A Practical Approach to Predict the “in-situ” Noise Absorption of Porous Pavement Materials

Abstract

Noise pollution has been identified as an important issue for public health. The WHO classified noise pollution as the second‐worst environmental cause of illness, behind only ultra‐fine particulate matter (PM2.5) air pollution. Among different transportation means, the road traffic noise is considered as the major cause of harm and discomfort, and the reason behind this is the increasing population growth and rapid urbanization. To reduce the noise, engineers are working on innovation of tires and pavement surface with an aim of eliminating the noise problem at its source.

To investigate the effect of materials on the pavement noise reduction, a research program was conducted that included extensive literature survey on the fundamentals of pavement noise, data collection and modeling. Through out of this work the JCAL (Johnson-Champoux-Allard-Lafarge) empirical model was selected and successfully verified, as a good tool for predicting the noise absorption of materials from simple laboratory measurements.  Consecutively, the Hamet equation was identified to bridge the JCAL modeled noise absorption coefficient well with the in-situ statistical pass-by noise measurement.