Modelling solar radiation modification in process-based integrated assessment models

As the gap keeps widening between current greenhouse gas emissions and the ever-shrinking remaining carbon budget for achieving the Paris Agreement, there has been a surge in interest in the implementation of geoengineering proposals such as solar radiation management (SRM). However, there are ethical concerns about the governance, economic viability, and climate impacts of such measures. Our understanding of climate impacts has improved with the GeoMIP protocol and dimensions of economic viability has been evaluated in engineering cost analyses and through impact functions in cost-benefit integrated assessment models (IAM) such as DICE. Nevertheless, a critical gap remains in the modelling of SRM as a mitigation measure in multisector and dynamic analyses.

In this study, we present GCAM-SRM, a modification of the Global Change Analysis Model (GCAM 8.2). GCAM is a dynamic-recursive model with technology-rich representations of the economy, energy sector, land use, and water linked to a reduced complexity Earth system model (Hector 3.2) for exploring consequences of and responses to global to local changes and stressors. GCAM-SRM models the G6Sulfur emissions scenario with an explicit representation of a technology for stratospheric aerosol injection (SAI) with cost and resource modelling and competition with regular mitigation strategies and carbon dioxide removal measures.

The SAI technologies explicitly emit stratospheric SO₂, and the Earth system model has a detailed representation of the radiative forcing due to stratospheric SO₂. The Global Warming Potential (GWP) for SO₂ is calculated according to IPCC guidelines to derive a CO₂ equivalent for SO₂, and the radiative forcing of 4.5 W/m² corresponding to the G6Sulfur scenario is achieved by setting a global CO₂e price, which acts as a subsidy for SAI technologies. We finally compare the resulting CO₂e price between the G6sulfur scenario and the SSP2-4.5 scenario with no SAI. Further developments will exploit GCAM’s capabilities to model climate impacts to differentiate resource availabilty and consumption in a wamer world with and without SAI.