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Presentation . 2026
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2026
License: CC BY
Data sources: Datacite
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Energy Demand Projection For Manufacturing Subsector In Ethiopia Using MAED Tools

Authors: TEREFA, SISAY SEBOKA; BUTA, ALIYI IDRIS;

Energy Demand Projection For Manufacturing Subsector In Ethiopia Using MAED Tools

Abstract

Abstract This study applies the Model for Analysis of Energy Demand (MAED) to evaluate long-term energy demand and emissions trajectories for the manufacturing subsector under alternative development scenarios up to 2051. The analysis is based on moderate economic growth of 7.2%, consistent with recent historical trends, and a gradual expansion of manufacturing output aligned with existing industrial parks, alongside the planned expansion of industrial parks and manufacturing clusters. Under these assumptions, the manufacturing GDP value-added (VA) share increases to 83% by 2051, reflecting sustained industrialization. Three scenarios are examined. In the Business-as-Usual (BAU) scenario, manufacturing growth continues with limited structural change, leading to rising energy demand and emissions. The High Industrial Growth (HIG) scenario results in a 40.40% increase in fossil fuel demand, corresponding to an estimated 40.40% increase in CO₂ emissions, assuming unchanged fuel mix and efficiency, highlighting significant decarbonisation risks. In contrast, the Low-Carbon Transition (LCT) scenario targets emission-free energy demand by 2051, achieved through a 25% increase in electricity consumption and a 25% reduction in fossil fuel use. This transition is supported by process optimization, deployment of energy-efficient machinery, and improved industrial energy management. The MAED results demonstrate that while high industrial growth can substantially increase emissions, electrification, efficiency improvements, and optimized production processes can effectively decouple manufacturing growth from fossil fuel dependence. The study underscores the importance of integrated energy and industrial planning to achieve long-term decarbonisation of the manufacturing subsector.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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