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Analysis of Jordan's industrial energy intensity and potential mitigations of energy and GHGs emissions

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  • Al-Ghandoor, A.

Abstract

This paper aims to identify the main drivers behind energy intensity changes of the Jordanian industrial sector and to introduce the impact of energy efficient measures within the Jordanian industrial sector. To achieve these objectives, two empirical models were developed for electricity and fuel intensities, respectively of the Jordanian industrial sector based on multivariate linear regression. It was found that the structural effect, electricity prices, capacity utilizations and number of employees are the most important variables that affect changes of electricity intensity while fuel prices, capacity utilizations and number of employees factors are the most important variables that affect fuel intensity. The results show that multivariate linear regression model can be used adequately to simulate industrial energy intensity with very high coefficient of determination. Also, the impact of implementing energy saving technologies, such as use of high efficiency motors (HEMs), optimize motor size, variable speed drives (VSDs), bare steam pipes insulations, steam leak prevention, steam traps repair, and adjustment of boiler air/fuel ratio were investigated and found to be significant. Without such basic energy conservation and management programs, energy consumptions and associated GHG emissions for the industrial sector are predicted to rise by 25% and 23%, respectively in the year 2021. If these measures are implemented on a gradual basis, over the next decade, industrial energy consumption is predicted to rise at a lower rate, reaching 11.9% for same period with low/no cost actions. This would yield an estimated annual emission reductions of 570×103t. In addition, the total installed capacity cost savings is estimated to be around 81.9 million US$ by year 2021.

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  • Al-Ghandoor, A., 2012. "Analysis of Jordan's industrial energy intensity and potential mitigations of energy and GHGs emissions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4479-4490.
    • Handle: RePEc:eee:rensus:v:16:y:2012:i:7:p:4479-4490
    DOI: 10.1016/j.rser.2012.05.007
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    References listed on IDEAS

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    1. Thirugnanasambandam, M. & Hasanuzzaman, M. & Saidur, R. & Ali, M.B. & Rajakarunakaran, S. & Devaraj, D. & Rahim, N.A., 2011. "Analysis of electrical motors load factors and energy savings in an Indian cement industry," Energy, Elsevier, vol. 36(7), pages 4307-4314.
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    4. Al-Ghandoor, Ahmed & Samhouri, Murad & Al-Hinti, Ismael & Jaber, Jamal & Al-Rawashdeh, Mohammad, 2012. "Projection of future transport energy demand of Jordan using adaptive neuro-fuzzy technique," Energy, Elsevier, vol. 38(1), pages 128-135.
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    Cited by:

    1. Gutiérrez-Pedrero, María Jesús & Tarancón, Miguel Ángel & del Río, Pablo & Alcántara, Vicent, 2018. "Analysing the drivers of the intensity of electricity consumption of non-residential sectors in Europe," Applied Energy, Elsevier, vol. 211(C), pages 743-754.
    2. Sauer, Ildo L. & Tatizawa, Hédio & Salotti, Francisco A.M. & Mercedes, Sonia S., 2015. "A comparative assessment of Brazilian electric motors performance with minimum efficiency standards," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 308-318.
    3. Hamed, Tareq Abu & Bressler, Lindsey, 2019. "Energy security in Israel and Jordan: The role of renewable energy sources," Renewable Energy, Elsevier, vol. 135(C), pages 378-389.

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