Reducing Exposures to Traffic-Related Air Pollution in Urban Areas: Regional Planning, Neighborhood Design, and Individual Behavior

Abstract

The assessment of exposure to traffic-related air pollution has seen advances along various dimensions. Air pollution dispersion models with fine spatial resolution and ability to reflect near-road air quality in street canyons, have made possible the development of exposure surfaces associated with strategic long-range scenarios affecting land-use and transportation in urban areas. Meanwhile, personal monitoring and GPS-enabled applications have motivated the development of a wide range of tools intended to inform users of their own exposure and ways to reduce it. While scientific evidence points to the success of these tools in identifying measures, at the policy or personal level, able to reduce air pollution exposures, there much left to learn about the impact of these tools on human behavior. How do policy makers use scenario-based information on air quality to formulate policy decisions? And how do individuals respond to air quality information provided to them? Are there individuals more inclined to respond to exposure reduction advice in a positive manner? This presentation will detail how high resolution air pollution data has informed a range of interventions to reduce traffic-related air pollution exposures in Canadian cities, from clean routes applications to large investments in transportation infrastructures and urban design. New evidence will also be presented from a stated-preference experiment examining how air pollution information impacts individual behavior.