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PDF: Towards more accurate and policy relevant footprint analyses
http://resources.trase.earth/documents/Godar%20et%20al.%20(2015)%20Ecological%20Economics.pdf
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
http://resources.trase.earth/documents/Godar%20et%20al.%20(2015)%20Ecological%20Economics.pdf
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
SEI-PCS: Spatially Explicit Information on Production to Consumption Systems
https://www.sei.org/wp-content/uploads/2019/03/sei-2019-p2cs-summary-sei-pcs.pdf
Countries, companies and individual consumers are increasingly aware that their consumption could be linked, via supply chains, to environmental and social sustainability impacts in distant parts of the world. However, most of the footprinting methods available prior to 2015 critically lacked detail – of the connections between consumption and production, and of how particular commodity flows were linked to sustainability issues in specific production sites. Instead, they estimated footprints at country level, based on assumptions and macroeconomic figures.
This limited their value for policymaking, attributing responsibility and taking preventive action, given the often localized nature of issues like deforestation, as well as the heterogeneity of landscapes and vulnerability that can exist, particularly in large countries like Brazil. br>
SEI-PCS (for Spatially Explicit Information on Production to Consumption Systems) is a modeling approach developed at SEI.1 SEI-PCS allows for fine-scale subnational assessments of the origin of traded commodities and the socio-environmental impacts embedded in them, such as carbon emissions, local pollution or biodiversity loss. It recreates supply chains and attributes sustainability impacts to commodity flows and actors, using a combination of detailed production data at subnational scales, information on domestic trade flows, customs data and international trade flows between countries.
https://www.sei.org/wp-content/uploads/2019/03/sei-2019-p2cs-summary-sei-pcs.pdf
Countries, companies and individual consumers are increasingly aware that their consumption could be linked, via supply chains, to environmental and social sustainability impacts in distant parts of the world. However, most of the footprinting methods available prior to 2015 critically lacked detail – of the connections between consumption and production, and of how particular commodity flows were linked to sustainability issues in specific production sites. Instead, they estimated footprints at country level, based on assumptions and macroeconomic figures.
This limited their value for policymaking, attributing responsibility and taking preventive action, given the often localized nature of issues like deforestation, as well as the heterogeneity of landscapes and vulnerability that can exist, particularly in large countries like Brazil. br>
SEI-PCS (for Spatially Explicit Information on Production to Consumption Systems) is a modeling approach developed at SEI.1 SEI-PCS allows for fine-scale subnational assessments of the origin of traded commodities and the socio-environmental impacts embedded in them, such as carbon emissions, local pollution or biodiversity loss. It recreates supply chains and attributes sustainability impacts to commodity flows and actors, using a combination of detailed production data at subnational scales, information on domestic trade flows, customs data and international trade flows between countries.
Trase Supply Chains
https://supplychains.trase.earth/
Trase is at the forefront of a data-driven revolution in supply chain sustainability, drawing on vast sets of production, trade and customs data, for the first time laying bare the flows of globally traded commodities at scales that are directly relevant to decision-making. Its pioneering approach to data analysis and visualization provides full coverage of the export routes and buyers responsible for all production and trade, and the associated sustainability risks, of a given commodity.
The supply chain mapping at the core of Trase balances scale and data resolution. It builds on an enhanced form of material flow analysis called Spatially Explicit Information on Production to Consumption Systems (SEI-PCS) originally developed by Godar et al. 2015. Three capabilities of the Trase approach together set it apart from other approaches to supply chain mapping:
https://supplychains.trase.earth/
Trase is at the forefront of a data-driven revolution in supply chain sustainability, drawing on vast sets of production, trade and customs data, for the first time laying bare the flows of globally traded commodities at scales that are directly relevant to decision-making. Its pioneering approach to data analysis and visualization provides full coverage of the export routes and buyers responsible for all production and trade, and the associated sustainability risks, of a given commodity.
The supply chain mapping at the core of Trase balances scale and data resolution. It builds on an enhanced form of material flow analysis called Spatially Explicit Information on Production to Consumption Systems (SEI-PCS) originally developed by Godar et al. 2015. Three capabilities of the Trase approach together set it apart from other approaches to supply chain mapping:
It systematically links individual supply chain actors to specific, subnational production regions, and the sustainability risks and investment opportunities associated with those regions;
It identifies the individual companies that export, ship and import a given traded commodity; and
It covers all of the exports of a given commodity from a given country of production.