BACKGROUND: The recognition of road traffic noise as one of the main sources of environmental pollution has led to develop models that enable to predict noise level from fundamental variables. Traffic noise prediction models are required as aids for designing roads and highways. In addition, sometimes are used in the assessment of existing or envisaged changes in traffic noise conditions. In this paper a statistical modelling approach has been used for predicting road traffic noise in Iranian road conditions. METHODS: The study was performed during 2005-2006 in Hamadan city, in the west of Iran. The data set consisted of 282 noise measurements. The entire data set was utilized to develop a new model for Iranian condition using regression analysis. RESULTS: The developed model has twelve explanatory variables in order to achieve a proper fit for measured values of Leq (r2= 0.913). CONCLUSION: The proposed road traffic noise model can be effectively used as a decision support tools for prediction of traffic noise index of Leq(30min), in Iran's cities.
BACKGROUND: The recognition of road traffic noise as one of the main sources of environmental pollution has led to develop models that enable to predict noise level from fundamental variables. Traffic noise prediction models are required as aids for designing roads and highways. In addition, sometimes are used in the assessment of existing or envisaged changes in traffic noise conditions. In this paper a statistical modelling approach has been used for predicting road traffic noise in Iranian road conditions. METHODS: The study was performed during 2005-2006 in Hamadan city, in the west of Iran. The data set consisted of 282 noise measurements. The entire data set was utilized to develop a new model for Iranian condition using regression analysis. RESULTS: The developed model has twelve explanatory variables in order to achieve a proper fit for measured values of Leq (r2= 0.913). CONCLUSION: The proposed road traffic noise model can be effectively used as a decision support tools for prediction of traffic noise index of Leq(30min), in Iran's cities.