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Xu M, He R, Cui G, Wei J, Li X, Xie Y, Shi P. Quantitative tracing the sources and human risk assessment of complex soil pollution in an industrial park. ENVIRONMENTAL RESEARCH 2024; 257:119185. [PMID: 38810828 DOI: 10.1016/j.envres.2024.119185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 04/30/2024] [Accepted: 05/18/2024] [Indexed: 05/31/2024]
Abstract
Pollution in industrial parks has long been characterized by complex pollution sources and difficulties in identifying pollutant origins. This study focuses on a typical industrial park consisting of 11 factories (F1-F11) including organic pigment, inorganic pigment, and chemical factories in Hunan Province, China, here, a total of 327 sample points were surveyed. Eight pollutants (Mn, Cd, As, Co, NH3-N, l, 1,2-Trichloroethane, chlorobenzene, and petroleum hydrocarbons) were classified as contaminants of concern (COCs). This study assessed the contributions of driving factors to the distribution of COCs in the soil. Pollutant source apportionment was conducted using positive matrix factorization (PMF) and random forest (RF). The results revealed that the main factors driving pollution are groundwater migration, non-compliant emissions, leaks during production, and interactions among pollutants. The primary pollution sources were four chemical factories and an inorganic pigment factory. Source 5 demonstrates significant correlations with TCA (29.6%), CB (30%), and As (31.6%). Two chemical factories (F7 and F10) are the most significant pollution source with a risk assessment contribution rate of more than 60%. The present study sheds some light on the contamination characteristics, source apportionment and source-health risk assessment of COCs in industrial park. By utilizing the proposed research framework, decision-makers can effectively prioritize and address identified pollution sources.
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Affiliation(s)
- Minke Xu
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China; School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Ruicheng He
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China
| | - Guannan Cui
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China
| | - Jinjin Wei
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China; School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Xin Li
- School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China; Department of Environment, College of Environment and Resources, Xiangtan University, Xiangtan, Hunan, 411105, China
| | - Yunfeng Xie
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China.
| | - Peili Shi
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China.
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Wang M, Gou Z, Zhao W, Qu Y, Chen Y, Sun Y, Cai Y, Ma J. Predictive analysis and risk assessment of potentially toxic elements in Beijing gas station soils using machine learning and two-dimensional Monte Carlo simulations. JOURNAL OF HAZARDOUS MATERIALS 2024; 477:135393. [PMID: 39106722 DOI: 10.1016/j.jhazmat.2024.135393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Revised: 06/27/2024] [Accepted: 07/30/2024] [Indexed: 08/09/2024]
Abstract
Gas stations not only serve as sites for oil storage and refueling but also as locations where vehicles frequently brake, significantly enriching the surrounding soil with potentially toxic elements (PTEs). Herein, 117 topsoil samples from gas stations were collected in Beijing to explore the impact of gas stations on PTE accumulation. The analysis revealed that the average Pollution Index (PI) values for Cd, Hg, Pb, Cu, and Zn in the soil samples all exceeded 1. The random forest (RF) model, achieving an AUC score of 0.95, was employed to predict PTE pollution at 372 unsampled gas stations. Additionally, a Positive Matrix Factorization (PMF) model indicated that gas station operations and vehicle emissions were responsible for 70 % of the lead (Pb) enrichment. Probabilistic health risk assessments showed that the carcinogenic risk (CR) and noncarcinogenic risk (NCR) for PTE pollution to adult females were the highest, at 0.451 and 1.61E-05 respectively, but still within acceptable levels. For adult males at contaminated sites, the Pb-associated CR and NCR were approximately twice as high as those at uncontaminated sites, with increases of 107 % and 81 %, respectively. This study provides new insights for managing pollution caused by gas stations.
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Affiliation(s)
- Meiying Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Zilun Gou
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Wenhao Zhao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yajing Qu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Ying Chen
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yi Sun
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yuxuan Cai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jin Ma
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
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3
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Li JL, Gan CD, Du XY, Yuan XY, Zhong WL, Yang MQ, Liu R, Li XY, Wang H, Liao YL, Wang Z, Xu MC, Yang JY. Distribution, risk evaluation, and source allocation of cesium and strontium in surface soil in a mining city. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:270. [PMID: 38954122 DOI: 10.1007/s10653-024-02046-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/21/2024] [Indexed: 07/04/2024]
Abstract
Radioactive nuclides cesium (Cs) and strontium (Sr) possess long half-lives, with 135Cs at approximately 2.3 million years and 87Sr at about 49 billion years. Their persistent accumulation can result in long-lasting radioactive contamination of soil ecosystems. This study employed geo-accumulation index (Igeo), pollution load index (PLI), potential ecological risk index (PEPI), health risk assessment model (HRA), and Monte Carlo simulation to evaluate the pollution and health risks of Cs and Sr in the surface soil of different functional areas in a typical mining city in China. Positive matrix factorization (PMF) model was used to elucidate the potential sources of Cs and Sr and the respective contribution rates of natural and anthropogenic sources. The findings indicate that soils in the mining area exhibited significantly higher levels of Cs and Sr pollution compared to smelting factory area, agricultural area, and urban residential area. Strontium did not pose a potential ecological risk in any studied functional area. The non-carcinogenic health risk of Sr to the human body in the study area was relatively low. Because of the lack of parameters for Cs, the potential ecological and human health risks of Cs was not calculated. The primary source of Cs in the soil was identified as the parent material from which the soil developed, while Sr mainly originated from associated contamination caused by mining activities. This research provides data for the control of Cs and Sr pollution in the surface soil of mining city.
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Affiliation(s)
- Jia-Li Li
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
- Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, 644000, China
| | - Chun-Dan Gan
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
- Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, 644000, China
| | - Xin-Yue Du
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
- Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, 644000, China
| | - Xue-Ying Yuan
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
| | - Wen-Lin Zhong
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
- Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, 644000, China
| | - Meng-Qi Yang
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
| | - Rui Liu
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
- Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, 644000, China
| | - Xiao-Yu Li
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
- Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, 644000, China
| | - Hao Wang
- Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, 644000, China
- College of Forestry, Northeast Forestry University, Haerbin, 150000, China
| | - Yu-Liang Liao
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
| | - Zheng Wang
- College of Civil Engineering, Northwest Minzu University, Lanzhou, 730000, China
| | - Mu-Cheng Xu
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
| | - Jin-Yan Yang
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China.
- Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, 644000, China.
