Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Cement Sector
Adoption of efficient end-use technologies is one of the key measures for reducing greenhouse gas (GHG) emissions. How to effectively analyze and manage the costs associated with GHG reductions becomes extremely important for the industry and policy makers around the world. Energy-climate (EC) models are often used for analyzing the costs of reducing GHG emissions for various emission-reduction measures, because an accurate estimation of these costs is critical for identifying and choosing optimal emission reduction measures, and for developing related policy options to accelerate market adoption and technology implementation. However, accuracies of assessing of GHG-emission reduction costs by taking into account the adoption of energy efficiency technologies will depend on how well these end-use technologies are represented in integrated assessment models (IAM) and other energy-climate models.
- Research Organization:
- Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US)
- Sponsoring Organization:
- Environmental Energy Technologies Division
- DOE Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1011103
- Report Number(s):
- LBNL-4395E
- Country of Publication:
- United States
- Language:
- English
Similar Records
Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the U.S. Pulp and Paper Sector
Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector
Comparing projections of industrial energy demand and greenhouse gas emissions in long-term energy models
Technical Report
·
Sun Jul 01 00:00:00 EDT 2012
·
OSTI ID:1173273
Development of Bottom-up Representation of Industrial Energy Efficiency Technologies in Integrated Assessment Models for the Iron and Steel Sector
Technical Report
·
Thu Sep 30 00:00:00 EDT 2010
·
OSTI ID:1008330
Comparing projections of industrial energy demand and greenhouse gas emissions in long-term energy models
Journal Article
·
Sun Jan 08 19:00:00 EST 2017
· Energy
·
OSTI ID:1353317