Arif Susanto, D. Setyawan, Firman Setiabudi, Y. M. Savira, A. Listiarini, E. K. Putro, A. F. Muhamad, J. C. Wilmot, D. Zulfakar, Prayoga Kara, Iting Shofwati, Sodikin Sodikin, M. Tejamaya
{"title":"基于gis的机械化选矿噪声制图","authors":"Arif Susanto, D. Setyawan, Firman Setiabudi, Y. M. Savira, A. Listiarini, E. K. Putro, A. F. Muhamad, J. C. Wilmot, D. Zulfakar, Prayoga Kara, Iting Shofwati, Sodikin Sodikin, M. Tejamaya","doi":"10.1515/noise-2021-0001","DOIUrl":null,"url":null,"abstract":"Abstract Monitoring workers’ exposure to occupational noise is essential, especially in industrial areas, to protect their health. Therefore, it is necessary to collect information on noise emitted by machines in industries. This research aims to map the noise from mechanized mineral ore industry using the kriging interpolation method, and ArcGIS 10.5.1 to spatially process and analyze data. The experimental calculation result of the semivariogram showed a 0.83 range value, with an essential parameter of 1.75 sill and a spherical total theoretical model. The result shows that the main machines with the highest power consumption and the Leq value are located in the southwest position of the sampled areas with a noise map-projected to assess the workers’ noise exposure level. In conclusion, the study found that the highest noise level was generated ranged from 88 to 97 dBA and contributed to the whole sound pressure level at certain positions.","PeriodicalId":44086,"journal":{"name":"Noise Mapping","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/noise-2021-0001","citationCount":"5","resultStr":"{\"title\":\"GIS-based mapping of noise from mechanized minerals ore processing industry\",\"authors\":\"Arif Susanto, D. Setyawan, Firman Setiabudi, Y. M. Savira, A. Listiarini, E. K. Putro, A. F. Muhamad, J. C. Wilmot, D. Zulfakar, Prayoga Kara, Iting Shofwati, Sodikin Sodikin, M. Tejamaya\",\"doi\":\"10.1515/noise-2021-0001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Monitoring workers’ exposure to occupational noise is essential, especially in industrial areas, to protect their health. Therefore, it is necessary to collect information on noise emitted by machines in industries. This research aims to map the noise from mechanized mineral ore industry using the kriging interpolation method, and ArcGIS 10.5.1 to spatially process and analyze data. The experimental calculation result of the semivariogram showed a 0.83 range value, with an essential parameter of 1.75 sill and a spherical total theoretical model. The result shows that the main machines with the highest power consumption and the Leq value are located in the southwest position of the sampled areas with a noise map-projected to assess the workers’ noise exposure level. In conclusion, the study found that the highest noise level was generated ranged from 88 to 97 dBA and contributed to the whole sound pressure level at certain positions.\",\"PeriodicalId\":44086,\"journal\":{\"name\":\"Noise Mapping\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1515/noise-2021-0001\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Noise Mapping\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/noise-2021-0001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ACOUSTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Noise Mapping","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/noise-2021-0001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ACOUSTICS","Score":null,"Total":0}
GIS-based mapping of noise from mechanized minerals ore processing industry
Abstract Monitoring workers’ exposure to occupational noise is essential, especially in industrial areas, to protect their health. Therefore, it is necessary to collect information on noise emitted by machines in industries. This research aims to map the noise from mechanized mineral ore industry using the kriging interpolation method, and ArcGIS 10.5.1 to spatially process and analyze data. The experimental calculation result of the semivariogram showed a 0.83 range value, with an essential parameter of 1.75 sill and a spherical total theoretical model. The result shows that the main machines with the highest power consumption and the Leq value are located in the southwest position of the sampled areas with a noise map-projected to assess the workers’ noise exposure level. In conclusion, the study found that the highest noise level was generated ranged from 88 to 97 dBA and contributed to the whole sound pressure level at certain positions.
期刊介绍:
Ever since its inception, Noise Mapping has been offering fast and comprehensive peer-review, while featuring prominent researchers among its Advisory Board. As a result, the journal is set to acquire a growing reputation as the main publication in the field of noise mapping, thus leading to a significant Impact Factor. The journal aims to promote and disseminate knowledge on noise mapping through the publication of high quality peer-reviewed papers focusing on the following aspects: noise mapping and noise action plans: case studies; models and algorithms for source characterization and outdoor sound propagation: proposals, applications, comparisons, round robin tests; local, national and international policies and good practices for noise mapping, planning, management and control; evaluation of noise mitigation actions; evaluation of environmental noise exposure; actions and communications to increase public awareness of environmental noise issues; outdoor soundscape studies and mapping; classification, evaluation and preservation of quiet areas.