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4
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Wang M, Yu P, Tong Z, Shao X, Peng J, Hamid Y, Huang Y. A Modified Model for Quantitative Heavy Metal Source Apportionment and Pollution Pathway Identification. TOXICS 2024; 12:382. [PMID: 38922062 PMCID: PMC11209494 DOI: 10.3390/toxics12060382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 05/14/2024] [Accepted: 05/17/2024] [Indexed: 06/27/2024]
Abstract
Current source apportionment models have successfully identified emission sources and quantified their contributions. However, when being utilized for heavy metal source apportion in soil, their accuracy needs to be improved, regarding migration patterns. Therefore, this work intended to improve the pre-existing principal component analysis and multiple linear regression with distance (PCA-MLRD) model to effectively locate pollution pathways (traffic emissions, irrigation water, atmospheric depositions, etc.) and achieve a more precise quantification. The dataset of soil heavy metals was collected from a typical area in the Chang-Zhu-Tan region, Hunan, China in 2021. The identification of the contribution of soil parent material was accomplished through enrichment factors and crustal reference elements. Meanwhile, the anthropogenic emission was identified with principal component analysis and GeoDetector. GeoDetector was used to accurately point to the pollution source from a spatial differentiation perspective. Subsequently, the pollution pathways linked to the identified sources were determined. Non-metal manufacturing factories were found to be significant anthropogenic sources of local soil contamination, mainly through rivers and atmospheric deposition. Furthermore, the influence of irrigation water on heavy metals showed a more pronounced effect within a distance of 1000 m, became weaker after that, and then gradually disappeared. This model may offer improved technical guidance for practical production and the management of soil heavy metal contamination.
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Affiliation(s)
- Maodi Wang
- National Engineering Laboratory of High Efficient Use on Soil and Fertilizer, College of Resources, Hunan Agricultural University, Changsha 410128, China; (M.W.); (P.Y.); (Z.T.); (X.S.); (J.P.)
| | - Pengyue Yu
- National Engineering Laboratory of High Efficient Use on Soil and Fertilizer, College of Resources, Hunan Agricultural University, Changsha 410128, China; (M.W.); (P.Y.); (Z.T.); (X.S.); (J.P.)
| | - Zhenglong Tong
- National Engineering Laboratory of High Efficient Use on Soil and Fertilizer, College of Resources, Hunan Agricultural University, Changsha 410128, China; (M.W.); (P.Y.); (Z.T.); (X.S.); (J.P.)
| | - Xingyuan Shao
- National Engineering Laboratory of High Efficient Use on Soil and Fertilizer, College of Resources, Hunan Agricultural University, Changsha 410128, China; (M.W.); (P.Y.); (Z.T.); (X.S.); (J.P.)
| | - Jianwei Peng
- National Engineering Laboratory of High Efficient Use on Soil and Fertilizer, College of Resources, Hunan Agricultural University, Changsha 410128, China; (M.W.); (P.Y.); (Z.T.); (X.S.); (J.P.)
| | - Yasir Hamid
- Ministry of Education (MOE) Key Lab of Environment, Remediation and Ecological Health, College of Environmental and Resources Science, Zhejiang University, Hangzhou 310058, China;
| | - Ying Huang
- National Engineering Laboratory of High Efficient Use on Soil and Fertilizer, College of Resources, Hunan Agricultural University, Changsha 410128, China; (M.W.); (P.Y.); (Z.T.); (X.S.); (J.P.)
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Xu D, Wang Z, Tan X, Xu H, Zhu D, Shen R, Ding K, Li H, Xiang L, Yang Z. Integrated assessment of the pollution and risk of heavy metals in soils near chemical industry parks along the middle Yangtze River. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170431. [PMID: 38301773 DOI: 10.1016/j.scitotenv.2024.170431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 01/13/2024] [Accepted: 01/23/2024] [Indexed: 02/03/2024]
Abstract
Industrialization in riparian areas of critical rivers has caused significant environmental and health impacts. Taking eight industrial parks along the middle Yangtze River as examples, this study proposes a multiple-criteria approach to investigate soil heavy metal pollution and associated ecological and health risks posed by industrial activities. Aiming at seven heavy metals, the results show that nickel (Ni), cadmium (Cd), and copper (Cu) exhibited the most significant accumulation above background levels. The comprehensive findings from Pearson correlation analysis, cluster analysis, principal component analysis, and industrial investigation uncover the primary sources of Cd, arsenic (As), mercury (Hg), and lead (Pb) to be chemical processing, while Ni and chromium (Cr) are predominantly derived from mechanical and electrical equipment manufacturing. In contrast, Cu exhibits a broad range of origins across various industrial processes. Soil heavy metals can cause serious ecological and carcinogenic health risks, of which Cd and Hg contribute to >70 % of the total ecological risk, and As contributes over 80 % of the total health risk. This study highlights the importance of employing multiple mathematical and statistical models in determining and evaluating environmental hazards, and may aid in planning the environmental remediation engineering and optimizing the industry standards.
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Affiliation(s)
- Dong Xu
- Hubei Provincial Academy of Eco-Environmental Sciences, Wuhan 430074, China
| | - Zejun Wang
- School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan 430072, China.
| | - Xiaoyu Tan
- School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan 430072, China
| | - Haohan Xu
- Hubei Provincial Academy of Eco-Environmental Sciences, Wuhan 430074, China
| | - Dongbo Zhu
- Hubei Provincial Academy of Eco-Environmental Sciences, Wuhan 430074, China
| | - Ruili Shen
- Hubei Provincial Academy of Eco-Environmental Sciences, Wuhan 430074, China
| | - Kang Ding
- Hubei Provincial Academy of Eco-Environmental Sciences, Wuhan 430074, China
| | - Hongcheng Li
- Hubei Provincial Academy of Eco-Environmental Sciences, Wuhan 430074, China
| | - Luojing Xiang
- Hubei Provincial Academy of Eco-Environmental Sciences, Wuhan 430074, China.
