A mixed‐effect model approach for assessing land‐based mitigation in integrated assessment models: A regional perspective

Abstract

Given the prospects of low short‐term emissions reduction, carbon removals (CDRs) are expected to play an important role in achieving ambitious mitigation targets in future scenarios of integrated assessment models (IAMs), particularly Bioenergy with Carbon Capture and Storage (BECCS). In this paper, we explore the IAMC 1.5℃ database to depict the characteristics of the two main CDR options present in mitigation scenarios: BECCS and afforestation/reforestation. We apply a linear mixed‐effect model to capture the specific regional and cross‐IAM effects. Results reveal that the distribution of BECCS and afforestation deployment differs across IAMs and regions and, to a second extent, time. BECCS is preferred in the scenarios not for its ability to expand energy use but actually because it appears as an alternative to afforestation, which is associated with a decrease in energy use. However, the regional distribution of CDR deployment does not show a common pattern across scenarios and IAMs. Therefore, a more comprehensive investigation is needed before it can support policy proposals.

Sustainable bioenergy contributes to cost-effective climate change mitigation in China

“…From the perspective of future projections, the Integrated Assessment Models (IAM) can aid in delineating regional and global land usage within an evolving market landscape, consequently facilitating the estimation of overall biomass supply and requirements through a "top-down" approach. 13 , 62 Finally, with China transitioning toward low- or zero-carbon emissions in the future, 63 the emission reduction potential of bioenergy may undergo significant shifts. Decarbonizing the energy sector (e.g., supercritical power plants) could alter the baseline emissions from conventional energy sources such as thermal power generation and heat supply, 64 thereby affecting the emissions displaced by bioenergy and its co-products.…”

emIAM v1.0: an emulator for Integrated Assessment Models using marginal abatement cost curves

“…Regarding emission sources, total anthropogenic emissions and energy-related emissions (e.g., energy and 120 industrial processes) were separately used to derive global MAC curves for three gases (only total anthropogenic emissions for regional MAC curves due to computational requirements for validating regional MAC curves). Non-energy-related emissions (e.g., agriculture, forestry, and land-use sector), the differences between the two, were not used for generating MAC curves because non-energy-related emissions did not appear to be strongly correlated with carbon prices in most IAMs and influenced by other factors (Diniz Oliveira et al, 2021). targets under exogenously given energy demand scenarios (Azar et al, 2003;Hedenus et al, 2010;Azar et al, 2013;Lehtveer and Hedenus, 2015;Lehtveer et al, 2019).…”

Using large ensembles of climate change mitigation scenarios for robust insights

“…In the context of multi-models ensembles, and unstructured ensembles, meta-modelling techniques using multiple regression analysis can be employed to quantify the relative importance of uncertain factors and different model structures. Applications have investigated uncertainties in land cover projections 79 , in the costs of achieving climate targets 80 , in carbon price dynamics in ambitious mitigation scenarios 81 , and in carbon dioxide removal deployment 82 . More complex forms of such meta-modelling techniques have been employed to scenario ensembles beyond the field of climate mitigation, for example considering non-linearities in the scenario drivers 83 .…”