Achieving Long-term Energy, Transport and Climate Objectives: Multidimensional Scenario Analysis and Modeling Within a Systems Level Framework

David L. McCollum

Institute of Transportation Studies, Working Paper Series from Institute of Transportation Studies, UC Davis

Abstract: Scenario analysis tools have emerged as a useful way to inform the policy debate by envisioning the potential evolution of energy systems over time. This dissertation describes three separate scenario analysis projects, each of which looks at the potential for a dramatic transformation of the energy system over the long term at varying geographic and sectoral scales. First, the 80in50 study analyzes the various pathways for making deep reductions in greenhouse gas emissions across all subsectors of U.S. transport system. The CA-TIMES project then takes this work to the next level by developing an energy-engineering-environmental-economic optimization model for the California energy system, in order to bring economics and dynamics into the analysis, as well as to study the interactions between transport and the various other energy producing and consuming sectors. Finally, a collaborative project with scientists at the International Institute for Applied Systems Analysis (IIASA) is described, in which a global systems engineering optimization model (MESSAGE) and a global climate model (MAGICC) are jointly utilized to evaluate synergies and trade-offs between a variety of energy objectives (climate mitigation, air pollution, energy security, and affordability)

Keywords: Engineering (search for similar items in EconPapers)
Date: 2011-02-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.escholarship.org/uc/item/5601w3pp.pdf;origin=repeccitec (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cdl:itsdav:qt5601w3pp

Access Statistics for this paper

More papers in Institute of Transportation Studies, Working Paper Series from Institute of Transportation Studies, UC Davis Contact information at EDIRC.
Bibliographic data for series maintained by Lisa Schiff ().