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The share of cooling electricity in global warming: Estimation of the loop gain for the positive feedback

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  • Shakouri G., Hamed

Abstract

Our world's future is strongly connected to energy consumption trends. There are bi-directional relations between energy consumption and the average temperature of Earth, leading to positive causal loops. Increasing temperatures cause activity of more cooling systems most of which are electrified by burning hydrocarbons that consequently yield more carbon dioxide concentration and warmer climates. This paper is a trial to estimate the loop gain by employing a bottom-up regional model. The model is a spreadsheet containing sets of parameters and variables to estimate electricity used for cooling buildings in the residential and commercial sectors of 12 regions all around the world. The share of fossil-fuel based power plants determines each region's contribution to CO2 emissions. Then, by processing data on the global emission trend and land temperature anomaly, a linear ARMAX relationship is estimated to compute the loop gain. The results show that, even in the optimistic scenario of IPCC (A1B), emission from cooling electricity will double up by the end of the century. With the estimated 1 + 1.4 × 10-6 loop gain, even if fossil-fuel electricity generation is gradually reduced to 40%, after a short fall, it will start growing again in the mid-century.

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  • Shakouri G., Hamed, 2019. "The share of cooling electricity in global warming: Estimation of the loop gain for the positive feedback," Energy, Elsevier, vol. 179(C), pages 747-761.
    • Handle: RePEc:eee:energy:v:179:y:2019:i:c:p:747-761
    DOI: 10.1016/j.energy.2019.04.170
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    1. Satman, A & Yalcinkaya, N, 1999. "Heating and cooling degree-hours for Turkey," Energy, Elsevier, vol. 24(10), pages 833-840.
    2. Xu, Peng & Huang, Yu Joe & Miller, Norman & Schlegel, Nicole & Shen, Pengyuan, 2012. "Impacts of climate change on building heating and cooling energy patterns in California," Energy, Elsevier, vol. 44(1), pages 792-804.
    3. D. A. Stainforth & T. Aina & C. Christensen & M. Collins & N. Faull & D. J. Frame & J. A. Kettleborough & S. Knight & A. Martin & J. M. Murphy & C. Piani & D. Sexton & L. A. Smith & R. A. Spicer & A. , 2005. "Uncertainty in predictions of the climate response to rising levels of greenhouse gases," Nature, Nature, vol. 433(7024), pages 403-406, January.
    4. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Erratum: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6813), pages 750-750, December.
    5. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6809), pages 184-187, November.
    6. H. Damon Matthews & Nathan P. Gillett & Peter A. Stott & Kirsten Zickfeld, 2009. "The proportionality of global warming to cumulative carbon emissions," Nature, Nature, vol. 459(7248), pages 829-832, June.
    7. Papakostas, K. & Kyriakis, N., 2005. "Heating and cooling degree-hours for Athens and Thessaloniki, Greece," Renewable Energy, Elsevier, vol. 30(12), pages 1873-1880.
    8. Zhao, Hai-xiang & Magoulès, Frédéric, 2012. "A review on the prediction of building energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3586-3592.
    9. Joeri Rogelj & Malte Meinshausen & Reto Knutti, 2012. "Global warming under old and new scenarios using IPCC climate sensitivity range estimates," Nature Climate Change, Nature, vol. 2(4), pages 248-253, April.
    10. Jones, Rory V. & Fuertes, Alba & Lomas, Kevin J., 2015. "The socio-economic, dwelling and appliance related factors affecting electricity consumption in domestic buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 901-917.
    11. Eric A. Davidson & Ivan A. Janssens, 2006. "Temperature sensitivity of soil carbon decomposition and feedbacks to climate change," Nature, Nature, vol. 440(7081), pages 165-173, March.
    12. Fumo, Nelson, 2014. "A review on the basics of building energy estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 53-60.
    13. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    14. Jakubcionis, Mindaugas & Carlsson, Johan, 2017. "Estimation of European Union residential sector space cooling potential," Energy Policy, Elsevier, vol. 101(C), pages 225-235.
    15. Papakostas, K. & Mavromatis, T. & Kyriakis, N., 2010. "Impact of the ambient temperature rise on the energy consumption for heating and cooling in residential buildings of Greece," Renewable Energy, Elsevier, vol. 35(7), pages 1376-1379.
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