On a regular basis, the city of Montreal publishes the annual territorial greenhouse gas (GHG) emission inventory for the island of Montreal. The objective of such an inventory is to quantify and sum up all GHG emissions occurring on the territory during the year. The inventory is divided into sectors: transportation, industrial sources (combustion and other emissions), commercial and institutional sources, residential sources, waste management, and agriculture, forestry and other land uses. The transportation sector is the main contributor as it is responsible for around 40% of GHG emissions.
GHG emission inventories are important tools to identify the main contributing activities and to measure the global efficiency of GHG emission reduction plans. However, they involve high uncertainties as appropriate data is not always available and several assumptions must be made. Indeed, in an ideal world, each movement of a person producing GHG emissions whether they use cars, trucks, buses, motorcycles, etc. occurring on the territory during the year would be recorded with the distance traveled (by the person) and the speed of their movement, and then identify the means of transport with some assumptions, then multiplied by a specific emission factor (mass of GHG emitted per km) according to the type of vehicle. Such data about the movement of vehicles is currently not available, and GHG emission inventories rely on very incomplete and approximate data. Hence, the objective of this research project is to use data provided through the data ofTajet MTL Insights to record people’s movements on the island of Montréal during one month in order to provide more accurate estimates of the contribution of the transportation sector to GHG emissions.
The results show that there is a major difference between the quantity of GHGs emitted by the road transportation sector calculated by the City of Montréal and that calculated using the methodology developed in this study. This difference is due to the different uncertainties and approximations made in the two approaches. However, our research presents a methodology that makes it possible to improve the spatial and temporal resolution of GHG emissions and to analyze the effects of various factors on these emissions, such as climatic conditions. In addition, this study presents room for improvement to eliminate uncertainties in the results and to build an accurate and precise inventory of road transportation GHG emissions.
| Date | 31 Aug 2020 |
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| Original language | French |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Annie Levasseur (Supervisor) |
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Labidi, A. (Author),
Levasseur (Supervisor),
31 Aug 2020Student thesis: Master's thesis › Master in Engineering: Environmental Engineering