Contamination, ecological and health risks of trace elements in soil of landfill and geothermal sites in Tibet

Journal Pre-proof Contamination, ecological and health risks of trace elements in soil of landfill and geothermal sites in Tibet

Xutong Wang, Zeng Dan, Xiaoqiang Cui, Ruixue Zhang, Shengquan Zhou, Terrence Wenga, Beibei Yan, Guanyi Chen, Qiangying Zhang, Lei Zhong PII:

S0048-9697(20)30149-2

DOI:

https://doi.org/10.1016/j.scitotenv.2020.136639

Reference:

STOTEN 136639

To appear in:

Science of the Total Environment

Received date:

14 October 2019

Revised date:

16 December 2019

Accepted date:

9 January 2020

Please cite this article as: X. Wang, Z. Dan, X. Cui, et al., Contamination, ecological and health risks of trace elements in soil of landfill and geothermal sites in Tibet, Science of the Total Environment (2020), https://doi.org/10.1016/j.scitotenv.2020.136639

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© 2020 Published by Elsevier.

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Contamination, ecological and health risks of trace elements in soil of landfill and geothermal sites in Tibet Xutong Wanga, Zeng Dana, b, Xiaoqiang Cuia, Ruixue Zhanga, Shengquan Zhoua, Terrence Wengaa, Beibei Yana, c, d, *, Guanyi Chenb, *, Qiangying Zhanga, b, Lei Zhonga School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China

b

School of Science, Tibet University, Lhasa 850012, Tibet Autonomous Region, China

c

Tianjin Engineering Research Center of Biomass-derived Gas/Oil, Tianjin 300072, China

d

Tianjin Key Lab of Biomass/Wastes Utilization, Tianjin 300350 China

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Abstract

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Due to the utilization of landfill technology and geothermal energy production in Tibet, the contamination of the soils and underground water by trace element has

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currently become a serious problem, both ecologically and to the human health point

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of view. However, relevant studies concerning this critical problem, particularly in the Tibet area has not been found. Therefore, this study investigated the soil contamination and the spatial distribution of the trace elements in the areas surrounding the Tibetan landfill sites (LS) and geothermal sites (GS) through several pollution evaluation models. In addition, the possible sources of trace elements and their potential impact on public health were also investigated. Results showed that the trace elements in soils nearby LS and GS had moderate to high contamination risk. In soils surrounding LS, mercury had the highest concentration of 0.015 mg/kg and was *

Corresponding author: [email protected] (B. Yan); [email protected] (G. Chen)

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6 times higher than the background value of 0.008 mg/kg while in GS, arsenic had the highest concentration of 66.55 mg/kg, and exceeded the soil contamination risk value of 25 mg/kg. Maizhokunggar LS was the most polluted site with an average pollution load index value of 2.95 compared to Naqu, Nyingchi, Shigatse, and Lhasa. 42% of LS were with considerable ecological risk, and all GS had low ecological risk. Both

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carcinogenic and non-carcinogenic risk for children and adults (male, female) were

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within the acceptable range. According to the source analysis, unscientific

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anthropogenic activities including accumulated MSW, industrial discharges, and

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vehicle emissions significantly contributed 51.83% to soil trace element

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contamination. Considering that Tibet is an environment-ecologically vulnerable region with very weak self-adjustment ability, accumulated municipal solid waste in

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the landfill sites should be well disposed of, and even soil remediation should be well

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implemented.

Keywords: Tibet, Soil contamination, Trace element, Ecological risk, Landfill 1.

Introduction

Tibetan Autonomous Region (Tibet) is the world’s Third Pole (Wen et al., 2019), which serves an important shelter function for the ecological security in China. It is usually called ‘Water Tower of Asia’ and supplies drinking water to over one billion residents in Asia (Sun et al., 2019). Protecting the ecological nature of this landscape is an important aspect for the sustainable development, and social stability of the Tibetans. Tibet is also regarded as the pure land and can be used as the background

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land for comparing the toxic substances in the soil with those in other places in the world (Li et al., 2018a). However, with the rapid economic development, municipal solid waste (MSW) has been produced in large quantities and is usually disposed of in less expensive landfills which result in the surrounding soils being increasingly polluted by the trace element. High concentrations of arsenic (As) ~154.5 mg/kg had

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been detected in the eastern and southwestern parts of Tibet (Sheng et al., 2012). In

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addition, concentrations of cadmium (Cd), lead (Pb), mercury (Hg), and chromium

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(Cr) over 6 to 40 times higher than the background values have been reported in the

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mining and industrial area (Li et al., 2018b). Nevertheless, soil contamination by trace

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elements in the landfill and the geothermal area has not been givenattention. Soils can accumulate various pollutants, such as, Pb, zinc (Zn), Cr, nickel (Ni),

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Selenium (Se), Cd, As, Hg, and copper (Cu). These trace elements have been listed by

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the United States Environmental Protection Agency (USEPA) as priory control pollutants due to their toxicity, bioaccumulation, and low degradability (Chen et al., 2016; Zhou et al., 2019). The human central nervous system tend to be negatively affected by long exposure to these trace element soils contamination (Khanam et al., 2019). Chen et al. (2016) reported that Pb has negative influence on blood enzymes and central nervous system. Long and high dose exposure to Zn results in low cholesterol production: Cd leads to lung cancer, pulmonary adenocarcinomas and kidney dysfunction: As exposure may result in hyperkeratosis, skin lesions, cancer of lung, bladder, and kidney: Hg can cause fatty tissues and even damage human central

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nervous system after long-term exposure: Cu, Ni, Cr and excessive amounts of Se also have adverse effects on human health when exposures exceed the tolerable dose levels (Cai et al., 2019). For these reasons, research on trace elements in soil is extremely important for human health. In Tibet, the first incineration plant was recently built in 2018, while for over the

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decades landfill was the only disposal method of MSW. MSW usually contains toxic

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and carcinogenic pollutants, and trace elements which could be leached into the soil.