| | - Zhibing Yang
- State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei 430072, China
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6
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Zeng W, Wan X, Lei M, Chen T. Intercropping of Pteris vittata and maize on multimetal contaminated soil can achieve remediation and safe agricultural production. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 915:170074. [PMID: 38218467 DOI: 10.1016/j.scitotenv.2024.170074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/07/2024] [Accepted: 01/08/2024] [Indexed: 01/15/2024]
Abstract
Soil contamination by multimetals is widespread. Hyperaccumulator-crop intercropping has been confirmed to be an effective method for arsenic (As)- or cadmium (Cd)-contaminated soil that can achieve soil cleanup and agricultural production. However, the influencing factors and response of hyperaccumulator-crop intercropping to multimetal-contaminated soil are still unclear. In this study, intercropping of the As hyperaccumulator Pteris vittata and maize was conducted on two typical types of multimetal-contaminated soil, namely, Soil A contaminated by As, Cd, and lead (Pb) and Soil B contaminated by As, Cd, and chromium (Cr). Intercropping reduced As, Cd, and Pb in the maize grains by 60 %, 66.7 %, and 20.4 %, respectively. The concentrations of As, Cd, Pb, and Cr in P. vittata increased by 314 %, 300 %, 447.3 %, and 232.6 %, respectively, relative to their concentrations in the monoculture plants. Two soils with different levels of contamination showed that higher heavy metal content might diminish the ability of intercropping to reduce soil heavy metal risk. No notable difference in soil microbial diversity was found between the intercropped and monocultured plants. The composition of microbial communities of intercropping groups were more similar to those of monoculture P. vittata on two different soils (Soils A and B). An imbalance between the amount of As taken up by the plants and the reduction in As in the soil was observed, and this imbalance may be related to watering, As leaching, and heterogeneity of soil As distribution. Reducing the risk resulting from As leaching and enhancing the efficiency of phytoextraction should be emphasized in remediation practices.
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Affiliation(s)
- Weibin Zeng
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100089, China
| | - Xiaoming Wan
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100089, China.
| | - Mei Lei
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100089, China
| | - Tongbin Chen
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100089, China
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Huang X, Li X, Zheng L, Zhang Y, Sun L, Feng Y, Du J, Lu X, Wang G. Comprehensive assessment of health and ecological risk of cadmium in agricultural soils across China: A tiered framework. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133111. [PMID: 38043426 DOI: 10.1016/j.jhazmat.2023.133111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/12/2023] [Accepted: 11/26/2023] [Indexed: 12/05/2023]
Abstract
Soil cadmium (Cd) contamination has been increasingly serious in agricultural land across China, posing unexpected risks to human health concerning crop safety and terrestrial ecosystems. This study collected Cd concentration data from 3388 soil sites in agricultural regions. To assess the Cd risk to crop safety, a comprehensive sampling investigation was performed to develop reliable Soil Plant Transfer (SPT) model. Eco-toxicity tests with representative soils and organism was conducted to construct the Species Sensitivity Distribution (SSD) for ecological risk assessment. Then, a tiered framework was applied based on Accumulation index, deterministic method (Hazard quotient), and probabilistic assessment (Monte Carlo and Joint Probability Curve). The results revealed the widespread Cd enrichment in agricultural soils, mainly concentrated in Central, Southern, and Southwest China. Risk assessments demonstrated the greater risks related to crop safety, while the ecological risks posed by soil Cd were manageable. Notably, agricultural soils in southern regions of China exhibited more severe risks to both crop safety and soil ecosystem, compared to other agricultural regions. Furthermore, tiered methodology proposed here, can be adapted to other trace elements with potential risks to crop safety and terrestrial ecosystem.
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Affiliation(s)
- Xinghua Huang
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China; College of Environment Science and Engineering, Yangzhou University, Yangzhou 225127, China
| | - Xuzhi Li
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China.
| | - Liping Zheng
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Ya Zhang
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Li Sun
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Yanhong Feng
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Junyang Du
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Xiaosong Lu
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Guoqing Wang
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China.
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Zhao X, Meng J, Li Q, Su G, Zhang Q, Shi B, Dai L, Yu Y. Source apportionment and suitability evaluation of seasonal VOCs contaminants in the soil around a typical refining-chemical integration park in China. J Environ Sci (China) 2024; 137:651-663. [PMID: 37980048 DOI: 10.1016/j.jes.2023.02.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 02/20/2023] [Accepted: 02/21/2023] [Indexed: 11/20/2023]
Abstract
Accurate source apportionment of volatile organic compounds (VOCs) in soil nearby petrochemical industries prevailing globally, is critical for preventing pollution. However, in the process, seasonal effect on contamination pathways and accumulation of soil VOCs is often neglected. Herein, Yanshan Refining-Chemical Integration Park, including a carpet, refining, synthetic rubber, and two synthetic resin zones, was selected for traceability. Season variations resulted in a gradual decrease of 31 VOCs in soil from winter to summer. A method of dry deposition resistance model coupling partitioning coefficient model was created, revealing that dry deposition by gas phase was the primary pathway for VOCs to enter soil in winter and spring, with 100 times higher flux than by particle phase. Source profiles for five zones were built by gas sampling with distinct substance indicators screened, which were used for positive matrix factorization factors determination. Contributions of the five zones were 14.9%, 20.8%, 13.6%, 22.1%, and 28.6% in winter and 33.4%, 12.5%, 10.7%, 24.9%, and 18.5% in spring, respectively. The variation in the soil sorption capacity of VOCs causes inter-seasonal differences in contribution. The better correlation between dry deposition capacity and soil storage of VOCs made root mean square and mean absolute errors decrease averagely by 8.8% and 5.5% in winter compared to spring. This study provides new perspectives and methods for the source apportionment of soil VOCs contamination in industrial sites.
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Affiliation(s)
- Xu Zhao
- Key Laboratory of Environmental Nanotechnology and Health Effects, State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jing Meng
- Key Laboratory of Environmental Nanotechnology and Health Effects, State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qianqian Li
- Key Laboratory of Environmental Nanotechnology and Health Effects, State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guijin Su
- Key Laboratory of Environmental Nanotechnology and Health Effects, State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Qifan Zhang
- Key Laboratory of Environmental Nanotechnology and Health Effects, State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bin Shi
- Key Laboratory of Environmental Nanotechnology and Health Effects, State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lingwen Dai
- Key Laboratory of Environmental Nanotechnology and Health Effects, State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yong Yu
- State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Center, Beijing 100012, China.
