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Correcting temperature patterns for air quality and land-use change in Integrated Assessment Models

The Dutch Environmental Assessment Agency (PBL) uses an integrated assessment model (IAM), IMAGE, to address a set of global environmental issues and sustainability challenges. IMAGE is unique compared to other IAMs because of its high spatial resolution for land-based processes. Among others, IMAGE is used to develop a set of unique scenarios, the Shared Socio-economic pathways (SSPs), to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation.

In order to model temperature change at high resolution, a two-step approach is used. First, global temperature change is modelled with a reduced complexity climate model, which is scaled down using Earth System Model (ESM) results in a second step. However, SSPs studied with IMAGE can significantly deviate from the current downscaling scenarios, particularly in terms of air quality (AQ) or land-use (LU). This implies that the down-scaled temperature patterns only account for global effects of aerosol and LU-change effects, while strong local effects of AQ- and LU-changes are expected.

This study focuses on improving the temperature patterns by implementing temperature corrections for local AQ and LU effects. For AQ, a source receptor atmospheric chemistry model is used to model the concentration fields for aerosol components. Future concentrations are subsequently scaled with a set of controlled experiments and its temperature changes. For LU, aggregated remote sensing data on local biophysical LU change effects is applied. 

Applying these methods on the newly developed SSPs, local corrections of up to 1K for AQ and 0.5K for LU are calculated, while global averages are only marginally affected.

Supervisor: Maarten Krol