(418d) Assessment and Optimization of the Economic and Carbon Sequestration Potential of Renewable Energy and Negative Emission Technologies

Due to the delayed action in climate change mitigation, we need to multiply our efforts in the next decade to avoid the growing threat of abrupt and irreversible climate change. The practical implementation requires us to know where the resources locate and how to plan the utilization of the resources. Renewable energies (RE) are critical alternatives to fossil fuels for emission mitigation and negative emission technologies (NET) are promising candidates to mitigate emissions by removing CO2 from the atmosphere. As the intersection of both, bioenergy with carbon capture and storage (BECCS) and biochar (BC) are two key NETs based on the thermal conversion of biomass. However, the amount of renewable resources is usually constrained by geographical boundaries. There is a lack of geographical survey on the carbon mitigation and reduction potential that could be synthetically achieved by RE, BECCS, and BC in different regions around the world. This study sheds light on the carbon mitigation and reduction potential achievable by such combination of technologies globally and provides an overview of the best options for technology implementation to meet the Paris Agreement from a global perspective.

In this work, we assess the potential application of NETs and HERES at regional and global scales. At the regional scale, a stochastic multi-objective decision-support framework is developed to identify the optimal design of the energy mix under various weather scenarios was developed to address the tradeoff between economic and environmental criteria and the uncertainties caused by changing meteorology conditions. The economic and environmental performances of the system were evaluated using the net present value (NPV) and the greenhouse gas emissions (GHGe), respectively. The maximum NPV and the minimum GHGe were determined by finding the optimal capacities of the solar, wind, combustion, gasification, pyrolysis, and energy storage components in the system using mixed-integer nonlinear optimization programming (MINLP).

At the global scale, a snapshot of the current waste, emission, and policy information in different countries around the world is obtained according to real-world data sources. General Circulation Model (GCM)-based simulations of future climate and the Integrated Model to Assess the Global Environment (IMAGE) are used to generate possible future scenarios. Based on these inputs, mixed-integer linear programming (MILP) optimization is used to calculate the optimal mix of renewable and negative emission technologies for each region under different scenario pathways with the goal to maximize the profit while achieving the Paris agreement target.

The multi-scale studies address the techno-economic potential of the combined use of renewable energy and negative emission technologies from the local and practical operation aspect on the one hand and provide broader insight into the global applicability considering geographical difference on the other. The result regional study showed that negative emission and 100% renewable penetration were achievable with positive and competitive profitability for a rural case but not achievable for the urban case. Through the global analysis, it was found that most countries were decided to be profitable locations for the proposed system when net present value is maximized. Negative emission was possible to be achieved in the majority of the countries if greenhouse gas emission was minimized, but it may lead to a dramatic increase in cost compared to the optimal NPV scenario. The trade-off between the economic and environmental benefits was also discussed in the study.