https://cnrs.hal.science/tel-04749434/

*Authors*
Susanne Baur

2024

*Abstract*
Solar Radiation Modification (SRM) is a proposed method to halt global
warming and related impacts. This method is gaining interest in the climate
change community as a potential supplement to conventional mitigation
(emission reduction and carbon dioxide removal) to avoid surpassing a given
temperature threshold in an overshoot pathway. In this so-called
peak-shaving framework, SRM would lower global mean temperature to below
the specified threshold during the otherwise occurring overshoot until
mitigation has sufficiently brought down atmospheric CO2. At present, the
peak-shaving framework assumes that SRM can be added independently to
conventional mitigation. This additivity assumption disregards potential
interlinkages between the critical components of overshoot pathways,
emission reductions and net-negative emissions, and an SRM intervention.
The aim of this thesis is to assess the importance of these currently
unaccounted physical couplings between mitigation and SRM. It is
demonstrated that the range of uncertainty in future emission reductions
and net-negative emissions leads to a wide spectrum of different SRM
deployment trajectories, highlighting the uncertainty currently implied by
the peak-shaving framework and potential implications of non-additivity.
The additivity assumption of SRM and mitigation is subsequently scrutinized
by examining the impact of SRM on the practicality of decarbonization with
renewable energy and the change in negative emission burden under SRM due
to carbon feedback modification. I find that the potential to reduce
emissions with wind and solar renewable energy sources may become more
challenging with SRM. However, the model simulates temporarily enhanced
land and ocean carbon sinks, which imply that the negative emission burden
could be reduced during the upscaling of SRM deployment which may somewhat
compensate for the reduced decarbonization potential. Nevertheless, this
carbon uptake benefit is temporary and turns into an additional burden
during later stages of SRM deployment. The results of this thesis therefore
suggest that the additivity assumption does not hold in terms of physical
impacts of SRM on mitigation, since the deployment of it can significantly
change the underlying emissions trajectory. This provides a step away from
the highly idealized concept of the current peak-shaving framework towards
a more comprehensive outlook on the uncertainties implied by such a
deployment. This is important because the certainty that peak-shaving SRM
is predicated on could be misleading and needs to be taken into account
when moving towards more integrated assessments of SRM. The current
landscape of models for integrated climate policy scenarios is not well
suited for this purpose due to a lack of direct feedback from the climate
impact of SRM to the underlying mitigation trajectory. This thesis
highlights how this missing feedback between models is a major limitation
in SRM simulations and a barrier to comprehensive SRM scenario assessments.

*Source: CNRS*

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