{"query_echo":{"q":"","filters":{"analysis_type":["uncertainty quantification"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'uncertainty quantification' 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=uncertainty+quantification","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-000400","url":"https://climateinsightsdirectory.org/document/sei-000400","title":"Uncertainty analysis UK MRIO model results: Monte Carlo analysis UK multi-region input-output model embedded carbon dioxide emissions indicator","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"report","language":"en","date_published":"2009-01-20","source_url":"https://www.sei.org/publications/uncertainty-analysis-uk-mrio-model-results-monte-carlo-analysis-uk-multi-region-input-output-model-embedded-carbon-dioxide-emissions-indicator/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document describes an extension to the 'Embedded Carbon Emissions Indicator' project, specifically focusing on the uncertainty analysis of a UK-MRIO model. The study employs a Monte-Carlo analysis to determine error margins for direct and indirect carbon dioxide emissions associated with UK economic activities and trade. The process involved reviewing standard deviations of constraints, estimating input-output (IO) table uncertainties from constraints and matrix balancing, and calculating error propagation for embedded emissions. The report notes that such a thorough uncertainty analysis is rare in environmental MRIO studies.","ai_generated":true,"unit":"sei-000400#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The report implements a Monte-Carlo analysis to quantify error margins and test the sensitivity of the UK-MRIO model system regarding parameter uncertainty.","ai_generated":true,"unit":"sei-000400#insight-1","date_modified":"2026-10-23"},{"text":"The uncertainty analysis methodology consisted of five primary steps: reviewing standard deviation estimates for constraints, estimating IO table uncertainties from those constraints and from matrix balancing, using Monte-Carlo simulations for multiplier uncertainties, and calculating error propagation for embedded emissions.","ai_generated":true,"unit":"sei-000400#insight-2","date_modified":"2026-10-23"},{"text":"The authors state that no other environmental multi-region input-output (MRIO) study has previously conducted an uncertainty analysis of this level of thoroughness.","ai_generated":true,"unit":"sei-000400#insight-3","date_modified":"2026-10-23"}],"climate_tags":["carbon dioxide emissions","embedded emissions"],"geography_discussed":["Australia"],"frame_perspective":[],"analysis_type":["sensitivity analysis","uncertainty quantification"]}]}