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Trace elements are predicted to stay in landfill site of about 150 years with a leaching

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rate of 400 mm/yr (Adelopo et al., 2018). Besides, Yangbajain geothermal field is the

High-temperature

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largest wet steam field in China, which is also used for geothermal power generation. geothermal

water

generally

contains

trace

elements

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(González-Acevedo et al., 2018). Guo et al. (2015) reported that the As concentration

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in geothermal wastewater discharged by Yangbajain power plant was up to 3.18 mg/L. Because the Tibet population size is very low approximately 2 person/km2 and also due to less industrial activities, landfill and geothermal might be the major sources of pollution in Tibet. Therefore, it is necessary to investigate the contamination and potential risk by trace elements in landfill/ geothermal soils, and evaluate health risks of human exposed to these elements. Very few studies have reported on the soil trace element pollution severity around Tibetan plateau. Some researchers (Li et al., 2018b; Wu et al., 2016; Wu et al., 2018) have investigated the soil trace element pollution in the northeastern

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Qinghai-Tibet Plateau. Other researchers (Guo et al., 2014; Liu et al., 2019) have analyzed the metal characteristics of Yangbajain geothermal water, and evaluated the impact of Yangbajain geothermal resources on the surrounding environment. However the trace elements in soils around Yangbajain remain largely unknown. Up until now, there is still no comprehensive study that have been conducted on the trace elements

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in soils and its potential health risk to the public. Moreover, there is lack of an overall

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study on the spatial distribution of trace elements from main source point of pollution

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i.e., landfill sites in the Tibet landscape. Therefore, it is urgently needed to conduct an

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investigations on the trace elements pollution in soils around the Tibetan landfill/

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geothermal areas.

In this paper, the soil contamination properties of six representative Tibetan

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landfill sites and Yangbajain geothermal site were summarized by nine trace elements

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(Pb, Zn, Cr, Ni, Se, Cd, As, Hg, and Cu). Geoaccumulation index, pollution load index and Nemerow pollution index were used to estimate contamination of trace elements in soils. Ecological risk caused by trace elements was determined by a potential ecological risk index. Public health risks were estimated in terms of carcinogenic and non-carcinogenic risks for children, adult females, and males. Spatial distribution of trace elements was described using Ordinary Kriging (OK) methods in ArcGIS software. Furthuremore, the sources of soil trace elements were characterised by principal component analysis through SPSS software. The objective of this research was to obtain a comprehensive information of soil trace elements

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pollution in Tibetan landfill and geothermal sites, investigating potential risk and spatial distribution of trace elements. The results provide a useful reference for the environment protection, and update data for soil ecological management in Tibet. 2.

Materials and methods

2.1 Study area

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Landfill sites (LS) from Naqu, Nyingchi, Shigatse, Maizhokunggar, and Lhasa

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(two sites in Lhasa) were chosen to explore their influence on soil contamination risk

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in Tibet. Lhasa, Shigatse, Nyingchi, and Naqu are the four major cities in Tibet, which

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accounts for over 64.99% population of Tibet. Maizhokunggar County is part of

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Lhasa. The study area and sampling points are shown in Fig. S1. In each site, more than two parallel points were set to avoid system bias, which located upstream and

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downstream from the site. The sampling location and information are listed in Table

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S1, where 1-2 were from Naqu Bangor Country Landfill Site; 3-5 were from Nyingchi Jiangda County Landfill Site; 6-7 were from Shigatse Landfill Site; 8-9 were from Maizhokunggar Landfill Site; 10-11 were from Lhasa Old Landfill Site; 12-14 were from Lhasa Landfill Site; 15-19 were from Yangbajain Geothermal Site. Yangbajain geothermal site (GS) is the largest wet steam field in China (Zhang et al., 2019b). In this study, five sampling points in GS were selected according to the distribution where 15-16 were drilling hole, 17 were drainage hole, and 18-19 were drains. 2.2 Sample collection and analysis methods The top soils (20 cm depth from the surface) were collected according to the ISO

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standard 10381 (ISO/TC190, 2005). All samples were dried at 25 ºC and grounded under 100 mesh. The pH values were tested at a ratio of 1:5 (soil:water, wt%/ wt%) by digital ion meter (Xu et al., 2019b). Besides, nine elements i.e., Pb, Zn, Cr, Ni, Se, Cd, As, Hg, and Cu were considered. These trace elements are required for the soil contamination risk evaluation. During the digestion process, HNO3 (8 mL) with 8 mL

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solution of HCl-HF-HClO4 were mixed with 0.1 g soil sample. After that, the samples

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were soaked for 6 hours, and then heated until no white smoke evolved. Then, 5 mL

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of HNO3 was added. Sample concentration was accomplished by inductively coupled

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each element was 0.005 mg/kg.