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9
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Zhou M, Li Y. Spatial distribution and source identification of potentially toxic elements in Yellow River Delta soils, China: An interpretable machine-learning approach. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169092. [PMID: 38056655 DOI: 10.1016/j.scitotenv.2023.169092] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 11/15/2023] [Accepted: 12/02/2023] [Indexed: 12/08/2023]
Abstract
Identifying the driving factors and quantifying the sources of potentially toxic elements (PTEs) are essential for protecting the ecological environment of the Yellow River Delta. In this study, data from 201 surface soil samples and 16 environmental variables were collected, and the random forest (RF) and Shapley additive explanations (SHAP) methods were then combined to explore the key factors affecting soil PTEs. An innovative t-distributed random neighbor embedding-RF-SHAP model was then constructed, based on the absolute principal component score and multivariate linear regression model, to quantitatively determine PTE sources. Although average PTE concentrations did not exceed the risk control values, PTE distributions exhibited significant differences. It was found that sodium, soil organic matter, and phosphorus contents were the three most important factors affecting PTEs, and human activities and natural environmental factors both influence PTE contents by altering the soil properties. The proposed model successfully determined PTE sources in the soil, outperforming the original linear regression model with a significantly lower RMSE. Source analysis revealed that the parent material was the main contributor to soil PTEs, accounting for more than half of the total PTE content. Industrial and agricultural activities also contributed to an increase in soil PTEs, with average contributions of 19.91 % and 17.44 %, respectively. Unknown sources accounted for 10.83 % of the total PTE content. Thus, the proposed model provides innovative perspectives on source parsing. These findings provide valuable scientific insights for policymakers seeking to develop effective environmental protection measures and improve the quality of saline-alkali land in the Yellow River Delta.
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Affiliation(s)
- Mengge Zhou
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yonghua Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
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10
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Shi Z, Lu J, Liu T, Zhao X, Liu Y, Mi J, Zhao X. Risk assessment and source apportionment of available atmospheric heavy metal in a typical sandy area reservoir in Inner Mongolia, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168960. [PMID: 38043824 DOI: 10.1016/j.scitotenv.2023.168960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 11/22/2023] [Accepted: 11/26/2023] [Indexed: 12/05/2023]
Abstract
This study evaluated dry and wet deposition of atmospheric heavy metals (HMs) in a sandy area of Inner Mongolia, China, with the Dahekou Reservoir, Xilin Gol League, adopted as the study area. Monthly monitoring of atmospheric HM dry and wet deposition was conducted over one year (2021 to 2022) at 12 monitoring points, producing 144 dry and wet deposition samples, respectively. The sample contents of eight HMs (Cr, Ni, Pb, Cu, Zn, Mn, As, and Cd) were determined to estimate the fluxes of available forms of heavy metal (AHM) in dry and wet deposition. The potential ecological index (Eri), risk assessment coding (RAC), and ratio of secondary phase to primary phase (RSP) were used to evaluate the impact of atmospheric HM dry deposition on ecological security. Correlation analysis, principal component analysis, and the absolute principal component scores-multiple linear regression (APCS-MLR) receptor model were used to quantitatively analyze the sources of AHMs in atmospheric dry and wet deposition. The results showed that the study area experienced annual dry and wet deposition fluxes of AHMs of 1712.59 kg and 534.97 kg, respectively. Atmospheric heavy metal dry deposition over the entire year presented a strong ecological risk, with Cd contributing most to this risk. Risk assessment of HM speciation showed that the greatest risks of migration and transformation were for Cd and Pb. The APCS-MLR receptor model identified five and three sources of dry and wet deposition, respectively, in order of proportion of total contribution of: natural wind and sand > road traffic and coal combustion > mineral mining > other human activities > industrial soot.
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Affiliation(s)
- Zhenyu Shi
- Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China
| | - Junping Lu
- Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China; Water Resources Protection and Utilization Key Laboratory, Inner Mongolia Agricultural University, Hohhot 010018, China.
| | - Tingxi Liu
- Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China; Water Resources Protection and Utilization Key Laboratory, Inner Mongolia Agricultural University, Hohhot 010018, China
| | - Xiaoqin Zhao
- Hohhot Sub Station of the General Environmental Monitoring Station of Inner Mongolia Autonomous Region, Hohhot 010030,Inner Mongolia, China
| | - Yinghui Liu
- Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China
| | - Jiahui Mi
- Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China
| | - Xiaoze Zhao
- Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China
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Yang J, Wang J, Zhao C, Wang L, Wan X, Shi H, Lei M, Chen T, Liao X. Identifying driving factors of soil heavy metal at the mining area scale: Methods and practice. CHEMOSPHERE 2024; 350:140936. [PMID: 38159737 DOI: 10.1016/j.chemosphere.2023.140936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 11/26/2023] [Accepted: 12/08/2023] [Indexed: 01/03/2024]
Abstract
Identifying driving factors is of great significance for understanding the mechanisms of soil pollution. In this study, a data processing method for driving factors was analyzed to explore the genesis of Arsenic (As) pollution in mining areas. The wind field that affects the atmospheric diffusion of pollutants was simulated using the standard k-ε model. Machine learning and GeoDetector methods were used to identify the primary driving factors. The results showed that the prediction performances of the three machine learning models were improved after data processing. The R2 values of random forest (RF), support vector machine, and artificial neural network increased from 0.45, 0.69, and 0.24 to 0.55, 0.76, and 0.52, respectively. The importance of wind increased from 20.85% to 26.22%. The importance of distance to the smelter plant decreased from 43.26% to 33.19% in the RF model. The wind's driving force (q value) increased from 0.057 to 0.235 in GeoDetector. The average value of historical atmospheric dust reached 534.98 mg/kg, indicating that atmospheric deposition was an important pathway for As pollution. The outcome of this study can provide a direction to clarify the mechanisms responsible for soil pollution at the mining area scale.
