components (PCs) were extracted with eigenvalues>1, accounting for 85.8% of the total variance. Indeed, the PCA

373

(Fig. S4a and Table S1) showed that Cd, As, Pb, Zn and Cu were clustered to PC1, which explains 53.4% of the 17 / 29

374

total variance, suggesting that Cd, As, Pb, Zn and Cu may have a common source or similar sources and moving

375

together (Chabukdhara and Nema, 2012). As mentioned above, the dominant pollutions of HMs in sediments came

37＞

from Cu, Zn and As, and Cu, Zn and As are often associated with Pb and Cd (Alloway, 1995). Hence, these

377

elements may derive from Rona tributary acid water. PC2 explained 32.4% of the total variance, and the loadings of

378

Hg and Cr are 90.6% and 89.4%, of which concentrations were slightly lower or close to their ABVs. Moreover, Cr

379

was lithogenic component (Hanesch et al., 2001). Therefore, Cr and Hg may primarily originate from lithogenic

380

sources seemed to be controlled by parent rocks (Mico et al., 2006).

381

The results of PCA for the HMs concentration in surface soils are tabulated in Table S2. Three rotated

382

principal components (PCs) were extracted with eigenvalues>1, accounting for 83.5% of the total variance. The

383

PCA (Fig. S4b and Table S2) showed that As, Hg and Pb were clustered to PC1 accounting for 36.3% of the

384

variance, and Cd, Zn and Cu were clustered to PC2 accounting for 30.2% of the variance. The mean concentrations

385

of Cu, Pb, Zn, As and Cd were all higher than their ABVs, which may derive from the surface sulfide ores

38＞

oxidation. Notably, the content of Hg was lower than its ABV, came from lithogenic sources. Cr was clustered to

387

PC3 accounting for 17.1% of the variance, of which concentration was slightly lower than its ABV, which may also

388

originate from lithogenic sources.

389

3.3.2. Cluster analysis

390

CA was used to group the HMs having homologous characteristics, which could give more details to further

391

verify the results of above PCA analysis (Chabukdhara and Nema, 2012). CA examines distances between HMs and

392

the most similar HMs are grouped forming one cluster and the process is repeated until all HMs belong to one

393

cluster (Danielsson et al., 1999). The lower the value on the distance cluster, the more significant was the

394

association. A criterion for the distance cluster of between 15 and 20 was used in this analysis.

395

In the sediments, two distinct clusters can be identified (Fig. S5a). Cluster 1 contained Cu, Zn, Cd, Pb and As. 18 / 29

39＞

Due to high content, these elements probably came from acid water. Cluster 2 contained Cr and Hg. The contents of

397

these elements are below their ABVs and may originate from lithogenic sources. In the surface soils, three distinct

398

clusters can be identified (Fig. S5b). Cluster 1 contained Zn, Cd and Cu. The concentrations of these elements are

399

higher than their ABVs and may come from surface sulfide ores oxidation. Cluster 2 contained Hg, As and Pb. The

400

contents of As and Pb are higher than their ABVs and may derive from sulfide ores oxidation. Due to low content,

401

Hg may originate from lithogenic sources. Cluster 3 contained only Cr. Due to low content, the Cr may originate

402

from lithogenic sources. In general, the results of the CA agreed well with that of the PCA analysis. The Rona Cu

403

deposit HMs inputs into the surrounding environment caused significant enrichments of HMs, such as Cu, Pb, Zn,

404

As and Cd in the sediments and surface soils. Overall, the elements of Cu, Pb, Zn, As and Cd in sediments and

405

surface soils enriched beyond their ABVs are seriously affected by Rona Cu deposit, whereas Cr and Hg may

40＞

primarily originate from lithogenic sources. The causes of HMs formation are described as follows.

407

Rona tributary acid water formed in the middle of Rona Cu deposit may be caused by the North-South tectonic

408

fault of the Tibetan plateau. The destruction of the original stable protection layer for metal sulfide ores and

409

surrounding rocks caused the exposure of sulfur-bearing minerals in Rona deposit to atmospheric oxygen and

410

moisture, under appropriate environmental conditions, sulfides are quickly oxidized and many associated elements,

411

such as Cu, Pb, Zn, As and Cd are released and separated from sulphur, resulting in a large amount of AMD

412

(Duruibe et al., 2007). Harrison et al. (1992) showed that the North-South tectonic fault in the study area formed in

413

7-9 Ma, later than the mineralization age of the deposit in 116-120 Ma (Tang et al., 2016). Furthermore, field

414

observation showed that the tributary water distributed along the North-South tectonic fault (Fig. 1a). Compared