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plasma optical emission spectrometry (ICP-OES), Agilent 730ES. Detection limit for

2.3 Contamination and ecological risk assessment

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Four methods including Geoaccumulation index (Igeo) (Xu et al., 2019a),

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Pollution load index (PLI) (Memoli et al., 2019), Potential ecological risk index (PERI) (Lin et al., 2019), and Nemerow pollution index (NWPI) (Martinez-Guijarro et al., 2019) were picked to assess contamination of trace elements in Tibetan soils. Igeo is mainly used to estimate the pollution of individual trace elements while PLI is usually employed to quantify the pollution degree of all elements. NWPI is chosen to comprehensively evaluate the soil quality. PERI is used to determine the potential ecological risk caused by the elements. These indicators can be calculated as followings:

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PI i 

C xi Cbi

I geo  log 2

(1)

PI i 1.5

(2) 1

PLI   PI1  PI 2 K  PI n  n

 PIi max   PIi ave 2

NWPI 

(3)

2

(4)

2 n

PERI   Txi  PI i

(5)

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i 1

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where PI stands for pollution index of trace elements; C xi and Cbi (mg/kg) represent

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concentration of each trace elements in soil and background, the background value in

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soil was extracted from Ministry of Environmental Protection China MEPC (1990); n

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represents number of the elements; Txi stands for the biological toxicity factor of each element which refers to (Hakanson, 1980). Igeo, PLI, NWPI, and PERI can be

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divided into several levels, which is shown in Table 1.

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2.4 Health risk calculation

Human health risk including carcinogenic risk (CR) and non-carcinogenic risk (NCR) exposure to trace element was assessed based on the USEPA (1986). Target residents near the contaminated areas were categorized into three groups: children, male adults and female adults based on the behavioral and physiological differences. The dose–response was separately evaluated through ingestion, inhalation, and dermal absorption as follows (USEPA, 1989): IngR  EF  ED 106 EBW  AT SA  AF  ABS  EF  ED  Csoil  106 EBW  AT

ADDing  Csoil  ADDdermal

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(6) (7)

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InhR  EF  ED PEF  EBW  AT

(8)

where ADDing, ADDdermal, and ADDinh stand for the average daily exposure dose to soil ingestion, dermal, and inhalation from soil trace elements (mg/kg-d). Other parameters and reference data used to evaluate the exposure value and potential risk are shown in Table S2.

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NCR for each element exposed by all pathways was assessed by Eq. (9) (USEPA,

ADI i RfDi

(9)

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NCR   HQ i  

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1986).

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where NCR stands for non-carcinogenic risk, HQi stands for non-carcinogenic hazard

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quotient, and RfDi (mg/kg-d) represents references dose for trace elements.

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The incremental probability of single developing cancer in a lifetime exposure to carcinogenic hazards was used to calculate CR, as shown in Eq. (10) (USEPA, 1989).

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CR   ADI i  SFi

(10)

where CR stands for the total cancer risks through three exposure pathways (unitless), and SF represents the carcinogenicity slope factor (per mg/kg-d). The detailed information of RfD and SF parameters is listed in Table S3. 2.5 Source apportionment Pearson correlation coefficient (PCC) was utilized to determine the intensity of correlation between the trace elements (Huang et al., 2018). Elements with P <0.05 (two-tailed) could share significant correlation. The inter-relationship between trace elements suggests that they might originates form similar places, or own relative

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geochemical characteristics (Zhang et al., 2018b). Principal component analysis (PCA) was adopted to narrow the complexity indices into a smaller range of comprehensive indices, which was frequently applied to analyze the pollutant sources of trace elements (Fang et al., 2019). PCA is a statistical process which could convert the associated variables to linearly non-correlated variables through orthogonal

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transformation (Tripathi and Singal, 2019). PCA and PCC analysis were performed in

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SPSS 22.0 to describe the sources of soil trace elements.

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2.6 Spatial analysis method

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The spatial distribution of soil contamination was visualized by using

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geostatistical methods (Dai et al., 2019). Values and distribution of the number of sample sites were unbiasedly estimated by calculating their relevance with

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neighboring sites. The spatial trends of trace elements concentration, Igeo, PLI, NWPI,

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and PERI were constructed using Ordinary Kriging (OK) interpolation method, and semi-variogram was executed to examine the regional variables and predict the spatial interpolation (Jin et al., 2019). All the mapping process was carried out in ArcGIS 10.2. 3.

