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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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Yang Y, Lu X, Yu B, Wang Z, Wang L, Lei K, Zuo L, Fan P, Liang T. Exploring the environmental risks and seasonal variations of potentially toxic elements (PTEs) in fine road dust in resource-based cities based on Monte Carlo simulation, geo-detector and random forest model. JOURNAL OF HAZARDOUS MATERIALS 2024; 473:134708. [PMID: 38795490 DOI: 10.1016/j.jhazmat.2024.134708] [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: 04/03/2024] [Revised: 05/13/2024] [Accepted: 05/22/2024] [Indexed: 05/28/2024]
Abstract
The environmental pollution caused by mineral exploitation and energy consumption poses a serious threat to ecological security and human health, particularly in resource-based cities. To address this issue, a comprehensive investigation was conducted on potentially toxic elements (PTEs) in road dust from different seasons to assess the environmental risks and influencing factors faced by Datong City. Multivariate statistical analysis and absolute principal component score were employed for source identification and quantitative allocation. The geo-accumulation index and improved Nemerow index were utilized to evaluate the pollution levels of PTEs. Monte Carlo simulation was employed to assess the ecological-health risks associated with PTEs content and source orientation. Furthermore, geo-detector and random forest analysis were conducted to examine the key environmental variables and driving factors contributing to the spatiotemporal variation in PTEs content. In all PTEs, Cd, Hg, and Zn exhibited higher levels of content, with an average content/background value of 3.65 to 4.91, 2.53 to 3.34, and 2.15 to 2.89 times, respectively. Seasonal disparities were evident in PTEs contents, with average levels generally showing a pattern of spring (winter) > summer (autumn). PTEs in fine road dust (FRD) were primarily influenced by traffic, natural factors, coal-related industrial activities, and metallurgical activities, contributing 14.9-33.9 %, 41.4-47.5 %, 4.4-8.3 %, and 14.2-29.4 % to the total contents, respectively. The overall pollution and ecological risk of PTEs were categorized as moderate and high, respectively, with the winter season exhibiting the most severe conditions, primarily driven by Hg emissions from coal-related industries. Non-carcinogenic risk of PTEs for adults was within the safe limit, yet children still faced a probability of 4.1 %-16.4 % of unacceptable risks, particularly in summer. Carcinogenic risks were evident across all demographics, with children at the highest risk, mainly due to Cr and smelting industrial sources. Geo-detector and random forest model indicated that spatial disparities in prioritized control elements (Cr and Hg) were primarily influenced by particulate matter (PM10) and anthropogenic activities (industrial and socio-economic factors); variations in particulate matter (PM10 and PM2.5) and meteorological factors (wind speed and precipitation) were the primary controllers of seasonal disparities of Cr and Hg.
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Affiliation(s)
- Yufan Yang
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Xinwei Lu
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China.
| | - Bo Yu
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Zhenze Wang
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Lingqing Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Kai Lei
- School of Biological and Environmental Engineering, Xi'an University, Xi'an 710065, China
| | - Ling Zuo
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Peng Fan
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Tao Liang
- 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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Hu Y, Eziz M, Wang L, Subi X. Pollution and Health Risk Assessment of Potentially Toxic Elements in Groundwater in the Kǒnqi River Basin (NW China). TOXICS 2024; 12:474. [PMID: 39058126 PMCID: PMC11280737 DOI: 10.3390/toxics12070474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 06/25/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024]
Abstract
Potentially toxic elements (PTEs) pose a significant threat to the groundwater system and human health. Pollution and the potential risks of PTEs in groundwater in the Kǒnqi River Basin (KRB) of the northwest arid zones of China are still unknown. A total of 53 groundwater samples containing eight PTEs (Al, As, Cd, Cu, Mn, Pb, Se, and Zn) were collected from the KRB, and the pollution levels and probabilistic health risks caused by PTEs were assessed based on the Nemerow Index (NI) method and the health risk assessment model. The results revealed that the mean contents of Al, As, and Mn in the groundwater surpassed the Class III threshold of the Standard for Groundwater Quality of China. The overall pollution levels of the investigated PTEs in the groundwater fall into the moderate pollution level. The spatial distributions of contents and pollution levels of different PTEs in the groundwater were different. Health risk assessment indicated that all the investigated PTEs in groundwater in the KRB may pose a probabilistic non-carcinogenic health risk for both adults and children. Moreover, As may pose a non-carcinogenic health risk, whereas the non-carcinogenic health risk posed by the other seven PTEs in groundwater will not have the non-carcinogenic risks. Furthermore, As falls into the low carcinogenic risk level, whereas Cd falls into the very low carcinogenic risk level. Overall, As was confirmed as the dominant pollution factor and health risk factor of groundwater in the KRB. Results of this study provide the scientific basis needed for the prevention and control of PTE pollution in groundwater.
