To develop accurate air pollution control policies, it is necessary to determine the sources of different types of fugitive dust in mining and metallurgy areas. A method integrating principal component analysis and a positive matrix factorization model was used to identify the potential sources of heavy metals (HMs) in five different types of fugitive dust. The results showed accumulation of Mn, Fe, and Cu can be caused by natural geological processes, which contributed 38.55% of HMs. The Ni and Co can be released from multiple transport pathways and accumulated through local deposition, which contributed 29.27%. Mining-related activities contributed 20.11% of the HMs and showed a relatively high accumulation of As, Sn, Zn, and Cr, while traffic-related emissions contributed the rest of the HMs and were responsible for the enrichment in Pb and Cd. The co-applied source-identification models improved the precision of the identification of sources, which revealed that the local geological background and mining-related activities were mainly responsible for the accumulation of HMs in the area. The findings can help the government develop targeted control strategies for HM dispersion efficiency.

The international journal of Aerosol and Air Quality Research (AAQR) covers all aspects of aerosol science and technology, atmospheric science and air quality related issues.

This study aimed to assess the pollution levels, sources, and human health risks of heavy metals in street dust from a typical industrial district in Wuhan City, Central China. In total, 47 street dust samples were collected from the major traffic arteries and streets around Wuhan Iron and Steel (Group) Company (WISC) in Qingshan District, Wuhan. The concentrations of heavy metals (Cr, Mn, Ni, Zn, Fe, Cu, and Cd) in street dust were determined by atomic absorption spectroscopy. Results indicated that the mean concentrations of Zn (249.71 mg/kg), Cu (51.15 mg/kg), and Cd (0.86 mg/kg) in street dust were higher than their corresponding soil background values in Hubei Province. Heavy metal enrichment is closely related to urban transportation and industrial production. The pollution level of heavy metals in street dust was assessed using the geo-accumulation method (I_geo) and potential ecological risk assessment (PERI). Based on the I_geo value, Cr, Mn, Fe, and Ni showed no pollution, Zn and Cu showed light to moderate contamination, and Cd showed moderate contamination. The PERI values of heavy metals in street dust ranged between 76.70 and 7027.28, which represents a medium to high potential ecological risk. Principal component analysis showed that the sources of heavy metals in street dust were mainly influenced by anthropogenic activities. Among the studied metals, Cu, Cr, Zn, Fe, and Mn mainly come from industrial processes, while Ni and Cd come from traffic exhaust. The non-carcinogenic risk indexes of heavy metals for children and adults are ranked as Cr > Cu > Ni > Cd > Zn. The health risks to children through the different exposure pathways are higher than those for adults. Hand-to-mouth intake is the riskiest exposure pathway for non-carcinogenic risk. In addition, Cr, Ni, and Cd do not pose a carcinogenic risk for the residents.

In order to study the pollution characteristics, sources, and health risks of heavy metals in urban atmospheric PM_2.5, samples were collected in Huangshi City from June 2021 to May 2022. The contents of 16 kinds of metal elements were analyzed by XRF, and the pollution degree and sources of elements were analyzed by the enrichment factor method, correlation analysis, and cluster analysis. The health risk of heavy metal elements was evaluated by the USEPA health risk assessment model. The results of enrichment factor analysis show that the metal elements carried by PM_2.5 were affected by human emissions except for Ti. Heavy metals mainly come from industrial sources, motor vehicle sources, mixed combustion sources, and dust sources, according to correlation analysis and cluster analysis. Mn had a non-carcinogenic risk to children, and the non-carcinogenic risk of other elements to the human body was generally acceptable. The carcinogenic risks of Cr, As, Cd, and Co exceeded the acceptable carcinogenic risk threshold (10⁻⁶ ~10⁻⁴), and there were potential carcinogenic risks.

Pollutant leaching from tailings presents critical environmental risks driven by complex geochemical, hydrological, and biological interactions. This study conducted a systematic review of research trends in numerical modeling, transport mechanisms, and pollution control through topic modeling, identifying eight dominant thematic clusters. The results reveal an evolution from foundational investigations of leaching kinetics to advanced predictive simulations and sustainable remediation technologies. Numerical simulations, including geochemical and hydrological models, have improved our understanding of pollutant leaching processes. Transport mechanism studies have highlighted leaching kinetics, redox transformations, and adsorption-desorption in controlling pollutant mobility. In pollution control, adsorption-based treatments, microbe-driven remediation, and resource recovery are emerging as key strategies. Despite these advancements, significant challenges remain. Existing models struggle to integrate multi-process interactions, leading to uncertainties in long-term pollutant behavior. The heterogeneity of tailings complicates parameterization, and microbial contributions to pollutant immobilization remain underexplored. Additionally, climate change-induced variations in hydrological conditions pose new risks for pollutant leaching and migration. Future research should develop hybrid modeling frameworks incorporating artificial intelligence, enhance field-scale validation, and promote circular economy principles for tailings management. By leveraging data-driven approaches, this review provides a structured synthesis of existing knowledge and a foundation for innovative solutions in environmental risk mitigation and sustainable mining practices.