Soft-Linking Bottom-Up Energy Models with Top-Down Input-Output Models to Assess the Environmental Impact of Future Energy Scenarios

Soft-Linking Bottom-Up Energy Models with Top-Down Input-Output Models to Assess the Environmental Impact of Future Energy Scenarios

Matteo V. Rocco* Yassin Rady Emanuela Colombo 

Department of Enery, Politecnico di Milano, via Lambruschini 4, Milano 20156, Italy

The America University in Cairo (AUC), AUC Avenue, New Cairo 11835, Egypt

Corresponding Author Email:
23 March 2018
28 May 2018
30 June 2018
| Citation



Traditional bottom-up energy models have been widely applied so far to assess the future energy technologies over a specific time horizon, quantifying the direct economic and environmental implications of future energy scenarios. However, such approaches ignore the interactions that the energy sector has with other sectors in the economy, hence failing in quantifying the global impact of future energy technologies.

This study assesses the economic and environmental impact of an institutional energy scenario in the Egyptian economy, by soft linking a bottom-up, technology-rich model (OSeMOSYS) with a top-down Input-Output model (IOA). Based on the prospective institutional scenarios for Egypt, the energy model assesses the evolution of the Egyptian electricity mix towards 2040. Then, the future energy scenario has been applied to the IOA model in terms of change in energy technology mix, change in final demand of electricity and change in national GDP production.

It is found that while primary energy consumption and GHG emissions of the energy sector are likely to decrease in the next decades, a significant increase in the same indicators for all the other national sectors is expected, thus unveiling the need to increase and diversify the energy efficiency investments in all the Egyptian economy.


energy policy, energy modelling, developing countries, input-output analysis

1. Introduction
2. Methods and Models
3. Application to Egypt and Results
4. Conclusions

[1] Greening AL, Greene DL, Difiglio C, Agnew K, Goldberg M, Attia S, et al. (2015). The outlook for energy: A view to 2040. Irving, Texas 2015.

[2] Pfenninger S, Hawkes A, Keirstead J. (2014). Energy systems modeling for twenty-first century energy challenges. Renew Sustain Energy Rev 33: 74–86.

[3] Howells M, Rogner H, Strachan N, Heaps C. (2011). OSeMOSYS: the open source energy modeling system: an introduction to its ethos, structure and development. Energy Policy 2011.

[4] Taliotis C, Shivakumar A, Ramos E, Howells M, Mentis D, Sridharan V, et al. (2016). An indicative analysis of investment opportunities in the African electricity supply sector — Using TEMBA (The Electricity Model Base for Africa).

[5] Nikolaus PDMG, Fernando LLL, Pe G, Balderrama N, Howells M. (2017). South America power integration, Bolivian electricity export potential and bargaining power: An OSeMOSYS SAMBA approach. Energy Strateg Rev 17: 27–36.

[6] Miller RE, Blair PD. (2009). Input-output analysis: Foundations and extensions. Cambridge University Press.

[7] Miller RE, Blair PD. (1985). Input-output analysis.

[8] Hosoe N, Gasawa K, Hashimoto H. (2010). Textbook of Computable General Equilibrium Modelling: Programming and Simulations. New York St Martin’s Press Palgrave Macmillan, Pp Xix 235 2010:2-NaN, 235.

[9] Böhringer C, Rutherford TF. (2008). Combining bottom-up and top-down. Energy Econ 30: 574–96.

[10] World Bank Egypt, Arab Rep. (2017). Data, World Bank.

[11] Egyptian Electricity Holding Company. Annual Report 2014-2015. Cairo: 2015.

[12] Omar MEDM, Moussa AMA. (2016). Water management in Egypt for facing the future challenges. J Adv Res 7: 403–12.

[13] Program TARES. (2016). The EU promotes Governance Energy Efficiency in cooperation with the Ministry of Energy and Renewable Energy and Ministry of Petroleum and Mineral Resources. Cairo: 2016.

[14] TARES S. (2014). Update on Energy Strategy Modelling TIMES-EGYPT. Cairo: 2014.

[15] Pfenninger S. (2017). Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability. Appl Energy 197: 1–13.

[16] Loulou R, Remme U, Kanudia A, Lehtila A, Goldstein G. Documentation for the TIMES Model - Part II. IEA Energy Technol Syst Anal Program 2016: 1–78.

[17] Klinge JH. (1998). Integrating the bottom-up and top-down approach to energy–economy modelling: the case of Denmark. Energy Econ 20: 443–61.

[18] Bauer N, Baumstark L, Leimbach M. (2012). The REMIND-R model: the role of renewables in the low-carbon transformation—first-best vs. second-best worlds. Clim Change 114: 145–68.

[19] (2014). E3MLab/ICCS at National Technical University of Athens. PRIMES - Detailed Model Description. Athens: 2014.

[20] Gargiulo M, Gallachóir BÓ. (2013). Long-term energy models: Principles, characteristics, focus, and limitations. Wiley Interdiscip Rev Energy Environ 2: 158–77.

[21] Messner S, Schrattenholzer L. (2000). MESSAGE–MACRO: linking an energy supply model with a macroeconomic module and solving it iteratively. Energy 25: 267–82.

[22] Kober T, Summerton P, Pollitt H, Chewpreecha U, Ren X, Wills W, et al. (2016). Macroeconomic impacts of climate change mitigation in Latin America: A cross-model comparison. Energy Econ 56: 625–36.

[23] Heinrichs HU, Schumann D, Vögele S, Biß KH, Shamon H, Markewitz P, et al. (2017). Integrated assessment of a phase-out of coal-fired power plants in Germany. Energy 126: 285–305.

[24] Moksnes N, Welsch M, Gardumi F, Shivakumar A, Broad O, Howells M, et al. (2015). Working Paper Series 2015 OSeMOSYS User Manua.

[25] Lenzen M, Kanemoto K, Moran D, Geschke A. (2012). Mapping the Structure of the World Economy. Environ Sci Technol 46: 8374–81. doi:10.1021/es300171x.

[26] Lindner S, Legault J, Guan D. (2013). Disaggregating the electricity sector of china’s input–output table for improved environmental life-cycle assessment. Econ Syst Res 25: 300–20.

[27] Ozturk I. (2010). A literature survey on energy-growth nexus. Energy Policy 38: 340–9.

[28] BMI Research (A Fitch Group Company). Egypt Power Report Q2 2016. London: 2016.

[29] Davidsson S, Hagberg AK, Estimatin S, Davidsson AK, Hagberg, (2017). Estimating investment needs for the power sector in the african region, kth, 2014. https://www.diva (accessed June 11, 2017).g investment needs for the power sector. Kth, 2014.

[30] BNI Research. (2016). Report gas. oil & gas report Egypt oil & gas report Q4 2016. London: 2016.