415

with other sulfur-bearing minerals, pyrite is more likely to produce AMD (Obreque-Contreras et al., 2015) and the

41＞

formation can be represented by the following equations:

417

2FeS2 (s) + 2H2O + 7O2→2Fe2+ + 4SO42- + 4H+

(7) 19 / 29

418

2Fe2+ + 2H+ + 1/2O2 → 2Fe3+ + H2O

(8)

419

2Fe3+ + 6H2O↔2Fe (OH)3 (s) + 6H+

(9)

420

FeS2 (s) + 14Fe3+ + 8H2O → 15Fe2+ + 2SO42- + 16H+

421

The oxidation of chalcopyrite produced a large amount of soluble Cu2+, which was the main source of Cu

422

(10)

pollution in the study area, and the formation can be represented by the following equations:

1 O2+H2SO4→2CuSO4+Fe2(SO4)3+H2O 2

(11)

x ) O2 + x H2O→(1- x ) Fe2++ SO42−+2 x H+ 2

(12)

423

2CuFeS2+8

424

Fe1- x +(2-

425

Fe2++1/4O2+5/2H2O ↔ Fe(OH)3(s)+2 H+

42＞

3.4. Environmental risk assessment

(13)

427

Fig. S6 illustrated the potential ecological risks of the HMs in the sediments and surface soils. Cu in sediments

428

posed a low, moderate, high and serious potential ecological risk in approximately 55.2%, 17.2%, 22.4% and 5.2%

429

of the study area, respectively. In addition, Cd and Hg posed a moderate risk in approximately 1.7% and 22.4%,

430

respectively, whereas all of the sediment samples were free from ecological risk posed by other elements. Cu in

431

surface soils posed a moderate, serious and severe ecological risk in approximately 9.1%, 63.6% and 27.3% of the

432

study area, respectively, and As posed a low, moderate, high and serious ecological risk in approximately 72.7%,

433

9.1%, 13.6% and 4.6%, respectively. Additionally, Hg posed a moderate risk in approximately 13.6%, and Pb posed

434

a moderate and high risk in approximately 13.6% and 9.1%, respectively, whereas all of the surface soils were free

435

from ecological risk posed by Zn and Cr. Due to the easy dissolution and transport of major chemical fractions of

43＞

Cd in surface soils, 31.8% of moderate ecological risk of Cd were observed. In summary, the results indicated that

437

pollution control should be carried out in some locations, especially for Cu and As.

438

As presented in Figure 5, the RI values of the elements in the sediments ranged from 50.40 to 282.77. 20 / 29

439

According to the category of RI, 17 samples were classified into moderate risk and 41 samples were classified into

440

low risk. The RI values of the elements in the surface soils ranged from 139.07 to 982.53. According to the

441

category of RI, 2 samples were classified into very high risk; 15 samples were classified into considerable risk; 4

442

samples were classified into moderate risk; and 1 sample was classified into low risk. The distribution of RI values

443

in Fig. 5 showed an obviously corresponding relationship and similar changing trend with the distribution of Pn

444

values in Fig. 4. Therefore, more reliable results can be obtained by using these two evaluation methods

445

simultaneously.

44＞

The results of RAC assessment are tabulated in Table 2. Cu and Pb ranged from no risk to low risk in all

447

sediments and surface soils; and Zn ranged from low to medium risk in sediment samples, from no risk to low risk

448

in surface soil samples. Except sample Z6 (low risk), the element As was no risk in all sediments and surface soils.

449

Except sample S13 (low risk), Cr was no risk in all samples. Moreover, the Hg was low risk in all sediments and

450

surface soils. Notably, the Cd ranged from medium to very high risk in sediments, and low to high risk in surface

451

soils. Obviously, there was disagreement between the RAC and the Pi analysis shown in Table 2. There are

452

sediment and surface soil samples considered to be moderately or heavily polluted that ranged from no risk to low

453

risk according to the RAC, e.g. S1, S6, S7, S10, S13, Z9, Z13, X8, X12, T12, T13, T14, T17, T18, T21 and T22 for

454

Cu; and the samples considered to be slightly or heavily polluted are no risk according to the RAC, e.g. S10, Z13,

455

X5, X6, T12, T13, T14, T17, T21 and T22 for As. On the contrary, samples considered to be unpolluted are low to

45＞

very high risk according to the RAC for Cd. The all above analysis showed that there are obviously different

457

environmental risk assessments among different evaluation methods, such as Pi, Igeo, Eir and RAC, which may be

458

caused by different emphasis of evaluation. Accordingly, when evaluating environmental risk of HMs, both total

459

metal concentration and bioavailable metal fraction should be considered.

