Socioeconomic Inequalities in PM_2.5 Exposure and Local Source Contributions at Community Scales Using Hyper-Localized Taxi-Based Mobile Monitoring in Xi’an, China

The relationship between the socioeconomic status (SES) and PM_2.5 exposure is rather inconclusive. We employed taxi-based measurements with 30 m resolution to characterize PM_2.5 exposure with local source contribution (PM_2.5 adjusted concentration) discerned for 2019 winter and 2020 summer, in Xi'an. A big data set comprising ∼6 × 10⁶ hourly PM_2.5 measurements and SES data from ∼5000 communities was utilized to examine the socioeconomic inequalities in community-level PM_2.5 exposure. Our results indicate that the inhabitants with lower SES are more likely to be disproportionately exposed compared to those with higher SES. At least 92% of disproportionately exposed inhabitants in rural regions reside in low SES areas, whereas a relatively smaller proportion (69-78%) reside in urban regions. The local source has a more profound impact on PM_2.5 exposure during summer than winter. The inhabitants in <i>polluted areas</i> and low PM_2.5 adjusted concentration areas accounted for 22% and 26% of total PM_2.5 exposure during the winter. However, inhabitants residing in low-concentration areas contributed only 12% of total exposure during summer while those polluted areas contributed 30%. These findings provide valuable insights into the relationship between community-level PM_2.5 exposure and SES, highlighting the need for more sophisticated air quality policies to alleviate socioeconomic inequalities in PM_2.5 exposure.