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Reducing sectoral hard-to-abate emissions to limit reliance on carbon dioxide removal

AbstractTo reach net-zero greenhouse gas targets, carbon dioxide removal (CDR) technologies are required to compensate for residual emissions in the hard-to-abate sectors. However, dependencies on CDR technologies involve environmental, technical and social risks, particularly related to increased land requirements for afforestation and bioenergy crops. Here, using scenarios consistent with the 1.5 °C target, we show that demand and technological interventions can substantially lower emission levels in four hard-to-abate sectors (industry, agriculture, buildings and transport) and reduce reliance on the use of bioenergy with carbon capture and storage. Specifically, demand measures and technology-oriented measures could limit peak annual bioenergy with carbon capture and storage use to 0.5–2.2 GtCO2e per year and 1.9–7.0 GtCO2e per year, respectively, compared with 10.3 GtCO2e per year in the default 1.5 °C scenario. Dietary change plays a critical role in the demand measures given its large share in residual agricultural emissions.
- Utrecht University Netherlands
- Netherlands Environmental Assessment Agency Netherlands
- National Institute for Public Health and the Environment Netherlands
- Free University of Amsterdam Pure VU Amsterdam Netherlands
- Vrije Universiteit Amsterdam Netherlands
energy supply and demand, Life Science, Agriculture, SDG 15 - Life on Land
energy supply and demand, Life Science, Agriculture, SDG 15 - Life on Land
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).19 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
