Science of the Total Environment 468–469 (2014) 843–853

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Review

A review of soil heavymetal pollution frommines in China: Pollution andhealth risk assessment

Zhiyuan Li a,b, Zongwei Ma a, Tsering Jan van der Kuijp a, Zengwei Yuan a, Lei Huang a,⁎a State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, Chinab Atmospheric Research Center, Fok Ying Tung Graduate School, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

H I G H L I G H T S

• This paper reviews soil heavy metal pollution derived from mines in China.• A comprehensive pollution and health risk assessment was conducted.• Soils surrounding the examined mines are seriously polluted by heavy metals.• The soil heavy metal pollution continues to pose high health risks to the public.• The priority control heavy metals, mine types, and provinces were identified.

⁎ Corresponding author. Tel.: +86 25 8968 0535; fax: +E-mail addresses: lizhiyuankylelee@gmail.com (Z. Li),

(L. Huang).

0048-9697/$ – see front matter © 2013 Published by Elsehttp://dx.doi.org/10.1016/j.scitotenv.2013.08.090

a b s t r a c t

a r t i c l e i n f o

Article history:Received 6 December 2012Received in revised form 24 August 2013Accepted 27 August 2013Available online xxxx

Editor: Filip M.G. Tack

Keywords:Chinese mining areasSoil heavy metal pollutionPollution assessmentHealth risk assessment

Heavymetal pollution has pervadedmany parts of theworld, especially developing countries such as China. Thisreview summarizes available data in the literature (2005–2012) on heavy metal polluted soils originating frommining areas in China. Based on these obtained data, this paper then evaluates the soil pollution levels of thesecollected mines and quantifies the risks these pollutants pose to human health. To assess these potential threatlevels, the geoaccumulation index was applied, along with the US Environmental Protection Agency (USEPA)recommended method for health risk assessment. The results demonstrate not only the severity of heavymetal pollution from the examined mines, but also the high carcinogenic and non-carcinogenic risks that soilheavymetal pollution poses to the public, especially to children and those living in the vicinity of heavily pollutedmining areas. In order to provide keymanagement targets for relevant government agencies, based on the resultsof the pollution and health risk assessments, Cd, Pb, Cu, Zn, Hg, As, and Ni are selected as the priority controlheavy metals; tungsten, manganese, lead–zinc, and antimony mines are selected as the priority control minecategories; and southern provinces and Liaoning province are selected as the priority control provinces. Thisreview, therefore, provides a comprehensive assessment of soil heavy metal pollution derived from mines inChina, while identifying policy recommendations for pollution mitigation and environmental management ofthese mines.

© 2013 Published by Elsevier B.V.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8442. Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 844

2.1. Data collection and processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8442.2. Index of geoaccumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8452.3. Health risk assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 845

2.3.1. Exposure assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8452.3.2. Non-carcinogenic risk assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8452.3.3. Carcinogenic risk assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8462.3.4. Monte Carlo simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 846

86 25 8968 0586.njumazw@163.com (Z. Ma), tjvan10@gmail.com (T.J. van der Kuijp), yuanzw@nju.edu.cn (Z. Yuan), huanglei@nju.edu.cn

vier B.V.

844 Z. Li et al. / Science of the Total Environment 468–469 (2014) 843–853

3. Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8463.1. Provincial and resource-type distribution of the examined mining areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8463.2. Pollution assessment of the examined mining areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8463.3. Health risk assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 847

3.3.1. Non-carcinogenic risk from the eight heavy metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8473.3.2. Carcinogenic risk of As . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 849

3.4. Comparison with other heavy metal soil studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8503.5. Priority control components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8513.6. Recommendations for management efforts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8513.7. Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 851

4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 851Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 851Appendix A. Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 851References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 851

1. Introduction

China holds diversified and large-scale mineral resources. There are171 varieties ofmineral resources in China, and proven reserves of min-eral resources constitute 12% of the total mineral resources in theworld (Hu et al., 2009). Moreover, China is one of the largest globalproducers and consumers of metals/metalloids such as antimony (Sb),iron (Fe), lead (Pb), manganese (Mn), tin (Sn), tungsten (W), and zinc(Zn), aswell as of resources such as coal (Gunson and Jian, 2001).Mineralresources represent the key material foundation for socio-economic de-velopment, rendering the exploitation and utilization of mineral re-sources essential to China's modernization. Nonetheless, despite theimportance of mineral resources, mineral extraction has inflicted seriousenvironmental damage, especially in the realm of heavy metal pollution(Acosta et al., 2011; Komnitsas and Modis, 2006; Zhou et al., 2007).

Heavy metals such as lead (Pb), zinc (Zn), cadmium (Cd), mercury(Hg) and chromium (Cr) generally refer to metals andmetalloids havingdensities greater than 5 g/cm3 (Oves et al., 2012). Metalloids such asarsenic (As) often fall into the heavy metal category due to similaritiesin chemical properties and environmental behavior (Chen et al., 1999).Heavy metal pollution is covert, persistent and irreversible (Wang et al.,2001). This kind of pollution not only degrades the quality of the atmo-sphere, water bodies, and food crops, but also threatens the health andwell-being of animals and human beings by way of the food chain(Dong et al., 2011; Nabulo et al., 2010; Wang et al., 2001). For example,Pb is a non-essential element to the human body, and excessive intakeof the metal can damage the nervous, skeletal, circulatory, enzymatic,endocrine, and immune systems of those exposed to it (Zhang et al.,2012). Moreover, chronic exposure to Cd can have adverse effects suchas lung cancer, pulmonary adenocarcinomas, prostatic proliferativelesions, bone fractures, kidney dysfunction, and hypertension, while thechronic effects of As consist of dermal lesions, peripheral neuropathy,skin cancer, and peripheral vascular disease (Żukowska and Biziuk,2008).

