1
|
Jiang Z, Yang S, Luo S. Source analysis and health risk assessment of heavy metals in agricultural land of multi-mineral mining and smelting area in the Karst region - a case study of Jichangpo Town, Southwest China. Heliyon 2023; 9:e17246. [PMID: 37456041 PMCID: PMC10338313 DOI: 10.1016/j.heliyon.2023.e17246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 06/10/2023] [Accepted: 06/12/2023] [Indexed: 07/18/2023] Open
Abstract
In the Karst region of Southwest China, the content of soil heavy metals is generally high because of the geological background. Moreover, Southwest China is rich in mineral resources. A large number of mining and smelting activities discharge heavy metals into surrounding soil and cause superimposed pollution, which has drawn widespread concern. Due to the large variation coefficients of soil heavy metals in the Karst region, it is particularly essential to select appropriate analysis methods. In this paper, Jichangpo in Puding County, a Karst area with multi-mineral mining and smelting, is selected as the research object. A total of 368 pieces of agricultural topsoil in the study area are collected. The pollution level of heavy metals in agricultural soil is evaluated by the geological accumulation index (Igeo) and enrichment factor (EF). Absolute Factor Score/Multiple Linear Regression (APCS/MLR), geographic information system (GIS), self-organizing mapping (SOM), and random forest (RF) are used for the source allocation of soil heavy metals. Finally, the combination of APCS/MLR and health risk assessment model is adopted to evaluate the risks of heavy metal sources and determine the priority-control source. The results show that the average values of soil heavy metals in the study area (Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni) exceed the background values of corresponding elements in Guizhou Province. Three sources of heavy metals are identified by combining APCS/MLR, GIS, SOM, and RF. Zn (63.47%), Pb (55.77%), Cd (58.98%), Hg (32.17%), Cu (14.41%), and As (5.99%) are related to lead-zinc mining and smelting; Cr (98.14%), Ni (90.64%), Cu (76.93%), Pb (43.02%), Zn (35.22%), Cd (28.97%), Hg (22.44%), and As (5.84%) are mixed sources (natural and agricultural sources); As (88.17%), Hg (45.39%), Cd (12.04%), Cu (8.66%), and Ni (6.72%) are related to the mining and smelting of coal and iron. The results of health risk assessment show that only As poses a non-carcinogenic risk to human health. 3.31% of the sampling points of As have non-carcinogenic risks to adults and 10.22% to children. In terms of carcinogenic risks, As, Pb, and Cr pose carcinogenic risks to adults and children. Combined with APCS/MLR and the health risk assessment model, the mining and smelting of coal and iron is the priority-control pollution source. This paper provides a comprehensive method for studying the distribution of heavy metal sources in areas with large variation coefficients of soil heavy metals in the Karst region. Furthermore, it offers a theoretical basis for the management and assessment of heavy metal pollution in agricultural land in the study area, which is helpful for researchers to make strategic decisions on food security when selecting agricultural land.
