How uncertainty in technology costs and CDR availability affect climate mitigation pathways

Oct 26, 2026

Limiting global warming to well below 2°C under the Paris Agreement requires ambitious emissions reductions across all sectors. Rapid declines in energy technology costs and uncertainty in carbon dioxide removal (CDR) availability reshape energy investment and emissions, even under weak climate policies. Using the technology-rich energy-economy model REMIND, the study applies efficient large-scale sensitivity analysis to quantify how energy supply costs and CDR parameters influence mitigation pathways and key indicators.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages25

Reading Time1 h 3 min

AccessFree to download

Introduction

Scenario and method overview

Sensitivity analysis setup

Results and indicator sensitivity

Summary and conclusion

Originally published as: Giannousakis, A., Hilaire, J., Nemet, G. F., Luderer, G., Pietzcker, R. C., Dias Bleasby Rodrigues, R., Baumstark, L., Kriegler, E. (2021): How uncertainty in technology costs and carbon dioxide removal availability affect climate mitigation pathways. -Energy, 216, 119253. DOI: [https://doi.org/10.1016/j.energy.2020.119253](https://doi.org/10.1016/j.energy.2020.119253) How uncertainty in technology costs and CDR availability a􀀋ects climate mitigation pathways Anastasis Giannousakis, J􀀓er^ome Hilaire, Gregory F. Nemet, Gunnar Luderer, Robert C. Pietzcker, Renato Rodrigues, Lavinia Baumstark, Elmar Kriegler Abstract Limiting global warming to "well below 2 􀀎 C" as stated in the Paris Agreement requires ambitious emissions reductions from all sectors. Rapid technology cost declines in the energy sector are changing energy investment and emissions, even with only weak climate policies at present. We assess how energy supply costs and carbon dioxide removal (CDR) availability a􀀋ect mitigation pathways by performing an e􀀎cient large-scale sensitivity analysis with the technology-rich energy-economy model REMIND. We use new scenarios with carbon price paths that aim at reducing the frequently seen temperature overshoot. Further, we measure the sensitivities of important mitigation indicators to the costs of technologies across economic sectors. We assess the sensitivity to nine technoeconomic parameters: the costs of wind, solar, bioenergy, gas, coal, oil, and nuclear, as well as CDR 1 rates and costs of electric/hydrogen vehicles. While technology costs play a role in shaping optimal pathways, we 􀀌nd that transport sector costs a􀀋ect the economics of deep decarbonization, whereas costs of renewables are more important for scenarios under weak climate policies. This further highlights the character of renewable energy deployment asa no-regret option of climate policy. In terms of the sensitivity of model outputs, economic indicators become more sensitive to costs than emissions, with increasing policy stringency. Keywords: technology costs, electromobility, carbon dioxide removal 1. Introduction The energy sector accounts for the largest share of greenhouse gas (GHG) emissions (Papadis and Tsatsaronis, 2020) and holds the greatest decarbonization potential (Luderer et al., 2018) . Thus, investments in energy transformation technologies are key factors shaping climate mitigation pathways (Kumar et al., 2020; Kriegler et al., 2014; Pietzcker et al., 2014; Hirth and Steckel, 2016) . The uncertainty associated with the costs of energy technologies constitutes an important component of the overall uncertainty present in mitigation pathways (van Vuuren et al. , 2020; Bosetti et al., 2015; Mouratiadou et al., 2015; Bosetti et al., 2012; Candelise et al., 2013) Energy investment costs have changed drastically over time and vary considerably across space (Baker et al. , 2015) . Solar and onshore wind have levelized costs of electricity (LCOE) that are in some regions lower than the long-run-marginal-cost (LRMC) of standing coal capacity, but analysts suggest a strong policy signal (in the form of carbon price or e􀀎ciency standard) is still needed for a fast decarbonization of the power sector (Bistline and Blanford, 2020; Wang et al., 2019; Liu et al., 2018; Bertram et al., 2015; Tietjen et al., 2016; Creutzig et al. , 1 Carbon dioxide removal. Preprint submitted to the co-authors July 22, 2020 2017) . At the same time, the decarbonization of the transportation sector is proceeding (Knobloch et al., 2020) and depends on the cost of electric and fuel-cell vehicles (van der Zwaan et al., 2013; Haasz et al. , 2018; Hoekstra, 2019), as well as oil prices (Zimmer and Koch, 2017) and policies (Solaymani, 2019) . Given recent changes, what are the di􀀋erences in global mitigation pathways using 2015 technology cost projections versus 2019 cost projections? How are CDR demands and individual sec

FAQs

What question does the study address about climate mitigation pathways?

It evaluates how uncertainty in energy technology costs and CDR availability changes climate mitigation pathways, sector impacts, and the relative importance of different technologies.

Which model and method are used to analyze the uncertainties?

The study uses the technology-rich energy-economy model REMIND and performs an efficient large-scale sensitivity analysis of mitigation indicators under varying climate policy ambition levels.

How do transport costs versus renewable costs affect outcomes?

The findings indicate transport sector costs influence the economics of deep decarbonization, while renewable energy costs are more important under weak climate policies.

Oct 26, 2026

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