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Affiliation(s)
- Yonglong Hu
- College of Geographical Science and Tourism, Xinjiang Normal University, Urumqi 830054, China; (Y.H.); (L.W.); (X.S.)
- Laboratory of Arid Zone Lake Environment and Resources, Xinjiang Normal University, Urumqi 830054, China
| | - Mamattursun Eziz
- College of Geographical Science and Tourism, Xinjiang Normal University, Urumqi 830054, China; (Y.H.); (L.W.); (X.S.)
- Laboratory of Arid Zone Lake Environment and Resources, Xinjiang Normal University, Urumqi 830054, China
| | - Liling Wang
- College of Geographical Science and Tourism, Xinjiang Normal University, Urumqi 830054, China; (Y.H.); (L.W.); (X.S.)
| | - Xayida Subi
- College of Geographical Science and Tourism, Xinjiang Normal University, Urumqi 830054, China; (Y.H.); (L.W.); (X.S.)
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Zhou Q, Yang S, Sun L, Ye J, Sun Y, Qin Q, Xue Y. Evaluating the protective capacity of soil heavy metals regulation limits on human health: A critical analysis concerning risk assessment - Importance of localization. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 361:121197. [PMID: 38820791 DOI: 10.1016/j.jenvman.2024.121197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 05/05/2024] [Accepted: 05/16/2024] [Indexed: 06/02/2024]
Abstract
Heavy metal pollution of agricultural soil is a major global concern, prompting the establishment of maximum allowable limits (MALs) to ensure food safety and protect human health. This study collected and compared MALs for six heavy metals (As, Cd, Hg, Pb, Zn, and Cu) in agricultural soils from representative countries and organizations (EU and WHO/FAO). The research evaluated the critical health risks and efficacy of these MALs under the hypothetical scenario of metals concentrations reaching the maximum allowable level. Safe thresholds for heavy metals were then derived based on maximum acceptable health risk levels. The comparative analysis revealed significant variations in the specific limit values and terms of MALs across countries and organizations, even for the same metal. This suggests that there is no consensus among countries and organizations regarding the level of metal-related health risks. Furthermore, the risk analysis of metal concentrations reaching the maximum level accentuated heightened risks associated with As, suggesting that the current risk of soil As exposure was underestimated, particularly for children. However, soil Cu, Cd, and Zn limits generally resulted in low health risks, implying that the current limits may overestimate their hazard. Overall, the results highlight that the current MALs for soil heavy metals may not fully safeguard human health. There is a critical need to optimize current soil MALs based on localized risks and the actual impact of these metals on human health. It is suggested to appropriately lower the limits of metals (such as As) whose impact on health risks is underestimated, and cautiously increase the limits of metals (such as Cu, Cd, and Zn) that currently pose minor health risks. This approach aims to reduce both over and insufficient protection problems of soil heavy metal MALs, emphasizing the importance of considering the locality in setting these limits.
