Little work has accounted for congestion, using data that reflects driving patterns, traffic volume, and speed, to examine the association between traffic emissions and human health. In this study, we performed a health risk assessment of PM2.5 emissions during congestion periods in the Greater Toronto and Hamilton Area (GTHA), Canada.

Specifically, we used a micro-level approach that combines the Stochastic User Equilibrium Traffic Assignment Algorithm with a MOVES emission model to estimate emissions considering congestion conditions. Subsequently, we applied a concentration-response function to estimate PM2.5-related mortality, and the associated health costs. Our results suggest that traffic congestion has a substantial impact on human health and the economy in the GTHA, especially at the most congested period (7:00 am). Considering daily mortality, our results showed an impact of 206 (boundary test 95%: 116; 297) and 119 (boundary test 95%: 67; 171) deaths per year (all-cause and cardiovascular mortality, respectively). The economic impact from daily mortality is approximately $1.3 billion (boundary test 95%: 0.8; 1.9), and $778 million (boundary test 95%: 478; 981), for all-cause and cardiovascular mortality, respectively. Our study can guide reliable projections of transportation and air pollution levels, improving the capability of the medical community to prepare for future trends.

Paper in Environment International at