{"query_echo":{"q":"","filters":{"analysis_type":["footprinting"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'footprinting' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":1,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=footprinting","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"sei-001618","url":"https://climateinsightsdirectory.org/document/sei-001618","title":"SEI-PCS: Spatially Explicit Information on Production to Consumption Systems","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"briefing","language":"en","date_published":"2019-03","source_url":"https://www.sei.org/wp-content/uploads/2019/03/sei-2019-p2cs-summary-sei-pcs.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document introduces SEI-PCS, a modeling tool designed to overcome the limitations of traditional country-level footprinting by providing spatially explicit data on production-to-consumption systems. By integrating subnational production data, domestic trade flows, and international customs data, SEI-PCS allows for the tracing of commodities back to their origin to assess impacts such as carbon emissions, biodiversity loss, and deforestation. The tool is the foundation for the Trase initiative, which specifically monitors deforestation risks associated with agricultural commodities like soy in Brazil, Indonesia, and Latin America, helping companies and governments evaluate the effectiveness of zero-deforestation commitments and identify policy 'leakage' effects.","ai_generated":true,"unit":"sei-001618#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Traditional footprinting methods available before 2015 were limited because they estimated footprints at the country level using macroeconomic figures and assumptions, failing to capture the localized nature of issues like deforestation or the heterogeneity of landscapes in large countries such as Brazil.","ai_generated":true,"unit":"sei-001618#insight-1","date_modified":"2026-10-23"},{"text":"SEI-PCS enables fine-scale subnational assessments of commodity origins and their embedded socio-environmental impacts, including local pollution, carbon emissions, and biodiversity loss, by recreating supply chains through a combination of subnational production data, domestic trade flows, and international customs data.","ai_generated":true,"unit":"sei-001618#insight-2","date_modified":"2026-10-23"},{"text":"The SEI-PCS model serves as the basis for the Trase (Transparency for Sustainable Economies) initiative, which provides an open-access platform to track forest-risk commodities in Indonesia and Latin America, specifically focusing on Brazilian soy to estimate the 'deforestation risk' for actors in the supply chain.","ai_generated":true,"unit":"sei-001618#insight-3","date_modified":"2026-10-23"},{"text":"SEI-PCS is used to analyze the temporal dynamics of sourcing and the unintended consequences of environmental policies, such as 'leakage' where policies protecting the Amazon rainforest have led to increased soy deforestation rates in neighboring non-Amazonian areas.","ai_generated":true,"unit":"sei-001618#insight-4","date_modified":"2026-10-23"}],"climate_tags":["carbon dioxide emissions","biodiversity loss","deforestation","sustainable consumption","land use","climate change adaptation"],"geography_discussed":["Brazil","People's Republic of China","Indonesia","Latin America","MATOPIBA","Amazon rainforest","Q43695"],"frame_perspective":[],"analysis_type":["modeling","footprinting"]}]}