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| 1 |
ID:
115668
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| Publication |
2012.
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| Summary/Abstract |
Index decomposition analysis based on economic output is frequently employed to provide an indication of energy intensity trends in industry. Additionally, composite energy efficiency indicators, calculated using physical output, are used to give a more accurate view of energy efficiency progress. Both approaches are commonly presented in one study but often with a different mathematical basis for each. This may lead to inconsistent results. We demonstrate using practical case studies that when all physical and economic output data are available for industry sub-sectors, these can be combined in a single decomposition analysis that provides an energy efficiency indicator based on physical production and an indicator of the influence of structural change based on value added. Using the same methodology for both results ensures that the results are consistent and provides insights into the effects of changing prices of goods on aggregate energy intensity. In the case studies examined, falling unit values of industrial goods produced over time tend to increase the energy intensity of industry.
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| 2 |
ID:
111397
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| Publication |
2012.
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| Summary/Abstract |
To-date, decomposition analysis has been widely used at the macro-economic level and for in-depth analyses of the industry and transport sectors; however, its application in the residential sector has been rare. This paper uses the Log-Mean Divisia Index I (LMDI-I) methodology to decompose gas consumption trends in the gas-connected residential sector in Ireland from 1990 to 2008, which despite an increasing number of energy efficiency policies, experienced total final consumption growth of 470%. The analysis decomposes this change in gas consumption into a number of effects, examining the impact over time of market factors such as a growing customer base, varying mix of dwelling types, changing share of vacant dwellings, changing size of new dwellings, the impact of building regulations policy and other factors such as the weather. The analysis finds the most significant effects are changing customer numbers and changing intensity; the analysis also quantifies the impact of building regulations and compares it with other effects such as changing size of new dwellings. By comparing the historical impact on gas consumption of policy factors and non-policy factors, this paper highlights the challenge for policy-makers in achieving overall energy consumption reduction.
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