Abstract
Negative emission technologies (NETs) are now considered essential for achieving net-zero emissions by mid-century. These technologies work by removing carbon dioxide from the atmosphere and storing it in various mediums, such as biomass, soil, deep underground, or the ocean. Rather than relying on a single large-scale NET, portfolios offer a way to manage the risks and sustainability issues associated with these technologies. Optimizing the deployment of NET portfolios is an emerging area of research. One challenge in this optimization is considering the permanence of carbon dioxide removal (CDR) for different technologies, as some NETs are more susceptible to reversal (e.g., forests are at risk of fires) than others (e.g., geological storage has a lower risk of reversal). CDR permanence is crucial in NET portfolio optimization because it affects the actual CDR potential of the portfolio over time. Currently, there is a lack of studies considering the permanence of NETs in portfolios. One approach to address this is by using time-evaluated costs, where the various NETs have different costs of permanent removal (CPR) depending on the considered planning horizon or time of permanence. This work aims to bridge the research gap by applying the concept of CPR in optimizing NET portfolios. Two mixed-integer linear programming models are used to optimize a NET portfolio under CPR, resource, budget, and capacity constraints, subject to target CDR. Different times of permanence (from 25 to 1,000 y) are investigated. The results show varying NET portfolios depending on the time of permanence considered. This work contributes to the analysis of decarbonization portfolios for decision-making to mitigate climate change.