Result and discussion

3.1 Trace elements concentration Except one site in GS, soils in LS and GS were mostly alkaline with pH between 7.08 and 9.74. The background value and trace element concentration in soil of LS and GS are shown in Table S4 and Fig. 1. The concentration of trace elements in soils

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greatly varied from 0.011 to 174 mg/kg. It can be seen that the content of Hg (0.0483 mg/kg) in Nyingchi LS and Cd (0.28 mg/kg) in Maizhokunggar LS were about 6 times higher than that in background values (0.008 and 0.044 mg/kg), and Se in Shigatse LS (0.2 mg/kg), Lhasa LS (0.19 mg/kg) reached over 5 times higher than the background value (0.035 mg/kg). Besides, the concentration of As in Maizhokunggar

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(26.5 mg/kg) and Lhasa LS (36 and 25.9 mg/kg) exceeded the soil contamination risk

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value (25 mg/kg). Among these trace elements, Cr showed the highest concentration

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~174 mg/kg in all LS, while Hg (0.011 mg/kg) was the lowest. This result is

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consistent with those found in literature. Zhang et al. (2020) found that the Cr

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concentration in Tibet was two orders of magnitude greater than the average background concentration in the Earth’s crust (100 mg/kg) (Zhang et al., 2020).

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Besides, Cr was listed in top 17 chemicals causing the greatest threat to public due to

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high teratogen and carcinogen risks (Zhang et al., 2012), and was the most abundant metals in groundwater worldwide. Therefore, more attention should be paid on the control and removal of Cr contamination, since Tibet, being at high altitude, is the original source of the seven greatest rivers in Asia. The concentration of Pb in the Tibet LS soils was very high approximately 31.01 mg/kg. This finding contradicts the results observed in other regions of the world by (Adamcova et al., 2017), who studied municipal landfill in Czech Republic, and found Pb was 5.71 mg/kg and was one of the highest concentrations of heavy metal. This was much lower than the average contents in soil of Tibet. This may be connected with the transfer of Pb

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element directly from accumulated waste as well as MSW including batteries and electronic equipment waste. MSW was the main contamination source of the trace elements discharged to the LS soils, and the pollution condition of LS was closely related to the component of the MSW. Han et al. (2015) reported that MSW in Tibet consisted of plastics (21.34%), inert waste (23.25%), kitchen waste (16.25%), glass

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(14.94%), paper (11.29%), wood (6.23%), textiles and leather (4.71%), and metals

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(1.38%). The ratio of metal was relatively low compared to other MSW components.

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Although most of the trace elements were much lower than the standard value (see

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Table S4), they generally increased to some extent compared to the local background

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values, which is consistent with the conclusion of (Zhong et al., 2018). It implied an enrichment of trace elements in the topsoil. Hg, Cd, Se, Ni, Cr, Zn, As, and Pb

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elements require more attention in the future.

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The As content of each sampling point in GS was higher than the soil contamination risk value (25-30 mg/kg). This is a common effect because of the interactions between high temperature geothermal water (generally 40-90 °C) and rocks. The random discharging of geothermal water caused severe soil contamination due to the existence of trace elements such as Pb, As, and Hg. Interestingly, all the other trace elements were below the soil contamination risk value (see Table S4). However, the concentrations of these elements were higher compared to the background value. The concentration of As (66.55 mg/kg) was 6 times greater and Cu (17.73 mg/kg) was 3 times higher than the background value (10 and 5.3 mg/kg). The

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drainage area was the most polluted area among all the sampled areas in the GS, and the pollution of trace elements increased along the downstream of the drainage hole. Comparing the contamination characteristics with landfill sites from Beijing (Li et al., 2018c) and Shanghai (Liu et al., 2013), the average concentration of As (20.37 mg/kg) and Cr (57.34 mg/kg) in Tibet were unexpectedly higher than that (11.78 and

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27.26 mg/kg) in Beijing. And the average content of Pb (31.01 mg/kg) was also

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slightly higher than that in Shanghai (25.5 mg/kg). In Shanghai and Tibet, Zn was the

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element with highest concentration, while it was different in Beijing that Pb showed

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the highest concentration. The main reason for the above-mentioned distinction was

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that the component of MSW in Tibet was quite unique. The dietary habits and religion of Tibetans differed religion with human from the plain area. Also, Tibet is far from

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high industrialization which also leads to the variation of contamination.

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The distribution of individual trace elements significantly varied with different sites (Fig. 2). According to the Ordinary Kringing method, the mapping results indicated the concentration of As, Pb, and Cd gradually decreased from center to edges of the area. While for Se, Zn, Cr, Ni, and Cu, they gradually decreased from the west-eastdirection. The distribution of Hg element showed an erratic trend. The trace elements present irregular geometric figures over the study area and no obvious regularity was found in the distribution of these elements. 3.2 Soil contamination risk Trace elements pollution was evaluated according to the four methods: Igeo, PI,

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PLI, and NWPI (see Fig. 3-7 and Table S5). Igeo values exhibited significant variation in the specific element and spatial variation as shown in Fig. 3 and 4. The spatial distribution of Igeo presented similar trend with the individual trace elements. The average Igeo values varied from -0.61 (Pb) to 11.14 (Hg), while the minimum and maximum Igeo values were -1.20 (Ni) to 11.97 (Hg), respectively. Based on Igeo

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ranking standard (Xiao et al., 2019), the average Igeo value for Hg showed extreme

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pollution, whereas in most samples the element concentration ranged from unpolluted

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to moderately polluted level. Trace elements including Cd, Zn, Ni, Cr, and As had the

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contamination degree that ranged from 47.37 to 78.57% in the samples and were

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considered to be unpolluted to moderately polluted level. This was consistent with those reported by Barbieri et al. (2014) that Igeo values of Ad and Cd fell in the range

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of 0-2 in Rome, Europe. Pb and Cu were classified as unpolluted with the percentages

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of 94.74% and 60%, respectively. Hg was found to be the most contaminated metal since 100% of soil samples in all sites were extremely polluted. Li et al. (2018b) found that only 29.92% of sampling sites showed severe contamination in the northeastern part of Tibet, which means that the landfill activities have brought non-negligible changes to the soil. It was also illustrated that the anthropogenic activities have posed irreversible changes to soil. Krcmar et al. (2018) also classified the Igeo value for Hg as strongly polluted heavy metal in landfill site of Subotica, Serbia. And Hg might pose threat through landfill leachate and probably cause harmful effects to biota.

