Taking a typical lead-zinc mining area in Yangshuo county, Guangxi as the research object, the contents of 10 metal elements (Cr, Mn, Ni, Cu, Zn, As, Cd, Sb, Hg, and Pb) in the surface soil of Sidihe River basin in Yangshuo were analyzed and determined. Pearson correlation analysis, principal component analysis (PCA), positive definite matrix factorization (PMF), and other methods were comprehensively used to quantitatively analyze their contributions and identify pollution sources. In total, 168 surface soil samples were collected across the study area. The mean concentrations of Zn, Cd, Hg, and Pb in the soils were higher than the National Environmental Quality Standards for Soils in China. The mean contents of Sb, Cd, Cu, Pb, and Zn were higher than their corresponding local background values by approximately 1.01, 5.50, 3.29, 9.11, and 10.67 times, respectively, indicating that heavy metals have been enriched in topsoil. The showed that the major pollutant element in the soils was Hg, followed by Pb, Zn, and Mn. Correlation analysis and principal component analysis showed that the sources of metal pollution in surface soil in the study area were complex and mainly from human activities. Cu, Zn, Cd, Sb, As, and Pb were mainly derived from mining activities; Hg, Cr, and Ni were controlled by soil parent material sources; and Mn and Cd were mainly derived from mining activities and agricultural activities. PMF model analysis results showed that the metal pollution sources in the surface soil were jointly affected by these three sources. Mining activities, natural sources, and a mixed source of mining activities and agricultural activities were the main sources of heavy metal pollution in the soils, accounting for 58.0%, 13.5%, and 28.6% of the total heavy metal accumulation, respectively. Ni, Cu, Zn, As, Sb, Hg, and Pb were derived mainly from mining activities. Cr, Ni, and Hg were mainly attributed to natural sources, such as soil parent materials and rainfall erosion (44.6%, 23.2%, and 21.0%, respectively), and Mn and Cd were associated with a mixed source of mining activities and agricultural activities (75.4% and 70.4%).

Download full-text PDF

Source
http://dx.doi.org/10.13227/j.hjkx.202201127DOI Listing

Publication Analysis

Top Keywords

mining activities
24
surface soil
16
metal pollution
12
derived mining
12
activities agricultural
12
agricultural activities
12
activities
10
sources
9
sources heavy
8
heavy metals
8

Similar Publications

Lanthipeptides are ribosomally synthesized and post-translationally modified peptides (RiPPs) characterized by the presence of thioether cross-links called lanthionine and methyllanthionine, formed by dehydration of Ser/Thr residues and Michael-type addition of Cys side chains onto the resulting dehydroamino acids. Class II lanthipeptide synthetases are bifunctional enzymes responsible for both steps, thus generating macrocyclic natural products. ProcM is part of a group of class II lanthipeptide synthetases that are known for their remarkable substrate tolerance, having large numbers of natural substrates with highly diverse peptide sequences.

View Article and Find Full Text PDF

Preparation of chitin-derived hierarchical porous materials and their application and mechanism in adsorption of mycotoxins.

Int J Biol Macromol

December 2024

State Key Laboratory of Refractories and Metallurgy, Key Laboratory of Coal Conversion & New Carbon Materials of Hubei Province, School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan 430081, PR China. Electronic address:

In this study, the hierarchical porous materials for adsorbing mycotoxins were prepared by one-step carbonization-activation method using potassium permanganate (KMnO) and chitin as activators and carbon source, respectively. The hierarchical porous materials had different specific surface area and pore distribution owing to different carbonization temperatures. In this paper, the effects of pH, time and temperature of adsorption as well as the concentration of patulin on the adsorption characteristics were systematically investigated.

View Article and Find Full Text PDF

Objectives: To assess whether the gender (primary) and geographical affiliation (post-hoc) of the first and/or last authors are associated with publication decisions after peer review.

Design: Case-control study.

Setting: Biomedical journals.

View Article and Find Full Text PDF

To identify the spatial distribution patterns and assess the ecological risks associated with soil heavy metal pollution in the southern region of Hunan Province, a total of 362 surface soil samples were collected from the studied area. This study employed multivariate statistics and geographic information systems (GIS) to investigate the spatial distribution pattern of soil metals (Cd, Hg, As, Pb, Zn, Ni, Mn, Tl, and Sb). Furthermore, the pollution sources and source-specific ecological risk of heavy metals were quantified by combining the positive matrix factorization (PMF) model and the comprehensive ecological risk index model.

View Article and Find Full Text PDF

[Source and Health Risk Assessment of Heavy Metals in Groundwater of Datong Basin].

Huan Jing Ke Xue

January 2025

School of Water Resources & Environmental Engineering, East China University of Technology, Nanchang 330013, China.

The identification of distribution characteristics, pollution sources, and potential human health risks of heavy metals in groundwater is crucial for the scientific planning and rational development of groundwater resources in arid-semiarid regions. In this study, 46 groundwater samples were collected and analyzed using hydrogeochemical modeling and multivariate statistical analysis methods to reveal the pollution characteristics and speciation distribution of 11 heavy metals (As, B, Pb, Sb, Tl, Mn, Ba, Cd, Co, Cr, and Al) in the Datong Basin. The absolute principal component-linear regression (APCS-MLR) model and health risk assessment model (HRA) were employed to determine the sources and health risk levels of heavy metals in groundwater.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!