Soil heavy metal pollution has become a severe problem in manyparts of the world (Facchinelli et al., 2001; Solgi et al., 2012). Followingrapid social and economic development over the past several decades,soil pollution by heavy metals has been both serious and widespread inChina (Chen et al., 1999; Wang et al., 2001). Although heavy metalsmay occur naturally in soil, additional contributions come from anthro-pogenic activities such as agriculture, urbanization, industrialization,and mining (Facchinelli et al., 2001). Indeed, numerous studies haveshown that pollution sources of heavymetals in the environmentmainlyderive from these anthropogenic sources (Wei andYang, 2010). In China,the dominant sources of soil heavymetal pollution are sewage irrigation,sludge application, andmining and smelting operations for metallic ores(Chen et al., 1999). A six-year soil pollution study conducted by theChinese government departments found that the country's soil hadbeen vastly polluted by human activities in the industrial, mining, andfarming sectors (CSC, China State Council, 2012). Among these, mining

is considered to be one of themost significant sources of heavymetal con-tamination (Acosta et al., 2011; Dudka and Adriano, 1997; Fryer et al.,2006; Liu et al., 2005). Mining alone has generated about 1,500,000 haof wasteland in China, which has a total of 960 million hectares of land,and this wasteland figure is increasing at a rate of 46,700 ha per year(Zhuang et al., 2009a).

From a recent literature review, it was discovered that numerousstudies of soil heavy metal pollution related to mining activities hadbeen carried out in China during the past fewyears (2005–2012). For in-stance, Liu et al. (2005) reported that the heavymetal concentrations inthe study area's soil, which was covered with mine tailings, greatlysurpassed the maximum allowable concentration levels for Chineseagricultural soil, exceeding As level 24-fold and Cd level 13-fold. In aseparate report, Wu et al. (2011) suggested that 49.62% of all soilsamples posed significantly high or high potential ecological risksin the Xiaoqinling gold-mining region of Shaanxi, China. In addition,Zhuang et al. (2009b) found that the average concentrations of Cu, Zn,and Cd (502, 498, and 3.92 mg/kg, respectively) in paddy soil were 10,2.5, and 13 times above the Grade II environmental quality standard forsoils in China (GB15618-1995), respectively. However, a very limitednumber of health risk assessment studies have been carried out regardingsoil heavy metal pollution frommines. Moreover, most of the aforemen-tioned studies have focused on a single or just a fewmining areas; thus, acomprehensive nationwide pollution assessment of mining areas inChina is urgently needed. Therefore, the purpose of this study is to assesson a national scale the pollution levels and health risks of heavymetals inthe soils ofmining areas. The objectives of this research are 1) to evaluatethe soil heavy metal pollution levels of mines in China; 2) to assess thehealth risks posed by these contaminated soils; 3) and to propose recom-mendations for the environmentalmanagement ofmining areas in China.

2. Materials and methods

2.1. Data collection and processing

This study systematically reviews a host of studies related to soilheavy metal pollution from mines in China between 2005 and 2012.Eight heavymetals, namely Pb, Zn, Ag, Cd, Cr, Cu, Ni, andHg,were includ-ed in this study, all of which are priority heavymetal pollutants as desig-nated by the USEPA. From the main literature databases including Webof Science, China Knowledge Full-text Literature Database, and ChinaWanFang Literature Database, data from 72mining areas were collectedand analyzed. Background information on these mines is described inTable S1 of the supplementary information. Most of the collectedminingareas are located in the southern and eastern regions of China, which isconsistent with patterns of mineral exploitation in China (Cao et al.,2004). In addition, many of the examinedmines in this study are sourcesof critical mineral deposits with regard to scale and annual output andhave recently become research hot-spots in China. For example, theDexing copper mine in Jiangxi province has the highest annual copper

Table 1Seven classes comprising the geoaccumulation index.

Class Value Soil quality

0 Igeo ≤ 0 Practically uncontaminated1 0 b Igeo b 1 Uncontaminated to moderately contaminated2 1 b Igeo b 2 Moderately contaminated3 2 b Igeo b 3 Moderately to heavily contaminated4 3 b Igeo b 4 Heavily contaminated5 4 b Igeo b 5 Heavily to extremely contaminated6 5 b Igeo Extremely contaminated

845Z. Li et al. / Science of the Total Environment 468–469 (2014) 843–853

output in China and the second highest globally (H.Y. Li et al., 2008);Shizhuyuan tungsten–tin bismuth molybdenum mine in Hunanprovince is the largest non-ferrous metal mine in China (Lei et al.,2005); and Huayuan lead–zinc mine is the third largest reservoir oflead–zinc metal in China (Yang et al., 2012a, 2012b). Thus, to a great ex-tent, these mines maintain a high degree of representativeness.

