Towards more accurate and policy relevant footprint analyses: Tracing fine-scale socio-environmental impacts of production to consumption

Abstract

The consumption of internationally traded goods causes multiple socio-environmental impacts. Current methods linking production impacts to final consumption typically trace the origin of products back to the country level, lacking fine-scale spatial resolution. This hampers accurate calculation of trade and consumption footprints, masking and distorting the causal links between consumers' choices and their environmental impacts, especially in countries with large spatial variability in socio-environmental conditions and production impacts. Here we present the SEI-PCS model (Spatially Explicit Information on Production to Consumption Systems), which allows for fine-scale sub-national assessments of the origin of, and socio-environmental impacts embedded in, traded commodities. The method connects detailed production data at sub-national scales (e.g., municipalities or provinces), information on domestic flows of goods and in international trade. The model permits the downscaling of country-to-country trade analyses based on either physical allocation from bilateral trade matrices or MRIO models. The importance of producing more spatially-explicit trade analyses is illustrated by identifying the municipalities of Brazil from which different countries source the Brazilian soy they consume. Applications for improving consumption accounting and policy assessment are discussed, including quantification of externalities of consumption, consumer labeling, trade leakages, sustainable resource supply and traceability.

Patrick Meyfroidt

Professor of Land Systems and Sustainability Science

My research focuses on how land systems can contribute to sustainability.