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PI was used to identify the degree of trace element pollution compared with the background value (Table S5). The trace elements in LS can be ranked according to their PI in decreasing order of: Hg> Se> 3> Ni> Cd> Cr> Zn> As> 2> Pb, while the order in GS was As> 3> Cu> Zn> Ni> Cr> 1> Pb. The average value of Hg (PI=3.70) and Se (PI=3.27) in LS exhibited high contamination level, also there was a major

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enrichment of As in GS (PI=5.0). Ni, Cd, Zn, Cr, and As were suggested as

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moderately polluted level in LS. However, Pb in LS, and Cu, Cr, Zn, and Ni in GS

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were observed to have a low contamination level, with Pb in GS showing no pollution.

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Dong et al. (2018) have investigated the heavy metal contamination in top soil of

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Chongqing municipality, China. They indicated that PI values of As, Cu, Zn, Ni, Pb, and Cr were betweern 0.99 and 1.21, while the values of Hg and Cd were a little bit

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higher with 1.920 and 2.485, separately. Tian et al. (2017) studied the trace element

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contamination in soil of Jiangsu province, China. They suggested that PI values of the trace elements decreased in the order: Cd> 2> Pb> Zn> Cu> Cr> Ni. Compared with the soils in Chongqing municipality and Jiangsu province, the PIs of Tibet were relatively high. Although trace element concentrations were relatively low, and most of them were within the soil contamination risk value in the Tibet area, the LS and GS nearby soils have been seriously polluted compared with the background value. It implied that the trace element contamination might present serious threat to the public health and should not be ignored in Tibet. PLI also provided considerable details to evaluate the contamination degree of

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trace elements. Average PLI values of LS and GS were 2.40 and 1.57, respectively. On the basis of PLI ranking criteria, 8 sampling sites (42.11%) showed moderate level of pollution while 11 sites (57.89%) were in the high level of pollution as shown in Fig. 5a. Among them, 80% of GS samples showed moderate level of pollution, and the rest was with high level of pollution. It can also be seen that 71.43% of LS sampling sites

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showed high level of pollution, which including Shigatse, Maizhokunggar, Lhasa old

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and new LS. The most polluted area was the Maizhokunggar LS with average PLI of

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2.95. Of all the trace elements, elements including Hg, As, Cr, Ni, and Se were the

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main pollution contributors. According to the Kriging prediction results, the southern

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and western area of Tibet had a higher contamination level of trace elements, but the pattern gradually decreased from the southern to the northern parts and from the

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western to the eastern parts of Tibet (Fig. 5b).

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The NWPI of all samples were unexpectedly high, varying from 2.13 to 6.4 (see, Fig. 6a). It is clearly seen that 78.94% of the area was severely polluted while 21.05% was moderately polluted. The highest NWPI value was found in the samples collected from Naqu LS, with each LS having at least one sample with NWPI> 3. Elements including Cr, Hg, Cd, and Se greatly contributed to the pollution of LS, while in GS, As pollution was severely high. As shown in Fig. 6, the NWPI was relatively high in the center part and it gradually decreased from the western to the eastern area. In conclusion, the presented data and analysis on the LS and GS soils presented potential risks to soil quality from trace element pollutants, and consequently certain protection

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and remediation measures are needed to restore the original standard. Also, Tibet requires more effective treatment of MSW to prevent the environmental problems by landfill. Future monitoring and pollution control of geothermal sites are also of great importance. Based on the Igeo assessment, Hg showed extreme pollution, whereas the rest

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elements were classified as unpolluted to moderately polluted level. PI indicated that

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Hg and Se exhibited high contamination level separately in LS and GS, Ni, Cd, Zn, Cr

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were identified as moderately polluted level in LS. PLI also provided considerable

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details about the contamination degree, results showed that the most polluted LS was

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Maizhokunggar with average value of 2.95. And NWPI of all samples were unexpectedly high, and the highest one was from Naqu LS. PLI and NWPI evaluation

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and Igeo.

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has narrowed the pollution scope by weakening the extreme results compared to PI

3.3 Soil ecological risk

PERI, not only included the risk level of the individual element, but also summed up them comprehensively. PERI of trace elements varied from 46.72 to 482.43 as can be seen in Fig. 7a. The PERI of 5 samples in GS were identified as low risk. However, it was noted that 42% of LS had considerable risk and 58% of LS showed moderate risk. Five LS in Nyingchi, Shigatse, Maizhokunggar, Lhasa old LS, and Lhasa LS were within the ecological risk.In all the LS, Hg contributed over 50% of the ecological risks, while Cd presented around 30%. As element accounted for

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~65% to the ecological risks in GS. Compared with the results of Li et al. (2018b), Cd accounted for a lower percentage than that in soils of northeastern Qinghai-Tibet Plateau. They concluded that Cd dominantly contributed to the ecological risks with range of 50-77% in 22 sites, which was mainly because some mining activities existed in that area. Other trace elements such as Cr and Pb insignificantly contributed to the

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ecological risks. The spatial distribution of PERI showed large differences (Fig. 7b).

