The eco-conscious mining paradigm necessitates a detailed understanding of the environmental impacts of blasting operations, particularly shock-induced ground vibrations and atmospheric overpressure (airblast). These phenomena can cause structural damage, disturb communities, and degrade the surrounding environment. This paper synthesizes contemporary research on the prediction, control, and mitigation of these effects, emphasizing machine learning and data-driven models. It aims to bridge scientific advancement with sustainable mining practices. The study also explores regulatory frameworks, environmental thresholds, and engineering controls essential to reducing the ecological footprint of mining operations. An integrated and interdisciplinary approach is proposed for achieving safe, efficient, and environmentally responsible mining.
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The authors state that they have no conflicts of interest regarding this article.
The author confirms that they were solely responsible for the study's planning, data acquisition, results interpretation, and manuscript writing.
The authors received no financial support for the research, authorship, or publication of this article from any funding agencies.
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My thanks go to those who assisted with this study and manuscript preparation, and to the peer reviewers for their constructive feedback.
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