Atmospheric Pollution in Mining Areas

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: 28 July 2025 | Viewed by 2746

Special Issue Editor


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Guest Editor
Faculty of Engineering, CERENA - Center for Natural Resources and Environment, Universidade do Porto, 4099-002 Porto, Portugal
Interests: soil science; environmental radioactivity; environmental chemistry; mining engineering; environmental engineering; groundwater; remediation technologies
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Special Issue Information

Dear Colleagues,

Mining activities are fundamental to a thriving society, as they supply essential resources that drive global development. However, mining operations can cause air pollution at every stage, which greatly affects the health of workers and nearby communities. Both above-ground and underground mining operations generate air pollution, producing harmful aerosols like particulate matter, arsenic, and diesel emissions. A major source of this pollution comes from mineral extraction activities, including excavation, blasting, and transport. Exhaust emissions from the vehicles and heavy equipment used in mining operations also contribute to these pollution levels. Nevertheless, in general, the most critical emissions from mining activities are particulate matter (PM), sulfur dioxide (SO2), nitrogen dioxide (NO2), heavy metals and radionuclides.

Abandoned mines are also a recurrent problem for nearby communities around former mining areas. Different airborne contamination sources (such as tailings) may be continuously dispersed by wind around the surrounding environment, affecting flora, fauna, water, air and soil. Therefore, comprehensive understanding of these chemical, physical and biological processes is essential to assess the extension and effects of air pollution around mining areas, which should be based on a holistic approach.

This Special Issue aims to present research on issues related to air pollution in mining areas (active, abandoned or remediated). Research results, practical experiences, alternatives and new approaches are welcome, dealing with (but not limited to) the following: i) air pollutants and their sources; ii) air quality monitoring; iii) modeling dispersion, transport and fate; iv) innovative techniques and emission-management systems; v) life cycle assessments of mining and metallurgical processes; vi) applications of machine learning models to reduce emissions; vii) the influence of climate changes on air quality; viii) occupational and environmental exposure; ix) environmental risk assessment; and x) socioeconomic issues related to air quality in mining areas.

Other emerging topics in this field of research are also welcome. Thus, we encourage you to submit your original research or review papers.

Dr. Maria de Lurdes Dinis
Guest Editor

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Keywords

  • particulate matter
  • radionuclides
  • heavy metals
  • monitoring
  • air quality
  • modeling
  • machine learning
  • life cycle assessment
  • climate changes
  • socioeconomics

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Published Papers (2 papers)

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Research

26 pages, 3884 KiB  
Article
Modeling PM10 Emissions in Quarry and Mining Operations: Insights from AERMOD Applications in Malaysia
by Md Munir Hayet Khan, Tonni Agustiono Kurniawan, Indra Chandra and Thomas M. T. Lei
Atmosphere 2025, 16(4), 369; https://doi.org/10.3390/atmos16040369 - 24 Mar 2025
Cited by 1 | Viewed by 709
Abstract
PM10 emissions have been a significant concern in rock crushing and quarry operations (study site #1) and iron ore mining projects (study site #2) in certain regions of Malaysia, posing fears to the health and well-being of nearby communities with severe air [...] Read more.
PM10 emissions have been a significant concern in rock crushing and quarry operations (study site #1) and iron ore mining projects (study site #2) in certain regions of Malaysia, posing fears to the health and well-being of nearby communities with severe air pollution. To address this issue, it is crucial to develop effective mitigation strategies to reduce dust particle emissions like PM10 in the ambient air. The AERMOD model was applied to predict PM10 emissions during quarry operations and iron ore mining projects, both with and without control measures. The results indicated that PM10 emissions were reduced when control measures were implemented. The modeling result shows the mean PM10 concentration with and without control measures in study site #1 is 74.85 µg/m3 and 20,557.69 µg/m3, respectively. In comparison, the average PM10 concentration with and without control measures in study site #2 is 53.95 µg/m3 and 135.69 µg/m3. Therefore, the control measure has successfully reduced the PM10 concentrations by 99.90% and 60.24% in study sites #1 and #2, respectively, and ensures the air quality complies with the Malaysian Ambient Air Quality Guidelines (MAAQG) 24 h threshold limits at 100 µg/m3. In addition, the AERMOD modeling results showed that mitigation measures performed better in rock crushing and quarry operations than in iron ore mining projects in this case study. Full article
(This article belongs to the Special Issue Atmospheric Pollution in Mining Areas)
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21 pages, 5809 KiB  
Article
Characterization and Concentration Prediction of Dust Pollution in Open-Pit Coal Mines
by Guilin Wang, Wei Zhou, Zhiming Wang, Xiang Lu and Yirong Zhang
Atmosphere 2024, 15(12), 1408; https://doi.org/10.3390/atmos15121408 - 22 Nov 2024
Cited by 1 | Viewed by 1031
Abstract
Dust pollution is a major problem formed caused by opencast coal mining, and its prevention is a key prerequisite for the realization of green and climate-friendly mining in open-pit coal mines. In this paper, we conducted the real-time monitoring of dust concentration and [...] Read more.
Dust pollution is a major problem formed caused by opencast coal mining, and its prevention is a key prerequisite for the realization of green and climate-friendly mining in open-pit coal mines. In this paper, we conducted the real-time monitoring of dust concentration and meteorological parameter data in different areas of a large-scale open-pit coal mine in China and used multivariate statistical analysis to study the characteristics of the variation in dust concentration and its influencing factors in operating and non-operating areas. The results showed that there was a significant correlation between TSP, PM10, and PM2.5 in the same area. There was a significant difference in the percentage of PM2.5/PM10 between the operation area and the non-operation area, with particles in the range of 2.5–10 μm dominating close to the operation area and particles in the range of 0–2.5 μm dominating away from the operation area. The production intensity had a greater effect on dust concentration in the operation area, and there was no significant relationship with dust concentration away from the operation area. Wind speed—wind force—wind direction, temperature, and humidity are all correlated with particulate matter. The LSTM model is more suitable for predicting the dust concentration in open-pit coal mines. The results of this study can provide a reference for dust prevention and control in open-pit coal mines. Full article
(This article belongs to the Special Issue Atmospheric Pollution in Mining Areas)
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