Abstract

Gases like CH4, CO2 and H2 may play a key role in establishing a sustainable energy system: CH4 is the cleanest and least carbon-intensive among the fossil energy resources (that is, natural gas versus oil and coal); CO2 capture and storage can significantly reduce the climate footprint of especially fossil-based electricity generation; and the use of H2 as energy carrier could enable carbon-free automotive transportation. Yet the establishment of extensive distribution networks, required to transport these gases, is challenging. For instance the construction of large pipeline infrastructures usually constitutes a major and time-consuming undertaking, because of safety and environmental issues, legal and (geo)political siting arguments, technically un-trivial installation processes, and/or high investment cost requirements. In this paper we focus on the latter and present an overview of both the total costs and cost components of the distribution of these three gases via pipelines. Possible intricacies and external factors that strongly influence these costs, like the choice of location and terrain, are also included in our analysis. Our distribution cost breakdown estimates are based on transportation data for CH4, which we adjust for CO2 and H2 in order to account for the specific additional characteristics of these two gases. For CH4 and CO2 in any case the overall trend is that pipeline construction costs have more or less stabilized. For the purpose of designing energy policy and climate strategy we therefore know in principle with great reliability what the distribution cost components of future energy systems will be that rely on pipelining these gases. We speculate on the reasons why we observe limited learning-by-doing effects and expect that negligible construction cost reductions for future CH4 and CO2 pipeline projects will materialize. Cost data of individual pipeline projects may strongly deviate from the global average because of national or regional effects, such as related to varying costs of labor and fluctuating market prices of components like steel. We conclude that only in an optimistic scenario we may observe learning effects for H2 pipeline construction activity in the future, with a learning rate of around 20% – but the uncertainty of this prediction is large.

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