Near-term carbon dioxide removal deployment can minimize disruptive pace of decarbonization and economic risks towards United States’ net-zero goal

Deep decarbonization is essential for achieving the Paris Agreement goals, and carbon dioxide removal is required to address residual emissions and achieve net-zero targets. However, the implications of delaying the deployment of removal technologies remain unclear. We quantify how different carbon...

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Veröffentlicht in:Communications earth & environment 2024-12, Vol.5 (1), p.770-12, Article 770
Hauptverfasser: Adun, Humphrey, Ampah, Jeffrey Dankwa, Bamisile, Olusola, Hu, Yihua, Staffell, Iain, Gilani, Haris R.
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Sprache:eng
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Zusammenfassung:Deep decarbonization is essential for achieving the Paris Agreement goals, and carbon dioxide removal is required to address residual emissions and achieve net-zero targets. However, the implications of delaying the deployment of removal technologies remain unclear. We quantify how different carbon removal methods and their deployment timing affect achieving net zero emissions by 2050 in the United States. Our findings show that postponing novel technologies until mid-century forces accelerated decarbonization of energy-intensive sectors, reducing residual emissions by at least 12% compared with near-term deployment of carbon dioxide removal. This delay increases transition costs, requiring carbon prices 59–79% higher than with near-term deployment. It also heightens the risk of premature fossil fuel retirement in the electricity sector, leading to 128–220 billion USD losses compared to gradual scale up starting now. A balanced, near-term co-deployment of novel removal methods mitigates risks associated with relying on a single approach  and addresses sustainability and scalability concerns. In the US, the delay in novel carbon dioxide removal until mid-century and focus on other mitigation actions reduces 2050 residual emissions to 17 percent of 2020 levels but at a high economic cost, according to an analysis that uses a market equilibrium model with a scenario approach.
ISSN:2662-4435
2662-4435
DOI:10.1038/s43247-024-01916-4