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In the center part, the two circular distribution showed high and low contamination

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which gradually decreased to the edges.The eastern part had low contamination levels.

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Overally, the soils in landfill and geothermal sites of Tibet are contaminated and

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showed some ecological risks. It was established that higher ecological risk was due to elevated concentrations of Hg and As elements.

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3.4 Health risk assessment

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3.4.1 Non-carcinogenic risks (NCR) The assessment results of NCR to children,and male adults, and female adults exposed to trace elements in Tibetan LS and GS soils are shown in Table 2. The average HQ values for children via ingestion of Hg, As, Pb, Cr, Cu, Se, Zn, and Ni were 8.80E-11, 1.17E-10, 6.28E-08, 1.69E-07, 2.80E-11, 1.03E-09, 1.53E-11, 1.58E-10, and 7.76E-10, respectively; while that via dermal absorption were 1.15E-06, 1.36E-08, 4.39E-06, 2.36E-06, 2.00E-07, 0, 8.11E-08, 7.36E-09, and 1.58E-05, respectively; and via inhalation were 3.60E-07, 5.09E-08, 1.47E-05, 0, 3.43E-04, 0, 3.14E-07, 3.69E-08, and 1.76E-07, separately. It showed that three exposure pathways

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of trace elements for children reduced in the following sequence: inhalation> dermal contact> ingestion. Besides, HQ values for male and female adults have the same tendency of exposure pathways as compared to that for children. For most of the trace elements, the contribution of HQinh to NCR was in the order of: adult male (95.48%) > adult female (94.22%) > children (93.72%), indicating that inhalation was

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the main exposure pathway to threaten public health.

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As shown in Table 2, the NCR values of trace elements for children, male adults

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and female adults decreased in the sequence of Cr> As> Ni> Pb> Cd> Se> Hg>

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Zn >Cu, except the NCR of Hg and Zn was approximate in female adults. The

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children, male adults, and female adults were mostly exposed to Cr element with the contribution of 89.56%, 91.50%, and 89.93%. And each NCR value for trace elements

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was far below 1, implying that there was little NCR for children or adults. The total

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NCR values were in the sequence of children (3.83E-04)> adult males (3.53E-04)> adult females (2.78E-04). Thus children had greater exposure to NCR of soil trace element than adults. Wei et al. (2015) suggested that this was mainly because of children’s pica behavior, finger sucking and higher respiration rates. 3.4.2 Carcinogenic risks The results of CR for Cd, Ni, As, and Cr are shown in Table 2, Hg, Pb, Se, Cu and Zn elements were excluded because of lacking their carcinogenicity slope factors. The CR values in the soils were 3.89E-11 (Cd), 1.83E-08 (As), 1.26E-07 (Cr), and 1.39E-07 (Ni) for children, and 1.42E-10 (Cd), 6.58E-08 (As), 4.38E-07(Cr), and

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3.49E-07 (Ni) for adult male and 1.10E-10 (Cd), 5.17E-08(As), 3.53E-07(Cr), and 3.69E-07 (Ni) for adult female. Unlike the NCR, CR values for children was lower than that for adults, which was in the sequence of adult males (8.53E-07)> adult females (7.74E-07)> children (2.84E-07). And the CR values through dermal contact and inhalation in children and adult were much higher (104 times) than that through

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ingestion pathway. So, the effect on ingestion of soil particles is negligible and quite

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unlikely to pose any significant risk. Except for male adult, children and female adult

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are under higher chronic health risks through dermal than inhalation pathway. By

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calculation, all the CR of Cd, As, Cr, and Ni for children, adult male and female

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through three pathways were lower than 10-7, indicating that CR of the above-mentioned trace elements could be ignored. In general, the values for both

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NCR and CR assessed for children, and adults were all within the acceptable limits,

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showing that there were no severe adverse effects on human’s health. 3.5 Possible sources of trace elements in soil PCC and PCA (Cao et al., 2017; Zhang et al., 2019a) were employed to establish the source and correlation coefficient of trace elements in soils, and the results of Pearson correlation matrix are presented in Table 3. The results showed that Zn, Ni, Se, Cd, and Hg were positively correlated with each other, with r > 0.60. Thus, they possibly had homologous characteristics (Zhang et al., 2018a) and might have originated from same anthropogenic source. Hg was positively correlated with Zn, Cd, and Ni (P≤0.01), showing that Hg may be linked with numerous wastes. Se

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was exceptionally positively correlated with Zn, Ni, and Hg. Cu was also correlated to As, suggesting that they were originating from the same sources in each group. Leal-Acosta et al. (2018) suggested that the geothermal fluids in Yangbajain were rich in latent toxic elements such as As, Hg and Cd. Therefore, Hg and Cd might originate from the GS waste water. Besides, Cu was negatively correlated to Cd, Hg,

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and Se, and Cr was not associated with other trace elements. Luo et al. (2012) have

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reported that Cr and Ni might be influenced by natural processes for instance,

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weathering of granitic rocks, especially Tibet as the ‘roof of the world’ contributed

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more background concentrations through parent material and pedogenesis.

