Country-level assessment of the deployment potential of greenhouse gas removal technologies.

Date

2023-07

Journal Title

Journal ISSN

Volume Title

Publisher

Cranfield University

Department

SWEE

Type

Thesis or dissertation

ISSN

Format

Free to read from

Citation

Abstract

The deployment of greenhouse gas removal (GGR) technologies has been identified as an indispensable option in meeting the warming target of 1.5 °C by the end of the century. Despite the importance of this pathway, the Nationally Determined Contributions (NDCs) of countries indicates a low intent to deploy these technologies. Among the major factors responsible for this low level of inclusion is the lack of robust country-level bio-geophysical and techno-economic feasibility assessments to ascertain national GGR deployment potential. Herein lies the challenge that this thesis aimed to address. This study investigated the potential of 182 countries to deploy five of the most promising GGR technologies, including forestation, enhanced weathering, direct air carbon capture and storage, bioenergy with carbon capture and storage, and biochar. A comparative literature-based assessment was carried out to identify and rank the major factors required for optimum performance of these GGR methods. Based on the bio-geophysical and techno-economic characteristics, Machine Learning (ML) was applied to identify the range of GGR technologies that respective countries can suitably and effectively deploy. ML models were also developed for predictive locational resource mapping of these technologies. Furthermore, the extent of carbon dioxide removable by 2100 via these technologies for each country (national potential) was evaluated using a Multi Criteria Decision Analysis approach. An assessment of domestic and regional sufficiency was also carried out to provide an evidence base for international collaboration. Priority regions for the deployment of these GGR technologies were identified, with Latin America and Sub-Saharan Africa regions found to have surplus potentials, and thus, expected to serve as a major hub to support other regions of the world. While the obtained results indicate the need for regional cooperation among countries, it also provides useful evidence on the need for countries to include and prioritise GGR technologies in their revised NDCs.

Description

Nabavi, Sayed Ali - Associate Supervisor Manovic, Vasilije - Associate Supervisor

Software Description

Software Language

Github

Keywords

Negative emission technologies, BECCS, climate change mitigation, machine learning, carbon capture and storage, artificial neural network

DOI

Rights

© Cranfield University, 2023. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.

Relationships

Relationships

Supplements

Funder/s

Research Sponsor - Petroleum Technology Development Fund (PTDF), Nigeria. Doctoral study scholarship, award number: PTDF/ED/OSS/PHD/JOA/077/19.