Collapse
Affiliation(s)
- Zaiju Jiang
- Guizhou Coal Mine Geological Engineering Advisory and Geological Environment Monitoring Center, Guiyang, 550081, China
| | - Shaozhang Yang
- Guizhou Coal Mine Geological Engineering Advisory and Geological Environment Monitoring Center, Guiyang, 550081, China
- Guizhou Rongyuan Environmental Protection Technology Co. LTD, Guiyang, 550081, China
| | - Sha Luo
- Guizhou Coal Mine Geological Engineering Advisory and Geological Environment Monitoring Center, Guiyang, 550081, China
- Guizhou Rongyuan Environmental Protection Technology Co. LTD, Guiyang, 550081, China
| |
Collapse
|
2
|
Wang J, Zheng Y, Li Y, Wang Y. Potential risks, source apportionment, and health risk assessment of dissolved heavy metals in Zhoushan fishing ground, China. MARINE POLLUTION BULLETIN 2023; 189:114751. [PMID: 36967682 DOI: 10.1016/j.marpolbul.2023.114751] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 02/09/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Dissolved heavy metal pollution in the ocean is one of the most severe environmental concerns; however, the potential sources of heavy metals and the resulting health risks are not fully understood. To explore the distribution characteristics, source apportionment, and health risks of dissolved heavy metals (As, Cd, Cu, Hg, Pb, and Zn) in the Zhoushan fishing ground, this study analyzed heavy metals in surface seawater during the wet and dry seasons. The concentrations of heavy metals varied greatly between seasons, and the mean concentration in the wet season was generally higher than that in the dry season. A positive matrix factorization model coupled with correlation analysis was applied to identify promising sources of heavy metals. Four potential sources (agricultural, industrial, traffic, atmospheric deposition, and natural sources) were identified as the determinants of the accumulation of heavy metals. The health risk assessment results revealed that non-carcinogenic risk (NCR) for adults and children were acceptable (HI < 1), and carcinogenic risk (CR) were at a low level (1 × 10-6 < TCR ≤ 1 × 10-4). The source-oriented risk assessment indicated that industrial and traffic sources were the main sources of pollution, contributing 40.7 % of NCR and 27.4 % of CR, respectively. This study proposes forming reasonable, effective policies to control industrial pollution and improve the ecological environment of Zhoushan fishing grounds.
Collapse
Affiliation(s)
- Jing Wang
- Fishery College, Zhejiang Ocean University, Zhoushan 316022, China
| | - Yijia Zheng
- Fishery College, Zhejiang Ocean University, Zhoushan 316022, China
| | - Yi Li
- Fishery College, Zhejiang Ocean University, Zhoushan 316022, China
| | - Yingbin Wang
- Fishery College, Zhejiang Ocean University, Zhoushan 316022, China.
| |
Collapse
|
3
|
Wang W, Jiang R, Lin C, Wang L, Liu Y, Lin H. Multivariate statistical analysis of potentially toxic elements in the sediments of Quanzhou Bay, China: Spatial relationships, ecological toxicity and sources identification. ENVIRONMENTAL RESEARCH 2022; 213:113750. [PMID: 35753378 DOI: 10.1016/j.envres.2022.113750] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/17/2022] [Accepted: 06/19/2022] [Indexed: 06/15/2023]
Abstract
In this paper, the spatial distribution, pollution degree, ecological toxicity and possible sources of seven potentially toxic elements (PTEs) collected from the surface sediments of Quanzhou Bay (QZB) were analyzed by obtaining concentration measurements. The results indicated that the areas with high Cu, Pb, Zn and Hg concentrations were mainly located in the Luoyang River estuary, while the areas with high contents of Cd and As appeared in the Luoyang River estuary area and in the southern part of QZB, respectively. The contamination indices showed that the Cd pollution degree was slight to serious, while other elements were slightly enriched. The calculation results of the potential ecological risk index (RI) and toxic risk index (TRI) indicated that Cd was the main element posing ecological risk among the PTEs of sediments in QZB, followed by Hg. Moreover, in approximately 30% of the surveyed sites, PTEs exhibited low toxicity to aquatic ecosystems. Finally, the self-organizing map (SOM) and positive matrix factorization (PMF) model were used to determine the PTEs sources. Natural sources, industrial emissions, and the combustion of fossil fuels were three main sources for PTEs in the surface sediments of QZB. This study provides a reference for assessing sediment pollution and managing marine pollution in QZB.