Conventional sampling procedures have involved collecting repre-sentative soil samples located in the vicinity of mines. Some studieshave divided the areas under investigation into different zones (Liet al., 2010; Yin et al., 2008; Zhao et al., 2012). In general, every studyzone was further divided into a grid of cells using a systematic gridsampling method with regularly spaced intervals. Afterwards, soilsamples were collected in the field via random sampling methods,and samples were usually collected to a depth of 0–15 cm (Liuet al., 2007; Wu et al., 2010), 0–20 cm (Guo et al., 2011; Liu et al.,2006; Zhang et al., 2009), 20–40 cm (Hui et al., 2011) and thenmixed thoroughly to give a composite sample (Liu et al., 2007; Wuet al., 2010). In the laboratory, soil samples were always air-dried atroom temperature, and then pulverized and sieved. In general, soil sam-ples in these studies were digested with a typical concentrated acidmixture (e.g. HNO3–HClO4–HF or HNO3–HClO4–HCl or HCl–HNO3–

HF–HClO4) (Li et al., 2010; Liu et al., 2006, 2007; Zhao et al., 2012).Then, digested soil solutions were treated by a variety of analyticalmethods, such as atomic fluorescence spectrophotometry (Shi et al.,2010; Zhu et al., 2007) and inductively coupled plasma atomic emissionspectrometry (Feng et al., 2011; H.W. Li et al., 2008). The samplingstrategies and processing methods used in the selected studies are allwidely accepted by the scientific community.

The mean, range, and standard deviation values of the heavy metalsfound at various mining areas were collated (Table S2). In addition, inorder to substantiate the comparisons with standards, percentile values(10th, 25th, 50th, 75th, and 90th) of the heavy metal concentrationswere analyzed and the percentages of mining areas in comparisonswith soil standards were calculated (Tables S3, S4). All the statisticalanalyses for the data were performed by the software package SPSS19.0 (IBM SPSS Inc., Chicago, USA) for Windows.

2.2. Index of geoaccumulation

The geoaccumulation index (Igeo) was introduced byMüller (Müller,1969) and has been widely employed in European trace metal studies(Ji et al., 2008). It enables the assessment of environmental contamina-tion by comparing differences between current andpreindustrial concen-trations. Originally used with river bottom sediments, it can also beapplied to the assessment of soil contamination (Loska et al., 2004). Inthis study, the Igeo for the soils of examined mines was computed usingthe following equation:

Igeo ¼ log2 Cn=1:5Bnð Þ ð1Þ

where Cn is the measured concentration of every heavy metal found inthe mine soil (mg/kg), and Bn is the geochemical background value ofthe heavy metals found in the soil (mg/kg), which is given in Table S5(CNEMC, China National Environmental Monitoring Center, 1990).The constant 1.5 is used due to potential variations in the baselinedata (Loska et al., 2004; Solgi et al., 2012). The geoaccumulation indexconsists of 7 classes or grades (Table 1), whereby the highest class 6reflects a 100-fold enrichment above the background values (Forstneret al., 1990). The Igeo values for the heavy metals of the examinedmines are listed in Table S6.

2.3. Health risk assessment

Human health risk assessment is the process of estimating thenature and probability of adverse health effects in humans who maybe exposed to chemicals in contaminated environmental media (NRC,

National Research Council, 1983). Due to behavioral and physiologicaldifferences, this study divided the people who live in close proximityto the examined mining areas into three groups: children, adult malesand adult females. The health risks posed to these three groups wereestimated and analyzed.

2.3.1. Exposure assessmentThe general exposure equations used in this study are based on rec-

ommendations provided by several American and Canadian publications(HC, Health Canada, 2004; USEPA, 1989, 1992, 2003). To calculate levelsof human exposure to heavy metals, the average daily intake (ADI)(mg/kg-day) equation by a given route is used:

ADI ¼ C� IR � EF� EDBW� AT

ð2Þ

where C is the chemical concentration in a particular exposure medium(mg/L, mg/kg, mg/m3), IR is the ingestion rate (L/day, kg/day, m3/day),EF is the exposure frequency (day/per year), ED is the exposure duration(year), BW is the body weight of the exposed individual (kg), and AT isthe time period over which the dose is averaged (day).

For heavy metals in contaminated soils, ingestion and dermalabsorption play themost important roles among the potential exposurepathways (Fryer et al., 2006; Qu et al., 2012). For instance, Ordóñez et al.(2011) found that ingestion of soil is the most common exposurepathway for As, Cd, Cr, Cu, Ni, Pb, and Zn in the mercury miningareas of Northern Spain. Considering these two pathways, the exposuredose was calculated using Eqs. (3) and (4) adapted from the USEPA(USEPA, 1989).

Ingestion:

ADII ¼Cs � SIR� EF� ED

BW� ATð3Þ

where ADII is the average daily intake of heavy metals from soil inges-tion (mg/kg-day), CS is the heavy metal concentration found in thesoil (mg/kg), and SIR is the ingestion rate of soil (mg/day).

Dermal absorption:

ADID ¼ CS � SA� AF� ABS� EF� EDBW� AT

ð4Þ

where ADID is the average daily intake of heavy metals from dermalabsorption (mg/kg-day), SA is the exposed skin surface area (cm2), AFis the adherence factor (mg/cm2-day), and ABS is the dermal absorptionfactor (unitless).

2.3.2. Non-carcinogenic risk assessmentNon-carcinogenic hazards are typically characterized by the hazard

quotient (HQ). The hazard quotient is defined as the quotient of thechronic daily intake, or the dose divided by the toxicity thresholdvalue, which is referred to as the reference dose (RfD) of a specificchemical. The hazard quotient of a single chemical is determined byEq. (5) (USEPA, 1989):

HQ ¼ ADIRfD

ð5Þ

846 Z. Li et al. / Science of the Total Environment 468–469 (2014) 843–853

where RfD is the chronic reference dose for the chemical (mg/kg-day).To assess the overall potential for non-carcinogenic effects posed bymore than one chemical, a Hazard Index (HI) approachhas been applied(USEPA, 1986). For amixture of contaminations, the hazard index of themixture is calculated from Eq. (6) (USEPA, 1989):

HI ¼X

HQi ¼X ADIi

RfDið6Þ

If the HI value is less than one, the exposed population is unlikely toexperience obvious adverse health effects. If the HI value exceeds one,then adverse health effects may occur (Man et al., 2010). Because noreference doses are presently available for directly evaluating dermalabsorption exposure to contaminants, theUSEPAhasdeveloped amethodto extrapolate oral toxicity values for use in dermal risk assessment.RfDABS (Table S7) is calculated by using Eq. (7) (USEPA, 2002):

RfDABS ¼ RfDo � ABSGI ð7Þ

where RfDABS is the dermally adjusted reference dose (mg/kg-day),RfDo is the oral reference dose (mg/kg-day), and ABSGI is the gastro-intestinal absorption factor (unitless).

