a dynamic marginal abatement cost curve approach with Bayesian spatio-temporal modelling
One way of slowing the rise in atmospheric carbon dioxide – and arguably the only economically feasible means of reversing the trend – is to sequester or ‘capture’ carbon in terrestrial ecosystems by changing land use and management. To do this, most nations have included targets for sequestering carbon through land use, land-use change and forestry within their climate change commitments.
Land use and land-use change decisions aren’t made in a vacuum. There are competing demands on a limited supply of land, such as food production, leisure, and infrastructure. It is therefore important to know what policy decisions will result in sequestration of carbon (thereby mitigating climate change) at least cost, and how the marginal costs change as the uptake of policy options increases.
Marginal abatement cost curves are an established economic tool for use in making such decisions, but these have only been applied in very simplistic ways in relation to land use, land-use change and forestry. Previous approaches have tended to ignore changes in marginal costs, the opportunity costs and the large uncertainties involved.
The Landscapes For Sequestering Carbon project sought to develop a more rigorous marginal abatement cost curve approach for the land use, land-use change and forestry sector based on spatio-temporal dynamic modelling in a Bayesian framework. Using a Markov chain Monte Carlo approach, the project team explored thousands of realisations of future landscapes which could plausibly evolve from the present-day state. Because it is spatio-temporally explicit, the approach the team developed can account for the opportunity costs of the forgone land uses, and include the spatial variation in land value and the changing marginal costs.
The output produced from this approach is a mathematically and probabilistically rigorous analysis of which land-use transitions will occur, where land-use change is likely to take place, how much carbon will be sequestered, and at what cost. This will help policymakers to make informed, evidence-based decisions about how future landscapes can help to mitigate climate change. The work conducted as part of the project fed into a proposal and successful funding for a follow-on project from the Department for Business, Energy and Industrial Strategy, “Improving Land Use Change Tracking in the UK Greenhouse Gas Inventory”, which started on 1 August 2020 for one year with £300,000 of funding. The project ultimately helped aid our understanding of the interactions that determine how land use will be affected by future environmental and socio-economic change. With improved understanding, we can better predict the consequences for emissions, and make more informed decisions about what policies to pursue to mitigate climate change.
Peter Levy (Principal Investigator)
Peter Henrys (Co-Investigator)
Marcel Van Oijen (Co-Investigator)
Samuel James Tomlinson (Researcher)
The main output from the project was a proposal and successful funding for a follow-on project from the Department for Business, Energy and Industrial Strategy, “Improving Land Use Change Tracking in the UK Greenhouse Gas Inventory”, which started on 1 August 2020 for one year with £300,000 of funding.
|Link to the project page on the UKRI Gateway to Research: Landscapes For Sequestering Carbon|