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Affiliation(s)
- Qianhang Zhou
- School of Chemical and Environmental Engineering, Shanghai Institute of Technology, 201418, China; Eco-Environmental Protection Institution, Shanghai Academy of Agricultural Sciences, 201403, China
| | - Shiyan Yang
- Eco-Environmental Protection Institution, Shanghai Academy of Agricultural Sciences, 201403, China; Key Laboratory of Low-carbon Green Agriculture in Southeastern China, Ministry of Agriculture and Rural Affairs, 201403, China
| | - Lijuan Sun
- Eco-Environmental Protection Institution, Shanghai Academy of Agricultural Sciences, 201403, China; Key Laboratory of Low-carbon Green Agriculture in Southeastern China, Ministry of Agriculture and Rural Affairs, 201403, China
| | - Jing Ye
- School of Chemical and Environmental Engineering, Shanghai Institute of Technology, 201418, China.
| | - Yafei Sun
- Eco-Environmental Protection Institution, Shanghai Academy of Agricultural Sciences, 201403, China; Key Laboratory of Low-carbon Green Agriculture in Southeastern China, Ministry of Agriculture and Rural Affairs, 201403, China
| | - Qin Qin
- Eco-Environmental Protection Institution, Shanghai Academy of Agricultural Sciences, 201403, China; Key Laboratory of Low-carbon Green Agriculture in Southeastern China, Ministry of Agriculture and Rural Affairs, 201403, China
| | - Yong Xue
- Eco-Environmental Protection Institution, Shanghai Academy of Agricultural Sciences, 201403, China; Key Laboratory of Low-carbon Green Agriculture in Southeastern China, Ministry of Agriculture and Rural Affairs, 201403, China.
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Shi H, Du Y, Li Y, Deng Y, Tao Y, Ma T. Determination of high-risk factors and related spatially influencing variables of heavy metals in groundwater. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 358:120853. [PMID: 38608578 DOI: 10.1016/j.jenvman.2024.120853] [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: 12/10/2023] [Revised: 04/01/2024] [Accepted: 04/03/2024] [Indexed: 04/14/2024]
Abstract
Identifying high-risk factors (heavy metals (HMs) and pollution sources) by coupling receptor models and health risk assessment model (HRA) is a novel approach within the field of risk assessment. However, this coupled model ignores the contribution of spatial differentiation to high-risk factors, resulting in the assessment being subjective. Taking Dongting Plain (DTP) as an example, a coupling framework by jointly using the positive matrix factorization model (PMF), HRA, Monte Carlo simulation, and geo-detector was developed, aiming to identify high-risk factors in groundwater, and further explore key environmental variables influencing the spatial heterogeneity of high-risk factors. The results showed that at least 82.86 % of non-carcinogenic risks and 97.41 % of carcinogenic risks were unacceptable for people of all ages, especially infants and children. According to the relationships among HMs, pollution sources, and health risks, As and natural sources were defined as high-risk HMs and sources, respectively. The interactions among Holocene thickness, oxidation-reduction potential, and dissolved organic carbon emerged as the primary drivers of spatial variability in high-risk factors, with their combined explanatory power reaching up to 74%. This proposed framework provides a scientific reference for future studies and a practical reference for environmental authorities in developing effective pollution management measures.
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Affiliation(s)
- Huanhuan Shi
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Yao Du
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China.
