Residential past and future energy consumption: Potential savings and environmental impact

Residential past and future energy consumption: Potential savings and environmental impact

In order to identify main drivers behind changes in electricity and fuel consumptions in the household sector in Jordan, two empirical models are developed based on multivariate linear regression analysis. In addition, this paper analyzes and evaluates impacts of introducing some efficient measures,...

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Bibliographic Details
Published in:Renewable & sustainable energy reviews Vol. 13; no. 6; pp. 1262 - 1274
Main Authors: Al-Ghandoor, A., Jaber, J.O., Al-Hinti, I., Mansour, I.M.
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01-08-2009
Elsevier
Series:Renewable and Sustainable Energy Reviews
Subjects:
Applied sciences
Economic data
Electricity
Electricity Fuel GHG emissions Multivariate regression Jordan Residential sector
Energy
Energy economics
Energy policy
Exact sciences and technology
Fuel
General, economic and professional studies
GHG emissions
Jordan
Multivariate regression
Residential sector
Jordan
Asia
GHG emissions
Multivariate regression
Electricity
Jordan
Fuel
Residential sector
Energy consumption
Energy economy
Time series
Socioeconomic study
Multivariate analysis
Modeling
Energy savings
Energy conservation
Regression model
Lighting
Environment impact
Hot water production
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Summary:In order to identify main drivers behind changes in electricity and fuel consumptions in the household sector in Jordan, two empirical models are developed based on multivariate linear regression analysis. In addition, this paper analyzes and evaluates impacts of introducing some efficient measures, such as high efficiency lightings and solar water heating systems, in the housing stock, on the future fuel and electricity demands and associated reduction in GHG emissions. It was found that fuel unit price, income level, and population are the most important variables that affect demand on electrical power, while population is the most important variable in the case of fuel consumption. Obtained results proved that the multivariate linear regression models can be used adequately to simulate residential electricity and fuel consumptions with very high coefficient of determination. Without employing most effective energy conservation measures, electricity and fuel demands are expected to rise by approximately 100% and 23%, respectively within 10 years time. Consequently, associated GHG emissions resulting from activities within the residential sector are predicted to rise by 59% for the same period. However, if recommended energy management measures are implemented on a gradual basis, electricity and fuel consumptions as well as GHG emissions are forecasted to increase at a lower rate.
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ISSN:1364-0321
1879-0690
DOI:10.1016/j.rser.2008.09.008