2.3.3. Carcinogenic risk assessmentCarcinogenic risks are estimated by calculating the incremental

probability of an individual developing cancer over a lifetime as a resultof exposure to the potential carcinogen. The slope factor (SF) convertsthe estimated daily intake of a toxin averaged over a lifetime of exposuredirectly to the incremental risk of an individual developing cancer(USEPA, 1989):

Risk ¼ ADI� SF ð8Þ

where Risk is the unitless probability of an individual developingcancer over a lifetime and SF is the carcinogenicity slope factor (permg/kg-day). Risks surpassing 1 × 10−4 are viewed as unacceptable,risks below 1 × 10−6 are not considered to pose significant healtheffects, and risks lying between 1 × 10−4 and 1 × 10−6 are generallyconsidered an acceptable range, dependingon the situation and circum-stances of exposure (Fryer et al., 2006; Hu et al., 2012). Similarwith RfD,according to the USEPA's extrapolation method, SFABS (Table S7) iscalculated by using Eq. (9) (USEPA, 2002):

SFABS ¼ SFO=ABSGI ð9Þ

where SFABS is the dermally adjusted slope factor (per mg/kg-day) andSFO is the oral slope factor (per mg/kg-day).

2.3.4. Monte Carlo simulationUncertainty is pervasive in risk assessment (Carrington and Bolger,

1998; Mesa-Frias et al., 2012), especially when the uncertainty arisesdue to a lack of precise knowledge, the variability of environmental sys-tems, and the variability of individual human characteristics (Mari et al.,2009). To minimize the uncertainties of the above calculations, risk as-sessments were conducted via Monte Carlo simulations. The softwareplatform Oracle Crystal Ball (Oracle Corporation, Vallejo, US), which isone of the most commonly used Monte Carlo modeling tools (Molak,1997), was adopted to carry out the simulation. The toxicity parametersfor the heavy metals were derived from USEPA guidelines and interna-tional research findings. In addition, in order to reduce assessment un-certainties generated by distribution factors, values obtained directlywithin Chinawere given the highest priority when available. For exam-ple, body weight and skin surface area data were collected from thestudies conducted in China. For the remaining data gaps unfilled bylocalized research, data obtained by international agencies and relatedresearchers were used. The toxicological data for the heavy metals anddetailed information on the probabilistic exposure factors are presented

in Tables S7 and S8, respectively. The simulation was performed usingthe presented parameters, and the model ran for 10,000 iterations. Theresults of the analysis are presented in Tables S9 and S10.

3. Results and discussion

3.1. Provincial and resource-type distribution of the examinedmining areas

The 72 examinedmining areas are located in 22provinces throughoutChina (Fig. S1). Liaoning, Guizhou, and Guangxi provinces contain thegreatest number of mines (7) that were reviewed, and Jiangxi andHunan provinces both contain 6 examined mines, while Xinjiang, Tibet,Shanxi, and Hubei provinces have the least number of examined minesat 1. The other 13 provinces have different numbers of examinedminingareas, ranging from 2 to 5. Regarding the resource type (Fig. S2), thenumber of examined mines for coal, copper, lead–zinc, manganese,tungsten, iron, gold, antimony, and multi-metal are 14, 12, 17, 6, 6, 3,2, 2, 3, respectively. Furthermore, there are 7 other mines containingdifferent types of natural resources, such as silver–antimony andnickel–copper mine resources.

3.2. Pollution assessment of the examined mining areas

As shown in Fig. 1 and Table S3, the mean and median concentra-tions of each heavy metal both exceed the corresponding backgroundvalue for soils in China. The mean concentrations of As, Cd, Cr, Cu, Ni,Pb, Zn, and Hg are about 6.5, 36.5, 0.4, 2.1, 2.1, 2.1, 4.7, and 7.6 timesgreater, respectively, than the Grade II environmental quality standardfor soils in China (GB15618-1995). 86.4% of all the Cd samples surpasstheGrade II value (Fig. 1, Table S4). For Cr, the 90%percentile concentra-tion (178.9) lies lower than the corresponding Grade II value (200), andthe concentration of Cr for 95% of samples remains lower than theGradeII value (Fig. 1, Tables S3, S4). The median (50% percentile) concentra-tions for As (20.59), Cu (88.84), Ni (45.43), and Zn (241.9) are generallyslightly lower than the corresponding Grade II values for As (30), Cu(100), Ni (50), and Zn (250) (Fig. 1, Table S3). 35.3% of Pb samples and33.3% of Hg samples from the examined mining areas exceed their cor-respondingGrade II values (Table S4). From this analysis, the soils in thevicinity of the examined mining areas are contaminated the least by Crand the most by Cd.

