Index decomposition analysis for comparing emission scenarios: Applications and challenges

Abstract

As global action on climate change gathers momentum, an area of interest is what the world's greenhouse gas emission trajectory will be in the future and whether it can meet the emission targets set forth. To address these questions, emission scenarios which range from business-as-usual to deep decarbonization scenarios have been developed by researchers using different assessment models. An understanding of the sources of variations across the range of these emission trajectories is of interest for discussions, debates and policy planning. However, since these models often have different structures and input variables, comparisons of the results are not straightforward. In this regard, index decomposition analysis (IDA) has emerged as a tool to facilitate comparisons in a harmonized way. It allows differences in emissions over time or between models to be broken down based on a set of accepted driving factors. This paper reviews the literature and summarizes the features and challenges. A multi-level scenario decomposition framework is proposed to address the challenges which include how to quantify differences arising from the energy transformation sector, the adoption of renewable energy, carbon capture and storage, and bio-energy carbon capture and storage technologies. A case study and guidelines for implementing the framework are presented.