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International Journal of Science, Strategic Management and Technology

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ISSN: 3108-1762 (Online)
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REVIEW OF DUST AND NOISE POLLUTION CONTROL TECHNOLOGIES IN OPENCAST MINES: CHALLENGES, EMERGING SOLUTIONS, AND LESSONS FROM INDIAN COAL FIELDS

AUTHORS:
Aadil Khan
Mentor
Ram Chandra Chaurasia
Affiliation
Department of Mining and Mineral Processing, Lakshmi Narain College of Technology, Jabalpur, Madhya Pradesh, 482053, India.
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Opencast mining dominates coal production in India due to its high productivity, lower extraction costs, and suitability for shallow coal deposits. However, large-scale excavation, drilling, blasting, transportation, and material handling activities generate significant dust and noise pollution, posing serious environmental, occupational, and public health concerns. Dust emissions contribute to deteriorating air quality, respiratory diseases, vegetation damage, and reduced agricultural productivity, while excessive noise exposure affects worker health, community well-being, and ecosystem stability. With increasing emphasis on sustainable mining and environmental compliance, effective pollution control technologies have become a critical component of mine management. This review critically examines dust and noise pollution control technologies employed in opencast coal mines, with particular emphasis on Indian coalfields such as Jharia, Raniganj, Korba, Singrauli, Talcher, and SCCL-operated mines. A systematic review methodology based on PRISMA guidelines was adopted to evaluate scientific literature, government reports, and industrial case studies published between 2015 and 2026. The review assesses conventional control technologies including water sprinkling systems, fog cannons, wet drilling, acoustic enclosures, mufflers, green belts, and personal protective equipment. Emerging innovations such as IoT-enabled environmental monitoring, artificial intelligence-based predictive systems, drone-assisted dust suppression, chemical suppressants, autonomous mining equipment, and digital twin technologies are also examined. The findings indicate that while conventional technologies remain widely adopted, their effectiveness is often constrained by climatic conditions, operational practices, and maintenance challenges. Emerging smart technologies offer substantial opportunities for enhancing pollution control efficiency and regulatory compliance. Lessons learned from successful Indian mining operations demonstrate the importance of integrated environmental management strategies combining engineering controls, ecological restoration, real-time monitoring, and stakeholder engagement. The review concludes with recommendations for policy reforms, technological advancement, and future research aimed at achieving sustainable and environmentally responsible mining practices in India.

 
Keywords
Opencast mining dust control technologies noise control technologies environmental monitoring sustainable mining Coal India Limited air pollution occupational health
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Khan, A. (2026). Review of Dust and Noise Pollution Control Technologies in Opencast Mines: Challenges, Emerging Solutions, and Lessons from Indian Coal Fields. International Journal of Science, Strategic Management and Technology, 02(8), 1-9. https://doi.org/10.55041/ijsmt.v2i8.051

Khan, Aadil. "Review of Dust and Noise Pollution Control Technologies in Opencast Mines: Challenges, Emerging Solutions, and Lessons from Indian Coal Fields." International Journal of Science, Strategic Management and Technology, vol. 02, no. 8, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijsmt.v2i8.051.

Khan, Aadil. "Review of Dust and Noise Pollution Control Technologies in Opencast Mines: Challenges, Emerging Solutions, and Lessons from Indian Coal Fields." International Journal of Science, Strategic Management and Technology 02, no. 8 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijsmt.v2i8.051.

References

  1. Banerjee, S.P. (2026) “Air Pollution and its Control in Mining Areas,” in, pp. 167–180. doi:10.1201/9781003762119-20.

  2. Bisen, V., & Chaurasia, R. C. (2026). Risk assessment plan for mine closure. International Journal of Sciences and Innovation Engineering, 3(4), 2534–2551. https://doi.org/10.70849/ijsci03042618848

  3. Bisen, V., Chaurasia, R. C., Daharwal, V., Tiwari, G., Kiran, A. V., & Singh, K. (2025). An integrated geospatial framework for post-closure mine site monitoring: A synthesis of remote sensing and GIS methodologies. Journal of Civil and Environmental Engineering (IJCEE), 13(9), 210–220. https://doi.org/10.1018/IJCEE.2025.13.9.8169

  4. Chaulya, S.K. (2026) “Road Dust Management Technique for Opencast Coal Mines.” doi:10.1002/9781394373550.ch09.

  5. Chourasiya, D., & Chaurasia, R. C. (2026). A study of fly-ash utilization as backfilling material in mines. International Journal of Creative and Open Research in Engineering and Management, 2(5). https://doi.org/10.55041/ijcope.v2i5.789

  6. Chourasiya, D., & Chaurasia, R. C. (2026). Recent advances in treatment technologies and resource utilization of mine tailings in India: A review. International Journal of Sciences and Innovation Engineering, 3(5). https://doi.org/10.70849/ijsci03052676831

  7. Daharwal, V., & Chaurasia, R. C. (2026). Biosorption of heavy metals from mine tailing. International Journal of Creative and Open Research in Engineering and Management, 2(4). https://doi.org/10.55041/ijcope.v2i4.753

  8. Ghose, M.K. and Majee, S. (2001) “Air Pollution due to Opencast Coal Mining and It’s Control in Indian Context,” Journal of Scientific & Industrial Research, 60(10), pp. 786–797.

  9. Giri, V. K., & Chaurasia, R. C. (2025). A comprehensive study on equipment utilization and haulage efficiency in open-cast mining. International Journal of Innovative Research in Technology, 12(4).

  10. Kamran, M. et al.(2024) “Decision intelligence-driven predictive modelling of air quality index in surface mining,” Engineering Applications of Artificial Intelligence, 133, pp. 108399–108399. doi:10.1016/j.engappai.2024.108399.

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This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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