FromFig. 2, among themining areas, coal and coppermining areas ap-pear to be the least contaminated, with most of the Igeo values below 0.Meanwhile, tungsten, manganese, and lead–zinc mining areas show thehighest Igeo values for heavy metals. It is important to note that the Igeovalues for Pb and Zn from lead–zincmining areas, and for Cu from coppermining areas are higher than the Igeo values of other heavy metals fromthese mining areas. In addition, the remaining mining areas such asmulti-metal and antimony mining areas also have higher Igeo, butdue to the limited availability of studies regarding these categories, arepresentative result cannot be obtained.

Table 2 shows the class distribution of the geoaccumulation indicesfor the heavy metals, which was conducted based on the classificationsystem in Table 1. The Igeo values reveal that all of the mining areas forCr fall below class 2, with nearly 80% falling into class 0. More than60% of the examined mining areas are lower than class 1 for As, Ni,and Hg (Table 2). However, the Igeo values for Cd are above class 4 forapproximately 65% of the mining areas. The Cu, Pb, and Zn Igeo valuesvary the most, ranging from class 0 to class 6; however, most of theIgeo values for these three heavy metals lie below class 3.

As shown in Fig. 3, the average Igeo value for Cr is−0.56, placing theelement into the class of practically uncontaminated. The average As andNi Igeo values for all of the mining areas lie between 0 and 1, suggestingthat the soils be labeled as uncontaminated tomoderately contaminated.Average Igeo values for Cu, Zn, and Hg place these elements in class 2,while the index levels for Pb and Cd situate them in class 3 and class 4,respectively. Take in full, the contamination levels of these heavy metals

Fig. 1. Boxplots of the heavymetal concentrations (mg/kg) for the examinedmining areas (BVSC: Background values for soils in China; GIIEQSSC: Grade II environmental quality standardfor soils in China).

847Z. Li et al. / Science of the Total Environment 468–469 (2014) 843–853

are generally in the order of Cd N Pb N Cu/Zn/Hg N As/Ni N Cr (Table 2and Fig. 3). Similarly, Wei and Yang (2010) deduced that for heavymetals in urban soils in China, Cr and Ni appeared to cause the least con-tamination in the selected cities, whereas Cu, Pb, Zn, and Cd showed thehighest Igeo values for most cities.

According to Table 3, for the 22 provinces from which mines werecollected, Gansu, Heilongjiang, Henan, Hubei, Inner Mongolia, Shanxi,Xinjiang, and Yunnan provinces appear to be the least pollutedprovinces,with Igeo values of less than 2 for all the heavymetals. Beijing,Guizhou, Hubei, and Sichuan provinces, for which the average Igeo valueof a heavy metal is greater than 3, are viewed as moderately pollutedprovinces. Other provinces with at least one heavy metal valued at 4or 5 on the Igeo scale, or containing two or more heavy metals of at

Fig. 2. Average Igeo values of heavy metals for different types of examined mining areas.

least 3 on the scale (e.g., Guangxi province) are themost heavily pollutedprovinces. Thus, most of the examined mining areas which have higherIgeo values are located in the southern and eastern regions of China. Forexample, regarding Fujian province, the average Igeo values of theminingareas for Cd and Pb are higher than 5, and the average Igeo values of ex-amined mining areas for Zn remain higher than 3. This finding concurswith a previous study by Chen et al. (1999), which stated that soilheavy metal pollution in industrial and mining areas is prevalent insouthern China. However, due to the limited number of mines in eachprovince, further verification of these results is necessary.

3.3. Health risk assessment

3.3.1. Non-carcinogenic risk from the eight heavy metalsDermal absorption is themain exposure pathway for As, Cd, Cr, Cu, Ni

and Hg, while ingestion is amore common exposure pathway for Pb andZn. For example, in the Daxin manganese mining area, the average dailyintake of Cr through the dermal absorption pathway for adult malesreaches levels of 3.2 × 10−1 mg/kg-day, whereas the average dailyintake of Cr through the ingestion pathway for adult males is only

Table 2Class distribution of geoaccumulation index for heavy metals found in the examinedmining areas in China.

Class As Cd Cr Cu Ni Pb Zn Hg

0 51.5% 8.5% 77.5% 19.4% 45.8% 22.1% 24.6% 28.6%1 12.1% 11.9% 15.0% 22.4% 25.0% 14.7% 20.0% 33.3%2 6.1% 8.5% 7.5% 26.9% 16.7% 11.8% 23.1% 9.5%3 6.1% 5.1% 0.0% 19.4% 4.2% 13.2% 10.8% 0.0%4 6.1% 18.6% 0.0% 6.0% 4.2% 16.2% 7.7% 4.8%5 9.1% 10.2% 0.0% 3.0% 4.2% 11.8% 7.7% 9.5%6 9.1% 37.3% 0.0% 3.0% 0.0% 10.3% 6.2% 14.3%

Fig. 3. Boxplots of the Igeo values for the eight heavy metals.

Fig. 4. Average HI values (± standard deviation) for different types of the examinedmining areas.

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1.3 × 10−3 mg/kg-day. By contrast, for adult males in close proximityto this mining area, the average daily intake of Pb through ingestionand dermal absorption pathways are 1.6 × 10−1 mg/kg-day and4.2 × 10−2 mg/kg-day, respectively.

Among all the investigated heavy metals, people are most exposedto As, Cd, Ni and Pb because of their high concentrations in thesurrounding soil or low RfD values, whereas they are least exposed tothe other four heavy metals. For instance, in the surrounding area ofthe Chenzhou lead–zinc mine, the hazard quotients of As, Cd, Ni andPb account for 25.8%, 13.8%, 3.5%, and 54.0% of the entire HI value, re-spectively. By contrast, the total percentage of the other four heavymetals for the entire HI value is 0.2%. Analogously, in the surroundingarea of the Dabaoshan multi-metal mine, the total hazard quotients ofAs, Cd, Ni and Pb account for 98.6% of the full HI value.

