PhD proposal: Modeling Canada’s decarbonization trajectories



Prof. O. Bahn (GERAD and HEC Montréal)

Prof. N. Mousseau (University of Montreal)



Climate change is one of the greatest challenges we face in the foreseeable future. To address the threats of climate change, three main strategies can be used: mitigation, adaptation and geoengineering. The first is to reduce GHG emissions. The second is to reduce the negative impacts of climate change. The third is to deliberately change the climate system.

The complexity of the links between the economy and the environment suggests the use of a global and systemic method such as integrated assessment (IA). This is an interdisciplinary approach that can be implemented using mathematical integrated assessment models (IAM) to determine optimal (climate) policies, such as the MERGE model (Manne et al., 1995) and its variants (e.g., Bahn and Kypreos, 2003; Bahn et al., 2011).

The objective of this PhD is to work on improving the AD-MERGE model (Bahn et al., 2019), implemented in the GAMS mathematical programming language (, along several axes: regional disaggregation of data to explicitly model Canada; updating the description of the energy sector to reflect recent technological advances; modeling approaches to remove carbon dioxide from the atmosphere… The new model will thus be able to explicitly take into account the three main strategies (mitigation, adaptation, and geoengineering) that can be used to deal with climate change. It will also allow the study of Canadian energy and climate policies in an international context.


The candidate must have statistical and programming skills. The home department for the PhD will depend on the student’s background.


Program start date

Summer or Fall 2022



Bahn, O., de Bruin, K.C., Fertel, C. (2019). “Will adaptation delay the transition to clean energy systems? An analysis with AD-MERGE”, The Energy Journal, Vol. 40, pp. 207-233.

Bahn, O., Edwards, N., Knutti, R., Stocker, T.F. (2011). “Energy policies avoiding a tipping point in the climate system”, Energy Policy, Vol. 39, pp. 334-348.

Bahn, O., Kypreos, S. (2003). “Incorporating different endogenous learning formulations in MERGE”, Int. J. of Global Energy Issues, Vol. 19, p. 333–358.

Manne, A.S., Mendelsohn, R., Richels, R.G. (1995). “MERGE: A model for evaluating regional and global effects of GHG reduction policies”, Energy Policy, Vol. 23, pp. 17–34.