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As shown in Table 4, four principal components (PCs) with eigenvalues> 1 were extracted, which clarified 87.71% of the total variance, with relative contribution of

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51.832%, 14.534%, 11.017%, and 10.322%. These components effectively explained

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8.77 (5.183+1.453+1.102+1.032, eigenvalues) variables with higher representative levels. It can be seen that Pb, Cr, Ni, As, Hg, and pH contributed more to PC1, while PC2 was dominated by Cd PC3 was heavily loaded with Cr, and PC4 was affected by Se. Ma et al. (2018) reported that the common composition of batteries, waste tire, plastic and inks in MSW contributed large quantities of Zn, and Cd. As was an elemental marker of coal combustion, and McIlwaine et al. (2017) indicated that As was related with anthropogenic waste, such as sewage sludge and industrial discharges. Ni and Cr are usually introduced by vehicle emissions, and parent material (Zhang et al., 2018a). Thus, PC1 load was regarded as unscientific anthropogenic

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activities. Guo and Wang (2009) found that the main trace elements were Cd, and Pb in the geothermal discharge water at Yangbajain. Therefore, PC2 load might mainly have originated from geothermal draining. Consistent with PCCs, Cr was the only effect factor for PC3, and Cr was not associated with other trace elements. Therefore, PC3 load mainly related to the natural processes including parent rocks and sediment

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accumulation. It was suspected that Se may be brought by mutual reactions of MSW

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and groundwater, particularly after a strong downpour or resident groundwater (Yusof

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et al., 1999). Thus, PC4 load was relevant to the landfill leachate. In addition, the

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structure and source of trace elements in soil might also link with complex

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environmental conditions, such as soil loading, MSW size, and deposition or drainage rate. In conclusion, unscientific anthropogenic activities (i.e., intensive waste disposal

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activities, leachate and geothermal waste water discharge, automobile exhausts) might

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be the major factors of influencing the trace element contents in soil. The complex association among those factors might cause the enrichment of trace elements. 4.

Conclusion

This study analyzed the soil contamination, ecological risk, and their spatial distribution in landfill and geothermal sites in Tibet. Results showed that trace elements in LS and GS soils were under moderate to high contamination risk. Cr had the highest concentration in all LS, and Hg caused extreme pollution. As element in all GS samples exceeded the soil contamination risk level, and increased along the downstream of drainage hole. The concentration of As and Cr in Tibet LS were even

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higher than in Beijing LS, and the PI value of As and Cr in Tibet LS were both higher than that in Chongqing LS. According to the source analysis, unscientific anthropogenic activities including accumulated MSW, industrial discharges, and vehicle emissions significantly contributed 51.83% to soil contamination. In summary, considerable pollution of trace elements was detected in soils of

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landfill and geothermal sites. Soil ecological management is urgently and highly

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recommended. Considering that Tibet is an environment-ecologically vulnerable

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region with very weak self-adjustment ability, accumulated MSW in the landfill sites

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should be well disposed, and even soil remediation should be well implemented. This

Acknowledgements

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study provides a reliable reference for soil remediation in Tibet.

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This work was financially supported by Natural Science Foundation of China

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(No. 51676138 and No. 51878557) and Key Science and Technology Projects of Tibet Autonomous Region (No. Z2016C01G01106).

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Journal Pre-proof Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

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Figure Captions Fig. 1 Trace element contents in soils of LS and GS Fig. 2 Spatial distribution of individual trace element in LS and GS. Fig. 3 Box-plots of Igeo in soil of a) landfill and b) geothermal sites. Fig. 4 Spatial distribution of Igeo for soil trace elements.

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Fig. 5 a) PLI and b) spatial distribution of PLI for soil trace elements. Fig. 6 a) NWPI and b) spatial distribution of NWPI for soil trace elements.

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Fig. 7 a) PERI and b) spatial distribution of PERI in LS and GS.

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Fig. 1. Trace element contents in soils of LS and GS. Note: 1-2, Naqu Bangor Country Landfill Site; 3-5, Nyingchi Jiangda County Landfill Site; 6-7, Shigatse Landfill Site; 8-9, Maizhokunggar Landfill Site; 10-11, Lhasa Old Landfill Site Ⅰ;

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12-14, Lhasa landfill site Ⅱ; 15-19, Yangbajain geothermal site.

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Fig. 2. Spatial distribution of individual trace element in LS and GS.

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Fig. 3. Box-plots of Igeo in soil of a) landfill and b) geothermal sites.

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n r u

r P

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Fig. 4. Spatial distribution of Igeo for soil trace elements.

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n r u

r P

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Fig. 5. a) PLI and b) spatial distribution of PLI for soil trace elements.

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Fig. 6. a) NWPI and b) spatial distribution of NWPI for soil trace elements.

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Fig. 7. a) PERI and b) spatial distribution of PERI in LS and GS.

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Table Captions Table 1 Assessment methods of Igeo, PLI, PERI, and NWPI. Table 2 NCR and CR to adults and children through three pathways and trace elements. Table 3 PCC and significant level between trace metals in soils.