As shown in Fig. 4, except for the coal mine, other six types of mineshold HI values that surpass 1, suggesting that these mining areas canpose non-carcinogenic risks to the surrounding populations. However,the HI values of the lead–zinc, manganese, and tungsten mines greatlyexceed 1, whereas the HI values of the copper, gold, and iron mines arejust a bit greater than 1. The health risks of the former mining areas aremore significant than the latter ones.

Table 3Average Igeo values of the examined mining areas by province.

Province As Cd Cr Cu Ni Pb Zn Hg

Anhui 3.79 5.26 −0.80 1.78 0.34 1.27 1.52Beijing −2.36 3.39 1.23 0.54 2.61 −0.56 2.73Fujian 8.53 −1.31 1.30 5.26 3.59 −1.71Gansu 1.37 −0.30 0.87 1.32 0.21 −0.16Guangdong 3.46 4.63 0.30 2.15 0.45 2.52 1.43 −0.23Guangxi 5.40 3.92 −1.06 1.21 0.93 2.92 3.05Guizhou 0.89 1.54 −0.93 1.84 3.10 2.70 0.75Heilongjiang −0.67 0.31 −0.59 −0.57 −0.59 −0.49 −0.54 0.07Henan −0.79 0.16 −0.67 −0.18 −0.21 0.28 1.74 −0.50Hubei 3.97 −0.48 1.97 0.10 1.58 0.49Hunan 3.11 4.75 −1.14 2.22 2.12 3.33 1.49 0.26Inner Mongolia −0.89 −0.37 1.98 −0.57 −0.11 1.14Jiangsu 4.64 3.89 −0.72 1.82 −0.37 2.07 1.58Jiangxi 0.66 5.70 0.00 2.33 1.85 1.34 0.85 4.28Liaoning 1.65 5.05 −1.23 0.91 −0.07 2.58 0.13 2.97Shaanxi −0.25 3.78 −0.36 −1.95 2.65 1.32 5.93Shanxi −0.51 0.12 −0.75 −0.03 −1.09Sichuan −1.88 3.84 −0.42 1.02 −0.21 1.65 1.38 2.33Tibet 7.86 2.31 0.06 1.40Xinjiang −0.70 0.64Yunnan 1.72 −2.29 1.85 0.40 0.49 −1.09Zhejiang 2.35 4.71 0.26 3.20 0.31 5.74 3.53

For every mining area, the hazard index for different populationsvaries greatly, generally in the order of children N adult females N adultmales (Table S9). Comparedwith adults, children have a higher suscepti-bility of exposure to environmental contaminants per unit body weightdue to behavioral and physiological characteristics (e.g., hand-to mouthactivities for soils, higher respiration rates per unit body weight, and in-creased gastrointestinal absorption of some substances) (DHAenC,Department of Health and Aging and enHealth Council, 2012). Similarfindings can be seen from the studies of Qu et al. (2012), Man et al.(2010), and Zota et al. (2011).

Following the results of the non-carcinogenic risk assessment, thecumulative probabilities of the hazard quotients of exposed populationsare shown in Fig. 5. For hazard quotients applied to adult males, about47% of the mining areas are greater than 1, the proportion of miningareas whose hazard quotients lie between 0.1 and 1 is about 47%, andthe percentage of hazard quotients between 1 and 10 is approximately40%. For adult females, the proportion of mining areas whose hazardquotients are greater than 1, between 0.1 and 1, and between 1 and10 are 50%, 45%, and 43%, respectively. For children, 63%, 34% and 47%are the percentages of the mining areas whose hazard quotients aregreater than 1, between 0.1 and 1, and between 1 and 10. Accordingto the above analyses, it can be concluded that mining activities pose

Fig. 5. Cumulative probabilities of non-carcinogenic risks for the three population groups.

Fig. 7. Carcinogenic risks of As for the three population groups.

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potentially high non-carcinogenic risks to the public, especially tochildren. It is also worth noting that other heavy metals not consideredin this study, such as Ag and Sb, can contribute to the estimated riskposed by these mining areas.

When mapping the non-carcinogenic risk level distributions of theexamined mining areas (Fig. 6), worst-case scenarios were adopted byapplying the non-carcinogenic risk values of children. Fig. 6 revealsthat the non-carcinogenic risk values of mining areas in the southernprovinces (e.g., Hunan and Guizhou) are higher than those of other re-gions, whereas most of the northern and western mining areas' valuesare less than 1. Liaoning province is an exception to this trend, withonemining area surpassing 10 on theHI scale, onemining area between5 and 10, and 3 mining areas between 1 and 3. These results are consis-tentwith the findings of Zhang et al. (2012), which reported that due tolead/zinc mining and smelting activities, environmental pollution andrelated health effects are concentrated in south-central and southwestChina as well as the coastal areas of Liaoning, northern Henan,Zhejiang, and Fujian, whereas low pollution levels exist in northwestChina and Inner Mongolia.

