Source-specific soil heavy metal risk assessment in arsenic waste mine site of Yunnan: integrating environmental and biological factors DOI

Weigang Huang,

Yanwei Liu,

Xiaoyang Bi

et al.

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 486, P. 136902 - 136902

Published: Dec. 20, 2024

Language: Английский

Pollution sources, characteristics and environmental risk assessment of heavy metals in surface water and sediments of typical pyrite mine in Southwest China DOI

Ziqiu Nie,

Jing Luo, Jie Tang

et al.

Journal of Environmental Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

1
Heavy Metal Pollution and Source Analysis of Soils Around Abandoned Pb/Zn Smelting Sites: Environmental Risks and Fractionation Analysis DOI Creative Commons
Muhammad Adnan, Peng Zhao, Baohua Xiao

et al.

Environmental Technology & Innovation, Journal Year: 2025, Volume and Issue: unknown, P. 104084 - 104084

Published: Feb. 1, 2025

Language: Английский

Citations

1
Analysis of Heavy Metal Sources in Xutuan Mining Area Based on APCS-MLR and PMF Model DOI Creative Commons

Jieyu Xia,

Liangmin Gao,

Jinxiang Yang

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(8), P. 4249 - 4249

Published: April 11, 2025

The present study aims to determine the concentrations and forms of Copper (Cu), Lead (Pb), Zinc (Zn), Chromium (Cr), Cadmium (Cd), Arsenic (As) in water sediments Xutuan mining area. geoaccumulation index (Igeo) ecological risk assessment coding (RAC) methods were used assess heavy metal pollution levels risks sediments. positive matrix factorization (PMF) model absolute principal component score-multiple linear regression (APCS-MLR) quantitatively analyze sources metals evaluated results showed good quality Cu, Cr, Zn, As mainly residual form, while Cd Pb organic matter combined form. Igeo RAC that degree higher APCS-MLR PMF models analyzed contributions natural (72.5% 25.1%) anthropogenic sources, respectively, further distinguished coal (26.4%), agricultural (21.44%), traffic (27.05%) sources.

Language: Английский

Citations

0
Interface structure between coal gangue ceramsite and cement matrix DOI Creative Commons
Tianyu Han, Renliang Shan,

Guoye Jing

et al.

Case Studies in Construction Materials, Journal Year: 2025, Volume and Issue: unknown, P. e04691 - e04691

Published: April 1, 2025

Language: Английский

Citations

0
Tracing sources-oriented ecological risks of metal(loid)s in sediments of anthropogenically-affected coastal ecosystem from northeast bay of Bengal DOI
Abu Reza Md. Towfiqul Islam, Md. Nashir Uddin,

Md. Fazle Rabbi Joy

et al.

Marine Pollution Bulletin, Journal Year: 2024, Volume and Issue: 211, P. 117354 - 117354

Published: Dec. 2, 2024

Language: Английский

Citations

1
How Has the Source Apportionment of Heavy Metals in Soil and Water Evolved over the Past 20 Years? A Bibliometric Perspective DOI Open Access

Huading Shi,

Zexin He, Chenning Deng

et al.

Water, Journal Year: 2024, Volume and Issue: 16(22), P. 3171 - 3171

Published: Nov. 6, 2024

Exploring soil heavy metal sources is of great significance for ensuring the safety ecological environments and agricultural product safety, as well guiding pollution control management policies. This paper retrieved 452 research papers on source analysis published over 2004–2024 period from Web Science database. The collected literature was subjected to multidimensional bibliometric using CiteSpace 6.3.R1. results showed significantly increasing trends in scientific outputs number soils water study period. In addition, related topics have expanded single multiple elements environmental media increasingly recognized impact contamination. Research methods also evolved basic statistical complex spatial techniques, covering urban soils. Previous studies focused different areas, has now extended associated human health risks. present provides directions future guidance effective safe utilization land resources.

