The manufacturing industry is responsible for a third of the worldâs final energy use. Some of the energy is generated from carbon rich sources and the energy supply mix within each country is assigned a carbon emission factor. With the urgent and growing challenges of climate change, the interest in reducing energy consumption within manufacturing and reaching carbon neutrality at the process, factory, sub-sector and industry level has been growing. Complexity and diversity in the makeup of manufacturing has presented a challenge to existing energy analysts to recommend best-practice and sector-wide policies. This is compounded by the dichotomy of growth and consumption reduction. To reduce energy consumption at industry level it is important to understand the factors that drive energy consumption, model how growth (more wealth creation) can be realised while reducing energy consumption and to develop metrics to help focus on areas for improvement. In this PhD index decomposition analysis was used to break down the changes in aggregate energy consumption and attribute them to production, structure, and energy intensity effects. This was done for four countries enabling learning across multiple datasets and economies. When industry implements new and more energy-efficient technology this may not automatically lead to decrease in aggregate energy consumption. This rebound effect was modelled based on a new approach which captures vectors of change in energy effectiveness (economic-thermodynamic efficiency) alongside changes in production output. This new tool is useful in deriving targets for reducing aggregate energy consumption in clean growth. The third major contribution of the Thesis was a new index of energy effectiveness developed to assess the energy efficiency at the sub-sectoral level. This was necessary because the data had shown that the sub-sectors with the smallest share of aggregate energy consumption in an industry were the least effective in energy use. The index of energy effectiveness was developed to provide a generic tool that can be used to benchmark sectors and identify potential, though not absolute improvements. The metrics developed in this PhD has been applied to assessing energy consumption in manufacturing sectors and sub-sectors of South Africa, UK, Canada, Malaysia and India. However, the research horizon is limitless, and the metrics as presented here can be potentially applied to energy, resources, emission and waste stream analysis.
Date of Award | 31 Dec 2023 |
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Original language | English |
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Awarding Institution | - The University of Manchester
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Supervisor | Carl Diver (Supervisor) & Paul Mativenga (Supervisor) |
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- energy modelling
- manufacturing
- sustainability
- energy consmption
Metrics for Understanding Aggregate Energy Consumption in Manufacturing
Kan, H. L. K. (Author). 31 Dec 2023
Student thesis: Phd