Spatial disparities and environmental justice in PM_2.5 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 PM_2.5 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.