Development And Verification Of Traffic Noise Estimation Using Quarry Environmental Modeling (Qem)
Among the issues that are faced by quarries throughout the world is the emission of noise from the quarry that are potentially give the negative effects on the environmental society. The emission of the sound that come from the quarries is produced by lorries which is traffic noise. Sound emission t...
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| Format: | Monograph |
| Language: | English |
| Published: |
Universiti Sains Malaysia
2017
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| Online Access: | http://eprints.usm.my/52376/1/Development%20And%20Verification%20Of%20Traffic%20Noise%20Estimation%20Using%20Quarry%20Environmental%20Modeling%20%28Qem%29_Nuramizah%20Abdul%20Rahim_B1_2017.pdf http://eprints.usm.my/52376/ |
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| Summary: | Among the issues that are faced by quarries throughout the world is the emission of noise from the quarry that are potentially give the negative effects on the environmental society. The emission of the sound that come from the quarries is produced by lorries which is traffic noise. Sound emission that does not follow the standards level of noise will result in adverse effects on humans especially. This may result in emotional disturbances and also hearing loss. However, to prevent this phenomena, the responsible has made noise monitoring that is now been practiced around the quarry in Malaysia. This method is able to control the emission of excessive noise. Based on this study in Lumut, Perak, this thesis was to create a new prediction model of an algorithm that can predict the sound transmission and will be verified by a software called QEMs. Data for seven meteorological parameters were measured using the weather stations and noise was measured by using a noise measuring device which is KIMO DB 200 SLM. The data collected was analyzed using IBM SPSS 13.0 software package. The results of the analysis has been made by showed that R² value resulting from the statistical analysis was 0.044 which indicates that meteorological parameters do not have a strong correlation effects on the noise. While the R² resulting from QEMs is 0.790. It shows that the software QEMs is more efficient to use because it uses geological parameters such as distance, reflectance rate, vibration and others. |
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