{"query_echo":{"q":"","filters":{"analysis_type":["ex-ante assessment"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'ex-ante assessment' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":2,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=ex-ante+assessment","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":"clipolin-000760","url":"https://climateinsightsdirectory.org/document/clipolin-000760","title":"Os impactos ambientais da Ferrogrão: Uma avaliação ex-ante dos riscos de desmatamento","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"policy brief","language":"pt","date_published":"2020-03","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2020/03/PB_Os-impactos-ambientais-da-Ferrograo-1.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The policy brief estimates that the construction of the EF-170 Ferrogrão railway will induce the deforestation of 2,043 square kilometers of native vegetation in Mato Grosso if no mitigation measures are implemented. This land-use change is projected to release 75 million tonnes of carbon, representing an environmental cost of approximately US$ 1.9 billion, which is about 60% of the project's estimated implementation cost of US$ 3.1 billion. The analysis uses a 'market access' approach to show how improved logistics for grain producers will increase demand for land, specifically affecting 38 municipalities.","ai_generated":true,"unit":"clipolin-000760#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The construction of the EF-170 Ferrogrão railway is projected to induce the deforestation of 2,043 square kilometers of native vegetation in the state of Mato Grosso under a 'business-as-usual' scenario without mitigation.","ai_generated":true,"unit":"clipolin-000760#insight-1","date_modified":"2026-10-23"},{"text":"The projected deforestation will result in carbon emissions of 75 million tonnes, which, at a price of US$ 25 per tonne of carbon equivalent, equates to an environmental cost of nearly US$ 1.9 billion.","ai_generated":true,"unit":"clipolin-000760#insight-2","date_modified":"2026-10-23"},{"text":"The environmental cost associated with carbon emissions from deforestation represents approximately 60% of the railway's estimated total implementation cost of US$ 3.1 billion.","ai_generated":true,"unit":"clipolin-000760#insight-3","date_modified":"2026-10-23"},{"text":"The railway is expected to improve market access for 38 municipalities by an average of 8%, which incentivizes farmers and ranchers to expand production and increase demand for land.","ai_generated":true,"unit":"clipolin-000760#insight-4","date_modified":"2026-10-23"},{"text":"The deforestation estimate of 2,043 km² is considered conservative because the model may underestimate current export costs via the Miritituba port, ignore freight reductions in competing corridors (such as BR-163), and overlook potential population growth in benefited municipalities.","ai_generated":true,"unit":"clipolin-000760#insight-5","date_modified":"2026-10-23"},{"text":"The analysis establishes a 95% confidence interval for the induced deforestation between 1,671 square kilometers (US$ 1.55 billion in carbon costs) and 2,416 square kilometers (US$ 2.24 billion in carbon costs).","ai_generated":true,"unit":"clipolin-000760#insight-6","date_modified":"2026-10-23"}],"climate_tags":["deforestation","carbon dioxide emissions","carbon price","land-use change","rail transport","ecosystem service","biodiversity","climate bond","green infrastructure"],"geography_discussed":["Amazon rainforest","Pará","Sinop","Itaituba","Miritituba","Santos","Paranaguá"],"frame_perspective":[],"analysis_type":["ex-ante assessment","econometric modeling","cost-benefit analysis"]},{"id":"sei-001675","url":"https://climateinsightsdirectory.org/document/sei-001675","title":"CLEANED – a new comprehensive framework for ex ante assessment of environmental impacts of livestock and aquaculture system interventions","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"briefing","language":"en","date_published":"2014","source_url":"https://www.sei.org/mediamanager/documents/Publications/NEW/SEI-DB-2014-Morris-Ran-Barron-CLEANED.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The CLEANED framework provides a participatory, rapid assessment tool for evaluating the environmental footprints of livestock and aquaculture interventions across the entire value chain. It focuses on four main impact categories: water availability and quality, soil and land health, biodiversity, and greenhouse gas emissions. Designed for use in developing countries, the tool combines public global datasets with local participatory GIS data to provide scores (adverse, positive, or static) for specific spatial units. A pilot application in Tanzania's dairy sector demonstrated the tool's ability to visualize how increased milk demand could expand fodder production areas.","ai_generated":true,"unit":"sei-001675#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The CLEANED framework is designed as a rapid, ex-ante tool to assess environmental impacts at multiple spatial scales for planned livestock and aquaculture interventions, specifically targeting the fragmented agro-ecological landscapes of smallholder systems in developing countries.","ai_generated":true,"unit":"sei-001675#insight-1","date_modified":"2026-10-23"},{"text":"The framework evaluates environmental impacts across the entire value chain, including the natural resource base for feed, livestock production, processing, marketing, and consumption, with a specific emphasis on waste management throughout the chain.","ai_generated":true,"unit":"sei-001675#insight-2","date_modified":"2026-10-23"},{"text":"CLEANED assesses four primary environmental impact categories using specific indicators: water (availability, quality, and soil water-holding capacity), soil and land health (erosion, organic matter, and fertility), biodiversity (habitat pressure, species diversity, and genetic resources), and greenhouse gas emissions (methane, nitrogen oxides, and carbon dioxide equivalents based on IPCC guidelines).","ai_generated":true,"unit":"sei-001675#insight-3","date_modified":"2026-10-23"},{"text":"The tool is designed for general use with minimal expert knowledge, utilizing a combination of public global datasets (for climate, soil, and topography) and participatory geographic information systems (PGIS) to validate and collect local data.","ai_generated":true,"unit":"sei-001675#insight-4","date_modified":"2026-10-23"},{"text":"The framework outputs results as scores—categorized as adverse, positive, or static—which can be applied to a whole discrete unit (such as a watershed or district) or disaggregated spatially to identify specific sensitive areas.","ai_generated":true,"unit":"sei-001675#insight-5","date_modified":"2026-10-23"},{"text":"A proof-of-concept application in Tanzania's dairy sector showed that meeting anticipated milk consumption increases (projected to rise to 100 litres per capita by 2020) would potentially lead to substantial new areas being dedicated to fodder production.","ai_generated":true,"unit":"sei-001675#insight-6","date_modified":"2026-10-23"},{"text":"Global livestock and fish production are significant drivers of environmental change, contributing between 8.5% and 18% of global anthropogenic greenhouse gas emissions and utilizing approximately 33% of arable land and 37% of water allocated for crop production.","ai_generated":true,"unit":"sei-001675#insight-7","date_modified":"2026-10-23"}],"climate_tags":["aquaculture","greenhouse gas emissions","water resource","biodiversity","environmental impact assessment","smallholder"],"geography_discussed":["Tanzania","World"],"frame_perspective":[],"analysis_type":["framework development","ex-ante assessment","pilot study"]}]}