Abstract

This research aims at estimating a GHG emission inventory at the household level using completely disaggregate trip
data and taking into account all emitting modes. The impact of urban form (UF) and transit accessibility (TA)
characteristics on household level GHG emissions is then quantified and compared to the impact of the introduction
of emerging green technologies. Using a large and representative sample of household diaries, trip-level GHG
emissions are estimated by combining different sources of data (origin-destination (OD) survey data, vehicle fleet
characteristics, transit ridership data, etc.) and by using modelling tools (traffic assignment and GHGs models).
Moreover, UF and TA indicators are developed and combined to generate neighbourhood typologies. A simultaneous
equation modelling framework is then implemented to investigate the link between UF, TA, socio-demographics, and
travel GHGs, taking into account the well known “self-selection” issue. The potential impact of land use and transit supply strategies with emerging green technological scenarios is then compared. This is evaluated through the
modification of current fuel consumption rates with those provided by new technologies such as hybrid transit buses
and continuous improvement of vehicle fuel consumption rates. Our findings are consistent with the literature, more
specifically we have found that the built environment (BE) attributes are statistically significant (10% increase in
density, transit accessibility and land-use mix, results in 3.5 %, 5.8% and 2.5% reduction in GHG respectively),
number of workers and retirees at the household level play an important role in the contribution to GHG emissions
(102% increase by adding one worker and 51% decrease by adding a retiree to the household). Moreover, neighbourhood types represented by the combined effects of UF and TS have important effects on GHGs. Also it is found that by replacing transit fleet by electric trains and hybrid buses, the share of transit GHGs would decrease by 32%. With respect to the private motor-vehicle fleet, if current trends persist, the constant improvement of car fuel
consumption economy would reduce car GHGs by 7%. According to our results, the two most efficient strategies to reduce GHGs at the regional and household level seem to be the continuous fuel-efficiency improvement of the private motor-vehicle fleet and the increase of transit accessibility.