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Thesis title: Integrated Decision Support Framework for the Assessment of Oil Palm Bioenergy for Greenhouse Gas Mitigation: Malaysia-TIMES Energy Model
Primary supervisor: Dr. Gabrial Anandarajah
Secondary supervisor: Prof. Paul Ekins
Sponsor: Commonwealth Scholarship Commission in the UK
Starting date: Jan 2014
Completion date: Dec 2016
Bioenergy has a significant greenhouse gas (GHG) mitigation potential, provided that the resources are developed sustainably and that efficient bioenergy systems are used. As biomass resource potentials exhibit strong regional differences in bioenergy systems (due to region-specific influences such as bioenergy feedstock, site-specific climate and ecosystems, management conditions, production pathways, and end use), the aim of this research is to undertake a regional assessment on oil palm bioenergy for GHG mitigation in Malaysia. The first step towards this objective is developing the Malaysia-TIMES (The Integrated MARKAL EFOM System) model and to assess the role of bioenergy, in particular in the electricity generation and transportation sectors in long term decarbonisation scenarios (2012-2050). Secondly, taking into account the two primary sources of GHG emissions that could influence climate change (from the production and use of bioenergy) i.e. (i) emissions from the bioenergy production chain (including non-CO2 GHG such as N2O, CH4 and fossil GHG emissions from auxiliary energy use); and (ii) GHG emission related to changes in biospheric carbon stocks often caused by associated Land Use Change (LUC), an integrated energy assessment model will be developed incorporating the methodological details of a LCA-like method with the Malaysia-TIMES model. This could offer as an option to address the current methodological limitation associated with the assumption of carbon neutrality in bioenergy assessment using energy systems modeling. In addition, although this approach is illustrated for oil palm bioenergy, techniques may be applicable elsewhere with different bioenergy crops when suitable data are available.