The presence of heavy metals (HMs) in particulate matters (PMs) particularly fine particles such as PM poses potential risk to the health of human being. The purpose of this study was to analyze the contents of HMs in PM in the atmospheric monitoring stations in Isfahan city, Iran, in different seasons between March 2014 and March 2015 and their source identification using principle component analysis (PCA). The samples of PM were taken using a high volume sampler in 7 monitoring stations located throughout the city and industrial zones since March 2014 to March 2015. The HMs content of the samples was measured using ICP-MS. The results showed that the concentrations of As, Cd and Ni were in a range of 23-36, 1-12, and 5-76ng/m at all the stations which exceeded the US-EPA standards. Furthermore, the concentrations of Cr and Cu reached to 153 and 167ng/m in some stations which were also higher than the standard levels. Depending on the potential sources of HMs, their concentration in PM through the various seasons was different. PCA illustrated that the different potential sources of HMs in the atmosphere, showing that the most important sources of HMs originated from fossil fuel combustion, abrasion of vehicle tires, industrial activities (e.g., iron and steel industries) and dust storms. Management and control of air pollution of industrial plants and vehicles are suggested for decreasing the risk of the HMs in the region.
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http://dx.doi.org/10.1016/j.jes.2018.01.002 | DOI Listing |
Sci Total Environ
January 2025
Guangdong Provincial Academy of Environmental Science, Guangzhou 510045, China; Guangdong Laboratory of Soil Pollution Fate and Risk Management in Earth's Critical Zone and Guangdong Key Laboratory of Contaminated Environmental Management and Remediation, Guangzhou 510045, China.
This study integrated data-driven interpretable machine learning (ML) with statistical methods, complemented by knowledge-driven discrimination diagrams, to identify the primary driving factors of heavy metal (HM) and polycyclic aromatic hydrocarbon (PAH) contamination in agricultural soils influenced by complex sources in a rapidly industrializing region of a megacity in southern China. First, the statistical characteristics of the concentrations of HMs and PAHs, and their correlations with the environmental covariates were explored. Three ML models and a statistical model comprising multiple environmental variable predictors were developed and assessed to predict the concentration of HMs in the agricultural soil.
View Article and Find Full Text PDFHuan Jing Ke Xue
January 2025
Lunan Geo-engineering Exploration Institute of Shandong Province (Shandong Provincial Bureau of Geology and Mineral Resources No. 2 Geology Group), Jining 272100, China.
Soil heavy metal (HM) pollution is a prominent global environmental problem. Understanding the risk characteristics and quantitative analysis of potential sources of soil HM pollution is of great significance for accurate prevention and control, scientific management, and safe utilization of soil resources. In the surface soil of Shanxian County, the contents of eight HMs, such as As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, were collected and identified in 330 surface soil samples.
View Article and Find Full Text PDFWater Res
December 2024
Faculty of Applied Science, School of Engineering, University of British Columbia Okanagan Campus, Kelowna, British Columbia V1V 1V7, Canada.
In this research, a sustainable blue-green infrastructure (BGI) was developed to efficiently remove contaminants from stormwater through a combined use of modified porous asphalt (PA) and microalgae cultivation to provide a potential drinking water (DW) source. According to the results, the modified PA with powder activated carbon (PAC) could successfully reduce the level of total suspended solids (TSS), turbidity, polycyclic aromatic hydrocarbons (PAHs), oil and grease to below the DW standards but failed to efficiently remove some heavy metals (HMs) and nutrient pollutants. The results revealed that the treated stormwater was an appropriate medium for microalgae cultivation.
View Article and Find Full Text PDFToxicol Rep
December 2024
Department of Zootechnology, University of Science and Technology of Masuku, P.O Box 941, Franceville, Gabon.
With an obsolete livestock sector, Gabon relies on its huge hydrographic network rich in fish to supply its populations with animal proteins. This study aimed to conduct metal analyses in four fish species () frequently consumed by human populations in the Moyen-Ogooué and Haut-Ogooué Provinces of Gabon and infer the potential human health risks for those populations who rely on these freshwater produces as a source of proteins. Fish were sampled from Ezanga, Oguemoué, Onangué, Nguenè (Moyen-Ogooué) and Grand Poubara (Haut-Ogooué) Lakes during the high flow period (HF) and low flow period (LF) from 2021 to 2022, and analysed for seven heavy metals (HMs) using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) techniques.
View Article and Find Full Text PDFEnviron Geochem Health
December 2024
College of Resources and Environment, Key Laboratory of Agricultural Environment, Shandong Agricultural University, Tai'an, 271000, China.
Excessive heavy metals (HMs) exposure in surface soils may cause non-negligible health risks to human beings; however, the potential health risk assessment of HMs in Yellow River Delta wetland (YRDW) soils has rarely been evaluated. In this study, we sampled surface wetland soils from ten typical functional areas in YRDW, assessed the HMs pollution status, evaluated their potential health risks, stimulated their probabilistic distributions of health risks and analyzed their potential source apportionment using Positive matrix factorization and Monte Carlo simulation. Enrichment factor (EF) and geo-accumulation index (I) indicated significant anthropogenic impacts, particularly in oil-contaminated sites, while Sediment Quality Guidelines (SQGs) comparison results suggested potential ecological risks, especially for As and Ni, which were occasionally above threshold effect levels.
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