Louis-François Tétreault1, Naveen Eluru2, Marianne Hatzopoulou3, Patrick Morency4, Celine Plante5, Catherine Morency6, Frederic Reynaud7, Maryam Shekarrizfard3, Yasmin Shamsunnahar2, Ahmadreza Faghih Imani7, Louis Drouin4, Anne Pelletier5, Sophie Goudreau5, Francois Tessier5, Lise Gauvin8, Audrey Smargiassi9. 1. Department of Environmental and Occupational Health, school of Public Health, University of Montreal, Montreal, Quebec, Canada; Montreal's Public Health Department, Montreal, Quebec, Canada. 2. Department of Civil, Environmental and Construction Engineering University of Central Florida, FL, USA. 3. Department of Civil Engineering University of Toronto, Toronto, Ontario, Canada. 4. Montreal's Public Health Department, Montreal, Quebec, Canada; Department of social and preventive medicine, school of Public Health, University of Montreal, Montreal, Quebec, Canada. 5. Montreal's Public Health Department, Montreal, Quebec, Canada. 6. Département des génies civil, géologique et des mines, École Polytechnique de Montréal, Montreal, Quebec, Canada. 7. Department of Civil Engineering and Applied Mechanics, McGill University, Montreal, Quebec, Canada. 8. Department of social and preventive medicine, school of Public Health, University of Montreal, Montreal, Quebec, Canada. 9. Department of Environmental and Occupational Health, school of Public Health, University of Montreal, Montreal, Quebec, Canada; Institut national de santé publique du Québec, Montreal, Quebec, Canada. Electronic address: audrey.smargiassi@umontreal.ca.
Abstract
BACKGROUND: Since public transit infrastructure affects road traffic volumes and influences transportation mode choice, which in turn impacts health, it is important to estimate the alteration of the health burden linked with transit policies. OBJECTIVE: We quantified the variation in health benefits and burden between a business as usual (BAU) and a public transit (PT) scenarios in 2031 (with 8 and 19 new subway and train stations) for the greater Montreal region. METHOD: Using mode choice and traffic assignment models, we predicted the transportation mode choice and traffic assignment on the road network. Subsequently, we estimated the distance travelled in each municipality by mode, the minutes spent in active transportation, as well as traffic emissions. Thereafter we estimated the health burden attributed to air pollution and road traumas and the gains associated with active transportation for both the BAU and PT scenarios. RESULTS: We predicted a slight decrease of overall trips and kilometers travelled by car as well as an increase of active transportation for the PT in 2031 vs the BAU. Our analysis shows that new infrastructure will reduce the overall burden of transportation by 2.5 DALYs per 100,000 persons. This decrease is caused by the reduction of road traumas occurring in the inner suburbs and central Montreal region as well as gains in active transportation in the inner suburbs. CONCLUSION: Based on the results of our study, transportation planned public transit projects for Montreal are unlikely to reduce drastically the burden of disease attributable to road vehicles and infrastructures in the Montreal region. The impact of the planned transportation infrastructures seems to be very low and localized mainly in the areas where new public transit stations are planned.
BACKGROUND: Since public transit infrastructure affects road traffic volumes and influences transportation mode choice, which in turn impacts health, it is important to estimate the alteration of the health burden linked with transit policies. OBJECTIVE: We quantified the variation in health benefits and burden between a business as usual (BAU) and a public transit (PT) scenarios in 2031 (with 8 and 19 new subway and train stations) for the greater Montreal region. METHOD: Using mode choice and traffic assignment models, we predicted the transportation mode choice and traffic assignment on the road network. Subsequently, we estimated the distance travelled in each municipality by mode, the minutes spent in active transportation, as well as traffic emissions. Thereafter we estimated the health burden attributed to air pollution and road traumas and the gains associated with active transportation for both the BAU and PT scenarios. RESULTS: We predicted a slight decrease of overall trips and kilometers travelled by car as well as an increase of active transportation for the PT in 2031 vs the BAU. Our analysis shows that new infrastructure will reduce the overall burden of transportation by 2.5 DALYs per 100,000 persons. This decrease is caused by the reduction of road traumas occurring in the inner suburbs and central Montreal region as well as gains in active transportation in the inner suburbs. CONCLUSION: Based on the results of our study, transportation planned public transit projects for Montreal are unlikely to reduce drastically the burden of disease attributable to road vehicles and infrastructures in the Montreal region. The impact of the planned transportation infrastructures seems to be very low and localized mainly in the areas where new public transit stations are planned.