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Affiliation(s)
- Jun Yang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Jingyun Wang
- Shandong Institute of Geological Sciences, Jinan, 250013, China; Key Laboratory of Gold Mineralization Processes and Resource Utilization, MNR, Jinan, 250013, China; Shandong Provincial Key Laboratory of Metallogenic Geological Process and Resources Utilization, Jinan, 250013, China.
| | - Chen Zhao
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Lingqing Wang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Xiaoming Wan
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Huading Shi
- Institute of Soil and Solid Waste, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; Technical Centre for Soil, Agricultural and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China.
| | - Mei Lei
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Tongbin Chen
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Xiaoyong Liao
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
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12
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Chandra K, Proshad R, Islam M, Idris AM. An integrated overview of metals contamination, source-specific risks investigation in coal mining vicinity soils. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 45:7425-7458. [PMID: 37452259 DOI: 10.1007/s10653-023-01672-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 06/19/2023] [Indexed: 07/18/2023]
Abstract
Heavy metals in soil are harmful to natural biodiversity and human health, and it is difficult to estimate the effects accurately. To reduce pollution and manage risk in coal-mining regions, it is essential to evaluate risks for heavy metals in soil. The present study reviews the levels of 21 metals (Nb, Zr, Ag, Ni, Na, K, Mg, Rb, Zn, Ca, Sr, As, Cr, Fe, Pb, Cd, Co, Hg, Cu, Mn and Ti) in soils around Barapukuria coal-mining vicinity, Bangladesh which were reported in literature. An integrated approach for risk assessments with the positive matrix factorization (PMF) model, source-oriented ecological and health hazards were applied for the study. The contents of Rb, Ca, Zn, Pb, As, Ti, Mn, Co, Ag, Zr, and Nb were 1.63, 1.10, 1.97, 14.12, 1.20, 3.13, 1.22, 3.05, 3.85, 5.48, and 7.21 times greater than shale value. About 37%, 67%, 12%, and 85% of sampling sites posed higher risks according to the modified contamination factor, Nemerow pollution index, Nemerow integrated risk index, and mean effect range median quotient, respectively. Five probable metal sources were computed, including industrial activities to coal mining (17%), agricultural activities (33%), atmospheric deposition (19%), traffic emission (16%), and natural sources (15%). Modified Nemerow integrated risk index reported that agricultural activities, industrial coal mining activities, and atmospheric deposition showed moderate risk. Health hazards revealed that cancer risk values computed by the PMF-HHR model with identified sources were higher than the standard value (1.0E-04) for children, adult male, and female. Agricultural activities showed higher cancer risks to adult male (39%) and children (32%) whereas traffic emission contributed to female (25%). These findings highlight the ecological and health issues connected to potential sources of metal contamination and provide useful information to policymakers on how to reduce such risks.
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Affiliation(s)
- Krishno Chandra
- Faculty of Agricultural Engineering and Technology, Sylhet Agricultural University, Sylhet, 3100, Bangladesh
| | - Ram Proshad
- Key Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, Sichuan, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Maksudul Islam
- Department of Environmental Science, Patuakhali Science and Technology University, Dumki, Patuakhali, 8602, Bangladesh
| | - Abubakr M Idris
- Department of Chemistry, College of Science, King Khalid University, Abha, 62529, Saudi Arabia
- Research Center for Advanced Materials Science (RCAMS), King Khalid University, Abha, 62529, Saudi Arabia
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13
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Li J, Li KM, Jiao L, Zang F, Li X, Yang YQ, Mao XX, Tai XS. Contamination, ecological-health risks, and sources of potentially toxic elements in road-dust sediments and soils of the largest urban riverfront scenic park in China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 45:8169-8186. [PMID: 37548849 DOI: 10.1007/s10653-023-01715-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 07/25/2023] [Indexed: 08/08/2023]
Abstract
Identifying the contamination and sources of potentially toxic elements (PTEs) in road-dust sediment (RDS) and the surrounding greenspace soil of urban environments and understanding their ecological-health risks are important for pollution management and public health. The contamination characteristics, ecological and probabilistic health risks, and source apportionment of eight PTEs (Cd, Pb, Cr, Cu, Ni, As, Zn, and Hg) in the Yellow River Custom Tourist Line of Lanzhou, which is the largest open urban riverfront scenic park in China, were investigated. The results showed that all the RDS PTE mean concentrations exceeded their soil background values, whereas for the surrounding greenspace soils, the concentrations of the PTEs, except for Cr and Ni, were also higher than their local background levels. Moreover, the RDS-soil system was mainly contaminated by Cd, Zn, Pb, Cu, and Hg to varying degrees, and the integrated ecological risks of PTEs in the RDS and soil were high and considerable at most sites, respectively. The probabilistic health risk assessment results demonstrated that the non-carcinogenic hazard risk for humans was negligible, but the total carcinogenic risks should be considered. Source apportionment using a positive matrix factorization model combined with multivariate statistical analyses revealed that Cr, Ni, and As in the RDS-soil system were from natural and industrial sources, Cd, Pb, Zn, Cu came from vehicle emissions and pesticide and fertilizer applications, and Hg was from natural and industrial sources and utilization of pesticides with fertilizers. This work provides scientific evidence for urban planning and human health protection in urban environments.
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Affiliation(s)
- Jun Li
- College of Urban Environment, Lanzhou City University, Lanzhou, 730070, China.
| | - Kai-Ming Li
- College of Urban Environment, Lanzhou City University, Lanzhou, 730070, China
| | - Liang Jiao
- Key Laboratory of Resource Environment and Sustainable Development of Oasis, Gansu Province, Northwest Normal University, Lanzhou, 730070, China
| | - Fei Zang
- College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, 730020, China
| | - Xu Li
- College of Urban Environment, Lanzhou City University, Lanzhou, 730070, China
| | - Yun-Qin Yang
- College of Urban Environment, Lanzhou City University, Lanzhou, 730070, China
| | - Xiao-Xuan Mao
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Xi-Sheng Tai
- College of Urban Environment, Lanzhou City University, Lanzhou, 730070, China
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Zhao Z, Tian J, Zhang W, Zhang Q, Wu Z, Xing Y, Li F, Song X, Li Z. Chemical Source Profiles and Toxicity Assessment of Urban Fugitive Dust PM 2.5 in Guanzhong Plain, China. TOXICS 2023; 11:676. [PMID: 37624181 PMCID: PMC10458601 DOI: 10.3390/toxics11080676] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 08/02/2023] [Accepted: 08/05/2023] [Indexed: 08/26/2023]
Abstract
Urban fugitive dust is a significant contributor to atmospheric PM2.5 and a potential risk to humans. In 2019, both road dust and construction dust were collected from four cities, including Xi'an, Xianyang, Baoji, and Tongchuan, in Guanzhong Plain, China. Elements, water-soluble ions, and carbonaceous fractions were determined to establish the chemical source profile. High enrichment degrees of Se, Sc, Cl, and Zn in both road dust and construction dust indicated that the industrial system and energy consumption influenced Guanzhong Plain strongly. According to the coefficient of divergence, the two datasets within Xianyang and Tongchuan were similar. Combined with the chemical profile, road dust was affected by more stationary emission sources than construction dust in Xi'an, while biomass burning and vehicle exhaust contributed more to road dust than construction dust in Baoji. Moreover, the health risk of heavy metal was assessed, and corresponding influencing factors were identified. Road dust in all cities showed a non-negligible non-carcinogenic risk for children. Ingestion and inhalation were the main exposure pathways to which As and Co contributed the most, respectively. The land-use regression model revealed that the first-class road in a 100 m radius impacted all high-risk level metals, and the commercial building material and enterprises weakly influenced Co and Pb, respectively.
