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Stratospheric ozone changes under solar geoengineering: Implications for UV exposure and air quality


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Authors

Nowack, PJ 
Abraham, NL 
Braesicke, P 
Pyle, JA 

Abstract

jats:pAbstract. Various forms of geoengineering have been proposed to counter anthropogenic climate change. Methods which aim to modify the Earth's energy balance by reducing insolation are often subsumed under the term solar radiation management (SRM). Here, we present results of a standard SRM modelling experiment in which the incoming solar irradiance is reduced to offset the global mean warming induced by a quadrupling of atmospheric carbon dioxide. For the first time in an atmosphere–ocean coupled climate model, we include atmospheric composition feedbacks for this experiment. While the SRM scheme considered here could offset greenhouse gas induced global mean surface warming, it leads to important changes in atmospheric composition. We find large stratospheric ozone increases that induce significant reductions in surface UV-B irradiance, which would have implications for vitamin D production. In addition, the higher stratospheric ozone levels lead to decreased ozone photolysis in the troposphere. In combination with lower atmospheric specific humidity under SRM, this results in overall surface ozone concentration increases in the idealized G1 experiment. Both UV-B and surface ozone changes are important for human health. We therefore highlight that both stratospheric and tropospheric ozone changes must be considered in the assessment of any SRM scheme, due to their important roles in regulating UV exposure and air quality. </jats:p>

Description

Keywords

37 Earth Sciences, 3701 Atmospheric Sciences, Climate-Related Exposures and Conditions, 13 Climate Action

Journal Title

Atmospheric Chemistry and Physics

Conference Name

Journal ISSN

1680-7316
1680-7324

Volume Title

16

Publisher

Copernicus GmbH
Sponsorship
European Research Council (267760)
We thank the European Research Council for funding through the ACCI project, project number 267760. In particular, we thank Jonathan M. Gregory (UK Met Office, University of Reading), Manoj M. Joshi (University of East Anglia) and Annette Osprey (University of Reading) for model development as part of the QUEST-ESM project supported by the UK Natural Environment Research Council (NERC) under contract numbers RH/H10/19 and R8/H12/124. We acknowledge use of the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, which is a strategic partnership between the UK Met Office and NERC. For plotting, we used Matplotlib, a 2-D graphics environment for the Python programming language developed by Hunter (2007). We are grateful for advice of P. Telford during the model development stage of this project and thank the UKCA team at the UK Met Office for help and support.