{"query_echo":{"q":"","filters":{"analysis_type":["methodology description"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'methodology description' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":5,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=methodology+description","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":"iisd-002182","url":"https://climateinsightsdirectory.org/document/iisd-002182","title":"Sustainable Asset Valuation (SAVi)","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"guide","language":"en","date_published":"2019","source_url":"https://www.iisd.org/sites/default/files/publications/sustainable-asset-valuation-savi-tool-brochure.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The Sustainable Asset Valuation (SAVi) tool by the International Institute for Sustainable Development (IISD) integrates system dynamics simulation with project finance models to value risks and externalities typically ignored in traditional financial assessments. It applies to asset types including energy, roads, buildings, irrigation, sewerage treatment, and nature-based infrastructure. The tool aims to support the goals of the Paris Agreement and UN Sustainable Development Goals by optimizing value for money across an asset's life cycle. Case studies demonstrate its application in valuing climate-risk-related road disruptions in Morocco, the economic gains of wetland conservation in India, and the internal rate of return for wind energy in Senegal.","ai_generated":true,"unit":"iisd-002182#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"SAVi is a simulation-based methodology that quantifies the costs of environmental, social, and economic risks and externalities—which are typically omitted in traditional financial valuations—as well as societal and economic benefits such as GDP contributions, income, productivity, and employment.","ai_generated":true,"unit":"iisd-002182#insight-1","date_modified":"2026-10-23"},{"text":"The tool is applicable to various infrastructure types, specifically energy, roads, buildings, irrigation, sewerage treatment, and nature-based infrastructure, and can be customized for single projects, portfolios, or industrial policies.","ai_generated":true,"unit":"iisd-002182#insight-2","date_modified":"2026-10-23"},{"text":"Application of SAVi in Senegal showed that the N’Diaye wind project has an internal rate of return of 14 per cent when accounting for externalities and climate risks, whereas diesel-generated power has a negative internal rate of return.","ai_generated":true,"unit":"iisd-002182#insight-3","date_modified":"2026-10-23"},{"text":"In Morocco, SAVi estimated that climate-risk-related disruptions for the Rabat bypass road would result in EUR 7.3 million in additional reparation expenditures over the asset's lifetime.","ai_generated":true,"unit":"iisd-002182#insight-4","date_modified":"2026-10-23"},{"text":"Analysis of Dal Lake in Srinagar, India, identified solar-powered sewage treatment combined with an artificial wetland as the optimal solution, projecting economic gains of INR 377 billion between 2019 and 2060.","ai_generated":true,"unit":"iisd-002182#insight-5","date_modified":"2026-10-23"},{"text":"In Tanzania, the use of drip irrigation in the agricultural sector is projected to result in 8 per cent higher employment and 8 per cent more agricultural production, while reducing water usage by 14 per cent over the project's lifetime compared to floor irrigation.","ai_generated":true,"unit":"iisd-002182#insight-6","date_modified":"2026-10-23"},{"text":"Green investments in Georgia's tourism, housing, and agricultural sectors are estimated to increase annual GDP growth by 0.2 per cent between 2017 and 2040.","ai_generated":true,"unit":"iisd-002182#insight-7","date_modified":"2026-10-23"}],"climate_tags":["green infrastructure","climate risk","offshore wind power","carbon tax","Paris Agreement","sustainable procurement"],"geography_discussed":["Netherlands","Morocco","Canada","Manitoba","Senegal","Ghana","Germany","Georgia","Albania","People's Republic of China","Tanzania","Malawi","Sri Lanka","India"],"frame_perspective":[],"analysis_type":["methodology description","case study"]},{"id":"ucs-001242","url":"https://climateinsightsdirectory.org/document/ucs-001242","title":"Meeting—and Exceeding—the Clean Power Plan in Virginia","publisher":{"name":"Union of Concerned Scientists","organization":"union-of-concerned-scientists"},"document_type":"report","language":"en","date_published":"2016-01","source_url":"https://www.ucs.org/sites/default/files/attach/2016/01/virginia-clean-power-plan-analysis-technical-appendix.