Statistical modelling for urban roads traffic noise levels

Abstract

Traffic noise is one of the most significant types of vehicular emissions that result in physical and psychological health effects on humans and is caused by an increase in vehicular ownership and urbanisation. The central business district (CBD) of Ondo has been exposed to persistent road traffic and commercial activities due to development and expansion of the economy, and this has led to an increase in traffic noise levels. Due to the increase in traffic volume, urbanisation, and population deterioration of road pavements in the CBD, it was hypothesised that noise related to traffic has increased and is above the permissible limit of the World Health Organisation in the study area. Monitoring noise levels by administrative agencies will help mitigate traffic noise intensity and aid in urban planning. This study examined the traffic noise levels and developed models for the CBD of Ondo, Nigeria. Adopting the empirical methods of the Calculation of Road Traffic noise (CoRTN) model and statistical Multiple Linear Regression (MLR) modelling approach, traffic noise models for the assessment of equivalent noise levels (Leq) at the CBD of Ondo were developed. Over 90% of the roadsides surveyed were above the world health organization's 70 dB(A) threshold. Correlation between CoRTN and MLR models demonstrated reliable efficiency relative to observed noise levels with an acceptable coefficient of determination (R2) values of 0.943 and 0.963, respectively. The deviation between the noise levels measured with the expected noise levels (MLR and CoRTN) varied, between 0.44 dB(A) and 2.09 dB(A) with an average mean difference of 0.37 dB(A) to 1.9 dB(A). These values are adjudged satisfactory since it is within the +/- 3.0 (dB)A allowed by the Federal Highway Administration (FHWA). The models are therefore robust and accurate in estimating the level of noise from road traffic for the study area.