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CCS is the best alternative – it can be easily implemented into prexisting systems.

Dr. Mai Bui et al. 18, Research Associate in the Centre for Environmental Policy at Imperial College London. Her current research is on the topics of CCS, negative emissions technologies (BECCS & DAC), and grid-scale clean energy storage solutions, 1-1-2018, “Carbon capture and storage (CCS): the way forward,” Energy & environmental science, Vol. 11, Issue 5, https://pubs-rsc-org.proxy.lib.umich.edu/en/content/articlelanding/2018/EE/C7EE02342A // KG

Integrated Assessment Models (IAMs) have been at the heart of the Intergovernmental Panel on Climate Change's (IPCC) assessment of pathways towards keeping average global warming to less than 2 °C within this century.6 They provide a means to explore the future role of particular technologies in meeting climate targets such as renewables or nuclear.

CCS is one of the very attractive options in the IAMs mitigation portfolios, as it has a number of advantages. First, CCS can be integrated into existing energy systems without requiring large amendments to the system itself. Clearly, renewable technologies become more expensive at high penetration rates as a result of the need for the infrastructure to accommodate intermittency.29 Furthermore, CCS is a viable option for the decarbonisation of emission-intensive industries such as cement production (specific industrial CO2 capture costs are given in Section 3.3).30 And finally, CCS can be combined with low-carbon or carbon-neutral bioenergy (BECCS) to generate negative emissions,31i.e. while the cultivation of the feedstock biomass sequesters about as much CO2 as is generated during the process of producing energy (bio-electricity or biofuels), additionally capturing the latter leads to a withdrawal of CO2 from the atmosphere.32 BECCS has the double benefit of mitigating emissions and generating energy, making it attractive from the cost-optimisation perspective of an IAM.

3.1.1 CCS in integrated assessment models (IAMs) Based on the model intercomparison study by Koelbl et al.,33 some general statements on the implementation of CCS in IAMs can be made. In some cases, CCS is modelled as a lump-sum add-on cost to the technology it is combined with, while other models separate capture costs and transport & storage and a few separate all cost items. The latter modes obviously give more detail about the CCS supply chain, which enables modellers to also test the sensitivity of results to individual cost components. All IAMs include at least the power sector for CCS and many also cover industry and liquid fuels/hydrogen/gas production. At least 1 sector is also eligible for BECCS (in- and excluding liquid fuels), but many IAMs cover up to 3 sectors with BECCS. There is quite a divergence with respect to the assumption about CCS lifetimes, ranging from 30 to 60 years (partially depending on the technology), though most of the models assume around 40 years. It is also interesting in this light that there are some models not allowing early retirement of CCS plants. Almost all of the IAMs of the model intercomparison assume that CCS investment costs develop according to an exogenous constant (often declining); only two have endogenous learning.§

Finally, concerning storage, while many models have a regional differentiation of storage capacity, only a few models allow for international trade in storage capacity. The maximum capacity ranges between 3500 GtCO2 cumulative, and unlimited storage. Transportation and storage cost (excluding capture cost) varied between 10–300 US$ per ton CO2, depending on model and storage type.33 All of the models considered transportation and storage costs at the lower end of this range. Models that also considered high transportation and storage cost include the POLES model (upper range value of $300 USD) and the GRAPE model (upper range cost of $262 USD).33 The higher values for storage cost are associated with options that were offshore, enhanced coal bed methane (ECBM) and at greater depths (e.g., 2000–3000m).34

The IAMs thus differ widely in their deployment of CCS, yet the model intercomparison, which is the basis for the numbers cited above, could not explain the divergence of results on the basis of model type, model assumptions or the way in which CCS has been modelled. So either these are not the drivers of the difference or their impact is confounded by other factors via system effects. Individual model studies find that CCS contributes 50% more to mitigation if technological learning is included (Riahi et al.35 cumulative storage of 150–250 GtCO2) and that the contribution of CCS is sensitive to its cost in 2050 but not in 2100.36

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