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document details the use of the National Renewable Energy Laboratory’s Regional Energy Deployment System (ReEDS) to model energy pathways for Virginia. It outlines specific adjustments made to capital costs, performance projections, and policy assumptions for various electricity generating technologies compared to EIA benchmarks. The analysis compares a 'Reference Case' of existing policies against a 'Clean Path Case' involving Clean Power Plan compliance, mandatory energy efficiency standards, and a Renewable Portfolio Standard for Virginia.","ai_generated":true,"unit":"ucs-001242#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The analysis utilizes the 2015.2 version of the Regional Energy Deployment System (ReEDS), a capacity planning model for electric power generation in the contiguous United States through 2050, with specific adjustments to NREL's assumptions based on project-specific data.","ai_generated":true,"unit":"ucs-001242#insight-1","date_modified":"2026-10-23"},{"text":"UCS diverged from EIA's learning assumptions by assuming costs for mature technologies remain fixed over time, while costs for emerging technologies decline based on trajectories independent of technology penetration in a specific scenario.","ai_generated":true,"unit":"ucs-001242#insight-2","date_modified":"2026-10-23"},{"text":"For the 'Clean Path Case' scenario in Virginia, the model assumes the implementation of a mandatory Energy Efficiency Resource standard (EERS) with savings equivalent to 9 percent of statewide electricity sales in 2022, maintained through 2030.","ai_generated":true,"unit":"ucs-001242#insight-3","date_modified":"2026-10-23"},{"text":"The 'Clean Path Case' for Virginia includes a mandatory Renewable Portfolio standard (RPS) starting in 2018, requiring renewable generation to meet 8 percent of sales in 2025 and 16 percent of sales in 2030.","ai_generated":true,"unit":"ucs-001242#insight-4","date_modified":"2026-10-23"},{"text":"To calculate the monetary value of carbon dioxide reduction benefits, the analysis uses the U.S. Government's social costs of carbon (SCC) from the EPA's Regulatory Impact Assessment for the Final CPP rule, applying a 3-percent discount rate.","ai_generated":true,"unit":"ucs-001242#insight-5","date_modified":"2026-10-23"},{"text":"The model's cost assumptions for various technologies differ from EIA AEO 2015 benchmarks; for example, utility-scale solar PV capital costs are projected to drop from $4,464/kW in 2010 to $1,098/kW by 2030, whereas EIA projected $2,826/kW for 2030.","ai_generated":true,"unit":"ucs-001242#insight-6","date_modified":"2026-10-23"}],"climate_tags":["Clean Power Plan","Renewable portfolio standard","carbon capture and storage","distributed solar photovoltaics","offshore wind power","biomass","hydropower","nuclear power","natural gas"],"geography_discussed":["United States"],"frame_perspective":[],"analysis_type":["technical appendix","methodology description","scenario analysis"]},{"id":"wri-001421","url":"https://climateinsightsdirectory.org/document/wri-001421","title":"The Suitability Mapper","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"guide","language":"en","date_published":"2012-10-26","source_url":"https://wriorg.s3.amazonaws.com/s3fs-public/suitability_mapper_technical_document.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The Suitability Mapper is a public online tool developed by the World Resources Institute (WRI) and Sekala to help stakeholders identify potentially suitable areas for sustainable oil palm cultivation in Kalimantan. It uses a binary analysis of 11 environmental and crop indicators to classify land as either 'potential' or 'not suitable'. The tool allows users to apply default settings based on Project POTICO—which align with RSPO standards and Indonesian law—or customize criteria to fit specific project needs. Because the underlying data has not been systematically verified, the document emphasizes that field assessments and due diligence regarding legal and social issues are mandatory to confirm site suitability.","ai_generated":true,"unit":"wri-001421#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The Suitability Mapper uses a binary technique to determine land suitability based on 11 indicators; if any single indicator is classified as 'not suitable', the entire area is deemed not suitable.","ai_generated":true,"unit":"wri-001421#insight-1","date_modified":"2026-10-23"},{"text":"Environmental criteria for suitability focus on carbon stocks, biodiversity high conservation values (HCV 1–3), and soil and water protection, utilizing five indicators: land cover, peat, slope, and buffers for conservation areas and water resources.","ai_generated":true,"unit":"wri-001421#insight-2","date_modified":"2026-10-23"},{"text":"Crop criteria assess the economic feasibility and productivity of oil palm cultivation through six indicators: elevation, rainfall, soil drainage, soil depth, soil acidity, and soil type.","ai_generated":true,"unit":"wri-001421#insight-3","date_modified":"2026-10-23"},{"text":"Default settings for the tool are aligned with the Roundtable on Sustainable Palm Oil (RSPO) standards, Indonesian laws, and the national REDD+ strategy to promote expansion on low-carbon, degraded land.","ai_generated":true,"unit":"wri-001421#insight-4","date_modified":"2026-10-23"},{"text":"The tool is currently limited geographically to Kalimantan, although development is underway to expand it to Papua and eventually all of Indonesia and other palm oil producing countries.","ai_generated":true,"unit":"wri-001421#insight-5","date_modified":"2026-10-23"},{"text":"The data used in the application has not been systematically verified, making field assessments and site-level due diligence essential to confirm suitability and address legal or social issues, such as free, prior, and informed consent (FPIC).","ai_generated":true,"unit":"wri-001421#insight-6","date_modified":"2026-10-23"}],"climate_tags":["Reducing emissions from deforestation and forest degradation","biodiversity","peatland","Free, Prior and Informed Consent"],"geography_discussed":["Indonesia","Papua"],"frame_perspective":[],"analysis_type":["technical guide","methodology description"]},{"id":"iisd-001122","url":"https://climateinsightsdirectory.org/document/iisd-001122","title":"Outil d’identification des risques au niveau communautaire – Adaptation et en résumé moyens d’existence","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"guide","language":"fr","date_published":null,"source_url":"https://www.iisd.org/system/files/publications/brochure_cristal_fr.