Abstract
Energy models, such as Integrated Assessment Models (IAMs), are widely used in the forecasting of energy consumption and greenhouse gas (GHG) emissions and in the analysis and evaluation of the different GHG mitigation options. To construct efficient industry specific policies it is important to make careful estimations of the potentials for energy and GHG savings and the associated costs of mitigation that take into account the individual characteristics of the sector. However, many energy models are lacking on technological detail with many of them assessing the industry as a whole with only limited sub-sector division. In this analysis, the main parameters in modeling the cement industry, such as cement demand drivers, production technology representation and retrofitting options, were identified and a number of simple methodological modeling improvements were composed to assist the less detailed models incorporate more bottom-up sectoral information. Some of the improvements were implemented by two IAMs, POLES and IMAGE. Initial results obtained after the implementation of a number of suggested improvements showed the importance of using recent data that take into account recent industrial developments to construct the baseline and data that take into account regional differences.
Original language | English |
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Title of host publication | ECEEE Industrial Summer Study Proceedings |
Subtitle of host publication | Industrial Efficiency 2016 |
Publisher | European Council for an Energy-Efficient Economy |
Pages | 207-221 |
Number of pages | 15 |
Volume | 2016-September |
ISBN (Electronic) | 9789198048285 |
Publication status | Published - 2016 |
Event | 2016 ECEEE Industrial Summer Study: Industrial Efficiency - Kalkscheune, Berlin, Germany Duration: 12 Sept 2016 → 14 Sept 2016 |
Conference
Conference | 2016 ECEEE Industrial Summer Study: Industrial Efficiency |
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Country/Territory | Germany |
City | Kalkscheune, Berlin |
Period | 12/09/16 → 14/09/16 |
Keywords
- Cement industry
- Climate policy
- End-use demand
- Energy modelling
- Modelling