Cyclists’ personal exposure to traffic-related air pollution and its influence on bikeability

•Influence of air quality on bikeability index was evaluated.•The proposed air quality sub-index involves cyclists’ exposure to PM2.5 and BC.•Open-source data, land-use regression models, and deep neural network were utilized.•Cyclists’ exposure to TRAP is a significant component of the bikeability index.•The proposed framework is useful for recommending cycling routes in cities. Previous studies on bikeability/cycling index have explored factors that influence cycling in cities, and developed indicators to characterize a bicycle-friendly environment. However, despite its strong influence on cycling behavior, cyclists’ exposure to traffic-related air pollution has been often disregarded. To close this knowledge gap, we propose a comprehensive bikeability index that comprises four sub-indices: accessibility, suitability, perceptibility, and prevailing air quality in the vicinity of cycling routes. We evaluate cyclists’ exposure to fine particulate matter and black carbon, and used open-source data, land-use regression models, deep neural networks and spatial analysis. The application of the proposed bikeability framework reveals that the inclusion of air quality makes a significant difference when calculating bikeability index in Singapore and hence it merits serious consideration. We believe that the newly developed framework will convince city planners to consider the importance of assessing cyclists’ exposure to airborne particles when planning cycling infrastructure.