Modelling long-term industry energy demand and CO<sub>2</sub> emissions in the system context using REMIND (version 3.1.0)
<p>This paper presents an extension of industry modelling within the REMIND integrated assessment model to industry subsectors and a projection of future industry subsector activity and energy demand for different baseline scenarios for use with the REMIND model. The industry sector is the lar...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2024-03-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/17/2015/2024/gmd-17-2015-2024.pdf |
| _version_ | 1797271199264276480 |
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| author | M. Pehl F. Schreyer G. Luderer |
| author_facet | M. Pehl F. Schreyer G. Luderer |
| author_sort | M. Pehl |
| collection | DOAJ |
| description | <p>This paper presents an extension of industry modelling within the REMIND integrated assessment model to industry subsectors and a projection of future industry subsector activity and energy demand for different baseline scenarios for use with the REMIND model. The industry sector is the largest greenhouse-gas-emitting energy demand sector and is considered a mitigation bottleneck. At the same time, industry subsectors are heterogeneous and face distinct emission mitigation challenges. By extending the multi-region, general equilibrium integrated assessment model REMIND to an explicit representation of four industry subsectors (cement, chemicals, steel, and other industry production), along with subsector-specific carbon capture and sequestration (CCS), we are able to investigate industry emission mitigation strategies in the context of the entire energy–economy–climate system, covering mitigation options ranging from reduced demand for industrial goods, fuel switching, and electrification to endogenous energy efficiency increases and carbon capture. We also present the derivation of both activity and final energy demand trajectories for the industry subsectors for use with the REMIND model in baseline scenarios, based on short-term continuation of historic trends and long-term global convergence. The system allows for selective variation of specific subsector activity and final energy demand across scenarios and regions to create consistent scenarios for a wide range of socioeconomic drivers and scenario story lines, like the Shared Socioeconomic Pathways (SSPs).</p> |
| first_indexed | 2024-03-07T13:58:20Z |
| format | Article |
| id | doaj.art-a8069764a4c8452caf035d888a8eb351 |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-03-07T13:58:20Z |
| publishDate | 2024-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-a8069764a4c8452caf035d888a8eb3512024-03-07T07:03:17ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032024-03-01172015203810.5194/gmd-17-2015-2024Modelling long-term industry energy demand and CO<sub>2</sub> emissions in the system context using REMIND (version 3.1.0)M. PehlF. SchreyerG. Luderer<p>This paper presents an extension of industry modelling within the REMIND integrated assessment model to industry subsectors and a projection of future industry subsector activity and energy demand for different baseline scenarios for use with the REMIND model. The industry sector is the largest greenhouse-gas-emitting energy demand sector and is considered a mitigation bottleneck. At the same time, industry subsectors are heterogeneous and face distinct emission mitigation challenges. By extending the multi-region, general equilibrium integrated assessment model REMIND to an explicit representation of four industry subsectors (cement, chemicals, steel, and other industry production), along with subsector-specific carbon capture and sequestration (CCS), we are able to investigate industry emission mitigation strategies in the context of the entire energy–economy–climate system, covering mitigation options ranging from reduced demand for industrial goods, fuel switching, and electrification to endogenous energy efficiency increases and carbon capture. We also present the derivation of both activity and final energy demand trajectories for the industry subsectors for use with the REMIND model in baseline scenarios, based on short-term continuation of historic trends and long-term global convergence. The system allows for selective variation of specific subsector activity and final energy demand across scenarios and regions to create consistent scenarios for a wide range of socioeconomic drivers and scenario story lines, like the Shared Socioeconomic Pathways (SSPs).</p>https://gmd.copernicus.org/articles/17/2015/2024/gmd-17-2015-2024.pdf |
| spellingShingle | M. Pehl F. Schreyer G. Luderer Modelling long-term industry energy demand and CO<sub>2</sub> emissions in the system context using REMIND (version 3.1.0) Geoscientific Model Development |
| title | Modelling long-term industry energy demand and CO<sub>2</sub> emissions in the system context using REMIND (version 3.1.0) |
| title_full | Modelling long-term industry energy demand and CO<sub>2</sub> emissions in the system context using REMIND (version 3.1.0) |
| title_fullStr | Modelling long-term industry energy demand and CO<sub>2</sub> emissions in the system context using REMIND (version 3.1.0) |
| title_full_unstemmed | Modelling long-term industry energy demand and CO<sub>2</sub> emissions in the system context using REMIND (version 3.1.0) |
| title_short | Modelling long-term industry energy demand and CO<sub>2</sub> emissions in the system context using REMIND (version 3.1.0) |
| title_sort | modelling long term industry energy demand and co sub 2 sub emissions in the system context using remind version 3 1 0 |
| url | https://gmd.copernicus.org/articles/17/2015/2024/gmd-17-2015-2024.pdf |
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