A Superstructure Model for Integrated Deployment of Negative Emissions Technologies under Resource Constraints

Abstract

Negative Emissions Technologies (NETs) will be needed in order to achieve the net zero emissions targets being set by many countries. These technologies will offset the residual greenhouse gas emissions of sectors that are inherently difficult to decarbonize. NETs draw down carbon through different physical, chemical, or biological pathways, and transfer it for storage to other environmental compartments. Examples of these techniques include afforestation, Biochar application, BioEnergy with Carbon Capture and Storage (BECCS), enhanced weathering, and Direct Air Capture (DAC). The large-scale deployment of NETs will be constrained by the footprints they apply to limited resources such as land, water, energy, and nutrients. In this work, a superstructure-based Linear Programming (LP) model is developed to optimize the carbon drawdown of integrated NET deployment under resource constraints. Results show that varying the target negative emissions and resource constraints affect the NETs portfolio and total cost.