Slicing up the social metabolism with physical input-output techniques: Methodological considerations about the ins and outs of global environmental input-output analysis in social ecological research

SUPERVISOR: Nina EISENMENGER

PROJECT ASSIGNED TO: Hanspeter WIELAND

Progress towards sustainability necessitates comprehensive, quantitative research analyzing the relation between socioeconomic activities and biophysical processes across different spatiotemporal scales. A wide spectrum of models and accounting frameworks are available to social ecologists, each describing certain aspects of the socioeconomic metabolism (SEM), i.e. the biophysical flows exchanged between societies and their natural environment as well as the flows within and between social systems. To overcome the limitations of individual methods (e.g. life cycle assessment, material flow analysis or input-output analysis), various combinations of approaches have been presented in the literature. Such cross-fertilizations between modelling schools/tools have the potential to be more comprehensive and informative than either approach by itself. Physical input-output tables (PIOTs), sometimes referred to as IO-based material flow analysis (MFA), are conceived as a way for combining the strengths of input-output modeling and MFA. When constructed following an economy-wide perspective using a single physical unit (e.g. metric tonnes), PIOTs represent a mass balanced map of biophysical flows between socio-metabolic processes including society-nature interactions. Like their monetary counterparts, PIOTs are generally underdetermined systems, i.e. not all table elements are known or explicitly informed by primary data. A recurring challenge of all PIOT construction efforts is dealing with incomplete and mismatched data sources with high uncertainties, which makes the construction process a time-consuming and labor-intensive undertaking.

In paper one of my PhD project, I focus on advancing methodologies in physical IO modelling through creation of a virtual laboratory for building PIOTs. This modelling framework is used to compile global PIOTs for iron and steel. The sustainable production and consumption of non-renewable resources like metallic minerals is a key challenge in the transition to a low-carbon and circular economy. Metal ores are strategically important resources for industrialized and industrializing societies and their extraction and processing is regarded as one of the most energy intensive economic activities. Considering all this in the context that metal supply chains are increasingly organized on the global level, iron and steel provides an excellent case study to discuss the challenges faced in the compilation of global PIOTs and the utility of the modelling framework. The goal of the second paper of my PhD project is to extend the global PIOT for iron and steel with spatial information on the environmental conditions at the mining sites to design an indicator framework for estimating spatially explicit land-based environmental impact footprints. Because environmental conditions (e.g., water availability or state of biodiversity) can vary significantly within countries and regions, IO models should aim to move from the aggregated national to the more detailed subnational/spatial level. With these two papers, my PhD project will contribute to the further advancement of physical input-output analysis for socio-metabolic research, in a methodological and empirical way.