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Affiliation(s)
- Ziyi Zhao
- Key Laboratory of Northwest Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (Z.Z.); (Z.W.); (Z.L.)
| | - Jie Tian
- Key Lab of Aerosol Chemistry & Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061, China;
| | - Wenyan Zhang
- Zhongsheng Environmental Technology Development Company Limited, Shaanxi Environmental Protection Industry Group Company Limited, Xi’an 710065, China;
| | - Qian Zhang
- Key Laboratory of Northwest Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (Z.Z.); (Z.W.); (Z.L.)
- Key Lab of Aerosol Chemistry & Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061, China;
| | - Zhichun Wu
- Key Laboratory of Northwest Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (Z.Z.); (Z.W.); (Z.L.)
| | - Yan Xing
- Key Laboratory of Shaanxi Environmental Medium Trace Pollutants Monitoring and Early Warning, Shaanxi Environmental Monitoring Center, Xi’an 710054, China; (Y.X.); (F.L.); (X.S.)
| | - Fei Li
- Key Laboratory of Shaanxi Environmental Medium Trace Pollutants Monitoring and Early Warning, Shaanxi Environmental Monitoring Center, Xi’an 710054, China; (Y.X.); (F.L.); (X.S.)
| | - Xinyu Song
- Key Laboratory of Shaanxi Environmental Medium Trace Pollutants Monitoring and Early Warning, Shaanxi Environmental Monitoring Center, Xi’an 710054, China; (Y.X.); (F.L.); (X.S.)
- Environmental Monitoring Station of Baqiao Branch, Xi’an Ecology of Environment Bureau, Xi’an 710038, China
| | - Zhihua Li
- Key Laboratory of Northwest Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (Z.Z.); (Z.W.); (Z.L.)
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15
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Wang X, Liu E, Yan M, Zheng S, Fan Y, Sun Y, Li Z, Xu J. Contamination and source apportionment of metals in urban road dust (Jinan, China) integrating the enrichment factor, receptor models (FA-NNC and PMF), local Moran's index, Pb isotopes and source-oriented health risk. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 878:163211. [PMID: 37003334 DOI: 10.1016/j.scitotenv.2023.163211] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 03/18/2023] [Accepted: 03/28/2023] [Indexed: 05/13/2023]
Abstract
Contamination and source identifications of metals in urban road dust are critical for remediation and health protection. Receptor models are commonly used for metal source identification, whereas the results are usually subjective and not verified by other indicators. Here we present and discuss a comprehensive approach to study metal contamination and sources in urban road dust (Jinan) in spring and winter by integrating the enrichment factor (EF), receptor models (positive matrix factorization (PMF) and factor analysis with nonnegative constraints (FA-NNC)), local Moran's index, traffic factors and Pb isotopes. Cadmium, Cr, Cu, Pb, Sb, Sn and Zn were the main contaminants, with mean EFs of 2.0-7.1. The EFs were 1.0-1.6 times higher in winter than in spring but exhibited similar spatial trends. Chromium contamination hotspots occurred in the northern area, with other metal contamination hotspots in the central, southeastern and eastern areas. The FA-NNC results indicated Cr contamination primarily resulting from industrial sources and other metal contamination primarily originating from traffic emissions during the two seasons. Coal burning emissions also contributed to Cd, Pb and Zn contamination in winter. FA-NNC model-identified metal sources were verified via traffic factors, atmospheric monitoring and Pb isotopes. The PMF model failed to differentiate Cr contamination from other detrital metals and the above anthropogenic sources, largely due to the model grouping metals by emphasizing hotspots. Considering the FA-NNC results, industrial and traffic sources accounted for 28.5 % (23.3 %) and 44.7 % (28.4 %), respectively, of the metal concentrations in spring (winter), and coal burning emissions contributed 34.3 % in winter. Industrial emissions primarily contributed to the health risks of metals due to the high Cr loading factor, but traffic emissions dominated metal contamination. Through Monte Carlo simulations, Cr had 4.8 % and 0.4 % possibilities posing noncarcinogenic and 18.8 % and 8.2 % possibilities posing carcinogenic risks for children in spring and winter, respectively.
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Affiliation(s)
- Xiaoyu Wang
- College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China
| | - Enfeng Liu
- College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China.
| | - Mengxia Yan
- College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China
| | - Shuwei Zheng
- College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China
| | - Ying Fan
- College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China
| | - Yingxue Sun
- College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China
| | - Zijun Li
- College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China
| | - Jinling Xu
- College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China.
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16
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Xue W, Ying D, Li Y, Sheng Y, He T, Shi P, Liu M, Zhao L. Method for establishing soil contaminant discharge inventory: An arsenic-contaminated site case study. ENVIRONMENTAL RESEARCH 2023; 227:115700. [PMID: 36931375 DOI: 10.1016/j.envres.2023.115700] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 03/06/2023] [Accepted: 03/14/2023] [Indexed: 05/08/2023]
Abstract
The existing method to survey site pollution is generally based on soil-groundwater sampling and instrumental analysis, which enables us to access the detailed soil pollution status while lacking quantitative association with industrial activities. It is urgent to understand contaminant discharge modes and establish a discharge inventory for achieving process-targeted pollution control. This study took a 40-year phosphate fertilizer-sulfuric acid site as an example and constructed a contaminant tracing method based on on-site investigations and detailed industrial data. These investigations and data were combined to determine the characteristic pollutant of this site, arsenic. And the calculation process of four-pathway pollution modes (atmospheric deposition, wastewater, solid waste leaching, and storage dripping) is derived from the existing acceptance criteria and risk assessment guidelines. They are set to calculate the arsenic's factory-to-soil discharge flux. The absent process contaminant release information and parameters, such as discharge coefficient, were obtained from soil-groundwater pollution control standards and discharge handbooks. It was found that the high concentration of arsenic (around 1930 mg g-1) was preponderantly caused by sulfur-iron slag and tailing leaching (96.19%), while the other pathways accounted for only 0.13% (atmospheric deposition), 3.59% (wastewater) and 0.09% (storage tank). Results were verified by the measured arsenic concentration, and the difference was +16.29%, which was acceptable. Finally, a contaminant discharge inventory was established with high-resolution spatial distribution and time-scale (historical discharge) evolution. The innovation of this study lies in the preliminary construction of a method for formulating soil discharge inventory. This study would contribute to the refined management of site pollution and reduction of source contaminants discharge. In addition, it will help infer the pollution condition of sites that are difficult to sample so as to help the government achieve precise source control.
