Multiscale Emission Accounting and Emission Reduction Pathways for Achieving Well-being in Human-centred Everyday Life from a Systems Integration Pers

In the global context of climate change, obtaining accurate estimations of carbon emissions represents a pivotal element in actualizing sustainability objectives. The academic community is increasingly focusing on emissions accounting, looking at national and regional scales, specific economic sectors, and ecological systems in a macro context. Furthermore, scholars are expanding this research to examine the impacts of policies, energy transitions, and global events such as pandemics on carbon emissions.

Yet there's a gap in the literature concerning the human element-individual behaviours and choices rooted in the pursuit of well-being-that significantly affect emissions and are vital for sustainable development. Since the ultimate aim of economic growth, urbanization, and industrialization is to enhance societal well-being, integrating the personal dimension into emission assessments is essential for a full understanding of how human needs drive environmental change.

Thus, one of the key research issues in emission accounting is developing a framework for quantifying carbon emissions arising from daily pursuits for well-being, and identifying emission reduction pathways that concurrently advance well-being and economic growth.

Aiming at the above gaps, this project will use multi-source data and inter-disciplinary methods, take the United Kingdom as a research area, and initiate from a human-cantered perspective, focusing on the pursuit and implementation of well-being. Input-Output Modelling and Life Cycle Assessment (LCA) are the main approaches for carbon accounting. Well-being quantification will combine UN SDG approaches and text mining based on social media data to present both subjective and objective information.

The exploration and simulation of the mechanisms linking emissions to well-being will be conducted using approaches and perspectives representative of complex systems, such as multi-agent modelling, game theory, and system dynamics. In addition, Multi-Criteria Decision Analysis (MCDA) will be employed for the optimization of scenarios and the formulation of emission reduction trajectories.