The population and economic growth experienced by Canadian metropolitan areas in the past twenty years, has been associated with increased levels of car ownership and vehicle kilometres travelled leading to a deterioration of air quality and public health and an increase in greenhouse gas emissions. The need to modify urban growth patterns has motivated planning agencies in Canada to develop a broad range of policies aiming at achieving a more sustainable transportation sector. The challenge however, remains in the ability to test the effectiveness of proposed policy measures. This situation has led to a renewed interest in integrated land-use and transport models to support transport policy appraisal. This research is motivated by the need to improve transport policy appraisal through the use of integrated land-use and transport models linked with a range of sub-models that can reflect transport externalities. This research starts with an exploration of the transport policy environment in Canada through a questionnaire-based survey conducted with planners and policy-makers. The survey results highlight the need for tools reflecting the sustainability impacts of proposed policies. While the second part of this research explores sustainability indicators and recommends a set of social, economic, and environmental measures, linked with integrated land-use and transport models; effort is dedicated to estimate the environmental indicators as part of this thesis. As such, the third part of this research involves the development of an emission-dispersion-exposure modelling framework. The framework includes a suite of sub-models including an activity-based travel demand model (TASHA), an emission factor model (Mobile6.2C), a meteorological model (CALMET), and a dispersion model (CALPUFF). The framework is used to estimate link-based emissions of light-duty vehicles in the Greater Toronto Area under a base scenario for 2001. Dispersion of emissions is then conducted and linked with population in order to estimate exposure to air pollution.

The population and economic growth experienced by Canadian metropolitan areas in the past twenty years, has been associated with increased levels of car ownership and vehicle kilometres travelled leading to a deterioration of air quality and public health and an increase in greenhouse gas emissions. The need to modify urban growth patterns has motivated planning agencies in Canada to develop a broad range of policies aiming at achieving a more sustainable transportation sector. The challenge however, remains in the ability to test the effectiveness of proposed policy measures. This situation has led to a renewed interest in integrated land-use and transport models to support transport policy appraisal. This research is motivated by the need to improve transport policy appraisal through the use of integrated land-use and transport models linked with a range of sub-models that can reflect transport externalities. This research starts with an exploration of the transport policy environment in Canada through a questionnaire-based survey conducted with planners and policy-makers. The survey results highlight the need for tools reflecting the sustainability impacts of proposed policies. While the second part of this research explores sustainability indicators and recommends a set of social, economic, and environmental measures, linked with integrated land-use and transport models; effort is dedicated to estimate the environmental indicators as part of this thesis. As such, the third part of this research involves the development of an emission-dispersion-exposure modelling framework. The framework includes a suite of sub-models including an activity-based travel demand model (TASHA), an emission factor model (Mobile6.2C), a meteorological model (CALMET), and a dispersion model (CALPUFF). The framework is used to estimate link-based emissions of light-duty vehicles in the Greater Toronto Area under a base scenario for 2001. Dispersion of emissions is then conducted and linked with population in order to estimate exposure to air pollution.