Issue 14, 2024

Assessing the realism of clean energy projections

Abstract

Although pivotal in the climate change discourse, integrated assessment models (IAMs) often face criticism for their overly optimistic projections. In this contribution, we critically examine IAM limitations in the context of clean energy technologies and critical materials. IAMs project a very substantial increase in clean energy technology deployment by 2050. When considering diverse technology types and their material requirements – information missing from IAMs – we find that this may represent a substantial 571-fold surge in selenium demand and a 531-fold increase in gallium, figures that seem difficult to achieve. This challenges not only the capacity of material reserves but also the rate at which these can be produced. To address this gap, we propose establishing a direct link between industrial assets and required materials through simple constraints on material availability. We illustrate the capabilities of this approach by estimating the achievable clean energy capacities by 2050. We find potential shortages in the capacity developed for clean energy technologies compared to IAM projections that may result in deviations from the Paris agreement target by 0.06–0.95 °C. Therefore, incorporating material constraints and technological diversity into IAMs presents a valuable opportunity to enhance their predictive accuracy and guide evidence-based policymaking. Including these aspects in IAMs and decision-support tools will make them more useful in shaping a sustainable yet realistic energy sector.

Graphical abstract: Assessing the realism of clean energy projections

Supplementary files

Article information

Article type
Paper
Submitted
17 Febr. 2024
Accepted
17 Jūn. 2024
First published
18 Jūn. 2024
This article is Open Access
Creative Commons BY-NC license

Energy Environ. Sci., 2024,17, 5241-5259

Assessing the realism of clean energy projections

F. Rostami, P. Patrizio, L. Jimenez, C. Pozo and N. Mac Dowell, Energy Environ. Sci., 2024, 17, 5241 DOI: 10.1039/D4EE00747F

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