Language: Английский

Citations

0
Sources, Contamination and Risk Assessment of Heavy Metals in Riparian Soils of the Weihe River Based on a Receptor Model and Monte Carlo Simulation DOI Open Access

Wen Dong,

Bohan Niu,

Huaien Li

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10779 - 10779

Published: Dec. 9, 2024

The riparian ecosystem is highly susceptible to pollution, particularly heavy metals (HMs), due its unique spatial position and landscape characteristics. Therefore, assessing the risks of HM pollution identifying potential sources are crucial for formulating effective prevention control measures. This study investigates characteristics HMs (Ni, Cr, Zn, Cd, Cu, Pb) in Weihe River zone, identifies their sources, assesses associated ecological human health risks. results indicate that Ni, Cd primary pollutants soil, with average concentration being 5.64 times higher than background value, indicating a high risk. Spatially, concentrations middle upper reaches lower reaches. Vertically, as distance from increases, content exhibits “U”-shaped pattern (increase-decrease-increase). Absolute principal components multiple regression (APCS-MLR) receptor model identified four sources: traffic sources; agricultural industrial natural sources. Additionally, Monte Carlo simulation-based risk assessment indicates non-carcinogenic indices all within acceptable ranges. For carcinogenic indices, there 1.14% probability children. However, vast majority fall or no-risk categories.

Language: Английский

Citations

0
A Comprehensive Study of Spatial Distribution, Pollution Risk Assessment, and Source Apportionment of Topsoil Heavy Metals and Arsenic DOI Creative Commons
Honghua Chen, Xinxin Sun,

Longhui Sun

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2151 - 2151

Published: Dec. 10, 2024

Accurately identifying pollution risks and sources is crucial for regional land resource management. This study takes a certain coastal county in eastern China as the object to explore spatial distribution, risk, source apportionment of heavy metals topsoil. A total 633 samples were collected from topsoil with depth ranging 0 20 cm, which came different topographical use types (e.g., farmland, industrial areas, mining areas), concentrations HMs As measured by using atomic fluorescence spectrometry inductively coupled plasma mass spectrometry. Firstly, distribution soil (Cd, Cr, Hg, Ni, Pb) arsenic (As) was predicted incorporating environmental variables strongly affecting formation into geostatistical methods machine learning approaches. Then, various indicators employed conduct evaluations, potential ecological risk assessments implemented based on generated map. Finally, conducted random forest (RF), absolute principal component score–multiple linear regression (APCS-MLR), correlation analysis, As. Findings this research reveal that RF approach yielded best prediction performance (0.59 ≤ R2 0.73). The Nemerow geoaccumulation indices suggest levels exist area. average As, Ni are 7.233 mg/kg, 0.051 27.43 mg/kg respectively, being 1.14 times, 1.27 1.15 times higher than background levels, respectively. central–northern region presented slight Hg Cd identified primary factors. Natural, agricultural, transportation, activities main sources. These findings will assist design targeted policies reduce urban offer useful guidelines similar regions.

Language: Английский

Citations

0
Evaluation of Heavy Metal Contamination in Black Soil at Sanjiang Plain: From Source Analysis to Health Risk Assessment DOI Open Access
Zijie Gao, Jie Jiang, Guo‐Xin Sun

et al.

Processes, Journal Year: 2024, Volume and Issue: 12(12), P. 2829 - 2829

Published: Dec. 10, 2024

Heavy metals were discharged into the agricultural soil through coal mining, transportation, etc., posing a threat to human health food chain. In order investigate sources of heavy and potential risk population, we collected 298 surface samples in black area Sanjiang Plain Heilongjiang province tested concentrations seven metals. Toxic element contamination was evaluated by combining ecological index environmental capacity, pollution are identified positive matrix factorization. The results indicate that Cd As exceed background values 1.74 1.51 times, respectively, is significantly higher than those other toxic elements. comprehensive level moderate at 78.5% low 21.5%. metal elements include pesticide spraying (36.5%), input fertilizer transport activities (20.5%), mining metallurgy-related (43.1%). When linking PMF Human Health Risk Assessment model, it found about 56% pose carcinogenic children. Knowledge can certainly help understand risks people provide scientific basis for prevention pollution.

Language: Английский

Citations

0
Source-specific soil heavy metal risk assessment in arsenic waste mine site of Yunnan: integrating environmental and biological factors DOI

Weigang Huang,

Yanwei Liu,

Xiaoyang Bi

et al.

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 486, P. 136902 - 136902

Published: Dec. 20, 2024

Language: Английский

Citations

0