Urban noise, especially from road traffic, is a significant public health hazard that affects vulnerable urban populations disproportionately and exacerbates transport inequality. Transport noise exposure remains unevenly distributed due to structural disparities in transportation and land use planning. This study establishes modelling methods for city-level traffic noise modelling employing an automated traffic planning approach - Rapidex. Using Rapidex traffic data, noise levels are modelled for cities across Europe based on traffic volume, road type and vehicle composition at link and district/zone level. The method using open-source pervasive data sources allows city-to-city comparative analysis at the global scale. Disparities in noise exposure are assessed by computing mean excess noise and Gini equality index for seven cities across Europe. The selected cities vary in population size, terrain, transport mode share, and noise regulatory contexts, enabling robust comparative analysis. District/Zone-level maximum and mean noise exposure are assessed to identify zones and districts with excess noise, high-exposure areas and noise disparities across the cities. Results reveal significant intra-urban inequalities, with Amsterdam exhibiting the highest disparity (Gini = 0.176) , followed by Belfast, Berlin, and Dresden. Zurich, by contrast, demonstrates comparatively lower inequality ( E Z (%) = 20.24) . These findings underscore the importance of integrating equity considerations into noise mitigation policies and transport planning. The proposed approach offers a transferable framework for evaluating environmental justice in urban mobility systems globally.
Nayab et al. (Thu,) studied this question.