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Affiliation(s)
- Weizhen Xue
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Diwen Ying
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Ye Li
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
| | - Yi Sheng
- College of Chemical Engineering, Zhejiang University of Technology, Zhejiang, 310014, China
| | - Tianhao He
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
| | - Peili Shi
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, China
| | - Min Liu
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
| | - Ling Zhao
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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17
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Fei X, Lou Z, Lv X, Ren Z, Xiao R. Pollution threshold assessment and risk area delineation of heavy metals in soils through the finite mixture distribution model and Bayesian maximum entropy theory. JOURNAL OF HAZARDOUS MATERIALS 2023; 452:131231. [PMID: 36934631 DOI: 10.1016/j.jhazmat.2023.131231] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 06/18/2023]
Abstract
Pollution threshold and high-risk area determination for heavy metals is important for effectively developing pollution control strategies. Based on heavy metal contents in 3627 dense samples, an integrated framework combining the finite mixture distribution model and Bayesian maximum entropy (BME) theory was proposed to assess pollution thresholds, contamination levels and risk areas in an uncertain environment for soil heavy metals. The results showed that the average heavy metal contents were in the order Zn > Cr > Pb > Cu > Ni > As > Cd > Hg, with strong/moderate variation, and the corresponding pollution thresholds were 158.39, 84.29, 47.84, 49.75, 28.95, 18.01, 0.49 and 0.16 mg/kg, respectively. The thresholds were consistently greater than the Zhejiang Province backgrounds but lower than the national risk screening values, except for Cd. Approximately 27.9% of the samples were classified as contaminated at various levels, and they were distributed in the northern, northwestern and eastern regions of the study area. Additionally, 3.73%, 5.34% and 8.22% of the total area were classified as at-risk areas under confidence levels of 95%, 90% and 75%, respectively, through BME theory. The findings provide a reasonable classification system and suggestions for heavy metal pollution management and control.
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Affiliation(s)
- Xufeng Fei
- Zhejiang Academy of Agricultural Sciences, Hangzhou, China; Key Laboratory of Information Traceability of Agriculture Products, Ministry of Agriculture and Rural Affairs, China
| | - Zhaohan Lou
- Zhejiang Academy of Agricultural Sciences, Hangzhou, China
| | - Xiaonan Lv
- Zhejiang Academy of Agricultural Sciences, Hangzhou, China; Key Laboratory of Information Traceability of Agriculture Products, Ministry of Agriculture and Rural Affairs, China
| | - Zhouqiao Ren
- Zhejiang Academy of Agricultural Sciences, Hangzhou, China; Key Laboratory of Information Traceability of Agriculture Products, Ministry of Agriculture and Rural Affairs, China.
| | - Rui Xiao
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
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18
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Jin H, Zhihong P, Jiaqing Z, Chuxuan L, Lu T, Jun J, Xinghua L, Wenyan G, Junkang G, Binbin S, Shengguo X. Source apportionment and quantitative risk assessment of heavy metals at an abandoned zinc smelting site based on GIS and PMF models. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 336:117565. [PMID: 36868153 DOI: 10.1016/j.jenvman.2023.117565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/18/2023] [Accepted: 02/20/2023] [Indexed: 06/18/2023]
Abstract
The abandoned smelters have caused serious hazards to the surrounding environment and residents. Taking an abandoned zinc smelter in southern China as an example, a total of 245 soil samples were collected to study spatial heterogeneity, source apportionment, and source-derived risk assessment of heavy metal(loid)s (HMs) in the region. The results showed that the mean values of all HMs concentrations were higher than the local background values, with Zn, Cd, Pb, and As contamination being the most serious and their plume penetrating to the bottom layer. Four sources were identified by principal component analysis and positive matrix factorization, with their contributions to the HMs contents ranked as: surface runoff (F2, 63.2%) > surface solid waste (F1, 22.2%) > atmospheric deposition (F3, 8.5%) > parent material (F4, 6.1%). Among these, F1 was a determinant source of human health risk with a contribution rate of 60%. Therefore, F1 was considered to be the priority control factor, but it only accounted for 22.2% of HMs contents contribution. Hg dominated the ecological risk with a contribution of 91.1%. Pb (25.7%) and As (32.9%) accounted for the non-carcinogenic risk, while As (95%) dominated the carcinogenic effect. The spatial characteristics of human health risk values derived from F1 indicated that high-risk areas were mainly distributed in the casting finished products area, electrolysis area, leaching-concentration area, and fluidization roasting area. The findings highlight the significance of priority control factors (including HMs, pollution sources and functional areas) for consideration in the integrated management of this region, thus saving costs for effective soil remediation.
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Affiliation(s)
- He Jin
- School of Metallurgy and Environment, Central South University, Changsha, 410083, PR China.
| | - Peng Zhihong
- School of Metallurgy and Environment, Central South University, Changsha, 410083, PR China.
| | - Zeng Jiaqing
- School of Metallurgy and Environment, Central South University, Changsha, 410083, PR China.
| | - Li Chuxuan
- School of Metallurgy and Environment, Central South University, Changsha, 410083, PR China.
| | - Tang Lu
- School of Metallurgy and Environment, Central South University, Changsha, 410083, PR China.
| | - Jiang Jun
- School of Metallurgy and Environment, Central South University, Changsha, 410083, PR China.
| | - Luo Xinghua
- School of Metallurgy and Environment, Central South University, Changsha, 410083, PR China.
| | - Gao Wenyan
- School of Metallurgy and Environment, Central South University, Changsha, 410083, PR China.
| | - Guo Junkang
- School of Environmental Science and Engineering, Shanxi University of Science & Technology, Xi'an, 710021, PR China.
| | - Shao Binbin
- College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China.
| | - Xue Shengguo
- School of Metallurgy and Environment, Central South University, Changsha, 410083, PR China.