Collapse
Affiliation(s)
- Weili Wang
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005, China
| | - Ronggen Jiang
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005, China
| | - Cai Lin
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005, China.
| | - Lingqing Wang
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yang Liu
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005, China
| | - Hui Lin
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005, China
| |
Collapse
|
4
|
Zhi M, Zhang X, Zhang K, Ussher SJ, Lv W, Li J, Gao J, Luo Y, Meng F. The characteristics of atmospheric particles and metal elements during winter in Beijing: Size distribution, source analysis, and environmental risk assessment. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2021; 211:111937. [PMID: 33476848 DOI: 10.1016/j.ecoenv.2021.111937] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 01/04/2021] [Accepted: 01/11/2021] [Indexed: 06/12/2023]
Abstract
In order to investigate the pollution characteristics of size-segregated particles and metal elements (MEs) after the Chinese Air Pollution Prevention Action Plan was released in 2013, an intensive field campaign was conducted in the suburban area of Chaoyang District, Beijing in winter 2016. The size distributions of particle mass concentrations were bimodal, with the first peak in the fine fraction (0.4-2.1 µm) and the second peak in the coarse fraction (3.3-5.8 µm). Moreover, the proportion of fine particles increased and the proportion of coarse particles decreased as the pollution level was more elevated. It was found that the composition of coarse particles is as important as that of fine particles when pollution of aerosol metals in the atmosphere in 2016 were compared to 2013. In addition, according to the size distribution characteristics, 23 MEs were divided into three groups: (a) Fe, Co, Sr, Al, Ti, Ba, and U, which concentrated in coarse mode; (b) Zn, As, Cd, Tl, and Pb, which concentrated in fine mode; and (c) Na, K, Be, V, Cr, Mn, Ni, Cu, Mo, Ag, and Sn, showing bimodal distribution. Under clean air, slight pollution and moderate pollution conditions, most elements maintained their original size distributions, while under severe pollution, the unimodal distributions of most MEs became bimodal distributions. The factors analysis combined with size distributions indicated that Na, Zn, Mo, Ag, Cd, and Tl, showing the moderate to severe contamination on environment, were significantly influenced by diffuse regional emissions or anthropogenic source emissions (vehicle exhaust emissions and combustion process). The environmental risk assessment revealed that the heavy metal loading in the atmospheric particles collected had a high potential for ecological risk to the environment during sampling period because of the high contribution of Cd, Tl, Zn and Pb.
Collapse
Affiliation(s)
- Minkang Zhi
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xi Zhang
- Faculty of Environmental Engineering, The University of Kitakyushu, 1-1 Hibikino, Wakamatsu, Kitakyushu, Fukuoka 808-0135, Japan
| | - Kai Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Simon J Ussher
- School of Geography, Earth and Environmental Sciences, University of Plymouth, Plymouth PL4 8AA, United Kingdom
| | - Wenli Lv
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jie Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jian Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yuqian Luo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Fan Meng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| |
Collapse
|
5
|
Source Identification of Heavy Metals in Surface Paddy Soils Using Accumulated Elemental Ratios Coupled with MLR. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18052295. [PMID: 33652570 PMCID: PMC7956510 DOI: 10.3390/ijerph18052295] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 02/17/2021] [Accepted: 02/22/2021] [Indexed: 12/12/2022]
Abstract
Source identification of heavy metals in agricultural soils using small sample sizes, simple experimental procedures, and convenient analysis is urgently required. This study employed a simple source identification model using a visual comparison via radar plots, cluster analysis, principal component analysis, and a multiple linear regression model to determine the source of heavy metal pollution in soil samples from the Chang-Zhu-Tan urban agglomeration area of China. The elemental compositions of major pollution sources (atmospheric deposition, organic fertilizer, irrigation water, and tailings) were compared with soil samples from 11 study locations and the model was used to determine the relative contribution of different pollution sources at each sample site. The results showed that the model successfully calculated the contribution of different pollution sources at each site based on the pollution characteristics and contaminant transport rules of the region. The proposed method overcomes the requirement for extensive data and complex experimental procedures. Furthermore, the model can determine the source of heavy metal contamination in single or small plots, which is important for the prevention and control of heavy metal soil pollution and remediation at the plot scale.
Collapse
|