The Impact of Uncertainty in Climate Targets and CO2 Storage Availability on Long-Term Emissions Abatement

Abstract

A major characteristic of our global interactive climate-energy system is the large uncertainty that exists with respect to both future environmental requirements and the means available for fulfilling these. Potentially, a key technology for leading the transition from the current fossil fuel-dominated energy system to a more sustainable one is carbon dioxide capture and storage. Uncertainties exist, however, concerning the large-scale implementability of this technology, such as related to the regional availability of storage sites for the captured CO 2 . We analyze these uncertainties from an integrated assessment perspective by using the bottom-up model TIAM-ECN and by studying a set of scenarios that cover a range of different climate targets and technology futures. Our study consists of two main approaches: (1) a sensitivity analysis through the investigation of a number of scenarios under perfect foresight decision making and (2) a stochastic programming exercise that allows for simultaneously considering a set of potential future states-of-the-world. We find that, if a stringent climate (forcing) target is a possibility, it dominates the solution: if deep CO 2 emission reductions are not started as soon as possible, the target may become unreachable. Attaining a stringent climate target comes in any case at a disproportionally high price, which indicates that adaptation measures or climate damages might be preferable to the high mitigation costs such a target implies.

A multi-model study of energy supply investments in Latin America under climate control policy

“…For a brief characterisation of the models we refer to van der Zwaan et al (2016a), and detailed model descriptions can be derived from publications by their respective modelling teams: GCAM (Calvin et al, 2011); POLES (Kitous et al, 2010;Criqui et al, 2014;Markandya et al, 2014); TIAM-ECN (van der Zwaan et al, 2013a;Keppo and van der Zwaan, 2012;Kober et al, 2014;Rösler et al, 2014) and TIAM-WORLD (Loulou and Labriet, 2008;Loulou, 2008). For information on the models' base year calibrations and the development of the main socio-economic parameters and energy indicators in the business as usual scenario we refer to van Ruijven et al (2016), and for the analysis of the effects of climate policy measures on the energy sector we refer to van der Zwaan et al (2016a) and Clarke et al (2016).…”

Comparison and interactions between the long-term pursuit of energy independence and climate policies

“…With regard to climate change mitigation measures, the model covers reduction options for the three main greenhouse gas emissions, carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), for both energy and non-energy related emission sources. More detailed model descriptions and further examples of the application of TIAM-ECN can be found in [28][29][30][31] , as well as the references therein. As an energy system model, TIAM-ECN allows analysis of greenhouse gas reduction pathways over the whole energy supply chain up to end-use energy demand.…”

Offshore CCS and ocean acidification: a global long-term probabilistic cost-benefit analysis of climate change mitigation

“…Over the past years DEMETER has been used specifically for the purpose of studying economic opportunities and conditions for CCS deployment, including issues such as potential CO 2 leakage (van der Zwaan and Gerlagh 2009; Gerlagh and van der Zwaan 2012). We here build on that work, as well as the broader and still growing literature on this topic (see, for example, Ha-Duong and Keith 2003; Keller et al 2008;Keppo and van der Zwaan 2012;Teng and Tondeur 2007).…”

“…First, both these types of CCS are characterized by an energy penalty of 30 % (defined as the share of the electricity output of a power plant that needs to be employed to operate the CCS facility), which yields lower levels of CO 2 avoided versus the levels of CO 2 stored (Gerlagh and van der Zwaan 2006). Second and critically important in a model such as OCEAN, based on publications such as by the IPCC (2005; 2014); Keppo and van der Zwaan (2012) and Finkenrath (2012), we assume that the costs of onshore CCS amount to 50 €/tCO 2 (median) with a lognormal uncertainty range of 17-150 €/tCO 2 (2.5 % and 97.5 % probability levels). This uncertainty range is especially broad since large-scale deployment for CCS is still practically untested.…”