Abstract
Gold mining is a major economic activity in the Philippines participated in by large-scale, artisanal and small-scale entities. Small-scale gold mining has been a source of opportunities for jobs and livelihood to thousands of people. However, this sector is described as an informal and unregulated industry with minimal standards. This situation has raised concerns on risks that may affect its sustainability. Locally, a working organization is required to undergo self-assessment and inspection. In the absence of a risk assessment tool, this paper presents the development of this tool for a systematic examination and identification of the hazards on small-scale gold mining in the Philippines. To assess its usability, officials of the Provincial Environmental Natural Resources Office and the miners/operators used the tool at sites engaged in surface, underground or compressor mining. The results showed low compliance to standards and violations for the gold small-scale mining activities is due to the lack of information regarding the standards. It also showed that the top hazards identified in specific site depends on the choice of mining and extraction processes. Based on user evaluation, the risk assessment tool is effective, easy to learn and covers most hazards in small-scale mining in the Philippines.
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Acknowledgments
The authors acknowledge the support provided by the Engineering Research and Development for Technology (ERDT) program of the Department of Science and Technology and spearheaded by the UP College of Engineering. The data requirements gathered for this study was made possible through the ERDT Mineral Extraction with Responsibility and Sustainability (MINERS) Program, Project G, entitled: “The Gold and Copper Chase (Life Cycle Analysis of Sustainable Small Scale Production Systems”).
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Soriano, V., Bernaldez, I., Tamayao, MA. (2018). Development of a Risk Assessment Tool for Small Scale Gold Mining in the Philippines. In: Arezes, P. (eds) Advances in Safety Management and Human Factors. AHFE 2017. Advances in Intelligent Systems and Computing, vol 604. Springer, Cham. https://doi.org/10.1007/978-3-319-60525-8_38
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DOI: https://doi.org/10.1007/978-3-319-60525-8_38
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