3.3.2. Carcinogenic risk of AsBecause carcinogenic slope factors are not available for the other

seven heavy metals, only the carcinogenic risk of arsenic was estimated(Table S10). For adult males and adult females, dermal absorption is theprimary pathway of exposure, whereas for children ingestion and dermalabsorption both act as common routes of exposure. As shown in Fig. 7, forthe three exposed populations, the majority of the carcinogenic riskvalues for As lies above 1 × 10−5. The carcinogenic risk values for As atsomemining areas even exceed 1 × 10−4. As awhole, these carcinogenicrisk levels are unacceptable or close to unacceptable. For every miningarea, the carcinogenic risks of As for different populations vary greatly,generally in the order of adult females N adult males N children. The rea-son that the carcinogenic risk for children is less than that for adults lies in

Fig. 6. Non-carcinogenic risk level distribution

the shorter duration of exposure for children. Average As carcinogenicrisk values (standard deviation) for antimony, coal, copper, gold, andlead–zinc mining areas are 5.8 × 10−4 (7.6 × 10−4), 1.3 × 10−5

(6.9 × 10−6), 4.7 × 10−5 (7.1 × 10−5), 1.1 × 10−5 (7.7 × 10−6), and1.7 × 10−4 (2.0 × 10−4), respectively. Accordingly, carcinogenic risklevels for As at the antimony and lead–zinc mining areas remain higherthan at the other mining areas. However, because the number of exam-inedmining areas possessing concentration data for As is limited, furtherstudies are needed to verify these conclusions. To map the carcinogenicrisk level distribution of the examined mining areas in China (Fig. 8),theAs carcinogenic risk values for adult females (theworst-case scenario)were chosen. According to Fig. 8, almost all themining areas' carcinogenicrisk values are either at unacceptable levels or nearly unacceptable levels.

of the examined mining areas in China.

Fig. 8. Distribution of carcinogenic risks of As for the examined mining areas in China.

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Thus, because of the carcinogenic hazards posed by these levels, moreattention should be paid to this health topic.

3.4. Comparison with other heavy metal soil studies

In order to compare the examined mining areas in this paper withstudies from other countries, heavy metal concentrations in mining-contaminated soils in Iran, Spain, South Korea, Vietnam, and Indiawere collated (Table 4). Mining has been or is still an important activityin the selected countries, and studies have shown that the environmentsurrounding themines is often polluted by heavymetals dispersed frommining operations in these countries. For instance, large mines in thenorthern and southern regions of Spain have operated since antiquityand have led to high metal concentrations in surrounding soils(Ordóñez et al., 2011). Currently, there are about 1000 abandonedmetal mines in South Korea, and agricultural soils surrounding thesemines have been seriously polluted with As and other heavy metals(Kim et al., 2005). In Vietnam, many metalliferous mines are locatedin mountainous areas or in the upper reaches of lowland streams, and

Table 4Comparison of heavy metal concentrations (mg/kg) observed in this study with those found in

As Cd Cr

China (72 examined mines) Mean 195.5 11.0 84.28Iran (3 examined mines) Mean 146.2 1.49Spain (16 examined mines) Mean 191.9 6.59 63.20South Korea (70 examined mines) Mean 70.08 1.99Vietnam (3 examined mines) Mean 3144 135 1501India (5 examined mines) Mean 18.62 3.82 1509China (21 urban soils) Mean 15.00 0.88 76.80China (9 urban road dusts) Mean 2.03 109.2China (12 agricultural soils) Mean 10.18 0.43 58.87

Detailed information about sources a, b, c, d, e, f, g, and h of this table can be found in supplem

frequent flooding during the rainy season causes the dikes constructedaround the mines to collapse and not function properly, resulting inheavy metal pollution flowing into low streams and farmland areas(Kien et al., 2010). From Table 4, the mean concentrations of all listedheavy metals in the 72 mining areas of China are higher than themean values of the mining areas in Iran, Spain and South Korea, exceptfor Pb and Hg. Regarding Pb and Hg, compared with the 72 examinedmining areas in China, the values of the mining areas in Iran andSpain, are higher, respectively. Furthermore, except for Cr and Ni, themean concentrations of the mining areas in India are less than that ofthe 72 examined mining areas in China. However, when accountingfor all the heavy metals, the mean concentrations of the mining areasin Vietnam are higher than those of China. This is because long-termmining operations in Vietnam have generated considerable amountsof heavy metal pollution (Ha et al., 2011). Based on the above analyses,in comparison with the mining areas of other countries, the examinedmining areas of China contain severely high levels of heavy metalcontaminated soils. As indicated in Table 4, comparisons of heavymetal pollution using other types of soil were also carried out. Except

other heavy metal soil studies.

Cu Ni Pb Zn Hg

211.9 106.6 641.3 1163 3.82 This paper88.40 1002 363.4 3.13 a

120.8 28.35 881.8 465.8 52.9 b79.09 22.00 111.1 183.2 1.12 c

271.4 2254 30,635 41,094 d63.49 1069 304.7 338.8 e99.20 99.60 61.30 133.0 0.35 f

149.6 56.75 238.7 655.9 g31.71 27.53 37.55 117.7 0.24 h

entary information.

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for Cr, themean concentrations of heavymetals found in the 72 Chinesemining areas are higher than the mean values of the 21 urban soils, 9urban road dusts, and 12 agricultural soils that were investigated inChina. This finding reflects the significance ofmining activities in gener-ating heavymetal pollution as well as the greater impact mining has onsoil pollution compared with other anthropogenic activities.