4＞0

4. Conclusions and recommendations 21 / 29

4＞1

The results of this paper showed that environmental pollution in mines was not entirely caused by

4＞2

anthropogenic activities. Unexploited deposits in natural background also had strong environmental risk. Natural

4＞3

metallic acid water discharge and the oxidation of surface sulfide ores in Rona Cu deposit have resulted in severe

4＞4

HMs pollution of the study area in Tibet, China. The elements Cu and Zn were two pollutants in acid water, and

4＞5

Rona river was obviously affected by acid water. The acid water had no effect on groundwater. The dominant

4＞＞

pollution of HMs in sediments and surface soils came from Cu, Zn and As. Due to relatively high residual fraction,

4＞7

the environmental risk of Cu, Zn and As may be low. Cd in sediments and surface soils near high risk status.

4＞8

However, due to high content, the environmental risk of Cu, Zn and As still have to be highly focused. Due to low

4＞9

content, the environmental risk of Cd do not need to pay too much attention. The source of Cu, Pb, Zn, As and Cd

470

in sediments and surface soils may mainly derive from Rona Cu deposit, whereas Cr and Hg may primarily

471

originate from lithogenic sources. The treatment for Rona natural acid water pollution only needs to cut off the

472

sewage source, thus, the mining of Rona Cu deposit may be the best way to solve the pollution. Unexploited Rona

473

Cu deposit had produced considerable environmental risk for the surrounding environment, thus, it is necessary to

474

pay more attention to the environmental risk of more unexploited deposits.

475

Acknowledgements

47＞

This work was financially supported by Investigation and Evaluation of the Whole Industrial Chain of Core

477

Minerals in Emerging Industries (No.DD20190676) and Integrated Evaluation of Technology Economy and

478

Environment of Duolong Deposit in Tibet (No.DD20160330).

479

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Table 1 Summary of the background values, guideline values and basic statistics of the HMs and pH in the water, sediment and surface soil samples in the study area sample

water

HM concentrations (µg L-1 for water, mg kg-1 for sediments and surface soils, n=number)

Location

Surface soils

Cu

Zn

Cd

Pb

Hg

As

pH

Tributary

Range

1.49-4.54

1977.00-2168.00

1361.00-1434.00

0.98-1.08

0.32-6.39

-

-

2.70-3.08

(n=7)

Mean

2.85±1.09

2114.00±65.89

1402.14±27.36

1.04±0.04

1.87±2.55

-

-

2.89±0.15

Rona river

Range

0.38-12.50

1.87-55.60

2.24-110.00

0.002-0.12

0.04-0.23

-

-

7.08-7.92

(n=15)

Mean

6.19±4.30

15.78±16.64

19.48±27.71

0.04±0.03

0.14±0.07

-

-

7.66±0.26

Smalong river

Range

4.62-5.92

2.46-6.66

1.40-6.97

0.007-0.01

0.32-0.64

-

0.003-0.01

7.65-8.16

(n=3)

Mean

5.29±0.65

4.08±2.26

4.46±2.82

0.009±0.002

0.50±0.16

-

0.005±0.004

7.93±0.26

Samalong well water

Range

1.91-4.85

0.82-1.46

0.94-3.98

-

-

-

0.0027-0.003

7.98-8.01

(n=3)

Mean

3.76±1.61

1.11±0.32

2.70±1.58

-

-

-

0.003±0.0002

8.00±0.02

standard limits of GB25467-2010

-

200

1000

20

200

10

100

6.00-9.00

standard limits of GB 5749-2006

50

1000

1000

5

10

1

10

6.50-8.50

Class III

50

1000

1000

5

50

0.1

50

6.00-9.00

Range

19.62-65.54

110.58-1763.10

104.24-543.06

0.17-0.41

17.53-66.58

0.01-0.03

11.12-61.78

7.10-8.91

(n=20)

Mean

37.28±14.23

656.95±525.35

229.75±133.01

0.23±0.07

29.85±14.18

0.01±0.01

28.02±14.01

8.27±0.55

Z-Z’

Range

37.55-97.49

19.01-1166.50

62.00-451.33

0.16-0.48

17.21-50.55

0.02-0.05

11.32-43.14

8.20-9.52

(n=19)

Mean

64.29±18.82

307.86±340.64

178.65±112.00

0.27±0.10

32.22±11.37

0.02±0.01

23.75±10.09

8.65±0.35

X-X’

Range

65.29-145.68

51.78-1063.75

95.00-464.35

0.21-0.45

27.16-59.03

0.01-0.04

23.63-51.45

8.28-8.82

(n=19)

