In the ALPS project, ECE scientists and colleagues from Japan are researching ways to improve the representation of technological change in integrated assessment models (IAMs) to inform climate policy choices.

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The ALPS project (Alternative Pathways to sustainable development and climate Stabilization) is a collaboration between the ECE program at IIASA and the Research Institute for Innovative Technologies for the Earth (RITE), Japan.

The ALPS project aims at providing alternative plausible future scenarios and through quantification of multiple aspects of society on the assumptions that the real-world society is intrinsically consist of a wide range of values. This approach allows us to inform decision makers of more appropriate strategies toward sustainable development and climate stabilization from longer and wider perspectives. Another focus is to gain a clearer understanding of CO2 emissions structure on a national, sectoral and technological basis in order to deal with short and mid-term climate challenges. The scenarios on combinations of macro and micro views would generate further insights into climate change mitigation and sustainable development.

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ALPS project and the former TNT program at IIASA

Significant research progress was achieved in 2014. Prototype model formulations were consolidated by ENE’s Volker Krey into a novel multi-regional modeling framework; new and improved model parametrizations were also prepared based on extensive meta-analysis of expanding data and a comprehensive literature review and meta-analysis by Charlie Wilson and Arnulf Grubler. As part of the ALPS research project TNT was also able to update its unique data set underlying the research into the Scaling Dynamics of Energy Technologies (SD-ET).

An entirely new research field was also opened within the ALPS project in 2014: the improved modeling representation of decentralized consumer decisions. Unlike discrete, large-scale technology adoption decisions made by energy supply firms, energy-end use technologies and consumers “tick” quite differently. Millions of adoption decisions are made under imperfect information, vastly heterogeneous consumer preferences, and under presence of social network (or so-called peer) effects, which to date have eluded representation in IAMs.

To improve the state of the art in this field, a novel agent-based model of decentralized consumer technology adoption decisions was developed by TNT researcher Tieju Ma in collaboration with Arnulf Grubler [1]. An agent-based modeling strategy is particularly salient, as agent interactions are at the core of social network, or peer effects, to which companies, policymakers and energy and climate modelers have recently become increasingly attentive. Following the TNT research tradition of rapid prototyping of new modeling formulations, illustrative simulations were performed with the new model. Preliminary results suggest that the peer effect, while real, might be less significant in a transition to low carbon technologies on the consumer side, compared to traditional targets of centralized technology policy, such as technological performance and prices or technology standards.