A risk-based framework for assessing the effectiveness of stratospheric aerosol geoengineering

Ferraro, A. J., Charlton-Perez, A. J. ORCID: https://orcid.org/0000-0001-8179-6220 and Highwood, E. J. (2014) A risk-based framework for assessing the effectiveness of stratospheric aerosol geoengineering. PLoS ONE, 9 (2). e88849. ISSN 1932-6203 doi: 10.1371/journal.pone.0088849

Abstract/Summary

Geoengineering by stratospheric aerosol injection has been proposed as a policy response to warming from human emissions of greenhouse gases, but it may produce unequal regional impacts. We present a simple, intuitive risk-based framework for classifying these impacts according to whether geoengineering increases or decreases the risk of substantial climate change, with further classification by the level of existing risk from climate change from increasing carbon dioxide concentrations. This framework is applied to two climate model simulations of geoengineering counterbalancing the surface warming produced by a quadrupling of carbon dioxide concentrations, with one using a layer of sulphate aerosol in the lower stratosphere, and the other a reduction in total solar irradiance. The solar dimming model simulation shows less regional inequality of impacts compared with the aerosol geoengineering simulation. In the solar dimming simulation, 10% of the Earth’s surface area, containing 10% of its population and 11% of its gross domestic product, experiences greater risk of substantial precipitation changes under geoengineering than under enhanced carbon dioxide concentrations. In the aerosol geoengineering simulation the increased risk of substantial precipitation change is experienced by 42% of Earth’s surface area, containing 36% of its population and 60% of its gross domestic product.

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/37731
Identification Number/DOI	10.1371/journal.pone.0088849
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Public Library of Science
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