BC3 Journal Article “Carbon risk and optimal retrofitting in cement plants: An application of stochastic modelling, MonteCarlo simulation and Real Options Analysis”


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Abadie, L.M., Goicoechea, N. and Galarraga, I. 2017. Carbon risk and optimal retrofitting in cement plants: An application of stochastic modelling, MonteCarlo simulation and Real Options Analysis. Journal of Cleaner Production. 142 (Part 4). 3117-3130. DOI (10.1016/j.jclepro.2016.10.155)

Abstract

The cement sector is highly intensive in CO2 emissions and is the second biggest industrial sector in terms of emissions after the electricity generation sector. It emits CO2 from the combustion of fossil fuels, the calcination process and, indirectly, from electricity consumption. The ambitious climate change policy in the EU means that carbon prices and fuel prices are two very important sources of uncertainty that may affect the competitiveness of the sector. This paper focuses on understanding the risk associated with the future price of European Union Emission Trading System allowances. This is done by modelling a stochastic process with parameters calculated using market prices. Risks are valued with the Expected Shortfall and Value at Risk measures over the lifetime of a plant using MonteCarlo simulation: two well-known risk measures in financial economics. Risks are greater and returns lower in the wet process than in the dry one. The paper includes a sensitivity analysis of the effects arising from changes in the prices of allowances as a consequence of a hypothetical drastic change in climate policy, including jumps, withdrawing of free emission allowances and changes in future carbon prices. In this case impacts will also be higher in the wet process. Finally, the paper illustrates the optimal conditions for retrofitting a wet cement plant to convert it to a dry cement plant under uncertainty of the price of carbon allowances. This is done using Real Options Analysis. The trigger price is €114 million for a plant with remaining lifetime of 25 years and a production of one million tonnes.

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