{"query_echo":{"q":"","filters":{"analysis_type":["ex-ante impact assessment"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'ex-ante impact 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+impact+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-000578","url":"https://climateinsightsdirectory.org/document/clipolin-000578","title":"Guidelines to Assess the Direct and Indirect Area of Influence of Transportation Infrastructure Projects","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"guide","language":"en","date_published":"2023-02","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2023/02/Guidelines-Infra-EN.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The guide details a market access methodology that shifts from simple geographical distance buffers to a model incorporating transportation costs, market size, and land conversion data. By converting infrastructure networks into graphs, the approach can simulate how new roads or bridges change market connectivity and subsequently drive deforestation. The document includes a practical example in Amapá, Brazil, demonstrating how a fictional road could lead to an estimated 368 km2 of deforestation and 17 million tons of CO2 emissions.","ai_generated":true,"unit":"clipolin-000578#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The market access methodology is presented as a superior alternative to traditional geographical distance buffers because it accounts for social and economic dynamics, specifically how a project connects different markets rather than just its physical outline.","ai_generated":true,"unit":"clipolin-000578#insight-1","date_modified":"2026-10-23"},{"text":"The methodology relies on three core components: transportation costs (the cost of connecting markets), market size (represented by population or production value), and land conversion (measured via deforestation data).","ai_generated":true,"unit":"clipolin-000578#insight-2","date_modified":"2026-10-23"},{"text":"Transportation networks are modeled as graphs (nodes and edges), allowing for the flexible inclusion of various modes such as roads, railroads, waterways, and ports, as well as specific costs like loading fees or tolls.","ai_generated":true,"unit":"clipolin-000578#insight-3","date_modified":"2026-10-23"},{"text":"The 'fishbone pattern' of deforestation occurs when new roads enable the creation of secondary legal or illegal roads in surrounding regions, often due to a lack of oversight in protected areas.","ai_generated":true,"unit":"clipolin-000578#insight-4","date_modified":"2026-10-23"},{"text":"The relationship between market access and deforestation can be estimated using a log-linear statistical model, where the coefficient determines the percentage increase in deforestation resulting from a 1% increase in market access.","ai_generated":true,"unit":"clipolin-000578#insight-5","date_modified":"2026-10-23"},{"text":"Carbon footprints can be calculated by overlapping deforestation data with carbon stock maps or by using average emission factors, such as the Amazon Fund's estimate of 48,510 tons of CO2 per km2.","ai_generated":true,"unit":"clipolin-000578#insight-6","date_modified":"2026-10-23"},{"text":"In a simplified application for the state of Amapá, a fictional road was estimated to cause 368 km2 of deforestation (approximately 2.2 km2 per km of road) and the release of 17 million tons of CO2.","ai_generated":true,"unit":"clipolin-000578#insight-7","date_modified":"2026-10-23"}],"climate_tags":["deforestation","carbon footprint","environmental impact assessment","climate finance"],"geography_discussed":["Amapá","Amazon rainforest","Pará"],"frame_perspective":[],"analysis_type":["methodological guide","ex-ante impact assessment"]},{"id":"clipolin-000579","url":"https://climateinsightsdirectory.org/document/clipolin-000579","title":"Diretrizes para Avaliação da Área de Influência Direta e Indireta de Projetos de Infraestrutura de Transporte","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"guide","language":"pt","date_published":"2023-02","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2023/02/Guidelines-Infra-PT.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The guide details a methodology that moves beyond simple geographic distance to assess the 'area of influence' of infrastructure by analyzing how projects change market access. It combines transport costs, market size, and deforestation data into a statistical model to estimate ex-ante environmental risks.","ai_generated":true,"unit":"clipolin-000579#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The market access methodology is presented as a superior alternative to traditional geographic distance buffers because it incorporates socio-economic dynamics, recognizing that the impact of a project depends on what it connects rather than just its physical design.","ai_generated":true,"unit":"clipolin-000579#insight-1","date_modified":"2026-10-23"},{"text":"The methodology relies on three primary components: transport costs (calculated via a graph-based network of roads, ports, and waterways), market size (represented by population, income, or production), and land conversion (measured through deforestation data).","ai_generated":true,"unit":"clipolin-000579#insight-2","date_modified":"2026-10-23"},{"text":"The guide demonstrates that specific infrastructure elements, such as bridges, can have disproportionately large impacts on market access and land use compared to their physical size, as they can instantly connect previously isolated markets.","ai_generated":true,"unit":"clipolin-000579#insight-3","date_modified":"2026-10-23"},{"text":"The 'fishbone' pattern of deforestation is explained as a result of new roads enabling access to protected areas, where a lack of enforcement allows the creation of secondary paths that minimize transport costs.","ai_generated":true,"unit":"clipolin-000579#insight-4","date_modified":"2026-10-23"},{"text":"Carbon emissions from infrastructure projects can be estimated by overlaying predicted deforestation areas with carbon stock maps; for the Amazon, a baseline emission potential of 48,510 tons of CO2 per km2 is cited.","ai_generated":true,"unit":"clipolin-000579#insight-5","date_modified":"2026-10-23"},{"text":"In a simplified application for the state of Amapá, the model estimated that a hypothetical new road would result in a deforestation footprint of 368 km2, equivalent to approximately 2.2 km2 of deforestation per kilometer of road, releasing 17 million tons of CO2.","ai_generated":true,"unit":"clipolin-000579#insight-6","date_modified":"2026-10-23"},{"text":"The guide suggests that the resulting risk maps should guide mitigation efforts, such as command-and-control actions, implementation of the forest code, and payments for ecosystem services (PSE).","ai_generated":true,"unit":"clipolin-000579#insight-7","date_modified":"2026-10-23"}],"climate_tags":["deforestation","carbon dioxide emissions","land-use change","environmental impact assessment","climate finance"],"geography_discussed":["Amapá","Amazon rainforest"],"frame_perspective":[],"analysis_type":["methodological guide","ex-ante impact assessment"]}]}