Practical Use of Area Noise Measurements in Stone, Sand, and Gravel (SSG) Mines
Public Domain
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2019/06/16
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Series: Mining Publications
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Description:Despite the requirement for hearing conservation programs, hearing loss caused by occupational noise exposure is a frequent occurrence in the mining industry. Recent surveillance initiatives indicate that stone, sand, and gravel (SSG) mining operations may be at a greater risk for occupational noise overexposure and hearing loss than other mining commodities. As part of a larger investigation into the effectiveness of hearing loss prevention programs, NIOSH personnel have collected area noise data at three surface stone, sand, and gravel operations. The operational characteristics of the mines, as well as their final consumer product, varied. Sound contour maps were developed from these data. These maps were provided to the participating mines with specific recommendations to modify worker movement throughout the mine or to modify job procedures to reduce miner noise dose. In addition, positive reinforcement was given regarding the use of signage, personal protective equipment (PPE), and worker training at these sites. This paper discusses the use of area noise data, especially sound contour maps, to improve hearing loss prevention programs at stone, sand, and gravel mine sites. The focus is on the integration of sound contour maps with other components of hearing loss prevention programs, especially training and the use of hearing protection, for increased effectiveness and efficiency. [Description provided by NIOSH]
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ISBN:9788487985317
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NIOSHTIC Number:nn:20057367 ; nn:20058417
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Citation:Inter-Noise 2019: Noise Control for a Better Environment, the 48th International Congress and Exposition on Noise Control Engineering: June 16-19, 2019, Madrid, Spain. Madrid, Spain: Spanish Acoustical Society, 2019 Jun; :1358
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Email:AAzman@cdc.gov
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Federal Fiscal Year:2019
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Peer Reviewed:False
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Main Document Checksum:urn:sha-512:4878c2883112e384076107d3155b6cd8fc9ef9a29f999414f6bdfd05e530f3071c77734c020f126c2d2050715facf79fde4ba8e5bfbee237bcd55aab68ba79b3
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