Impact of traffic policy on travel population exposure during heavy pollution episodes: A Chengdu case study

Abstract

Previous studies on exposure have often omitted the impact of travelers' response to policies during air pollution, particularly for multi-modal traffic system. To address this gap, we investigate the population exposure of three modes (cars, buses, and metro) during morning rush hour in Chengdu, China, amidst the implementation of contingent traffic-related policies during heavy pollution episodes with elevated background pollutant concentrations of PM2.5. We introduce a trip-based average population exposure model to evaluate travel population exposure. This model allows to calculate the exposure for all modes, and assess its changes owing to modal shifts. Additionally, we propose a traffic-modal exposure coefficient to quantify PM2.5 exposure disparities among traffic modals. The results indicate that: the population exposure of total travelers experiences a growth effect, influenced not only by increased pollutant concentration but also by modal shift. Lastly, the inside-to-outside ratio, bus waiting time, and attractiveness of active traveler are discussed for more policy implications. This study not only offers a quantitative model to uncover potential overestimation of the effect of policies on reducing exposure if failure to consider modal shift, but also provides valuable insights for managing exposure growth to safeguard health of urban residents and promote sustainable development of cities.