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"CRiSTAL (Community Risk Identification and Adaptation Tool) is a decision-support framework developed by IUCN, IISD, SEI, and Intercooperation to assist project managers in designing activities that enhance community resilience. The tool uses a logical sequence of four analytical steps, divided into two modules, to assess how climate hazards affect livelihood resources and how project activities can be adjusted to improve adaptation capacity. It relies on a combination of secondary scientific climate data and stakeholder consultations, with data managed via Microsoft Excel. Since its 2007 launch, the tool has been applied in over 20 countries, following initial field trials in Mali, Bangladesh, Tanzania, Nicaragua, and Sri Lanka.","ai_generated":true,"unit":"iisd-001122#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"CRiSTAL provides a specific analytical framework to understand the relationship between climate hazards, local livelihoods, and project interventions, specifically focusing on how hazards affect project areas, how people cope, which livelihood resources are most critical, and how project activities influence the availability of these resources.","ai_generated":true,"unit":"iisd-001122#insight-1","date_modified":"2026-10-23"},{"text":"The tool is structured into two modules containing four logical steps: Module 1 focuses on climate context (Step 1) and livelihood resources (Step 2), while Module 2 focuses on project impacts (Step 3) and project adjustment to reduce vulnerability and improve adaptation capacity (Step 4).","ai_generated":true,"unit":"iisd-001122#insight-2","date_modified":"2026-10-23"},{"text":"CRiSTAL was developed by a partnership including the International Union for Conservation of Nature (IUCN), the International Institute for Sustainable Development (IISD), the Stockholm Environment Institute (SEI), and Intercooperation to ensure project activities promote adaptation and minimize the risks of inadequate adaptation.","ai_generated":true,"unit":"iisd-001122#insight-3","date_modified":"2026-10-23"},{"text":"Since its launch in 2007, the tool has been used in more than 20 countries, with early field testing conducted in Sri Lanka, Nicaragua, Tanzania, Bangladesh, and Mali.","ai_generated":true,"unit":"iisd-001122#insight-4","date_modified":"2026-10-23"}],"climate_tags":["climate change adaptation","risk reduction","community resilience","natural resource management","vulnerability assessment"],"geography_discussed":["Mali","Bangladesh","Tanzania","Nicaragua"],"frame_perspective":[],"analysis_type":["methodology description"]},{"id":"napglob-000264","url":"https://climateinsightsdirectory.org/document/napglob-000264","title":"Envisioning Resilience","publisher":{"name":"NAP Global Network","organization":"nap-global-network"},"document_type":"fact sheet","language":"en","date_published":null,"source_url":"https://napglobalnetwork.org/wp-content/uploads/2024/01/napgn-en-2023-envisioning-resilience-creative-approach-infographic.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"Envisioning Resilience is a creative initiative developed by the NAP Global Network, Lensational, and GirlsCARE to increase the inclusion of underrepresented women in climate adaptation decision-making. The approach uses a four-step process: training in photography and storytelling, the development of individual and collective visual stories, a policy dialogue between trainees and government decision-makers to establish shared adaptation priorities, and an income-generation mechanism through the sale of photographs.","ai_generated":true,"unit":"napglob-000264#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The 'Envisioning Resilience' initiative employs a four-step creative approach to facilitate policy dialogue on adaptation: training in photography and climate change, the creation of visual stories based on lived experiences, a policy dialogue with government and non-government decision-makers to identify community adaptation priorities, and the sale of photos for income generation.","ai_generated":true,"unit":"napglob-000264#insight-1","date_modified":"2026-10-23"},{"text":"The initiative aims to address existing challenges in making National Adaptation Plan (NAP) processes inclusive and participatory by specifically amplifying the voices of underrepresented women.","ai_generated":true,"unit":"napglob-000264#insight-2","date_modified":"2026-10-23"}],"climate_tags":["climate change adaptation","gender equality","climate change mitigation"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["methodology description"]}]}