Mean

99.00±22.06

445.24±397.26

205.37±123.21

0.31±0.08

42.77±9.10

0.03±0.01

34.54±7.97

8.59±0.14

Mean

66.35±31.40

473.24±446.88

205.02±122.88

0.27±0.09

34.86±12.88

0.02±0.01

28.76±11.72

8.50±0.42

ABVs

79.30

46.00

131.00

0.35

43.30

0.03

25.40

7.10

S-S’

sediments

Cr

A-B

Range

17.57-65.90

154.60-1489.35

55.38-344.74

0.10-0.31

20.01-270.17

0.01-0.09

10.05-404.03

5.00-8.65

(n=22)

Mean

37.77±11.61

785.38±343.79

123.99±76.41

0.17±0.06

86.09±69.45

0.03±0.02

62.29±84.59

7.48±1.07

ABVs

52.73

14.85

49.27

0.13

13.88

0.05

12.97

-

Grade II

200

200

250

0.6

300

0.5

30

6.50-9.00

- Not detected or no data is available (detection limits: Cd<0.002, Pb<0.002, Hg<0.10 and As<0.60 µg L-1)

Table 2 Comparison table of Pi and RAC assessment results for Cu, As and Cd Sample name S1 S6 S7 S10 S13 Z1 Z5 Z6 Z9 Z13 X1 X5 X6 X8 X12 T12 T13 T14 T17 T18 T21 T22

Cu

As

Cd

Pi

RAC

Pi

RAC

Pi

RAC

Moderately polluted Heavily polluted Heavily polluted Heavily polluted Moderately polluted Safety Safety Safety Heavily polluted Moderately polluted Safety Safety Safety Heavily polluted Moderately polluted Heavily polluted Heavily polluted Heavily polluted Heavily polluted Moderately polluted Heavily polluted Heavily polluted

L L L L L N L L L L L L L L L N N N N N L L

Safety Safety Safety Slightly polluted Safety Safety Safety Safety Safety Slightly polluted Safety Slightly polluted Slightly polluted Safety Safety Slightly polluted Slightly polluted Slightly polluted Slightly polluted Safety Heavily polluted Heavily polluted

N N N N N N N L N N N N N N N N N N N N N N

Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety Safety

H M M H VH VH H H H H H H H M M H M H M L H H

Appendix: List of figures

Fig. 1. Photographs of the unexploited Rona Cu deposit study area: a Rona tributary river (natural spring water), b Tributary river water flows down slope and into Rona river, c Riparian vegetation changes before and after the inflow of tributary water (The red circle is the inlet position of tributary water), d Yellowish brown water of the Rona river, e Abundant yellow foam on the ice sheet, f Adjacent hillside covered with abundant oxidized ores

Fig. 2. Location of the study area and surface water, sediments and surface soils sampling sites

80

80

60

60

Pb (%)

100

40

40

20

20

100 0

100 0

80

80

60

60

Cd (%)

Cu (%) As (%)

100

40

20

20

0 100

0 100

80

80

60

60

Hg (%)

Cr (%)

40

40

40

20

0 100

0 S1 S6 S7 S1 0 S1 3 Z1 Z5 Z6 Z Z19 3 X1 X5 X6 X X18 T12 T12 T13 T14 T17 T28 T21 2

20

Zn (%)

80 F1 F2 F3 F4 F5 F6 F7

60

40

S1 S-S' sample Z1 Z-Z' sample X1 X-X' sample T12 A-B sample

20

S1 S6 S S17 0 S1 3 Z1 Z5 Z6 Z Z19 3 X1 X5 X6 X X18 T12 T12 T13 T14 T17 T28 T21 2

0

Fig. 3. The percentage contents of HM fractions in selected sediment and surface soil samples

Fig. 4. The results of different Pn values for sediment and surface soil samples

Fig. 5. The values of the RI for HMs in the sediment and surface soil samples

HIGHLIGHTS • Unexploited Rona Cu deposit at Tibet has resulted in considerable environmental risk. • pH and HMs in water, sediments and surface soils in the study area were investigated. • The dominant pollution of HMs in sediments and surface soils came from Cu, Zn and As. • The contents of Cu and Zn in acid water were 2114.0 and 1402.1 µg L-1, respectively. • Both total metal concentration and bioavailable metal fractions should be considered.

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our research work. There is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the manuscript entitled “Pollution, sources and environmental risk assessment of heavy metals in the surface AMD water, sediments and surface soils around unexploited Rona Cu deposit, Tibet, China”.