Landscapes For Sequestering Carbon:

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 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 (LULUCF) 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 (food production, leisure, infrastructure, etc.), so there is a need 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 uptake of policy options increases.

Marginal abatement cost (MAC) curves are an established economic tool for use in making such decisions, but in the LULUCF sector, these have only been applied in very simplistic ways to date, ignoring the changes in marginal costs, the opportunity costs and the large uncertainties.

Marginal abatement cost (MAC) curves are an established economic tool for use in making such decisions, but in the LULUCF sector, these have only been applied in very simplistic ways to date, ignoring the changes in marginal costs, the opportunity costs and the large uncertainties.

Because it is spatio-temporally explicit, this approach will account for the opportunity costs of the forgone land uses, and include the spatial variation in land value and the changing marginal costs.

Our project will develop a much more rigorous MAC curve approach for the LULUCF sector, based on spatio-temporal dynamic modelling in a Bayesian framework. Using a Markov chain Monte Carlo approach, we will effectively explore thousands of realisations of future landscapes which could plausibly evolve from the present-day state.

The output 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 policy-makers to make informed, evidence-based decisions about how future landscapes can help to mitigate climate change.

Our research aims to increase 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.

Link to the project page on the UKRI Gateway to Research: Landscapes for sequestering carbon