Fuzzy mixed-integer linear and quadratic programming models for planning negative emissions technologies portfolios with synergistic interactions

Fuzzy mixed-integer linear and quadratic programming models for planning negative emissions technologies portfolios with synergistic interactions

Blog Article

Fossil fuels will still be used in the coming decades following the agreement to phase down coal and phase out fossil fuels subsidies in COP26.Negative Emissions Technologies (NETs) can offset the emissions caused by the residual use of fossil fuels.NETs such as Afforestation/Reforestation (AR), biochar application (BC), Soil Carbon Sequestration (SCS) Bioenergy with Carbon Capture and Storage (BECCS), Enhanced Weathering (EW), and Direct Air Carbon Capture and Storage (DACCS) remove CO2 from the atmosphere and store helmets it in reservoirs.The large-scale implementation of NETs will incur resource footprints; thus, NETs should operate within the Planetary Boundaries.No single NET can sustainably deliver the required CO2 removal, and optimized regional portfolios of NETs can reduce the biophysical and social impacts of their implementation.

In such portfolios, some NETs may have synergistic effects and consume Kits fewer resources when implemented together.In this work, fuzzy mixed-integer programming models are developed to optimize the CO2 removal (CDR) potential of a NETs portfolio while considering possible synergistic interactions, as well as uncertainties in the resource constraints and negative emission targets.The models are illustrated with a regional case study that demonstrates the changes in the optimal NETs portfolio depending on different scenarios.