3.5. Priority control components

Based on the pollution assessment section above, the averageIgeo values for the heavy metals are generally in the order of Cd N Pb N

Cu/Zn/Hg N 1 N As/Ni N Cr. Therefore, Cd, Pb, Cu, Zn, and Hg are selectedas priority control heavymetals. According to the health risk assessment,among all the investigated heavy metals, people are most exposed to As,Cd, Ni, and Pb. From this point, As, Cd, Ni, and Pb are identified. In addi-tion, As should also be selected because the majority of the carcinogenicrisk values for As are above 1 × 10−5. As a whole, Cd, Pb, Cu, Zn, Hg, As,and Ni are selected as the priority control heavy metals. However, thecontrol of Cr should not be neglected as either its concentration is greaterthan Grade II value or the Igeo value for this metal is higher than 1 forsome mining areas (Tables S2, S6).

Based on the geoaccumulation index assessment, the tungsten,manganese, and lead–zinc mining areas reflect the highest Igeo valuesfor the metals. Moreover, based on the health risk assessment, the HIvalues for these categories of mines are higher as well. Moreover, thecarcinogenic risk levels for As at the antimony and lead–zinc miningareas are higher than at other mining areas. Therefore, the tungsten,manganese, lead–zinc, and antimony mining areas are selected as thepriority control mining areas.

Based on the aforementioned pollution assessment section, for the22 provinces in which the mining areas were studied, Anhui, Fujian,Guangdong, Guangxi, Hunan, Jiangsu, Jiangxi, Liaoning, Shaanxi, Tibet,and Zhejiang provinces appear to be themost heavily polluted provinces.According to the non-carcinogenic risk assessment, the risk values of thesouthern provinces (e.g., Hunan and Guizhou) and Liaoning province arehigher. As a result, the southern provinces and Liaoning province are se-lected as the priority control provinces.

3.6. Recommendations for management efforts

The foundation for regulating hazardousmining activities in China isweak and relatively young. At present, China faces the difficult task ofbalancing critical mineral resource development and usage with envi-ronmental protection efforts, ranging from managing extensive miningwastes, confronting shortage of advanced exploitation technology andeffective management skills, and improving low efficiency and lowresource recovery rates (MLR of China, Ministry of Land and Resourcesof China, 2012). Government regulators and mining companies musttake serious steps to address heavymetal pollution generated byminingactivities as well as the related health risks associated with industrialdevelopment. The most effective approach to mitigating soil heavymetal pollution is efficient control of the pollution sources and strictenforcement of environmental regulations, especially in terms of wastedischarge (Chen et al., 1999). In China, a growing number of small-scalemining enterprises are inflicting severe pollution damage to the en-vironment, largely due to the application of obsolete technology andinefficiency of mining operations (Zhong, 1997). Small-scale mining inChina is a significant source of mercury emissions. In particular, small-scale coal, gold, and mercury mining operations emit hundreds of tonsof mercury annually into the environment (Gunson and Veiga, 2004;P. Li et al., 2008). Emphasis should be placed on supporting sustainable,integrated approaches (i.e., regulation, training, and incentives to applyappropriate pollution control technology) for small-scale mining com-munities. Although all mining companies in China are required by lawto engage in environmental restoration efforts, overall restorationrates are very low due to weak enforcement of the relevant laws and

regulations (Li, 2006). Moreover, the remediation of polluted soils con-taining heavy metals is both technically difficult and costly. Comparedwith soil replacement and leaching practices, phytoremediation ischeaper and more effective (Wang et al., 2001; Wu, 2007; Yin et al.,2008). More diversified restoration efforts, such as nursery and habitatto wildlife, should be encouraged rather than currently restricted to ag-ricultural and forestry uses for income generation (Li et al., 2007). Spe-cial attention should be paid to the priority control components asdescribed above in order to target the biggest threats to human health.In addition, the protection of vulnerable populations, especially childrenliving in the vicinity of mining areas, should be prioritized. For example,soil ingestion rates for children living near the mining areas can be re-duced through specific measures, such as reducing out-door playingtime.

3.7. Limitations

There aremore than 9000 large andmedium-sizedmines and 26,000small-sized mines in China (Li and Jiang, 2004); therefore, the examinedmining areas in this studymay not fully represent China's overall soil pol-lution situation in the vicinity of mines. Furthermore, when obtainingthese heavy metal concentration data, some discrepancies may occurdue to variations among different studies, which may impact the consis-tency of the obtained data. However, these discrepancies are not largeenough to affect the general assessment results because the researchmethods used by selected studies are very similar to one another andare widely accepted by the scientific community. The choice of exposureparameters also plays a very important role in health risk assessment. Inorder to minimize the potential for error, the human body exposureparameters were mainly selected from relevant research conductedwithinChina,while the toxicity parameters for theheavymetalswerede-rived fromUSEPA guidelines and international researchfindings. Even so,we cannot completely eliminate the uncertainty brought about by theseexposure parameters.

4. Conclusion

Through a systematic literature review of Chinese and English data-bases, data from 72 Chinese mining areas in 22 provinces were collectedfor this study. Despite its limitations, this review gives the first descrip-tion of the overall pollution levels and health risks posed by heavymetalsin the soils of variousmining areas throughout China. Based on the resultsof the pollution and health risk assessments, it is apparent that the soilssurrounding the mining areas are seriously polluted by heavy metalsemitted frommining activities. Moreover, soil pollution by heavy metalscontinues to pose high carcinogenic and non-carcinogenic risks tothe public, especially to children and those living in the most severelypolluted regions. This review provides quantitative evidence demon-strating the critical need for strengthened mining regulations inorder to protect residents from heavy metal discharges into China'senvironment.

Acknowledgments

This research was supported by the Chinese Natural SciencesFoundation (41271014 & 41171411) and the China 863 Project(2013AA06A309). Furthermore, the support of the U.S. Fulbright Programis gratefully acknowledged.

Appendix A. Supplementary data

Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.scitotenv.2013.08.090.

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