Stratospheric ozone projections under sulfur-based stratospheric aerosol injection: Insights from the multi-model G6-1.5K-SAI experiment
E. M. Bednarz; A. H. Butler; J. M. Haywood; M. Henry; A. Jones; B. Kravitz; W. R. Lee; D. G. MacMartin; A. C. Maycock; T. Sekiya; S. Watanabe; D. Visioni · DOAJ Open Access Articles
Abstrak / Ringkasan
<p>Owing to the crucial role of stratospheric ozone in shielding the Earth from harmful solar ultraviolet radiation, impacts of human activities on the ozone layer remain of interest. Here we provide an assessment of the potential impacts of Stratospheric Aerosol Injection (SAI), a proposed method to temporarily offset global warming, on stratospheric ozone projections over the 21st century using the new multi-model GeoMIP G6-1.5K-SAI experiment. The experiment injects SO<span class="inline-formula"><sub>2</sub></span> at a pair of subtropical latitudes and utilizes a more plausible “middle-of-the-road” greenhouse gas emission pathway (SSP2-4.5) and SAI start date compared to earlier studies.</p>
<p>All three participating Earth system models show a decrease in global mean total column ozone of a few Dobson units (1?%–2?%) under SAI compared to the no-SAI scenario. This decrease is dominated by enhancement in active halogens from heterogenous chemistry on sulfate aerosol, most clearly evident in the Southern Hemisphere mid- and high latitudes. This is unlike previous results using strategies injecting at the equator, which show increased global mean column ozone, partly due to larger ozone transport changes. As background halogen levels continue to decrease, the potential of SAI to deplete ozone is found to be a factor of <span class="inline-formula">?</span>?2 larger in earlier part of the 21st century (2045–2064) than later (2065–2084). We further identify areas of model disagreement and sources of uncertainty, but also areas of more confidence and potential emergent constraints. Our results highlight the need to assess any projected SAI impacts in the wider strategy and scenario dimension using a multi-model framework.</p>
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