The increasing evidence base and public concern on the health effects of exposure to high levels of air pollution, combined with stricter environmental legislation, are forcing local governments to take drastic measures. One of the policy instruments, the low emission zone (LEZ), specifically targets a reduction in emissions from vehicles, a key source in urban environments. It is a contested instrument, with supporters who think it is a fair “polluter pays” instrument that especially benefits more deprived communities, while opponents fear an unequal social impact on people's accessibility and finances. This study wants to add a data-driven perspective to the discussion by simultaneously analysing the unequal exposure to air pollution and the unequal accessibility impact, in a comparative study of the LEZs in London and Brussels. The analysis combines a conventional multivariate regression analysis with a geographically weighted regression (GWR) modelling to define the local spatial variation in the relationships, which is of particular concern when considering an explicitly spatial problem and solution. The study shows that GWR is a promising method in distributional environmental justice research through identifying parts of the city where effects are more unequal, as such facilitating customized policy instruments and targeted support.