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Wang Y, Cheng H. Soil heavy metal(loid) pollution and health risk assessment of farmlands developed on two different terrains on the Tibetan Plateau, China. CHEMOSPHERE 2023:139148. [PMID: 37290519 DOI: 10.1016/j.chemosphere.2023.139148] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 06/10/2023]
Abstract
The quality of farmland soils on the Tibetan Plateau is important because of the region's ecological vulnerability and their close link with local food security. Investigation on the pollution status of heavy metal (loid)s (HMs) in the farmlands of Lhasa and Nyingchi on the Tibetan Plateau, China revealed that Cu, As, Cd, Tl, and Pb were apparently enriched, with the soil parent materials being the primary sources of the soil HMs. Overall, the farmlands in Lhasa had higher contents of HMs compared to those in the farmlands of Nyingchi, which could be attributed to the fact that the former were mainly developed on river terraces while the latter were mainly developed on the alluvial fans in mountainous areas. As displayed the most apparent enrichment, with the average concentrations in the vegetable field soils and grain field soils of Lhasa being 2.5 and 2.2 times higher compared to those of Nyingchi. The soils of vegetable fields were more heavily polluted than those of grain fields, probably due to the more intensive input of agrochemicals, particularly the use of commercial organic fertilizers. The overall ecological risk of the HMs in the Tibetan farmlands was low, while Cd posed medium ecological risk. Results of health risk assessment show that ingestion of the vegetable field soils could pose elevated health risk, with children facing greater risk than adults. Among all the HMs targeted, Cd had relatively high bioavailability of up to 36.2% and 24.9% in the vegetable field soils of Lhasa and Nyingchi, respectively. Cd also showed the most significant ecological and human health risk. Thus, attention should be paid to minimize further anthropogenic input of Cd to the farmland soils on the Tibetan Plateau.
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Affiliation(s)
- Yafeng Wang
- MOE Key Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Hefa Cheng
- MOE Key Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China.
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Li Y, Ye Z, Yu Y, Li Y, Jiang J, Wang L, Wang G, Zhang H, Li N, Xie X, Cheng X, Liu K, Liu M. A combined method for human health risk area identification of heavy metals in urban environments. JOURNAL OF HAZARDOUS MATERIALS 2023; 449:131067. [PMID: 36827727 DOI: 10.1016/j.jhazmat.2023.131067] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/02/2023] [Accepted: 02/20/2023] [Indexed: 06/18/2023]
Abstract
Multi-medium heavy metals pollution is a crucial pathway to destroy the urban environmental resources cycle. In this study, Nanjing of China, a typical mega city, was taken as the study area. Compared with other cities or countries, Cr, Cu and Zn in human nails and hair in the study area have higher concentration characteristics, while Cd and Pb have lower concentration characteristics. By combining the health risk status of heavy metals in soil and dustfall, the spatial clustering characteristics of heavy metals in soil dustfall and the concentration information of heavy metals in humans in the study area, a potential toxic risk area identification method based on soil-dustfall-human (SDB-HR) was established. Through Monte Carlo analysis, it's found that the risk of Zn and Cr in soil-dustfall to human health is relatively high, with the probability of carcinogenesis reaching 51.2 % and 50.2 %, respectively. By the proposed method, different levels of heavy metal risk areas in urban environments can be more reasonably and effectively identified, which will provide important technical and theoretical support for the precise management of heavy metals in urban environments.
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Affiliation(s)
- Yan Li
- Collaborative Innovation Center of Sustainable Forestry, College of forestry, Nanjing Forestry University, Nanjing, Jiangsu, China; Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, China; Key Laboratory of Watershed Earth Surface Processes and Ecological Security,Zhejiang Normal University, Jinhua, Zhejiang, China.
| | - Zi Ye
- Collaborative Innovation Center of Sustainable Forestry, College of forestry, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Ye Yu
- Collaborative Innovation Center of Sustainable Forestry, College of forestry, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Ye Li
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, China.
| | - Jiang Jiang
- Collaborative Innovation Center of Sustainable Forestry, College of forestry, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Liangjie Wang
- Collaborative Innovation Center of Sustainable Forestry, College of forestry, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Genmei Wang
- Collaborative Innovation Center of Sustainable Forestry, College of forestry, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Huanchao Zhang
- Collaborative Innovation Center of Sustainable Forestry, College of forestry, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Ning Li
- Collaborative Innovation Center of Sustainable Forestry, College of forestry, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Xuefeng Xie
- Key Laboratory of Watershed Earth Surface Processes and Ecological Security,Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Xinyu Cheng
- Collaborative Innovation Center of Sustainable Forestry, College of forestry, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Ke Liu
- School of Oceanography, Shanghai Jiao Tong University, Shanghai, China; School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, China
| | - Min Liu
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, China.
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Wu B, Li L, Guo S, Li Y. Source apportionment of heavy metals in the soil at the regional scale based on soil-forming processes. JOURNAL OF HAZARDOUS MATERIALS 2023; 448:130910. [PMID: 36736212 DOI: 10.1016/j.jhazmat.2023.130910] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/03/2023] [Accepted: 01/29/2023] [Indexed: 06/18/2023]
Abstract
Source apportionment is crucial to the prevention and control of heavy metals in the soil. The major methods focus on the identification of soil heavy metals from different pollution sources. However, they are unsuited to the source apportionment at a regional scale due to ignoring the spatial heterogeneity of heavy metal content caused by soil formation. Thus, we built a source apportionment model by introducing the weathering and leaching coefficients as the key parameters of soil-forming processes. In this study, we selected Liaohe Plain in China as the study area, which was the starting point of China's industrial development, with dense industrial areas and high levels of heavy-metal emission. Heavy metals concentrations in surface and deep soil of reference and grid points were collected as model data. The results showed that the average contribution rates of soil-forming process to Cd, Hg, As, and Pb were 82.7%, 85.2%, 88.6%, and 91.7%, respectively, and those of anthropogenic activities were 17.3%, 14.8%, 11.4%, and 8.3%, respectively. Spatial distribution of contribution rates showed the superposition of soil environmental background and pollution sources. This study provides a feasible method to quantify heavy metals contents from natural and anthropogenic sources at a regional scale.
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Affiliation(s)
- Bo Wu
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, PR China
| | - Linlin Li
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Shuhai Guo
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, PR China; National-Local Joint Engineering Laboratory of Contaminated Soil Remediation by Bio-physicochemical Synergistic Process, Shenyang 110016, PR China.
| | - Yang Li
- Liaoning Provincial Ecology & Environment Monitoring Center, Shenyang 110161, PR China
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