| | - Yueping Li
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Yamin Deng
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Yanqiu Tao
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Teng Ma
- College of Resources and Environmental Engineering, Wuhan University of Science and Technology, Wuhan, 430081, China
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Pan Y, Han W, Shi H, Liu X, Xu S, Li J, Peng H, Zhao X, Gu T, Huang C, Peng K, Wang S, Zeng M. Incorporating environmental capacity considerations to prioritize control factors for the management of heavy metals in soil. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 351:119820. [PMID: 38113783 DOI: 10.1016/j.jenvman.2023.119820] [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: 10/22/2023] [Revised: 11/22/2023] [Accepted: 12/09/2023] [Indexed: 12/21/2023]
Abstract
Heavy metals (HMs) pollution threatens food security and human health. While previous studies have evaluated source-oriented health risk assessments, a comprehensive integration of environmental capacity risk assessments with pollution source analysis to prioritize control factors for soil contamination is still lacking. Herein, we collected 837 surface soil samples from agricultural land in the Nansha District of China in 2019. We developed an improved integrated assessment model to analyze the pollution sources, health risks, and environmental capacities of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. The model graded pollution source impact on environmental capacity risk to prioritize control measures for soil HMs. All HMs except Pb exceeded background values and were sourced primarily from natural, transportation, and industrial activities (31.26%). Approximately 98.92% (children), 97.87% (adult females), and 97.41% (adult males) of carcinogenic values exceeded the acceptable threshold of 1E-6. HM pollution was classified as medium capacity (3.41 kg/hm2) with mild risk (PI = 0.52). Mixed sources of natural backgrounds, transportation, and industrial sources were identified as priority sources, and As a priority element. These findings will help prioritize control factors for soil HMs and direct resources to the most critical pollutants and sources of contamination, particularly when resources are limited.
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Affiliation(s)
- Yujie Pan
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Wenjing Han
- Geological Survey Research Institute, China University of Geosciences, Wuhan, 430074, China
| | - Huanhuan Shi
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Xiaorui Liu
- China Electric Power Research Institute, Beijing, 100192, China
| | - Shasha Xu
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Jiarui Li
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Hongxia Peng
- School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430074, China.
| | - Xinwen Zhao
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan, 430205, China
| | - Tao Gu
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan, 430205, China
| | - Chansgheng Huang
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan, 430205, China
| | - Ke Peng
- Survey Affairs Center for Natural Resources and Planning of Yongzhou City, Yongzhou, 425000, China
| | - Simiao Wang
- College of Information Science and Engineering, Northeastern University, Shenyang, 314001, China
| | - Min Zeng
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan, 430205, China.
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Han W, Pan Y, Welsch E, Liu X, Li J, Xu S, Peng H, Wang F, Li X, Shi H, Chen W, Huang C. Prioritization of control factors for heavy metals in groundwater based on a source-oriented health risk assessment model. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 267:115642. [PMID: 37924799 DOI: 10.1016/j.ecoenv.2023.115642] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/23/2023] [Accepted: 10/26/2023] [Indexed: 11/06/2023]
Abstract
Heavy metals (HMs) in groundwater seriously threaten ecological safety and human health. To facilitate the effective management of groundwater contamination, priority control factors of HMs in groundwater need to be categorized. A total of 86 groundwater samples were collected from the Huangpi district of Wuhan city, China, during the dry and wet seasons. To determine priority control factors, a source-oriented health risk assessment model was applied to compare the pollution sources and health risks of seven HMs (Cu, Pb, Zn, Cr, Ni, As, and Fe). The results showed that the groundwater had higher As and Fe contents. The sources of HM pollution during the wet period were mainly industrial and agricultural activities and natural sources. During the dry period, origins were more complex due to the addition of domestic discharges, such as sewage wastewater. Industrial activities (74.10% during the wet period), agricultural activities (53.84% during the dry period), and As were identified as the priority control factors for groundwater HMs. The results provide valuable insights for policymakers to coordinate targeted management of HM pollution in groundwater and reduce the cost of HM pollution mitigation.
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Affiliation(s)
- Wenjing Han
- Geological Survey Research Institute, China University of Geosciences, Wuhan 430074, China
| | - Yujie Pan
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Emily Welsch
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; Department of Geography and Environment, The London School of Economics and Political Science, London, UK
| | - Xiaorui Liu
- China Electric Power Research Institute, Beijing 100192, China
| | - Jiarui Li
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Shasha Xu
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Hongxia Peng
- School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China.
| | - Fangtin Wang
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan 430205, China
| | - Xuan Li
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan 430205, China
| | - Huanhuan Shi
- School of Environment, China University of Geosciences, Wuhan 430074, China
| | - Wei Chen
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan 430205, China
| | - Changsheng Huang
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan 430205, China.
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