Urban road traffic noise is a serious environmental issue that directly affects people’s health and quality of life in big cities. This study statistically investigates the relationship between traffic noise levels and pavement surface condition on urban roads with rigid pavement in Najaf City, Iraq. Field data were collected on three urban road segments with Pavement Condition Index (PCI) values of 65, 77, and 86, representing fair, good, and very good conditions. A total of 432 observations were obtained during daytime peak periods (06:00–18:00) under dry weather. At each observation, traffic noise levels (dB) were measured at the roadside using a calibrated Class 1 sound level meter in accordance with ISO 1996-1:2016. Concurrently, traffic volume and vehicle classification were extracted from video recordings; vehicle speeds were derived from time–distance analysis and checked against accelerometer readings; and PCI values were computed from ASTM D6433 condition surveys supported by drone imagery. The statistical analysis comprised analysis of covariance (ANCOVA), Spearman’s rank correlation, and linear regression modelling. The results indicate that pavement condition significantly affects noise levels, with lower PCI values associated with higher noise levels. Although the bivariate correlation between speed and noise is modest (r ≈ 0.3), the ANCOVA results show that pavement condition moderates the speed–noise relationship. The findings highlight the importance of incorporating pavement quality indicators, such as PCI, into local noise prediction models to support more reliable urban planning and pavement management decisions.
