Spatial disparities and environmental justice in PM2.5 exposure among urban E-bike Commuters:A case study of Changsha.

Amid increasing residential segregation, disparities in resource allocation and environmental health faced by vulnerable groups have drawn widespread attention. Electric bicycles (E-bikes), favored by low-income populations due to their affordability, convenience, and eco-friendliness, have gained widespread popularity, particularly in China. However, whether E-bikes can reduce daily air pollution exposure and mitigate associated environmental health inequalities remains unclear. This study integrates land use regression and space syntax to quantify spatial disparities in PM2.5 exposure among E-bike commuters in Changsha, China. Results show that by broadening route options, E-bikes reduced the exposure difference between behavior-based and fast routes to 4.2 % (0.32 μg) within a 15-min commuting isochrone, down from 7.5 % (0.9 μg) for walking. Yet structural disparities persist, over 30 % of high-exposure clusters are concentrated in gated-community-dominated new towns, and low-income neighborhoods exhibit stronger exposure-built environment correlations (Pearson's |r| = 0.32-0.51, p < 0.01). Inadequate infrastructure (e.g., roads, green space) in these areas limits health benefits from route optimization. Moreover, about 50 % of low-income commuters exhibit significantly higher exposure increments than other groups under equivalent additional time costs when selecting behavior-based routes, suggesting greater potential health gains could be achieved if they adopt low-exposure routes. We propose tailored interventions, such as prioritizing built-environment upgrades in disadvantaged communities and deploying real-time exposure-aware navigation. Methodologically, our dynamic simulation of socioeconomic heterogeneity and actual route choices advances the assessment of exposure, offering a targeted framework for environmental health governance in high-density cities.