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Table 4 Rotated component matrix of each trace metals.

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Table 1 Assessment methods of Igeo, PLI, PERI, and NWPI. Igeo

PLI

PERI

NWPI

Ⅰ

<0: unpolluted

0-1: Low level

≤150: Low risk

≤0.7: Safety

Ⅱ

0-1: unpolluted-

1-2:

150-300:

0.7-1.0:

moderately polluted

Moderate level

Moderate risk

Precaution

1-2:

2-5:

300-600:

1.0-2.0:

moderately polluted

High level

Considerable risk

Slightly pollution

2-3: moderately-

>5: Extremely

≥600:

2.0-3.0:

heavily polluted

high level

High risk

Moderately polluted

3-4: heavily polluted

Ⅵ

4-5: heavily- extremely polluted

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>5: extremely polluted

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Ⅶ

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Ⅴ

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Classification

>3: Severely polluted

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Table 2 NCR and CR to adults and children through three pathways and trace elements. NCR Children

CR

Male adult

Female

Children

Male adult

adult

2.34E-07

1.46E-07

8.15E-08

1.02E-11

3.40E-11

3.99E-11

ADDdermal

2.40E-05

1.54E-05

1.64E-05

1.60E-07

3.99E-07

4.24E-07

ADDinh

3.58E-04

3.38E-04

2.61E-04

1.24E-07

4.54E-07

3.50E-07

Cd

1.76E-06

1.26E-06

1.22E-06

3.89E-11

1.42E-10

1.10E-10

Hg

7.54E-08

6.62E-08

5.41E-08

-

-

-

As

1.91E-05

1.67E-05

1.37E-05

1.83E-08

6.58E-08

5.17E-08

Pb

2.53E-06

1.62E-06

1.64E-06

-

-

-

Cr

3.43E-04

3.23E-04

2.50E-04

1.26E-07

4.38E-07

3.53E-07

Cu

7.18E-09

4.47E-09

3.80E-09

-

-

-

Ni

1.60E-05

1.03E-05

1.09E-05

1.39E-07

3.49E-07

3.69E-07

Zn

4.44E-08

3.96E-08

5.42E-08

-

-

-

Se

4.61E-07

4.06E-07

3.31E-07

-

-

-

Total

3.83E-04

3.53E-04

2.78E-04

2.84E-07

8.53E-07

7.74E-07

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Note: -: not applicable.

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ADDing

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adult

Female

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Table 3 PCC and significant level between trace metals in soils. Pb

Zn

Cr

Ni

Cd

As

Hg

Pb

1

0.091

0.885

0.683

0.001

0.648

0.080

Zn

0.398

1

0.584

0

0.002

0.025

0

Cr

-0.036

0.134

1

0.276

0.411

0.130

0.263

1

0.035

0.062

Ni Cd As Hg Se

0.100 **

0.690

-0.112 0.412 0.229

**

0.871

**

0.672

-0.511

*

**

0.808

**

0.726

0.200

0.485

*

-0.360

-0.436

0.247

0.750

**

0.793

**

0.164

*

-0.351

-0.432

-0.289

-0.130

Cu

-0.237

-0.483

pH

-0.028

-0.193

0.736

-0.558*

0.631

**

*

l a

n r u

r P

0.053

Note: Right upper part were significant levels, and left lower part were correlation coefficients. ** Two-tailed correlation was significant at the 0.01 level.

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* Two-tailed correlation was significant at the 0.05 level.

1

**

-0.706

pH

0.346

0.328

0.910

0

0.036

0.430

ro

0.502

0.141

0.229

0

0.065

0.595

0

0.004

0.001

0.828

0.013

0.044

0.000

0.196

1

0

0.001

0.770

0.005

0.691

1

0.795

-0.064

1

0.308

0.007

**

**

Cu

p e

1 -0.600

Se

-0.466 0.852

**

0.311

0

0.792

f o

**

-0.698

**

-0.072

1 -0.611

**

0.098

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PC1

PC2

PC3

PC4

Pb

0.868

0.082

0.224

0.335

Zn

0.342

-0.663

-0.158

-0.156

Cr

0.799

-0.07

0.516

0.191

Ni

0.85

0.275

-0.354

-0.031

Cd

-0.741

0.4

0.23

0.255

As

0.918

0.091

0.09

0.053

Hg

0.839

0.162

0.355

-0.085

Se

-0.804

0.101

0.214

0.489

-0.12

0.69

0.19

-0.635

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Factors

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Table 4 Rotated component matrix for soil trace metals.

Cu

0.868

0.082

0.224

0.335

5.183

1.453

1.102

1.032

% of variance

51.832

14.534

11.017

10.322

Cumulative%

51.832

66.366

77.383

87.705

pH

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Eigenvalues

Note: Extraction method: principal component analysis; PCA loadings N>0.4 are shown in bold.

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Highlights •Trace elements in Tibet landfill soil were with moderate to high contamination risk. •Hg, As were separately the most polluted elements in landfill and geothermal sites. •42% of landfill sites were with considerable ecological risk. •Health risks of trace element pollution were within the acceptable range.

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•MSW, industrial discharges, vehicle emissions contributed 51.83% to soil pollution.

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